i
i
Compiled and Edited by:
Tee Yee Kai
Organized by:
Kajang
 2023
ii
Engineering and Science: UTAR LKC FES 2022 Colloquium
© 2023 by UTAR Press
All rights reserved. No part of this publication may be reproduced, stored in a retrieval
system, or transmitted, in any form or by any means, electronic, mechanical, photocopying,
recording, or otherwise, without any prior written permission of the publisher.
Cataloguing-in-Publication
Cataloguing-in-Publication Data Data
Perpustakaan Negara
Malaysia
Perpustakaan
Negara
Malaysia
A catalogue record for this book is available
A
catalogue
record
this book is available
from
the National
Libraryfor
of Malaysia
from the National Library of Malaysia
eISBN 978-967-2477-15-0
eISBN 978-967-2477-15-0
Published by:
UTAR Press
Universiti Tunku Abdul Rahman
Sungai Long Campus
Jalan Sungai Long
Bandar Sungai Long
Cheras 43000, Kajang
Selangor Darul Ehsan
Email: dspm@utar.edu.my
LKC FES Postgraduate Colloquium 2022 organized by:
Lee Kong Chian Faculty of Engineering and Science
Universiti Tunku Abdul Rahman
Sungai Long Campus
Jalan Sungai Long
Bandar Sungai Long
Cheras 43000, Kajang
Selangor Darul Ehsan
Email: teeyk@utar.edu.my
Website: https://lkcfes.utar.edu.my/
iii
Contents
Welcome Message .................................................................................................................................. v
Colloquium Committee .......................................................................................................................... vi
Itinerary ................................................................................................................................................. vii
Foreword .............................................................................................................................................. viii
Keynote Lecture 1: My Journey to Johns Hopkins and Amide Proton Transfer MRI Development ..... 1
Keynote Lecture 2: Why Postgraduate Research Training is Important to Change Your Life? .............. 2
Keynote Lecture 3: Publishing in Web of Science Journals .................................................................... 3
Keynote Lecture 4: Current Technological Development and Future Prospects of Palm Oil Industry in
Malaysia ................................................................................................................................................... 4
Postgraduate Presentation Sessions ......................................................................................................... 5
Abstract ................................................................................................................................................. 11
Applied Engineering 1 ....................................................................................................................... 12
Applied Engineering 2 ....................................................................................................................... 28
Applied Mathematics, Simulation & Computing ............................................................................... 44
Health Science & Technology ........................................................................................................... 60
Green Technology & Sustainable Development................................................................................ 74
Energy, Project & Intelligent Management ........................................................................................ 90
iv
Welcome Message
Dear Distinguished Guests, Postgraduate Students, Ladies and Gentlemen,
We are delighted to welcome you to the 4th Lee Kong Chian Faculty of Engineering and
Science (LKC FES) Postgraduate colloquium 2022.
This year the colloquium is back to the physical mode after being cancelled in 2020 and held
virtually in 2021. We received overwhelming supports from the LKC FES postgraduate
students this year; 87 abstracts were submitted, and 54 postgraduate students registered as
participants. We are grateful for your generous support and hope that this year colloquium can
provide an avenue for our postgraduate students to present their latest research findings and
exchange research ideas and knowledge with their peers and academic staff.
Herewith, a word of special welcome is given to our keynote speakers who are generous to
contribute to our colloquium and share their research experience with us. They are:
1. Prof Dr Zhou Jinyuan, Professor, Department of Radiology, Johns Hopkins
University School of Medicine, USA
2. Prof Dr Chong Kok Keong, Professor, Department of Electrical and Electronic
Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku
Abdul Rahman, Malaysia
3. Prof Ts Dr Yau Kok Lim, Professor, Department of Internet Engineering and
Computer Science, Lee Kong Chian Faculty of Engineering and Science, Universiti
Tunku Abdul Rahman, Malaysia
4. Dr Steven Lim, Assistant Professor, Department of Chemical Engineering, Lee Kong
Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia
Additionally, our special thanks go to our LKC FES Research Centres, Session Chairs, Faculty
General Office (FGO) and all the other committee members for their excellent work and
contribution to the success of this colloquium.
We sincerely wish all of you will enjoy this colloquium and contribute effectively toward it.
Thank each of you for your efforts in making this year colloquium a success.
Yours sincerely,
Colloquium Organizing Committee
v
Colloquium Committee
Chairperson:
Dr. Tee Yee Kai
Program and Registration:
Ts. Dr. Khaw Chwin Chieh, Dr Ng Yee Sern
Centre Chairperson:
1. CPAMR: Dr. Steven Lim
2. CPSE: Ir. Prof. Dr. Lim Yun Seng
3. CRIE: Ir. Dr. Chua Kein Huat
4. CCS: Dr. Denis Wong Chee Keong
5. CAICA: Dr. Ng Oon-Ee
6. CCSN: Prof. Ts. Dr. Lim Eng Hock
7. CMS: Dr. Sim Hong Seng
8. CDRR: Dr. Lim Ming Han
9. CHST: Ir. Dr. Chee Pei Song
10. CSMT: Ir. Ts. Dr. Bernard Saw Lip Huat
11. COSA: Dr. Lim Poh Im
Webmaster:
Mr Choong Ren Jun
Refreshment and Venue Booking:
FGO
Postgraduate Helpers:
Mr Pang Swee Qi, Mr Rami Alhayek, Mr Yong Ming
Ping
vi
Itinerary
Date:
30 November 2022 (Wednesday)
Time:
8.00 am – 5.00 pm
Venue:
Please proceed to KB Level 9 Concourse Area for registration
and breakfast, KB207 will be used for welcoming remarks and
keynote talks
Time
Agenda
08.00 am – 08.45 am Registration & Breakfast (Level 9 Concourse Area)
08.45 am – 09.00 am Welcoming Remarks, KB 207
Dr Yap Wun She
Dean
Lee Kong Chian Faculty of Engineering and Science
Universiti Tunku Abdul Rahman, Malaysia
09.00 am – 10.00 am Keynote Speaker 1: My Journey to Johns Hopkins and Amide
Proton Transfer MRI Development (via Zoom in KB 207)
Prof Dr Zhou Jinyuan,
Professor
Department of Radiology,
Johns Hopkins University School of Medicine, USA
10.00 am – 10.40 am Keynote Speaker 2: Why postgraduate research training is important
to change your life?, KB 207
Prof Dr Chong Kok Keong,
Professor
Department of Electrical and Electronic Engineering
Lee Kong Chian Faculty of Engineering and Science
Universiti Tunku Abdul Rahman, Malaysia
10.40 am – 11.20 am Keynote Speaker 3: Publishing in Web of Science Journals, KB 207
Prof Ts Dr Yau Kok Lim,
Professor
Department of Internet Engineering and Computer Science
Lee Kong Chian Faculty of Engineering and Science
Universiti Tunku Abdul Rahman, Malaysia
11.20 am – 12.00 pm Keynote Speaker 4: Current Technological Development and
Future Prospects of Palm Oil Industry in Malaysia, KB 207
Dr Steven Lim,
Assistant Professor
Department of Chemical Engineering
Lee Kong Chian Faculty of Engineering and Science
Universiti Tunku Abdul Rahman, Malaysia
12.00 pm – 1.00 pm
1.00 pm – 5.00 pm
5.00 pm
Lunch (Level 9 Concourse Area)
Postgraduate presentations (parallel sessions)
KB 607, KB 609, KB 903, KB 502, KB 904, KB 803
Networking session & refreshment (Level 9 Concourse Area)
vii
Foreword
First and foremost, congratulations to the committee members
of LKC FES Postgraduate Colloquium 2022 for their effort and
determination in succeeding this project.
The purpose of the colloquium is mainly to provide a platform
for the postgraduate students in Lee Kong Chian Faculty of
Engineering and Science (LKC FES) to present their recent
works or findings in their fields of research. In addition, this
event also serves as a platform for postgraduate students and
academic staff of LKC FES to exchange ideas and gather
feedback on their research works.
The 4th postgraduate colloquium was participated by LKC FES postgraduate students from five
research areas, namely: Applied Engineering; Applied Mathematics, Simulation & Computing;
Health Science & Technology; Green Technology & Sustainable Development; and Energy,
Project & Intelligent Management. Through these interactions, I believe students will gain
experience in presenting their works and expose themselves to the different fields of research
undertaken by other students in the faculty.
Lastly, I wish and hope that LKC FES Postgraduate Research Colloquium 2022 will be
successfully held, and the students will benefit from the colloquium.
Ts Dr Yap Wun She
Dean
Lee Kong Chian Faculty of Engineering and Science
Universiti Tunku Abdul Rahman
viii
Keynote Lecture 1: My Journey to Johns
Hopkins and Amide Proton Transfer MRI
Development
Prof. Jinyuan Zhou is an MRI physicist. He earned his Ph.D. in
physics from Wuhan Institute of Physics, Chinese Academy of
Sciences, in 1996. After that, he performed a post-doctoral
fellowship on in vivo MRI at Johns Hopkins University, and he
joined the Johns Hopkins faculty in 1999. Dr. Zhou is currently a
Professor in the Department of Radiology and Radiological
Science. Dr. Zhou’s research focuses on developing new in vivo
MRI methodologies to study brain function and diseases. His
major work is on the development of various novel chemical
exchange saturation transfer (CEST) MRI technologies. Together
with his colleagues, he invented the Amide Proton Transfer (APT)
MRI approach, a specific type of CEST imaging, for brain pH imaging and tumor protein
imaging. His initial paper on brain pH imaging was published in Nature Medicine in 2003, and
his initial paper on tumor treatment effect was published in Nature Medicine in 2011. Recently,
he led a panel of 36 international experts in the field to publish consensus recommendations
for APT imaging of brain tumors. For his work in CEST/APT imaging, he was just awarded
the fellowship at the 2022 Annual Meeting of the International Society of Magnetic Resonance
in Medicine (ISMRM) in London, UK.
Abstract: In this talk, I will briefly introduce my journey from Wuhan Institute of Physics,
Chinese Academy of Sciences, to Johns Hopkins University, where I have been working as a
Post-doctoral Fellow, Research Associate, Assistant Professor, Associate Professor, and Full
Professor on a novel molecular MRI technique called Amide proton transfer (APT) imaging
over the past 25 years. The APT-MRI signal depends primarily on the mobile protein amide
proton concentration and amide proton exchange rates (which are related to tissue pH). The
APT technique has been successfully used for non-invasive pH imaging in stroke (where pH
drops) and protein content imaging in tumor (where many proteins are overexpressed). I will
talk about the basic principle of APT imaging at the protein level and review its current
successful applications for imaging of brain tumors, including the detection and grading of
tumors, the assessment of treatment effect versus tumor recurrence, and the identification of
genetic markers. Other clinical application examples, including imaging of stroke, Alzheimer’s
disease, Parkinson’s disease, and traumatic brain injury, will be briefly reviewed. Finally, I will
introduce the challenging issues and the recent consensus recommendations for APT imaging
of brain tumors on 3T MRI systems.
1
Keynote Lecture 2: Why Postgraduate
Research Training is Important to Change
Your Life?
Prof. Dr. Chong Kok Keong received B.Sc. (Hons) 1st class
degree from University of Malaya in 1998 and Ph.D. (Optical
Engineering) degree from Universiti Teknologi Malaysia in
2002. He is also Fulbright visiting scholar in Princeton
University, USA in 2015. He is a chartered engineer registered
under the engineering council, United Kingdom and a certified
HRDF trainer with certificate no. TTT/14963. For research
experience, he has been working in the field of solar energy
engineering for more than 20 years and his research interest
including concentrating solar power, concentrator photovoltaic
system, photovoltaic, and solar thermal system.
He has been honoured to receive Top Research Scientists Malaysia (TRSM) 2018, Malaysia
Toray Science Foundation (MTSF) Science & Technology Award 2017, JCI Ten Young
Outstanding Malaysian (TOYM) Award 2013, Fulbright Scholar Award 2015-16, Gold Award
in PECIPTA’17, as well as UTAR Research Excellence Award 2010 and UTAR Innovation
Excellence Award 2012 & 2014. To honour his contribution in academics & research, he has
been elected as Fellow of Academy of Science Malaysia 2019, Fellow of ASEAN Academy of
Engineering & Technology (AAET) 2018, Global Young Academy 2014, Young Affiliate
Fellow for The World Academy of Sciences (TWAS) 2011, Young Scientist NetworkAcademy of Science Malaysia 2012, and Honorary Treasurer of Fulbright Alumni Association
Malaysia 2018-2020.
He is Associate Editor of Frontiers in Energy Research WoS with Impact Factor 3.858. Besides
and International Journal of Photoenergy (Hindawi) with Impact Factor 2.535
Abstract: In this talk, I would like to share my research journey and experience. As researchers,
we are trained to have independent thinking, know-how to solve problems, innovative and
creative, and continuously self-upgrading. The postgraduate training is an important milestone
after the undergraduate program, which will bring you to the next height of intelligence.
2
Keynote Lecture 3: Publishing in Web of
Science Journals
Prof. Ts. Dr Yau Kok Lim is a Professor at the Department of
Internet Engineering and Computer Science, Lee Kong Chian
Faculty of Engineering and Science, Universiti Tunku Abdul
Rahman (UTAR), Malaysia. He received B.Eng. degree (Hons.)
in Electrical and Electronics Engineering from Universiti
Teknologi PETRONAS, Malaysia, in 2005, M.Sc. degree in
Electrical Engineering from the National University of
Singapore, in 2007, and Ph.D. degree in Network Engineering
from the Victoria University of Wellington, New Zealand, in
2010. He received the 2007 Professional Engineer Board of
Singapore Gold Medal for being the best graduate of the M.Sc.
degree. He is a researcher, a lecturer, and a consultant in applied artificial intelligence,
particularly in the application of reinforcement learning and deep learning to digital marketing,
intelligent transportation systems, and wireless networks. He serves as the Lead Organising
Chair for AICS’22, Vice General Co-Chair for ICOIN’18, Co-Chair for IET ICFCNA’14, and
Co- Chair (Organizing Committee) for IET ICWCA’12. He serves as an Editor for the KSII
Transactions on Internet and Information Systems, and an Associate Editor for IEEE Access.
He is also the Vice-Chair of IEEE Special Interest Group on Big Data with Computational
Intelligence.
Abstract: Participants will enhance their motivation and learn tips to publish in Web of
Science (WoS) journals. It helps participants to understand the impact factor and the review
process and learn the essentials of journal paper writing for winning the hearts of editors and
reviewers. This talk covers four key points. Firstly, motivating the need for publishing inspires
and motivates participants to publish in WoS journals in order to achieve their research and
career goals. Secondly, the journal impact factor explains how publishing in WoS journals can
increase the citations of papers, and hence the h-index of the authors. Understanding this aspect
motivates authors to decide on the right journal for their research papers. Thirdly,
understanding the review process helps participants to understand what the editors and
reviewers are looking for and how to fulfil their requirements. Fourthly, ethics and rules
highlight the need for good practices to get a paper accepted in a WoS journal.
3
Keynote Lecture 4: Current Technological
Development and Future Prospects of Palm
Oil Industry in Malaysia
Dr. Steven Lim is an assistant professor at the Department of
Chemical Engineering, Lee Kong Chian Faculty of Engineering
and Science, Universiti Tunku Abdul Rahman, Malaysia. He is
also the chairperson of the Centre for Photonics and Advanced
Materials Research. He obtained his PhD in Chemical
Engineering from Universiti Sains Malaysia (USM) in 2014.
His research interests revolve around devising sustainable and
cost-effective methods to synthesis renewable energy (biodiesel,
bioethanol and syngas) and other value-added products
(bioplastic, cellulose nanofiber and triacetin) from renewable
sources such as biomass. They encompass multidisciplinary fields and research areas including
heterogeneous catalytic reaction, supercritical fluids, mass transfer, kinetics, thermodynamics,
engine emissions, surface area characterization, waste water treatment, fermentation, ultrasonic
reaction, microwave irradiation, process simulation and life-cycle assessment.
Dr Steven’s ultimate goal is to enable the creation of a sustainable integrated bio-refinery
processing system which can transform our country’s rich agricultural resources and biomass
waste into other high value bio-products in a circular economy. He has published a lot of
researches in high impact journals such as Bioresource Technology, Journal of Hazardous
Material and Journal of Applied Energy. He is also a guest editor for the Sustainability journal.
He has won the prestigious 2022 Tan Sri Emeritus Professor Augustine S H Ong International
Special Award on Innovation and Inventions in Palm Oil - Young Scientist Award and also
listed as one of the Stanford University’s list of top 2% scientists worldwide for single recent
year 2021.
4
Postgraduate Presentation Sessions
Applied Engineering 1
Venue: KB 607
Chairperson 1: Dr. Woon Kai Siong
Chairperson 2: Dr. Low Jen Hahn
Time
Name
1.00 – 1.15 pm
Ang Xiang
1.15 – 1.30 pm
Chai Khem Fei
1.30 – 1.45 pm
Chen Zi Mun
1.45 – 2.00 pm
Chong Woon Shing
2.00 – 2.15 pm
Choong Ren Jun
2.15 – 2.30 pm
Chua Xin Rong
2.30 – 2.45 pm
Danyal Sorayyaei
Azar
2.45 – 3.00 pm
Foong Jun Kit
3.00 – 3.15 pm
Hoo Dick Sang
3.15 – 3.30 pm
Ignatius Lim Yuze
3.30 – 3.45 pm
Jiang, Shengqi
3.45 – 4.00 pm
Jonathan Yong Kai
Yeang
4.00 – 4.15 pm
Khor Jen Feng
4.15 – 4.30 pm
Kiran Nadeem
4.30 – 4.45 pm
Lim Jeng Jit
Title
Formulation of Liquid Binder-Metal Mixture to 3D
Print Carbon Steel via Direct Ink Writing
Strength Performance of Deep Beam with
Embedded Side Plates as New Shear
Reinforcement
Seismic Resistance Lightweight Fiber-Reinforced
Interlocking Concrete Block
Delay-Constrained Backscatter-aided Resource
Allocation
Visual Microphone with Machine Learning:
Intelligent Pixel Selection
Investigation of Parameters that Affect Regenerative
Braking Energy Recovery for Third Rail
Development of Bamboo Fiber-based Biocomposites as an Alternative Reinforcing Material
Visible Light Communication-based Indoor
Positioning System
Mitigation of Harmonic Distortions in Third Rail
Electrical Systems: A Case Study in Malaysia
The Sintering of Three-Dimensional Printed
Zirconia Ceramic
A Load Balance Scheme for UAV-assisted
Heterogeneous Networks
Performance Evaluation of a Multi-stage Solar
Distiller in Malaysian Weather
An Improved Monthly Oil Palm Yield Predictive
Model in Malaysia
Three-dimensional Array as an Enabling
Technology for 5G Wireless Networks
Silicone Rheological Behavior Modification for
Extrusion-based 3D Printing
5
Page
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14
15
16
17
18
19
20
21
22
23
24
25
26
27
Applied Engineering 2
Venue: KB 609
Chairperson 1: Dr. Ong Chuan Fang
Chairperson 2: Ir Ts. Dr. Bernard Saw Lip Huat
Time
Name
1.00 – 1.15 pm
Lim Wei Han
1.15 – 1.30 pm
Muthukannan
Murugesh
1.30 – 1.45 pm
Ng Wei Wuen
1.45 – 2.00 pm
Nicole Tan Xin Hui
2.00 – 2.15 pm
Ooi Yenn Harn
2.15 – 2.30 pm
Sean Fong Wei Zen
2.30 – 2.45 pm
Sim Sheng Wei
2.45 – 3.00 pm
Subbiah
Alagiasundaram
3.00 – 3.15 pm
Tai Mae Hwa
3.15 – 3.30 pm
Tan Jiun Ian
3.30 – 3.45 pm
Tay Joo Yee
3.45 – 4.00 pm
Tey Wei Lun
4.00 – 4.15 pm
Vinod Ganesan
4.15 – 4.30 pm
Yau Zhi Yong
4.30 – 4.45 pm
Yong Cherng Liin
Title
Lightweight CNN Model for Near Real-time
Wood Defects Detection on Embedded
Processors
Compact Ring Antennas with High-impedance
Line Loaded with Distributed Inductors for Onmetal Tag Design
Preparation of Self-healable Nafion-PVA Proton
Exchange Membranes from Freeze-Thaw Method
for Direct Methanol Fuel Cells
Machine Learning for Human Detection and
Identification Using Radiofrequency Sensors
Implementing Industry 4.0 and Lean Practices for
Business Performance in Malaysian Manufacturing
Firms
Investigate the Performance of Liquid Based
Binder for Three-Dimensional Stainless Steel
Printing Using Direct Ink Writing Method
Development of Fleet Management Algorithm for
AGV in Factory-like Environment
Compact Hybrid Dipole-Loop Antenna for Onmetal UHF RFID Tag Design
Development of Self-healing Sulfonated Poly
(ether ether ketone)-based Membrane for Durable
Direct Methanol Fuel Cell (DMFC)
Design and Optimization of Omnidirectional Tag
Antenna for On-Metal RFID Tagging Applications
Development of Microporous Breathable
Polyethylene Film using Different Types of Linear
Low-Density Polyethylene with Calcium Carbonate
as Filler
Adaptive Fourier Single-pixel Imaging Based on
Probability Estimation
Development of a Conductive Transparent
Graphene/PEDOT:PSS film
Switchable Multiwavelength Brillouin Raman Fiber
Laser via Power Coupling Optimization
Human Tracking and Following using Machine
Vision on a Mobile Service Robot
6
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30
31
32
33
34
35
36
37
38
39
40
41
42
43
Applied Mathematics, Simulation & Computing
Venue: KB 903
Chairperson 1: Dr. Sim Hong Seng
Chairperson 2: Dr. Denis Wong Chee Keong
Time
1.00 – 1.15 pm
1.15 – 1.30 pm
Name
Chan Tai Chong
Ganesh
Subramaniam
1.30 – 1.45 pm
Gillian Woo Yi Han
1.45 – 2.00 pm
Kenneth Lee Kai
Fong
2.00 – 2.15 pm
Kenny Chu Sau Kang
2.15 – 2.30 pm
Kevin Yew Choon
Liang
2.30 – 2.45 pm
Koay Yeong Lin
2.45 – 3.00 pm
Tai Yu Bin
3.00 – 3.15 pm
Tan Lee Hang
3.15 – 3.30 pm
Tang Wen Kai,
Adrian
3.30 – 3.45 pm
Victor Low Jian Ming
3.45 – 4.00 pm
Wai Kok Poh
4.00 – 4.15 pm
Wong Chiong Liong
4.15 – 4.30 pm
Wong Kuan Wai
4.30 – 4.45 pm
Woo Bing Hong
Title
Page
A Study on (m,n)-Centralizer Finite Rings
45
f(Q)-Gravity and Early Universe Cosmology
46
Low-Rank Approximation of Semi-Orthogonal
Matrix with Sparse Constraint
Reassessment of the Curve Number Runoff
Prediction Methodology
Self-tuning PID Controller Based on Deep
Learning Technique
Proximal Gradient Method in Mean-variance
Portfolio Selection
Stochastic Gradient Descent Algorithm with
Multiple Adaptive Learning Rate for Deep
Learning
Multi-bridge Graphs are Anti-Magic.
