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91
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s 1
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at
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ms 2
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o
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k
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s 204
6.
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7
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l
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n
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ows 206
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l
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r
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u
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ows 207
6.
2.
9
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c
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l
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k
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e 2
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ows 21
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t
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2
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yc
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i
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g 225
6.
4 Summa
r
y 229
7 Dynami
c
sofSt
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ksandFl
ows 231
7.
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.
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at
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l
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br
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u
m 23
2
7.
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s 23
2
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.
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n 23
4
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r
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s
xvi
i
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.
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2
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8.
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r
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ms 263
8,
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c
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bl
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9
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.
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s
sPoi
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c
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f
i
de
nc
e 272
8.
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g
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ba
c
ka
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a
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or 281
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8.
5
.
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mal
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n
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8.
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r
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r
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0
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3
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f
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6
9.
1
.
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h 296
9.
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cEqu
at
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o
n 29
7
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s 29
9
9.
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0
9.
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l
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s 3
0
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9.
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.
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.
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t
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t
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4
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4
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9
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9.
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umma
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46
1
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pe
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t
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k 349
1
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49
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1
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54
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1
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2
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dsFo
r
ma
t
i
o
n 391
1
0.
8.
1 Mo
de
lSt
r
uc
t
ur
e 3
9
2
1
0.
8.
2 Mo
de
lBe
hav
i
or 3
96
1
0.
8.
3 Pol
i
c
yI
mpl
i
c
at
i
o
ns 402
Cha
l
l
e
nge:Pol
i
c
yAna
l
ys
I
S 403
Cha
ll
e
nge:Ext
e
ndi
ngt
heMo
de
l 40
4
1
0.
9 Summa
r
y 406
PARTI
V TOOLSFORMODELI
NGDYNAMI
CSYSTEMS 407
l
l De
l
a
ys 409
1
1
.
1 De
l
a
ys
:
Anl
nt
r
od
uc
t
i
on 409
Co
nt
e
nt
s
XI
X
Cha
l
l
e
ng
e:Dur
a
t
i
ona
ndDy
na
mi
c
sofDe
l
a
ys 409
1
1
.
1
.
1 De
f
i
ni
n
gDe
l
a
y
s 41
1
.
2 Ma
t
e
r
i
a
lDe
l
a
ys
:
St
r
uc
t
ur
ea
ndBe
ha
vi
o
r 41
2
1
1
1
.
2.
1 What
I
st
heAv
e
r
ageLe
n
gt
ho
ft
heDe
l
a
y? 41
3
1
1
1
･
2･
2 What
l
st
heDi
s
t
r
i
but
i
o
no
ft
heOu
t
put
ar
o
un
dt
heAv
e
r
age
De
l
a
yT
l
'
me? 41
3
1
1
.
2.
3 Pi
pe
l
i
neDe
l
a
y 41
5
.
2.
4 Fi
r
s
t
1
07
de
rMat
e
r
i
al
De
l
a
y 41
5
1
1
1
1
.
2.
5 Hi
ghe
r
‑
Or
de
rMat
e
r
i
alDe
l
a
y
s 41
7
1
1
.
2.
6 HowMu
c
hl
si
nt
heDe
l
a
y?Li
t
t
l
e'
sLaw 421
Cha
ll
e
ng
e:Re
s
po
ns
eofMa
t
e
r
i
a
lDe
l
a
yst
o
St
e
ps
,
Ra
mps
,
a
ndCyc
l
e
s 425
1
1
.
3 I
nf
o
r
ma
t
i
o
nDe
l
a
ys
:
St
r
uc
t
ur
ea
ndBe
ha
v
i
o
r 426
1
1
.
3.
1 Mo
de
l
i
ngPe
r
c
e
pt
i
o
ns
:
Ada
pt
l
V
eEx
pe
c
t
at
i
o
nsa
nd
Ex
pone
nt
i
alSmoot
hi
ng 428
1
1
.
3.
2 Hi
g
he
r
‑
Or
de
rI
n
f
or
mat
i
o
nDe
l
a
y
s 432
1
1
.
4 Re
s
po
ns
et
oVa
r
i
a
bl
eDe
l
a
yTi
me
s 43
4
Cha
l
l
e
ng
e:Re
s
po
ns
eofDe
l
a
yst
oCha
ng
i
ngDe
l
a
yTi
me
s 43
5
1
1
.
4.
1 Nonl
i
ne
arAd
j
u
s
t
me
ntT
l
'
me
s
:
Mo
de
l
i
n
gRat
c
he
t
E
j
f
e
c
t
s 43
6
1
1
･
5 Es
t
i
ma
t
l
ngt
heDur
a
t
i
o
na
ndDi
s
t
r
i
but
i
o
no
fDe
l
a
ys 43
7
1
1
.
5.
1 Es
t
i
mat
i
ngDe
l
a
y
sV
V
he
nNu
me
r
i
c
al
Dat
a
Ar
eAv
ai
l
abl
e 43
7
.
5.
2 Es
t
i
mat
l
ngDe
l
a
ysWhe
nNu
me
r
i
c
alDat
a
1
1
Ar
eNot
Av
ai
l
abl
e 445
1
1
.
5.
3 Pr
oc
e
s
sPoi
nt
:1
砺‡
l
kt
heLi
ne 4
49
1
1
.
6 Sys
t
e
mDyna
mi
c
si
nAc
t
i
o
n:
Fo
r
e
c
a
s
t
l
ngSe
mi
c
o
nd
uc
t
o
rDe
ma
nd 4
49
1
1
･
7 Ma
t
h
e
ma
t
i
c
sofDe
l
a
ys
:
Koyc
kLa
gsa
ndEr
l
a
ngDi
s
t
r
i
but
i
o
ns 462
1
1
.
7.
1 Ge
ne
r
alFor
mul
at
i
onf
orDe
l
a
y
s 46
2
.
7.
2 Fi
r
s
t
‑
OT
l
de
rDe
l
a
y 46
4
1
1
1
1
.
7.
3 Hi
ghe
r
‑
Or
de
rDe
l
a
y
s 46
5
.
7.
4 Re
l
at
i
ono
fMat
e
r
i
alandI
n
f
or
mat
i
onDe
l
a
y
s 466
1
1
1
1
.
8 Su
mma
r
y 466
1
2 Co
f
L
owsa
ndAg
i
ngCha
i
ns 469
1
2.
1 Ag
i
n
gCha
i
ns 470
1
2.
1
.
1 Ge
ne
r
alSt
r
u
c
t
ur
eo
fAgi
ngCh
ai
ns 47
0
1
2.
1
.
2 Exa
mpl
e
:Po
pul
at
i
onandI
n
f
r
as
t
r
u
c
t
ur
ei
nUr
ba
n
Dyna
mi
c
s 472
1
2.
1
.
3 Exampl
e
:ThePo
pul
at
i
onPyr
a
mi
dan
dt
h
eDe
mo
gr
a
phi
c
Tr
ans
i
t
i
on 474
1
.
4 Agi
ngChai
nsandPo
pul
at
i
o
nl
ne
r
t
i
a 48
0
1
2.
1
2.
1
.
5 S
y
s
t
e
mDyn
ami
c
si
nAc
t
i
o
n:
WT
or
l
dPo
pul
at
i
onandEc
o
no
mi
cDe
v
e
l
o
pme
nt 481
1
2.
1
.
6 Cas
eSt
ud
y/
Gr
1
0Wt
handt
heAgeSt
r
uc
t
ur
eo
fOr
ga
ni
z
at
i
ons 48
5
1
2.
1
.
7 Pr
o
mot
i
o
nCh
ai
nsandt
heLe
ar
nmgCu
y
ve 49
0
X
X
Cont
e
nt
s
1
2.
1
.
8 Me
nt
or
l
ngandOn‑
The
‑
JobTr
ai
nl
ng 493
CI
l
a
l
l
e
nge:TheI
nt
e
r
a
c
t
i
o
nso
fTr
a
i
n
i
ngDe
l
a
ysa
ndGr
owt
h 495
1
2.
2 Cof
lows
:
Mo
de
l
i
ngt
heAt
t
r
i
b
ut
e
sofaSt
o
c
k 497
Cha
ll
e
nge:Co
lows 5
f
03
1
2.
2.
1 Co
jl
owswi
t
hNonc
ons
e
r
v
e
dFl
ows 504
CI
l
a
l
l
e
nge:TheDy
na
mi
c
sofEx
pe
r
i
e
nc
ea
ndLe
a
r
nl
ng 5
08
2.
2 I
nt
e
gr
at
i
ngCo
j
l
owsandAgi
ngChai
ns 509
1
2.
Cha
l
l
e
nge:Mo
de
l
i
ngDe
s
i
g
nWi
nsi
nt
he
Se
mi
c
o
nduc
t
o
rl
ndus
t
r
y 51
1
1
2･
3 Summa
r
y 51
1
13 Mo
de
l
i
ngDe
c
i
s
i
onMa
ki
ng 51
3
1
3.
1 Pr
i
nc
i
pl
e
sf
o
rMo
de
l
i
ngDe
c
i
s
i
o
nMa
ki
ng 51
3
1
3.
1
.
1 De
ci
s
i
onsandDe
c
i
s
i
onRul
e
s 51
4
1
3.
1
.
2 Fi
v
eFor
mul
at
i
onFundame
nt
al
s 51
6
Cha
ll
e
nge:Fi
ndi
ngFo
r
mul
a
t
i
o
nFl
a
ws 520
1
3.
2 Fo
r
mul
a
t
i
ngRa
t
eEqua
t
i
o
ns 5
22
1
3.
2.
1 Fr
ac
t
i
onalI
nc
r
e
as
eRat
e 522
1
3.
2.
2 Fr
ac
t
i
onalDe
c
r
e
as
eRat
e 523
1
3.
2.
3 Ad
j
us
t
me
ntt
oaGoal 523
1
3.
2.
4 TheSt
oc
kManage
me
ntSt
r
uc
t
ur
e:
Rat
e‑ Nor
mal
Rat
e+Ad
j
u
s
t
me
nt
s 524
1
3.
2.
5 Fl
ow‑Re
s
our
c
e*
Pr
oduc
t
i
v
i
y 524
t
1
3.
2.
6 Y‑ Yj
‑
*EHe
c
to
fXIOnY*E
He
c
to
fX20nY*.
..
*E
He
c
t
o
fXnonY 525
1
3.
2.
7 Y‑ YS
+E
He
c
to
fXIOnY+E
j
f
e
c
to
fX20nY+･
･
.
+
E
He
c
to
fXn onY 527
Cha互
l
e
nge:Mul
t
i
pl
eNo
nl
i
ne
a
rEfe
c
t
s 5
29
1
3.
2.
8 Fu
z
z
yMI
NFu
nc
t
i
on 529
1
3.
2.
9 Fuz
z
yMAXFu
nc
t
i
o
n 530
1
3
.
2.
1
0 Fl
oat
i
ngGoal
s 532
Chal
l
e
nge:Fl
o
a
t
i
ngGoa
l
s 533
Chal
l
e
nge:Goa
lFo
r
ma
t
i
o
nwi
t
hI
nt
e
r
na
la
ndExt
e
r
na
lI
n
put
s 53
5
1
3.
2.
ll Nonl
i
ne
arWe
i
ght
e
dAv
e
r
age 535
1
3.
2.
1
2 Mode
l
i
ngSe
ar
c
h:Hi
l
l
‑
Cl
i
mbi
ngOpt
i
mi
z
at
i
on 537
Chai
l
e
nge:Fi
ndi
ngt
heOpt
i
ma
lMi
xo
fCa
pi
t
a
la
ndLa
bo
r5
43
1
3.
2.
1
3 Re
s
our
c
eAl
l
oc
at
i
on 544
1
3.
3 Co
mmo
nPi
t
f
a
l
l
s 5
45
1
3.
3.
1 Al
l0ut
jl
owsRe
qui
r
eFi
r
s
t
‑
Or
de
rCont
r
ol 545
Cha
l
l
e
nge:Pr
e
ve
nt
i
ngNe
ga
t
i
veSt
oc
ks 5
47
1
3.
3.
2 Av
oi
dI
F...T
HEN...ELSEFor
mul
at
i
ons 547
1
3.
3.
3 Di
s
aggr
e
gat
eNe
tFl
ows 547
1
3･
4 Su
mma
r
y 5
49
1
4 For
mul
at
i
ngNo
nl
i
ne
arRe
l
at
i
ons
hi
ps 551
1
4.
1 Ta
bl
eFunc
t
i
ons 552
1
4.
1
.
1 S
pe
c
l
j
yi
ngT
abl
eFu
nc
t
i
ons 552
1
4.
I
.
2 Exampl
e/Bui
l
di
ngaNonl
i
ne
arFunc
t
i
on 552
Cont
e
nt
s
XXl
1
4.
I
.
3
Pr
oc
e
s
sPoi
nt
:T
abl
eFunc
t
i
onsv
e
r
s
us
Anal
yt
i
cFu
nc
t
i
ons 562
1
4.
2 Ca
s
eSt
udy:
Cut
t
i
ngCo
r
ne
r
sve
r
s
usOve
r
t
i
me 563
Cha
l
l
e
nge
:Fo
m ul
r
a
t
i
ngNo
n
l
i
ne
a
rFunc
t
i
o
ns 566
1
4.
2.
1 Wor
ki
ngOv
e
r
t
i
me:
TheE
j
f
e
c
to
fSc
he
dul
ePr
e
s
s
ur
eonT
V
or
k
we
e
k 567
1
4.
2.
2 Cut
t
i
ngCor
ne
r
s
:
TheEHe
c
to
fSc
he
dul
ePr
e
s
s
u誓onTi
mepe
rT
as
k 568
1
4.
3 Ca
s
eSt
udy:
Es
t
i
ma
t
i
ngNo
nl
i
ne
a
rFunc
t
i
o
nsWi
t
hQua
l
i
t
a
t
i
vea
nd
Nu
me
r
i
c
a
lDa
t
a 56
9
Chal
l
e
nge
:Re
f
i
ni
ngTa
bl
eFunc
t
i
onswi
t
hQua
l
i
t
a
t
i
veDa
t
a 5
69
4 Co
mmo
nPi
t
f
a
l
l
s 573
1
4.
1
4.
4.
1 Us
i
ngt
heWr
ongl
n
put 5
73
Cha
l
l
e
nge
.
ACr
i
t
i
qul
ngNonl
i
ne
a
rFunc
t
i
o
ns 575
1
4.
4.
2 I
mpr
o
pe
rNor
mal
i
z
at
i
on 576
1
4.
4.
3 Av
oi
dHump‑
Sha
pe
dFunc
t
i
ons 577
CI
l
a
l
l
e
nge:Fo
r
mul
a
t
i
ngt
heEr
r
o
rRa
t
e 58
3
Cha
l
l
e
nge
:Te
s
t
i
ngt
heFullMo
de
l 58
5
1
4.
5 El
i
c
i
t
i
ngMode
lRe
l
a
t
i
ons
h
i
psl
nt
e
r
a
c
t
i
ve
l
y 58
5
1
4.
5.
1 Cas
eSt
ud
y:Es
t
i
mat
i
ngPr
e
c
e
de
nc
eRe
l
at
i
ons
hi
psi
n
Pr
oduc
tDe
v
e
l
o
pme
nt 58
7
1
4.
6 Su
mma
r
y 595
1
5 Mode
l
ngHl
i
l
ma
nBe
havi
or:Bo
unde
dRa
t
i
o
na
li
t
yo
r
Ra
t
i
ona
lExpe
c
t
a
t
i
o
ns
? 597
1
5.
1 Hu
ma
nDe
c
i
s
i
onMa
k
i
ng:
Bo
und
e
dRa
t
i
o
na
l
i
t
yo
r
Ra
t
i
o
na
lEx
pe
c
t
a
t
i
o
ns
? 5
98
1
5.
2 Co
g
ni
t
i
veLi
mi
t
a
t
i
o
ns 599
1
5.
3 hd
i
vi
d
ua
la
ndOr
ga
ni
z
a
t
i
o
na
lRe
s
po
ns
e
st
o
Bo
und
e
dRa
t
i
o
na
l
i
t
y 6
01
1
53.
1 Habi
t
,Rout
i
ne
s
,andRul
e
so
fThu
mb 601
1
5.
3.
2 Managi
ngAt
t
e
nt
i
on 601
1
5.
3.
3 GoalFor
mat
i
onandSat
i
s
fi
c
i
ng 601
1
53.
4 Pr
obl
e
mDe
c
ompos
i
t
i
onandDe
c
e
nt
r
al
i
z
e
d
De
c
i
s
i
onMak
i
ng 602
1
5.
4 Ⅰ
nt
e
nde
dRa
t
i
ona
l
i
t
y 6
03
1
5.
4.
1 T
e
s
t
i
ngf
orI
nt
e
nde
dRat
i
onal
i
y:Par
t
t
i
al
Mode
lT
e
s
t
s 605
1
5.
5 Ca
s
eSt
udy:
Mode
l
i
ngHi
g
h‑
Te
c
hGr
o
wt
hFi
r
ms 6
05
1
5.
5.
1 Mode
lSt
r
uc
t
ur
e
:Ov
e
nノ
i
e
w 606
1
5.
5.
2 0r
derFul
fi
l
l
me
nt 607
1
5.
5.
3 Ca
pac
i
yAc
t
qui
s
i
t
i
on 609
Cha
l
l
e
nge:Hi
l
lCl
i
mbi
ng 61
5
1
5.
5.
4 TheSal
e
sFor
c
e 61
5
1
5.
5.
5 TheMar
k
e
t 61
9
1
5.
5.
6 Be
hav
i
oro
ft
heFul
lS
ys
t
e
m 621
Cha
i
l
e
nge:Pol
i
c
yDe
s
i
g
ni
nt
heMa
r
ke
tGr
owt
hMo
de
l 62
4
1
5.
6 Summa
r
y 629
x
x
j
i
Cont
e
nt
s
1
6 For
e
c
a
s
t
sandFudgeFa
c
t
o
r
s
:Mode
l
i
ngExpe
c
t
at
i
onFor
mat
i
on 6
31
1
6.
1 Mode
l
i
ngEx
pe
c
t
a
t
i
o
nFo
r
ma
t
i
o
n 631
1
6.
1
.
1 Mo
de
l
i
n
gGr
o
wt
hEx
pe
c
t
at
i
o
ns
:
TheT
RENDFu
nc
t
i
o
n 63
4
1
6.
1
.
2 Be
h
av
i
oro
ft
heT
RENDFu
nc
t
i
o
n 638
1
6.
2 Ca
s
eSt
udy:
Ene
r
g
yCo
ns
u
mpt
l
On 638
1
6.
3 Ca
s
eSt
ud
y:
Co
mmod
i
t
yPr
i
c
e
s6
43
1
6.
4 Ca
s
eSt
udy:
I
n
la
f
t
i
o
n 6
45
1
6.
5 I
mpl
i
c
a
t
i
o
nsf
o
rFo
r
e
c
a
s
tCo
ns
ume
r
s 655
Cbal
l
e
nge
:Ex
t
r
a
pol
a
t
i
o
na
ndSt
a
bi
l
i
t
y 656
1
6.
6 I
ni
t
i
a
l
i
z
a
t
i
o
na
ndSt
e
a
dySt
a
t
eRe
s
po
ns
eo
f
t
heTRENDFunc
t
i
o
n 6
58
1
6.
7 Su
mma
r
y 6
6
0
PARTV I
NSTABI
LI
TYANDOSCI
LLATI
ON 661
1
7 Suppl
yCha
insandt
heOr
i
g
i
no
fOs
c
i
l
l
at
i
ons 66
3
1
7.
1 Su
ppl
yCha
i
nsi
nBus
i
ne
s
sa
ndBe
yond 66
4
1
7.
1
.
1 0s
c
i
l
l
at
i
o
n
,
Ampl
i
f
i
c
at
i
o
n
,andPhas
eL
J
a
g 6
6
4
1
7.
2 TheSt
oc
kMa
na
g
e
me
ntPr
o
bl
e
m 666
1
7.
2.
1 Man
agl
n
gaSt
oc
k
ISt
r
u
c
t
ur
e 668
1
7.
2.
2 St
e
ad
ySt
at
eEr
r
or 6
71
1
7.
2.
3 Man
agi
n
gaSt
oc
k
IBe
hav
i
or 6
72
Chal
l
e
nge
:Ex
pl
o
r
l
ngAmpl
i
f
i
c
a
t
i
on 674
1
7.
3 TheSt
oc
kMa
na
g
e
me
ntSt
r
u
c
t
u
r
e 6
75
1
7.
3.
1 Be
ha
v
i
oro
ft
heSt
oc
kMana
ge
me
ntSt
r
uc
t
ur
e 68
0
Cha
l
l
e
nge;Ex
pl
o
r
i
ngt
heSt
o
c
kMa
na
ge
me
n
tSt
r
uc
t
ur
e 68
3
1
7.
4 TheOr
i
g
i
no
fOs
c
i
l
l
a
t
i
o
ns 68
4
1
7.
4.
1 Mi
s
mana
gl
ngt
heSu
ppl
yLi
ne
I
me 68
4
TheBe
e
rDi
s
t
r
i
bu
t
i
o
nGa
7.
4.
2 Wh
yDoI
V
eI
gnor
et
heSu
ppl
yLi
ne? 69
5
1
1
7.
4.
3 Ca
s
eSt
u
d
y:Bo
o
mandBu
s
ti
nRe
al
Es
t
at
eMar
k
e
t
s 6
98
Chal
l
e
nge
:Ex
pa
nd
i
ngt
heRe
a
lEs
t
a
t
eMo
de
l7
07
1
7.
5 Summa
r
y 7
07
1
8 TheManuf
ac
t
ur
ingSuppl
yChai
n 709
1
8.
1 ThePo
l
i
c
ySt
r
uc
t
u
r
eo
fl
nve
nt
o
r
ya
ndPr
od
uc
t
i
o
n 71
0
1
8.
1
.
1 07
de
rFu
l
f
i
l
l
me
nt 71
1
1
8.
1
.
2 Pr
o
duc
t
i
on 71
3
1
8.
1
,
3 Pr
o
duc
t
i
o
nSt
ar
t
s 71
4
1
8.
1
.
4 De
mandFor
e
c
a
s
t
i
n
g 71
6
1
8.
1
.
5 Pr
oc
e
s
sPoi
nt
II
ni
t
i
al
i
z
l
n
gaMo
de
li
nEqui
l
i
br
i
u
m 71
6
Chal
l
e
nge:Si
mul
t
a
ne
o
usI
ni
t
i
a
lCo
ndi
t
i
ons 71
8
1
8.
1
.
6 Be
ha
v
i
oro
ft
hePr
o
du
c
t
i
o
nMode
l 72
0
1
8.
1
.
7 Enr
i
c
hi
ngt
heMo
de
l
:
Addi
ngOy
de
rBac
k
l
o
gs 7
23
1
8.
1
.
8 Be
hav
i
oro
ft
heFi
r
mwi
t
hOy
de
rBac
k
l
o
gs 725
1
8.
1
.
9 Addi
ngRawMat
e
r
i
al
sl
nv
e
nt
oY
y 725
1
8.
2 I
nt
e
r
a
c
t
i
o
nsa
mongSu
ppl
yCha
i
nPa
r
t
ne
r
s 729
1
8.
2.
I I
nst
abi
l
it
ya
n
dT
r
u
s
ti
nSu
ppl
yChai
ns 735
x
xi
i
i
Co
n
t
e
nt
s
2.
2
1
8.
Fr
omFunc
t
i
onalSi
l
ost
oI
nt
e
gr
at
e
dSu
ppl
yChai
n
Manage
me
nt 7
40
Cha
ll
e
nge
:Re
e
ngl
ne
e
r
l
ngt
heSu
ppl
yCha
i
n 7
41
1
8.
3 Sys
t
e
mDyna
mi
c
si
nAc
t
i
o
n:
Re
e
ng
l
ne
e
r
l
ngt
heSuppl
yCha
i
ni
na
Hi
g
h‑
Ve
l
oc
i
t
yI
nd
us
t
r
y 7
43
1
8.
3.
1 I
ni
t
i
alP7
1
0bl
e
mDe
f
i
ni
t
i
on 743
1
8.
3.
2 Re
f
e
r
e
nc
eModeandDynami
cHy
pot
he
s
i
s 746
1
8.
3.
3 Mode
lFor
mul
at
i
on 749
1
8.
3
.
4 T
e
s
t
i
ngt
heMode
l 749
1
8.
3.
5 Pol
i
c
yAnal
ys
I
S 751
1
8.
3.
6 I
mpl
e
me
nt
at
i
on:Se
que
nt
i
alDe
bot
t
l
e
ne
c
ki
ng 753
1
8.
3.
7 Re
s
ul
t
s 755
1
8.
4 Summa
r
y 755
1
9 TheLabo
rSuppl
yCha
ina
ndt
heOr
i
g
i
nofBus
i
ne
s
sCyc
l
e
s 75
7
1
9.
1 TheLa
borSuppl
yCha
i
n 758
1
9.
1
.
1 St
r
uc
t
ur
eo
fLaborandHi
r
i
ng 758
1
9.
I
.
2 Be
havi
oro
ft
heLaborSu
ppl
yChai
n 760
1
9.
2 I
nt
e
r
a
c
t
i
onsofLa
bo
ra
ndl
nve
nt
o
r
yMa
na
ge
me
n
t 76
4
Cha
l
l
e
nge:Me
nt
a
lSi
mul
a
t
i
o
no
f
l
nv
e
nt
o
r
yMa
na
ge
me
ntwi
t
hLa
bo
r 76
6
1
9.
2.
1 I
nv
e
nt
o7
7‑T
Y
or
k
f
or
c
eI
nt
e
r
ac
t
i
ons
:Be
havi
or 766
1
9.
2.
2 Pr
oc
e
s
sPoi
nt
:Ex
pl
ai
nl
ngMode
lBe
havi
or 767
Cha
l
l
e
nge:Ex
pl
a
i
nl
ngOs
c
i
l
l
a
t
i
o
ns 76
7
2.
3 Unde
r
s
t
andi
ngt
heSour
c
e
so
fOs
c
i
l
l
at
i
on 771
1
9.
Cha
l
l
e
mge:Po
l
i
c
yDe
s
i
g
nt
oEnha
nc
eSt
a
bi
l
i
t
y 773
2.
4 Addi
ngOv
e
r
t
i
me 774
1
9.
1
9.
2.
5 Re
s
pons
et
oFl
e
xi
bl
eWor
k
we
e
k
s 776
Cha
l
l
e
nge:Re
e
ngl
ne
e
r
l
ngaMa
nuf
a
c
t
ur
i
ngFi
r
m
f
o
rEnha
nc
e
dSt
a
bi
l
i
t
y 778
1
9.
2.
6 TheCos
t
so
fl
ns
t
abi
l
i
y 7
t
79
Cba
l
l
e
nge:TheCos
t
so
fl
ns
t
a
bi
l
i
t
y 78
0
CI
l
a
l
l
e
nge:
Addi
ngTr
a
i
ni
nga
ndEx
pe
r
i
e
nc
e 78
0
1
9.
3 I
nv
e
nt
o
r
y
‑Wo
r
kf
o
r
c
eI
nt
e
r
a
c
t
i
o
nsa
ndt
heBus
i
ne
s
sCyc
l
e 78
2
1
9.
3.
1 I
st
heBu
s
i
ne
s
sCyc
l
eDe
ad? 785
1
9｡
4 Summa
r
y 788
20 Thel
nv
is
i
bl
eHandSo
me
t
i
me
sSha
ke
s
:Co
mmodi
t
yCyc
l
e
s 791
20･
1 Commodi
t
yCyc
l
e
s
:
Fr
o
mAi
r
c
r
a
f
tt
oZi
nc 792
2
0.
2 AGe
ne
r
i
cCo
mmodi
t
yMa
r
ke
tMod
e
1 798
20.
2.
1 Pr
oduc
t
i
onandI
nv
e
nt
oT
y 8
01
20.
2.
2 Ca
paci
y Ut
t
i
l
i
z
at
i
on 802
20.
2.
3 Py
1
0duc
t
i
onCa
pac
i
y 8
t
05
20.
2.
4 De
s
i
r
e
dCa
pac
i
y
t
8
07
Cha
l
l
e
nge
:I
nt
e
nde
dRa
t
i
o
na
l
i
t
yo
ft
heI
n
ve
s
t
me
ntPr
o
c
e
s
s 81
0
20.
2.
5 De
mand 81
1
20.
2.
6 ThePr
i
c
e‑
Se
t
t
i
ngPr
oc
e
s
s 81
3
20.
3 App
l
i
c
a
t
i
on:
Cyc
l
e
si
nt
hePul
pa
ndPa
pe
rl
nd
us
t
r
y 8
24
Cl
l
a
l
l
e
nge
:Se
ns
i
t
i
vl
t
yt
OUnc
e
r
t
a
i
nt
yi
nPa
r
a
me
t
e
r
s 8
28
X
X
r
V
Co
n
t
e
n
t
s
Cha
l
l
e
nge
:Se
ns
i
t
i
vl
t
yt
OSt
r
uc
t
ur
a
lCha
nge
s 831
Cha
l
l
e
nge
:I
mpl
e
me
nt
l
ngSt
uc
r
t
ur
a
lCha
nge
s
I
Mod
e
l
i
ngLi
ve
s
t
oc
kMa
r
ke
t
s 8
36
Cha
l
l
e
nge
:Po
l
i
c
yAna
l
ys
I
S 8
40
20.
4 Su
mma
r
y 8
4l
PARTVI MODELTESTI
NG 843
21 7hl
t
handBe
aut
y:
Va
l
i
dat
i
ona
ndMode
lTe
s
t
i
ng 8
45
21
.
1 Va
l
i
da
t
i
o
na
ndVe
r
i
f
i
c
a
t
i
o
nAr
eI
mpos
s
i
bl
e 8
46
21
.
2 Que
s
t
i
onsMod
e
lUs
e
r
sSho
ul
dAs
k‑ButUs
ua
l
l
yDo
nう
ー8
51
21
.
3 Pr
a
g
ma
t
i
c
sa
ndPol
i
t
i
c
sofMode
lUs
e 8
51
21
.
3.
1 T
y
pe
so
fDat
a 8
53
21
.
3.
2 Doc
u
me
nt
at
i
o
n 8
55
21
.
3.
3 Re
pl
i
c
abi
l
i
y 8
t
5
5
21
･
3･
4 Pr
ot
e
c
t
i
v
ev
e
.
r
s
u
sRe
j
l
e
c
t
i
v
eMo
de
l
i
ng 8
58
21
.
4 Mo
de
l
Te
s
t
i
ngi
nPr
a
c
t
l
C
e 8
58
21
.
4.
1 Bou
n
d
a7
TAde
qu
ac
yT
e
s
t
s 8
61
21
A.
2 St
r
u
c
t
u
r
eAs
s
e
s
s
me
ntT
e
s
t
s 8
63
21
.
4.
3 Di
me
n
s
i
o
nalCon
s
i
s
t
e
nc
y 8
66
4 Par
a
me
t
e
rAs
s
e
s
s
me
nt 8
66
21
.
4.
21
.
4.
5 Ext
r
e
meCo
n
di
t
i
o
nT
e
s
t
s 8
69
Cha
ll
e
nge
:Ext
r
e
meCo
ndi
t
i
o
nTe
s
t
s 8
71
21
.
4.
6 I
nt
e
gr
at
i
o
nEr
r
orT
e
s
t
s 8
72
21
.
4.
7 Be
ha
v
i
orRe
pr
odu
c
t
i
o
nT
e
s
t
s 8
74
21
.
4.
8 Be
hav
i
orAno
mal
yT
e
s
t
s 88
0
21
.
