Deliang Lei
Writing 116
March 25,2012
Blank/Sample Synthesis Grid
In terms of
Source 1
An improved
curvilinear
gradient method
for parameter
optimization in
complex
biological
models
Source 2
On the
Dynamics of a
General
Predator-Prey
System.
Source 3
Challenges of
living in the
harsh
environments:
A mathematical
modeling study.
Synthesis Area 1
Synth Area 2
Synth Area 3
Synth Area 4
It showed a biological
science study (simulate
the cardiac action
potential waveform)
with mathematical
modeling. Telling us an
efficient way to
evaluation objective
surface.
a biological science
study: predator-prey
model with some
parameters. Telling us
how to analysis the
solution of mathematical
model.
a biological science
study: of prey –
middle predator – top
predator interaction
model with some
parameters (importance
of parameters)
This idea could help
scientists to predict future
behavior or to prove
quantitative hypothesis
test.
Quantitative research
Required: a dataset.
Numerical/ computational
experiment. Data
analysis.
Mathematical model
Understanding a sensible
competing animals’
behavior by use the model.
Quantitative research
Numerical/ computational
experiment. Data
analysis.
Mathematical model
More complicated animals
(3 types) behavior with
harsh environment.
Quantitative research with
more conditions (these
conditions could describe
by the parameters in the
mathematical model)
Numerical/ computational
experiment. Data
analysis.
Telling the parameters is
important for models to
describe different animals’
behaviors.
Complex mathematical
model with multi
parameters.
Iteration/ cycles.
With 3 some parameters
Limited cycles.
Deliang Lei
Writing 116
March 25,2012
Source 4
Modelling the
dynamics of
animal groups
in motion.
a biological science
study: of population
density. Parameters’
influence.
Different large group
animals with 3 types
interaction in these models:
attraction, alignment, and
repulsion.
Source 5
Predicting the
dynamics of
animal
behaviour in
field
populations
a biological science
Gather enough data to
study to predict animals’ predict future animal
behavior.
behavior.
Quantitative research of
animal dynamic in 3
different methods:
mathematical, physical,
and computational.
Showing the influence from
the model parameters when
we modeling the behaviors.
Data analysis and
prediction.
Showing the variability in
the data to predict the
behavior.
Deliang Lei
Writing 116
March 25,2012
Annotated Bibliography
Adam Hill, et al. "An Improved Curvilinear Gradient Method For Parameter Optimization In Complex Biological Models." Medical &
Biological Engineering & Computing 49.3 (2011): 289-296. Academic Search Complete. Web. 25 Mar. 2012.
This article talks about the significant of the parameters in mathematical modeling. It generalize a model of
electrophysiological recording of a cardiac ion channel, to shows us a more efficient and accuracy model with 22 parameters of
finding the global minima in a vast surface, telling us how should we analyze the data with math skills, and the importance of math to
help other scientific aspects to have a more believable result.
This article talks about the important and the difficulty of mathematical modeling, when it applies to other aspects with a vast
dataset and many different conditions. It shows us a general method that mathematicians use to analyze the different dynamic of the
problems.
El-Sheikh, M. M. A, S. A. A. El-Marouf, and Z. M. Alaofy. "On The Dynamics Of A General Predator-Prey System." Journal Of
Mathematics & Statistics 7.4 (2011): 295-301. Academic Search Complete. Web. 25 Mar. 2012.
This is a short article telling us how the authors to generalize a two dimensional predator-prey mathematical model and use it
to analysis the possibility of the dynamic of the competing animals’ existence.
This article gives me a simpler example and tells me how scientists use mathematical modeling to analysis the dataset. The
idea of how to use mathematical model is very similar to An Improved Curvilinear Gradient Method For Parameter Optimization In
Complex Biological Models. Although they are describe two different types of animal dynamic problems, the idea of how to use the
dataset point is similar.
Upadhyay, R.K., V. Rai, and S.N. Raw. "Challenges Of Living In The Harsh Environments: A Mathematical Modeling Study."
Applied Mathematics & Computation 217.24 (2011): 10105-10117. Academic Search Complete. Web. 25 Mar. 2012.
Deliang Lei
Writing 116
March 25,2012
This is a mathematical article generalizes the model of macaque (a type of monkey) lives in the harsh environment. The
authors use this model to study the population of macaque, and the food chain behavior in both normal and harsh environment. The
authors use parameters to make the model become more realistic that fit into the macaque behavior on the Japanese island.
This article is analyzing the linear and non-linear stability of the dynamic of the macaque behavior in extreme conditional
environment. The parameters in the model have a significant effect that leads this model become more realistic.
Lett, Christophe, and Vincent Mirabet. "Modelling The Dynamics Of Animal Groups In Motion." South African Journal Of Science
104.5/6 (2008): 192-198. Academic Search Complete. Web. 25 Mar. 2012.
This article shows the result, significance, and efficient of mathematical modeling, physical modeling, and computational
modeling of the large group of animals behavior. Basically, it shows the interaction of the group dynamic with its neighbours, the
effect of parameters to the different models.
It analyzes the animal dynamics with 3 methods: mathematical, physical, and computational. Notice the computational is most
efficient way of this large group animal dynamic. It shows the complement of different methods.
Joseph G. Galusha, et al. "Predicting The Dynamics Of Animal Behaviour In Field Populations." Animal Behaviour 74.1 (2007): 103110. Academic Search Complete. Web. 25 Mar. 2012.
This article is interesting because it use mathematical modeling and correct data to predict animals’ behavior. It analyze a
group instead for individual, however, the variation among individual can be considerate as a trend of the group behaviors. Therefore,
we might use mathematical modeling to predicting the behavior of both animals and humans.