Road Traffic Noise Mapping with Probabilistic
Simulation Approach
Matrices in Physics Data Processing
Application of Mixture Autoregressive Models for
Intermediate-to-long Term Bus Section Travel
Time Prediction
Water Quality Index Prediction using Long Shortterm Memory (LSTM) Deep Learning Method
with Signal Pre-processing
Robust Control Charts for Outliers and Change
Points Detections
A New Image Encryption Scheme Based on
Hyperchaotic System and SHA-2
Deep Learning Strategy for Computational Single
Pixel Imaging
7
47
48
49
50
51
52
53
54
55
56
57
58
59
Health Science & Technology
Venue: KB 502
Chairperson 1: Dr. Chee Pei Song
Chairperson 2: Dr. Khaw Chwin Chieh
Time
Name
Title
1.00 – 1.15 pm
Abdulrahman
Hussein Abdullah AlHamed
1.15 – 1.30 pm
Choo Ming Jack
1.30 – 1.45 pm
Joana Chan Sing Sien
1.45 – 2.00 pm
Kiruthika Selvakumar
2.00 – 2.15 pm
Kwa Eng Keat
2.15 – 2.30 pm
Lee Kok Tong
2.30 – 2.45 pm
Lim Han Xiang
2.45 – 3.00 pm
Mahbuba Ferdowsi
3.00 – 3.15 pm
Pan Swee Qi
3.15 – 3.30 pm
Rachel Boon Weng
Kei
3.30 – 3.45 pm
Siroshini A/P K
Thiagarajan
3.45 – 4.00 pm
Wong Mei Yi
4.00 – 4.15 pm
Yong Ming Ping
Gait Analysis After Anterior Cruciate Ligament
Reconstruction Using Motion Analysis and
Medical Images
Development of an IoT-based Motion Analysis
System for Telerehabilitation Purpose
Therapeutic Architecture: Role of Nature in the
Healing Process for Cancer Patients
Impact of COVID-19 Pandemic on Existing
Migraine Symptoms Among University Students in
Malaysia: A Cross-Sectional Pilot Study
Study of Effectiveness of Audio Guided Deep
Breathing on Improving the Wellness of Visually
Impaired Group
Skin-alike Smart Biosensor for Monitoring ECG
Signals
Effect of Shoe Cushioning Hardness to Running
Biomechanics
Classification of Syncope Patients from
Physiological Signals Acquired in Head-up Tilt
Table Test
Amide Proton Transfer Magnetic Resonance
Imaging (APT MRI) as a better imaging modality
for brain tumor treatment monitoring
Effect of Running Shoe Cushioning on Muscle
Activation Using OpenSim
Receptor-Mediated AKT/PI3K Signalling and
Behavioural Alterations in Zebrafish Larvae
Reveal Association between Schizophrenia and
Opioid Use Disorder
An Emoji-based Attention Bias Modification
Intervention for Depressive Symptom Severity in
Young Adults
Improving Deep Learning Performance for Small
Dataset in Histopathological Gastric Cancer
Detection
8
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61
62
63
64
65
66
67
68
69
70
71
72
73
Green Technology & Sustainable Development
Venue: KB 904
Chairperson 1: Dr. Steven Lim
Chairperson 2: LAr. Ts. Dr. Beh Jin Han
Time
Name
1.00 – 1.15 pm
Asrin Awang Selan
1.15 – 1.30 pm
Chai Kian Hoong
1.30 – 1.45 pm
Chooi Chee Yoong
1.45 – 2.00 pm
Lai Li Xuan
2.00 – 2.15 pm
Lau Sie Yee
2.15 – 2.30 pm
Nourhan Sherif
Mostafa Hassan
Ibrahim
2.30 – 2.45 pm
Soo Yew Hang
2.45 – 3.00 pm
Tan Hui Wun
3.00 – 3.15 pm
Tan Jia Hui
3.15 – 3.30 pm
Tan Wei Yang
3.30 – 3.45 pm
Tejas Sharma
3.45 – 4.00 pm
Thiresamary Kurian
4.00 – 4.15 pm
Wong Eng Cheong
4.15 – 4.30 pm
Wong Wan Ying
4.30 – 4.45 pm
Yong Zi Cong
Title
Development of Aluminium-Air Battery
MgO Sorbents Modified with Ternary Eutectic
Mixtures for CO2 Removal from Simulated Flue
Gas at Intermediate Temperature
Development of Cellulose Based Magnetic
Responsive Microcapsule for The Removal of
Microbial Pollutant
Sustainability Criteria for Affordable Housing in
Malaysia
Approach to Establish an Industry 4.0 Enabling
Technology Adoption Model
Waste Scavenging and The Informal Settlement: A
Case of El-Zabballen City
Vacuum Assisted Solution Process for Deposition
of High Crystallinity and Uniformity
Methylammonium Lead Iodide Perovskite Film
Phytoremediation of Zinc in Water for
Biosynthesis of Zinc Oxide Nanoparticles using
Hyperaccumulator Plants
Effect of Phase Change Material on the
Productivity of a Passive Solar Still
Development of Magnetic Responsive Polymeric
Microcapsules for the Removal of Methyl Orange
A Short Study on Long Persistent Luminescence
Material and its Application in Perovskite Solar
Cells
Colorimetric-based Biodegradable Film for Zero
and Near-zero Power Ammonia Sensing
Development of Polyethylenimine-Polyacrylic
Acid Polymeric Membrane with Water
Responsive Self-Healing Property for Water
Filtration
Synthesis of Renewable Heterogeneous Acid
Catalyst from Oil Palm Empty Fruit Bunch for
Glycerol-Free Biodiesel Production
Functional and Mechanical Properties of
Lightweight Foamed Macro Polypropylene Fibre
Reinforced Ferrocement Concrete Incorporating
Bio-based and Industrial Waste Aggregate
9
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76
77
78
79
80
81
82
83
84
85
86
87
88
89
Energy, Project & Intelligent Management
Venue: KB 803
Chairperson 1: Ir Dr Wong Jianhui
Chairperson 2: Dr. Seah Choon Sen (Sean)
Time
Name
1.00 – 1.15 pm
Bong Huoy Lih
1.15 – 1.30 pm
Chang Xi Liang
1.30 – 1.45 pm
Chew Siak Kor
1.45 – 2.00 pm
Dylon Lam Hao
Cheng
2.00 – 2.15 pm
Homayun Kabir
2.15 – 2.30 pm
Karim Sherif Mostafa
Hassan Ibrahim
2.30 – 2.45 pm
Kum Yi Tong
2.45 – 3.00 pm
Liew Son Qian
3.00 – 3.15 pm
Miow Xie Cherng
3.15 – 3.30 pm
3.30 – 3.45 pm
Mohammad Omar
Hamid Wagiealla
Muaid Abdulkareem
Alnazir Ahmed
3.45 – 4.00 pm
Ong Wei Heng
4.00 – 4.15 pm
Tung Yew Hou
4.15 – 4.30 pm
Vivien Lai Mei Yen
Title
Recuperation of Regenerative Braking Energy for
DC Third Rail System with Energy Storage
Wearable Flexible Antenna for Microwave
Wireless Power
Development of Disruptive Artificial Intelligence
Prototype for Quantity Surveying Practices
Long Short-Term Memory Recurrent Neural
Network for Estimating State of Charge of Energy
Storage System for Grid Services
Twin Delayed DDPG Based Dynamic Power
Allocation in Internet of Robotic Things
Intelligent Reservoir Operation System Based on
Artificial Intelligence and Meta-heuristics Models
Initiating Innovative Technology-based Health and
Safety Management for Construction Projects
during COVID-19 Pandemic
Comprehensive Modelling for Analyzing the Power
Conversion Efficiency of Polycrystalline Silicon
Photovoltaic Device under Indoor Operating
Conditions
ANN-based Load Controller with Robust Input
Normalization for Energy Saving and Peak Demand
Reduction
Application of Artificial Intelligence in
Optimization Reservoir Management
Application of Convolution Neural Network for
Adaptive Traffic Controller System
Why you’re here COVID-19? You’re affecting my
Company’s Operation: How it Impacting Malaysia
Main Contractor’s Working from Home
Exploring Agile Project Management in the
Malaysian Construction Industry
Operation of Klang Gate Dam: A Comparison of
Reservoir Simulation and Reservoir Optimisation
under Climate Change Impact
10
Page
91
92
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94
95
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99
100
101
102
103
104
Abstract
11
Applied Engineering 1
12
Formulation of Liquid Binder-Metal Mixture to 3D Print Carbon Steel Via Direct Ink
Writing
Xiang Ang1, Jing Yuen Tey1, Wei Hong Yeo1, Pui Yee, Katrina Shak1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Metal 3D printing is growing in popularity in recent years as it enables more
freedom in the design of metal parts. Common metal 3D printing methods fuse metal powders
together to form a solid object using high power laser [1]. There are several disadvantages in
laser-based methods due to significant shrinkage, distortion of the product and requires a
controlled environment. Direct ink writing is another method that extrudes out material onto a
platform to form a solid part. The part can be sintered in a conventional furnace to become a
fully metallic part. However, the study in ink rheology and printability is still lacking in
literature. This research studies different ink formulations and the effect on ink rheology and
printability.
Methods: The ink consists of metal powder and a liquid binder system. The ink rheological
properties were measured using a rotational rheometer. The rheology tests were shear rate,
oscillatory frequency sweep and oscillatory stress sweep tests. A printing test was designed to
quantify the ink printability based on the rheological properties. Thermogravimetric analysis
(TGA) was done on the ink to evaluate the thermal degradation behavior. The 3D printed
samples were sintered in a conventional furnace to become fully metallic products. The final
products were physically and mechanically characterized.
Results: The inks exhibit shear-thinning behavior. Storage modulus was found to be most
significant in ink printability and can be categorized into unprintable (< 1.73 × 107 Pa),
slumping (1.73 × 107 –2.59 × 107 Pa) and printable (> 2.59 × 107 Pa) ranges. The 3D printed
samples were debound at 240 ℃ based on TGA result. The samples were then sintered at
1300 ℃ in a conventional furnace.
Conclusion: Direct ink writing shows promise as a 3D printing method for metallic materials.
Ink rheology were studied to evaluate and quantify the ink printability. The 3D printed samples
were successfully sintered in a conventional furnace.
Reference: 1. Grossin, D., Montón, A., Navarrete-Segado, P., Özmen, E., Urruth, G., Maury,
F., Maury, D., Frances, C., Tourbin, M., Lenormand, P. and Bertrand, G. (2021). A review of
additive manufacturing of ceramics by powder bed selective laser processing (sintering /
melting): Calcium phosphate, silicon carbide, zirconia, alumina, and their composites. Open
Ceramics, 5, p.100073. doi:10.1016/j.oceram.2021.100073.
13
Strength Performance of Deep Beam with Embedded Side Plates as New Shear
Reinforcement
Khem Fei Chai1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: The major design criteria in reinforced concrete deep beam is shear failure,
which many researches had investigated the effect of different shear strengthening method on
the load carrying capacity of beam. The existing alternative shear reinforcement methods for
reinforced concrete beam include: introducing fibre reinforced cementitious matrix on the
external surface of concrete beam, attaching steel reinforcement to the concrete beam
externally, and embedding steel I-beam in the concrete beam. However, each method come
along with respective effect such as delamination of fibre reinforced cementitious matrix and
external steel reinforcement, and steel congestion issue when embedding steel I-beam in a
reinforced concrete beam. The purpose of this research is to investigate the feasibility of
alternative shear reinforcement method which could maintain the load carrying capacity while
resolving the steel congestion issue during deep beam casting. This research proposed a method
which replace the shear link with mild steel plate as alternative shear reinforcement.
Methods: Five number of reinforced concrete deep beams were casted which comprise of one
control specimen, one specimen with mild steel plate without any hole (specimen A) and three
specimens with perforated mild steel plates of different detailing as shear reinforcement
(specimen B, C, and D). All the mild steel plates were of 2 mm thick. All beams were in 1100
mm length x 275 mm depth x 150 mm width. Figure 1 shows the beam detailing for all five
tested specimens. A four-point load test was performed for all the five specimens. The
respective mid-span deflection of the loading was recorded at every 5 kN interval until the
specimen fails.
Figure 1: Specimen detailing
Results: The tested ultimate load bearing capacity of control specimen, specimen A, B, C and
D are 240 kN, 225 kN, 247kN, 242kN, and 235 kN respectively. Meanwhile the mid-span
deflection at ultimate load are 7.27 mm, 18.39 mm, 8.53 mm, 7.53 mm and 8.57 mm
respectively. The result shows that Specimen A recorded the lowest ultimate load carrying
capacity accompanied by the least stiff behaviour among the five specimens. The reason for
this phenomenon could be weak bonding between concrete and flat and smooth surface of mild
steel plate, as Specimen A adopted mild steel plate without any holes as shear reinforcement.
Specimen B, C, and D show similar behaviour as control specimen.
Conclusion: Embedding perforated mild steel plates is a feasible alternative replacement for
conventional shear link in deep beam. As this detailing enable the formation of concrete tenon
in the perforated mild steel plate that promotes sufficient bonding between concrete and mild
steel plate while resolving steel congestion issue in deep beam casting at the same time.
14
Seismic Resistance Lightweight Fiber-Reinforced Interlocking Concrete Block
1
Chen Zi Mun1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: The addition of expanded polystyrene (EPS) beads and the kenaf fiber into the
concrete is for the purpose of obtaining a lightweight concrete and improving the concrete’s
tensile performance. The mix proportions of the expanded polystyrene-kenaf fiber (EPS-KF)
concrete are determined through laboratory testing of the optimum ratio. After determining the
optimum mix proportion, the EPS-KF concrete is applied as a concrete interlocking block and
subjected to shaking table test to study its dynamic response to seismic activity.
Methods: The water/cement ratio used was 0.4. There were 15 cube specimens for
compression test, 15-cylinder specimens split tensile test and 15 beam specimens for flexural
strength test, with the dimensions of 100 x 100 x 100 mm, diameter 100 mm x length 200 mm,
and 100 x 100 x 500 mm respectively, were prepared. There were another 18 cube specimens
with the dimensions of 100 x 100 x 100 mm, that were prepared for the use of preliminary
testing. The preliminary testing was done on specimens without kenaf fibers and the
superplasticizer to choose the EPS concrete mix with suitable compressive strength before
incorporating the fibers and also verify its raw characteristics. 22 concrete interlocking blocks
and 22 concrete blocks were produced and assembled as a scaled down segment of a full-size
wall and subjected to shaking table test.
Results: With reference to MS 76:1972 [1], a target strength of a minimum 5.2 N/mm2 was set.
The results have shown that the EPS-KF can achieve compressive strength higher than the
target, and falls in the range of 7.5 – 9.2 N/mm2, while the tensile strength ranges from 6.5 to
8.5 N/mm2. The concrete interlocking block wall panel which was subjected to the shaking
table test, shows that it can withstand 8 levels of varying frequency and displacement, with no
visible cracks and disintegration of the wall panel. Whereas, the normal concrete block wall
panel was not able to withstand the seismic simulation and collapse at the last level, with visible
cracks observed on the wall panel.
Conclusion: Through this study, it is observed that the addition of expanded polystyrene and
kenaf fiber into the concrete mix yields favourable results in regard to compressive and tensile
strength. The interlocking feature of a concrete block is a promising element that is able to
provide stability in wall structures.
Reference: 1. Malaysian Standard., 1972. MS76:1972 - Specification for bricks and blocks of
fired brickearth, clay or shale part 2: metric units.
15
Delay-Constrained Backscatter-aided Resource Allocation.
WoonShing Chong1, YingLoong Lee1, MauLuen Tham1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Backscatter communication is a key enabling technology to realize energyefficient communication. The effective capacity (EC) concept [1] allows the system to achieve
the expected throughput under the specific statistical delay quality-of-service (QoS)
requirements. This paper aims to develop an effective energy efficiency (EEE) resource
allocation scheme for backscatter communication based on the EC concept by jointly
optimizing the transmit power and reflection coefficient.
Methods: Firstly, the optimal reflection coefficient is obtained by setting the energy harvesting
equal the transmitter circuit power consumption and undergoing mathematical calculations.
With the optimal reflection coefficient, the objective function becomes convex-based. The
optimal power allocation is solved using Dinkelbach’s method and Lagrangian method. The
lagrange multiplier is updated using the subgradient method.
Results: The performance evaluation of the
proposed scheme is carried out using MATLAB
software where it is compared with a baseline, socalled the Max-Min scheme from [2]. Figure 1
shows that the proposed scheme outperforms the
baseline. The EEE decreases with increasing
delay-QoS which implies the trade-off between
huge EEE and lower delay-QoS.
Conclusion: At the end of the research, it is
expected that a delay-constrained backscatteraided resource allocation scheme will be developed
and the superiority of the proposed scheme will be
compared with the baseline scheme.
Figure 1: Performance comparison
for effective energy efficiency
versus different values of
delayQoS.
References: 1. Dapeng Wu and Negi, R. (2003). Effective capacity: A wireless link model for
support of quality of service. IEEE Transactions on Wireless Communications, 24(5), pp.630–
643. doi:10.1109/twc.2003.814353.
2. Yang, H., Ye, Y. and Chu, X. (2020). Max-Min Energy-Efficient Resource Allocation for
Wireless Powered Backscatter Networks. IEEE Wireless Communications Letters, [online]
9(5), pp.688–692. doi:10.1109/LWC.2020.2965942.
16
Visual Microphone with Machine Learning: Intelligent Pixel Selection
1
Ren Jun, Choong1, Wun She, Yap1, Yee Kai, Tee1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Sound is caused by vibrating objects, and vibrating objects cause sound. But
sound may not travel through the air as well as light can. An object’s vibrations, recorded by a
camera at a distance can be extracted and converted into sound, even when the sound can’t be
heard at the camera’s location. However, existing methods for the sound recover use the whole
video frame, where a large number of pixels without meaningful vibration information leads to
a poor recovered sound quality. Improvements suggested were purely based on observing
image features to select patches of pixels.
Methods: In this study, we show that taking pixel intensity changes as a function alone are
sufficient for sound recovery. Furthermore, to improve the recovered sound quality, we train a
convolutional neural network (CNN) to make a no-reference prediction of a particular sound
signal’s signal-to-noise ratio, enabling us score each of the pixels. Finally, under the
assumption that the noise has a mean of 0, we select the top n % of pixels in a video, and sum
them up after shifting them in time to ensure that the actual sound signal constructively
interferes, while the noise destructively interferes. We compare our proposed CNN against an
existing voice activity likelihood (VAL) prediction algorithm.
Results: Our proposed CNN has better precision at ranking the pixels than the voice activity
likelihood algorithm, where for a small number of pixels of the highest scores, the sound
recovered from summing the pixel intensity changes as a function of time is better with the
pixels picked by the CNN than the pixels picked by the VAL. Furthermore, as can be seen in
Figure 1, in the second row where the video has a strong image noise, the VAL fails to work,
while our proposed CNN can still function, showing its robustness in dealing with a wide range
of signal-to-noise levels.