4.
9 Fa
mi
l
yMe
mbe
rT
e
s
t
s 881
21
.
4.
1
0 Su
r
pr
i
s
eBe
h
av
i
orT
e
s
t
s 88
2
21
.
4.
l
l Se
ns
i
t
i
v
i
yAnal
t
y
s
i
s 883
21
.
4.
1
2 S
y
s
t
e
mI
mpr
o
v
e
me
ntT
e
s
t
s 88
7
Cha
l
l
e
nge
:Mo
de
lTe
s
t
i
ng 88
9
21
.
5 Summa
r
y 8
9
0
PARTVI
I COMMENCEMENT 89
3
22 Chal
l
e
nge
sf
o
rt
heFut
ur
e 8
95
22.
1 The
o
r
y 8
95
22.
2 Te
c
hno
l
o
gy 8
96
22.
3 I
mpl
e
me
nt
a
t
i
on 8
99
22.
4 Ed
uc
a
t
i
on 9
0
0
22.
5 Appl
i
c
a
t
i
ons 901
Chal
l
e
nge:Put
t
i
ngSys
t
e
mDyna
mi
c
si
nt
oAc
t
i
o
n 9
01
APPENDI
XA NUMERI
CALI
NTEGRATI
ON 903
Chal
l
e
ng
e:Choos
i
ngaTi
meSt
e
p 91
0
APPENDI
XB NOI
SE 91
3
Chal
l
e
ng
e:Ex
pl
o
r
l
ngNo
i
s
e 922
REFERENCES 9
25
I
NDEX 947
Dyna
mi
c
sofMu
l
t
i
pl
e
‑
Loo
pSys
t
e
ms 1
4
Hy
pot
he
s
i
sTe
s
t
l
ng 3
0
I
d
e
n
t
i
f
y
i
ngFe
e
d
ba
c
kSt
r
uc
t
ur
ef
r
omSys
t
e
mBe
ha
vi
o
r 1
1
7
I
d
e
n
t
i
f
y
i
ngt
heLi
mi
t
st
oGr
owt
h 1
22
As
s
i
g
ni
ngLi
nkPo
l
a
r
i
t
i
e
s 1
43
I
d
e
n
t
i
f
yi
ngLi
nka
ndLoo
pPo
l
a
r
i
t
y 1
45
Emp
l
o
ye
eMo
t
i
v
a
t
i
o
n 1
47
Pr
o
c
e
s
sl
mpr
ove
me
n
t 1
58
Po
l
i
c
yAna
l
ys
i
swi
t
hCa
us
a
lDi
a
g
r
a
ms 1
68
TheOi
lCr
i
s
e
so
ft
he1
970s 1
72
Spe
c
ul
a
t
i
veBub
bl
e
s 1
73
TheTho
r
o
ug
hbr
e
dHo
r
s
eMa
r
ke
t 1
7
4
TheMe
di
ga
pDe
a
t
hSpi
r
a
l 1
76
I
d
e
n
t
i
f
y
i
ngt
heFe
e
d
ba
c
kSt
r
uc
t
u
r
eo
fPo
l
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a
c
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mode
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di
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i
o
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ta
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st
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te
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t
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.
‑
21
3･
4 TheModel
岳
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ocess
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i
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t
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t
i
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:
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nc
ewa
sl
a
r
ge
l
y
s
e
e
na
sapr
oc
e
s
sofde
f
e
c
tc
o
r
r
e
c
t
i
o
n(
r
e
pa
i
roff
a
i
l
e
de
q
ui
pme
nt
)a
ndt
hema
i
nt
e
‑
na
nc
ef
unc
t
i
o
nwa
svi
e
we
da
sac
os
tt
obemi
ni
mi
z
e
d･
Thef
i
r
s
tc
onc
e
pt
ua
ls
hi
f
t
wa
st
oc
ha
ng
et
hef
o
c
usf
r
o
m de
f
e
c
tc
o
r
r
e
c
t
i
ont
ode
f
e
c
tpr
e
ve
nt
i
ona
ndde
f
e
c
t
e
l
i
mi
na
t
i
o
n.Themode
lt
he
r
e
f
o
r
ec
e
nt
e
r
e
dont
hephys
i
c
so
fbr
e
a
kdo
wnsr
a
t
he
r
t
ha
nt
hec
os
tmi
ni
mi
z
a
t
i
onme
nt
a
l
i
t
yt
ha
tpr
e
va
i
l
e
dt
hr
o
ug
ho
utt
heo
r
ga
ni
z
a
t
i
o
n.
Equi
pme
ntf
a
i
l
swhe
nas
uf
f
i
c
i
e
ntn
umbe
rofl
a
t
e
ntd
e
f
e
c
t
sa
c
c
umul
a
t
ei
ni
t
.
La
t
e
nt
d
e
f
e
c
t
sa
r
ea
nypr
obl
e
mt
ha
tmi
g
htu
l
t
i
ma
t
e
l
yc
a
us
eaf
a
i
l
ur
e
.
The
yI
nc
l
udel
e
a
ky
o
i
ls
e
a
l
si
npumps
,di
r
t
ye
qul
pme
ntt
ha
tc
a
us
e
sbe
a
r
i
ngwe
a
r
,pumpa
ndmot
o
r
s
ha
f
t
st
ha
ta
r
eo
uto
ft
r
uea
ndc
a
us
ev
i
br
a
t
i
o
n,
poo
r
l
yc
a
l
i
br
a
t
e
di
ns
t
r
ume
nt
a
t
i
o
n,
a
nds
oo
n.
Ap
umpwi
t
hal
e
a
kyo
i
ls
e
a
lo
rdi
r
t
ybe
a
r
l
ngSC
a
nS
t
i
l
l
r
u
nbutwi
l
le
ve
n
t
ua
l
l
yf
a
i
lunl
e
s
st
he
s
el
a
t
e
ntde
f
e
c
t
sa
r
ee
l
i
mi
na
t
e
d.
‑
68
Pa
r
t
IP
e
r
s
p
e
c
t
i
v
ea
n
dPr
o
c
e
s
s
Thet
ot
a
lnumbe
rofl
a
t
e
ntdef
e
ct
si
napl
a
nt
'
sequi
pme
nti
sas
t
oc
k(
Fi
gur
e
21
8)
･De
f
e
ct
sa
r
ec
r
ea
t
e
dbyope
r
a
t
i
ons(
nor
ma
lwea
ra
ndt
ea
r
)a
ndbycol
l
a
t
e
r
a
l
da
ma
gea
r
i
s
i
ngf
r
om br
ea
kdowns(
whe
nt
heoi
ll
ea
ksoutoft
hepumpbea
r
i
nga
nd
t
hebea
r
l
ngS
e
i
z
es
,t
hes
ha
f
tmaybebe
nt
,t
hemot
orma
yove
r
hea
t
,a
ndt
hevi
br
a
‑
t
i
onma
ybr
e
a
kcoupl
i
ngsa
ndpi
pes
,i
nt
r
oduc
i
ngne
w pr
obl
e
ms
)
IMor
es
ubt
l
y,
ma
i
nt
e
na
nc
ea
c
t
i
vl
t
yCa
nC
r
ea
t
enewde
f
e
c
t
s
,
t
hr
oughme
c
ha
ni
ce
r
r
or
sort
heus
eof
poorqua
li
t
yr
e
pl
a
ce
me
ntpa
r
t
s
･
Thel
owe
rt
hei
nt
r
i
ns
i
cdes
i
gnqua
l
i
t
yoft
heequ
me
nt
,t
hemor
ede
f
e
c
t
st
hes
ea
ct
i
vi
t
i
esc
r
ea
t
e.
Thes
t
oc
kofde
f
e
c
t
si
sdr
a
i
ne
dbyt
wof
lows
:r
e
a
c
t
i
vema
i
nt
e
na
nce(
r
e
pa
i
rof
f
a
i
l
edequi
pme
nt
)a
ndpl
a
nne
dma
i
nt
e
na
nce(
pr
oa
c
t
i
ver
e
pa
i
rofope
r
a
bl
eequi
p
me
nt
)
.
1
3Ea
c
hoft
hes
ea
c
t
i
vi
t
i
esf
or
msaba
l
a
nc
i
ngf
e
edba
c
kl
oop.
Asde
f
ec
t
sa
cI
c
umul
a
t
e,
t
hec
ha
nc
eofabr
ea
kdowni
nc
r
eas
es
.
Br
ea
kdownsl
e
a
dt
omor
er
ea
ct
i
ve
l P
‑
‑
FI
GURE2‑
8 Def
ec
tcr
eat
i
onandel
i
mi
nat
i
on
Thedi
agr
am i
ssi
mpl
i
f
i
ed.l
nt
hef
ul
lmodel
equl
PmentWasdi
vi
dedi
n
t
ooper
abl
e,br
ok
en
down,andt
ak
endownf
orpl
annedmai
nt
enance,
wi
t
hanas
soci
at
eds
t
ockofl
at
ent
def
ec
t
sf
oreachcat
egor
y
.
i
v
e(
t
i
me
‑
b
a
s
e
d
)wo
rk
,
e
.
g
.
,
r
e
p
l
a
c
ewo
r
np
a
r
t
so
n
1
3
pl
a
n
n
e
dma
i
n
t
e
n
a
n
c
ei
n
c
l
u
d
e
sp
r
e
v
e
n
t
p
u
mp
se
v
e
r
ynmo
n
t
h
s
,
a
n
dp
r
e
d
i
c
t
i
v
e(
c
o
n
d
i
t
i
o
n
‑
b
a
s
e
d
)wo
r
k,
e
.
g
,
,r
e
p
l
a
c
ewo
r
np
a
r
t
so
nap
u
mp
i
fv
i
b
r
a
t
i
o
ne
x
c
e
e
d
sac
e
r
t
a
i
nt
ol
e
r
a
n
c
e
.
69
Ch
a
p
t
e
r2 S
y
s
t
e
mDy
n
a
mi
c
si
nAc
t
i
o
n
ma
i
nt
e
na
nc
e,a
nd,a
f
t
e
rr
e
pa
l
r
,t
hee
qul
Pme
nti
sr
e
t
ur
ne
dt
os
e
r
vi
c
ea
ndt
hes
t
oc
k
ofde
f
e
c
t
si
sr
e
d
uc
e
d(
t
heRe
a
c
t
i
veMa
i
nt
e
na
nc
el
oopBl
)
.Si
mi
l
a
r
l
y,s
c
he
dul
e
d
ma
i
nt
e
na
nc
eore
qui
pme
ntmoni
t
or
i
ngma
yr
e
ve
a
lt
hepr
e
s
e
nceo
fl
a
t
e
ntde
f
e
c
t
s(
a
vi
br
a
t
i
ngpump,
a
no
i
ll
e
a
k)
.
Thee
qui
pme
nti
st
he
nt
a
ke
noutofs
e
r
vi
c
ea
ndt
hede
‑
f
e
c
t
sa
r
ec
or
r
e
c
t
e
dbe
f
or
eabr
e
a
kdownoc
c
ur
s(
t
hePl
a
nne
dMa
i
nt
e
na
nc
el
oo
pB2)
.
Obvi
ous
l
yb
r
e
a
kdownsr
e
duc
epl
a
ntupt
l
me.I
na
ddi
t
i
on,mos
tpl
a
nne
dma
i
n‑
t
e
na
nc
ea
c
t
i
vi
t
ya
l
s
or
e
d
uc
esupt
l
meS
i
nc
epl
a
nne
dma
i
nt
e
na
nc
ef
r
e
que
nt
l
yr
e
‑
qul
r
e
SOpe
r
a
bl
ee
qul
pme
ntbet
a
ke
noutofs
e
r
vi
c
es
ot
hene
e
de
dwo
r
kc
a
nbedone･
Fi
gur
e2‑
8S
howsonl
yt
hemos
tba
s
i
cphys
i
csofde
f
e
c
ta
c
c
umul
a
t
i
on.Thet
wo
ne
ga
t
i
vef
e
e
d
ba
c
ksr
e
gul
a
t
i
ngt
hes
t
oc
kofde
f
e
c
t
sa
ppea
rt
obes
ymme
t
r
i
ca
l
:De
‑
f
e
c
t
sca
nbee
l
i
mi
na
t
e
de
i
t
he
rbypl
a
nne
dma
i
nt
e
na
nc
eorr
e
pa
i
rOff
a
i
l
e
de
qul
p‑
me
nt
.Thef
ul
ls
ys
t
e
mi
smo
r
ec
ompl
e
x,howe
ve
r
,a
ndi
ncl
ude
sanumbe
rof
pos
i
t
i
ve,s
e
l
f
‑
r
e
i
nf
or
c
i
ngf
e
e
dba
c
ks(
Fi
gur
e21
9)
.
Fr
GURE2‑
9 Posi
t
i
vef
eedback
sunder
cu
t
t
i
ngpl
ann
edmai
nt
enan
ce
+
70
Pa
r
t
IP
e
r
s
p
e
c
t
i
v
ea
n
dP
r
o
c
e
s
s
Cons
i
de
rt
hei
mpa
c
toft
hef
i
r
s
toi
lc
r
i
s
i
si
nl
a
t
e1
973.
I
nputa
ndo
pe
r
a
t
l
ngc
os
t
s
s
kyr
oc
ke
t
e
d.
Butt
hes
e
ve
r
er
e
c
es
s
i
ont
ha
tbe
ga
ni
n1
974me
a
ntc
he
mi
c
a
lpr
oduc
‑
e
r
sc
oul
dnotpa
s
st
hee
nt
i
r
ec
os
ti
nc
r
e
a
s
eont
oc
ons
ume
r
s
.
Unde
ri
nt
e
ns
ef
i
na
nc
i
a
l
pr
e
s
s
ur
e,a
l
lpl
a
nt
sa
ndf
u
nc
t
i
onsha
dt
oc
utc
os
t
s
･
I
fma
i
nt
e
na
nc
ede
pa
r
t
me
nt
sa
r
e
a
s
ke
dt
oc
ute
xpe
ns
esne
a
r
l
ya
l
loft
hec
utha
st
oc
omef
r
o
ma
ct
ivi
t
i
ess
uc
ha
spl
a
n一
ml
nga
ndpr
e
ve
nt
i
vema
i
nt
e
na
nc
e:Whe
nc
r
i
t
i
c
a
le
qul
pme
ntbr
e
a
ksdown,i
tmus
t
bef
i
xe
d.
Att
hes
m et
a
i
me,
f
i
na
nc
i
a
lpr
es
s
ur
el
e
a
dst
oot
he
ra
c
t
i
ons(
e.
g.
,
pos
t
pon1
1
ngr
e
pl
a
c
e
me
ntofol
de
r
,
l
e
s
sr
e
l
i
a
bl
ee
qul
pme
ntOrr
unnl
nge
qul
pme
ntl
onge
ra
nd
mo
r
ea
gg
r
e
s
s
i
ve
l
yt
ha
nor
i
gi
na
ldes
i
gns
pe
c
i
f
i
c
a
t
i
onsi
ndi
c
a
t
e
)
,
whi
c
hi
nc
r
e
a
s
et
he
ma
i
nt
e
na
nc
ewo
r
kl
oa
d.
Wi
t
hr
es
our
c
e
sf
o
rpl
a
nne
dma
i
nt
e
na
nc
edi
mi
ni
s
hi
nga
nd
ma
i
nt
e
na
nc
ene
e
dsi
nc
r
e
a
s
i
ng,t
hes
t
oc
kofde
f
e
c
t
sgr
ows
.
Br
e
a
kdownsi
nc
r
ea
s
e.
Br
e
a
kdownsc
a
us
ec
ol
l
a
t
e
r
a
lda
ma
ge,di
r
e
c
t
l
yi
nc
r
e
a
s
i
ngt
hes
t
oc
kofde
f
e
c
t
sf
ur
‑
t
he
ra
ndl
e
a
di
ngt
os
t
i
l
lmor
ebr
e
a
kdownsi
navi
c
i
ousc
yc
l
e(
t
hepos
i
t
i
vel
oopRl
)
.
Be
c
a
us
et
het
ot
a
lnumbe
rofme
c
ha
ni
c
si
sl
i
mi
t
e
d,mor
ebr
e
a
kdownsne
c
e
s
s
a
r
i
l
y
pul
lme
c
ha
ni
c
sof
fpl
a
nne
dwor
ka
sma
na
ge
me
ntr
e
a
s
s
l
gnSme
c
ha
ni
c
st
or
e
pa
l
r
wo
r
k.
Butma
nyme
c
ha
ni
c
sa
ls
opr
e
f
e
rr
e
pa
l
rWOr
k.
Apl
a
nne
dma
i
nt
e
na
nc
ema
n‑
a
ge
ri
nonepl
a
ntc
omme
nt
e
d,H
We
'
Veha
ds
e
ve
r
a
lpe
o
pl
ewhos
a
yt
he
ywa
ntt
oge
t
i
nvol
ve
di
npr
e
ve
nt
i
vewor
kbutwhe
na
nout
a
gec
o
me
sa
nd[
t
he
y]ha
veac
ha
nc
e
t
owo
r
k1
4‑1
6hour
spe
rwe
e
kove
r
t
i
met
he
ys
a
ỳ
t
ohe
l
lwi
t
ht
hi
svi
br
a
t
i
on[
mo
n‑
i
t
or
i
ng]s
t
uf
F
,Ⅰ
'
mgoi
ngt
ot
heout
a
gea
r
e
a.
"'
Wi
t
hl
e
s
spl
a
nne
dwor
k,
br
ea
kdowns
i
nc
r
e
a
s
es
t
i
l
lmor
e
,f
or
ml
ngt
her
e
i
nf
or
c
i
ngGot
ot
heOut
a
gel
oopR2.
Ther
i
s
i
ngbr
e
a
kdownr
a
t
emea
nsmor
ec
r
i
t
i
c
a
le
qul
Pme
ntWi
l
lbeoutofs
e
r
‑
vi
c
ea
wa
i
t
l
ngr
e
pa
i
r
.
Pl
a
ntupt
l
mef
a
l
l
s
.Pl
a
ntope
r
a
t
or
sf
i
ndi
tha
r
de
rt
ome
e
tde
‑
ma
nd.
Whe
name
c
ha
ni
corma
i
nt
e
na
nc
es
upe
r
vi
s
o
rr
e
q
ue
s
t
st
ha
tac
e
r
t
a
i
npl
e
C
eOf
e
qui
pme
ntbet
a
ke
nof
fl
i
net
oc
or
r
e
c
tl
a
t
e
ntde
f
e
c
t
s
,t
heha
r
r
i
e
dl
i
nema
na
ge
ri
s
l
i
ke
l
yt
os
ho
uts
ome
t
hi
ngl
i
keH
Ic
a
nba
r
e
l
yme
e
tde
ma
nda
si
ti
sa
ndyouwa
ntme
t
ot
a
ket
hi
sl
i
nedo
wn?Nowa
yJfyouma
i
nt
e
na
nc
epe
o
pl
ewe
r
edoi
ngyourj
ob,
I
woul
dn'
tha
ves
oma
nydownpumpsi
nt
hef
i
r
s
tpl
a
c
e.Nowge
toutofhe
r
e,I
'
ve
gotapl
a
ntt
or
un.
"Theba
l
a
nc
i
ngTooBus
yf
orPM l
oop(
B3)me
a
nso
pe
r
a
t
or
sa
r
e
l
e
s
swi
l
l
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e
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e
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t
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mi
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t
i
o
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pr
oa
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a
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i
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e
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e
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orp
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ne
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ve
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s
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l
l
TABL
E21
1
ResuJ
t
sf
r
om
s
e一
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t
edpo一
i
c
y
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muf
at
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73
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n
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Pr
of
i
t
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year
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l
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om
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20
pr
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9.
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,
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or
c
et
heH
whydowe
ne
e
di
t
"di
s
c
us
s
i
o
natt
hes
t
rto
a
ft
hepr
o
j
e
c
t
.
･
The
r
ea
r
ema
n
ypr
o
bl
e
msf
o
rwhi
c
hs
ys
t
e
mdy
na
mi
c
si
snotus
e
f
ul
Ca
r
e
f
u1
1
yc
o
ns
i
d
e
rwhe
t
he
rs
ys
t
e
md
yna
mi
c
si
st
her
i
g
h
tt
e
c
hni
q
uef
ort
he
pr
o
bl
e
m.
Mod
e
l
e
r
ss
ho
ul
dwe
l
c
o
med
i
f
f
i
c
ul
tq
ue
s
t
i
o
nsf
r
o
mt
hec
l
i
e
nt
s
a
bo
utho
wt
hep
r
o
c
e
s
swo
r
ksa
ndhowi
tmi
g
hthe
l
pt
he
mwi
t
ht
he
i
r
pr
o
bl
e
m.
Thee
a
r
l
i
e
rt
he
s
ei
s
s
ue
sa
r
edi
s
c
us
s
e
d,
t
hebe
t
t
e
r
.
4. Sys
t
e
m dyna
ic
m
sdoe
snots
t
anda
l
one
.
Us
eo
t
he
rt
oo
l
sa
ndme
t
hodsas
a
ppr
o
pr
i
a
t
e
.
Mos
tmod
e
l
i
ngpr
o
j
e
c
t
sa
r
ePa
r
tO
fal
a
r
ge
re
f
f
o
r
ti
nvo
l
v
i
ngt
r
a
d
i
t
i
o
na
l
s
t
r
a
t
e
gl
Ca
ndo
pe
r
a
t
i
o
na
la
na
l
ys
i
s
,
i
nc
l
udi
ngbe
nc
hma
r
k
i
ng,
s
t
a
t
i
s
t
i
c
a
lwo
r
k,
ma
r
ke
tr
e
s
e
a
r
c
h,
e
t
c
.
Ef
f
e
c
t
i
vemode
l
i
ngr
e
s
t
so
nas
t
r
o
ngba
s
eo
fda
t
aa
nd
und
e
r
s
t
a
nd
i
ngo
ft
hei
s
s
ue
s
,
Mode
l
i
ngwo
r
ksbe
s
ta
sac
ompl
e
me
ntt
oo
t
he
r
t
o
ol
s
,
no
ta
sas
u
bs
t
i
t
u
t
e.
t
.
5.Foe
l
l
SO
ni
mpl
e
me
nt
a
t
i
o
nf
r
om t
hes
t
ar
to
ft
hepr
o
j
e
c
I
mpl
e
me
nt
a
t
i
o
nmus
ts
t
a
r
to
nt
hef
i
r
s
tda
yoft
hepr
o
J
e
C
LCo
ns
t
a
nt
l
ya
s
k,
Howwi
l
lt
hemo
d
e
lhe
l
pt
hec
l
i
e
ntma
kede
c
i
s
i
o
ns
?Us
et
hemode
lt
os
e
t
pr
l
O
r
i
t
i
e
sa
n
dde
t
e
r
mi
net
hes
e
que
nc
eofpo
l
i
c
yl
mpl
e
me
nt
a
t
i
o
n･
Us
et
he
mod
e
lt
oa
ns
we
rt
heque
s
t
i
on,
Ho
wdowege
tt
he
r
ef
r
o
mhe
r
e
?Ca
r
e
f
ul
l
y
c
o
ns
i
de
rt
her
e
a
lwo
r
l
di
s
s
ue
si
nvol
ve
di
npul
l
i
ngva
r
i
o
uspo
l
i
c
yl
e
ve
r
s
.
Qua
nt
if
yt
hef
ul
lr
a
n
geo
fc
os
t
sa
ndbe
ne
f
i
t
so
fpo
l
i
c
i
e
s
,
no
to
n
l
yt
hos
e
a
l
r
e
a
d
yr
e
po
r
t
e
dbye
xi
s
t
i
nga
C
C
O
unt
l
ngS
yS
t
e
mS
･
6.Mo
de
l
i
ngwor
ksbe
s
ta
sa
ni
t
e
r
at
i
vepr
oc
e
s
so
fj
oi
nti
nqui
r
ybe
t
we
e
n
.
di
e
ntandC
ons
ul
t
ant
Mode
l
i
ngl
Sapr
oc
e
s
sO
fdi
s
c
ove
r
y･
Thegoa
li
st
or
e
a
c
hne
wunde
r
s
t
a
ndi
ng
ofhowt
hep
r
o
bl
e
ma
r
i
s
e
sa
nd血e
nus
et
ha
tunde
r
s
t
a
nd
i
ngt
od
e
s
i
gnhi
g
h
l
e
ve
r
a
gepo
l
i
c
i
e
sf
ori
mpr
o
ve
me
n
t
･
Mode
l
i
ngs
ho
ul
dno
tbeus
e
da
sat
ool
f
c
L
ra
d
voc
a
c
y
.
Do
n'
tbu
i
l
dac
l
i
e
nf
jspr
i
o
rOPl
ni
o
na
bo
utwha
ts
ho
ul
dbe
donei
nt
oamo
de
l
.
Us
ewo
r
ks
ho
pswhe
r
et
hec
l
i
e
nt
sc
a
nt
e
s
tt
hemod
e
l
t
he
ms
e
l
ve
s
,
i
nr
e
a
lt
i
me.
7.Avo
i
dbl
ac
kboxmo
de
l
i
ng.
Mode
l
sbu
i
l
to
uto
ft
hes
i
g
htoft
hec
l
i
e
ntwi
l
lne
ve
rl
e
a
dt
oc
ha
ngei
n
de
e
pl
yhe
l
dme
nt
a
lmo
de
l
sa
ndt
he
r
e
f
o
r
ewi
l
lnotc
ha
ngec
l
i
e
n
tbe
ha
vi
o
r
.
I
nvo
l
vet
hec
l
i
e
nt
sa
se
a
r
l
ya
nda
sde
e
pl
ya
spos
s
i
bl
e
.
Sho
wt
he
mt
hemode
l
･
Enc
ou
r
a
get
he
mt
os
ug
ge
s
ta
ndr
unt
he
i
ro
wnt
e
s
t
sa
ndt
oc
r
i
t
i
c
i
z
et
he
mod
e
l
.
Wわ
r
kwi
t
ht
he
mt
or
e
s
ol
vet
he
i
rc
r
i
t
i
c
i
s
mst
ot
he
i
rs
a
t
i
s
f
a
c
t
i
on.
Ch
a
p
t
e
r
2 S
y
s
t
e
mDy
n
a
mi
c
s
i
nAc
t
i
o
n
81
8.Va
l
i
dat
i
o
ni
sac
ont
i
nuo
uspr
o
c
e
s
so
ft
e
s
t
i
ngandbui
l
di
ngc
onf
i
de
nc
ei
n
t
hemode
l
.
Mode
l
sa
r
eno
tva
l
i
da
t
e
da
f
t
e
rt
he
ya
r
ec
o
mpl
e
t
e
dno
rbya
nyon
et
e
s
ts
uc
h
a
st
he
i
ra
b
i
l
i
t
yt
of
i
thi
s
t
o
r
i
c
a
ld
a
t
a
.
Cl
i
e
nt
s(
a
ndmod
e
l
e
r
s
)bu
i
l
dc
o
nf
i
d
e
nc
e
i
nt
heut
i
l
i
t
yofamo
de
lg
r
a
d
ua
l
l
y
,
b
yc
ons
t
a
nt
l
yc
onf
r
o
nt
i
ngt
hemo
d
e
lwi
t
h
da
t
aa
nde
x
pe
r
to
pi
ni
o
n
‑t
he
i
rowna
ndo
t
he
r
s
'
.
Thr
o
ught
hi
spr
o
c
e
s
sbot
h
mo
de
la
nde
x
pe
r
to
pi
ni
o
nswi
l
lc
ha
ngea
ndde
e
pe
n.
Se
e
ko
uto
ppo
r
t
uni
t
i
e
s
t
oc
ha
l
l
e
n
get
hemo
de
l
'
sa
bi
l
i
t
yt
or
e
pl
i
c
a
t
eadi
ve
r
s
er
a
ngeo
fhi
s
t
o
r
i
c
a
l
e
X
l
j
e
r
l
e
nC
e
S
.
⊥
9.Ge
tapr
e
l
i
mi
nar
ymode
lwor
ki
nga
ss
oonaspos
s
i
bl
e
｡
Addde
t
ilo
a
nl
y
aSne
e
e
S
S
a
r
y
･
De
ve
l
o
pawo
r
ki
ngs
i
mul
a
t
i
o
nmod
e
la
ss
oo
na
spos
s
i
bl
e.
Don'
tt
r
yt
o
de
ve
l
o
pac
ompr
e
he
ns
i
vec
o
n
c
e
pt
ua
lmode
lp
r
l
O
rt
Ot
hede
ve
l
o
pme
nto
fa
s
i
mul
a
t
i
o
nmode
l
,
Co
nc
e
pt
ua
lmod
e
l
sa
r
eo
nl
yhypo
t
he
s
e
sa
ndmus
tbe
t
e
s
t
e
d.
Fo
r
ma
l
i
z
a
t
i
o
na
nds
i
mul
a
t
i
o
no
f
t
e
nu
nc
o
ve
rf
la
wsi
nc
o
nc
e
pt
ua
l
ma
psa
ndl
e
a
dt
oi
mpr
o
ve
dunde
r
s
t
a
nd
i
ng･
Ther
e
s
ul
t
sofs
i
mul
a
t
i
o
n
e
x
pe
r
i
me
nt
si
nf
o
r
mc
onc
e
p
t
ua
lunde
r
s
t
a
ndi
nga
ndhe
l
pbui
l
dc
o
nf
i
de
nc
ei
n
t
her
e
s
ul
t
s
.
Ea
r
l
yr
e
s
ul
t
spr
o
v
i
dei
mme
d
i
a
t
eva
l
uet
oc
l
i
e
nt
sa
ndj
us
t
i
f
y
c
o
nt
i
nue
di
nve
s
t
me
nto
ft
he
i
rt
i
me.
1
0.Abr
oadmode
lbo
undar
yl
Smor
ei
mpo
r
t
a
ntt
hanagr
e
atde
lo
a
fde
t
il
a
.
Mo
de
l
smus
ts
t
r
i
keaba
l
a
nc
ebe
t
we
e
naus
e
f
u
l
,
o
pe
r
a
t
i
ona
lr
e
pr
e
s
e
n
t
a
t
i
o
n
oft
hes
t
r
u
c
t
ur
e
sa
ndpo
l
i
c
yl
e
ve
r
sa
va
i
l
a
bl
et
ot
hec
l
i
e
nt
swhi
l
ec
a
pt
u
r
l
ng
t
hef
e
e
d
ba
c
ksg
e
ne
r
a
l
l
yuna
c
c
o
unt
e
df
o
ri
nt
he
i
rme
nt
a
lmode
l
s
.
I
ng
e
ne
r
a
l
,
t
hed
yna
mi
c
so
fas
ys
t
e
me
me
r
g
ef
r
o
mt
hei
nt
e
r
a
c
t
i
o
nsoft
hec
o
mpo
ne
nt
s
i
nt
hes
ys
t
e
m‑C
a
pt
u
r
i
ngt
hos
ef
e
e
d
ba
c
ksi
smo
r
ei
mpo
r
t
a
ntt
ha
nal
o
to
f
de
t
a
i
li
nr
e
pr
e
s
e
nt
i
ngt
hec
o
mpo
ne
n
t
st
he
ms
e
l
ve
s
.
l
l
.Us
ee
xpe
r
tmo
de
l
e
r
s
,
notnovi
c
e
s
.
Whi
l
et
hes
of
t
wa
r
ea
va
i
l
a
bl
ef
o
rmo
de
l
i
ngl
Se
a
s
i
l
yma
s
t
e
r
e
dbyahi
g
h
s
c
hoo
ls
t
u
d
e
nto
rCEO,
mo
de
l
i
ngl
SnotC
Omput
e
rp
r
Og
r
a
mml
ng.
Yo
uc
a
n
no
t
de
ve
l
o
paq
ua
li
t
a
t
i
v
edi
a
g
r
a
ma
ndt
he
nha
ndi
tof
ft
oapr
og
r
a
mme
rf
o
r
c
odi
ngI
nt
oaS
i
mul
a
t
i
o
nmo
d
e
l
.
Mode
l
i
ngr
e
qui
r
e
sad
i
s
c
i
pl
i
ne
da
pp
r
oa
c
h
a
nda
nun
de
r
s
t
a
ndi
ngo
fbus
i
ne
s
s
,
s
ki
l
l
sde
ve
l
o
pe
dt
h
r
o
ug
hs
t
ud
ya
nd
e
xpe
ie
r
nc
e
.
Ge
tt
hee
x
pe
r
ta
s
s
i
s
t
a
nc
eyo
une
e
d.
Us
et
hepr
o
j
e
c
ta
Sa
n
o
ppo
r
t
u
nl
t
yt
Ode
ve
l
o
pt
hes
k
i
l
l
so
fo
t
he
r
so
nt
het
e
a
ma
ndi
nt
hec
l
i
e
n
t
o
r
ga
ni
z
a
t
i
o
n,
1
2｡I
mpl
e
me
nt
at
i
ondoe
snote
ndw
it
has
i
ngl
epr
o
j
e
c
t
.
I
na
l1t
h
r
e
ec
a
s
e
st
hemode
l
i
ngwo
r
kc
o
nt
i
nue
dt
oha
vei
mpa
c
tl
o
nga
f
t
e
r
t
hei
ni
t
i
a
l
pr
o
j
e
c
tWa
so
ve
r
.
Mo
de
l
sa
ndma
na
ge
me
ntf
li
g
hts
i
mul
a
t
o
r
swe
r
e
a
ppl
i
e
dt
os
i
mi
l
a
ri
s
s
ue
si
no
t
he
rs
e
t
t
l
ngS
.
Themode
l
e
r
sde
ve
l
o
pe
de
x
pe
r
t
i
s
e
t
he
ya
ppl
i
e
dt
or
e
l
a
t
e
dpr
o
bl
e
msa
ndc
l
i
e
nt
smo
ve
di
nt
one
wpos
i
t
i
onsa
nd
ne
wo
r
ga
n
i
z
a
t
i
o
ns
,
t
a
ki
ngt
hei
ns
i
g
ht
st
he
yga
i
ne
da
nd,s
o
me
t
i
me
s
,
ane
w
wa
yoft
h
i
n
ki
ng,
wi
t
ht
he
m.
Ⅰ
mpl
e
me
nt
a
t
i
o
ni
sal
o
ng‑
t
e
r
mpr
oc
e
s
so
f
pe
r
s
o
na
l
,
o
r
ga
ni
z
a
t
i
ona
l
,
a
nds
o
c
i
a
lc
ha
nge.
甘言
はき呈
t
,
畠曽
呈
主嘩 苧
i
t
串
∈
e
軍
§
Pe
r
h
a
pst
h
ef
aul
tl
f
ort
hepoori
mpl
e
me
nt
at
i
o
nr
e
c
of
l
df
ormode
l
s
]l
i
e
si
nt
he
or
i
gi
nso
fmana
ge
r
i
almode
l
‑
ma
k
i
n
g‑t
het
r
a
ns
l
at
i
ono
fme
t
ho
dsa
ndpr
i
n‑
C
i
pl
e
so
ft
heph
y
s
i
c
als
c
i
e
nc
e
si
nt
owar
t
i
meo
pe
r
at
i
on
sr
e
s
e
ar
c
h. .I
f
h
y
pot
he
s
i
s
,d
at
a
,an
da
nal
y
s
i
sl
e
adt
opr
oo
fandne
wk
nowl
e
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s7(
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‑
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.
86
TABLE3
1
l
St
epsoHhe
model
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ngpr
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Pa
r
tI Pe
r
s
pe
c
t
i
vea
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o
c
e
s
s
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obl
em Ar
t
i
cul
at
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ect
i
on:Whati
st
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si
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obl
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abl
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abl
esandc
oncept
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t
consi
der
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mehor
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z
on:Howf
ari
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ut
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et
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oot
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obl
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ni
t
i
on(
r
ef
er
encemodes)
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or
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cal
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u
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e?
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s
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or
?
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ocus:For
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at
eadynami
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ai
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dynami
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eedbacks
t
r
uc
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em di
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3.
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4
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ua
t
i
o
ns
,
e
s
pe
c
i
a
l
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s
ys
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e
ms
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ul
t
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hi
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he
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l
i
ngPr
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e
s
s
103
r
e
a
lwor
l
de
xpe
r
i
me
nt
st
ha
tmi
ghtr
e
ve
a
lt
hef
la
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s
i
s
.
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nt
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ma
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Or
l
y ofc
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a
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e
s
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tc
onduc
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hes
ee
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i
me
nt
si
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r
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lwor
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d.
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o,
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r
omt
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e
a
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ys
pe
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e
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z
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l
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or
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ognl
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e
pt
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e
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ntunnot
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lpha
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r
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et
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r
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a
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ur
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omput
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ptnoha
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gume
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i
e
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e
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i
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omee
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oughoutt
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l
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i
a
l
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hes
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ude
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i
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oveyourunde
r
s
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a
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ngoft
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ys
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e
m.
‑
3.
5.
4 1
T
esl
i
ng
Tes
t
i
ngbe
gi
nsa
ss
oo
na
syouwr
i
t
et
hef
i
r
s
te
qua
t
i
o
n.
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r
toft
es
t
i
ng,Ofc
our
s
e,i
s
c
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l
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hes
i
mul
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t
e
dbe
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oroft
hemode
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ot
hea
c
t
ua
lbe
ha
vi
oroft
hes
ys
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t
e
m.
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e
s
t
l
ngI
nvol
ve
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a
rmor
et
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nt
her
e
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i
c
a
t
i
onofhi
s
t
o
r
i
c
a
lbe
ha
vi
o
r
.
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r
y
va
r
i
a
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emus
tc
o
r
r
e
s
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a
ni
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u
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e
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nt
her
e
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lwor
l
d.Eve
r
ye
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tbec
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ke
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o
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ona
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ons
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t
e
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y(
s
oyo
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e
n'
ta
ddi
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ppl
e
sa
nd
or
a
nge
s
)
.
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e
ns
i
t
i
vi
t
yofmode
lbe
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ora
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i
c
yr
e
c
omme
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i
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tbe
a
s
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e
s
s
e
di
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i
ghto
ft
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a
i
nt
yl
na
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S
umpt
l
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bot
hpa
r
a
me
t
r
i
ca
nds
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r
uc
t
ur
a
l
.
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xt
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e
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ons
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i
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vebe
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e
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ve
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nt
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e
a
lwor
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heGDPofas
i
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e
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o?Wha
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nt
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e
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ra
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oul
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e
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ve
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ys
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e
mmus
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t
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r
gy,t
heGDPofamode
r
ne
c
on‑
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a
l
lne
a
r
l
yt
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e
r
o;
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t
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C
eOnebi
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l
i
ont
i
me
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ma
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r
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l
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e
r
o;
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t
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usofc
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e
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ot
s
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oduc
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ons
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ds
oonf
a
l
lt
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e
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obutca
nnotbe
c
omene
ga
t
i
ve.
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ghti
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gi
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t
mode
l
swoul
dne
ve
rf
a
i
lt
opa
s
ss
uc
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oust
e
s
t
s
,
t
ha
tpr
od
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t
i
onwi
t
houte
ne
r
gy,
de
ma
ndf
o
rgoodst
ha
tc
os
tmor
et
ha
nt
het
ot
a
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a
l
t
hofma
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i
ons
,a
ndne
ga
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t
i
vepr
oduc
t
i
onwoul
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ra
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i
s
e.
Butyou'
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o
ng.
Ma
nywi
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yus
e
dmode
l
s
i
ne
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onom
ic
s
,
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yc
hol
ogy
,
ma
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ge
me
nt
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he
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s
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i
pl
i
nesvi
ol
a
t
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s
i
cl
a
wsof
phys
i
c
s
,
e
ve
nt
ho
ught
he
yma
yr
e
pl
i
c
a
t
ehi
s
t
or
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c
a
lbe
ha
vi
orqui
t
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l
l(
S
e
es
e
c
t
i
on
9.
3.
2a
ndc
ha
pt
e
r21
)
.
Ext
r
e
mec
ondi
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i
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t
s
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a
l
ongwi
t
hot
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rt
e
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sofmode
lbe
‑
ha
vi
or
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r
ec
r
i
t
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c
a
lt
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s
c
ove
rt
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nyourmode
la
nds
e
tt
hes
t
a
gef
or
i
mpr
ove
dunde
r
s
t
a
ndi
ng.
‑
3.
5.
5
Po‖Cy Desi
gn and Eva一
uati
on
Onc
eyoua
ndt
h
ec
l
i
e
ntha
vede
ve
l
ope
dc
onf
i
de
nc
ei
nt
hes
t
r
uc
t
ur
ea
ndbe
ha
vi
or
oft
hemode
l
,yo
uc
a
nus
ei
tt
odes
i
gna
nde
va
l
ua
t
epol
i
c
i
e
sf
ori
mpr
ove
me
nt
.
104
P
a
r
t
IP
e
r
s
p
e
c
t
i
v
eandP
r
o
c
e
s
s
Pol
i
c
yde
s
i
g
ni
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hmo
r
et
ha
nc
ha
ng
l
ngt
heva
l
ue
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r
a
me
t
e
r
ss
uc
ha
sat
a
x
S
,
r
a
t
eo
rma
r
kupr
a
t
i
o.
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l
i
c
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s
i
g
ni
nc
l
ud
e
st
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r
e
a
t
i
o
nofe
nt
i
r
e
l
yne
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t
r
a
t
e
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l
e
S
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r
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onr
ul
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o
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o
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e
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o
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t
o
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us
t
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e
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e
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os
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d:
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o
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e
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ome
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o
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nt
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gl
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･
‑
3】
6
SuMMARY
Thi
sc
ha
pt
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rd
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s
c
r
i
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Whi
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t
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ve.
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e
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e
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.
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o
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pe
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i
o
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nt
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l
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e
a
r
l
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us
e
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ve
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e
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ys
‑
t
e
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i
mpl
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f
i
c
a
t
i
o
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;
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t
ho
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l
e
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pos
e
,
yo
uha
venoba
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Thi
spr
o
pe
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yl
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r
e
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que
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t
i
ve
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e
e
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c
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hene
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t
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pe
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t
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c
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pt
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i
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e
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c
kne
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l
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ne
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t
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a
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e
a
t
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e
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i
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t
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r
e
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est
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e
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r
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i
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gur
e4‑
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omee
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ve
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l
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r
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ong
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xa
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es
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t
hel
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ge
rt
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FI
GURE4
‑
2
Exponen
t
i
algr
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h:
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t
r
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c
t
ur
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or
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nt
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ur
e
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h
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t
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al
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o
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at
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i
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uen
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eRat
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he一
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eaddst
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em
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t
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re
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a
mpl
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e
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i
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1x
2 GoaESeeki
ng
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i
t
i
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e
dba
c
kl
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r
a
t
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i
f
y de
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a
t
i
ons
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e
i
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e
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e
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l
a
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t
i
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e
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i
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t
a
t
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ys
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e
mi
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i
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t
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a
t
e.
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ount
e
r
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ur
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e
st
ha
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t
a
t
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ys
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e
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l
.
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lne
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t
i
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e
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c
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hes
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r
uc
t
ur
es
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e4‑
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t
a
t
eof
FI
GURE4
‑
4
Goal
s
eek
i
ng:
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t
r
uc
t
ur
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or
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at
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he
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em
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r
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at
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em)
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r
e
e) D
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t
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c
t
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o
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11
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e
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t
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e
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l
.
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ft
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pa
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ys
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e
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t
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o
汀e
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t
i
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t
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o
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i
a
t
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a
t
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ys
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e
m ba
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k
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l
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ue
a
t
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t
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f
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i
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;
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or
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.
43.
2 Randomness
.
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a
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a
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h(
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1
28
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t
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pe
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st
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ong･
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we
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r
,t
her
a
n
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sac
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nwes
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o
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e
a
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o
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e
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a
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pe
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ha
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or
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c
a
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o
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t
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o
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c
ur
a
c
y
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f
t
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a
c
c
o
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i
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ur
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e
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o
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ome
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r
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omnow.
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i
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c
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a
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ont
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i
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ks
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ne
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r
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mt
he
s
er
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r
‑
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t
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r
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e
,
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f
t
ua
t
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o
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t
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o
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i
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a
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ude
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ore
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et
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c
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Fi
g
u
r
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)
.
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a
i
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a
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s
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l
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rs
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t
a
nt
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o
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mi
c
s
,
howe
ve
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.
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nt
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r
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r
a
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j
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o
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y
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ne
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i
t
emode
so
fbe
ha
vi
ort
ha
to
t
he
r
wi
s
ewoul
dl
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edo
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ma
nt
.
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pe
nd
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um s
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i
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wa
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i
c
t
i
o
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i
s
s
i
pa
t
e
s
i
t
se
ne
r
gy;
e
ve
nt
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l
yt
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u
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o
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,
s
t
r
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ve
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ur
bt
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t
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o
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r
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f
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t
e
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a
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t
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,
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ute
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g
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oms
o
mee
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t
e
ma
ls
o
u
r
c
es
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a
shi
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f
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a
t
e
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mi
c
s(
c
ha
pt
e
r
s
1
8
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d
ee
xa
mpl
e
s
)
.
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nd
omno
i
s
ec
a
na
l
s
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r
e
e
z
es
ys
t
e
mst
ha
ta
r
es
t
uc
k
onl
o
c
a
lo
pt
i
ma,s
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nd
i
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mi
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oane
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g
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r
ho
odwhe
r
et
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mi
c
sa
r
e
q
ui
t
ed
i
fe
r
e
nt
,
a
ndc
a
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e
r
mi
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c
ho
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qua
l
l
ya
t
t
r
a
c
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i
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t
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ys
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e
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t
a
ke
s
,
c
o
nt
r
i
bu
t
i
ngt
opa
t
hde
pe
nd
e
nc
e(
s
e
ec
ha
pt
e
r1
0)
.
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s
edi
s
t
ur
ba
nc
e
sc
a
nbe
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e
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e
da
sr
a
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r
i
a
t
i
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ro
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ve
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o
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Ve
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hee
qua
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i
o
ns
c
a
pt
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r
i
ngt
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e
e
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c
ks
t
r
uc
t
ur
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ft
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ys
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e
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rt
i
me
si
ti
smo
r
ea
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o
p
r
i
a
t
e
t
omo
de
lt
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vi
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e
me
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c
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o
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si
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ys
t
e
m,
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c
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a
s
eno
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‑
a
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ha
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ora
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i
s
e
sf
r
omt
hehe
t
e
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og
e
ne
l
t
yO
ft
hepo
pul
a
t
i
onofa
ge
nt
s
.
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s
er
ol
e
s
f
o
rr
a
ndo
mpe
r
t
ur
ba
t
i
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l
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o
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e
di
nl
a
t
e
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r
s
.
‑
‑
Ch
a
p
t
e
r
4 S
t
r
u
c
t
l
l
r
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n
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h
a
v
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o
ro
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n
a
mi
cS
y
s
t
e
ms
1
29
4.
3.
3 Ch
a
os
l
nr
e
c
e
ntye
a
r
sc
ha
osha
sbe
c
omeaubi
qul
t
OuSbuz
zwor
di
nt
hepopul
a
rpr
e
s
sa
nd
ma
na
ge
me
ntl
i
t
e
r
a
t
ur
e･Booksa
nda
r
t
i
c
l
esbyahos
tofne
wa
gema
na
ge
me
ntgu‑
r
uswa
r
nc
o
mpa
ni
e
st
oH
ma
na
gea
tt
hee
dgeofc
ha
os
Horbeove
r
t
a
ke
nbymor
e
ni
mbl
ec
ompe
t
i
t
o
r
s
.Ext
r
a
va
ga
ntc
l
a
i
msha
vebe
e
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det
ha
tc
ha
osi
sane
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nd
r
a
di
c
a
l
l
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f
f
e
r
e
n
ts
c
i
e
nc
e,
Onewhi
c
hi
sf
unda
me
nt
a
l
l
ynonl
i
ne
a
ra
ndc
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e
x,
One
t
ha
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a
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tbee
xp
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a
i
ne
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t
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omemys
t
e
r
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o
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o
r
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ua
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m
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ha
os
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c
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or
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or
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i
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or
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or
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m.
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i
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i
r
s
tdes
c
r
i
bes
ome
mo
r
ec
om ont
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pe
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DampedOsci
l
l
at
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r
OnS:LocalSt
abi
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mpo
r
t
a
ntc
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r
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c
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cofos
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i
fa
nos
c
i
l
l
a
t
or
ys
ys
t
e
mi
s
pe
r
t
ur
be
do
nc
ea
n
dt
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nl
e
f
tundi
s
t
ur
be
d,
wi
l
lt
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t
ua
t
i
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fs
o,
t
hec
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c
l
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137
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pe
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et
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t
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門
7 2
5.
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2 Labe圭
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t
hef
e
e
d
ba
c
ke
f
f
e
c
tofas
ma
l
l
c
ha
ngei
nt
hev
a
r
i
a
bl
ea
si
tr
e
t
ur
nst
oi
t
s
e
l
f
.
Thepol
a
r
i
t
yoft
hel
oo
pi
st
hes
i
gnof
t
heope
nl
oopg
a
l
n:
‑
Po
l
a
r
i
t
yo
fl
o
o
p‑SGN(
∂
Ⅹ1
0
/
∂
Xi
i
)
(
5‑
1
)
whe
r
eSGN(
)i
st
hes
i
gnum ors
i
gnf
unc
t
i
on,
r
e
t
ur
ni
ng+1i
fi
t
sa
r
gume
nti
spos
i
‑
t
i
vea
nd‑1i
ft
hea
r
g
ume
nti
sne
ga
t
i
ve(
i
ft
heope
nl
oo
pga
i
ni
sz
e
r
o,t
heSGN
f
unc
t
i
on‑0:t
he
r
ei
snol
oop)
A
Theope
nl
oopga
i
ni
sc
a
l
c
ul
a
t
e
dbyt
hec
ha
i
nr
ul
e
f
r
om t
hega
l
nSO
ft
hei
ndi
vi
dua
ll
i
nks
,∂
xl
/
∂
xl
【1
:
SGN(
∂
xl
O
/
∂
x1
7
)‑sGN[
(
∂
xl
O
/
∂
x
n
)
(
∂
X
n
/
∂
x
n
̲1
)
(
∂
X
n
̲1
/
∂
xn
̲2)･･
･
(
∂
x2/
∂
xI
I
)
] (
5‑
2)
146
Fd
GURE5
‑
6
Cal
c
ul
a
t
i
n
gt
h
e
op
en
‑
l
oopgal
n
ofal
o
op
t
h
e
‑
o
p
a
t
a
n
y
p
i
n
t
∴‑
I
も
t 了x
l
O
｢
e
f
.
u
e
n
c
x
L3
)
,
)4
fe
x
Lx
r
°
Pa
r
tI
I ¶)
o
l
sf
o
rS
y
s
t
e
ms
Th
i
n
k
i
n
g
Br
e
ak
t
r
acet
h
:n望change
t
he一
oop
a
x
4
.
PoJ
ar
i
t
y=SGN(
∂
xl
O
/
∂
xl
l
)
0/
∂
xl
l
‑(
∂Ⅹ1
0/
∂Ⅹ4
)
(
∂
Ⅹ4
/
∂
x3
)
(
∂Ⅹ3
/
∂
x2
)
(
∂x2
/
∂x
I
B
)
∂
xl
Si
nc
et
hes
i
g
nofapr
od
uc
ti
st
hepr
o
duc
toft
hes
l
gnS
,l
oo
ppol
a
r
l
t
yl
Sa
l
s
o
g
l
Ve
nby:
SGN(
∂Ⅹ1
0
/
∂
Ⅹ1
Ⅰ
)‑SGN(
∂
Ⅹ1
0
/
∂
X
｡
)*
SGN(
∂
X
｡
/
∂
Xn
ー1
)辛S
GN(
∂
x
｡
̲1
/
∂
X
n
̲2
)
*･
･
･
*SGN(ax2/axi
I
)
(
51
3)
Us
i
ngt
her
i
g
htme
t
hodt
ode
t
e
r
mi
nel
oo
ppo
l
a
r
i
t
ybyt
r
a
c
l
ngt
hee
fe
c
tofa
s
ma
l
lc
ha
ngea
r
oundal
oo
pi
se
qui
va
l
e
ntt
oc
a
l
c
ul
a
t
i
nge
qua
t
i
on(
5‑
3)
.
Eq
ua
t
i
o
n
(
5‑
3
)a
l
s
oe
xpl
a
i
nswhyt
hef
a
s
tme
t
ho
dwo
r
ks
:Si
nc
et
hepr
od
uc
toft
wone
ga
t
i
ve
s
l
g
nSi
sapos
i
t
i
ves
l
gn,
ne
ga
t
i
v
eo
pe
nl
oo
ppo
l
a
r
l
t
yr
e
q
ul
r
e
Sa
nOddn
umbe
ro
fn
e
g‑
a
t
i
vel
i
n
ksi
nt
hel
oo
p｡
Al
lLi
nksShou/
dHav
eUnambi
guousPol
an
'
t
i
es
So
me
t
i
me
spe
o
pl
es
a
yal
i
nkc
a
nbee
i
t
he
rpos
i
t
i
veo
rne
ga
t
i
ve
,
de
pe
ndi
ngo
no
血e
r
pa
r
a
me
t
e
r
soro
nwhe
r
et
hes
ys
t
e
mi
so
pe
r
a
t
l
ng.
Fo
re
xa
mpl
e
,pe
o
pl
eo
f
t
e
nd
r
a
w
血edi
a
g
r
a
mo
nt
hel
e
f
ts
i
deo
fFi
g
u
r
e5‑
7r
e
l
a
t
l
ngaf
i
r
m'
sr
e
ve
nuet
ot
hepr
l
C
eO
f
i
t
spr
o
d
uc
ta
ndt
he
na
r
g
uet
ha
t
t
hel
i
n
kbe
t
we
e
npr
l
C
ea
ndc
o
mpa
nyr
e
ve
nuec
a
nbe
e
i
t
he
rpos
i
t
i
veo
rne
ga
t
i
ve
,de
pe
ndi
ngo
nt
hee
l
a
s
t
i
c
i
t
yOfde
ma
nd.I
fde
ma
ndi
s
%i
nc
r
e
a
s
ei
npr
l
C
e
hi
g
hl
ye
l
a
s
t
i
c
,ahi
g
he
rpr
l
C
eme
a
nsl
e
s
sr
e
ve
nuebe
c
a
us
ea1
%.
Thel
i
nkwoul
dha
vene
ga
t
i
v
epol
a
r
i
t
y.
I
fd
e
‑
c
a
us
e
sde
ma
ndt
of
a
l
lmo
r
et
ha
n1
i
c,
t
he
na1
%i
nc
r
e
a
s
ei
np
r
l
C
eC
a
us
e
sde
ma
ndt
odr
o
pl
e
s
st
ha
n1
%,
ma
ndi
si
ne
l
a
s
t
s
or
e
ve
nue
sr
i
s
e.
Thel
i
nkwo
ul
dbepos
i
t
i
ve
.
I
ta
ppe
a
r
snos
i
ngl
epol
a
r
i
t
yc
a
nbe
a
s
s
l
g
ne
d.
Whe
nyouha
vet
r
ou
bl
ea
s
s
l
g
nl
ngaC
l
e
a
ra
nduna
mbi
guo
uspol
a
r
i
t
yt
oal
i
n
ki
t
us
ua
l
l
yme
a
nst
he
r
ei
smo
r
et
ha
no
nec
a
us
a
l
pa
t
hwa
yc
o
nne
c
t
l
ngt
het
wova
r
i
a
bl
e
s
.
Yo
us
ho
ul
dma
ket
he
s
ed
i
fe
r
e
ntpa
t
hwa
yse
x
pl
i
c
i
ti
nyo
urd
i
a
g
r
a
m.
I
nt
hee
xa
m‑
pl
e
,
pr
i
c
eha
sa
tl
e
a
s
tt
woe
f
f
e
c
t
so
nr
e
v
e
nue:(
1
)i
tde
t
e
r
mi
ne
showmuc
hr
e
v
e
nue
i
sg
e
ne
r
a
t
e
dpe
runi
ts
ol
da
nd(
2)i
ta
f
f
e
c
t
st
henumbe
ro
funi
t
ss
ol
d.
Tha
ti
s
,
Re
ve
‑
nue‑Pr
i
c
e*
Sa
l
e
s
,a
nd(
Uni
t
)Sa
l
e
sde
pe
ndo
nPr
i
c
e(
pr
e
s
uma
bl
yt
hede
ma
nd
c
u
r
vei
sdownwa
r
ds
l
opi
ng:Hi
ghe
rp
r
i
c
e
sr
e
d
uc
es
a
l
e
s
)
.Thepr
o
pe
rd
i
a
g
r
a
mi
s
147
Cha
pt
e
r5 Ca
us
a
lLoo
pDi
a
g
r
a
ms
FI
GURE 5‑
7
Cau
s
a川nk
s
mus
th
a
v
e
unambi
guou
s
p
ol
ar
i
t
y
.
App
ar
en
t
l
y
ambi
gu
ou
s
poL
ar
i
t
i
esusu
al
l
y
i
n
di
c
a
t
et
h
e
pr
es
en
c
eof
mul
t
i
pl
ec
au
s
al
pat
h
wa
y
st
ha
t
s
houl
dbe
r
epr
es
en
t
ed
s
epar
a
t
e一
y
.
Cor
r
ect
l
ncor
r
ect
r
P
r
i
c
e
,(
･o
r‑
)
R
e
v
enue
r
･
R
e
v
e
n
u
e
Pr
i
ce
＼
Jメ +
sa.
es
s
ho
wno
nt
her
i
g
hts
i
deofFi
gu
r
e51
7.
Th
e
r
ei
sno
wnoa
mbi
gui
t
ya
bo
utt
hepol
a
r
1
1
t
yO
fa
n
yo
ft
h
el
i
n
ks
.
Thepr
i
c
ee
l
a
s
t
l
C
l
t
yO
fde
ma
ndde
t
e
r
mi
ne
swhi
c
hc
a
us
a
l
pa
t
hwa
ydo
mi
na
t
e
s
･
I
f
d
e
ma
ndi
sq
ui
t
ei
ns
e
ns
i
t
i
vet
opr
i
c
e(
t
hee
l
a
s
t
i
c
i
t
yo
fd
e
ma
ndi
sl
e
s
st
ha
no
ne
)
,
t
he
n
t
hel
o
we
rpa
t
hi
nFi
g
ur
e5‑
7i
swe
a
k,pr
l
C
er
a
i
s
e
suni
tr
e
ve
nuemo
r
et
ha
ni
tde
‑
c
r
e
a
s
e
ss
a
l
e
s
,a
ndt
hene
te
f
f
e
c
tofa
ni
nc
r
e
a
s
ei
npr
i
c
ei
sa
ni
nc
r
e
a
s
ei
nr
e
ve
nue.
Co
nve
r
s
e
l
y
,i
fc
us
t
o
me
r
sa
r
equi
t
epr
i
c
es
e
ns
i
t
i
ve(
t
hee
l
a
s
t
i
c
i
t
yofde
ma
ndi
s
g
r
e
a
t
e
rt
ha
no
n
e
)
,t
hel
o
we
rpa
t
hdo
mi
na
t
e
s
.
Thei
nc
r
e
a
s
ei
nr
e
ve
n
uepe
runi
ti
s
mo
r
et
ha
no
f
f
s
e
tbyt
hede
c
l
i
nei
nt
hen
umbe
ro
fu
ni
t
ss
ol
d,s
ot
hene
te
fe
c
tofa
pr
i
c
er
i
s
ei
sad
r
o
pl
nr
e
ve
n
ue.
Se
pa
r
a
t
l
ngt
hepa
t
hwa
ysa
l
s
oa
l
l
o
wsyo
ut
os
pe
c
i
f
y
di
f
f
e
r
e
n
td
e
l
a
ys
,
i
fa
ny
,l
ne
a
c
h.
I
nt
hee
xa
mpl
ea
bove
,
t
he
r
ei
sl
i
ke
l
yt
obeal
o
ng
de
l
a
ybe
t
we
e
nac
ha
ng
ei
npr
l
C
ea
ndac
ha
ng
ei
ns
a
l
e
s
,
whi
l
et
he
r
ei
sl
i
t
t
l
eo
rnode
‑
l
a
yl
nt
hee
f
f
e
c
to
fpr
i
c
eo
nr
e
ve
n
ue.
Se
pa
r
a
t
l
ngl
i
nkswi
t
ha
ppa
r
e
nt
l
ya
mbi
g
uo
uspo
l
a
r
i
t
yI
nt
ot
heunde
r
l
y
i
ngmul
‑
t
i
pl
epa
t
hwa
ysi
saf
r
ui
t
f
u
lme
t
hodt
ode
e
pe
nyo
urunde
r
s
t
a
ndi
ngoft
hec
a
us
a
l
e
,
d
e
l
a
ys
,
a
ndbe
ha
vi
oroft
hes
ys
t
e
m.
s
t
r
u
c
t
ur
Enl
Pi
oyeeMo的f
at
i
on
Yo
urc
l
i
e
ntt
e
a
mi
swo
r
r
i
e
da
bo
ute
mpl
o
ye
emot
i
va
t
i
o
na
ndi
sde
ba
t
i
ngt
hebe
s
t
wa
yst
oge
ne
r
a
t
ema
xi
mume
fo
r
tf
r
o
mt
he
i
rpe
o
pl
e･
The
yha
ved
r
a
wnadi
a
g
r
a
m
(
Fi
g
u
r
e5‑
8
)a
n
da
r
ea
r
gui
nga
bo
utt
hepo
l
a
r
i
t
yo
ft
hel
i
n
ks
･
Oneg
r
o
upa
r
g
ue
st
ha
t
t
heg
r
e
a
t
e
rt
hepe
r
f
o
r
ma
nc
es
ho
r
t
f
a
l
l(
t
heg
r
e
a
t
e
rt
hega
pbe
t
we
e
nRe
qui
r
e
dPe
r
f
o
r
ma
nc
ea
ndAc
t
ua
lPe
r
f
o
r
ma
nc
e
)
,
t
heg
r
e
a
t
e
rt
hemo
t
i
va
t
i
ono
fe
mpl
oye
e
swi
l
l
be
.
The
ya
r
guet
ha
tt
hes
e
c
r
e
to
fmot
i
va
t
i
o
ni
st
os
e
ta
gg
r
e
s
s
i
ve
,
e
ve
ni
mpos
s
i
bl
e
goa
l
s(
s
oI
C
a
l
l
e
ds
t
r
e
t
c
ho
b
j
e
c
t
i
ve
s
)t
oe
l
i
c
i
tma
xi
mummo
t
i
va
t
i
ona
nde
fo
r
t
.
The
o
t
he
rg
r
o
u
pa
r
g
ue
st
ha
tt
o
obi
gape
r
f
o
r
ma
nc
es
ho
r
t
f
a
l
ls
i
mpl
yc
a
us
e
sf
r
us
t
r
a
t
i
o
na
s
pe
o
pl
ec
o
nc
l
ud
et
he
r
ei
snoc
ha
nc
et
oa
c
c
o
mpl
i
s
ht
hegoa
l
,
s
ot
hel
i
nkt
oe
mpl
o
ye
e
mo
t
i
va
t
i
o
ns
ho
u
l
dbene
ga
t
i
ve.