Figure 1: From left to right: heatmap of normalized sound quality scores as predicted by the
proposed CNN, representative video frame, heatmap of normalized sound quality scores as
predicted by the VAL algorithm
Conclusion: We have shown in this work that the individual pixel intensity changes contain
sufficient vibration for sound recovery from object vibrations in silent videos, and shown that
our proposed no-reference sound quality predictor is more precise at ranking sound signal
quality, while being robust enough to handle a wide range of signal-to-noise levels.
17
Investigation of Parameters that Affect Regenerative Braking Energy Recovery for
Third Rail
Xin Rong Chua1, Kein Huat Chua1, Lee Cheun Hau1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Regenerative braking energy recovery can improve the energy efficiency of the
electrical railway system (ERS), reduce the carbon dioxide emissions, and reduce the operating
costs. This paper aims to investigate the key parameters that affect the regenerative braking
energy (RBE) recovery of a DC ERS. A third rail system has been modelled using the ETAPEtrax software based on the data provided by the rail operator. The effects of the speed limit,
track elevations, track curvature, and headway time have been analysed and evaluated.
Methods: Electrical Transit and Analysis Program (ETAP) power system software is used to
perform the system analysis for the electrical distribution network based on the data of MRT
line 2. This study imitates the train travelling under different headway time and track scenarios,
for instant, straight track, elevated track, and curved track. Each of the track scenario will be
studied in simulation to investigate its impact on the energy consumption and the recuperation
of braking energy of a train.
Results: The results showed that the track’s elevation has the highest affect in energy
consumption which is difference 6.25 kWh for every 10 m of the elevation increase. While, the
speed limits have the most significant variation on the amount of RBE recovery which is 14.55
kWh variation. Besides, the variation of headway time also gives an impact on the amount of
the regenerative braking energy. The most optimum headway time for MRT line 2 is 3 minutes
which can save up to 2.2 kWh per trip. In short, utilizing the regenerative braking energy has
shown a significant amount of around 231.6 kWh of energy saving.
Conclusion: These analyses will improve the accuracy of quantitative regenerative braking
energy under different scenarios for energy storage system sizing.
18
Develepment of Bamboo Fiber Based Bio-Composites as an Alternative Reinforcing
Material
Danyal Sorayyaei Azar1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Today, we are in the midst of a new development, sparked by the introduction
of epoxy polymer composites, a revolutionary type of material characterised by the
combination of disparate individual components that function together to create capabilities
that are greater than the sum of their parts. Additionally, natural fibers such as bamboo promote
promising attributes such as mechanical and chemical properties in which they could be used
in the composites as reinforcements. Bamboo features a hollow part and a thin wall with a
tapering form a macro perspective. Furthermore, in this research in order to enhance the
properties of the bamboo fiber composites some nano-additives such as E-fiber glass will be
added to the mixtures constitute in order to create a hybrid composite. Therefore, the proposed
topic for the research of development of bamboo fiber based bio-composites as an alternative
reinforcing material is intended to find and introduce a suitable and a sustainable candidate to
replace current composites.
Methods: Natural fibres are hydrophilic, and the presence of lignin, pectin, waxy compounds,
and natural oils on the exterior layer of the fibre cell wall creates poor interfacial contact
between the polymer matrix and the fibre, thus in order to overcome this obstacle some forms
of treatments of the fibers such as alkali treatment was carried out. Therefore, the bamboo
fibres were to be extracted utilising NaOH (6% solution) to yield the most suitable results.
Once, the treatment was complete, different sets of fibres were extracted through various
treatment schemes and later they were set to dry after being extracted by hand. The proper
weight and volume ratio of the fibres for the composite were calculated and the epoxy-resin
hardener mixture was prepared. The composite was created in accordance to ASTM D-638.
Once the samples were cured, they were sent for mechanical testing (UTM) and thereafter they
were sent to the conduct further characterization testing (SEM, FTIR, XRD and TGA).
Results: Based on the extracted data from the mechanical testing as well as the characterization
tests, it was found that the alkali treatment of the fibres was a success. This finding was visible
through the FTIR results, was there happened to be a shift in the wavelengths of the data from
untreated bamboo fibres and treated fibres. Secondly, from the UTM testing it was observable
that the composites with 20Vf% (with long and continuous fibres) exerted the highest
mechanical strength. The following data was also backed by the SEM results of the samples.
Conclusion: In conclusion it was observed that the implementation of bamboo fibres was
successful in creating a sustainable bio-composite, where the mechanical as well as the
chemical properties seems to be satisfying and suitable for various structural applications.
19
Visible Light Communication-Based Indoor Positioning System
1
Foong Jun Kit1, See Yuen Chark1, Ng Oon-Ee1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Indoor Positioning System (IPS) is vital for various indoor applications when
Global Positioning System (GPS) signal is insufficient to provide accurate results. Due to the
popularity and advantages of light-emitting diodes (LEDs), visible light communication (VLC)
has drawn the interest of researchers and industries. As a result, VLC-based IPS may be able
to replace or complement radio frequency (RF) based systems. This research is to investigate
the feasibility of the VLC-based IPS by constructing a hardware prototype and analysing the
system performance in various situations.
Methods: The system consisted of multiple LED transmitters and a photodiode (PD) receiver.
The transmitters’ optical signals were modulated with different frequencies using the ESP32
microcontroller. The receiver converts the received signal from optical to electrical, then feed
it into the ADC of the ESP32 microcontroller. Then, the ESP32 processed the signals with fast
Fourier transform (FFT) algorithm and computed the receiver’s coordinate using the
Lambertian direct current (DC) channel gain equation and trilateration algorithm.
Results: Table 1 shows the prototype estimation result with four transmitters in a room with a
dimension of 1 m ✕ 1 m ✕ 0.6 m. The maximum and minimum errors were determined to be
0.645 m and 0.005 m, respectively, with an average error of 0.202 m. This demonstrated that
the VLC-based IPS could be adopted for indoor positioning.
Received Optical
Power -FFT output
Distance1, r1 (m)
Distance2, r2 (m)
Distance3, r3 (m)
Distance4, r4 (m)
Coordinate (xe, ye)
LED Coordinate 22 Coordinate 24 Coordinate 26 Coordinate 28
TX (0.15,0.475) (0.35,0.475) (0.55,0.475) (0.75,0.475)
1
336778.22
276917.28
159704.91
79738.84
2
142769.47
217647.02
361123.06
437871.81
3
409533.47
321077.03
212609.14
126238.12
4
92773.6
145441.8
232521.78
308393.53
0.406615
0.822507
0.171331
0.910546
-0.089,0.513
0.49116
0.571876
0.319129
0.584634
0.345, 0.576
0.746672
0.290484
0.618883
0.354515
0.811, 0.579
1.130985
0.166957
0.917798
0.224959
1.395, 0.698
Table 1: Estimated coordinate and actual coordinate of PD receiver
Conclusion: Current findings showed the proposed VLC-based IPS has an acceptable average
positioning error for indoor navigation. Meanwhile, the prototype’s accuracy in a more
complex scenario is being tested.
20
Mitigation of Harmonic Distortions in Third Rail Electrical Systems: A Case Study in
Malaysia
Dick Sang Hoo1, Kein Huat Chua1, Yun Seng Lim1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: The extensive use of power electronic converters in the third rail system causes
harmonic distortions. High harmonic distortions could cause the overheating of electric
machines and transformers and lead to premature failures of these equipment [1]. It is therefore
important to address the harmonic distortions at the electrical networks. Four operational
scenarios of the rail power supply, which is one normal operation and three degraded operations,
have been investigated. This study can confirm the effectiveness of the single-tuned filters
under various operating operations.
Methods: The simulation studies are carried out by using Electrical Transient and Analysis
Program (ETAP) software to model the distribution network of the Mass Rapid Transit Line 2
(MRT Line 2) in Malaysia. Figure 1Figure shows the simplified electrical network for the third
rail power supply and distribution. The individual voltage harmonic distortion (IHDv) and total
voltage harmonic distortion (THDv) obtained from the simulation studies are benchmarked
against the statutory limits of IEEE 519:2014 standard. Single-tuned filters are placed at the 33
kV feeders to mitigate the harmonic distortions.
Figure 1: Simplified electrical network for the third rail power supply and distribution
Results: The results showed that the 11th and 13th order harmonics are the dominant harmonic
orders due to the use of 12-pulse rectifiers on the third rail system.
Conclusion: The 11th and 13th order harmonics of the third rail system are dominant harmonic
orders in the rail electrical network because the used of 12-pulse rectifiers for providing the
DC supply to the train. This study shows the importance of having harmonics mitigation
devices particularly for degraded operations which are common issues in the real-time
operation of third-rail power systems.
Reference: 1. Hu, H., Shao, Y., Tang, L., Ma, J., He, Z. and Gao, S. (2018). Overview of
Harmonic and Resonance in Railway Electrification Systems. IEEE Transactions on Industry
Applications, [online] 54(5), pp.5227–5245. doi:10.1109/TIA.2018.2813967.
21
The Sintering of Three-Dimensional Printed Zirconia Ceramic
Ignatius Lim Yuze1, Ting Chen Hunt1, Tey Jing Yuen1, Yeo Wei Hong1, Ng Chui Kim2
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
2
Faculty of Engineering & Technology, Tunku Abdul Rahman University College, Malaysia
Introduction: Ceramics like zirconia are difficult to process and fabricate using conventional
methods due to their hardness and brittleness. The conventional methods also come with
drawbacks like long production lead time, high equipment costs and inability to produce
complex geometrics. Fused Deposition Modelling (FDM) is a simple process with relatively
low equipment and material costs, and high accessibility that can produce zirconia parts with
complex geometrics. Hence, a suitable printer and binder system is needed to enable the 3D
printing of zirconia through FDM.
Methods: Zirconia (3Y-TZP) feedstocks with solid loadings from 50 – 68 vol% were prepared
and printed using FDM printer fitted with screw extruder head. The binder system used consists
of 60vol% paraffin wax and 40vol% LDPE. The printed 3Y-TZP samples were fully debound
by a two-step debinding process: solvent debinding (cyclohexane+ethanol) and thermal
debinding (140 – 600°C at 0.2°C/min), followed by sintering (1500°C, 2 hours). TGA was
performed on the feedstock; while bulk density and mechanical properties of the sintered
zirconia samples were measured.
Relative density (%)
Results: The TGA result shows two significant drops in weight starting at 180°C and 380°C,
which corresponds to paraffin wax and LDPE, respectively. A minimum of 40% of soluble
binder was removed from the green sample after solvent immersion for 3 hours at 40°C for
solid loadings of 55vol% and above. Increasing density was observed with increasing solid
loading, with a highest of 97.5% achieved by 68 vol% solid loading (Figure 1). Comparable
Vickers hardness of ~12.3 GPa was achieved for sintered samples printed from 60 – 68 vol%
feedstocks; while fracture toughness of ~5.4 – 5.6 MPa∙m1/2 was obtained.
100
95
90
Relative density
Reference relative density
85
50
55
60
65
Solid loading (%)
70
Figure 1: Relative density of sintered samples (50 – 68 vol%)
Conclusion: 3D printing of 3Y-TZP feedstock via FDM is feasible even with high solid
loadings that is usually difficult to fabricate into flexible filaments and print due to high
viscosity.
22
A Load Balance Scheme For UAV-assisted Heterogeneous Networks
Sheng Qi Jiang1, Ying Loong Lee1, Mau-Luen Tham1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Although the UAV-BS technology is promising for wireless communications
beyond 5G, a number of open issues and challenges need to be addressed for the successful
implementation of UAV-BSs [1]. Especially, the load balancing issues among UAV BSs and
ground users in UAV-assisted heterogeneous networks (HetNets), which are vital for efficient
network resource utilization and quality of service (QoS) provisioning, have been largely
neglected [2]. This study investigated the UAV-BS placement scheme for energy-efficient load
balancing in UAV-assisted HetNets.
Methods: A model which introduces the effective capacity (EC) into fairness function will be
proposed to evaluate the balance state of UAV networks. An algorithm based on the grey wolf
optimizer algorithm is proposed to optimize UAV deployment and user association. And 2
methods are as comparisons: the random deployment (RnD) strategy, and the partitioned
deployment (PD) method.
Results: Figure 1 show the fairness value which is used to evaluate the load status of the
network, and Figure 2 is the loss rate which is used to count the unserved users. The results of
GWO are better than other methods with the same number of users.
Figure 1. Fairness Value
Figure 2. Loss Rate
Conclusion: The results show that the proposed model is efficient to evaluate the balance state
of UAV networks. The proposed algorithm also provides a better solution for the deployment
of the UAV-BSs and the connection status between the UAV-BSs and the ground users.
References: 1. Mozaffari, M., Saad, W., Bennis, M. and Debbah, M. (2015). Drone Small
Cells in the Clouds: Design, Deployment and Performance Analysis. [online] IEEE Xplore.
doi:10.1109/GLOCOM.2015.7417609.
2. Zeng, Y., Zhang, R. and Lim, T.J. (2016). Wireless communications with unmanned aerial
vehicles: opportunities and challenges. IEEE Communications Magazine, 54(5), pp.36–42.
doi:10.1109/mcom.2016.7470933.
23
Performance Evaluation of a Multi-stage Solar Distiller in Malaysian Weather
1
Jonathan Yong Kai Yeang1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Water scarcity has been widely known to be a huge current issue. Even though
seas and oceans cover a total of 97.5% of global water, only 0.5% of water that is found fresh.
Solar distiller can turn water fresh by undergoing desalination. However, the design of solar
distiller was underutilized as it does not make use of the latent heat released. Also, the lack of
any solar concentrating power (CSP) technology on the solar distiller also resulted in poor
performance in terms of productivity. This study investigated the performance of the proposed
multi-stage solar distiller system with Fresnel lens as an alternative to the expensive CSP
technology.
Methods: Prototype is placed on the rooftop of KB building of Universiti Tunku Abdul
Rahman Sungai Long Campus on the 22nd August 2022, with the readings being taken down
in 1 hour interval from 9:00 am to 7:00 pm. The amount of fresh water produced is measured
with a 25 ml measuring cylinder for each stage. K type thermocouple was used to measure the
temperature of the water. Solar radiation was also measured in an hour interval using a SM206
model solar power meter.
19:00
18:00
17:00
16:00
15:00
14:00
13:00
12:00
11:00
10:00
Time of the day
Cumulative yield obtained in stage 1
Cumulative yield obtained in stage 2
Cumulative yield obtained in stage 3
Cumulative yield obtained in stage 4
Time of the day
Ambient Temperature
1
0.8
0.6
0.4
0.2
0
9:00
Yield, kg/m2
1600
1400
1200
1000
800
600
400
200
0
Solar irradiance, W/m2
40
35
30
25
20
15
10
5
0
9:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
17:00
18:00
19:00
Temperature, °C
Results: Efficiency for the first stage solar distiller and multi-stage solar distiller is calculated
to be 21.33%, with a productivity of 0.09375 g/kJ, and 45.3% with a productivity of 0.18609
g/kJ respectively. Unit cost of first stage is calculated to be around $0.220/L and multi-stage
system will have a unit cost of $0.215/L. As for the multi-stage system, the distribution of yield
obtained was 51.0%, 31.3% and 17.7% for stage 2, stage 3, and stage 4, respectively.
Solar irradiance
Figure 1: Data of solar irradiance and ambient temperature (Left) and the cumulative amount
of water collected by each stage throughout the day (Right)
Conclusion: The proposed design has shown decent productivity, especially the multi-stage
system. Furthermore, the unit costs of both systems are actually really low, which is suitable
to be implemented in remote areas.
24
An Improved Monthly Oil Palm Yield Predictive Model in Malaysia
Jen Feng Khor1, Lloyd Ling1, Wei Lun Tan1, Zulkifli Yusop2
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
2
Centre for Environmental Sustainability and Water Security (IPASA), Universiti Teknologi
Malaysia, Malaysia
Introduction: Oil palm crop yields which are sensitive to the heat stress, are affected by El
Niño that causes drought in Malaysia. This study investigates the direct relationship between
Oceanic Niño Index (ONI) (an index used to measure El Niño) and the monthly oil palm yields
in Malaysia. Furthermore, this study uses an improved model, called Fresh Fruit Bunch Index
(FFBI) [1] to model the impact of El Niño on the oil palm yields in Malaysia.
Methods: FFBI is created with the monthly Fresh Fruit Bunch (FFB) yield data through a
similar calculation method of ONI which is based on the monthly sea surface temperature. The
correlations between FFB and FFBI with ONI were tested using non-parametric Spearman’s
rho correlation test. FFB and FFBI time series forecasting models with ONI as predictor were
created using the Expert Modeler in IBM SPSS Statistics. Residual analyses were conducted
to compare the predictive accuracy of both models.
Results: FFBI model shows higher correlation with ONI compared to FFB model. FFBI model
suggests that oil palm yields in Malaysia could be affected after 2 to 16 months of the
occurrence of El Niño events. The improved FFBI model also shows significantly higher
predictive accuracy (adjusted R-squared = 0.9312) than the conventional FFB model (adjusted
R-squared = 0.8274). The FFBI model forecasts an oil palm under-yield concern in Malaysia
from July 2021 to December 2023 and matches with the actual national oil palm under-yield
trend to date (July 2021 to September 2022).
Conclusion: The FFBI model shows improved predictive accuracy than the conventional FFB
model. Malaysian oil palm yields showed a production downtrend pattern even before the
pandemic market lock down, which strongly suggests that there are other hidden threats that
have plagued the Malaysian palm oil industry for years, other than the climatic factor.
Reference: 1. Khor, J.F., Ling, L., Yusop, Z., Tan, W.L., Ling, J.L. and Soo, E.Z.X. (2021).
Impact of El Niño on Oil Palm Yield in Malaysia. Agronomy, 11(11), p.2189.
doi:10.3390/agronomy11112189.
25
Three-dimensional Array as an Enabling Technology for 5G Wireless Networks
1
Kiran Nadeem 1, Gobi Vethratanam 1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: This research aims to show the proof of concept whether a 3D antenna will be
useful in a 5G network, and the difficulties associated with a 3D. Current 2D planar array
antenna can indeed produce 3D beam scanning. However, the scanning of beam is only
practical within the area of boresight. Once the scanning angle is large, the beam broadens, and
the advantage of scanning is lost. This can be overcome by using multiple arrays. A linear array
can only generate a 2D beam pattern in either the E-plane or H-plane, due to architectural
constraint it can only be beneficial to users working either in E or H-plane. Consequently, 2D
beamforming cannot fully utilise the 3D spatial domain [1]. Utilizing the same technique as
two-dimensional beamforming, three-dimensional beamforming can be performed using
planar array antennas with specific beam pattern properties. In contrast to 2D beamforming,
3D beamforming has the capacity to identify the complete spatial domain by creating beam
patterns in any angular direction [2].
Methods: Printed dipole antenna is selected for 3D array antenna. Elements are placed in three
dimensions to form cubical shaped array configuration. All Simulations are performed on
Computer Simulation Technology (CST. Array Factor Formulas are also derived for threedimensional steering of beam to calculate the phases and injected into antenna element.Feeding
network is also designed for 8-port printed dipole array and simulated on ADS and CST for
verification. Later on, Fabrication of feeding network and 2×2×2 array printed dipole antenna
was tested to measure the results of beam steering.
Results: Beam tilting is achieved at every angle with minimum change in gain in H-plane.
From Table I, it can be seen that, maximum gain is achieved at 0° and minimum at 45-degree
steer angle. The gain difference is about 3.23 dBi.
Phase Shift
0°
10°
20°
30°
40°
50°
60°
Three Dimensional (Scan Angles)
0°
8°
16°
24°
31°
38°
45°
Gain (dBi) (H-Plane)
10.40
10.30
9.78
9.14
8.49
7.75
7.17
Table I: Scan Angles and Gain of 2×2×2 Array Antenna
Conclusion: An array of printed dipole antenna organised in a three-dimensional (3D)
configuration is investigated. The array elements are fed to achieve maximum beam at the front
or broadside and achieves a gain of 10.40 dBi in this direction. Beam scanning over the entire
360° is possible with this 3D configuration.
Reference: 1. Ghasemi, A., Burokur, S.N., Dhouibi, A. and de Lustrac, A. (2013). High Beam
Steering in Fabry–Pérot Leaky-Wave Antennas. IEEE Antennas and Wireless Propagation
Letters, [online] 12, pp.261–264. doi:10.1109/LAWP.2013.2248052.
2. Chataut, R. and Akl, R. (2020). Massive MIMO Systems for 5G and beyond Networks—
Overview, Recent Trends, Challenges, and Future Research Direction. Sensors, 20(10), p.2753.
doi:10.3390/s20102753.
26
Silicone Rheological Behaviour Modification for Extrusion-Based 3D Printing
Lim Jeng Jit1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Silicone elastomer has been widely used in various industries for decades for its
outstanding performance including resistance to extreme temperature, weatherability, thermal
conductivity, chemically inert and bioinert. When it comes to extreme heat or cold situations,
silicone elastomer is capable of withstanding temperature up to 316 ℃ and as low as -52 ℃
with minor changes to its properties. This makes silicone elastomer an ideal material when it
comes to aviation and aerospace where it is used as sealants for panelling, windows and doors.