Ex
pa
ndt
hed
i
a
g
r
a
mt
or
e
s
o
l
vet
hea
p
pa
r
e
n
tc
o
n
li
f
c
t
byi
nc
o
r
po
r
a
t
i
n
gbot
ht
he
o
r
i
e
s
.
Di
s
c
us
swhi
c
hl
i
n
ksdo
mi
na
t
eunde
rdi
f
f
e
r
e
ntcr
c
ums
t
a
n
c
e
s
.
Ca
nyougi
ves
o
mee
xa
mpl
e
sf
r
o
myou
rowne
x
pe
r
i
e
nc
ewhe
r
et
he
s
e
di
f
f
e
r
e
ntpa
t
hwa
yswe
r
edomi
na
nt
?Howc
a
nama
na
ge
rt
e
l
lwhi
c
hpa
t
hwa
yl
S
l
i
ke
l
yt
odo
mi
n
a
t
ei
na
n
ys
i
t
ua
t
i
on?W
h a
ta
r
et
hei
mpl
i
c
a
t
i
o
nsf
o
rgoa
ls
e
t
t
l
ngl
nO
r
‑
ga
ni
z
a
t
i
ons
?Ac
t
ua
la
ndr
e
q
ui
r
e
dpe
r
f
o
r
ma
nc
ea
r
enote
xoge
no
usbutpa
r
toft
he
f
e
e
d
ba
c
ks
t
r
uc
t
u
r
e
.How doe
smo
t
i
va
t
i
o
nf
e
e
dba
c
kt
ope
r
f
o
r
ma
nc
e
,a
ndho
w
mi
g
hta
c
t
ua
l
pe
r
f
o
r
ma
nc
ea
f
f
e
c
tt
hegoa
l
?I
nd
i
c
a
t
et
he
s
el
oo
psi
nyo
urdi
a
g
r
a
ma
nd
e
x
pl
a
i
nt
he
i
ri
mpo
r
t
a
nc
e
.
i
‑
148
Pa
r
t
I
IT
わ
o
l
sf
o
rS
y
s
t
em s
Th
i
n
k
i
n
g
Act
ual
Per
f
or
mance
＼ヽ 〆 /
/
Requi
r
ed
Per
f
or
mance
/
Per
f
or
mance
Shor
t
f
al
l
Empl
oyee
Mot
i
vat
i
on
5.
2,
4 N･
3meYourLoops
Whe
t
he
ryouus
ec
a
us
a
ldi
a
gr
a
mst
oe
l
i
c
i
tt
heme
nt
a
lmode
l
sofac
l
i
e
ntgr
oupo
rt
o
c
ommuni
c
a
t
et
hef
e
e
dba
c
ks
t
r
uc
t
ur
eofamode
l
,
youwi
l
lof
t
e
nf
i
ndyour
s
e
l
ft
r
yi
ng
t
oke
e
pt
r
a
c
kofmo
r
el
oopst
ha
nyouc
a
nha
ndl
e･
Yourdi
a
gr
a
msc
a
ne
a
s
i
l
yove
r
‑
whe
l
mt
hepe
opl
eyoua
r
et
r
yl
ngt
Or
e
a
c
h.
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l
pyoura
udi
e
nc
ena
vl
ga
t
et
hene
t
‑
wor
kofl
oops
,
i
t
'
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l
pf
ult
ogl
Veea
c
hi
mpor
t
a
ntf
e
e
d
ba
c
kanumbe
ra
ndana
me.
Numbe
r
i
ngt
hel
oo
psRl
,
R2,
B1
,
B2,
a
nds
oonhe
l
psyoura
udi
e
nc
ef
i
nde
a
c
hl
oo
p
a
syoudi
s
c
us
si
t
･
Na
ml
ngt
hel
oo
pshe
l
psyoura
udi
e
nc
eunde
r
s
t
a
ndt
hef
u
nc
t
i
onof
e
a
c
hl
oo
pa
ndpr
ovi
de
sus
e
f
u
ls
hor
t
ha
ndf
ordi
s
c
us
s
i
on.
Thel
a
be
l
st
he
ns
t
a
ndi
nf
わr
ac
ompl
e
xs
e
tofc
a
us
a
ll
i
nks
･
Whe
nwor
ki
ngwi
t
hac
l
i
e
ntg
r
oup,l
t
'
sof
t
e
npos
s
i
‑
bl
et
oge
tt
he
mt
ona
met
hel
oop.
Ma
nyt
i
mes
,
t
he
ywi
l
ls
ugge
s
tawhi
ms
i
c
a
l
phr
a
s
e
o
rs
omeor
ga
ni
z
a
t
i
on‑
s
pe
c
i
f
i
cj
a
r
gonf
o
re
a
c
hl
oop.
Fi
gur
e51
9S
howsac
a
us
a
ldi
a
gr
a
mde
ve
l
ope
dbye
ngi
ne
e
r
sa
ndma
na
ge
r
si
na
wor
ks
hopdes
i
gne
dt
oe
xpl
or
et
hec
a
us
esofl
a
t
ede
l
i
ve
r
yf
ort
he
i
ror
ga
ni
z
a
t
i
on'
s
des
i
gnwor
k｡Thedi
a
gr
a
mr
e
pr
es
e
nt
st
hebe
ha
vi
oroft
hee
ngl
ne
e
r
St
r
yl
ngt
O
c
ompl
e
t
eapr
o
j
e
c
ta
ga
l
nS
tade
a
dl
i
ne.
Thee
ngl
ne
e
r
Sc
ompa
r
et
hewo
r
kr
e
ma
i
ni
ng
t
obedonea
ga
i
ns
tt
het
i
mer
e
ma
i
ni
ngbe
f
or
et
hede
a
dl
i
ne.
Thel
a
r
ge
rt
hega
p,
t
he
mor
eSc
he
dul
ePr
e
s
s
ur
et
he
yf
e
e
l
･Whe
ns
c
he
dul
epr
es
s
ur
ebui
l
dsup,e
ngl
ne
e
r
S
ha
ves
e
ve
r
a
lc
hoi
c
e
s
.
Fi
r
s
t
,
t
he
yc
a
nwor
kove
r
t
i
meJns
t
e
a
doft
heno
r
ma
l50hour
s
pe
rwe
e
k,
t
he
yc
a
nc
omet
owor
ke
a
r
l
y,
s
ki
pl
unc
h,s
t
a
yl
a
t
e
,
a
ndwo
r
kt
hr
ought
he
we
e
ke
nd.Bybur
ni
ngt
heMi
dni
ghtOi
l
,t
he
yi
nc
r
e
a
s
et
her
a
t
ea
twhi
c
ht
he
yc
om‑
pl
e
t
et
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i
rt
a
s
ks
,c
utt
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c
kl
ogofwor
k,a
ndr
e
l
i
e
vet
hes
c
he
dul
epr
es
s
ur
e(
ba
l
‑
a
nc
i
ngl
oopB1
)
.
Howe
ve
r
,
i
ft
hewor
kwe
e
ks
t
a
yst
oohi
ght
ool
ong,
f
a
t
i
g
ues
e
t
si
n
a
ndpr
oduc
t
i
vl
t
yS
uf
f
e
r
s
･Aspr
oduc
t
i
vi
t
yf
a
l
l
s
,t
het
a
s
kc
ompl
e
t
i
onr
a
t
edr
ops
,
whi
c
hi
nc
r
e
a
s
ess
c
he
dul
epr
es
s
ur
ea
ndl
e
a
dst
os
t
i
l
ll
onge
rhour
s
:t
her
e
i
nf
o
r
c
i
ng
Bur
no
utl
oopRll
i
mi
t
st
hee
fe
c
t
i
ve
ne
s
sofove
r
t
i
me.
Anot
he
rwa
yt
oc
ompl
e
t
et
he
wor
kf
a
s
t
e
ri
st
or
e
duc
et
het
i
mes
pe
ntonea
c
ht
a
s
k.Spe
ndi
ngl
es
st
i
meone
a
c
h
t
a
s
kboos
t
st
henumbe
roft
a
s
ksdonepe
rhour(
pr
oduc
t
i
vi
t
y)a
ndr
e
l
i
e
vess
c
he
dul
e
pr
e
s
s
ur
e,
t
husc
l
os
i
ngt
heba
l
a
nc
l
ngl
oopB2･
Di
s
c
us
s
i
o
noft
hena
mef
ort
hi
sl
oop
wa
shea
t
e
d.Thema
na
ge
r
sc
l
a
i
me
dt
hee
ngl
ne
e
r
Sa
l
wa
ysgol
d‑
pl
a
t
e
dt
he
i
rwor
k;
t
he
yf
e
l
ts
c
he
dul
epr
es
s
ur
ewa
sne
e
de
dt
os
que
e
z
eoutwa
s
t
ea
ndge
tt
hee
ngi
ne
e
r
s
t
of
oc
usont
hej
ob.
Thee
ngl
ne
e
r
Sa
r
gue
dt
ha
ts
c
he
dul
epr
es
s
u
r
eo
f
t
e
nr
os
es
ohi
gh
t
ha
tt
he
yha
dnoc
hoi
c
ebutt
oc
utba
c
kqua
l
i
t
ya
s
s
ur
a
nc
ea
nds
ki
pdoc
ume
nt
a
t
i
on
149
Ch
a
p
t
e
r5 Ca
u
s
a
l
Lo
o
pDi
a
g
r
a
ms
FI
GURE 5
‑
9
T
i
m
Rm
a
n
m
g
r
+
e
Nameandnumb
er
yourl
oopst
o
i
ncr
easedi
agr
am
cf
ar
i
t
yandpr
ovi
de
memor
abl
el
abel
s
f
ori
mpor
t
an
t
f
eedback
s.
e
W
o
r
k
R
e
m
a
m
n
g
苛
≡
て
二
M
i
d
n
i
g
h
tと
Schedub
e
Pr
es
sur
e
F
a
t
i
g
u
e
C
o
m
p
一
e
t
i
o
n
R
a
t
＼
二
色
鼻
+
o
u
t
c
t
i
v
i
t
y
i
u
r
n
一
一.
P
r
o
d
u
oft
he
i
rwor
k.
The
yc
a
l
l
e
di
tt
heCo
me
rCut
t
i
ngl
oo
p(
B2)
.
Thee
ngi
ne
e
r
st
he
na
ト
gue
dt
ha
tc
or
ne
rc
ut
t
i
ngl
SS
e
l
f
‑
de
f
e
a
t
l
ngbe
c
a
us
ei
ti
nc
r
e
a
s
est
hee
r
r
o
rr
a
t
e
,
whi
c
h
l
e
a
dst
or
e
wor
ka
ndl
owe
rpr
oduc
t
i
vl
t
yi
nt
hel
ongr
un:"
Ha
s
t
ema
ke
swa
s
t
e
,
Ht
he
y
s
a
i
d,a
nds
c
he
d
ul
epr
e
s
s
ur
er
i
s
e
sf
u
r
t
he
r
,l
e
a
di
ngt
os
t
i
l
lmo
r
epr
es
s
ur
et
oc
utc
or
‑
ne
r
s(
l
oopR2)
.
Thef
ul
lmode
li
nc
l
ude
dma
nymor
el
oops(
s
e
c
t
i
on5.
1pr
ovi
de
sac
l
os
e
l
yr
e
‑
l
a
t
e
de
xa
mpl
e;s
e
ea
l
s
os
e
c
t
i
on2.
3)
.
Thena
me
sgi
ve
nt
ot
hel
oopsbyonegr
oup
(
e
ngi
ne
e
r
s
)c
ommuni
c
a
t
e
dt
he
i
ra
t
t
i
t
ude
sa
ndt
her
a
t
i
ona
l
ef
ort
he
i
rbe
ha
vi
ort
ot
he
ma
na
ge
r
si
nac
l
ea
ra
ndc
ompe
l
l
i
ngwa
y.
Thec
onve
r
s
a
t
i
ondi
dnotde
ge
ne
r
a
t
ei
nt
o
a
dhomi
ne
ma
r
gume
nt
sbe
t
we
e
nma
na
ge
r
ss
hout
i
ngt
ha
te
ngi
ne
e
r
sJ
us
tne
e
dt
o
ha
vet
he
i
rbut
t
sk
i
c
ke
da
nde
ngl
ne
e
r
Sgr
l
pl
ngt
ha
tge
t
t
l
ngpr
omot
e
dt
oma
na
ge
me
nt
t
ur
nsyourbr
a
i
nt
ol
f
T
e
r
t
i
l
i
z
e
r
]
‑t
hemodeofdi
s
c
our
s
emos
tc
ommoni
nt
heo
r
ga
‑
ni
z
a
t
i
onpr
l
Ort
Ot
hei
nt
e
r
ve
nt
i
on.
Pa
r
t
i
c
l
pa
nt
SS
OOnbe
ga
nt
ot
a
l
ka
boutt
heBur
nout
Loopki
c
ki
ngl
na
ndt
henonl
i
ne
a
rr
e
l
a
t
i
o
ns
hi
psbe
t
we
e
ns
c
he
dul
epr
e
s
s
ur
e,ove
r
t
i
me,
f
a
t
i
gue,a
nde
r
r
or
s
.
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mesf
ort
hel
oopsma
dei
te
a
s
yt
or
e
f
e
rt
oc
ompl
e
x
c
hunksoff
e
e
d
ba
c
ks
t
r
uc
t
ur
e.
Thec
onc
e
pt
sc
a
pt
ur
e
dbyt
hena
me
sgr
a
dua
l
l
ybe
ga
n
t
oe
nt
e
rt
heme
nt
a
lmode
l
sa
ndde
c
i
s
i
onma
ki
ngoft
hema
na
ge
r
sa
nde
ngl
ne
e
r
Si
n
t
heor
ga
ni
za
t
i
o
na
ndl
e
dt
oc
ha
ngei
nde
e
pl
yI
ng
r
a
i
ne
dbe
ha
vi
or
s
.
‑
150
Pa
r
tH To
ol
sf
o
rSys
t
e
msTh
i
n
ki
ng
5.
2.
5 ;
ndi
cat
e!
n
l
POr
t
antDe!
ays弓
1
1G訓J
Saきし
.
∃
nks
De
l
a
ysa
r
ec
r
i
t
i
c
a
li
nc
r
e
a
t
l
ngd
y
na
mi
c
s
.
De
l
a
ysgl
VeS
ys
t
e
msi
ne
r
t
i
a
,
c
a
nc
r
e
a
t
es
c
i
l
l
a
t
i
ons
,a
nda
r
eo
f
t
e
nr
e
s
pons
i
bl
ef
o
rt
r
a
de
‑
of
f
sbe
t
we
e
nt
hes
ho
r
t
‑a
n
dl
o
n
g‑
un
r
e
fe
c
t
sofpol
i
c
i
e
s
.
Yo
u
rc
a
us
a
ld
i
a
g
r
a
mss
ho
ul
di
nc
l
ud
ede
l
a
yst
ha
ta
r
ei
mpo
r
t
a
n
t
t
ot
hed
yna
mi
chy
po
t
he
s
i
so
rs
i
g
ni
f
i
c
a
ntr
e
l
a
t
i
vet
oyo
urt
i
meho
r
i
z
o
n.
Ass
ho
wni
n
c
ha
pt
e
rll
,
de
l
a
ysa
l
wa
ysi
nvo
l
v
es
t
oc
ka
ndf
l
ows
t
r
uc
t
u
r
e
s
.So
me
t
i
me
si
ti
si
m‑
po
r
t
a
ntt
os
ho
wt
he
s
es
t
r
uc
t
u
r
e
se
x
pl
i
c
i
t
l
yl
nyo
urd
i
a
gr
a
ms
.
Of
t
e
n,
ho
we
ve
r
,
i
ti
s
s
uf
f
i
c
i
e
ntt
oi
nd
i
c
a
t
et
hep
r
e
s
e
nc
eofat
i
mede
l
a
yl
naC
a
us
a
ll
i
n
kwi
t
ho
ute
x
pl
i
c
‑
i
t
l
ys
howi
ngt
hes
t
o
c
ka
ndf
lows
t
uc
r
t
ur
e.
Fi
gur
e5‑
1
0s
howsho
wt
i
med
e
l
a
ysa
r
e
r
e
pr
e
s
e
nt
e
di
nc
a
us
a
ldi
a
g
r
a
ms
.
Whe
nt
hepr
l
C
eO
fagoo
dr
i
s
e
s
,
s
uppl
ywi
l
lt
e
ndt
oi
nc
r
e
a
s
e
,
b
uto
f
t
e
no
n
l
ya
f
‑
t
e
rs
i
g
ni
f
i
c
a
ntd
e
l
a
yswh
i
l
ene
wc
a
pa
c
i
t
yl
SO
r
de
r
e
da
ndbui
l
ta
ndwhi
l
ene
wf
i
r
ms
e
nt
e
rt
hema
r
ke
t
.
Se
ea
l
s
ot
het
i
mede
l
a
ysi
nt
heBu
r
no
uta
ndHa
s
t
eMa
ke
sWa
s
t
e
l
oo
psi
nFi
g
ur
e5‑
9｡
o
‑
Exampl
e:Ener
gyDemand
Ther
e
s
po
ns
eofga
s
o
l
i
nes
a
l
e
st
opr
l
C
ei
nvo
l
ve
sl
o
ngd
e
l
a
ys
.
I
nt
hes
ho
r
t
r
un,
ga
s
o‑
l
i
nede
ma
ndi
squl
t
ei
ne
l
a
s
t
i
c:
i
fpr
i
c
e
sr
i
s
e
,
pe
o
pl
ec
a
nc
utd
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5.
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ONCASESTUDY:
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ol
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e
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pe
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pe
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s
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o
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t
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c
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t
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t
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ri
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f
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r
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a
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t
l
yc
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r
e
d.
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r
i
a
bl
e
swi
t
ht
hes
a
meuni
t
sa
r
epl
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t
t
e
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a
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re
xa
mpl
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,
t
he
a
s
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l
g
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ta
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t
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r
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s
ks
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t
t
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.
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udo
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tne
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nt
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e
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l
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a
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ors
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oc
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gur
e6‑
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ome
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oc
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‑
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NTEGRAL(
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NTEGRAL(
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n
lo
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o
c
k
t
｡
)
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6‑
3)
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pr
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nt
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t
t
hes
t
oc
ka
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c
umul
a
t
e
si
t
si
nf
lowsl
es
si
t
sout
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f
,
be
gi
nni
ngWi
t
h
kt
o
･
a
ni
ni
t
i
a
lva
lueo
fSt
oc
6.
1.
3 TheCont
r
i
but
i
onofSt
ockst
oDynami
cs
St
oc
ksa
rec
r
i
t
i
c
a
li
nge
ne
r
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t
i
ngt
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mi
csofs
ys
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e
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ort
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e
a
s
ons
(
Ma
s
s1
98
0)
:
1
. St
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ac
t
e
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i
z
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at
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e
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ae
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.
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oc
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mt
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e
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o
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t
.
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t
a
t
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r
c
r
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f
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i
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on,
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ude
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l
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t
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e
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m ca
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or
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i
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s
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ma
t
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ona
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e
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t
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ns
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al
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f
s
.
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oc
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ys
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e
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i
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y
.
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oc
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c
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umul
a
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.
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t
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c
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nt
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l
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c
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9
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et
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oc
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l
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om
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a
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i
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e
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i
e
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sa
r
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t
oc
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tc
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r
a
c
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r
i
z
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nt
a
l
s
t
a
t
es
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i
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r
s
i
s
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me
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t
l
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aa
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i
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ude
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or
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i
e
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r
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i
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ra
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n,
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i
e
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t
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r
s
e
r
vi
c
er
e
ma
i
nse
ve
ni
ft
he
y'
vei
mpr
ove
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196
Pa
r
tI
IT
o
o
l
sf
o
rS
y
s
t
em s
Th
i
n
k
i
n
g
3. St
oc
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ret
hes
our
c
eofde
l
ays
.
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lde
l
a
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nvol
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t
oc
ks
･
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l
a
yl
Sapr
oc
e
s
sWhos
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putl
a
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t
s
l
nPut
.
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e
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t
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puta
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c
umul
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a
li
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ei
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ra
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i
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e
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e
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ve
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l
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e
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e
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e
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umul
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t
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l
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umpSby1
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ys
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me
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ome
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t
e.
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s
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ons
･
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n
a
dd
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ea
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er
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ys
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r
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be
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t
r
uc
t
ur
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s
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i
l
.
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ksde
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oupl
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e
soff
l
owandc
r
e
at
edi
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e
qui
l
i
br
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um dyna
mi
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s
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oc
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e
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t
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fows
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t
l
ng
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lowst
f
oapr
oc
es
st
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f
f
e
r
.
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ne
qui
l
i
br
i
um,
t
het
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a
l
i
nf
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t
oc
ke
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l
si
t
st
ot
a
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f
ot
hel
e
ve
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t
oc
ki
s
unc
ha
ngl
ng.
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ve
r
,
i
nf
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ua
l
l
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fe
rbe
ca
us
et
he
ya
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e
o
f
t
e
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me
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r
e
ntde
c
i
s
i
onpr
oc
e
s
s
e
s
.
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s
e
qui
l
i
br
i
um i
st
her
ul
e
r
a
t
he
rt
ha
nt
hee
xc
e
pt
l
On.
Ch
a
p
t
e
r
6 S
t
o
c
k
s
a
n
dF
l
o
ws
197
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o
d
uc
t
i
ono
fgr
a
i
nde
pe
ndso
nt
heye
a
r
l
yc
yc
l
eofpl
a
nt
l
nga
nd
ha
r
v
e
s
t
,
a
l
o
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t
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e
di
c
t
a
bl
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t
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r
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a
t
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o
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a
t
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s
t
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t
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o
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umpt
l
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i
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pe
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hs
t
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ea
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et
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e
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t
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ng
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i
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o
d
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t
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o
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umpt
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on
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umu
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ks
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o
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n
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o
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c
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t
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i
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e
rt
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f
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od
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mpt
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on,
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umpt
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e
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r
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ve
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s
.
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e
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c
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t
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o
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ft
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e
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r
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c
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ul
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e
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ha
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e
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t
s
.
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l
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ve
r
a
get
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o
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i
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umpt
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(
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n
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e
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sf
a
r
me
r
sr
e
s
po
ndt
oma
r
ke
tp
r
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c
e
sa
ndi
nve
nt
o
r
yc
ondi
t
i
ons
i
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t
e
r
mi
n
i
ngho
wmuc
ht
opl
a
nt
,
a
nda
sc
o
ns
ume
r
sa
d
j
us
tc
o
ns
umpt
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on
i
nr
e
s
pons
et
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l
C
e
Sa
nda
va
i
l
a
bi
l
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t
y
,
p
r
od
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t
i
o
na
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o
ns
umpt
l
O
na
r
e
r
a
r
e
l
ye
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ua
l
.
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ne
v
e
rt
woc
o
upl
e
da
c
t
i
v
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t
i
e
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r
ec
o
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l
l
e
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i
fe
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e
ntde
c
i
s
i
o
n
ma
ke
r
s
,
i
nv
o
l
vedi
f
f
e
r
e
ntr
e
s
o
ur
c
e
s
,
a
nda
r
es
u
b
j
e
c
tt
odi
f
f
e
r
e
ntr
a
ndo
m
s
ho
c
ks
,ab
u
fe
ro
rs
t
oc
kbe
t
we
e
nt
he
mmus
te
x
i
s
t
,
a
c
c
u
mul
a
t
i
ngt
he
d
i
f
f
e
r
e
nc
e
.
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he
s
es
t
oc
ksva
r
y
,
i
nf
o
r
ma
t
i
o
na
bo
utt
hes
i
z
eoft
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f
e
r
wi
l
lf
e
e
dba
c
ki
nva
r
i
o
uswa
yst
oi
n
lue
f
nc
et
hei
nf
lo
wsa
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lows
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.
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utnott
her
a
t
ea
twhi
c
hy
o
ua
r
es
pe
ndi
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tnow.
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ft
i
mes
t
o
ppe
d,
i
two
ul
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s
i
bl
et
ode
t
e
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mi
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nt
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o
mpa
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r
i
c
e
o
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e
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a
l
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hene
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a
t
eo
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nt
o
r
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her
a
t
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la
t
i
o
ni
n
ma
t
e
r
i
a
l
spr
l
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e
S
.
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ps
hott
e
s
ta
p
pl
i
e
sa
l
s
ot
ol
e
s
st
a
ngi
bl
es
t
oc
ks
･
Thepl
a
nt
ma
na
ge
r
'
Se
x
pe
c
t
a
t
i
ono
ft
hec
us
t
o
me
ro
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d
e
rr
a
t
ea
ta
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ns
t
a
ntO
rpe
r
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e
p
t
l
O
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ft
he
s
i
z
eo
fi
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nt
o
r
ya
r
es
t
o
c
ks
,
e
ve
nt
ho
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ht
he
ya
r
eme
nt
a
la
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i
c
a
ls
t
o
c
ks
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ps
ho
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fpe
o
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sme
nt
a
ls
t
a
t
e
s
,
ho
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ve
r
,
d
oe
snoti
ndi
c
a
t
eho
wf
a
s
tt
h
e
ya
r
e
r
e
v
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l
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rbe
l
i
e
f
s
.
,
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g
ur
e61
3l
i
s
t
ss
o
mec
o
mmo
nc
o
nc
e
pt
sa
ndi
de
nt
i
f
i
e
st
he
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ss
t
oc
kso
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l
o
ws
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ho
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i
rs
t
oc
ka
ndf
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t
r
uc
t
u
r
ea
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t
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ur
e
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pul
a
t
i
o
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oy‑
e
e
s
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es
t
r
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g
ht
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o
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wa
r
d.
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st
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l
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eOfapr
oduc
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i
c
e
s
t
.
c
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c
t
e
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z
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a
t
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e
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nt
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umus
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ype
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r
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t
e
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e
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ne
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nt
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li
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ha
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j
us
ta
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o
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ge
t
si
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ni
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nt
o
r
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e
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li
ti
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uc
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no
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nt
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r
sc
a
l
l
e
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r
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d
i
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i
‑
do
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s
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f
e
rr
e
ma
i
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ne
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c
t
na
n
c
i
a
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ke
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oc
ks
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l
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i
ts
ho ve
l
t
e
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r
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i
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r
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nt
i
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st
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c
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e
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us
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ome
ro
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t
ef
o
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od
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t
oc
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e
a
r
l
y
,
hea
t
c
‑
t
ua
lc
us
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ome
ro
r
de
rr
a
t
ei
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wo
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us
t
ome
ro
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r
sa
c
c
umul
a
t
e
si
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c
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ogo
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t
oc
ko
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i
l
l
e
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de
r
sun
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i
lt
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o
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uc
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nbed
e
l
i
ve
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e
d.
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we
ve
r
,
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ma
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ge
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l
i
e
fa
bo
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t
ea
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c
hc
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o
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ro
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sa
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o
c
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i
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t
a
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eo
ft
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ys
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e
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nt
hi
sc
a
s
eame
nt
a
ls
t
a
t
e.
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nek
nowst
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r
uec
u
r
r
e
nt
o
rf
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u
r
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r
de
rr
a
t
e.
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hema
na
ge
r
'
sbe
l
i
e
fa
bo
uto
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d
e
r
sc
a
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l
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O
e
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i
f
‑
f
e
rf
r
o
mt
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r
ueo
r
d
e
rr
a
t
e(
t
hebe
l
i
e
fc
a
nbewr
o
ng)
.
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na
ge
r
s
'
be
l
i
e
f
sa
bo
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he
c
us
t
ome
ro
r
de
rr
a
t
ewi
l
lt
e
ndt
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e
ma
i
nt
hes
a
meun
t
i
lt
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ybe
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o
mea
wa
r
eo
fne
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i
nf
o
r
ma
t
i
o
na
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t
et
he
i
rbe
l
i
e
f
s
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ngei
nEx
pe
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t
e
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rRa
t
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st
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r
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t
ea
twhi
c
ht
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e
l
i
e
fi
su
pda
t
e
d.
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et
heuni
t
sofme
a
s
u
r
ef
o
rt
hee
x
pe
c
t
e
do
r
‑
de
rr
a
t
e.
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ket
hea
c
t
ua
lo
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rr
a
t
e
,
t
hee
xp
e
c
t
e
do
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t
ei
sme
a
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ur
e
di
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d
ge
t
s
pe
rt
i
mepe
r
i
od(
s
a
ywe
e
ks
)
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t
so
fme
a
s
u
r
ef
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her
a
t
ea
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c
ht
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e
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e
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a
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us
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o
me
ro
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e
r
si
su
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t
e
da
r
e(
wi
d
ge
t
s
/
we
e
k)
/
we
e
k
r
t
‑
l
i
200
Ft
GURE6‑
3
Exampl
esof
s
t
ock
sandf
l
ows
wi
t
ht
hei
runi
t
sof
measur
e
Thech
oi
ceoft
i
me
uni
tf
ort
hef
l
ows
(
e.
g.
,
days,
week
s,
year
s)i
sar
bi
t
r
ar
y
bu
tmu
s
tbe
c
onsi
s
t
en
twi
t
hi
na
.
sl
ngl
emodel
Pa
r
tH To
ol
sf
o
rSys
t
e
msTh
i
n
k
i
ng
て
｢
7
由一 .
ー
Popu
一
at
i
on
て
｢
7
血
,
.
.
̲
(
peopl
e
/
year
)
Repayment
(
S
/
year
)
Bor
r
owi
ng
(
S
/
ye
ar
)
Rat
eofPr
i
ce
Change
(
S
/
uni
t
)
(
S
/
unWyear
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Changei
n
Expect
ed
Or
derRat
e
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ed
Cust
omer
1
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der
s
(
wi
dget
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/
week
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(
wI
'
dget
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/
weeJ
dweek
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et
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tt
her
a
t
eofpr
l
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eC
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ha
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nt
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c
t
e
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de
rr
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t
ec
a
n
bepos
i
t
i
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t
i
ve(
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ic
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ma
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or
e
c
a
s
t
sc
a
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i
s
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a
l
l
)
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nt
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oroutofas
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oc
kc
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nbee
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t
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rpos
i
t
i
veorne
ga
t
i
ve｡Thedi
r
e
c
t
i
onoft
hea
r
r
ow
(
poi
nt
i
ngi
nt
oo
ro
uto
fas
t
oc
k)de
f
i
nest
hes
i
gnc
onve
nt
i
onf
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rt
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nf
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a
ddst
ot
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t
oc
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nt
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i
t
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ve;
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ft
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sne
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t
i
vei
ts
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r
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c
t
sf
r
om
t
hes
t
oc
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nt
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ut
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f
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i
t
i
ve,
t
hef
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r
a
c
t
sf
r
o
mt
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t
oc
k.
Ch
a
p
t
e
r6 S
t
o
c
k
sa
n
dF
l
o
ws
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!
dent
i
f
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ngSt
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ows
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et
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ol
l
owi
ngc
o
nc
e
pt
sS
t
oc
kso
rf
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a
was
t
oc
ka
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pf
ore
a
c
h
a
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vet
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i
ru
ni
t
so
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s
ur
e.
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nt
e
r
e
s
tr
a
t
e(
e.
g.
,
t
hepr
i
mei
nt
e
r
es
tr
a
t
eorr
a
t
eont
he30‑
ye
a
rUSTr
e
a
s
ur
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bond)
.
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mpl
oy
me
ntr
a
t
e.
Hi
nt
:Wha
tdoe
st
hewo
r
d"
r
a
t
e
"me
a
ni
nt
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es
e
t
t
i
ngs
?
6.
2.
3 Conser
vat
i
onofMat
er
i
a一i
n
St
ockandFl
owNet
wor
ks
Ama
j
orS
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r
e
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hes
t
oc
ka
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e
pr
es
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nt
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t
i
oni
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l
e
a
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s
t
i
nc
t
i
onbe
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t
we
e
nt
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i
c
a
lf
lowst
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oug
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hes
t
oc
ka
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t
wor
ka
ndt
hei
nf
or
ma
t
i
on
f
e
e
dba
c
kst
ha
tc
ou
pl
et
hes
t
oc
kst
ot
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l
os
et
hel
oo
psi
nt
hes
ys
t
e
m.
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ont
e
nt
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hes
t
oc
ka
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wo
r
ksa
r
ec
o
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e
r
v
e
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nt
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e
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et
ha
ti
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e
mse
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t
e
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l
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t
oc
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e
ma
int
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r
eunt
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lt
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yf
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.
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na
ni
t
e
mf
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r
omones
t
oc
k
t
oa
not
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rt
hef
i
r
s
ts
t
oc
kl
os
e
spr
e
c
i
s
e
l
ya
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ha
st
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e
c
ondga
i
ns
.
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i
de
rt
he
s
t
oc
ka
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lOws
t
r
uc
t
ur
er
e
pr
e
s
e
nt
i
ngt
hea
c
c
ount
sr
e
c
e
i
va
bl
eofaf
i
r
m(
Fi
gur
e
6‑
4)
･
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t
oc
ko
fr
e
c
e
i
va
bl
e
si
si
nc
r
e
a
s
e
dbybi
l
l
i
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c
r
e
a
s
e
dbypa
yme
nt
s
r
e
c
e
i
ve
da
ndbyde
f
a
ul
t
s
.
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lOwofbi
l
l
i
ngsi
sc
ons
e
r
ve
di
nt
hes
e
ns
et
ha
tonc
ea
c
us
t
ome
ri
sbi
l
l
e
d,
t
hei
nvo
i
c
er
e
ma
i
I
I
Si
nt
hes
t
oc
kofr
e
c
e
i
va
bl
e
sunt
i
li
te
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i
c
i
t
l
y
lowsoutwhe
f
nt
her
e
c
e
i
va
bl
e
sde
pa
r
t
me
ntr
e
c
or
dst
hec
us
t
o
me
r
'
spa
yme
ntora
c
‑
knowl
e
dgest
ha
t
t
hec
us
t
ome
rha
sde
f
a
ul
t
e
da
ndwr
i
t
e
sof
ft
hea
c
c
ount
.
I
nc
o
nt
r
a
s
t
,
i
nf
わr
ma
t
i
ona
bo
utt
hes
t
oc
kofr
e
c
e
i
va
bl
esi
snotc
ons
e
r
ve
d.Thec
or
po
r
a
t
ea
c
‑
C
ount
l
ngS
ys
t
e
m ma
kest
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l
ueof也er
e
c
e
i
va
bl
e
ss
t
oc
ka
va
i
l
a
bl
et
oma
ny
hr
t
oughoutt
heo
r
ga
ni
z
a
t
i
on.
Ac
c
e
s
s
l
nga
ndus
i
ngt
hi
si
nf
or
ma
t
i
ondoe
snotus
ei
t
upo
rma
kei
tuna
va
i
l
a
bl
et
oot
he
r
s
.
Not
ea
l
s
ot
ha
twhi
l
et
heuni
t
sofa
c
count
spa
ya
bl
ea
r
edol
l
a
r
sa
nd也ebュ
l
l
i
ng,
pa
yme
nt
,a
ndde
f
a
ul
tmowsa
r
eme
a
s
ur
e
di
ndol
l
a
r
spe
rt
i
mepe
r
i
od,
t
hec
ont
e
nt
sof
血es
t
oc
ka
r
enota
c
t
ua
l
l
ydo
l
l
a
r
s
.
Ra
t
he
r
,
t
hec
ont
e
ntoft
her
e
c
e
i
va
bl
ess
t
oc
ki
si
n‑
f
o
r
ma
t
i
on,s
pe
c
i
f
i
c
a
l
l
y
,al
e
dge
ro
rda
t
a
ba
s
ec
ons
i
s
t
l
ngOfr
e
c
o
r
dso
fi
nvoi
c
e
sout
‑
s
t
a
ndi
ng.
Tos
e
ewhy
,
i
ma
gi
net
r
yi
ngt
Oe
xc
ha
ngeyourf
i
r
m'
ss
t
oc
kofr
e
c
e
i
va
bl
es
f
orc
a
s
h‑youc
a
ns
e
l
lt
he
mt
oac
ol
l
e
c
t
i
ona
ge
nc
y,
butonl
yf
o
rmuc
hl
e
s
st
ha
n1
00
c
e
r
l
t
SOn払edol
l
a
r
.
Thought
hec
ont
e
nt
soft
hes
t
oc
kofr
e
c
e
i
va
bl
esi
si
nf
or
ma
t
i
on
a
ndnotama
t
e
r
i
a
lqua
nt
i
t
y,l
ti
sne
ve
r
t
he
l
es
sc
ons
e
r
ve
d‑youc
a
nnots
e
l
lagl
Ve
n
s
t
oc
kofr
e
c
e
i
va
bl
e
smo
r
et
ha
no
nc
e(
notl
e
ga
l
l
y,
a
nywa
y)
.
St
oc
ksc
a
nr
e
pr
e
s
e
nti
n‑
f
or
ma
t
i
ona
swe
l
la
smor
et
a
ng
ibl
equa
nt
i
t
i
ess
uc
ha
spe
o
pl
e,
mone
y
,a
ndma
t
e
r
i
‑
a
l
s
.St
oc
ksc
a
na
l
s
or
e
pr
es
e
nti
nt
a
ngi
bl
eva
r
i
a
bl
esi
nc
l
udi
ngps
yc
hol
ogi
c
a
ls
t
a
t
es
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pe
r
c
e
pt
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c
t
a
t
i
onss
uc
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se
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oye
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l
e
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hee
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pe
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t
e
dr
a
t
eofi
nf
la
‑
t
i
on,orpe
r
c
e
i
ve
di
nve
nt
or
y.
202
I
IT
o
o
l
sf
o
rS
y
s
t
em s
Th
i
n
k
i
n
g
Pa
r
t
Fl
GURE6‑
4
St
ockandf
l
ow
s
t
r
u
c
t
ur
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ac
c
oun
t
s
r
ec
ei
vabl
e
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t
er
i
al
f
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ow‑
l
ngt
hr
ought
he
net
wor
ki
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t
u
aH
y
i
nf
or
mat
i
onabou
t
cus
t
omer
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he
amoun
t
st
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yowe,
Thi
si
n
f
or
mat
i
oni
s
c
on
ser
ved
‑t
he
onl
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ecei
v
abl
e,
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ebi
l
l
ed,
i
sr
emovedf
r
om
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hes
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ocki
si
ft
he
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omerpaysor
def
aul
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sJn
f
or
ma‑
t
i
onabou
tt
hesi
z
e
andcomposi
t
i
onof
acc
oun
t
spayab一
e,
howev
er
,
canbe
madeavai
l
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e
t
hr
oughou
tt
he
s
ys
t
eman
di
s
notdepl
et
edb
y
u
Sa
ge･
‑
6.
2.
堵 S竜
aモ
e‑
Deモ
er
mi
medSysを
ems
Thet
he
or
yofdyna
mi
cs
ys
t
e
mst
a
kesas
t
a
t
e
‑
d
e
t
e
r
mi
ne
ds
ys
t
e
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t
a
t
eva
r
i
a
bl
e
a
ppr
oa
c
h.
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ywa
yas
t
oc
kc
a
nc
ha
ngei
svi
ai
t
si
nf
lowsa
ndout
lows
f
.
I
nt
um,
hes
t
t
oc
ksde
t
e
r
mi
net
hef
lows(
Fi
g
ur
e6‑
5)
.
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t
e
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he
r
e
f
or
eco
ns
i
s
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t
wor
ksofs
t
oc
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i
nke
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o
r
ma
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i
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e
e
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c
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r
omt
hes
t
oc
kst
ot
her
a
t
e
s(
Fi
g
ur
e6‑
6)
.
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howni
nt
hef
i
g
ur
e,
t
he
de
t
e
mi
na
nt
sofr
a
t
e
si
nc
l
udea
nyc
ons
t
a
nt
sa
nde
xoge
no
usva
r
i
a
bl
es
･
Thes
et
ooa
r
e
s
t
oc
ks
.Cons
t
a
nt
sa
r
es
t
a
t
eva
r
i
a
bl
e
st
ha
tc
ha
nges
os
l
owl
yt
he
ya
r
ec
ons
i
de
r
e
dt
o
bec
ons
t
a
ntove
rt
het
i
mehor
i
z
onofi
nt
e
r
e
s
ti
nt
hemode
l
.
Exoge
nousva
r
i
a
bl
esa
r
e
s
t
oc
ksyouha
vec
hos
e
nnott
omode
le
xpl
i
c
i
t
l
ya
nda
r
et
he
r
e
f
or
eout
s
i
det
hemode
l
bounda
r
y.
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re
xa
mpl
e,i
namode
loft
hede
ma
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orane
wvi
de
oga
me,t
hes
i
z
e
oft
hepot
e
nt
i
a
lma
r
ke
tmi
ghtde
pe
ndont
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pul
a
t
i
onbe
t
we
e
n,s
a
y,a
ge
s4a
nd
20･
Thepr
oduc
tl
i
f
ec
yc
l
ewi
l
ll
a
s
taf
e
wye
a
r
sa
tmos
t
.
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rt
hi
st
i
mehor
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z
ont
he
popul
a
t
i
onbe
t
we
e
n4a
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rsofa
a
gei
snotl
i
ke
l
yt
oc
ha
nges
i
gni
f
i
c
a
nt
l
ya
nd
c
a
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e
a
s
ona
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s
s
ume
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ons
t
a
nt
.
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t
e
r
na
t
i
ve
l
y,youc
oul
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lt
hes
t
oc
kof
c
hi
l
dr
e
ni
nt
het
a
r
ge
ta
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oupasa
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xoge
no
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a
bl
e,us
l
ngC
e
ns
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t
aa
nd
pr
qe
c
t
i
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oes
t
i
ma
t
ei
t
sva
l
ues
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ki
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a
t
i
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t
a
ntore
xoge
nousi
sa
c
‑
c
e
pt
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bl
ei
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a
s
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i
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et
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ea
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i
c
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e
e
d
ba
c
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e
ns
a
l
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de
o
ga
me
sa
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r
t
h,de
a
t
h,ormi
gr
a
t
i
onr
a
t
e
s
.
6.
2,
5 Aux百
日
岳
aF
yVar
i
ab日
es
Asi
l
l
us
t
r
a
t
e
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gur
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ma
t
he
ma
t
i
c
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lde
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c
r
l
pt
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e
mr
e
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r
e
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yt
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s
t
oc
ksa
ndt
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i
rr
a
t
esofc
ha
nge.
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a
s
eofc
ommuni
c
a
t
i
ona
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l
a
r
i
t
y,
howe
ve
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,
i
ti
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t
e
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l
pf
ult
ode
f
i
nei
nt
e
r
me
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a
t
eorau
xi
l
i
ar
yV
ar
i
abl
e
s
.
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l
i
a
r
i
e
sc
ons
i
s
t
off
u
nc
t
i
onsofs
t
oc
ks(
a
ndco
ns
t
a
nt
sore
xoge
nousi
nput
s
)
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xa
mpl
e,
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t
i
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e
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es
e
ntt
hene
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r
t
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t
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f
r
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c
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t
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t
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r
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t
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e
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i
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oodpe
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a
pl
t
a.
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e
f
ts
i
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gur
e61
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howst
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r
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ur
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qua
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a
p
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e
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t
o
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n
dF
l
o
ws
FI
GURE6
‑
5
St
a
t
e‑
det
er
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ed
s
ys
t
ems
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t
emse
vol
v
e
b
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n
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om
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a
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y
s
t
emt
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l
owst
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atal
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er
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hes
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a
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es
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t
:
Cau
s
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賢
√
‑
/
l
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l
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epr
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en
t
a
t
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whi
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t
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k
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o
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at
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a
t
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heSyst
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s
t
r
u
c
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ur
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t
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a
t
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t
em)
e
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.
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ght
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t
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t
oc
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c
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ur
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e
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umul
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a
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o
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i
a
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va
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a
c
t
i
o
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t
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ene
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oc
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t
i
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s
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ya
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ef
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nc
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i
o
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o
c
ks(
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nde
xoge
no
usi
n
put
s
,
i
nt
hi
sc
a
s
eFood
)
.
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pu‑
c
or
r
es
p
on
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ot
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e l
a
t
i
o
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r
t
i
c
i
pa
t
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e
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ba
c
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i
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r
e
s
t
oc
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t
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e
s
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s
on,
l
owe
r
map.
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et
f
r
a
c
t
i
o
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lne
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r
t
hr
a
t
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,
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e
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t
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me
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t
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f
l
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n
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d
l
o
o
p
p
o
o
ft
h
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t
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ki
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a
r
i
t
i
e
s
.
f
un
c
t
i
ono
ft
he
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ux
i
l
i
a
r
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e
sc
a
na
l
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l
i
mi
na
t
e
da
ndt
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lr
e
d
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t
oc
ki
t
s
el
f
,
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o
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i
s
t
i
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t
oc
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ndt
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i
rf
lows
･
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ubs
t
i
t
ut
i
ngt
hee
qua
t
i
on
c
l
os
l
n
gt
h
e
f
o
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p
i
t
ai
n
t
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q
ua
t
i
o
nf
o
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a
c
t
i
o
na
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r
t
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t
ea
ndt
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ns
ubs
it
t
ut
l
f
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c
kl
oop.
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l
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her
e
s
ul
ti
n
t
ot
hee
q
ua
t
i
o
nf
o
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tBi
r
h Ra
t
t
e
,
yo
uc
a
ne
l
i
mi
na
t
et
hea
u
xi
l
i
a
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e
s
r
e
d
uc
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d
e
lt
oo
newi
t
ho
nl
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tBi
r
t
hRa
t
ea
ndPo
pul
a
t
i
o
n.
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i
ghts
i
de
o
fFi
gu
r
e6‑
7s
h
o
wst
hi
smode
la
ndi
t
se
q
ua
t
i
ons
.
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ug
ht
hemo
d
e
li
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t
he
ma
t
‑
i
c
a
l
l
ye
q
ul
Va
l
e
n
tt
ot
hemode
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t
ha
uxi
l
i
a
r
i
e
s
,
i
ti
sha
r
d
e
rt
oe
x
pl
a
i
n,
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e
r
s
t
a
nd,
a
ndmodi
f
y
.
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t
et
ha
ti
nt
her
e
duc
e
df
o
r
mmode
l
po
pul
a
t
i
o
ne
n
t
e
r
st
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q
ua
t
i
o
nf
o
r
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her
a
t
eo
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n
g
eo
fpo
pul
a
t
i
o
ni
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t
ht
henume
r
a
t
o
ra
ndde
no
mi
na
t
o
r
.The
,
po
l
a
r
l
t
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ft
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a
us
a
ll
i
n
kbe
t
we
e
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pul
a
t
i
o
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r
t
hsi
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uous
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et
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t
i
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ht
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e
e
dba
c
kl
oo
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nvo
l
vi
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pul
a
t
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on
a
ndbi
r
t
hs
.
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o
c
e
s
so
fc
r
e
a
t
l
ngt
her
e
duc
e
df
o
r
mmode
lbys
u
bs
t
i
t
ut
i
ono
fi
nt
e
r
me
d
i
‑
l
.
a
t
eva
r
i
a
bl
e
si
n
t
ot
he
i
rr
a
t
e
si
sage
ne
r
a
lo
nea
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a
nbec
a
血e
do
uto
na
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we
ve
r
,t
heus
eofa
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l
i
a
r
yva
r
i
a
bl
e
si
sc
r
i
t
i
c
a
lt
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f
f
e
c
t
i
vemode
l
i
ng.I
de
a
l
l
y
,
e
a
c
he
q
ua
t
i
o
ni
nyo
u
rmode
l
ss
houl
dr
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pr
e
s
e
nto
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i
ni
de
a
.
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n'
tt
r
yt
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c
o
no‑
mi
z
eo
nt
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q
ua
t
i
onsbywr
l
t
l
ngl
o
ngo
ne
st
ha
te
mbe
dmul
t
i
pl
ec
on‑
c
e
pt
s
･
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s
el
o
n
ge
q
ua
t
i
o
nswi
l
lbeha
r
dl
bro
t
he
r
st
or
e
a
da
ndu
nde
r
s
t
a
nd.
The
y
wi
l
lbeha
r
df
oryout
ounde
r
s
t
a
nd.Fi
na
l
l
y
,e
qua
t
i
o
nswi
t
hmul
t
i
pl
ec
ompone
nt
s
a
ndi
de
a
sa
r
eha
r
dt
oc
ha
ngei
fyo
urc
l
i
e
ntdi
s
a
g
r
e
e
swi
t
ho
neo
ft
hei
d
e
a
s
.
‑
204
P
a
r
t
I
IT
o
o
l
sf
o
rS
y
s
t
e
msTh
i
n
k
i
n
g
F】
GURE6
‑
6
Ne
t
wor
k
sofs
t
ock
sandf
l
owsar
ec
oupl
edb
yi
n
f
or
ma
t
i
onf
eedback
St
ock
sac
cumul
at
et
hei
rr
at
esoff
l
ow;i
n
f
or
mat
i
onabou
tt
h
es
t
ock
sf
eedsbackt
oal
t
ert
her
at
es,
cl
osl
ngt
hel
oopsi
nt
hes
y
s
t
em.
Cons
t
an
t
sar
es
t
ock
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n
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yt
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edexpl
l
Ci
t
l
y;
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ogenousvar
i
abl
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es
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oc
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t
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det
hemodel
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ar
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e.
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omer
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umul
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ome
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ks
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n
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l
o
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t
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ar
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ac
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ock
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at
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om Popul
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ect
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/
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c
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hedi
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ms
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opof
Fi
gur
e6‑
8.
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yc
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Te
C
t
l
yr
e
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ognl
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et
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ome
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epr
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om t
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oc
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ome
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s
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l
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t
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s
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e
as
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oc
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a
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f
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vi
t
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e
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s
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ome
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us
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s
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sope
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o
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ome
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t
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om t
hes
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oc
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20
6
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GURE6‑
8
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ock
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hr
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r
t
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ect
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oc
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ow
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e
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2.
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nuousTi
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ows
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ur
ebe
ha
vi
or
a
lf
e
e
dba
c
kss
uc
h
a
st
hef
e
e
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c
kf
r
omt
hel
e
ngt
hoft
hel
i
net
ot
her
a
t
ea
twhi
c
hpe
opl
eJ
Ol
nt
hel
i
ne.
Somemode
l
sa
ndag
r
e
a
tma
nyoft
het
he
or
e
msi
nque
ul
ngt
he
o
r
ya
s
s
umet
ha
tt
he
r
a
t
eofa
r
r
i
va
l
st
oaq
ue
ues
uc
ha
st
hec
he
c
koutl
i
nei
se
xoge
nous
.
Pe
opl
ea
c
t
ua
l
l
y
c
hoos
et
oe
nt
e
ral
i
neba
s
e
doni
t
sl
e
ngt
h(
mor
epr
e
c
i
s
e
l
y
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he
i
re
s
t
i
ma
t
eofe
x‑
pe
c
t
e
dwa
i
t
i
ngt
i
me
)
.
Al
o
ngl
i
newi
l
lc
a
us
epe
opl
et
os
wi
t
c
ht
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r
,
de
f
e
rt
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i
r
s
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Oal
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s
sc
r
owde
dt
i
meofda
y
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ve
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oadi
fe
r
e
nts
t
or
e.
Suc
hb
al
k
‑
mgc
r
e
a
t
e
sapowe
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f
ulne
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t
i
vef
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e
d
ba
c
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oo
p:
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onge
rt
hel
i
ne,
hes
t
ma
l
l
e
rt
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a
r
r
i
va
lr
a
t
e.
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t
t
l
ngS
uc
hf
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e
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c
kpr
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es
s
e
sf
r
omyo
urmode
li
nt
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nt
e
r
e
s
t
sof
a
na
l
yt
i
c
a
lt
r
a
c
t
a
bi
l
i
t
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ogr
a
mml
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OnVe
ni
e
nc
ewi
l
lof
t
e
nl
e
a
dt
oaf
a
t
a
lma
w
i
nyoura
na
l
ys
t
sa
ndpol
i
c
yc
onc
l
us
i
ons
.
Ch
a
p
t
e
r6 S
t
o
c
k
sa
n
dF
l
o
ws
209
6.
2.
10 Pr
ocessPoi
nt
:
Por
t
r
ay岳
ngSt
ocksandFF
owsi
nPr
act
i
ce
Ea
c
hoft
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t
o
c
ka
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e
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e
s
e
nt
a
t
i
onsi
nFi
gur
e6‑
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t
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t
ht
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t
oc
ka
nd
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a
gr
a
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nt
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le
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a
i
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e
c
i
s
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l
yt
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s
a
mei
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or
ma
t
i
o
n.
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ya
r
ee
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c
t
l
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Va
l
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nt
.
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c
hs
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et
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pe
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pe
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hemode
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o
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a
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m we
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t
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i
c
s
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ts
e
ve
r
a
lc
o
mme
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t
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e
a
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ke
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r
t
s
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t
SS
t
oc
ka
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l
ows
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r
uc
t
ur
ea
st
a
nksa
ndpi
pes
･
Wha
ti
fyou
rc
l
i
e
nt
sha
vee
ve
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e
s
st
e
c
hni
c
a
lt
r
a
i
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ha
nt
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ec
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mi
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a
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om‑
pa
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xe
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ut
i
ve
s
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t
ht
ubme
t
a
phori
sof
t
e
nus
e
dt
ogoode
fe
c
t
,a
si
l
l
us
t
r
a
t
e
d
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a
s
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o
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l
el
e
a
s
i
ng(
s
e
eFi
gur
e2.
4)
A
Wha
ti
ft
hes
t
o
c
ksa
ndf
lowsi
n
yourmode
lare
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ta
st
a
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ea
sba
r
r
e
l
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s
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tc
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e
a
t
l
veJna
ma
na
ge
me
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li
gh
ts
i
mul
a
t
o
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a
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l
a
i
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ng(
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m1
98
9;Di
e
hl
1
994)
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t
e
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sa
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r
i
vi
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e
pr
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e
nt
e
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t
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o
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wc
l
a
i
ms
t
ot
hes
t
oc
k ofunre
s
ol
ve
dc
l
a
i
ms
.
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t
t
e
r
sc
ont
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i
ni
ngC
he
c
ksf
lo
we
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tt
ot
hec
us
‑
t
ome
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sa
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e
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t
l
e
d.
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c
onsofpe
o
pl
er
e
pr
e
s
e
nt
e
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o
c
ka
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uc
r
‑
t
ur
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l
a
i
m sadjus
t
e
r
s(
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gur
e61
9)
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r
t
i
c
i
pa
nt
si
nwor
ks
ho
psus
i
ngt
hemode
l
we
r
ea
bl
eto unde
rs
t
andt
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ys
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e
ms
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r
uc
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ur
emuc
hbe
t
t
e
rt
ha
ni
ft
h
emo
r
ea
bs
t
r
a
c
t
s
ymbol
shad be
e
n us
e
d.
Ia
m notre
com m e
nd
i
ngt
ha
tyouke
e
pt
hee
qua
t
i
onsors
t
o
c
ka
n
df
l
owdi
a
l
gr
a
mshi
dde
nf
rom yourc
l
i
e
nt
･
Ne
ve
rhi
deyourmode
lf
r
omac
u
r
i
o
uscl
i
e
nt
･
You
s
houl
da
l
wayslook forandc
r
e
a
t
eo
ppor
t
uni
t
i
esf
orc
l
i
e
ntt
e
a
mme
mb
e
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st
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ea
n
r
mor
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boutthem ode
l
i
ng p
r
oc
e
s
s
;yous
houl
da
l
wa
ysbepr
e
pa
r
e
dt
oe
x
p
l
a
i
nt
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wor
ki
ngsofyourm ode
l.
‑
a
‑
210
I
IT
o
o
l
s
f
o
rS
y
s
t
e
msTh
i
n
k
i
n
g
P
a
r
t
FI
GURE6
‑
9
St
o
ck
san
df
l
o
ws
o
fc
J
ai
msand
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l
ai
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u
s
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er
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l
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n
Sur
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e
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omp
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撃薄
≡
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Ad
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Re
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e
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a
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ms
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t
s
t
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r
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o
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r
≡
牽
Cl
ai
ms
Se
t
t
日
e
d
Sour
ce.
I
Ki
m 1989.
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l
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a
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i
o
nt
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t
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ma
t
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c
a
l
l
ys
o
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c
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t
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e
ra
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l
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c
a
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e
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nt
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t
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t
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o
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e
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a
na
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oa
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i
s
e:s
omec
l
i
e
nt
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‑
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e
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dbywha
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r
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t
t
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st
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o
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s
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nt
a
t
i
ono
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t
oc
ka
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low di
a
g
r
a
mso
r
e
v
e
ne
q
ua
t
i
o
ns
･
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l
wa
ys
,
yo
umus
tge
tt
okno
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urc
l
i
e
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e
pl
ya
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a
r
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yl
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e
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i
ngpr
o
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e
s
s
.
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na
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l
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ac
a
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o
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t
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e
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NG STOeKSAND FLOWS
63.
1 WhenSh⑳uはPea
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St
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ow St
r
uct
ur
e?
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us
a
ld
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a
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r
a
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t
houts
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ngt
hes
t
oc
ka
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lo
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t
r
uc
t
ur
eo
fa
s
ys
t
e
m芋
Or
,
a
ss
h
owni
nFi
g
ur
e6‑
8ー
he
yc
a
ni
nc
l
u
det
hes
t
o
c
ka
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l
o
ws
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r
l
J
p
C
t
lr
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e
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ndwhe
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pl
i
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t
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y.
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nc
l
udet
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t
o
c
ka
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t
r
uc
t
ur
yo
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t
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n
e
r
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l
l
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yous
houl
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nc
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udes
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ka
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lo
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,de
ve
l
o
pas
t
oc
ka
ndf
lowma
pf
o
rt
hega
s
ol
i
nedi
s
t
r
i
but
i
ons
ys
t
e
m･
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u
ne
e
dno
tc
o
ns
i
de
rt
hee
nt
i
r
es
u
ppl
yc
ha
i
nf
o
rga
s
ol
i
nebutc
a
nf
oc
uso
nr
e
t
a
i
ld
i
s
‑
t
r
i
but
i
o
n.
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urdi
a
g
r
a
ms
ho
ul
dbe
g
i
nwi
t
ht
hef
lOwofga
s
ol
i
net
os
e
r
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c
es
t
a
t
i
o
ns
,
t
he
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e
pr
e
s
e
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hes
t
oc
ka
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t
r
uc
t
ur
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t
ss
ubs
e
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t
o
r
a
ge
,s
a
l
e
,a
nd
e
ve
nt
ua
lc
ombus
t
i
o
n.
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eyo
u'
vema
ppe
dt
hes
t
o
c
ka
ndf
lows
t
r
u
c
t
ur
e
,
i
de
nt
i
f
yt
hei
nf
o
ma
r
t
i
o
ni
n‑
pu
t
st
ot
her
a
t
e
soff
lo
wi
nyo
urdi
a
g
r
a
m･
As
s
umet
ha
tt
her
a
t
ea
twhi
c
hga
s
ol
i
nei
s
de
l
i
ve
r
e
dt
os
e
r
vi
c
es
t
a
t
i
o
nsi
se
xo
ge
no
us
.
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de
nt
i
f
yi
ngt
hei
nf
o
r
ma
t
i
o
ni
n
pu
t
st
O
Ch
a
p
t
e
r
6 S
t
o
c
k
sa
n
dF
l
o
ws
213
tef
h
lo
wsi
nyo
u
rs
t
oc
ka
ndf
lowma
p,yo
uwi
l
lbec
l
os
l
ngs
omef
e
e
d
ba
c
kl
oo
ps
,
l
o
o
pswhi
c
hs
h
o
ul
dhe
l
pe
xpl
a
i
nwh
yt
hes
ho
r
t
a
g
eo
c
c
ur
r
e
da
nda
ns
we
rt
heq
ue
s
‑
t
i
o
n,Whe
r
edi
dt
hega
sg
o?Bes
ur
et
oa
s
kho
wi
nd
i
vi
d
ua
ldr
i
ve
r
swoul
dl
e
a
r
n
a
bo
utt
hes
ho
r
t
a
gea
ndwha
tt
he
i
rbe
ha
vi
o
rwo
ul
dt
he
nbe.
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na
l
l
y,us
l
ngyo
urdi
a
g
r
a
m,a
s
s
e
s
st
hel
i
ke
l
ye
fe
c
t
i
ve
ne
s
soft
hema
xi
mum
p
ur
c
ha
s
ea
ndo
d
d
/
e
ve
npol
i
c
i
e
s
.
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i
c
i
e
soft
hi
st
y
pehe
l
pe
a
s
et
hes
ho
r
t
a
geo
r
ma
kei
two
r
s
e
?Why?Wha
tpol
i
c
ywoul
dyo
ur
e
c
o
mme
ndt
oe
a
s
et
hes
ho
r
t
a
g
e?
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pl
a
i
nwhyyo
ut
hi
nkyourpol
i
c
ywoul
dbee
fe
c
t
i
vei
nt
e
r
msoft
hes
t
oc
k
/
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f
w
a
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e
e
d
ba
c
ks
t
r
u
c
t
u
r
eo
ft
hes
ys
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e
m.
6.
3.
2 Aggr
egat
i
Qn喜
nSt
ockandFl
ow Mappi
r
!
g
Thea
bi
l
i
t
yt
oma
pt
hes
t
oc
ksa
ndf
lowsi
nas
ys
t
e
mi
sc
r
i
t
i
c
a
lt
oe
fe
c
t
i
vemod
e
l
‑
i
ng.
Us
ua
l
l
yi
ti
swi
s
et
oi
de
nt
i
f
yt
hema
i
ns
t
oc
ksi
nas
ys
t
e
ma
ndt
he
nt
hef
lo
ws
t
ha
ta
l
t
e
rt
hos
es
t
oc
ks
.Yo
umus
ts
e
l
e
c
ta
na
ppr
o
p
r
l
a
t
el
e
ve
lofa
gg
r
e
ga
t
i
ona
nd
bo
unda
r
yf
o
rt
he
s
es
t
oc
ka
ndf
lowma
ps
.Thel
e
ve
lo
fa
gg
r
e
ga
t
i
onr
e
f
e
r
st
ot
he
n
umbe
ro
fi
nt
e
r
na
lc
a
t
e
go
r
i
e
so
rs
t
oc
ksr
e
pr
e
s
e
nt
e
d.
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r
yr
e
f
e
r
st
ohow
f
a
ru
ps
t
r
e
a
ma
nddowns
t
r
e
a
mo
nec
ho
os
e
st
or
e
pr
e
s
e
ntt
hef
lOwso
fma
t
e
r
i
a
l
sa
nd
l
.
o
t
he
rq
ua
nt
i
t
i
e
si
nt
hemode
Toi
l
l
us
t
r
a
t
e
,c
ons
i
d
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rt
hema
nu
f
a
c
t
u
r
i
ngPr
o
c
e
s
sdi
s
c
us
s
e
da
bovei
nwhi
c
h
ma
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e
r
i
a
lf
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ompr
od
uc
t
i
o
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t
a
r
t
st
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o
ug
hWI
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o
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yt
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ni
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o
r
y
a
ndf
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na
l
l
ys
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p
me
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ot
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us
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ome
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.