When it comes to soft tissue reconstruction and modification, silicone has been the top choice
among materials for implant composition, as it has a high level of biocompatibility in the
human body.
Methods: There are three stages to this study. The first stage is to identify what rheological
behaviour is desired in DIW Silicone formulation. This includes running rheological test on
pure Silicone polymers to understand shortcomings of it. The second stage will be
understanding the effect of rheology modifiers on rheological behaviour of silicone formulation.
This is done by studying the individual and the combined effects of said rheology modifiers
using rheology tests. In the final stages, shortlisted silicone formulations will undergo rheology
and mechanical characterisation to provide quantitative comparison against pure Silicone
polymer. These formulations will also be used in 3D printing test to find out their printability.
From the printing results, rheological behaviours can be related back to printability of a
formulation.
Results: Pure Silicone polymer typically
exhibits Newtonian-fluid like behaviour. To
make Silicone polymer printable, an
appropriate amount of nano-silica is
introduced into the formulation. This
transforms Silicone polymer into ideal DIW
ink as it now has gel-like behaviour and is
able to hold its shape. Diving deeper with the
help of rheology tests, it can be observed that
it now behaves like non-Newtonian behaviour
where viscosity decreases with increasing
shear rates. This ensures smooth extrusion
through nozzles. Silicone ink formulation
now has solid-like behaviour as storage
Figure 1: Rheology behaviour of pure silicone
modulus is consistently higher than loss
formula and modified silicone formulation
modulus throughout the range. This gives the
printed structure the ability to sustain its printed shape until complete curing of the formulation.
Conclusion: Nano-silica is found to be the key to a successful DIW silicone formulation as it
gives pure silicone polymer yield stress and shear-thinning behaviour.
27
Applied Engineering 2
28
Lightweight CNN Model for Near Real-time Wood Defects Detection on Embedded
Processors
1
Wei-Han Lim1, Mohammad Babrdel Bonab1, Kein Huat Chua1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Traditionally, wood defect detection is performed by trained labor based on eye
inspection. This method poses several disadvantages including high human error, low
efficiency and inconsistent results. The development of Convolutional Neural Networks (CNN)
allows automatic detection of wood defects based on image data. However, recent
developments focus on using large CNN models which require powerful workstations to
perform inference. This research focuses on developing a real-time wood defect detection
model that can run on embedded processors through a series of optimization. This can benefit
the wood manufacturers especially in developing nations by lowering the barrier to adoption
for automated inspection solutions.
Methods: The YOLOv4-Tiny [1] architecture is selected as the base model for improvements.
A series of optimization focused on model accuracy was then performed. These optimizations
are hyperparameter search via grid search for the initial learning rate, batch size, optimizer type
and scheduler type; data augmentation via random flipping, color jittering and scale jittering;
architectural modifications via Efficient Channel Attention (ECA) [2]. After optimizing for
accuracy, the model is compressed using channel pruning via L1 norm. The model is then tested
on the ARM Cortex-A72 CPU on a Raspberry Pi 4.
Results: The model is able to perform similarly with other State of The Art (SOTA) models
for object detection but has significantly lower model complexity and higher inference speed.
The model is able to run on the ARM Cortex-A72 CPU at near real-time speeds.
Metrics
Value
Mean Average Precision (mAP)
0.8824
Precision
0.8844
Recall
0.8004
FPS (CPU)
7.307
Model Size (MB)
36.81
Table 1: Model performance evaluated on an ARM Cortex-A72 CPU
Conclusion: An extremely lightweight model has been developed for wood defects detection
based on the YOLOv4-Tiny architecture. This research can encourage the development of other
efficient defect detectors capable of inference on low-cost embedded devices.
References: 1. Bochkovskiy, A., Wang, C.-Y. and Liao, H.-Y.M. (2020). YOLOv4: Optimal
Speed and Accuracy of Object Detection. arXiv:2004.10934 [cs, eess]. [online] Available at:
https://arxiv.org/abs/2004.10934.
2. Wang, Q., Wu, B., Zhu, P., Li, P., Zuo, W. and Hu, Q. (2020). ECA-Net: Efficient Channel
Attention for Deep Convolutional Neural Networks. arXiv:1910.03151 [cs]. [online]
Available at: https://arxiv.org/abs/1910.03151.
29
Compact Ring Antennas with High-impedance Line Loaded with Distributed
Inductors for On-metal Tag Design
1
Muthukannan Murugesh1, Eng-Hock Lim1, Pei-Song Chee1, Yong-Hong Lee1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Radio Frequency Identification (RFID) is an advanced technology that has
received much attention in recent years due to its many practical applications. The passive
ultra-high-frequency (UHF) RFID tags, which are usually designed to contain a microchip and
a radiating antenna without involving any power sources, are commonly used for tracking and
identifying physical objects [1]. In some applications, the UHF RFID tags are required to be
attached on metal surfaces such as steel plates and containers. However, a label-type tag may
not be working properly on metal as its radiation pattern, input impedance, radiation efficiency,
and resonant frequency can deteriorate significantly due to the existence of the backing metal
[2].
Methods: Two compact UHF tag antennas, which consists of a square ring loaded with two
distributed inductors, are proposed for on-metal applications. Miniaturization of the antenna
footprint is realized through the incorporation of two distributed inductors. It will be shown
that the required inductances are much dependent on their locations on the ring resonator due
to the variation of the current intensity. Due to the high-inductive nature of the distributed
inductor, the antenna resistance of the ring resonator can be significantly enhanced so that it
can achieve a conjugate impedance match with the microchip.
Results: The proposed miniature tag antennas can achieve a far read distance of greater than 9
m on metal when they are tested with an effective isotropic radiated power (EIRP) of 4W.
Important to mention is that the tag resonant frequencies of the proposed tag antennas are stable
and they are not affected much by the backing metallic objects.
(a)
(b)
Figure 1: Configuration of the proposed tag antennas
Conclusion: The proposed tag antennas are compact in size, low in complexity, and low in
profile. It should be mentioned that the tag resonant frequency is also very stable.
References: 1. D. M. Dobkin, 2013. The RF in RFID: Passive UHF RFID in Practice. 2nd ed.,
Elsevier.
2. Marrocco, G. (2008). The art of UHF RFID antenna design: impedance-matching and sizereduction techniques. IEEE Antennas and Propagation Magazine, 50(1), pp.66–79.
doi:10.1109/map.2008.4494504.
30
Preparation of Self-healable Nafion-PVA Proton Exchange Membranes from FreezeThaw Method for Direct Methanol Fuel Cells
Wei Wuen Ng1, Hui San Thiam1, 2, Yean Ling Pang1, 2, Yun Seng Lim1, Jianhui Wong1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
2
Centre for Photonics and Advanced Materials Research, Universiti Tunku Abdul Rahman,
Malaysia
1
Introduction: Direct methanol fuel cell (DMFC) emerges as a viable option to produce
electricity from chemical energy without combustion reaction. Main parts of DMFC compose
of proton exchange membrane (PEM), catalyzed anode and cathode. Nafion is the most
commonly used PEM due to its high proton conductivity and high chemical stability. However,
methanol fuel tends to pass through Nafion from anode to cathode, leading to serious methanol
crossover issue. Methanol crossover reduces fuel efficiency and open circuit voltage, as well
as poisoning the electrode. Furthermore, Nafion membrane is subject to the mechanical
degradation which causes formation of microcracks and pinholes, leading to more severe
methanol crossover. Thus, a self-healable PEM made up of Nafion and PVA is investigated in
this study. Our objective is to develop a Nafion-based PEM with high methanol resistant and
the ability to self-heal to restore its original properties for DMFC applications.
Methods: Nafion-PVA blend membrane was prepared through a simple freezing thawing
method to establish physical crosslinking. Proton conductivity and methanol permeability of
the Nafion-PVA membrane were measured. The self-healing properties of the Nafion-PVA
membrane was examined through scanning electron microscopy and by comparing the
methanol permeability of the membrane before and after self-healing.
Results: Nafion-PVA blend membrane at a weight ratio of 8:2 decreases the methanol
permeability by 40.3 % at the expense of 33.3 % reduction in proton conductivity as compared
to recast Nafion membrane. Figure 1 shows the SEM images of a Nafion-PVA membrane that
has been damaged and subsequently healed, which have proven that the Nafion-PVA
membrane exhibits self-healing function.
Figure 1: SEM images of Nafion-PVA blend membrane when: (a) damaged, (b) after being
healed
Conclusion: Nafion-PVA membrane establishes higher selectivity because of its acceptable
proton conductivity and better methanol blocking properties, as well as its self-healing property,
suggesting the potential use of the Nafion-PVA membrane as PEM in DMFC.
31
Machine Learning for Human Detection and Identification Using Radiofrequency
Sensors
1
Nicole Tan Xin Hui1, Ng Oon-Ee1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Various ambient-based sensor systems have been proposed to overcome the
issue of privacy in human monitoring systems. These systems utilize various ranges of
frequencies on the electromagnetic spectrum to characterise humans based on soft biometrics.
The data involved in these systems are typically processed as spectrograms (2-D images).
Research has shown that the usage of 1D signals is computationally more efficient in other
areas of study. However, not much research has investigated the usage of 1D signals in this
area of study. This study examines the potential of utilizing 1-dimensional signal data on
various machine learning algorithms in a computationally efficient manner without
compromising accuracy.
Method: The setup comprises of a transmitting antenna, a receiving antenna, and a data
processor as depicted in Figure 1. This system utilizes twelve frequencies in the range between
100MHz and 1GHz. Radiofrequency signatures of twenty persons have been collected as they
walked through the antennas. These raw signals were used as the input to nine machine learning
algorithms, and the results were analysed.
Figure 1: Setup of system
Results: It was observed that the ensemble methods produced better results in terms of
accuracy compared to other linear and non-linear algorithms. Specifically, the Extra Trees
classifier obtained the highest rate of accuracy which was comparable to that of the onedimensional convolutional neural network (1D CNN), while requiring less processing time.
Conclusion: Ensemble machine learning algorithms show promise in identifying human
subjects using one-dimensional signal data without compromising accuracy and computational
efficiency.
32
Implementing Industry 4.0 and Lean Practices for Business Performance in
Malaysian Manufacturing Firms
1
Yenn Harn Ooi1, Tan Ching Ng1, Wen Chiet Cheong1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: The global industrial environment had progressed profoundly with the debut of
disruptive Industry 4.0 Digital Technologies (I4.0 DT). As a result, manufacturing firms are
keen on implementing Industry 4.0 with proven Lean Manufacturing Practices (LMP) to
conceive a hybrid robust manufacturing system. As a result, this study aims to investigate the
correlation of LMP, I4.0 DT and business performance (BP) as well as explore the mediating
influence of I4.0 DT on LMP and BP.
Methods: Quantitative study technique was used in this study with a proposed research
framework with four hypotheses formulated as shown in Figure 1. Then, a cross-sectional
questionnaire-based survey was designed and distributed to collect empirical data from
Malaysian manufacturing firms for data analysis. The data collected was assessed and analysed
using Partial Least Square Structural Equation Modelling (PLS-SEM) technique with
SmartPLS software to establish the correlations and confirm the hypotheses.
Results: A total of 124 respondents representing their respective manufacturing firms were
gathered and the findings from the data analysis indicate that all four hypotheses formulated
are supported, where LMP and I4.0 DT are positively correlated with one another as well as
both LMP and I4.0 DT individually are found to have positive effects towards BP. Moreover,
I4.0 DT is also discovered to have mediating effects towards LMP and BP.
Figure 1: Proposed Research Framework
Conclusion: It can be concluded that the proposed research framework is accepted with a
medium predictive power identified establishing their direct and indirect positive correlations.
Therefore, this study successfully reiterates the substantial roles of both I4.0 DT and LMP in
manufacturing firms and the importance of implementing both concurrently in achieving
business excellence.
33
Investigate The Performance Of Liquid Based Binder For Three-Dimensional Stainless
Steel Printing Using Direct Ink Writing Method
1
Fong Sean Wei Zen1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Direct Ink Writing is a material extrusion method that prints at room
temperature. Conventionally, metals are fabricated using formative and subtractive techniques.
Additive manufacturing techniques introduce means of producing complex geometric parts
with low cost especially with low volume production. Commonly, metal printing methods are
limited to the usage of laser or an electron beam which poses a risk of a safety hazard and high
operating cost. This study explores the performance of the binder-metal feedstock for 17-4 PH
stainless steel printing by using the direct ink writing method.
Methods: Several ink components were studied in terms of rheology and printability for the
mapping of the printable region. The rheological effects were quantified based on varying ink
components, namely – metal content, binder concentration and plasticizer. The rheology
properties such as viscosity, static yield, dynamic yield and storage modulus were linked to the
printability via a single wall print test. The printability region is established with a printing
score designation 1-5 on the printability of the formulation based on defined criteria. Further
correlation analysis – Spearman Correlation is applied to identify the dominating rheology
properties and its corresponding ink components to formulate the printable formulation.
Results: The rheology effects showed a clear indication of a positive trend with increasing
metal content and binder concentration. It is observed that the printability of the ink improves
after exceeding a certain rheological requirement. With the Spearman Correlation analysis, the
dominating ink components and rheology properties are the metal content, static yield and
storage modulus. The resulting mechanical performances of the debound and sintered sample
were comparable to the ASTM standards of 17-4PH stainless steel.
Conclusion: The study showcases the capability of utilizing the direct ink writing method for
metal printing application, showing promising results in fabricating complex parts which
conventional machining is unable to produce.
34
Development of Fleet Management Algorithm for AGV in Factory-like Environment
Sheng-Wei Sim1, Ban-Hoe Kwan1, Danny Wee-Kiat Ng1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Nowadays, Automated Guided Vehicles (AGVs) are commonly used to build
up a large-scale robotics transportation system in working plants to replace the human working
force [1]. This research illustrates how to develop a multi-robot system that operates on ROS2
(Robot Operating System 2) based on the Gazebo robotics simulator. The simulation was set
up to be as realistic as possible to represent the operating environment. In this simulation, 3
AGVs were spawned in a factory-like environment and the management algorithm was tested.
Methods: A multi-robot simulation was built based on Zalpha AGV models in a factory-like
environment. 3 Zalpha AGVs were spawned while each of the AGV operates on its own Nav2
stack to perform navigation. In addition, free_fleet from Open-RMF was adopted as a fleet
server to command the AGVs in the simulated world. Fig 1 shows the block diagram of the
proposed system.
Results: A Gazebo instance was started and 3 Zalpha
AGV models with different namespaces were spawned
by using spawn_entity functions. Each model was
equipped with 2 LiDAR sensors and 2 bumper sensors.
Each robot was able to discover other robots that were
working in the same environment through laser scans
provided by the Hokuyo LiDAR. Besides, a map for the
environment was generated and AMCL and Nav2 were
setup according to the method discussed in the previous
section.
Figure 1: Block diagram of the
proposed system
Conclusion: The simulation result is more realistic as it takes consideration of sensors,
localization, and navigation. A fleet server has also been added into the framework to control
the robot. The fleet server only required robots to send in their location information while it
sends back the goal or generated path to the robots. This provides flexibility when doing
experiments with fleet management algorithm.
References: 1. Liu Z, Zhou S.B, Wang H.S, Shen Y, Li H.A and Liu Y.H, “A Hierarchial
Framework for Coordinating Large-Scale Robot Networks”, International Conference on
Robotics and Automation (ICRA). May 2019.
35
Compact Hybrid Dipole-Loop Antenna for On-metal UHF RFID Tag Design
Subbiah Alagiasundaram 1, Kim-Yee Lee 1, Eng-Hock Lim 1, Pei-Song Chee 1, Yong-Hong
Lee 1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: RFID tag antenna is required to be small, insensitive to the platform, high in
gain, and long in reading range. To miniaturize and tune a tag antenna effectively, many
techniques such as shorting stubs, meander slots, and serrated edges can be applied. A loopdipole antenna [1] that comprises an interleaved loop and a pair of dipolar patches was
proposed for the design of a uniplanar antenna for pulmonary edema detection. However, it
can’t be used for on-metal applications. This is because the existence of the metal objects can
detune and deteriorate their antenna performances significantly.
Methods: A pair of a dipole is tactfully integrated with a loop, where a loading patch is
employed for tuning the tag resonant frequency. Without needing tuning mechanisms such as
meandering, vias, and shorting stubs the tag resonant frequency can be brought down to the
regulated UHF passband by adjusting the dimensions of the dipole and the patch.
Results: The tag antenna can achieve a high realized gain of −1.182 dBi in the boresight
direction, which is equivalent to a far read range of 15.3 m. By adjusting the dimension of the
dipole arms as well as the size of the loading rectangular patch, the tag resonant frequency can
be effectively tuned down to the desired UHF passband. It's important to note that the proposed
tag antenna’s tag resonant frequency is stable and is not significantly impacted by the metallic
objects.
c
Microchip
f
y
x
L
d
e
b
a
W
z
x
h1
H h2
h1
Radiator
RT Duroid
6010LM.2
Substrate
Ground
Figure 1: Configuration of the proposed tag antenna
Conclusion: The proposed tag antenna is compact size, low in complexity, low profile and not
affected by backing metallic object.
Reference: 1. Ahdi Rezaeieh, S., Bialkowski, K.S., Zamani, A. and Abbosh, A.M. (2016).
Loop-Dipole Composite Antenna for Wideband Microwave-Based Medical Diagnostic
Systems With Verification on Pulmonary Edema Detection. IEEE Antennas and Wireless
Propagation Letters, [online] 15, pp.838–841. doi:10.1109/LAWP.2015.2476515.
36
Development of Self-healing Sulfonated Poly (ether ether ketone)-based Membrane for
Durable Direct Methanol Fuel Cell (DMFC)
1
Mae Hwa Tai1, Hui San Thiam1, Shiau Foon Tee1, Yun Seng Lim1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: DMFC is a device applying the electrochemical energy conversion mechanism
to convert the chemical energy to electrical energy in a cleaner way. The advantages of DMFC
include high energy efficiency during the application, high energy density at low operating
temperature, simpler system design and ease of handling. However, Nafion, the most
extensively used polymer electrolyte membrane shows several disadvantages that hinders the
performance of the fuel cell including severe methanol crossover, loss of performance after
long period of operation and pricey. The objective of this study is to develop a self-healing
SPEEK-based proton exchange membrane as an alternative to Nafion membranes and examine
the electrochemical performance of the self- healable membrane incorporated DMFCs.
Methods: PEEK was sulfonated to form SPEEK with desired degree of sulfonation. SPEEK
and PVA solutions were mixed in different mass ratio and doping with different percentage of
silica. Once the composite membrane was fabricated, several characterisations were carried out
to justify the performance of the membrane.
Results: Zhang et al. (2017) discovered that poly(vinyl alcohol) (PVA) hydrogel prepared
using the freezing or thawing method can self-repair at room temperature without the need for
any stimulus or healing agent [1]. The proton conductivity of the polymer membrane is
dominated by free water facilitated vehicular mechanism. The improvement of the conductivity
of the proton in the silica filled polymer membrane at medium to higher temperature is due to
the strong interaction between the silica and water resulting in a reduction in the loss of
evaporation of water [2].
Conclusion: The addition of PVA in the membrane structure can lead to an increase in the
presence of modifiable groups. In this way, SiO2 can be efficiently added into the membrane
structure to achieve membrane with superior properties. Hydrogen bonding between SPEEK,
PVA, as well as the silica additives, is expected to contribute to self-healing and improved
transport properties of SPEEK composite membrane. As a result, a self-healing SPEEK-based
membrane as an alternative to commercial Nafion membranes with comparable cell efficiency
is expected to be developed.
References: 1. Zhang, H., Xia, H. and Zhao, Y. (2012). Poly(vinyl alcohol) Hydrogel Can
Autonomously Self-Heal. ACS Macro Letters, 1(11), pp.1233–1236. doi:10.1021/mz300451r.
2. Murmu, R., Roy, D., Patra, S.C., Sutar, H. and Senapati, P. (2021). Preparation and
characterization of the SPEEK/PVA/Silica hybrid membrane for direct methanol fuel cell
(DMFC).
Available
at:
https://www.semanticscholar.org/paper/Preparation-andcharacterization-of-the-hybrid-forMurmuRoy/d6f53321c9ef0c1e089b1272b85bcbefa62b8f75
[Accessed 24 Nov. 2022].
37
Design and Optimization of Omnidirectional Tag Antenna for On-Metal RFID Tagging
Applications
1
Jiun-Ian Tan1, Yong-Hong Lee1, Eng-Hock Lim1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: The Radio Frequency Identification (RFID) is one of the contactless
communication technologies that incorporates the use of electromagnetic waves to track
objects automatically. The ultrahigh frequency (UHF) band, typically ranges from 860 MHz to
960 MHz, is a widely used RFID spectrum. This is because it can provide a faster data transfer
rate and a higher antenna gain than other designated bands that operate at a much lower
frequency. Currently, the UHF RFID technology has a high degree of commercial usage, and
it can be easily found in many industrial applications such as warehouse management,
transportation, animal tracking, patient monitoring, and access control. Tag antenna plays a
crucial role in a typical RFID system. It is used by the tag to communicate with the RFID reader
using radio frequency waves. As such, tag antenna needs to have high gain, miniature size,
wide coverage area, and insensitive to backing platform. Currently, there are very few
omnidirectional tags that can be used for on-metal applications and their read ranges are usually
not more than 7 m.