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lt
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o
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t
s
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ompo
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a
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t
e
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ge
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ri
nt
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oc
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ug
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hef
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r
m
ma
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a
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r
yt
e
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ft
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us
a
ndso
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t
oc
kk
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e
pi
nguni
t
s
)
,
t
he
s
ei
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v
i
dua
li
t
e
ms
a
r
ea
l
la
gg
r
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ga
t
e
di
nt
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i
ngl
es
t
oc
ko
ff
i
n
i
s
h
e
di
nve
nt
or
y.
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nypur
pos
e
st
he
a
g
g
r
e
ga
t
epi
c
t
u
r
ei
ss
uf
f
i
c
i
e
nt
.
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we
ve
r
,
t
hemod
e
l
pur
pos
emi
g
htr
e
q
ui
r
emo
r
ed
e
‑
t
a
i
l
.
I
ft
hepu
r
pos
ei
nvol
ve
dac
l
os
e
rl
oo
ka
tt
hema
nuf
a
c
t
ur
l
ngpr
o
c
e
s
s
,
yo
uC
O
ul
d
,
d
i
s
a
gg
r
e
ga
t
et
h
es
t
oc
kofwo
r
ki
npr
oc
e
s
ss
e
r
i
a
l
l
yt
or
e
pr
e
s
e
ntt
hedi
fe
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nts
t
a
g
e
s
s
uc
ha
spa
r
tf
a
b
r
i
c
a
t
i
on,
a
s
s
e
mbl
y
,
a
ndt
e
s
t
i
ng(
Fi
g
ur
e6‑
1
1
)
･
Thes
umo
ft
het
hr
e
ei
nt
e
r
me
d
i
a
t
es
t
o
c
ksi
st
het
ot
a
lwo
r
ki
npr
oc
e
s
si
nve
n
t
o
r
y,
bu
tno
wt
hemo
d
e
lt
r
a
c
kst
hr
o
ug
h
puta
taf
i
ne
rl
e
v
e
lofr
e
s
ol
ut
i
o
na
ndc
a
nr
e
p
r
e
s
e
nt
mo
r
epo
t
e
nt
i
a
l
bo
t
t
l
e
ne
c
ksi
nt
hepr
o
d
uc
t
i
o
npr
o
c
e
s
s
.
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t
et
ha
ti
nbo
t
ht
heo
r
l
g
l
na
l
,
a
g
g
r
e
ga
t
edi
a
g
r
a
ma
ndi
nt
hi
smo
r
ed
e
t
a
i
l
e
dd
i
a
g
r
a
mt
he
r
ei
snopr
o
vi
s
i
onf
o
rr
e
‑
wo
r
ko
rs
c
r
a
p.
Al
luni
t
ss
t
a
r
t
e
da
r
ee
ve
nt
ua
l
l
yc
o
mpl
e
t
e
d
‑t
hef
low ofwi
dge
t
s
t
hr
o
ug
ht
hes
ys
t
e
mi
sc
o
ns
e
r
ve
d.
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t
ea
l
s
ot
ha
ta
sma
t
e
r
i
a
lf
lo
wst
hr
o
ug
ht
hes
ys
t
e
mi
ti
st
r
a
ns
f
o
r
me
df
r
o
mpa
r
t
st
of
i
ni
s
he
dp
r
o
d
uc
t
.
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i
nt
a
i
nc
ons
i
s
t
e
ntuni
t
s
ofme
a
s
ur
ewemi
ghtme
a
s
ur
epa
r
t
si
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te
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Va
l
e
nt
s
‑t
ha
ti
s
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t
'
s
wo
r
t
ho
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r
t
s
.
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fne
c
e
s
s
a
r
yf
o
rt
hepu
r
pos
e
,
yo
uc
a
nf
ur
t
he
rd
i
s
a
gg
r
e
ga
t
et
hes
t
oc
k
a
n
df
lows
t
r
u
c
t
u
r
e.
‑
Modi
f
yi
ngSt
ockandFI
ow Maps
1
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i
f
yt
h
edi
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g
r
a
mi
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ur
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l
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e
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e
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e
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21
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saggr
egat
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om abuf
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r
.
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a
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e
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ga
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e
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ort
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a
br
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howt
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onha
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oc
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e
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o
br
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kdownt
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t
a
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o
ughout
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ows
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om t
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ef
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t
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t
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e
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e
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s
mi
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si
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g
ur
e6‑
1
2.
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r
ea
r
enowt
hr
e
edi
s
t
i
nc
ts
t
oc
ka
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ha
i
ns
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a
c
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o
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ne
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C
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s
i
s
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s
s
e
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r
s
.
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c
a
us
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21
6
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Th
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乱3 Gui
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1993)
.
40
60
Ti
meuni
t
s
80
1
00
222
P
a
r
t
I
IT
わ
o
l
s
f
o
rS
y
s
t
e
ms
Th
i
n
k
i
n
g
S.
3.
5 Set
t
i
ngt
heMode一Boundar
y:
"
ChaHengi
r
f
gt
heC萱
ouds"
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ppl
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hes
t
o
c
ka
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lOw s
t
r
uc
t
ur
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fas
ys
t
e
mi
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ve
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mpo
r
t
a
ntd
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c
i
s
i
ons
a
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a
r
yoft
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de
l
･
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nr
e
a
l
i
t
y
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e
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i
a
l
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pe
o
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a
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o
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o
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ome
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ogos
ome
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l
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a
bl
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umus
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r
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et
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s
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s
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nks
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e
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nt
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nt
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e
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g
ur
e61
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ur
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g
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1
9
93,
p.1
3
2)
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e
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uds
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ig
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o
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nt
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e
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nt
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ys
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i
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i
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o
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l
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t
r
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･
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o
ra
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o
n,
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i
ni
s
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n‑
ve
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o
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s(
Fi
g
ur
e6‑
1
6)
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a
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t
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ur
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rt
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li
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e
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c
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t
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a
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nt
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us
t
o
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to
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nt
s
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nc
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ll
e
ng
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rt
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o
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rt
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r
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ma
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e
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t
s
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nt
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s
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t
u
r
e
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rt
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ge
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s
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a
l
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r
so
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d
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rmo
r
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omt
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t
yc
utba
c
k.
Fi
g
ur
e6‑
1
7e
xpa
ndst
hemode
lbounda
r
yt
oc
a
pt
u
r
et
he
s
ee
fe
c
t
s
.
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ona
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i
t
i
e
s
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up
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e
r
s
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ma
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Themode
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e
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e
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e
n
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s
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ga
ni
z
a
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ur
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f
a
c
t
ur
e
r
s
,
a
ndde
a
l
e
r
s
.
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n
ve
nt
o
r
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r
t
she
l
dbyt
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st
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ut
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:as
t
oc
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pl
i
c
i
t
.Thes
uppl
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st
hes
a
meba
s
i
cs
t
r
uc
t
ur
f
i
ni
s
he
di
nve
nt
or
ya
ndas
t
oc
ko
fwo
r
ki
npr
oc
e
s
s
.
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hes
hi
pme
nte
nd,
ma
nuf
a
c
‑
lowi
n
t
od
e
a
l
e
rs
t
o
c
ks
,
a
l
l
o
wl
t
u
r
e
rs
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pme
nt
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o
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rd
i
s
a
ppe
a
ri
n
t
oas
i
nkbutf
hed
e
a
l
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ri
nv
e
nt
o
r
ya
nds
a
l
e
s
l
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ut
Omode
lt
hepur
c
ha
s
er
a
t
ea
saf
u
nc
t
i
onoft
t
oc
us
t
ome
r
s
.
‑
223
t
o
c
k
sa
n
dF
l
o
ws
Ch
a
p
t
e
r6 S
Fl
GURE6
･
16
I
ni
t
i
al
s
t
ockand
f
l
owmapf
or
t
heau
t
omobi
一
e
i
ndus
t
r
y
,
showl
n
g
t
hemodel
boundar
y
Thes
our
cesan
d
si
nk
sf
ort
he
f
l
owst
hr
ough
t
hes
y
s
t
emar
e
assumedt
obe
i
nf
i
ni
t
eandcan
havenoi
mpac
ton
t
hed
yn
ami
cs･
Sour
ce.
･
Unl
i
mi
t
ed
suppl
yof ヽ
Absor
pt
i
on
Capaci
t
y
J
Youc
oul
da
nds
houl
dc
ont
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nuet
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ha
l
l
e
nget
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yoft
hemode
l
.
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mode
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owsyout
or
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ror
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y
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sc
a
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ne
c
k
a
nds
t
a
r
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ut
omo
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l
epr
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t
i
on･
Butnowt
hes
uppl
i
e
r
sa
r
eas
s
ume
dt
oha
veun‑
l
i
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t
e
dpa
r
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a
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sa
va
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l
a
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l
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t
y.I
st
hi
sa
ppr
o
pr
i
a
t
e?I
tde
pe
ndsont
he
mode
lpur
pos
e.
Yo
uc
oul
dc
ont
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nuet
oe
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ndt
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st
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r
s
,
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ndt
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lyour
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tt
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a
l
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a
r
t
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tup‑
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e
a
ms
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ri
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i
mi
t
e
d.
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t
e
ma
t
i
ve
l
y,
yot
l
C
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dr
e
pr
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e
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hee
nt
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m
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ha
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t
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ps
ho
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nFi
gur
e61
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l
s
oa
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ume
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omt
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oc
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sont
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c
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e
sofne
wc
a
r
s
.
Thi
si
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ous
l
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s
s
umpt
l
On:Sa
l
esofne
wc
a
r
sde
pe
ndont
henumbe
ra
nd
a
geoft
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a
r
spe
o
pl
ea
l
r
e
a
dyha
ver
e
l
a
t
i
vet
ot
he
i
rne
e
ds
･
Pe
o
pl
ewhoha
vej
us
ta
c
‑
qui
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e
dane
wc
a
ra
reunl
i
ke
l
yt
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not
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rf
ors
e
ve
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a
lye
a
r
s
,unt
ilt
he
i
rl
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ni
s
pa
i
dof
f
,
t
he
i
rl
e
a
s
ee
xpi
r
e
s
,
Ort
he
i
rc
a
ri
si
nvol
ve
di
na
na
c
c
i
de
nta
ndmus
tber
e
‑
pl
a
c
e
d(
S
e
es
e
c
t
i
o
n2.
2)
.
Fi
gur
e6‑
1
8e
xpa
ndst
hedowns
t
r
e
a
me
ndoft
hes
t
oc
ka
nd
lowma
f
pt
oi
nc
l
ud
et
hes
t
oc
kofc
a
r
sont
her
oa
d.
Youc
a
nc
ont
i
nuet
oc
ha
l
l
e
nget
hemode
lbounda
r
y.Wha
tha
ppe
nst
ot
he
ca
r
swhe
nt
he
ya
r
es
c
r
a
ppe
d?I
nt
hec
ur
r
e
ntma
p,
t
he
ys
i
mpl
ydi
s
a
ppe
a
r
.
I
nr
e
a
l
i
t
y,
t
he
ydon'
t
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nNor
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hAme
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i
c
as
ome1
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o1
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l
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onve
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c
l
e
sa
r
es
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r
a
ppe
dpe
r
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r
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y9
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r
es
hr
e
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da
ndt
hes
t
e
e
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omenonf
e
r
r
ousme
t
a
l
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r
e
224
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msTh
l
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P
a
Fd
GURE6
‑
17
Chal
l
engmgt
he
c一
ouds
Addi
ngasuppl
l
er
an
ddea一
ers
ec
t
or
t
ot
hes
t
ockand
f
l
owchai
nf
or
au
t
omobi
l
epr
o‑
du
c
t
i
on.Rec
t
an一
g】
eswi
t
hr
ounded
c
or
ner
sdenot
e
t
heboundar
i
es
bet
weendi
f
f
er
en
t
or
gani
z
at
i
onal
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t
i
t
i
esanddeci
si
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mak
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e
dpa
r
t
sa
n
dma
t
e
r
i
a
l
se
x
pl
i
c
i
t
,
i
ti
se
a
s
i
e
rt
os
e
et
ha
tt
he
r
ei
si
mpe
r
f
e
c
tc
oo
r
‑
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a
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nt
i
a
li
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a
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e
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i
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umpt
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e
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i
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ms
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s
t
i
t
ut
i
o
na
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t
r
u
c
t
u
r
e
ss
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e
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u
l
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me
nt
St
ha
ts
e
r
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c
ec
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nt
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r
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en
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e
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a
c
e
me
nt
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r
t
sc
a
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r
wh
e
l
mt
hel
o
g
i
coft
hema
r
ke
t
.
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r
ke
tme
c
ha
ni
s
ms
,
e
ve
nwhe
np
r
e
‑
s
e
nt
,a
r
enotl
i
ke
l
yt
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r
ks
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t
hl
y
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s
i
bl
yl
e
a
di
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oi
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t
a
bi
l
i
t
ya
ndi
ne
f
f
i
‑
c
i
e
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y
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mi
l
a
rd
y
na
ic
m
sha
v
ea
l
r
e
a
dybe
e
no
bs
e
r
ve
di
nt
hema
r
ke
tf
o
rr
e
c
yc
l
e
d
pa
pe
r(
Ta
yl
o
r1
9
9
9
)
.
Su
ppl
ys
i
des
t
e
pst
oi
nc
r
e
a
s
er
e
c
yc
l
a
bi
l
i
t
ya
l
o
nea
r
eno
tl
i
ke
l
y
t
obee
fe
c
t
i
veu
nl
e
s
sma
t
c
he
dbypol
i
c
i
e
st
oi
nc
r
e
a
s
et
heus
a
geofr
e
c
o
ve
r
e
dpa
r
t
s
er
i
a
l
sa
ndt
hea
c
t
ua
lr
e
c
yc
l
i
ngof
a
ndma
t
e
r
i
a
l
s
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ol
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e
c
t
i
o
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e
c
yc
l
a
bl
ema
t
t
hos
ema
t
e
r
i
a
l
sa
r
e
n'
t血es
a
me仙i
ng.
6.
4
SL
B
MMARY
Thi
sc
ha
pt
e
ri
nt
r
o
d
uc
e
dt
hes
t
oc
ka
ndf
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onc
e
pt
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oc
ksa
c
c
umul
a
t
et
he
i
ri
n‑
lo
f
wsl
e
s
st
he
i
ro
u
t
lows
f
.
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oc
ksa
r
et
hes
t
a
t
e
so
ft
hes
ys
t
e
mu
po
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c
hde
c
i
s
i
o
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a
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t
i
o
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r
eba
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e
d,
a
r
et
hes
ou
r
c
eo
fi
ne
r
t
i
aa
ndme
mo
r
yl
nS
ys
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e
ms
,
C
r
e
a
t
ede
‑
1
a
ys
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ndge
ne
r
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t
ed
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s
e
q
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l
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b
r
i
umd
yna
mi
c
sbyde
c
o
upl
i
ngr
a
t
e
so
ff
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w.
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i
a
‑
g
r
a
mml
ngnot
a
t
i
o
nf
o
rs
t
o
c
ksa
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lOwsc
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e
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t
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er
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ud
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e
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te
a
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a
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us
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ld
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ft
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ys
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e
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u
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t
e(
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n
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g
r
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t
e
)t
he
i
ri
nf
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e
s
st
he
i
ro
ut
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f
.
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i
va
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e
nt
l
y
her
t
a
t
eo
fc
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ng
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t
o
c
ki
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het
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a
li
nf
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e
s
st
het
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a
lo
ut
lo
f
w.
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t
o
c
k
a
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lo
wma
pc
o
r
r
e
s
po
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xa
c
t
l
yt
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ys
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nt
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g
r
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lo
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le
q
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t
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o
ns
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we
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,
s
t
oc
ka
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df
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a
s
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rt
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kwi
t
ha
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x
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a
i
n.
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r
ea
r
es
e
v
e
r
a
lwa
yst
oi
de
nt
i
f
yt
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t
oc
ksi
ns
ys
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e
ms
.
I
nt
hes
na
ps
hott
e
s
t
youi
ma
gl
nef
r
e
e
z
i
ngt
hes
ys
t
e
ma
tamome
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i
me
‑t
heme
a
s
u
r
a
bl
eq
ua
nt
i
t
i
e
s
(
phys
i
c
a
l
,
i
nf
o
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ma
t
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o
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l
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a
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og
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c
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l
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et
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t
oc
ks
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whi
l
ef
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eno
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s
t
a
nt
a
ne
ous
l
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e
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a
s
ur
a
bl
e.
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t
sofme
a
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ur
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l
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pi
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nt
i
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y
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t
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fas
t
oc
ki
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a
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ur
e
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t
sf
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s
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r
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ni
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rt
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od.
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oc
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t
l
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e
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si
nane
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wo
r
kc
a
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s
ho
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t
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l
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e
l
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t
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z
o
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c
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nt
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r
e
s
t
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t
i
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a
l
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l
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c
t
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t
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nt
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ki
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t
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e
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l
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z
es
i
mi
l
a
rr
e
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o
ur
c
e
sa
ndi
ft
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2
30
Pa
r
t
I
I To
o
l
sf
o
rS
ys
t
e
msTh
i
n
ki
n
g
r
e
s
i
de
nc
et
i
me
so
ft
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t
e
msi
nt
hes
t
o
c
ksi
ss
i
mi
l
a
re
no
ug
hf
o
rt
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pos
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ur
l
.
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e
So
ur
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e
sa
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i
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ort
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m ha
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nf
i
ni
t
ec
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pa
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ke
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t
o
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her
e
a
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l
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e
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e
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hemode
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.
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l
e
r
s
s
ho
ul
da
l
wa
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ha
l
l
e
nget
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s
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unda
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s
s
umpt
l
O
nS
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s
ki
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ft
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s
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umpt
i
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i
nf
i
ni
t
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up
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o
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ur
c
e
sa
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nf
i
ni
t
ea
bs
o
r
pt
1
0
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a
pa
c
i
t
yf
o
rs
i
n
ksi
sa
ppr
o
pr
l
a
t
e
r
e
l
a
t
i
vet
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hemo
de
lpur
pos
e.
i
3
i
{
i
3
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畠
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:
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立至表
現頭首呈
t
i
笥享
Nat
u
r
el
au
g
h
satt
h
edl
Hi
c
ul
t
i
e
so
fi
nt
e
gr
at
i
o
n.
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e
r
r
e
‑
S
i
mo
nd
eLa
p
l
a
c
e(1749‑1827)
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u
c
c
e
s
s
e
so
ft
hedl
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r
e
nt
i
ale
qu
at
i
onpar
adi
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r
ei
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e
s
s
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e
xt
e
ns
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v
e
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nc
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u
di
ng bas
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ca
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mpor
t
anto
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s
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e
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qu
at
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o
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atc
oul
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es
ol
v
e
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e
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SO
fs
e
l
f
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s
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t
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n
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e
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y
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at
i
o
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atc
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v
e
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r
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o
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c
al
l
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e
s
si
nt
e
r
e
s
tt
h
an
t
hos
et
hatc
o
u
l
d.
‑I
anS
t
e
wa
r
t(
1
989,
p.39)
.
Cha
pt
e
r6i
nt
r
o
d
u
c
e
dt
hes
t
oc
ka
ndf
lOwc
o
nc
e
pta
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e
c
hni
q
ue
sf
o
rma
ppl
ngt
he
s
t
oc
ka
ndf
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e
t
wo
r
kso
fs
ys
t
e
ms
.
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sc
ha
pt
e
re
x
pl
o
r
e
st
hebe
ha
v
i
o
rofs
t
oc
ks
a
ndf
lows
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ve
nt
hed
yna
mi
c
soft
hef
lows
,wha
ti
st
hebe
ha
vi
o
ro
ft
hes
t
oc
k?
Fr
omt
hedyna
mi
c
so
ft
hes
t
oc
k,c
a
nyo
ui
nf
T
e
rt
hebe
ha
vi
o
ro
ft
hef
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s
e
t
a
s
ksa
r
ee
q
ul
Va
l
e
ntt
oi
nt
e
g
r
a
t
i
ngt
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lowst
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e
l
dt
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t
oc
ka
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fe
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e
nt
i
a
t
i
ng
t
hes
t
o
c
kt
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e
l
di
t
sne
tr
a
t
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fc
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ng
e.
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rpe
opl
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rs
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udi
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dc
a
l
c
u‑
T
√
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i
us
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t
he
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ec
o
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e
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t
sc
a
ns
e
e
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l
nf
a
c
t
,
r
e
l
a
t
i
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hed
y
na
mi
c
so
fs
t
oc
ksa
nd
lowsi
f
sa
c
t
ua
l
l
yq
ui
t
ei
nt
ui
t
i
ve
;l
ti
st
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a
mi
l
i
a
rno
t
a
t
i
o
na
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oc
uso
n
a
na
l
yt
i
cs
ol
ut
i
o
n
st
ha
tde
t
e
r
sma
nype
o
pl
ef
r
o
ms
t
ud
yo
fc
a
l
c
ul
us
.
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ti
fyo
uha
veas
t
r
o
ngba
c
kg
r
oundi
nc
a
l
c
ul
usa
ndd
i
f
f
e
r
e
n
t
i
a
le
q
ua
t
i
ons
?
I
ti
sge
ne
r
a
l
l
yno
t
pos
s
i
bl
et
os
o
l
vee
v
e
ns
ma
l
lmod
e
l
sa
na
l
yt
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c
a
l
l
yd
uet
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i
rhi
g
h
o
r
de
ra
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n
e
a
r
i
t
i
e
s
,s
ot
hema
t
he
ma
t
i
c
a
lt
ool
sma
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o
pl
eha
ves
t
udi
e
da
r
e
ofl
i
t
t
l
edi
r
e
c
tus
e
.
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fyouha
vemo
r
ema
t
he
ma
t
i
c
a
lba
c
kg
r
o
undyo
uwi
l
lf
i
ndt
hi
s
c
ha
pt
e
rs
t
r
a
i
g
ht
f
o
r
wa
r
dbuts
ho
ul
ds
t
i
l
ldot
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r
a
phi
c
a
li
nt
e
g
r
a
t
i
o
ne
xa
mpl
e
sa
nd
c
ha
l
l
e
nge
st
obes
ur
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uri
nt
ui
t
i
veunde
r
s
t
a
nd
i
ngl
Sa
SS
Ol
i
da
syo
urt
e
c
hni
c
a
l
231
232
P
a
r
tI
IT
o
o
l
sf
o
rS
y
s
t
e
msTh
i
n
k
i
n
g
,
knowl
e
dge｡
Mode
l
e
r
s
,noma
t
t
e
rhowgr
e
a
tors
ma
l
lt
he
i
rt
r
a
i
nl
ngl
nma
t
he
ma
t
i
c
s
ne
e
dt
obea
bl
et
or
e
l
a
t
et
hebe
ha
vi
oro
fs
t
oc
ksa
ndf
lowsi
nt
ui
t
i
ve
l
y,
us
l
nggr
a
Phi
C
a
la
ndot
he
rnonma
t
he
ma
t
i
ca
lt
e
c
hni
q
ue
s
.
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ha
pt
e
ra
l
s
oi
l
l
us
t
r
a
t
eshows
t
oc
k
a
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lOwdyna
mi
c
sgi
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ns
i
ghti
nt
ot
woi
mpor
t
a
ntpol
i
c
yi
s
s
ue
s
:gl
oba
lwa
r
ml
ng
a
ndt
hewa
rondr
ugs
.
‑
7.
1
RELAT1
0NS川PBETWEEN STOCKSAND FLOWS
Re
c
a
l
lt
heba
s
i
cde
f
i
ni
t
i
onsofs
t
oc
ksa
ndf
lows
:
t
hene
tr
a
t
eofc
ha
ngeofas
t
oc
ki
s
t
hes
umofa
l
li
t
si
nf
lowsl
es
st
hes
umofa
l
li
t
so
ut
lows
f
.
St
oc
ksa
c
c
umul
a
t
et
hene
t
r
a
t
eofc
ha
nge.
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he
t
ma
t
i
c
a
l
l
y,s
t
oc
ksi
nt
e
gr
a
t
et
he
i
rne
tf
lows
;
t
hene
tf
lowi
st
he
de
r
i
va
t
i
veoft
hes
t
oc
k.
'
l.
.
虹1 S竜
甜 CandDynami
cEqus
t
S
!
t
bF
!
'
um
As
t
oc
ki
si
ne
qui
l
i
br
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um whe
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as
ys
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e
mi
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ne
qui
l
i
br
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um whe
n
al
li
t
ss
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tr
a
t
eca
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xpr
es
s
e
da
sac
e
r
t
a
i
nt
ypeof
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t
he
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t
i
ca
lf
unc
t
i
on.Butwhe
t
he
rt
hene
tr
a
t
ec
a
nbei
nt
e
gr
a
t
e
da
na
l
yt
l
C
a
l
l
yo
r
not
,
t
hea
mounta
dde
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oas
t
oc
ki
sa
l
wa
yst
hea
r
e
aunde
rt
hene
tr
a
t
e.
Gr
a
phi
c
a
li
n‑
t
e
gr
a
t
i
oni
st
hepr
oc
e
s
so
fe
s
t
i
ma
t
l
ngt
ha
ta
r
e
af
r
om agr
a
phoft
hene
tr
a
t
e.
7.
1.
3 Gr
aphi
caHnt
egr
at
i
on
Toi
l
l
us
t
r
a
t
egr
a
phi
ca
li
nt
e
gr
a
t
i
on,c
ons
i
de
rt
hemos
tba
s
i
cs
t
oc
ka
ndf
lows
ys
t
e
m:
as
l
ngl
es
t
oc
kwi
h onei
t
nf
lowa
ndoneo
ut
low･
f
As
s
umet
hef
lowsa
r
ee
xoge
no
us
‑
t
he
r
ea
r
enof
e
e
dba
c
ksf
r
omt
hes
t
oc
kt
oe
i
t
he
rf
low.
Suppos
et
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ut
lowf
f
r
omt
he
oc
e
d
u
r
ed
e
s
c
r
i
b
e
da
b
o
v
ei
sk
n
o
wna
sEu
l
e
ri
n
t
e
g
r
a
t
i
o
na
n
di
st
h
emo
s
t
c
o
mmo
n
l
yu
s
e
d
l
Th
ep
r
me
t
h
o
df
o
rn
u
me
r
i
c
a
ls
i
mu
l
a
t
i
o
n
.
Ot
h
e
rme
t
h
o
d
ss
u
c
ha
sRu
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g
e
‑
Ku
t
t
ai
n
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e
g
r
a
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i
o
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r
es
o
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h
i
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i
c
a
t
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dme
t
h
o
d
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s
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i
ma
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et
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r
e
aa
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l
e
c
t
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h
et
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e
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e
eAp
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e
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i
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‑
Ch
a
p
t
e
r
7 D
y
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a
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o
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.
(
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FJ
GURE7‑
2
Gr
aphi
c
al
i
n
t
egr
a
t
i
on:
examp一
e
Whi
l
et
her
a
t
e
s
t
epsu
pan
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t
ep
s
down,
t
hes
t
oc
k
r
i
s
esandr
emai
n
s
atahi
gh
erl
e
v
eL
Not
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e
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d
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235
400
竜宮 300
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桟
20
0
1
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蓮
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華∃
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20
30
Ti
me(
seconds
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s
t
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ppos
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l
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ot
ha
tt
hei
nf
lo
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ot
hes
t
oc
kf
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l
l
o
wst
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e
ns
r
hown
i
nFi
g
ur
e7‑
21
Thei
nnowbe
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i
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r
o･
Att
i
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ud
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yl
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e
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e
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i
a
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hes
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o
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Ta
bl
e7‑
2S
howst
hes
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e
psi
nvol
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ng
r
a
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c
a
li
nt
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g
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i
on.
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e
2,
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i
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s
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k,
l
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du
punde
rt
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r
a
ph
s
t
e
pst
oFi
gu
r
e71
f
o
rt
hef
lows
.
Ne
xtc
a
l
c
u
l
a
t
et
hene
tr
a
t
e
.Si
nc
et
he
r
ei
so
nl
yonei
nf
lo
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ndone
o
ut
low,a
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f
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ta
l
lt
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s
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hene
tr
a
t
eo
fc
ha
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he
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oc
k(
To
t
a
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nf
lo
wITo
t
a
lOut
low)s
f
i
mpl
ye
q
ua
l
st
hei
n
lo
f
w.
I
ni
t
i
a
l
l
y
,
t
hes
t
oc
k
ha
sava
l
ueo
fl
oou
ni
t
s
.
Be
t
we
e
nt
i
me0a
ndt
i
me1
0,t
hene
tf
lowi
sz
e
r
ouni
t
s
/
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hene
tr
a
t
e
s
e
c
o
nd,s
ot
hes
t
o
c
kr
e
ma
i
nsc
ons
t
a
nta
ti
t
si
ni
t
i
a
lva
l
ue.
Att
i
me1
J
umpst
O20uni
t
s
/
S
e
c
o
nda
ndr
e
ma
i
nst
he
r
ef
o
r1
0s
e
c
o
nds
.
Thea
mo
unta
dd
e
di
s
t
hea
r
e
aunde
rt
hene
tr
a
t
ec
ur
ve(
be
t
we
e
nt
hene
tr
a
t
ec
ur
vea
ndt
hez
e
r
ol
i
ne
)
.
Si
nc
et
her
a
t
ei
sc
o
ns
t
a
nt
,
t
hea
r
e
ai
sar
e
c
t
a
ngl
e20uni
t
s
/
s
e
c
ondhi
g
ha
nd1
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e
c
‑
ondsl
ong,s
ot
h
es
t
o
c
kr
i
s
e
sby2
00u
ni
t
s
,
g
l
Vl
ngat
o
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ll
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ve
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0
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i
t
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i
me
20･
Be
c
a
us
et
hene
t
r
a
t
el
Spos
i
t
i
vea
ndc
o
ns
t
a
ntd
u
r
i
ngt
hi
si
nt
e
r
va
l
,
t
hes
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oc
kr
i
s
e
s
l
i
ne
a
r
l
ya
tar
a
t
e2
0uni
t
s
/
s
e
c
o
nd(
t
hes
l
o
peoft
hes
t
o
c
ki
s2
0uni
t
s
/
s
e
c
o
nd)
.
Att
i
me20,
t
hei
nf
lows
udd
e
nl
yc
e
a
s
e
s
.
Thene
tr
a
t
eofc
ha
ng
ei
sno
wz
e
r
oa
nd
r
e
ma
i
nsc
ons
t
a
n
t
,a
ndt
hes
t
o
c
ki
sa
ga
i
nunC
ha
ngl
ng,t
壬
1
0
ug
hno
wa
tt
hel
e
ve
lof
300u
ni
t
s
.
No
t
ehowt
h
epr
oc
e
s
sofa
c
c
umul
a
t
i
o
nc
r
e
a
t
e
si
ne
r
t
i
a
:
t
ho
ug
ht
her
a
t
er
i
s
e
sa
nd
f
a
l
l
sba
c
kt
oi
t
so
r
l
gl
na
ll
e
v
e
l
,
hes
t
t
o
c
kdo
e
snot
r
e
t
ur
nt
oi
t
so
r
l
gl
na
ll
e
v
e
l
.
I
ns
t
e
a
d,
i
tr
e
ma
i
nsa
ti
t
sma
xi
mum whe
nt
hene
tr
a
t
ef
a
l
l
sba
c
kt
oz
e
r
o.I
nt
hi
sf
a
s
hi
o
n,
S
t
oc
kspr
ovi
deame
mo
r
yofa
l
lt
hepa
s
te
ve
n
t
si
nas
ys
t
e
m.