Methods: Two planar inverted-L antenna
(PILAs), which are placed in a rotational
symmetrical style, can complementing each
other to exhibit a stable omnidirectional
radiation pattern as shown in Fig. 1. Here, a
simple feeding mechanism is employed to
excite both the PILAs simultaneously. As
such, additional circuitry such as Wilkinson
power divider is not required. In addition, the
tag antenna does not require any additional
matching circuit as the antenna input
impedance could be simply modified by
varying the dimensions of the circular loop,
shorting stubs, and notches of the PILAs.
Fig. 1. Orthographic views of the tag antenna
Results: Despite having a miniature size of 35 × 35 × 3.2 mm3, the proposed tag antenna can
produce an omnidirectional radiation pattern with high realized gain of −4.4 dBi in all
directions in the azimuth plane while it is attached on a conductive surface, which is equivalent
to 10.9 m. Meanwhile, the gain variation in the xy-plane is not more than 0.6 dBi, showing that
the antenna is having an even field distribution and good omnidirectional characteristics.
Conclusion: A new type of miniature omnidirectional RFID tag has been designed for metalmountable tagging applications. When the omnidirectional tag is situated on the conductive
surface, it can generate a stable omnidirectional radiation pattern. This is practically useful
when it comes to the applications that require 360-degree coverage.
38
Development of Microporous Breathable Polyethylene Film using Different Types of
Linear Low-Density Polyethylene with Calcium Carbonate as Filler
1
Joo Yee Tay1, Steven Lim1,2, Shee Keat Mah1,2
Department of Chemical Engineering, Lee Kong Chian Faculty of Engineering and Science,
Universiti Tunku Abdul Rahman, Malaysia
2
Centre for Photonics and Advanced Materials Research, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Typically, Ziegler-Natta LLDPE (ZNLLDPE) is mostly served as the polymer
matrix in the microporous film as it provides better tensile strength among the other
polyethylene polymers. However, for most of the synthesized microporous film in the literature
up to date, the trade-off between film breathability and elongation still exists. Therefore, the
objective of this study is to provide a breakthrough to the typical limits of the breathabilityelongation relationship by replacing ZNLLDPE with metallocene LLDPE (MLLDPE) which
has a narrower molecular weight distribution.
Methods: LDPE/ZNLLDPE/Calcium carbonate filler (CC) and LDPE/MLLDPE/CC
microporous films were prepared to investigate the influence of ZNLLDPE and MLLDPE on
the film breathability and elongation. The microporous films were characterized by Scanning
Electron Microscope (SEM) analysis, X-ray Diffraction (XRD) analysis and Particulate
Filtration Efficiency (PFE) analysis, Water Vapor Transmission Rate (WVTR) testing and
mechanical properties testing.
Results: Based on the result, LDPE/MLLDPE/CC film yielded film breathability of 335.73
g/m2 ∙ day which is 95.3% higher than LDPE/ZNLLDPE/CC film due to the higher LDPEMLLDPE film crystallinity and prominent dewetting behaviour between CC and
LDPE/MLLDPE matrix. Moreover, the high degree of tie molecules in MLLDPE enabled the
film to stretch further upon film elongation. Therefore, LDPE/MLLDPE/CC film showed up
to 207.2% comparatively better film elongation than LDPE/ZNLLDPE/CC film.
Conclusion: The improved film breathability and film elongation render the mixture of
LDPE/MLLDPE/CC as a better material for breathable polyethylene glove production. These
improvements were due to the high film crystallinity of LDPE/MLLDPE/CC film and the
prominent dewetting behaviour between CC filler and LDPE/MLLDPE matrix which resulted
in high pore number and large pore diameter. Moreover, LDPE/MLLDPE/CC film
demonstrated better improvement in film elongation than LDPE/ZNLLDPE/CC film as the
high degree of chain entanglement in LDPE/MLLDPE/CC film allowed the film to elongate
further before chain break.
39
Adaptive Fourier Single-pixel Imaging Based on Probability Estimation
1
Wei Lun Tey1, Sing Yee Chua1. Mau-Luen Tham1, Yeong-Nan Phua1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Fourier single-pixel imaging (FSI) is able to reconstruct images by sampling the
information in the Fourier domain. The conventional sampling method of FSI acquires the low
frequency Fourier coefficients to obtain the image outlines but misses out on the image details
in high frequency bands. The variable density sampling method improves the image quality
but follows a predefined mechanism where the power of image information decreases when
frequency increases. An adaptive approach is proposed to sample the Fourier coefficients based
on probability estimation. While the low frequency Fourier coefficients are fully sampled to
secure the image outlines, the high frequency Fourier coefficients are sparsely sampled
adaptively, and the image is reconstructed through Compressed sensing (CS) algorithm.
Methods: Fourier coefficients are fully sampled in the low frequency bands while the high
frequency coefficients are sparsely sampled adaptively. The probability of sampling the next
sampling point is decided based on the Fourier coefficient of the point sampled. This estimation
is repeated in the sampling process until the targeted sampling ratio is met. Finally, the image
is reconstructed using the CS algorithm.
Results: When the sampling ratio SR
increases,
all
four
methods
reconstruct images with better
quality. The proposed adaptive
sampling approach gives the best
image quality for all cases as
compared to the variable density
sampling method.
Conclusion: Based on the results
obtained, the proposed adaptive
sampling method gives better image
quality as compared to the existing
methods.
With
the
adaptive
characteristic of the proposed
sampling approach, it is able to
perform well for various images
while other methods do not work well
in some images with peculiar Fourier
spectrum patterns.
Figure 1: SSIM of USAF chart on different
approach
40
Development of a Conductive Transparent Graphene/PEDOT:PSS Film
1
Vinod Ganesan1, Pei-Song Chee1, Eng-Hock Lim1, Chun-Hui Tan1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Transparent conductive films have received tremendous attention due to their
remarkable optoelectronic properties. Conventional transparent conductive film is usually
made of indium tin oxide (ITO) or fluorine tin oxide (FTO). However, several drawbacks such
as poor mechanical flexibility, inconsistent transmittance, and rarity of the material have
limited their practical applications. Carbon-based materials such as carbon black, carbon
nanotube, and graphene have shown excellent conductivity, carrier mobility, flexibility and
stability. This work proposes a hybrid structure consisting of graphene and PEDOT:PSS coated
on a glass substrate using the spin coating method.
Methods: To coat the graphene on the glass substrate, a graphene dispersion was prepared by
stirring and sonicating the graphene nanoplatelets in a dimethyl sulfoxide solution.
PEDOT:PSS solution was coated on top of glass substrate and left to dry on the hotplate. The
prepared graphene dispersion was later dispensed using a pipette on a glass substrate and spun
at 2000 RPM to form a hybrid thin transparent graphene/PEDOT:PSS layer.
Results: The fabricated hybrid transparent graphene/PEDOT:PSS film was successfully able
to exhibit an optical transmittance of 75.39 % over the spectral window between 350 nm to
800 nm and using the Keithley Electrometer the electrical resistance of the coated sample
showed 4.93 Ωk.
Figure 1: Demonstration of the feasibility to light up LED circuit using the fabricated
transparent hybrid graphene/PEDOT:PSS film
Conclusion: The hybrid transparent film using the composition of graphene and PEDOT:PSS
on an insulating glass substrate based on spin coating techniques was proven to be successful
and able to exhibit optical transmittance of 75.39 % and electrical resistance of 4.93 kΩ.
41
Switchable Multiwavelength Brillouin Raman Fiber Laser via Power Coupling
Optimization
Yau Zhi Yong1, Shee Yu Gang1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: A multiwavelength Brillouin Raman Fiber Laser (MWBRFL) uses nonlinear
optical effects, such as Raman amplification and Stimulated Brillouin Scattering to construct a
multiwavelength fiber laser. Conventional methods to achieve multiwavelength optical sources
are broadband spectrum splicing, laser diode arrays, Brillouin Fiber Lasers(BFL), and Brillouin
Erbium Fiber Lasers(BEFL). However, the MBRFL provides advantages over its other SBS
based fiber laser BFL and BEFL such as stable multiwavelength operation over a wide
wavelength band, significantly higher number of optical channels, improved flatness and
OSNR, while also providing a cost effective and less complicated method compared to other
alternatives such as Micro-ring resonator based Kerr frequency combs. This study investigated
the use of different power coupling in order to find the optimum coupling ratio for 10 GHz and
20 GHz wavelength spacing MWBRFL.
Methods: A Brillouin Pump(BP) laser and Raman Pump(RP) is injected into 7.2 km of
Dispersion Compensated Fiber (DCF). The RP and BP injection power is optimised so that the
SBS threshold can be reached, and a cascading effect occurs due to the Brillouin Stokes lines
generated being amplified by the Raman amplification as well. Different coupling ratios are
used to split and recirculate the power of the RP and BP in order to find a coupling ratio with
switchable wavelength spacing.
Results: Among all the coupling ratios, using a 50/50 coupler for coupler 1 and 80/20 coupler
for coupler two is the only coupling ratio that allows us to achieve both 10 GHz and 20 GHz
wavelength spacing. A maximum of 441 channels and 213 channels could be achieved for 10
GHz and 20 GHz respectively.
Conclusion: By using 50/50 + 80/20 coupler combination, we are able to achieve a switchable
MWBRFL by varying the injection pump power of RP and BP.
42
Human Tracking and Following using Machine Vision on a Mobile Service Robot
1
Cherng Liin Yong1, Ban Hoe Kwan1, Danny Wee-Kiat Ng1, Hong Seng Sim2
Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of
Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia
2
Department of Mathematical and Actuarial Sciences, Lee Kong Chian Faculty of
Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia
Introduction: Service robot technology is rapidly improving to give rise to robust and reliable
machines operating along-side humans. This paper presents a human-following system that can
identify a target human in a crowded environment and track the person’s motion,
simultaneously avoiding obstacles while navigating through the environment.
Methodology; We implement the system on a mobile service robot platform with light
detection and ranging (LIDAR) and RGBD sensors. The system uses a Discriminative
Generative network (DG-net) for human detection. After detection, the localization module
will locate the target person’s position in the environment. The navigation module generates a
cost map of the surroundings for path planning. It allows the robot to navigate the changing
environment avoiding obstacles while tracking the target person.
Results: Experimental results showed that the robot could identify and follow the target person
reliably (Figure 1). At the same time, the robot navigates the crowded environment safely,
avoiding other people and obstacles in the environment. Despite all that, the recovery module
could not recover reliably after losing the target person. Figure 1: The figure shows a
visualization of the path generated during the human-following task.
Figure 1: The figure shows a visualization of the path generated during the human-following
task
Conclusion: We present a novel human following software that uses the state-of-the-art DGnet on a mobile service robot. The software provides reliable and safe human tracking services.
However, the recovery module requires improvement.
43
Applied Mathematics,
Simulation & Computing
44
A Study on (𝒎, 𝒏)-Centralizer Finite Rings
1
Tai Chong Chan1, Kiat Tat Qua1, Denis Chee Keong Wong1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Let 𝑅 be a ring. The centralizer of 𝑟 in 𝑅 is defined as 𝐶𝑅 (𝑟) = { 𝑠 ∈ 𝑅 ∣ 𝑠𝑟 =
𝑟𝑠}. A ring 𝑅 is said to be 𝑛-centralizer ring if 𝑅 has 𝑛 distinct centralizers. The notion of the
𝑛 -centralizer ring first appeared in [1]. In this study, we generalise the notion of the 𝑛 centralizer ring. For any 𝑚 distinct elements 𝑟1 , 𝑟2 , ⋯ , 𝑟𝑚 in a ring 𝑅, the 𝑚-element centralizer
of {𝑟1 , 𝑟2 , … , 𝑟𝑚 } in 𝑅 is defined as 𝐶𝑅 ({𝑟1 , 𝑟2 , ⋯ , 𝑟𝑚 }) = {𝑠 ∈ 𝑅 ∣ 𝑠𝑟1 = 𝑟1 𝑠, 𝑠𝑟2 =
𝑟2 𝑠, ⋯ , 𝑠𝑟𝑚 = 𝑟𝑚 𝑠}, where 𝑚 ∈ ℕ with 𝑚 ≥ 2. We define the set of all distinct 𝑚-element
centralizers in a ring 𝑅 by 𝑚 − 𝐶𝑒𝑛𝑡(𝑅) , where 𝑚 ∈ ℕ with 𝑚 ≥ 2. Further, 𝑅 is called
(𝑚, 𝑛)-centralizer ring if |𝑚 − 𝐶𝑒𝑛𝑡(𝑅)| = 𝑛. The aim of this study is to obtain some new
results on the characterisation of (𝑚, 𝑛)-centralizer ring.
Methods: To develop the main results of this study, the collection and reading of the related
articles will be conducted. At the same time, the mathematical analysis and analytical
computation of the (𝑚, 𝑛)-centralizer ring are carried out. In the meanwhile, to collect more
information on the (𝑚, 𝑛)-centralizer ring, some of the properties and structure of the (𝑚, 𝑛)centralizer ring will be deeply investigated. Also, the verifications and corrections will be
conducted from time to time.
Results: In this study, we have presented some relations between the 𝑛-centralizer finite ring
and (𝑚, 𝑛)-centralizer finite ring. Also, we have computed the value of |𝑚 − 𝐶𝑒𝑛𝑡(𝑅)| for
some finite ring 𝑅. Lastly, we have obtained the characterisation for some (𝑚, 𝑛)-centralizer
finite rings for 𝑛 ≤ 7.
Conclusion: This study can be continued by considering 𝑛 ≥ 8.
Reference: 1. Nath, R., Dutta, J. and Basnet, D. (2015). Characterizing Some Rings of Finite
Order.
undefined.
[online]
Available
at:
https://www.semanticscholar.org/paper/Characterizing-Some-Rings-of-Finite-Order-NathDutta/60d5b5d10ff29d214b95cb0dcd1734012f6809ed [Accessed 24 Nov. 2022].
45
f(Q)-Gravity and Early Universe Cosmology
Ganesh Subramaniam1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Standard big bang cosmology suffers from the early singularity, horizon
problems and some conceptual problems (e.g. treating the matter as a perfect fluid at very high
temperatures despite the classical description of the matter breaks down) whereas in the late
time the universe suffers from Hubble and sigma tensions, and more importantly the
dependencies on the yet undetectable dark sectors to describe the late time acceleration of the
universe. All these mysteries of the universe have motivated researchers to investigate
alternative theories of gravity. Concerning that, f(Q)-gravity as a symmetric teleparallel theory
of gravity has been introduced lately [1]. As in f(R)-gravity where the Ricci scalar, R in
Einstein-Hilbert action is replaced with f(R), a function of R, in f(Q)-gravity this R in action,
S can be replaced with f(Q), where Q is a non-metricity scalar. We studied f(Q)-gravity theory
in the radiation era of the universe with anisotropic Bianchi-1 spacetime as a background
spacetime.
Methods: First, we solve modified field equations for f(Q)-gravity to find the equation of
motion in axially symmetric Bianchi’s universe. The resulting equation of motion consists of
five unknowns therefore two assumptions are required to obtain the exact solutions. Hence, we
considered the barotropic equation of state 𝑝 = 𝜔𝜌 and 𝜎2 ∝ 𝜃 2 , where p is the barotropic
pressure, 𝜔 is the equation of state parameter, 𝜌 is the density, 𝜎2 is the shear scalar and 𝜃 is
the expansion scalar.
1
Results: The resulting model of f(Q) in radiation era (𝜔 = 3 in the barotropic equation of state)
of the universe is 𝑓(𝑄) = 𝑓0 𝑄 2 and this model cannot retrieve general relativity. Furthermore,
we obtained f(Q) = 0 for the pressure-less dust era (p=0) and early vacuum-dominated era (𝑝 =
𝜌 = 0). Apart from that, in pure vacuum, from the density equation of motion, we obtained
f(Q) ∝ √𝑄 . Note that, non-negative Q corresponds to an expansion rate smaller than the shear
scalar (𝜃2 < 𝜎 2 ) throughout cosmic evolution and the universe never isotropizes.
Conclusion: We found that the f(Q)-gravity model under consideration is not isotropizes the
universe and not produces the needed decelerated expansion in the early radiation era which
was required for the formation of the structures as described by modern cosmology [2].
References: 1. J.B. Jimenez, L. Heisenberg and T. Koivisto (2018). Coincident General
Relativity, Phys. Rev. D 98, 044048.
2. A. De, D. Saha, G. Subramaniam and A. K. Sanyal (2022). Probing symmetric teleparallel
gravity in the early universe. http://arxiv.org/abs/2209.12120v1.
46
Low-Rank Approximation of Semi-Orthogonal Matrix with Sparse Constraint
1
Gillian Yi Han Woo1, Hong Seng Sim 1, Yong Kheng Goh 1, Wah June Leong 2
Mathematical and Actuarial Sciences Department, Lee Kong Chian Faculty of Engineering
and Science, Universiti Tunku Abdul Rahman, Malaysia
2
Institute for Mathematical Research, Universiti Putra Malaysia, Malaysia
Introduction: Modern information processing relies heavily on the low-rank decomposition
of the data matrix. A typical low-rank decomposition scenario in data science is given an
observation vector, 𝑦 ∈ 𝑅 𝑚 , on a data matrix V ∈ 𝑅 𝑛1 × 𝑛2 , and one would like to find two
lower rank matrices W ∈ 𝑅 𝑛1 × 𝑟 , and H ∈ 𝑅 𝑛2 × 𝑟 , such that V= W𝐻 𝑇 and rank 𝑟 ≪ min
{𝑛1 ,𝑛2 }. Based on optimisation-based approximations, we would like to investigate the lowrank approximation of a data matrix with a semi-orthogonal structure and sparse prior
constraints:
𝛼
𝛽
min ‖V − 𝑊𝐻 𝑇 ‖22 + ‖𝑊 𝑇 𝑊 − 𝐼‖22 +𝛾‖𝐻‖0
(1)
𝑊,𝐻 2
2
subject to 𝑊 ≥ 0, and 𝐻 ≥ 0,
where 𝛼 > 0, 𝛽 > 0, and 𝛾 > 0. The academic challenge for this project is that the above
optimisation problem is highly non-convex and easily trap in local minima. In this project, we
would like to tackle this optimisation problem with the non-convex alternating minimisation
and, eventually, compare the effectiveness of the resulting low-rank matrices for topical
modelling or image processing.
Methods: In particular, we would like to focus on the non-negative factorisation case, which
resembles the optimisation problem we are interested in solving. Then, the non-convex
alternating minimisation method will be extended to cater to the ‖𝐻‖0 sparsity and semiorthogonal W constraints. We will apply the resulting algorithm to topical modelling or image
reconstruction. The effectiveness of the resulting semi-orthogonal low-rank approximation will
be compared with the outcomes from non-negative matrix factorisation (NMF) [1] and latent
Dirichlet allocation (LDA). During the comparison, we will use perplexity and coherence as
possible comparison metrics.
Results: We have compared LDA and NMF on topic modelling problem. Based on the
experimental results, the NMF method identifies the hidden information with greater coherence
and lesser execution time compared with LDA. For the first step in developing our algorithm,
𝛼
𝛽
we solve min 2 ‖V − 𝑊𝐻 𝑇 ‖22 + 2 ‖𝑊 𝑇 𝑊 − 𝐼‖22 using optimisation approach, steepest
𝑊,𝐻
descent method with the initial 𝑊, 𝐻 obtained from the NMF model with Euclidean distance.
The results show that the topics’ coherence is high and the algorithm converges. 𝑊 also shows
orthogonal structure, which 𝑊 𝑇 𝑊 ≈ 𝐼.
Conclusion: We expect to develop NMF with optimisation method that can decompose a high
dimensional matrix into two low-rank matrices with sparse and orthogonal constraints. This
will benefit the machine learning algorithm for topic modelling and image processing.
Reference: 1. Lee, D.D. and Seung, H.S. (1999) “Learning the parts of objects by non-negative
matrix factorization,” Nature, 401(6755), pp. 788–791.
47
Reassessment of the Curve Number Runoff Prediction Methodology
Kenneth Kai Fong Lee1, Lloyd Ling1, Ren Jie Chin1, Zulkifli Yusof 2
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
2
Centre for Environmental Sustainability and Water Security, Universiti Teknologi
Malaysia, Malaysia
Introduction: The United States Department of Agriculture (USDA) Soil Conservation
Services (SCS) Curve Number (CN) methodology had been widely accepted since 1954 and it
had been incorporated in lots of software, adopted by Malaysian government agencies for flood
retention plannings and even in hydrology textbooks. However, some studies had shown failure
in the prediction of the runoff results based on this methodology. From the data plotting, SCS
field data points were plotted on the logarithmic graph (as shown in Figure 1), while SCS
introduced a linear model (Ia = λS) to correlate the variables, instead of the power-regressed
model of Ia = S0.2. This can be the major reason that led to the failure of runoff prediction. There
is no study analysing this matter yet. If Ia and S correlate differently, the current rainfall-runoff
model will need to be rederived as the fundamental of the model which supports the linear
model was vague.