Theo
nl
ywa
yf
o
rt
he
s
t
oc
kt
of
a
l
li
sf
o
rt
hen
e
tr
a
t
et
obe
c
o
mene
ga
t
i
ve(
f
o
rt
heo
ut
lo
f
wt
oe
xc
e
e
dt
hei
n
low)
f
A
No
t
ea
l
s
ohowt
hepr
oc
e
s
so
fa
c
c
umul
a
t
i
onc
ha
ng
e
dt
hes
ha
peo
ft
hei
n
put
.
Thei
nputi
sar
e
c
t
a
ng
ul
a
rpul
s
ewi
t
ht
wod
i
s
c
ont
i
nuo
usJ
umps
;t
heout
puti
sa
s
moo
t
h,
c
ont
i
n
uo
usc
u
r
v
e
.
‑
2
36
TABLE7
‑
2
St
epsi
ngr
aphi
cal
i
nt
egr
at
i
on
Pa
r
tI
I To
ol
sf
o
rSys
t
e
msThi
nk
i
ng
1.Cal
cul
at
eandgr
apht
het
ot
alr
at
eofi
nf
l
owt
ot
hes
t
ock(
t
hesum ofal
l
i
nf
l
ows
)
.Cal
cul
at
eandgr
apht
het
ot
alr
at
eofou
t
刊owf
r
om t
hes
t
ock(
t
he
sum ofa"ou
t
f
l
ows
)
.
2,Cal
cul
at
eandgr
apht
henetr
at
eofchangeoft
hes
t
ock(
t
het
ot
aHnf
l
owl
ess
t
het
ot
a一
out
f
l
ow)
.
3.Mak
easetofaxest
ogr
apht
hes
t
ock.St
ock
sandt
hei
rf
l
owshavedi
f
f
er
ent
uni
t
sofmeasur
e(
i
fas
t
ocki
smeasur
edi
nuni
t
si
t
sf
l
owsar
emeasur
edi
n
uni
t
spert
i
meper
i
od)
.
Ther
ef
or
es
t
ock
sandt
hei
rf
l
owsmustbegr
aphedon
separ
at
es
cal
es.Mak
easepar
at
egr
aphf
or帥es
t
ockundert
hegr
aphf
or
t
hef
l
ows,
wi
t
ht
het
i
meaxesl
i
nedup.
4.Pl
ott
hei
ni
t
i
al
val
ueoft
hes
t
ockont
hes
t
ockgr
aph.
Thei
ni
t
i
al
val
uemus
t
bespeci
f
i
ed;i
tcannotbei
nf
er
r
edf
r
omt
henetr
at
e,
5lBr
eakt
henetf
J
owi
nt
oi
nt
er
val
swi
t
ht
hesamebehavi
orandcal
cul
at
et
he
amoun
taddedt
ot
hes
t
ockdur
i
ngt
hei
n
t
er
valSegmen
t
smi
ghtbei
nt
er
val
s
i
nwhi
cht
henetr
at
ei
scons
t
ant
,
changl
ngl
l
near
F
y,Orf
oI
I
owI
ngsomeOt
her
pat
t
er
n.
Theamountaddedt
oorsubt
r
ac
t
edf
r
omt
hes
t
ockdur
i
nga
segmen
ti
st
hear
eaundert
henetr
at
ecur
vedur
i
ngt
hatsegmen
t
･For
exampF
e,doest
henetf
l
owr
emai
ncons
t
antf
r
omt
i
met
lt
Ot
i
met
2?E
fso,
t
her
at
eofchangeoft
hes
t
ockdur
i
ngt
hats
egmenti
scons
t
ant
,andt
he
quan
t
i
t
yaddedt
ot
hes
t
ocki
st
hear
eaoHher
ec
t
angl
edef
i
nedbyt
henet
r
at
ebet
weent
landt
2.1
日henetr
at
er
i
sesl
i
near
l
yl
nasegment
,
t
hent
he
amountaddedi
st
hear
eaoft
het
r
i
angl
e.Es
t
i
mat
et
hear
eaundert
henet
r
at
ecur
vef
ort
hesegmentandaddi
tt
ot
heval
ueoft
hest
ockatt
hes
t
ar
tof
t
hesegment
.
Thet
ot
ali
st
heval
ueoft
hes
t
ockatt
heendoft
hesegment
.
Pl
ott
hi
spoi
n
tont
hegr
aphoft
hes
t
ock.
6.Sk
et
cht
het
r
a
j
ec
t
or
yoft
hes
t
ockbet
weent
hes
t
ar
tandendofeach
.
segmen
t
.Fi
ndt
heva山eoft
henetr
at
eatt
hebegl
nnl
ngOft
hesegment
f
si
tposi
t
i
v
eornegat
i
ve?l
ft
henetf
l
owi
sposi
t
i
ve,t
hes
t
ockwi
nbe
i
ncr
easl
ngatt
hatt
i
me.l
ft
henetf
l
owi
snegat
i
ve,t
hes
t
ockwH
lbe
deer
easmg.
Thenaskwhet
herj
ti
sr
i
sl
ngOrf
al
l
l
ngatani
ncr
easl
ngOr
decr
easl
ngr
at
e,andsk
et
cht
hepat
t
er
nyoui
n
f
eront
hegr
aph.
l
ft
henetr
at
ei
sposi
t
i
veandi
nc
r
easl
ng,t
hes
t
ocki
ncr
easesatan
i
ncr
easl
'
ngr
at
e(
t
hes
t
ockaccel
er
at
esupwar
d)
.
l
ft
henetr
at
ei
sposi
t
i
veanddecr
easl
ng,t
hes
t
ocki
ncr
easesata
decr
easi
ngr
at
e(
t
hes
t
ocki
sdecel
er
at
i
ngbuts
t
i
l
lmovi
ngupwar
d)
.
l
ft
henetr
at
ei
snegat
i
veandi
t
smagni
t
udei
s/
I
ncr
easi
ng(
t
henetr
at
ei
s
'
ncr
easi
ngr
at
e,
becomi
ngmor
enegat
i
ve)
,
t
hes
t
ockdecr
easesatan/
l
ft
henetr
at
ei
snegat
i
veandi
t
smagnl
J
t
udei
sdecr
easi
ng(
becomi
ngl
ess
negat
i
ve)
.
t
hes
t
ockdecr
easesatadecr
easi
ngr
at
e1
7.Whenevert
henetr
at
ei
szer
o,
t
hes
t
ocki
sunchangl
ng.Mak
esur
et
hat
nt
hes
t
ockever
ywher
et
henet
yourgr
aphoft
hes
t
ockshowsnochangei
r
at
ei
szer
o.l
ft
henetr
at
er
emai
nszer
of
orsomei
nt
er
val
,
t
hes
t
ock
r
emai
nscons
t
an
tatwhat
everval
uei
thadwhent
henetr
at
ebecamezer
o.
Atpoi
nt
swher
et
henetr
at
echangesf
r
om posi
t
i
vet
onegat
i
ve,
t
hes
t
ock
r
eachesamaxi
mum asi
tceasest
or
i
seands
t
ar
t
st
of
a川
.
Atpoi
nt
swher
e
r
om negat
i
vet
oposi
t
i
ve,
t
hes
t
ockr
eachesa
t
henetr
at
echangesf
mi
ni
mum asi
tceasest
of
al
l
ands
t
ar
t
st
or
i
se.
i
l
done.
8.Repeats
t
eps5t
hr
ough7unt
237
Ch
a
p
t
e
r7 Dy
n
a
mi
c
so
fS
t
o
c
k
sa
n
dF
l
o
ws
FI
GURE7･
3 Theac
cumul
at
i
onpr
oc
es
scr
ea
t
esdel
ay
s.
Not
et
heone‑
quar
t
erc
y
cl
el
agbet
we
ent
hepeak
soft
henetf
l
owandt
hepeak
so
ft
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t
ock.
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nt
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ow
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6
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i
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ons
i
d
e
rt
hef
lOwss
pe
c
i
f
i
e
di
nt
het
oppa
ne
lofFi
g
ur
e71
3.
Theout
low
f
i
sc
ons
t
a
nta
t1
0
0uni
t
s
/
mont
h,
1
D
utt
hei
nf
l
owF
l
uc
t
ua
t
esa
r
ounda
na
ve
r
a
geofl
oo
wi
t
hape
r
i
odo
f1
2mont
hsa
nda
na
mpl
i
t
udeof±50uni
t
s
/
mont
h.
Att
hes
t
a
r
t
,
t
he
i
nf
lowi
sa
ti
t
sma
xi
mum.
As
s
umet
hei
ni
t
i
a
lva
l
ueoft
hes
t
o
c
ki
s500uni
t
s
.
Si
nc
et
heo
ut
low i
f
sc
ons
t
a
nt
,t
hene
ti
nf
l
ow i
saf
luc
t
ua
t
i
onwi
t
ha
mpl
i
t
ude
±50uni
t
s
/
mont
ha
ndame
a
nofz
e
r
o.
Thes
t
oc
kbe
gi
nsa
ti
t
si
ni
t
i
a
lva
l
ueof500
uni
t
s
,buts
i
nc
et
hei
nf
lowi
sa
ti
t
sma
xi
mum,t
hes
t
oc
ki
ni
t
i
a
l
l
yr
i
s
eswi
h as
t
l
ope
of50uni
t
s
/
mon
t
h.
Howe
ve
r
,
t
hene
tf
lowf
a
l
l
sove
rt
hef
i
r
s
t3mont
hs
,
s
ot
hes
t
oc
k
i
nc
r
e
a
s
e
sa
tade
c
r
e
a
s
i
ngr
a
t
e.
Atmont
h3t
hene
tf
lowr
e
a
c
he
sz
e
r
o,
t
he
ngoesne
g‑
a
t
i
ve.
Thes
t
oc
kmus
tt
he
r
e
f
わr
er
ea
c
hama
xi
mum a
tmont
h3.
Thea
mounta
dde
d
t
ot
hes
t
oc
ki
nt
hef
i
r
s
t3mont
hsi
st
hea
r
e
aunde
rt
hene
tr
a
t
ec
ur
ve.
I
ti
snotea
s
y
2
3
8
I
IT
わ
o
l
s
f
o
rS
y
s
t
em s
Th
i
n
k
i
n
g
P
a
r
t
t
oe
s
t
i
ma
t
et
hea
r
e
af
r
omt
heg
r
a
p
hbe
c
a
us
et
hen
e
tr
a
t
ec
ur
vei
sc
o
ns
t
a
nt
l
yc
ha
ng
1
ng.
Yo
uc
o
ul
de
s
t
i
ma
t
ei
tbya
ppr
oxi
ma
t
l
n
gt
hea
r
e
aa
sas
e
tofr
e
c
t
a
ngl
e
s
,a
sde
‑
s
c
r
i
be
da
bo
ve,t
ho
ug
ht
hi
swo
ul
dt
a
ket
i
me
.Us
i
ngs
i
mul
a
t
i
ont
oc
a
r
r
youtt
he
a
c
c
umul
a
t
i
o
ns
howst
ha
tal
i
t
t
l
el
e
s
st
ha
n1
00u
ni
t
sa
r
ea
dde
dt
ot
hes
t
oc
kbyt
he
t
i
met
hene
tr
a
t
ef
a
l
l
st
oz
e
r
oa
tmo
nt
h3.
Fr
o
m mont
h3t
omo
nt
h6,t
hene
tr
a
t
ei
sne
ga
t
i
ve
.Thes
t
oc
ki
st
he
r
e
f
o
r
e
f
a
l
l
i
ng.
J
us
ta
f
t
e
rmont
h3,
t
hene
t
r
a
t
el
S
J
us
t
ba
r
e
l
yne
ga
t
i
ve
,
S
ot
her
a
t
eofde
c
l
i
ne
o
ft
hes
t
o
c
ki
ss
l
i
g
ht
.
Butt
hema
gni
t
udeo
ft
hene
tr
a
t
ei
nc
r
e
a
s
e
s
,S
ot
hes
t
oc
kf
a
l
l
s
a
ta
ni
nc
r
e
a
s
i
ngr
a
t
e.
At6mo
nt
hs
,
t
hene
t
r
a
t
eha
sr
e
a
c
he
di
t
sm
i ni
mum(
mos
tne
g‑
a
t
i
v
e
)va
l
ueof‑50uni
t
s
/
mo
nt
h.
Thes
t
oc
ki
sde
c
l
i
ni
nga
ti
t
sma
xi
mumr
a
t
e;
t
he
r
e
i
sa
ni
n
le
f
c
t
i
o
npo
l
nti
nt
het
r
a
j
e
c
t
o
r
yO
ft
hes
t
oc
ka
tmo
nt
h6.
Howmuc
hd
i
dt
hes
t
oc
kl
os
ebe
t
we
e
nmo
nt
h3a
ndmont
h6?As
s
umi
ngt
he
luc
f
t
ua
t
i
o
ni
nt
hene
tr
a
t
ei
ss
ymme
t
r
i
c
a
l
,
t
hel
os
sJ
us
t
ba
l
a
nc
e
dwha
twa
sga
i
ne
di
n
t
hef
i
r
s
t3mo
nt
hs
,
r
e
duc
i
ngt
hes
t
oc
kba
c
kt
oi
t
si
ni
t
i
a
ll
e
ve
lo
f50
0uni
t
s
.
Fr
o
mmo
nt
h6t
omon
t
h9,
t
hene
tf
lo
wr
e
ma
i
nsne
ga
t
i
ve
,s
ot
hes
t
oc
kc
o
nt
i
n
ue
st
of
a
l
l
,
butnowa
tade
c
r
e
a
s
l
ngr
a
t
e.Bymo
nt
h9t
hene
tf
lowa
ga
l
nr
e
a
c
he
s
r
o,
s
ot
hes
t
o
c
kc
e
a
s
e
st
of
a
l
la
ndr
e
a
c
he
si
t
smi
ni
mum.
Aga
i
nus
i
ngt
hea
s
s
u
mp‑
z
e
t
i
ono
fs
y
mme
t
r
y
,
t
hequa
nt
l
t
yl
os
tf
r
o
mmo
n
t
hs6t
o9i
se
q
ua
lt
ot
hequa
nt
l
t
yl
os
t
f
r
o
mmo
n
t
hs3t
o6,S
ot
hes
t
o
c
kf
a
l
l
st
oal
e
ve
l
j
us
ta
bo
ve400uni
t
s
.
Fr
o
mmo
nt
hs9t
o1
2t
hene
tf
lowi
spos
i
t
i
ve
,
s
ot
hes
t
oc
ki
sr
i
s
i
ng.
Dur
i
ngt
hi
s
t
i
met
hene
tr
a
t
er
i
s
e
s
,s
ot
hes
t
oc
ki
nc
r
e
a
s
e
sa
ta
ni
nc
r
e
a
s
i
ngr
a
t
e
,e
ndi
ngwi
t
ha
s
l
o
p
eo
f5
0uni
t
s
/
mo
nt
ha
st
hene
t
r
a
t
er
e
a
c
he
si
t
sma
x
i
mum.
Aga
i
n,
t
hes
t
oc
kg
a
l
nS
t
hes
a
mea
mo
unt
,
r
e
c
ove
r
l
ngI
t
si
ni
t
i
a
ll
e
v
e
lo
f5
00uni
t
se
xa
c
t
l
ya
tmo
nt
h1
2.
Be
‑
y
on
dmo
n
t
h1
2t
hec
yc
l
er
e
pe
a
t
s
.
Thee
xa
mpl
ei
l
l
us
t
r
a
t
e
st
hewa
yl
nWh
i
c
ht
hepr
o
c
e
s
so
fa
c
c
umul
a
t
i
o
nc
r
e
a
t
e
s
d
e
l
a
ys
,
Thei
nputt
ot
hes
ys
t
e
mi
saf
luc
t
ua
t
i
o
nwi
t
ha1
2
‑
mo
nt
hpe
r
i
odr
e
a
c
hi
ngI
t
s
pe
a
ka
tt
i
me‑0,1
2,
24,...
mo
nt
hs
.
Thes
t
o
c
k,
o
ro
ut
puto
ft
hes
ys
t
e
m,
a
l
s
of
luc
t
ua
t
e
swi
t
ha1
21
mOnt
hpe
r
i
odbutl
a
gsbe
hi
ndt
hene
ti
nf
lo
wr
a
t
e
,r
e
a
c
hi
ngI
t
s
pe
a
ksa
tt‑3,1
5,2
7,‥ .
mo
nt
hs
.
Thel
a
gl
Spr
e
c
i
s
e
l
yo
ne
‑
q
ua
r
t
e
rc
yc
l
e.
Thel
a
g
a
r
i
s
e
sbe
c
a
us
et
hes
t
oc
kc
a
no
nl
yde
c
r
e
a
s
ewhe
nt
hene
tf
lo
wi
sne
ga
t
i
ve.
I
ft
hene
t
lowi
f
spos
i
t
i
vea
ndf
a
l
l
st
oz
eo,
t
hes
t
o
c
ki
nc
r
e
a
s
e
sa
ndr
e
a
c
he
si
t
sma
xi
mum.
‑
‑
‑
r
Anal
yt
i
c
alI
nt
egr
at
i
onofaFl
uct
uat
l
r
On
Thee
xa
mpl
ei
nFi
gur
e7‑
3c
a
nbema
depr
e
c
i
s
eus
l
ngal
i
t
t
l
eba
s
i
cc
a
l
c
ul
us
.
The
s
t
oc
kSi
st
hei
nt
e
gr
a
loft
hene
tr
a
t
eR.
As
s
umi
ngt
hen
e
tf
lo
wi
sac
os
i
newi
t
hpe
‑
r
i
od1
2mo
nt
hsa
nda
mpl
i
t
ude50uni
t
s
/
mo
n
t
h,
R=5
0c
os
(
2T
r
t
/
1
2)
,
t
he
n
‑l
5
0c
o
s2
Tu1
2
)
d
t‑50(
1
2
/
2T)
s
i
n(
2
Tu
1
2
)+S
t
s‑lRd
t
(
D
(
7
‑
2
)
Thes
t
o
c
kf
o
l
l
o
wsas
i
newa
vewi
t
ht
hes
a
mepe
r
i
o
da
nda
mpl
i
t
ud
e(
1
2
/
2¶ )t
i
me
s
t
ha
toft
hene
tf
low.
Thede
l
a
yc
a
us
e
dbyt
hea
c
c
umul
a
t
i
o
npr
oc
e
s
si
se
a
s
i
l
ys
e
e
n
s
i
nc
es
i
n(
0
)=c
os
(
0‑¶/
2)
:
汀t
/
1
2‑¶/
2
)+S
t
｡
S‑5
0
(
1
2
/
ユ
′
汀)
c
o
s
(
2
′
(
7
‑
3
)
Thes
t
o
c
kf
ol
l
owst
hes
a
met
r
a
j
e
c
t
o
r
ya
St
hene
tf
lo
wbutwi
t
hapha
s
el
a
go
f7
T
/
2
(
one
‑
qua
r
t
e
rc
yc
l
e
)
.
Equa
t
i
on(
7‑
2)a
l
s
os
howst
ha
tt
hea
mpl
i
t
udeo
ft
hes
t
oc
ki
s
(
50uni
t
s
/
mont
h)*(
1
2mont
hs
/
2T
r
)‑ 96uni
t
s
,S
ot
hes
t
oc
kf
luc
t
ua
t
e
sbe
t
we
e
n
a
bo
ut40
4a
nd5
96,
a
ss
e
e
ni
nt
hef
i
g
ur
e
.
239
Ch
a
p
t
e
r7 Dy
n
a
mi
c
so
fS
t
o
c
k
sa
n
dFl
o
ws
Gr
aphi
c
a
Hn
t
e
gr
a
t
i
on
Cons
i
de
ras
t
o
c
kwi
t
has
i
ngl
ei
nf
lowr
a
t
eRla
nds
i
ngl
eo
ut
nowr
a
t
eR2･
Dr
a
wt
he
be
ha
vi
oroft
hes
t
oc
kgi
ve
nt
her
a
t
e
sRla
ndR2S
howni
ne
a
c
hpa
ne
lofFi
gur
e7‑
4.
Thei
ni
t
i
a
lva
l
u
eoft
hes
t
oc
ki
s1
00uni
t
si
nbot
hc
a
s
es
.
Donotus
eac
omput
e
r
.
The
pol
nti
st
ode
v
e
l
o
pyo
uri
nt
ui
t
i
ona
bouts
t
oc
ksa
ndRowsa
ndyoura
bi
l
i
t
yt
or
e
l
a
t
e
t
he
i
rbe
ha
vi
o
r
.
Us
i
ngs
i
mul
a
t
i
onde
f
e
a
t
st
ha
tpur
pos
ea
ndwi
l
lt
a
kel
onge
ra
swe
l
l
.
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nf
l
ow
O〆
ut
f
一
ow
1
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j
g
4
9
4
t
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こ
.
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.
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.
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‑
一
■
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■
5
20
‑
10
‑
‑
■‑
′
1
5
20
7.
1
.
4 Gr
a
phi
c
al
Di
f
f
er
en
t
i
a
t
i
on
Thei
nve
r
s
eofi
nt
e
gr
a
t
i
oni
sdi
fe
r
e
nt
i
a
t
i
on,t
heca
l
c
ul
a
t
i
onoft
hene
tr
a
t
eof
c
ha
ngeofas
t
o
c
kf
r
o
mi
t
st
r
a
j
e
c
t
ory.Gi
ve
nagr
a
phofas
t
oc
k,
i
ti
sa
l
wa
yspos
s
i
‑
bl
et
oi
nf
e
rt
hene
tr
a
t
eofc
ha
ngea
ndpl
oti
t
.
Asi
nt
hec
a
s
eofi
nt
e
gr
a
t
i
on,
t
he
r
ea
r
e
a
na
l
yt
i
cme
t
ho
dst
oc
a
l
c
ul
a
t
et
hene
tr
a
t
eofas
t
oc
kl
ft
hef
u
nc
t
i
ondes
c
r
i
bi
ngt
he
s
t
oc
k'
spa
t
hi
sknown.
Howe
ve
r
,
i
nmos
tdyna
mi
cmode
l
snoa
na
l
yt
i
cf
u
nc
t
i
onf
or
t
hes
t
oc
ksi
skn
own,S
oyoumus
tde
ve
l
opt
hes
ki
l
lofg
r
a
phi
c
a
ldi
f
f
e
r
e
nt
i
a
t
i
on･
Gr
a
phi
c
a
ld
i
fe
r
e
nt
i
a
t
i
oni
ss
t
r
a
i
ght
f
or
wa
r
d･Si
mpl
ye
s
t
i
ma
t
et
hes
l
opeoft
he
s
t
oc
ka
te
a
c
hpo
l
nti
nt
i
mea
ndpl
o
ti
tonagr
a
phoft
hene
tr
a
t
e.
Fi
g
ur
e7‑
5pr
ovi
des
a
ne
xa
mpl
e.
2
4
0
0
0
0
2
0
5
7
1
l!
s un)qU
(
FI
GURE7
‑
5
Gr
aphi
c
a一
di
f
f
er
en
t
i
at
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on
Pa
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l
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e
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242
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t
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a
t
e.
Thef
lowo
ft
hes
ys
t
e
m,
de
‑
not
e
dbya
r
r
owsi
nt
hepha
s
epl
o
t
,
i
sa
l
wa
yst
owa
r
dt
hes
t
a
bl
ee
qui
l
i
br
i
um.
Thedot
s
ont
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s
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ots
howt
hel
oc
a
t
i
onoft
hes
ys
t
e
me
ve
r
y1
0t
i
meuni
t
s
.
Not
ehow
275
Cha
p
t
e
r8 Cl
os
i
n
gt
heLoo
p:
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‑
a
mi
c
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mp
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ur
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s
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GURE8
‑
6
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alSt
r
uct
ur
e
Fi
r
s
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i
near
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vef
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s
t
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uct
ur
eand
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e
=‑NetOut
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d
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act
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onal
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e
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eci
at
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onRat
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f
et
i
me
FI
GURE8
‑
7
≡‑
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t
l
ow Rat
e
Netl
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l
ow Rat
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a
u!
t
J
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a
t
t
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t
]きOl
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uJl
a
N
Phasep一
otf
or
exponen
t
i
aldecay
vi
a‖
nearnegat
i
ve
f
eedback
276
Pa
r
t
I
IT
わ
o
l
sf
o
rS
y
s
t
e
msTh
i
n
k
i
n
g
‑
8 Exponent
i
al
dec
ay:s
t
r
uc
t
ur
e(
ph
as
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ot
)andbehavi
or(
t
i
mepl
ot
)
FI
GURE8
Thef
r
ac
t
i
onal
decayr
at
ed‑5%/
t
i
meuni
t
.I
ni
t
i
al
s
t
at
eoft
hes
ys
t
em ‑1
00uni
t
s.
Behavi
or
St
r
uct
ur
e
5
40
60
80
S
t
a
t
eo
fS
y
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t
e
m(
u
n
i
t
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)
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i
tsJti
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t
l
n
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g
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t
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40
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Ti
me
t
hea
d
j
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t
me
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sr
a
pi
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tf
i
r
s
ta
ndf
a
l
l
sove
rt
i
me.
Thes
t
a
t
eo
ft
hes
ys
t
e
mf
a
l
l
sa
ta
di
mi
ni
s
hi
ngr
a
t
ea
si
ta
ppr
oa
c
he
sz
e
r
o･
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xpone
nt
i
a
lde
c
a
ys
t
r
uc
t
ur
ei
sas
pe
c
i
a
lc
a
s
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i
r
s
t
1
0
r
de
rl
i
ne
a
rne
ga
t
i
vef
e
e
dba
c
ks
ys
t
e
m.
Asdi
s
c
us
s
e
di
nc
ha
pt
e
r4,a
l
lne
ga
t
i
vef
e
e
dba
c
kl
oo
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ve
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l
s
Jnt
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a
s
eofe
xpone
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a
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c
a
y,s
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ha
st
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a
t
hr
a
t
ea
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pr
e
c
i
a
t
i
one
x‑
a
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,t
hegoa
li
si
mpl
i
c
i
ta
nde
qua
lt
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e
r
oJnge
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r
a
l
,howe
ve
r
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l
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ne
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t
i
vel
oo
psa
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enotz
e
r
oa
nds
houl
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xpl
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c
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t
.
Fi
gur
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9s
howst
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e
r
a
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t
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r
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ur
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ort
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s
t
1
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i
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dba
c
ks
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t
e
m wi
t
ha
ne
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c
i
t
goa
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.
Exa
mpl
esi
nc
l
udet
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e
s
sbywhi
c
haf
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r
ma
d
j
us
t
si
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si
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i
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l
.Pos
s
i
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l
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nc
ha
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i
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r
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sa
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nt
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a
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Te
C
t
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t
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onde
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e
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mi
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t
a
t
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e
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bl
ynonl
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ne
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t
i
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t
a
t
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ys
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e
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a
ndt
he
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i
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ds
t
a
t
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hes
ys
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e
m,S*:
‑
Ne
tI
n
lo
f
w‑i
(
S,
SX
)
.
(
8
‑
1
4)
Thes
i
mpl
es
tf
or
mul
a
t
i
on,howe
ve
r
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sf
ort
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or
r
e
c
t
i
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t
i
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nt
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r
a
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pa
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we
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nt
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s
i
r
e
da
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c
t
ua
ls
t
a
t
eof
t
hes
ys
t
e
m:
Ne
tl
n
f
l
o
w
‑Di
s
c
r
e
p
a
n
c
y
,
/
AT‑(
S*‑S)
,
/
AT
(
8
‑
1
5
)
whe
r
et
hepa
r
a
me
t
e
rATi
sknowna
st
hea
d
j
u
s
t
me
ntt
i
meort
i
mec
ons
t
antf
ort
he
l
oop.
Not
et
heuni
t
sofe
qua
t
i
on(
8‑
1
5)
:
t
hene
ti
nf
lowha
sdi
me
ns
i
o
nsofuni
t
s
/
ime
t
pe
r
i
od･
Thedi
s
c
r
e
pa
nc
ybe
t
we
e
nt
hedes
i
r
e
da
nda
c
t
ua
ls
t
a
t
eoft
hes
ys
t
e
mha
sdi
一
me
ns
i
onsofuni
t
s
I
Fo
re
xa
mpl
e,i
ft
hedes
i
r
e
di
nve
nt
or
yofaf
i
r
mi
s1
00uni
t
sa
nd
c
ur
r
e
nti
nve
nt
or
yl
SOnl
y60uni
t
s
,
t
hedi
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c
r
e
pa
nc
yi
s40uni
t
s
.
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d
j
us
t
me
ntt
i
me
r
e
pr
e
s
e
nt
showqui
c
kl
yt
hef
i
r
mt
r
i
est
oc
or
r
e
c
tt
hes
ho
r
t
f
a
l
l
:i
ft
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i
r
ms
e
e
kst
o
c
or
r
e
c
tt
hes
hor
t
f
a
l
lqui
c
kl
y,
t
hea
d
j
us
t
me
ntt
i
mewo
ul
dbes
ma
l
l
.
Fore
xa
mpl
e,
t
he
f
i
r
mma
ys
e
tt
hea
d
j
us
t
me
ntt
i
met
oAT‑ 1we
e
k,
me
a
nl
ngt
ha
tt
he
ywo
ul
dc
or
r
e
c
t
277
Cha
pt
e
r8 Cl
os
i
n
gt
heLo
o
p:
Dyna
mi
c
so
fSi
mpl
eSt
mc
t
u
r
e
s
Fl
GURE81
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r
s
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i
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i
vef
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y
s
t
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he
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s
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uct
ur
e
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at
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em
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epancy
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AT
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/
AT
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me
★
Examp一
es
Desi
r
ed
hvent
or
y
l
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=
‑
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Shor
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i
a
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t
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s
/
we
e
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e
t
t
i
ng
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e
kswo
ul
de
nt
a
i
la
ni
ni
t
i
a
lne
ti
nf
low of20uni
t
s
/
we
e
k,a
nda
ne
ve
n
mo
r
ea
ggr
es
s
i
vef
i
r
mmi
ghts
e
t
AT‑0.
5we
e
ks
,
l
e
a
di
ngt
oa
ni
ni
t
i
a
lne
ti
nf
lowof
i
nve
nt
or
yof8
0uni
t
s
/
we
e
k.
Ofc
o
ur
s
e
,
t
hes
ec
or
r
e
c
t
i
vea
c
t
i
onsc
a
us
et
hei
nve
nt
o
r
y
s
hor
t
f
a
l
lt
odi
mi
ni
s
h,r
e
duc
i
ngt
hene
ti
nf
low ove
rt
i
meunt
i
lt
hedi
s
c
r
e
pa
nc
yl
S
e
l
i
mi
na
t
ed.
Thedi
s
c
r
e
pa
nc
yc
a
nbene
ga
t
i
ve,a
swhe
nt
he
r
ei
se
xc
e
s
si
nve
nt
or
y;
l
n
t
hi
sc
a
s
et
hene
ti
nf
lowi
sne
ga
t
i
vea
ndt
hes
t
a
t
eoft
hes
ys
t
e
mf
a
l
l
s
.
278
Pa
r
tI
I n)
O
l
sf
o
rSys
t
em s
Thi
n
ki
ng
Ther
e
c
i
pr
oc
a
loft
hea
d
j
us
t
me
ntt
i
meha
suni
t
sofl
/
t
i
mea
ndi
se
qui
va
l
e
ntt
o
tef
h
r
a
c
t
i
ona
la
d
j
us
t
me
ntr
a
t
e,
C
or
r
e
s
pondi
ngt
ot
hef
r
a
c
t
i
ona
lde
c
a
yr
a
t
ei
nt
hee
x‑
pone
nt
i
a
lde
c
a
yc
a
s
e.