Methods: The validity of the linear model (Ia = λS) had been analysed under the guidance of
statistics information. Then, the power-regressed model (Ia = Sλ) had been introduced to study
the accuracy and performance of the new calibrated rainfall-runoff model on different regional
datasets from different countries (Malaysia, Greece and China).
Results: The linear model was proven to be statistically insignificant at alpha level of 0.01,
based on previous studies. The introduction of power-regressed model also helps the model to
obtain high runoff amount estimate accuracy (Nash-Sutcliffe model efficiency index from
0.655 to 0.919) for different regional datasets.
Conclusion: The linear model (Ia = λS) had been proven to be statistically insignificant and
power-regressed model (Ia = Sλ) is able to capture the rainfall-runoff data better. The
introduction of power-regressed model into the SCS-CN rainfall-runoff model can improve its
predictive ability, even for different regional datasets.
48
Self-Tuning PID Controller Based on Deep Learning Technique
KennySauKang, Chu1, KuewWai, Chew1, YoongChoon Chang1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: The objective of the PID in the control system is to give a stable system. PID
controller is commonly used in a variety of fields, it is because it is simple to implement.
Unfortunately, there are difficulties to optimize the performance of the controller [1]. When
there are time-variant systems and external influences, the parameters of the system are
required to be adjusted constantly to maintain the performance of the system. Deep learning
model is trained with the data of characteristics of the system, it can be more adaptive to the
system. This study investigated the deep learning model to improve the performance of the
system.
Methods: The experiment was conducted with a DC motor to test out the response of the
system, and the PID controller was optimized with the deep learning model. This deep learning
model is used to find the most suitable combination of the PID gain values. The controller
receives the predicted PID gains values from the DL model to compute accurate PWM signals
for the driver to control the DC motor.
Results: The proposed PID controller is to predict Kp, Ki, and Kd gain values by using the
deep learning model. The deep model was able to extract features in the data, and the predicted
gain values can give a fast response to the system. Figure 1 is the result of the speed test,
compared with the other method. In the speed test of the DC motor, it can perform a 1e-7 rising
time, the steady-state error (%) is around 0.005%, and no overshoot scenario.
Figure 1: Step Response at Different Speeds of the DC Motor
Conclusion: The proposed model has shown good performance and is more flexible for
implementation. DNN is the neural network used for the proposed PID controller in the DC
motor. The model had computed the precise gain values (Kp, Ki, and Kd) to control the system
efficiently.
Reference: 1. Rodriguez-Abreo, O., Rodriguez-Resendiz, J., Fuentes-Silva, C., HernandezAlvarado, R. and Falcon, M.D.C.P.T. (2021). Self-Tuning Neural Network PID With Dynamic
Response Control. IEEE Access, 9, pp.65206–65215. doi:10.1109/access.2021.3075452.
49
Proximal Gradient Method in Mean-Variance Portfolio Selection
Kevin Yew Choon Liang1 Wong Wai Kuan1, Sim Hong Seng1, Goh Yong Kheng1, Pan Wei
Yeing1, Sim Shin Zhu2
1
Centre for Mathematical Sciences, Universiti Tunku Abdul Rahman, Malaysia
2
School of Mathematical Sciences, University of Nottingham Malaysia, Malaysia
Introduction: Markowitz pioneered the construction of portfolios using a mathematical
approach that takes into consideration the computation of return and risk. Nevertheless, the
classical Markowitz’s model has a major drawback: it is extremely sensitive to even the
slightest changes in the mean values, thus leading to poor performance using out of sample
data to construct sample means and sample covariance. Hence, in this study, we improve the
traditional Markowitz portfolio selection method by adding 𝑙0 -norm and 𝑙2 -norm. We also
introduce a proximal spectral gradient method (PSG) to obtain sparse portfolio.
Methods: We compare the efficiency of PSG with Steepest Descent (SD), Multiple Damping
Gradient (MDG), and Proximal Steepest Descent (PSD), using equal weightage (EW) portfolio
as our benchmark. In this paper, we set the convergence tolerance 𝜖 = 10−10 and the sparsity
parameter 𝜇𝑠𝑝𝑎𝑟𝑠𝑒 = 8.12 × 10−4 to obtain 10 active stocks in our optimal portfolio. We stop
(𝑘+1)
the algorithm when |∑𝑥𝑖
− 1|≤ 𝜖. We compute the daily return, 𝑟𝑑𝑎𝑖𝑙𝑦 for every stock
from Bursa Malaysia with the timeframe spanning from 1st January 2018 to 31st December
2018. With these daily returns, we compute the annual return, the standard deviation, the
Sharpe ratio and the Sortino ratio of the stocks. We select 25 Malaysia stocks with a good
Sortino ratio, that is 2 and above, and set them as our dataset throughout the study.
Results: In this study, the portfolio generated by PSG shows the best performance, followed
by the portfolio from PSD. Therefore, sparse portfolio performs better than the benchmark EW
portfolio.
Return (%)
Risk (%)
Methods
Coefficient of
Variation (%)
Sharpe Ratio
Sortino Ratio
2019
2020
2019
2020
2019
2020
2019
2020
2019
2020
EW
19.0863
58.9578
0.0056
0.0279
0.0293
0.0474
0.4683
0.5439
0.8788
0.9291
SD
19.5166
58.7212
0.0056
0.0281
0.0285
0.0479
0.4763
0.5420
0.8896
0.9253
MDG
19.4644
58.7500
0.0056
0.0281
0.0286
0.0479
0.4753
0.5422
0.8883
0.9258
PSD
24.4150
98.3180
0.0094
0.0383
0.0383
0.0390
0.5222
0.8429
0.9098
1.3907
PSG
24.7813
96.7217
0.0095
0.0386
0.0382
0.0399
0.5304
0.8320
0.9223
1.3726
Table 1: The portfolio performance for 1 year timeframe
Conclusion: It is found that the mean-variance portfolio can be efficiently improved by
combining regularization methods with norm constraints on the portfolio weights. The result
shows that the PSG has better performance in terms of Sharpe ratio and Sortino ratio.
50
Stochastic Gradient Descent Algorithm with Multiple Adaptive Learning Rate for Deep
Learning
1
Yeong Lin Koay1, Hong Seng Sim1, Yong Kheng Goh1,Sing Yee Chua1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: The process of training neural networks involves solving optimization problems
heavily. Learning rate or step size is one of the most crucial factors in optimization. Most
practical neural network optimization approaches are based on the stochastic gradient descent
(SGD) method. Since adjustment is needed throughout the training process, the learning rate
of SGD can be challenging to tune. Adaptive methods have been presented as SGD variations
that can use different learning rates for each parameter. Adaptive Moment Estimation (Adam)
[1] is simple to implement and does not need a large amount of memory. However, for these
adaptive learning rate methods, although the different adjusted learning rates are used for
training every iteration, the same learning rate is used for every weight component and bias
component.
Methods: The spectral parameter has been added to tune the learning rate in SGD and Adam.
The proposed method adapts the learning rate in every single component, i.e., every weight
component and bias component. The proposed method uses the approximated inverse Hessian
matrix of the loss function 𝐵 −1 as the tuning parameter. 𝜇𝐵 −1 is a diagonal matrix that
encapsulates the different learning rates in the algorithm.
Results: To illustrate the performance of the proposed method, we applied the proposed
method as the optimization method to train the neural network by using four datasets. The
proposed algorithms were compared with the existing methods SGD and Adam in terms of loss
values. The analysis was performed for different hidden layer sizes and batch sizes. MAdaGrad
performs the best, followed by SGD(Constant) and SGD(Adaptive). As the number of layers
and neurons increases, MAdaGrad still showed the best performance within these methods.
Besides, MAdaGrad Adam also gave better results compared to Adam.
Conclusion: A modified stochastic gradient descent method and a modified adaptive moment
estimation method are proposed. The numerical results show that the proposed methods are
comparable with SGD and Adam. Therefore, MAdaGrad and MAdaGrad Adam can be
alternative optimization methods in machine learning.
Reference: 1. Kingma, D.P. and Ba, J. (2014). Adam: A Method for Stochastic Optimization.
[online] undefined. Available at: https://www.semanticscholar.org/paper/Adam%3A-AMethod-for-Stochastic-Optimization-KingmaBa/a6cb366736791bcccc5c8639de5a8f9636bf87e8.
51
Multi-bridge Graphs are Anti-Magic
Yu Bin Tai1, Gek L. Chia1, Poh-Hwa Ong1
1
Department of Mathematical and Actuarial Sciences, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: An anti-magic graph is a graph whose |E| edges can be labelled with the first |E|
natural numbers such each edge receives a distinct number and each vertex receives a distinct
vertex sum which is obtained by taking the sum of the labels of all the edges incident to it. The
concept of anti-magic graphs has its origin from the book where Hartsfield and Ringel [1]
conjectured that all connected graphs but the single edge 𝐾2 are anti-magic. Since then, the
problem of deciding which graphs are anti-magic has attracted much attention. Other
mathematicians have proved that regular graphs are anti-magic. In view of this, we turn our
attention to graphs which are close to being regular. In other words, the main purpose of this
research is to prove the following result: Every r-bridge graph is anti-magic.
Methods: The proof is divided into three cases. For each case, we specify the number r and
specify the length of each bridge in the r-bridge graph. We label the graph using different
positive integers and prove that it is anti-magic.
Results: We prove that the multi-bridge graph is anti-magic. Currently, we are trying to prove
that multi-bridge graphs with cycle or cycles connected to the only two vertices having r
multiple edges joining them are anti-magic.
Conclusion: Other than multi-bridge graph, there are many graphs which are close to regular
needed to find the anti-magic labelling.
Reference: 1. Hartsfield, N. and Ringel, G., 1994. Pearls in Graph Theory, Academic Press,
Boston, pp. 108-109.
52
Road Traffic Noise Mapping with Probabilistic Simulation Approach
1
Tan Lee Hang1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Noise pollution has been recognised as a significant hazard impacting the
quality of life worldwide [1]. Because of the rapid increase in technology, and transport
systems, noise pollution has reached a disturbing level over the years, which needs to be studied
and controlled. Traffic noise is one of the most impactful noise pollution [2]. Therefore, the
primary concern is investigating and creating a model to predict road traffic noise mapping by
using the probabilistic simulation method. Using the probabilistic method in the road traffic
noise model can predict different complex situations since road traffic conditions are always
dynamic. The probabilistic method is efficient in proving the existence of combinatorial objects
having specific properties [3].
Methods: This project mainly focuses on the fundamentals of noise, noise prediction, and other
relevant information about the topic. The aim and objective of this project is to create a model
by using a probabilistic approach to predict traffic noise mapping and validate the accuracy and
reliability of field measurement. Next, field measurement will be carried out to compare the
model's accuracy. The field measurement was conducted at each sampling location with three
sets of measurements. The result collected from the road was compared with the model.
Results: By using the total sound pressure level from the model, the noise mapping will be
plotted to have a better visual representation of noise levels on the road. With this noise
mapping, the noise traffic on the road can be monitored. A general simulation framework will
be provided for a better understanding of the model.
Conclusion: This study expects to provide a new traffic noise prediction model using program
algorithms. The prediction model will combine with a probabilistic approach to create multiple
combinations of the scenarios. Therefore, this model can provide different cases of the noises
on the road. In addition, strategic noise mapping will be provided for documentaries and a
better visual for noise on the road.
References: 1. Dutilleux, G., Defrance, J., Ecotière, D., Gauvreau, B., Bérengier, M., Besnard
F., Duc, E.L. (2010). NMPB-Routes-2008: The Revision of the French Method for Road
Traffic Noise Prediction.
2. Mahadev, N., and Ravindra, R. (2015). Automobile noise and Vibration-Sources, Prediction,
and Control. NCRIET, 12(1):001-006.
3. Vandal, T., Kodra, E., Dy, J., Ganguly, S., Nemani, R. and Ganguly, A.R., 2018, July.
Quantifying uncertainty in discrete-continuous and skewed data with Bayesian deep learning.
In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery
& Data Mining (pp. 2377-2386).
53
Matrices in Physics Data Processing
1
Tang Wen Kai Adrian1, Ng Wei Shean1, Liew How Hui1
Department of Mathematical & Actuarial Sciences, Lee Kong Chian Faculty of Engineering
and Science, Universiti Tunku Abdul Rahman, Malaysia
Introduction: Source separation plays an important role in audio processing and image
processing by extracting information from the audio or images. For example, extracting face
features from face images. Therefore, we incorporate the idea into the audio signal to extract
music features from musical audio. Hence, source separation can be represented by the
equation below:
𝑁
𝑦(𝑡) = ∑ 𝑥𝑗 (𝑡) ,
𝑗=1
where y(t) is the mixed audio signal and xj(t) is the number of sources that exist. This study
investigates the performance of Non-negative Matrix Factorisation (NMF), Convolutive Nonnegative Matrix Factorisation (CNMF) and Iterpolative Decomposition (ID) applied to solve
audio source separations.
Methods: Two different sets of mixed audio underwent the Short-Time Frequency
Transformation (STFT) to represent the signal as spectrogram. Then, applying NMF and
CNMF with Euclidean distance (ED), Kullback-Leibler (KL) divergence and Itakura-Saito (IS)
divergence as the objective functions. After getting the individual components, we group the
same approximated musical instruments together as our approximated musical instruments
such as drum and guitar. Lastly, evaluation of the separation performance is done by listening
to the audio by ears and plotting the graph of approximated audio data and the original audio
data.
Results: From all the methods applied in the mixed audio where the first mixed audio is simple
and the second mixed audio is complex, NMF-IS factorisation techniques perform the best as
it can separate the drum and guitar audio and the melody is smooth. Another observation is that
NMF-IS is able to capture the drum cymbal from the second mixed audio while other methods
are not able to do it.
Conclusion: NMF-IS has a better performance in audio source separation as the Itakura-Saito
itself possessed the scale-invariant property by keeping the small energy component while
others are not able to.
54
Application of Mixture Autoregressive Models for Intermediate-to-long Term Bus
Section Travel Time Prediction
Victor Jian Ming Low1, Hooi Ling Khoo1, Lay Eng Teoh1, Wooi Chen Khoo2
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
2
Department of Applied Statistics, Sunway University, Malaysia
Introduction: Point and interval prediction of bus travel time from an intermediate-to-long
term perspective is important for bus scheduling and route planning activities. This study
identifies two important elements to guarantee the long-lasting reliability of the system for
intermediate-to-long term prediction of bus section travel time. First, the model used for
prediction guarantees high accuracy for a long period. Second, the variable used contains as
less noise as possible to ensure the reliability of the variable used for predictive analysis.
Methods: A total of 98 bus sections’ travel time data collected in Klang Valley, Malaysia for
a duration of 6 months is used for the analysis. This study proposed a mixture time series model,
the mixture autoregressive (MAR) model to conduct the intermediate-to-long term prediction
of bus section travel time. The MAR model is more capable to capture the multimodal
distributed bus section travel time. The bus section travel time is transformed into the reliability
ratio index (RRI) to ensure the resilience of the variable used for ILTP analysis.
Results: In terms of point prediction, the MAR model has the highest accuracy and is the
leading model in almost all of the bus sections. In terms of interval prediction, the MAR model
generates the narrowest or the smallest range of prediction interval for the RRI series. Although
the prediction interval is narrow, the adjustment required to capture the observed RRI values
is the smallest as well. This indicates that the MAR model is more capable to identify the
sudden up or down of the RRI values. However, the MAR model has a drawback which the
frequency of adjustment is high.
Conclusion: The MAR model provides the highest accuracy in point prediction and generates
favourable bus section travel time interval for bus schedule planning with minor adjustments
required during real-time operation.
55
Water Quality Index Prediction using Long Short-term Memory (LSTM) Deep
Learning Method with Signal Pre-processing
Wai Kok Poh 1, Chai Hoon Koo 1, Yuk Feng Huang 1, Woon Chan Chong 1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Globally, the water quality index (WQI) is employed to represent the quality of
river waters by aggregating characteristics of several parameters of interest. Most of the studies
on WQI focused on WQI estimation, however, these models are unable to forecast the future
trend of the WQI. Some researchers typically adopted river water quality (WQ) datasets of low
temporal resolution, and thus the model developed would result in relatively large gaps between
the prediction intervals [1]. It is thus highly desired to have an accurate WQI forecasting model
over a finer time scale for an immediate response towards an expected river pollution event.
Methods: In this study, two recurrent-based deep learning (DL) models, namely the long shortterm memory (LSTM) and gated recurrent unit (GRU), were selected for direct WQI
forecasting. The empirical mode decomposition (EMD) and the variational mode
decomposition (VMD) were used to decompose the original WQI series into several stable
intrinsic mode functions (IMFs). The characteristics of these IMFs were carefully analyzed and
were used to ease model learning on capturing their temporal patterns. Historical data of the
past 30 days are fed as multi-dimensional inputs to the model to forecast WQI at five steps
ahead.
Results: The results revealed that these data decomposition strategies showed a significant
impact on the model accuracy while both the GRU and LSTM offered some comparable
performances. By using the number of IMFs obtained in EMD as the pre-defined scale number
for VMD, the VMD showed better separation of the complex signal. This, in turn promoted the
model learning over the base LSTM. As a result, the VMD-LSTM that demonstrated the lowest
prediction errors (MAPE = 1.9237%, MAE = 1.0321, RMSE = 1.2441 and MBE = 0.1361) and
the highest Kling-Gupta efficiency (KGE = 0.6761) stood as the best model over a test period
of two months. The increment of approximately 20% of training duration is considered
tolerable for the sake of higher prediction accuracy in the VMD-LSTM over the base LSTM.
Conclusion: The signal decomposition-based deep learning hybrid models resolved a complex
signal into several stable IMFs to ease model learning on the temporal patterns. This novel
forecasting strategy based on the decomposed IMFs could assist policymakers and stakeholders
in their decision-making especially on remedies planning and efficient water resource
management.
Reference: 1. Poh Wai, K., Yan Chia, M., Hoon Koo, C., Feng Huang, Y. and Chan Chong,
W. (2022). Applications of Deep Learning in Water Quality Management: A State-of-the-Art
Review. Journal of Hydrology, p.128332. doi:10.1016/j.jhydrol.2022.128332.
56
Robust Control Charts for Outliers and Change Points Detections
1.
1
Wong Chiong Liong 1, Ng Kooi Huat 1, Tan Wei Lun 1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Control charts is the most applied tool in statistical process control analysis. The
main task is to monitor whether the processes are in control. Control charts are applied in
various fields such as financial world, manufacturing process, physical science domains etc.
Many charting methodologies have been proposed and developed for monitoring the process.
Conventional control charts such as Shewhart X-bar (with S or R) chart, R chart, Moving
Average and Moving Range charts are well known and widely adopted in statistical process
control analysis. However, the fact is that the conventional control chart complies only when
the assumption is based on normal distribution which is not practical in the real-world. To
resolve the issue, robust charting methods are introduced. In this research, an improved robust
charting method which focuses on proposing improved estimators, modifying ψ function in the
robust estimator, and designing a new charting framework for gaining a better efficiency in its
actual application are proposed.
Methods: Control charts based on robust estimators such as Huber-Psi, Bi-weight, M-Scale
function are computed to compare with the conventional charts, X-Bar chart, R chart, etc while
applying the data that contains change point and outliers.
Results: Results showed that the robust charts outperformed the conventional charts. While
the control limits of conventional charts become wide due to the change point or outliers in the
data, robust chart which reduces the weight of outliers and detects the change points give
appropriate control limits.
Conclusion: Robust control charts is a control chart which shows better performance in nonnormal distributed data. However, when the data is normally distributed, it is most appropriate
to apply conventional control charts based on process mean and standard deviation.
57
A New Image Encryption Scheme Based on Hyperchaotic System and SHA-2
1
Kuan-Wai, Wong1, Wun-She1, Yap, Bok-Min, Goi1, Denis C.-K., Wong1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: This paper presents a new image encryption scheme by using a fourdimensional hyperchaotic system and adopting permutation-diffusion architecture. The initial
conditions of the hyperchaotic system are modified by the 256-bit digest of the plain image to
increase the sensitivity of the cipher to the plain image. An enhanced nonlinear equation is
applied in the diffusion process for the better encryption result. The experiment results show
that the proposed scheme has large key and subkey space, high key sensitivity, good
information entropy, and capability to resist statistical and differential attacks.
Methods: A four-dimensional hyperchaotic system presented is applied in the image
encryption scheme and the mathematical equation is given by the following equation:
𝑥̇ = 𝑎(𝑦 − 𝑥) − 𝑒𝑤,
𝑦̇ = 𝑥𝑧 − ℎ𝑦,
𝑧̇ = 𝑏 − 𝑥𝑦 − 𝑐𝑧,
𝑤̇ = 𝑘𝑦 − 𝑑𝑤,
where 𝑥, 𝑦, 𝑧, 𝑤 are the state variable, and 𝑎, 𝑏, 𝑐, 𝑑, 𝑒, ℎ, 𝑘 are the control parameters. SHA-256
hash algorithm is used to generate a 256-bit digest of the plain image, 𝐾 . PermutationDiffusion architecture is adopted in the design.