Thepha
s
epl
otf
o
rt
hes
ys
t
e
m(
Fi
gur
e8‑
1
0)s
howst
ha
tt
he
ne
ti
nf
lowr
a
t
et
ot
hes
t
a
t
eoft
hes
ys
t
e
mi
sas
t
r
a
i
ghtl
i
newi
t
hs
l
o
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/
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nd
e
qua
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nS‑S*
･
Thebe
ha
vi
oroft
hene
ga
t
i
vel
oo
pwi
t
ha
ne
xpl
i
c
i
tgoa
li
s
a
l
s
oe
xpone
nt
i
a
lde
c
a
y
,buti
ns
t
e
a
dofde
ca
yl
ngt
OZ
e
r
o,t
hes
t
a
t
eoft
hes
ys
t
e
m
r
e
a
c
he
se
q
ui
l
i
br
i
umwhe
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I
ft
hei
ni
t
i
a
ls
t
a
t
eoft
hes
ys
t
e
mi
sl
e
s
st
ha
nt
hedes
i
r
e
ds
t
a
t
e
,t
hene
ti
nf
lowi
s
pos
i
t
i
vea
ndt
hes
t
a
t
eoft
hes
ys
t
e
mi
nc
r
e
a
s
e
s
,
a
tadi
mi
ni
s
hi
ngr
a
t
e,
unt
i
lS‑S*
･
I
f
t
hes
t
a
t
eoft
hes
ys
t
e
mi
si
ni
t
i
a
l
l
ygr
e
a
t
e
rt
ha
nt
hegoa
l
,t
hene
ti
nf
lowi
sne
ga
t
i
ve
a
ndt
hes
t
a
t
eo
ft
hes
ys
t
e
mf
a
l
l
s
,a
tadi
mi
ni
s
hi
ngr
a
t
e
,
unt
i
li
te
qua
l
st
hegoa
l
.
The
lowoft
f
hes
ys
t
e
mi
sa
l
wa
yst
owa
r
dt
hes
t
a
bl
ee
qui
l
i
br
i
umpoi
nta
tS‑S*(
Fi
g‑
ur
es‑
ll
)
.
=(S★‑S)/AT
Netl
nf
l
ow Rat
e=‑NetOut
f
一
ow Rat
e
0
J
s
l!
un)
(
a
∈!
t
let
a ]きOl
‑u aN
FI
GURE8‑
10
Phas
epl
o
tf
or
f
i
r
s
トor
der一
i
near
negat
i
vef
eedback
s
y
s
t
emwi
t
h
expl
l
Ci
tgoal
FI
GURE8‑
ll
Exponen
t
i
al
appr
oacht
oagoal
Thegoal
i
sl
oo
uni
t
s.
Theupper
cur
vebegl
nSWi
t
h
S(
0)‑200;t
he
l
owercur
v
ebegl
nS
wi
t
hS(
0)‑0.
The
ad
j
us
t
men
tt
i
me
i
nbot
hc
as
esi
s
20t
i
meuni
t
s.
60
80
100
Ch
a
p
t
e
r8 Cl
o
s
i
n
gt
h
eLo
o
p
:
Dy
n
a
mi
c
so
fS
i
mp
l
eS
t
r
u
c
t
u
r
e
s
279
8.
3
.
1 Ti
meCon
s
t
an
t
sa
n
dHa
t
トLi
v
e
s
J
us
ta
se
xpone
n
t
i
a
lgr
owt
hdoubl
e
st
hes
t
a
t
eoft
hes
ys
t
e
mi
naf
i
xe
dpe
r
i
odoft
i
me,
e
xpone
nt
i
a
lde
c
a
yc
ut
st
hequa
nt
l
t
yr
e
ma
i
nl
ngbyha
l
fi
naf
i
xedpe
r
i
odoft
i
me.
Theha
l
f
‑
l
i
f
eofa
ne
xpone
nt
i
a
lde
c
a
ypr
oc
es
si
sc
a
l
c
ul
a
t
e
di
nt
hes
a
mef
a
s
hi
ona
s
t
hedoubl
i
ngt
i
me.
Thes
ol
ut
i
ont
oe
qua
t
i
o
n(
8‑
1
5)i
s
S
S(
t
)‑Sx‑(
r
‑
S(
0
)
)
e
x
p(
‑t
/
AT)
(
8
‑
1
6
)
I
ne
qua
t
i
on(
8‑
1
6)S*‑S(
0)i
st
hei
ni
t
i
a
lga
pbe
t
we
e
nt
hede
s
i
r
e
da
nda
c
t
ua
ls
t
a
t
es
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295
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e
pt
i
bl
epo
pul
a
t
i
o
nSi
sde
c
r
e
a
s
e
dbyi
Ⅰ
‑I
NTEGRAL(
I
R,Io)
S‑I
NTEGRAL(
‑I
R,
N‑Io)
(
9‑
1
6)
(
9
1
1
7
)
whe
r
eNi
st
het
ot
a
lpopul
a
t
i
o
汀i
nt
hec
o
mmunl
t
ya
ndI
｡i
st
hei
ni
t
i
a
lnumbe
ro
f
i
nf
e
c
t
i
o
uspe
o
pl
e(
as
ma
l
lnumbe
ro
re
ve
nas
i
ngl
ei
ndi
v
i
dua
l
)
.
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o
r
mul
a
t
et
he
i
nf
e
c
t
i
o
nr
a
t
e
,
c
o
ns
i
de
rt
hepr
o
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e
s
sbywhi
c
hs
us
c
e
pt
i
bl
epe
op
l
ebe
c
o
mei
nf
e
c
t
e
d.
me
a
‑
Pe
o
pl
ei
nt
hec
ommuni
t
yi
nt
e
r
a
c
ta
tac
e
r
t
a
i
nr
a
t
e(
t
heCont
a
c
tRa
t
e
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s
ur
e
di
npe
o
pl
ec
o
nt
a
c
t
e
dpe
rpe
r
s
o
npe
rt
i
mepe
r
i
od,
or1
/
t
i
mepe
r
i
od)
･
Th
ust
he
s
us
c
e
pt
i
bl
epo
pul
a
t
i
onge
ne
r
a
t
eSce
nc
o
unt
e
r
spe
rt
i
mepe
r
i
od.
So
meoft
he
s
ee
n
c
o
unt
e
r
sa
r
ewi
t
hi
nf
e
c
t
i
ouspe
o
pl
e
.
I
fi
nf
e
c
t
i
o
uspe
o
pl
ei
nt
e
r
a
c
ta
tt
hes
a
mer
a
t
ea
s
s
us
c
e
pt
i
bl
epe
o
pl
e(
t
he
ya
r
enotqua
r
a
n
t
i
ne
do
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o
nf
i
ne
dt
obe
d)
,
t
he
nt
hepr
o
ba
‑
bi
l
i
t
yt
ha
ta
nyr
a
ndo
ml
ys
e
l
e
c
t
e
de
nc
o
un
t
e
ri
sa
ne
nc
o
unt
e
rwi
t
ha
ni
nf
e
c
t
i
o
usi
n‑
d
i
v
i
d
ua
li
sI
/
N.
Note
ve
r
ye
nc
o
unt
e
rwi
t
ha
ni
nf
e
c
t
i
o
uspe
r
s
o
nr
e
s
ul
t
si
ni
nf
e
c
t
i
o
n.
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nf
e
c
t
i
vl
t
y
,i
,oft
hed
i
s
e
a
s
ei
st
hepr
o
ba
bi
l
i
t
yt
ha
tape
r
s
onbe
c
ome
si
nf
e
c
t
e
d
a
f
t
e
rc
ont
a
c
twi
t
ha
ni
nf
e
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t
i
ouspe
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s
on.Thei
nf
e
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t
i
o
nr
a
t
ei
st
he
r
e
f
or
et
het
ot
a
l
n
umbe
ro
fe
nc
ount
e
r
sScmul
t
i
pl
i
e
db
yt
hep
r
o
ba
bi
l
i
t
yt
ha
ta
nyo
ft
hos
ee
n
c
o
un
t
e
r
s
i
swi
t
ha
ni
nf
e
c
t
i
o
usi
nd
i
vi
dua
lI
/
Nmu
lt
i
pl
i
e
dbyt
hepr
o
ba
bi
l
i
t
yt
ha
ta
ne
nc
o
u
nt
e
r
wi
t
ha
ni
nf
e
c
t
i
o
uspe
r
s
o
nr
e
s
ul
t
si
ni
n
f
e
c
t
i
o
n:
‑
I
R‑(
c
i
S)
(
Ⅰ
/
N)
(
9
‑
1
8
)
a‑
Thed
yna
mi
c
sc
a
nbede
t
e
r
mi
ne
dbyno
t
l
ngt
ha
twi
t
ho
utbi
r
t
hs
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a
t
hs
,o
rml
g
r
t
i
o
n,
t
het
o
t
a
lpo
pul
a
t
i
oni
sf
i
xe
d:
S+Ⅰ‑N
(
9
‑
1
9
)
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ug
ht
hes
ys
t
e
mc
o
nt
a
i
nst
wos
t
oc
ks
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i
ti
sa
c
t
ua
l
l
yaf
i
r
s
t
‑
o
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de
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ys
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e
mbe
c
a
us
e
o
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ft
hes
t
oc
ksi
sc
o
mpl
e
t
e
l
yde
t
e
r
mi
ne
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t
he
r
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t
i
t
ut
l
ngN IIf
o
rS
i
n(
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e
l
ds
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R‑(
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)
(
i
)
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(
1‑
(
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20)
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t
i
on(
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si
de
nt
i
c
a
lt
oe
q
ua
t
i
o
n(
9‑
1
)
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hene
tbi
r
t
hr
a
t
ei
nt
hel
o
gi
s
t
i
c
mo
de
l
.
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pi
de
mi
c
,i
nt
hi
smod
e
l
,
g
r
owse
xa
c
t
l
yl
i
keapo
pul
a
t
i
o
ni
naf
i
xe
de
n‑
vi
r
o
nme
nt
.
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a
r
r
yl
ngC
a
pa
C
l
t
yi
st
het
o
t
a
lpo
pul
a
t
i
o
n,
N.
I
nt
heSImo
de
l
,
o
nc
e
a
ni
nf
e
c
t
i
o
usi
ndi
vi
d
ua
la
r
r
i
ve
si
nt
hec
o
mmunl
t
y
,
e
ve
r
yS
us
c
e
pt
i
bl
epe
r
s
one
v
e
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t
ua
l
l
ybe
c
ome
si
nf
e
c
t
e
d,
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t
ht
hei
nf
e
c
t
i
o
nr
a
t
ef
o
l
l
owl
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l
l
‑
s
ha
pe
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ur
v
ea
nd
Ch
a
p
t
e
r9 S
I
S
h
a
p
e
dGr
o
wt
h
:
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i
d
e
ic
m
s
,
I
n
n
o
v
a
t
i
o
nDi
fu
s
i
o
n
,
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n
dt
h
eGr
o
wt
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f
Ne
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r
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u
c
t
s3
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t
het
ot
a
li
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e
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t
e
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t
i
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l
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l
a
s
s
i
cSI
S
ha
pe
dpa
t
t
e
r
noft
hel
ogl
S
t
i
c
c
ur
ve(
Fi
gur
e9‑
1
)
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ghe
rt
hec
ont
a
c
tr
a
t
eort
hegr
e
a
t
e
rt
hei
nf
e
c
t
i
vi
t
y,t
he
f
a
s
t
e
rt
hee
pi
d
e
mi
cpr
og
r
e
s
s
e
s
.
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d
e
lc
a
pt
ur
e
st
hemos
tf
unda
me
nt
a
lf
e
a
t
ur
eofi
nf
e
c
t
i
ousdi
s
e
a
s
e
s
:
t
he
di
s
e
a
s
es
pr
e
a
dst
hr
o
ughc
ont
a
c
tbe
t
we
e
ni
nf
e
c
t
e
da
nds
us
c
e
pt
i
bl
ei
ndi
vi
dua
l
s
.
I
ti
s
t
hei
nt
e
r
a
c
t
i
onoft
he
s
et
wogr
oupst
ha
tc
r
e
a
t
e
st
hepos
i
t
i
vea
ndne
ga
t
i
vel
oops
a
ndt
henonl
i
ne
a
r
l
t
yr
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bl
e氏)
rt
hes
hi
f
ti
nl
oo
pdomi
na
nc
ea
st
hes
us
c
e
pt
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bl
e
po
pul
a
t
i
oni
sd
e
pl
e
t
e
d.Thenonl
i
ne
a
r
l
t
ya
r
i
s
e
sbe
c
a
us
et
het
wopopul
a
t
i
onsa
r
e
mul
t
i
pl
i
e
dt
oge
t
he
ri
ne
qua
t
i
on(
91
1
8)
;
i
tt
a
ke
sbot
h as
us
c
e
pt
ibl
ea
nda
ni
nf
e
c
t
i
ous
pe
r
s
ont
oge
ne
r
a
t
eane
wc
a
s
e･
9.
2.
2 Mode!
i
ngAcut
ehf
ect
i
on:TheS旧 Mode!
Whi
l
et
heSImode
lc
a
pt
ur
est
heba
s
i
cpr
oc
e
s
sofi
nf
e
c
t
i
on,
i
tc
ont
a
i
nsma
nys
i
m‑
pl
i
f
yi
nga
ndr
e
s
t
r
i
c
t
i
vea
s
s
umpt
l
OnS
.
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ldoesnotr
e
pr
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e
ntbi
r
t
hs
,de
a
t
hs
,
orml
g
r
a
t
i
on.
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a
t
i
oni
sa
s
s
ume
dt
obehomoge
ne
ous
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l
lme
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r
soft
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c
ommuni
t
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r
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s
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ume
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e
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ve
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ger
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om ot
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s
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s
e
a
s
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l
t
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rpe
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e'
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i
f
e
s
t
yl
es
:
i
nf
e
c
t
i
ve
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r
ea
s
s
ume
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nt
e
r
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c
ta
tt
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a
mea
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ger
a
t
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e
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e
s
.
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r
ei
s
nopos
s
i
bi
l
i
t
yo
fr
e
c
ove
r
y,quar
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nt
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ne,
ori
mmuni
z
a
t
i
on.
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lt
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ea
s
s
umpt
l
OnSC
a
nber
e
l
a
xe
d.
Thes
us
c
e
pt
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bl
epopul
a
t
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s
‑
a
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t
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nt
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ve
r
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s
t
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t
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ve
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e
pr
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nt
e
da
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s
t
i
nc
ti
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di
vi
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l
s
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a
c
hwi
t
has
pe
c
i
f
i
cr
a
t
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ont
a
c
twi
t
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r
s
.
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ddi
t
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t
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n
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e
pr
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e
ntqua
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a
nt
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ne
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l
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r
t
ha
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a
t
hr
a
t
e
s
c
a
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dde
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ndom e
ve
nt
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a
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i
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t
et
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ha
nc
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t
ur
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t
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t
sbe
t
we
e
ns
us
c
e
pt
i
bl
esa
ndi
nf
e
c
t
i
ves
.
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tr
e
s
t
r
i
c
t
i
vea
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e
a
l
i
s
t
i
cf
e
a
t
ur
eoft
hel
ogl
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t
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cmode
la
sa
ppl
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e
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o
e
pi
de
mi
c
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st
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s
s
umpt
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ont
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tt
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e
a
s
ei
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t
ha
f
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e
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t
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vi
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l
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ma
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ni
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e
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t
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ni
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nt
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e
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t
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ua
la
r
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i
ve
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nt
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t
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e
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nt
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e
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t
e
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et
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t
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oni
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e
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g.
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r
pe
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i
mpl
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x)
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e
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t
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e
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s
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e
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t
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o
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nes
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a
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l
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l
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t
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e
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ove
r
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ndt
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t
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a
t
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e
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bl
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t
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ove
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s
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pe
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e
la
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i
ca
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et
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e
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i
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e
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t
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ks
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e
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a
t
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t
heI
r
.
f
e
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t
i
o‑
uspopui
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t
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or
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I
,
a
ndt
heRe
c
ov‑
e
r
e
dpopul
a
t
i
on,良(
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gur
e9‑
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st
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l
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ma
c
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ove
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t
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e
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t
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e
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t
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r
t
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o
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r
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t
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ck
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mi
t
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h
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ec
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t
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i
ndi
vi
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l
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e
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t
e
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ove
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yr
a
t
ea
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hes
ma
l
l
e
rt
henumbe
rofi
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e
c
t
i
ous
pe
opl
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e
ma
i
nl
ng･
Al
lot
he
ra
s
s
umpt
l
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heor
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er
e
t
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ne
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t
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t
i
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t
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nf
e
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t
i
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t
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umul
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t
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st
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c
t
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t
el
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st
her
e
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a
t
e
RRa
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e
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ove
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a
t
i
on良a
c
c
umul
a
t
e
st
her
e
c
ove
r
yr
a
t
e:
S‑I
NTEGRAL(
‑I
R,
N‑ⅠO‑ Ro
)
Ⅰ‑I
NTEGRAL(
I
R‑RR,Io)
良
‑I
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RR,
Ro
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ni
t
i
a
ls
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e
pt
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epo
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a
t
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t
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a
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i
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e
c
t
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vesa
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ni
t
i
a
l
l
yr
e
c
ove
r
e
da
ndi
mmunei
ndi
vi
dua
l
s
.
Ther
e
c
ove
r
yr
a
t
ec
a
nbemode
l
e
ds
e
ve
r
a
lwa
ys
･
I
nt
heSI
Rmode
l
,
t
hea
ve
r
a
ge
dur
a
t
i
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e
c
t
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t
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d,
i
sa
s
s
ume
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ons
t
a
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e
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ove
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es
si
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ume
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of
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l
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r
s
t
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t
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e
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c
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es
s
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‑
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/
d.
(
9‑
2
4)
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ve
r
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gedur
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t
i
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c
t
i
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t
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ve
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a
r
ei
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t
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ove
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yr
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r
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ns
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nt
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Rmo
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t
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l
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e
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o
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t
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e
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t
e
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l
C
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t
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t
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et
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on
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a
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r9 S
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o
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n
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t
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c
t
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pe
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ove
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t
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l
swi
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o
ve
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r
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nf
e
c
t
i
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a
t
ei
sf
or
mul
a
t
e
de
xa
c
t
l
ya
si
nt
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li
ne
qua
t
i
on(
9‑
1
8)
.
9
.
2
.
3 Mo
de=∋
e
h
a
vi
or
:
Th
eTi
ppi
n
gP1
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Unl
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ket
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l
sc
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de
r
e
dt
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r
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t
e
mi
snow s
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or
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r(
t
he
r
ea
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e
nt
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o
nl
yt
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r
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pe
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)
.
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we
ve
r
,
t
hr
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t
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ks
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buts
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nc
et
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ys
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et
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t
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us
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ft
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f
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c
t
i
onr
a
t
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sl
es
st
ha
nt
her
e
c
ove
r
yr
a
t
e,t
hei
nf
e
c
t
i
ouspopul
a
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l
l
.
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t
f
a
l
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s
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e
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t
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a
t
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nf
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i
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nt
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e
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yonec
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a
c
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s
e
a
s
e.
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r
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ums
t
a
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e
swi
l
lt
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nt
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oduc
t
i
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ni
nf
e
c
t
i
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vi
d
ua
lt
o
ur
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t
hei
nf
e
c
t
hepopul
a
t
i
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us
ea
ne
pi
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c?I
nt
ui
t
i
ve
l
y
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ora
ne
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de
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ct
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c
ionr
t
a
t
emus
te
xc
e
e
dt
her
e
c
ove
r
yr
a
t
e;
i
fs
o,t
hei
nf
e
c
t
i
o
uspopul
a
t
i
onwi
l
lg
r
ow,
l
e
a
di
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os
t
i
l
lmor
ene
wc
a
s
es
.
I
f
,whi
l
ee
a
c
hpe
r
s
onwa
si
nf
e
c
t
i
oust
he
ypa
s
s
e
d
t
hedi
s
e
as
eont
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xa
c
t
l
yonemor
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r
s
on,t
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nt
hes
t
oc
kofi
nf
e
c
t
i
ve
swo
ul
dr
e
‑
ma
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t
a
nts
i
nc
et
hei
nf
e
c
t
i
onr
a
t
ewoul
dbej
us
tof
f
s
e
tbyt
her
e
c
ove
r
yr
a
t
e.
ur
,
e
a
c
hi
nf
e
c
t
i
vemus
t
,ona
ve
r
a
ge,
pa
s
st
hedi
s
The
r
e
f
or
e,
f
ora
ne
pi
de
mi
ct
ooc
c
e
a
s
eont
omor
et
ha
noneot
he
rpe
r
s
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l
Ort
Or
e
C
OVe
r
l
ng.
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t
i
onofwhe
t
he
ra
ne
pi
de
mi
cwi
l
loc
c
uri
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e
a
l
l
yaques
t
i
ona
bout
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c
hf
e
e
dba
c
kl
oo
psa
r
edo
i na
m
ntwhe
nt
hedi
s
e
a
s
ea
r
ive
r
si
nac
ommunl
t
y.
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ft
he
pos
i
t
i
vec
ont
a
g
l
Onl
oopdomi
na
t
e
st
her
e
c
ove
r
ya
ndde
pl
e
t
i
onl
oops
,t
he
nt
hei
n‑
t
r
oduc
t
i
onofe
ve
nas
l
ngl
ei
nf
e
c
t
i
vei
ndi
vi
dua
lt
oac
ommunl
t
yt
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l
gge
r
Sa
ne
Pl
‑
de
mi
c.
Thei
nf
e
c
t
i
onr
a
t
ewi
l
le
xc
e
e
dt
her
e
c
ove
r
yr
a
t
e,C
a
us
l
ngt
hei
nf
e
c
t
i
onr
a
t
e
t
ogr
ow s
t
i
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lf
u
r
t
he
r
,unt
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pl
e
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t
hepoolofs
us
c
e
pt
i
bl
esf
i
na
l
l
yl
i
mi
t
st
he
e
pi
de
mi
c.
I
f
,
howe
ve
r
,
t
hepos
i
t
i
vel
oo
pl
SWe
a
ke
rt
ha
nt
hene
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t
i
vel
oo
ps
,
a
ne
p1
‑
de
mi
cwi
l
lnotoc
c
urs
i
nc
ei
nf
e
c
t
i
o
uspe
o
pl
ewi
l
lr
e
cove
rona
ve
r
a
gef
a
s
t
e
rt
ha
n
ne
wc
a
s
e
sa
r
i
s
e
.
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rofne
wc
a
s
e
sc
r
e
a
t
e
dbyea
c
hi
nf
e
c
t
i
vepr
i
o
rt
Ot
he
i
r
r
e
c
ove
r
y
,a
ndt
he
r
e
f
o
r
et
hes
t
r
e
ngt
hoft
hedi
fe
r
e
ntl
oops
,de
pe
ndsont
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ve
r
a
ge
dur
a
t
i
onofi
nf
e
c
t
i
ona
ndt
henumbe
rofne
wc
a
s
esea
c
hi
nf
e
c
t
i
vege
ne
r
a
t
e
spe
r
t
i
mepe
r
i
od.
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ghe
rt
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ont
a
c
tr
a
t
eo
rt
hegr
e
a
t
e
rt
hei
nf
ec
t
i
vl
t
yOft
hedi
s
e
a
s
e,
t
hes
t
r
onge
rt
hepos
i
t
i
vel
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ke
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s
e
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t
hel
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r
ge
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a
c
t
i
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a
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t
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ons
us
c
e
pt
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et
oi
nf
e
c
t
i
on,
t
hewe
a
ke
rt
hede
pl
e
t
i
onl
oop.
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na
l
l
y,
t
hel
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rt
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‑
‑
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wh
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l
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s
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mp
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t
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nt
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o
nt
a
c
tr
a
t
er
i
s
e
sa
bo
vet
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r
i
t
i
c
a
lt
h
r
e
s
hol
doft
wo,
t
hes
ys
t
e
m be
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o
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t
a
bl
e
,a
nda
ne
pi
de
mi
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c
u
r
s
.Thehi
g
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rt
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tr
a
t
e
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he
s
t
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o
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a
g
l
Onl
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t
i
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ove
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yl
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a
ndt
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f
a
s
t
e
rt
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d
e
mi
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og
r
e
s
s
e
s
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he
t
r
,
t
hes
t
r
o
ng
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rt
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t
i
vel
oo
p,
t
heg
r
e
a
t
e
r
t
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i
onul
t
i
ma
t
e
l
yc
ont
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a
c
t
l
ngt
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s
e
a
s
e
.
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ha
nget
ha
ti
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r
e
a
s
e
st
he
s
t
r
e
ngt
ho
ft
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t
i
vel
oo
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l
lyi
e
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ds
i
mi
l
a
rr
e
s
ul
t
s
･
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nc
r
e
a
s
ei
ni
nf
e
c
t
i
v
l
t
y
s
t
r
e
ng
t
he
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i
t
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vel
o
o
pa
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nt
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c
a
l
i
ni
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c
t
t
oa
ni
n
c
r
e
a
s
ei
nc
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nt
a
c
tf
r
e
‑
q
ue
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y.
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nc
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e
a
s
ei
nt
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ur
a
t
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o
no
ft
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nf
e
c
io
t
uspe
r
i
odwe
a
ke
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e
c
ove
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y
l
n
t
･
l
o
o
pa
nda
l
s
opus
he
st
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ys
t
e
mf
a
r
he
t
rpa
s
tt
het
l
P
Pl
ngPO
‑
Exphr
i
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heS旧 ModeI
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mul
a
t
et
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e
rva
r
i
o
usc
ombi
na
t
i
onsofpa
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a
me
t
e
r
s
.Wha
tde
‑
t
e
r
mi
ne
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t
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ra
ne
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mi
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l
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c
ur
?Wha
tde
t
e
r
mi
ne
st
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r
a
c
t
i
onoft
he
po
p
ul
a
t
i
o
nr
e
ma
i
ni
nguni
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e
c
t
e
di
ne
q
ui
l
i
br
i
u
m?Why?
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xa
c
tt
l
ppl
ngpO
l
n
ti
nt
heSI
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lc
a
ne
a
s
i
l
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a
l
c
ul
a
t
e
d.
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ra
ne
pi
de
mi
c
ur
,
t
hei
nf
e
c
t
i
o
nr
a
t
emus
te
xc
e
e
dt
her
e
c
o
ve
r
yr
a
t
e:
t
oo
c
c
I
R>RR=⇒c
i
S(
Ⅰ
/
N)>Ⅰ
/
d
(
9‑
25)
o
re
q
ul
Va
l
e
n
t
l
y
,
c
i
d(
芸)>1
(
9‑
26)
I
ne
qua
t
i
o
n(
9
‑
26)
,
t
hepr
o
duc
to
ft
hec
o
nt
a
c
tr
a
t
ea
ndi
n
f
e
c
t
i
vi
t
yi
st
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i
nf
e
c
t
i
o
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t
a
c
t
spe
rt
imepe
r
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ode
a
c
hi
nf
e
c
t
i
o
uspe
r
s
o
nge
ne
r
a
t
e
s
.
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t
i
pl
yi
ng
byt
hea
ve
r
a
gedu
r
a
t
i
ono
fi
nf
e
c
t
i
on,d,y
i
e
l
dst
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me
ns
i
o
n
l
e
s
sr
a
t
i
oc
i
d,
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mbe
y
:
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we
ve
r
,
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l
lt
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s
ec
o
nt
a
c
t
swi
l
l
bewi
t
hs
us
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e
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bl
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o
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st
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l
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e
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ti
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e.
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e
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t
i
o
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a
c
t
st
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t
ua
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ti
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e
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t
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o
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us
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e
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pe
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o
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l
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t
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i
nf
T
e
c
t
i
ve
se
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ou
nt
e
rs
us
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e
pt
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bl
e
s
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s
umi
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a
t
i
o
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ne
ous
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he
pr
o
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l
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t
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nc
o
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e
r
l
ngaS
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e
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bl
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l
Ve
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e
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l
e
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eo
fs
us
c
e
pt
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bl
e
s
i
nt
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t
i
o
n,S/
N.
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x
pr
e
s
s
i
o
nc
i
d(
S/
N)i
sa
l
s
ok
no
wna
st
her
e
pr
oduc
t
i
on
r
at
ef
o
rt
hee
pi
de
mi
c
｡
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ua
t
i
o
n(
9‑
26)t
he
r
e
f
o
r
ed
e
f
i
ne
st
het
i
p
pi
ngpo
i
n
to
rt
h
r
e
s
h
ol
da
t
whi
c
ha
ne
pi
de
mi
coc
c
ur
si
napo
pul
a
t
i
o
na
ndi
sk
no
wna
st
het
hr
e
s
hol
dt
he
‑
or
e
mi
ne
pi
d
e
mi
ol
og
y
.
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et
ha
tt
hec
o
nt
a
c
tnumbe
rc
a
nbel
a
r
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fi
nf
e
c
ivl
t
t
yi
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ri
ft
hed
ua
t
i
o
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nf
e
c
t
io
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o
ng.
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ur
a
t
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o
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l
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o
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e
a
s
e
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l
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hi
c
ke
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sve
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ys
ho
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t
t
e
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,
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e
a
s
e
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umbe
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e
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ua
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oug
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t
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)
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ve
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l
e
s
s
,
t
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c
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umbe
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o
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i
g
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a
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et
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t
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o
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e
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t
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o
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ss
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o
ng.
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n
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t
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onpe
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o
dpr
l
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rt
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hede
ve
l
o
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n
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l
i
n
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c
a
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e
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ge
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ut1
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a
r
s(
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e
es
e
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t
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o
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2.
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.
r
‑
Ch
a
p
t
e
r9 S
‑
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h
a
p
e
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o
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h
:
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i
d
e
mi
c
s
,
Ⅰ
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t
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o
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f
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r
o
d
u
c
t
s309
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gur
e9‑
8s
howshowt
het
i
ppl
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ntde
pe
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r
a
me
t
e
r
s
.
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ur
ve
i
st
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unda
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ybe
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t
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e
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o
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e
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nt
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et
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i
ghtoft
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ve
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t
hes
ys
t
e
mi
suns
t
a
bl
e
,a
ndt
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r
ei
sa
ne
pi
de
mi
c.
9.
2.
4 ⊆
mmun章
Zat
i
onandt
heEr
adi
cat
i
onofSmaHpox
Thee
xi
s
t
e
nc
eoft
het
i
ppi
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nt(
e
qua
t
i
on(
9‑
26)
)me
a
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ti
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o
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e
t
i
c
a
l
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et
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ompl
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t
eadi
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va
c
c
i
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s
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li
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yt
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i
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et
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e
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e
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t
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ur
t
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e,
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ome
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e
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e.
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e
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e
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ti
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i
c
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t
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t
e
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e
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e
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i
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o
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l
a
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i
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e
a
s
e,bot
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c
hha
vea
ni
ma
l
hos
t
s
)
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rt
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a
pi
di
nl
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us
c
e
pt
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bl
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o
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et
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oughbi
r
hs
t
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gr
a
t
i
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he
de
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a
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nl
t
y.
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l
l
pox,
howe
ve
r
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r
e
nt
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l
l
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s
e
a
s
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ct
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oughoutt
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e
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t
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l
l
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t
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e
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t
i
oni
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t
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c
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e
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t
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ti
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t
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n
t
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r
e
a
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ma
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e
s
e
r
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st
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.
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s
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t
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t
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o
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t
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nt
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e
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i
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e
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t
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et
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or
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l
l
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a
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t
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