Results: To test the security of the proposed method, the key and subkey space, ability to resist
statistical and differential attacks, and information entropy are tested in the experiments. The
results are summarized as follows:
Key
Space
2254.57
Correlation
Horizontal Vertical Diagonal
-0.0034
-0.0021
0.0052
Differential Attack
NPCR
UACI
99.61%
33.46%
Information
Entropy
7.997
Conclusion: All the numerical results demonstrate that our proposed scheme has good security
performance and thus it is suitable for image encryption.
58
Deep Learning Strategy for Computational Single Pixel Imaging
Bing Hong Woo1, Sing Yee Chua1, Mau-Luen Tham1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Image quality and time efficiency are the primary concerns in single pixel
imaging (SPI) system. In general, one can increase the number of measurements to improve
the image quality, but this will overload the acquisition and reconstruction process on the other
hand. The improvement in SPI should not only address the image quality issue, but also needs
to consider the efficiency. Therefore, this project proposes a deep learning-based SPI using
coarse-to-fine sampling. Benefitting from the deep learning reconstruction, the proposed
method progressively samples (C2F) and reconstruct image with higher efficiency using GAN.
Methods: The overall design consists of the three major parts including the coarse-to-Fine
sampling, GAN image reconstruction and image colourisation. Pseudo-random sensing
patterns are used as the sampling mask and has an increasing resolution from a base resolution
to a maximum resolution. After sampling with M masks, the output is a single dimensional
array of M measurements. The measurements array will be used to pre-reconstruct using L2norm recovery method to generate a noisy image, which is then fed into the generator for GAN
based image reconstruction. Finally, the output image reconstructed will be enhanced visually
with colourisation.
Results: The results show that coarse-to-fine sampling consistently outperforms the uniform
sampling in terms of image quality, whereby the improvement can be seen in SSIM (21%),
PSNR (8%) and RMSE (17%) on average. At the same time, efficient image computation is
achieved by the deep learning GAN based reconstruction. The total time taken for deep learning
reconstruction method is only 0.025% of the time taken for conventional L1 reconstruction
method, which is approximately 4000 times faster on average.
Reconstruction Method
Sampling Method
Sampling Time (s)
Pre-recon Time (s)
Reconstruction Time (s)
Total Time (s)
SSIM
PSNR
RMSE
Conventional Method
L1 (Basis Pursuit)
Uniform
C2F
0.0228
0.1608
10.5557
11.8772
120.2161
112.9264
130.7946
124.9644
0.4447
0.5627
19.0732
21.0121
0.1136
0.0910
Deep Learning Method GAN
Uniform
C2F
0.0228
0.1608
0.2498
1.4431
0.0301
0.0301
0.3027
1.6340
0.4778
0.5384
19.7714
20.6199
0.1049
0.0945
Table 1: Performance comparison for different sampling and reconstruction method
Conclusion: In conclusion, the proposed deep learning-based SPI using C2F sampling
outperforms in terms of image quality as well as overall time efficiency. As such, the proposed
method is proven as a feasible solution to optimise the balance between computational time
and image quality.
59
Health Science & Technology
60
Gait Analysis After Anterior Cruciate Ligament Reconstruction using Motion Analysis
and Medical images
Abdulrahman Hussein Abdullah Alhamed1, Sayed Ahmad Zikri Sayed Aluwee2
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
2
Faculty of Information and Communication Technology Universiti Tunku Abdul Rahman
Kampar, Malaysia
Introduction: This work aims to analyse the gait of ACLR, then analyse the knee behaviour
after an ACL rupture, through the finite element (FE) method. For the walking experiment
measuring (Angle, Moment, Ground reaction force, and temporal spatial). For FE, it is used a
fully tridimensional model of the tibiofemoral joint, with and without ACL, where loads that
evidence the ligament function are applied.
Methods: In three stages. Firstly, Qualisys Track Manager system with five cameras has been
used to conduct Gait analysis and was done on ACLR 6 months (n = 8) and control group (n
=15). Paired t tests were used to compare the injured and uninjured knees. Secondly, the 3D
model of the knee joint was created using MRI and CT data in 3D slicer software. The
Segmentation of the models was conducted manually through visual identification of the region
boundaries. Lastly, for FE analysis using Abaqus software the knee ligaments were modelled
with the anisotropic Holzapfel-Gasser-Ogden (HGO) model. And follow previous studies in
terms of meshing, boundary condition and material properties.
Results: The patients applied external flexion forces and moments to their damaged knees
throughout midstance while level walking. The injured knee's (12.16º) maximal external
flexion force was substantially lower than the contralateral (14.06º) and control (15.97º) knees.
The ACLR group (661.41 N) produced significantly less force than the uninjured knee (672.21
N), therefore, the involvement of the gait cycle, as the stance phase of uninjured knee involved
in the gait cycle 66% more than the injured knee (57%). Eleven parts of the knee joint have
been segmented. In FE, The ACL provides the major constraint to anterior tibial motions and
plays an important role on restraining internal rotation of the tibia. When the ACL is absent,
the collateral ligaments are the first structures to be requested to sustain anterior-posterior
forces. The MCL is the ligament that supports more load in this situation.
Conclusion: Result of the FE simulation can provide information and a question that ACL for
ACLR subjects may not fully healed and may quadriceps not the only reason for the aberrant
gait. According to these data, asymmetric gait patterns maintained up to 6 months after surgical
reconstruction. These findings suggest that to regain normal performance following ACLR,
therapists should add particular therapies aimed at enhancing knee function during walking.
61
Development of an IoT-based Motion Analysis System for Telerehabilitation Purpose
1
Ming Jack Choo1, Yu Zheng Chong1, Yea Dat Chuah2, Joo Ling Loo1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
2
Faculty of Science and Engineering, University of Nottingham Malaysia, Selangor,
Malaysia
Introduction: Traditional rehabilitation is a one-to-one treatment where therapist evaluates
patient recovery subjectively. In region where therapists are scarce, the lack of manpower to
sustain the service spiked the cost for rehabilitation. The limited service available demotivated
patients, and this led to incomplete/premature rehabilitation [1]. Telerehabilitation is suggested
as an alternative to traditional rehabilitation for its ability to eliminates these barriers. This
research aims to develop a systematic telerehabilitation system to streamline the tracking of
patient progression and recovery with IoT application.
Methods: A telerehabilitation system is designed to help patient to conduct rehabilitation
remotely. 50 healthy human subjects will be recruited to test Hand Grip Strength (HGS test)
and Active Range of Motion (aROM test) on healthy subjects. The collected data will be
uploaded to cloud and then analyzed statistically using SPSS and MATLAB (Figure 1). The
analyzed data is then displayed on software interface to evaluate the performance of the
prototype and accuracy of the sensors.
Figure 1: Software architecture on the cloud level
Results: The system will record physio-kinematic parameters digitally with the help of
wearable prototype. It will consistently measure objective, quantifiable progress outcome by
observing changes and trend against number of sessions attempted. This system conveniently
allows storage of data online while the graphical interface display on user-end helps therapists
to provide evidence-based evaluation on progression of rehabilitation process, and to
rehabilitation regime according to individual need.
Conclusion: This system facilitates hand rehabilitation and can produce the empirical data and
analysis from aROM and HGS tests which help the therapist to quantitatively measure the
progression of hand motor function after telerehabilitation treatment remotely and reliably with
implementation of IoT system.
Reference: 1. Jafni, T.I., Bahari, M., Ismail, W. and Hanafi, M.H. (2018). Exploring Barriers
that Affect Telerehabilitation Readiness: A Case Study of Rehabilitation Centre in Malaysia.
Advances in Intelligent Systems and Computing, [online] pp.761–771. doi:10.1007/978-3-31999007-1_70.
62
Therapeutic Architecture: Role of Nature in the Healing Process for Cancer Patients
Joana Chan Sing Sien1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Cancer is a disease that results in cellular changes that cause uncontrolled
growth and division of cells. However, there are a few types of cancer treatments, namely
chemotherapy, radiation therapy, hormone therapy, and surgery. Some of the treatments have
various side effects and often lead to the substantial permanent impartment of several organ
systems. While others become terminally ill after the treatment. On the other hand, there is a
nature-based treatment that can reduce the pain of cancer patients. By nature-based treatment,
cancer patients can be healed mentally, emotionally, and physically thus making them feel
happy and increasing their quality of life despite struggling with cancer. Thus, this research
aimed to study the effectiveness of nature elements as tools in the cancer healing process.
Methods: The data for this research was collected using a mixed method (quantitative method
and qualitative method). Under the quantitative method, the online survey was used. Whereas
the qualitative method involved fifteen minutes of audio interviews with cancer patients
through WhatsApp.
Results: Most respondents agreed/ strongly agreed that nature is a healing element in the
cancer healing process, healing spaces can soothe and lift the mood of cancer patients, and
stimulation of the human senses by nature can add to the healing process of cancer.
Conclusion: In conclusion, spiritually, nature and life on earth are created by God, thus when
humans get sick/ tired/ stressed, they should seek help from nature (God’s creation). This is
because nature therapy is always free, painless, and has no side effects. It not only allows the
body to heal and recover naturally but also helps in the rejuvenation of the body, mind, and
spirit/soul. Cancer patients who are physically, mentally, and emotionally exhausted because
of fighting cancer should also go out to connect with nature.
63
Impact of COVID-19 Pandemic on Existing Migraine Symptoms Among University
Students in Malaysia: A Cross-sectional Pilot Study
Kiruthika Selvakumar1*, Tan Lee Fan2, Foo Chai Nein3
Department of Physiotherapy, M. Kandiah Faculty of Medicine and Health Sciences,
Universiti Tunku Abdul Rahman, Malaysia
2
Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of
Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia
3
Department of Population Medicine, M. Kandiah Faculty of Medicine and Health Sciences,
Universiti Tunku Abdul Rahman, Malaysia
1
Introduction: Differentiating between migraine and COVID-19 attacks is essential for
treatment. Studies were also done during this COVID-19 to analyse the impact of the pandemic
on migraine symptoms. Still, these studies are generalized, and cannot be confined to a specific
age group. Because many studies agree that migraine is more common and prevalent among
university students. If left untreated or undiagnosed, migraine can impact study, sleep patterns,
attention level during lectures, and social and emotional life. This pilot study aims to analyse
the impact of the COVID-19 pandemic on the existing migraine symptoms using a newly
developed and validated instrument.
Methods: The new scale developed was based on a three-stage analysis. Following these
preliminary steps, the final questionnaire consisted of 22 questions. The questionnaire was
disseminated to the existing students from both public and private universities through social
media like WhatsApp, Facebook, and E-mail. Data were collected between December 2021
and April 2022.
Results: A total of 493 participants enrolled in the study. Of the 485 participants who met the
inclusive criteria, 174 (35.9%) suffer from migraine and 311 (64.1%) don't suffer from any
migraine symptoms. Twenty (11.5%) were diagnosed with COVID-19 by PCR test since
October 2019, and 154 (88.5%) were not diagnosed with COVID-19. The common trigger
reported was lack of sleep (75%), stress (70%), fatigue (50%) in the diagnosed group, rather
stress (83.7%), lack of sleep (76.7%), fatigue (46.5%) was triggered in the non-diagnosed
group. Similarly, the coping adopted in the diagnosed group was adequate sleep (65%),
migraine medications (45%), acceptance (30%), and the non-diagnosed group was adequate
sleep (67.4%), relaxation exercise (48.8%), migraine medications (37.2%).
Conclusion: The newly developed and validated instrument would measure the trigger, coping
strategies and characteristics of migraine among university students with existing migraine
symptoms.
64
Study of Effectiveness of Audio Guided Deep Breathing on Improving the Wellness
of Visually Impaired Group
Eng Keat Kwa1, Soon Keng Cheong2, Lin Kooi Ong3, Poh Foong Lee1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
2
M. Kandiah Faculty of Medicine and Health Sciences, Universiti Tunku Abdul Rahman,
Malaysia
3
School of Health and Medical Sciences, University of Southern Queensland, Australia
School of Pharmacy, Monash University Malaysia, Malaysia. School of Biomedical
Sciences and Pharmacy, The University of Newcastle, Australia
1
Introduction: There is emerging evidence suggesting that deep breathing (DB) is a relaxation
technique, leading to the improvement of the wellness of mind and body. Thus, DB is
recommended for use as an adjuvant approach for visually impaired individuals, as the
restrictions caused by the defective vision have altered their autonomy and movement which
affects their wellness and quality of life. However, the incorporation of audio aid to guide DB
and its impact on the application of relaxation techniques is limited in people with visual
impairment. This study aimed to develop an audio-guided DB and evaluate its long-term impact
on the well-being of the visually impaired group.
Methods: Two prototypes were developed, consisting of audio-guided DB and audio-based
Go/No-Go paradigm. In total, 100 participants are recruited, and visually impaired subjects and
normally-sighted subjects are allocated into the DB group (N = 50) and control group (N = 50),
respectively. The DB group is submitted to 5 minutes of audio-guided DB daily for 14 days,
whereas the control group receives no intervention. Psychological state is evaluated using
Perceived Stress Scale, Cognitive and Affective Mindfulness Scale-Revised, Rosenberg's SelfEsteem Scale and World Health Organization Quality of Life, while the hair cortisol,
electroencephalogram, heart rate variability, Go/No-Go task and spirometry are assessed
before and after the 14 days.
Results: In the pilot test, 32 normally-sighted, healthy subjects underwent audio-guided DB
and its instantaneous impact was evaluated. Results showed a significant improvement in tidal
volume (p = 0.005) and task reaction time (p = 0.033). This supports the possibility that audioguided DB developed could enhance one’s pulmonary function and attention level effectively.
Conclusion: Audio-guided DB is an alternative relaxation technique that is hypothesized to
improve the wellness of the visually impaired group, provided the immediate improvement
brought by the audio-guided DB from the pilot study.
65
Skin-alike Smart Biosensor for Monitoring ECG Signals
Kok Tong Lee1, Pei Song Chee1, Eng Hock Lim1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Heart disease has become one of the leading causes of death in Malaysia. This
phenomenon can be avoided if early warning signs of heart disease are identified at the early
stages. Electrocardiogram (ECG) monitoring is one of the methods that can be used to detect
cardiac abnormalities. Holter monitoring devices, a clinical standard of diagnosis, can detect
and diagnose cardiac pace and rate disorders based on ECG waveform and rate-related data.
However, the device is susceptible to poor patient compliance due in part to its bulky form
factor and wired connections. In this study, a proof-of-concept of the stretchable biosensor for
ECG monitoring is proposed and developed.
Methods: The ECG monitoring device consists of a microcontroller unit (ESP32), ECG
module (AD8232), and MicroSD card module. The device is used to pick up ECG signals and
stored in a MicroSD card for further diagnosis. Besides, a stretchable ECG electrode was
fabricated by using silver-coated conductive fabric, and 3M transparent medical tape. The
design of ECG electrodes is drawn in AutoCAD and the material was cut using the Silhouette
Portrait electronic cutting machine.
Results: The silver-coated conductive fabric attached well with the 3M medical tapes to form
the dry ECG electrode. Conventional single lead ECG monitoring devices require 3 ECG
electrodes which are recommended to paste on the left arm, right arm, and left leg. The
proposed stretchable ECG patch only needs to be pasted on the chest. The stretchable ECG
patch combined 3 ECG electrodes in 1 piece patch with the size of 80mm x 40mm.
Conclusion: Stretchable ECG patches using silver-coated conductive fabric shows promise
can effectively eliminate the usage of wired connections between ECG electrode and hardware
device. Besides, the ECG patch form factor is reduced to 80mm x 40mm.
66
Effect of Shoe Cushioning Hardness to Running Biomechanics
Han Xiang Lim1, Yu Zheng Chong1, Yin Qing Tan1, Siow Cheng Chan1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Running is the simplest cardio exercise that helps in improving health.
Repetitive loading of the lower extremities musculoskeletal structure increases the rate of
running injuries and shoe cushioning hardness can be one of the main factors. Runners
accustomed to running gait with changes on flexion range of motion (FROM) could reduce the
peaks of vertical ground reaction force (VGRF) [1]. However, there are inconclusive findings
showing that VGRF peaks were not affected by cushioning hardness and giving different trends
of FROM [2]. The biomechanical effect of cushioning hardness after long duration running
still remains unclear. The aim of this research is to investigate the biomechanical effects of
shoe hardness for amateur runners after long distance running.
Methods: Ten male amateur runners who run minimum 10km weekly were recruited.
Experimental study was conducted at Institut Sukan Negara (ISN) using a 3D motion capture
system and instrumented treadmill. Two shoe models with different hardness are tested in this
study. Participants attended running tests for the first screening session and randomly separated
into hard or soft cushioning groups, then ran overground for a minimum 10km weekly. Another
three data collection sessions were carried out at the beginning 0km, followed by a cumulative
running distance of 40km and 80km with allocated shoes. Cushioning hardness, FROM at hip,
knee, and ankle joints, as well as maximum VGRF were collected and analyzed.
Results: Cushioning hardness was increased after cumulative running distance. The FROM is
lower with soft cushioning and increased with accumulated running distance in both groups.
Maximum VGRF is lower with soft cushioning and declines following the increase on
cushioning hardness after cumulative distance. Running with hard cushioning after cumulative
distance gives increased maximum VGRF and maintains at a peak level.
Conclusion: Shoe cushioning was degraded with accumulation of running distance. Lower
limb’s joint angles, FROM were increased when running with harder cushioning shoes.
Maximum VGRF were greater with hard cushioning. Soft cushioning is recommended to
reduce running injuries risks.
References: 1. Nigg, B.M., Baltich, J., Maurer, C. and Federolf, P. (2012). Shoe midsole
hardness, sex and age effects on lower extremity kinematics during running. Journal of
Biomechanics, 45(9), pp.1692–1697. doi:10.1016/j.jbiomech.2012.03.027.
2. Addison, B.J. and Lieberman, D.E. (2015). Tradeoffs between impact loading rate, vertical
impulse and effective mass for walkers and heel strike runners wearing footwear of varying
stiffness. Journal of Biomechanics, 48(7), pp.1318–1324. doi:10.1016/j.jbiomech.2015.01.029.
67
Classification of Syncope Patients from Physiological Signals Acquired in Head-up Tilt
Table Test
Mahbuba Ferdowsi1, Choon-Hian Goh1, Ban-Hoe Kwan1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Syncope, also known as temporary loss of consciousness, caused by transient
global cerebral hypoperfusion. Clinically, the gold standard of syncope diagnosis is performing
the head up tilt (HUT) assessment. During the test, the subjects experienced various common
issues such as nausea, sweating, pallor, the feeling of palpitations, being on the verge of passing
out, and fainting. The study's goal is to develop an algorithm to classify syncope patients based
on physiological signals (blood pressure (BP) and electrocardiography (ECG) obtained from
the HUT test.
Methods: The subject began 10 minutes of supine rest, then followed with tilting at 70 degrees
on a tilt table for up to 40 minutes. An 800 micrograms of glyceryl trinitrate were infused once
after the subject was tilted. A continuous non-invasive monitoring device (Task Force Monitor,
CNSystem, Austria) that continuously captured ECG and BP were used to record
hemodynamic measurements throughout the assessment. Beat-to-beat heart rate and blood
pressure data were then exported in MATLAB format. The study used mean imputation and
K-Nearest Neighbor imputation approaches to handle missing values. Next, feature selection
techniques were implemented, including genetic algorithm, recursive feature elimination, and
feature importance, to determine the crucial features. The Mann-Whitney U Test was then
performed to find the statistical difference between two groups. Machine learning classifiers,
including Support Vector Machine (SVM), Gaussian Naive Bayes, Multinomial Naive Bayes,
K- Nearest Neighbors, Logistic Regression, and Random Forest, were used to classify the
selected features via 5-fold cross-validation. Partial dependence plot was further utilized to
explain the developed model.
Results: A total of 137 subjects aged between 9-93 years were recruited for this study, 54 of
them experienced syncope symptoms and therefore diagnosed as syncope positive, the
remaining 83 were labeled as syncope negative, by the clinician. A total of 56 features were
extracted from heart rate and blood pressure data. The KNN imputation technique and 3 tilting
features, named 'CV_SBPV' (Coefficient of variance of Systolic BP Variability),' CV_DBPV'
(Coefficient of variance of Diastolic BP Variability),' LFnu_SBPV' (Low-frequency
normalized power of Systolic BP Variability) paired with SVM produced the best results. The
optimum obtained result is 90.5% accuracy, 87.0% sensitivity, 92.7% specificity, 88.6%
precision, 87.8% F1 score, and 95.4% ROC.
Conclusion: The developed classification algorithm effectively classifies syncope patients
with over 90% accuracy. However, the current research study was confined to a small sample
size and from single medical center. More clinical datasets are required to ensure that our
approach is generalizable.
68
Amide Proton Transfer Magnetic Resonance Imaging (APT MRI) as a Better
Imaging Modality for Brain Tumor Treatment Monitoring
1
Swee Qi Pan1, Yee Kai Tee1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Conventional magnetic resonance imaging (MRI) technique for identifying the
brain tumor relies on T₁-weighted acquisition (T1w), and T2-weighted fluid-attenuated inversion
recovery (T2w-FLAIR). However, both imaging modalities only provide anatomical
information about lesion morphology and structure and highly depend on the occurrence of
blood brain barrier (BBB) disruption. Amide proton transfer (APT) is a chemical exchange
saturation transfer MRI technique that reflects the concentration of metabolites that are
involved in exchanging protons. This may provide physiological information to improve brain
tumor identification and treatment monitoring. This study investigated the use of APT MRI for
the treatment response prediction in gamma knife.
Methods: The preliminary study included 5 newly diagnosed brain metastasis patients
scheduled for gamma knife treatment in Hospital Universiti Kebangsaan Malaysia (HUKM).
T1, T2 and APT MRI were acquired before treatment and 2-weeks after treatment using a 3T
MRI scanner. Z-spectrum was corrected by using Lorentzian-fitting and CEST effect was
quantified by using magnetization transfer ratio asymmetry analysis (MTRasym). Follow-up
on patients’ recovery status with neurologists has been done a few months after the treatment.
Results: In all 5 patients, the observed tumor in T1 and T2 images before and after gamma knife
treatment depicted minimal changes. Upon analyzing the APT MRI image, the tumor location
showed an obvious drop in signal intensity after treatment. This demonstrated that the tumor
has responded to gamma knife treatment to become less active biologically. Furthermore, all
patients showed good recovery status during follow-up sessions with neurologists, consistent
with prediction of treatment response based on APT MRI.
Figure 1: Pre- (top row) and post-treatment (bottom row) T1, T2 and APT MRI tumor area
(red arrows) of a representative patient
Conclusion: APT MRI is a non-invasive imaging technique that can provide physiological
information in brain tumors. It shows promising ability in complementing conventional MRI
imaging to better identify biologically active tumor site and predict treatment response.
69
Effect of Running Shoe Cushioning on Muscle Activation Using OpenSim
Rachel Weng Kei Boon1, Siow Cheng Chan1, Yin Qing Tan1, Yu Zheng Chong1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Computational modeling and simulation tools were developed to perform
prediction analysis on running with different footwear [1], which produces insights into the
underlying behaviour of biomechanical function. Coaches are able to develop an efficient
training protocol to optimize the athlete’s performance and improve injury prevention [2].
However, the muscle activation contributing to running biomechanics for Malaysian runners
remains unclear. This study aims to develop a running gait model using open-source software
– OpenSim and investigate the effect of shoe cushioning on muscle activation during running.
Methods: Six healthy Malaysian male amateur runners were recruited into this study (age:
29.67±3.44 years; height: 170.32±3.36cm; body mass: 68.23±4.90 kg). Participants ran on the
instrumented treadmill with embedded force plates at a fixed speed of 12km/h. Running gait
models were developed using Opensim, and muscle activations were estimated using the static
optimization method. Independent-sample t-test was used to investigate the differences
between muscle activation while running in hard and soft cushioned shoes.
Results: The hard cushioning resulted in slightly greater muscle force than soft cushioning
(Figure 1). Results demonstrated significant differences in the rectus femoris (10-30%, p<0.001;
40-60%, p=0.014). Hard cushioning shoe promotes higher muscle activation force and thus
helps improve running performance, while soft cushioning shoes reduce injury risks.
Figure 1: Mean muscle force between Hard and Soft shoe cushioning for the (a) biceps
femoris, (b) lateral gastrocnemius, (c) rectus femoris and (d) tibialis anterior
Conclusion: A running musculoskeletal model was developed using the Opensim software in
which the muscle activations were estimated through the static optimization method. Our study
suggested that hard cushioning shoes can promote higher muscle activation force and thus helps
to improve running performance, while soft cushioning shoes benefit in reducing injury risks.
References: 1. Sinclair, J., Brooks, D. and Stainton, P. (2019). Biomechanical effects of a
lightweight, sock-style minimalist footwear design during running: a musculoskeletal
simulation and statistical parametric mapping approach. Footwear Science, 11(2), pp.71–83.
doi:10.1080/19424280.2019.1593516.
2. Yeadon, F.R. (1998). Computer Simulation in Sports Biomechanics. ISBS - Conference
Proceedings
Archive.
[online]
Available
at:
https://ojs.ub.unikonstanz.de/cpa/article/view/1561 [Accessed 25 Nov. 2022].
70
Receptor-Mediated AKT/PI3K Signalling and Behavioural Alterations in Zebrafish
Larvae Reveal Association between Schizophrenia and Opioid Use Disorder
1
Siroshini K Thiagarajan 1, Siew Ying Mok 1, Pek Yee Tang 1
Department of Mechatronics and Biomedical Engineering, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: The link between substance abuse and the development of schizophrenia
remains elusive. In this study, we assessed the molecular and behavioural alterations associated
with schizophrenia, opioid addiction, and opioid withdrawal using zebrafish as a biological
model. Apart from the impaired cognitive functioning, substance misuse is associated with
poorer outcomes in psychosis [1].
Methods: Larvae of 2 days post fertilization (dpf) were exposed to domperidone (DMP), a
dopamine-D2 dopamine D2 receptor antagonist, and morphine for 3 days,10 days and
withdrawal syndrome was assessed 5 days, respectively. The expressions of schizophrenia
susceptibility genes, i.e., pi3k, akt1, slc6a4, creb1 and adamts2, in brains were quantified, and
the levels of whole-body cyclic adenosine monophosphate (cAMP), serotonin and cortisol were
measured. The aggressiveness of larvae was observed using the mirror biting test (Figure 1).
Results: The long-term exposure, akt1 was
downregulated by DMP and morphine.
Downregulation of pi3k and slc6a4 was
observed in the morphine-treated larvae,
whereas creb1 and adamts2 were
upregulated by DMP. The levels of cAMP
and cortisol were elevated after 3 days,
whereas significant increases were
observed in all of the biochemical tests
after 10 days. Compared to controls,
increased aggression was observed in the
DMP-, but not morphine-, treated group.
These two groups showed reduction in
Figure 1: Experimental design schematics
aggressiveness when drug exposure was
prolonged. Both the short- and long-term morphine withdrawal groups showed downregulation
in all genes examined except creb1, suggesting dysregulated reward circuitry function.
Conclusion: Both the short- and long-term morphine withdrawal groups showed
downregulation in all genes examined except creb1, suggesting dysregulated reward circuitry
function. These results suggest that biochemical and behavioural alterations in schizophrenialike symptoms and opioid dependence could be controlled by common mechanisms. The genes
involved in the PI3K–AKT signalling pathway play important roles in the modulation of
behavioural and neurological activity induced by DMP and morphine.
Reference: 1. Winklbaur, B., Ebner, N., Sachs, G., Thau, K., Fischer, G. (2006). Substance
abuse in patients with schizophrenia. Dialogues Clin. Neurosci., 8, 37.
71
An Emoji-based Attention Bias Modification Intervention for Depressive Symptom
Severity in Young Adults
Mei-Yi Wong1, Soon Keng Cheong2, Poh Foong Lee1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
2
M. Kandiah Faculty of Medicine and Health Sciences, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Globally, the rates of young adults and college students reporting symptoms of
depression have been rising over the past decade. The lack of treatments targeting underlying
factors of depression cause insufficient remission of depression and relapses to occur in some
patients. There has been increasing interest in behavioural and cognitive mental health
interventions with the potential for remote applications. Therefore, this study aims to evaluate
the feasibility and acceptability of using an emoji-based attention bias modification (ABM)
training paradigm on depressive symptom severity compared with a deep breathing practice
protocol in a randomized controlled experiment.
Methods: A preliminary study was carried out to determine the emotional valence of emojis to
be used as stimuli in the ABM paradigm. An independent sample of 121 respondents rated 38
emotional emojis based on their perceived emotional valence. For the main study, a target
sample size of 120 participants will be recruited. Participants will be randomized to either the
emoji-based ABM training, mindful deep breathing practice, sham training, or no-intervention
control group.
Results: The 12 highest and lowest rated emojis were used as the positive and negative stimuli
respectively, in the ABM task. Meanwhile, the Spearman’s rank-order correlation coefficients
between the emotional rating of the emojis and participant scores on the DASS-21 and PHQ-9
questionnaires ranged from -0.239 to 0.269 (p < 0.05), implying weak correlation strength.
Table 1: Median ranking of emojis with happy, sad, and neutral emotional valences
Conclusion: Individual differences in symptoms of depressive, anxiety, and stress only
minorly contribute to differences in the emotional rating of emotional emojis, suggesting that
happy and sad emojis are interpreted similarly across the sample of respondents. Currently,
participant recruitment for the main study is in progress.
72
Improving Deep Learning Performance for Small Dataset in Histopathological Gastric
Cancer Detection
1
Ming Ping Yong1, Yee Kai Tee1, Wun-She Yap1, Choon Hian Goh1.
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Gastric cancer is a major leading cause of cancer-related death worldwide. The
histopathological examination by pathologists is the gold standard for the diagnosis of gastric
cancer. However, this manual process is exhausting, time-consuming, and subject to intraobserver agreement. The computer aided diagnosis (CAD) tools with deep learning as primary
examples have been introduced to assist the pathologists in the diagnosis. This study
investigated the transfer learning and ensemble model algorithms in overcoming the small
dataset issue to detect and classify histopathology gastric cancer and non-cancer images.
Methods: Two datasets were used to fine-tune a list of pre-trained networks for histopathologic
gastric image classification into cancer and non-cancer images. These models were initially
fine-tuned on the larger BOT AI Challenge dataset and the fine-tuned models were transferred
to fit the smaller GasHisSDB dataset [1] for evaluation. Additionally, the ensemble models
were used to combine top performing base models in making predictions.
Results: The pre-trained networks and ensemble models achieved higher performance than the
same models in our previous study which used different training strategies by directly fitting
the pre-trained networks onto the small GasHisSDB dataset as shown in table below:
Accuracy (%)
Models
Without prior fineWith prior fine-tuning
tuning
MobileNetV2
99.4279
98.415
EfficientNetB0
99.2578
98.33
EfficientNetB1
99.4511
98.3609
DenseNet121
99.5206
98.6779
DenseNet169
99.4974
98.5697
Ensemble-Weighted Averaging
99.7681
99.1573
Ensemble-Unweighted Averaging
99.7294
99.2036
Ensemble-Majority Voting
99.7294
99.1341
Table 1: Accuracy of the proposed models on the GasHisSDB dataset classification with or
without prior fine-tuning on the BOT AI Challenge dataset
Conclusion: We designed a robust transfer learning scheme through prior fine-tuning on a
large histopathology dataset and ensemble model scheme for gastric cancer detection to
improve the generalizability and performance of models on the small dataset.
Reference: 1. Hu, W. et al. (2022) ‘GasHisSDB: A new gastric histopathology image dataset
for computer aided diagnosis of gastric cancer’, Computers in Biology and Medicine, 142, p.
105207. Available at: https://doi.org/10.1016/J.COMPBIOMED.2021.105207.
73
Green Technology &
Sustainable Development
74
Development of Aluminium-Air Battery
1
Asrin Awang Selan1, Bernard Saw Lip Huat1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: World energy demand is rising day by day due to the development of advanced
technologies in various industries. Therefore, alternative and safe energy sources should be
implemented in order to keep the environment clean and sustainable. Aluminum-air batteries
have been recognized as a low-cost energy storage system compared to other types of energy
storage systems [1]. Unfortunately, the corrosion that occurs at the aluminum anode in the
aqueous system reduces the overall energy density of the battery. Therefore, a novel idea of a
cellulose-based aluminum-air battery is proposed to achieve a green and cheaper battery. In
this work, a cellulose-based aluminum-air battery was constructed using aluminum foil as an
anode, activated carbon as an air-cathode and KOH as the electrolyte. The separator was added
to separate the anode and cathode to prevent short circuit. This experiment was done to compare
the result of battery by using different molarity of KOH.
Methods: Aluminium foil was used as the anode, filter paper as the separator and KOH as the
electrolyte. Carbon nickel mesh was fabricated which act as cathode. These components were
sandwiched together to and analyse by using Galvanostat.
Results: From above figure, as the concentration of the electrolyte increases, the time take
elapsed also increase. This reaction was done with discharge current at -10mA. 1M of KOH,
the discharge time was about 15.93 min, 52.65 min for 2M of KOH and 66.98 min for 3M of
KOH. The results show 2M of KOH can produce the stable performance compared to 1M and
3M.
Conclusion: Aluminium-air battery can be produced to replaced lithium-ion battery as it
greener and can generate high energy. By implementing green material in the components, the
product will be safe to use.
Reference: 1. Rahman, Md. A., Wang, X., & Wen, C. (2013). High Energy Density Metal-Air
Batteries: A Review. Journal of The Electrochemical Society, 160(10), A1759–A1771.
https://doi.org/10.1149/2.062310jes.
75
MgO Sorbents Modified with Ternary Eutectic Mixtures for CO2 Removal from
Simulated Flue Gas at Intermediate Temperature
Kian Hoong Chai1, Yeow Hong Yap1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Post-combustion CO2 capture requires a sorbent capable of efficiently capturing
CO2 from a 4-14% (volume-based) mixture [1, 2]. The low concentration of CO2 in postcombustion flue gas streams forms a significant constraint for developing capture technologies.
In this work, MgO impregnated with ternary eutectic mixtures of LiNO3, NaNO3 and KNO3
were synthesized and the adsorption performance was studied using a dilute stream of CO2
(15%). The effect of the ratio of the alkali metal nitrates and adsorption temperature was
investigated.
Methods: Six MgO sorbents promoted with different ratio of ternary alkali salt were
synthesized. Characterization performed on the adsorbent included Fourier transform infrared
(FT-IR) analysis, X-ray diffraction (XRD) analysis, surface area and porosity analyses,
temperature-programmed desorption of carbon dioxide (CO2-TPD) and scanning electron
microscopy (SEM) analysis. CO2 sorption study is conducted with a fixed bed reactor at several
sorption temperatures.
Results: The results demonstrate that regardless of the CO2 sorption temperature, the LiNO3
molar ratio in the ternary eutectic mixture should be kept low to reduce the induction period
for fast carbonation. Due to the shorter induction period, MgO impregnation with 10 mol%
(Li0.18Na0.52K0.3)NO3 exhibited the highest adsorption capacity of 5.56 mmol/g at 240 °C in 4
h and a final CO2 adsorption capacity of 3.18 mmol/g over 5 cycles in the dilute stream of CO2,
suggesting its potential to be used as CO2 adsorbent for post-combustion application.
Conclusion: The findings of the current study suggested that the eutectic mixture’s molar
composition should be NaNO3 > KNO3 > LiNO3. Increasing the NaNO3 molar composition in
the eutectic mixture increased the CO2 uptake whereas increasing the LiNO3 molar composition
lead to a significant drop of CO2 sorption at the sorption temperature investigated in the current
study (220 to 260 °C).
References: 1. Pires, J.C.M., Martins, F.G., Alvim-Ferraz, M.C.M. and Simões, M. (2011).
Recent developments on carbon capture and storage: An overview. Chemical Engineering
Research and Design, 89(9), pp.1446–1460. doi:10.1016/j.cherd.2011.01.028.
2. Samanta, A., Zhao, A., Shimizu, G.K.H., Sarkar, P. and Gupta, R. (2011). Post-Combustion
CO2 Capture Using Solid Sorbents: A Review. Industrial & Engineering Chemistry Research,
51(4), pp.1438–1463. doi:10.1021/ie200686q.
76
Development of Cellulose Based Magnetic Responsive Microcapsule for The Removal of
Microbial Pollutant
Chooi Chee Yoong1, Shuit Siew Hoong1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Water plays a crucial role in all living things, including plants, animals, and
human beings. Hence, wastewater reuse and recycle have become significantly important to
increase water availability and conserve water resources. Wastewater treatment is aimed at
decreasing the concentrations of specific pollutants to levels that are safe for effluent reuse or
discharge into the environment [1]. It was reported that 85% of the river water and sediment
samples in peninsular Malaysia contained Escherichia coli (E.coli) which cause serious
diseases. Adsorption no doubt is one of the effective methods to remove water pollutants.
Although single adsorption process will remove the E.coli, secondary waste will be produced
as the adsorbent need to be further destroy or regenerate, thus , the Fenton process is introduced
for the degradation of the adsorbed E.coli. This research focus in the simultaneous adsorption
and degradation of E.coli by using PDDA/Fe3O4-cellulose acetate microcapsule.
Methods: The effectiveness in adsorption and degradation of E.coli by using Fe3O4-cellulose
acetate microcapsule will be studied. Firstly, the development of Fe3O4-cellulose acetate
microcapsule will be optimized by varying concentration of the cellulose acetate, composition
of pore forming reagent and dosage of PDDA/Fe3O4 during encapsulation. The
characterization of PDDA/Fe3O4-cellulose acetate microcapsule, for example, F-TIR, SEMEDX and BET will be conducted for supporting the results in adsorption and degradation of
E.coli. The optimization of reaction condition such as contact time, dosage of microcapsule,
initial pH, concentration of H2O2 and initial concentration of E.coli during adsorption and
degradation will be carried out. Lastly, the adsorption isotherm study and kinetic study of E.coli
degradation will be studied to reveal the behaviour of Fe3O4-cellulose acetate microcapsule.
Results: The concentration of cellulose acetate (1 wt%, 3 wt%, 5 wt%, 7 wt%, and 9 wt%) had
been investigated. According to the observation, the microcapsule that developed by using 1
wt% (formation of flakes that float on the surface of continuous phase) and 3 wt% (formation
of microcapsule with tails) of cellulose acetate were not in the round sphere shape which
incapable for the research. Besides that, due to the low viscosity in 1 wt% and 3 wt% of
cellulose acetate, the PDDA/Fe3O4 did not dispersed evenly in the mixture which lead to
uneven distribution of core materials within microcapsule.
Conclusion: The research for concentration of cellulose acetate focused in 5 wt%, 7 wt% and
9 wt%.
Reference: 1. Sakr, M., Mohamed, M.M., Maraqa, M.A., Hamouda, M.A., Aly Hassan, A.,
Ali, J. and Jung, J. (2022). A critical review of the recent developments in micro–nano bubbles
applications for domestic and industrial wastewater treatment. Alexandria Engineering Journal,
61(8), pp.6591–6612. doi:10.1016/j.aej.2021.11.041.
77
Sustainability Criteria for Affordable Housing in Malaysia
1
Lai Li Xuan1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Housing affordability has been a grave concern, and there is a growing number
of overhang affordable housing in Malaysia due to the incompatibility between the supply and
demand side of the housing and household income could not outpace the escalating housing
price. In many circumstances, the B40 and M40 households are short on money after spending
a large portion of their income on housing-related costs such as a mortgage, taxes, utilities, and
maintenance. As a result, they may have to sacrifice other living expenses, which could affect
their future consumption and activity in an unsustainable way. Therefore, this research intends
to determine the sustainability criteria for affordable housing.
Methods: Sequential explanatory method is adopted in this research, where a questionnaire
survey is distributed to the targeted respondents (B40 and M40 households), followed by
validation through semi-structured interviews with the housing practitioners. The quantitative
data were analysed with Mean Ranking, Spearman Correlation and Ordinal Logistic
Regression.
Results: Mean ranking results showed that the B40 and M40 homebuyers place high
importance on housing subsidies, low interest rates and the availability of disaster resistance
features. Contrastingly, they place the least preference on the availability of smart or green
features and the cultural and historical conservation in a sustainable affordable housing
development. Besides, ordinal regression results revealed females, older generations and
married households have higher preferences for sustainable affordable housing criteria. The
quantitative results were validated in the interview.
Conclusion: The research aims to determine the sustainable affordable housing criteria from
the homebuyers’ perspective. The results confirmed that economic sustainability criteria are
the most important criteria among B40 and M40 homebuyers, while gender, generation and
marital status of the homebuyers would influence their preferences on sustainable affordable
housing criteria.
78
Approach to Establish an Industry 4.0 Enabling Technology Adoption Model
Sie Yee Lau1, Tan Ching Ng1, Meng Suan Liang1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Manufacturing industry has historically been critical to global economic
progress and the industrial revolution. Computers and robotics are integrated into the
manufacturing environment and have resulted in autonomous manufacturing [1]. This has the
potential to transform the manufacturing environment and boost company competitiveness.
However, its implementation is still a relatively unknown phenomena that has to be
investigated. Adoption and usage of new innovative technology will not succeed in enhancing
the competitiveness of the contemporary manufacturing industry unless the factors influencing
the level of adoption of new innovative technology are distinguished. In this study, a TOEbased decision-making framework is constructed, which includes a comprehensive set of
decision-making factors relevant to the adoption of Industry 4.0 enabling technology.
Methods: In order to develop a research model, the researcher reviewed previous studies on
technology adoption in various contexts and identified key findings. Then, the researcher
identified research gaps and appropriate theories to support the development of the framework
based on key findings. Various variables were then associated with the discovered theory to
support the study’s purpose. When developing a research design, the procedure for collecting
data from a target population via survey was focused in the proposed research setting.
Results: In this study, technological context refers to perceived compatibility, cost savings,
perceived value, and security and privacy concerns as deciding variables affecting
manufacturers’ adoption of Industry 4.0 enabling technology. Organizational context involves
three determinants including information intensity, manufacturing digitalization strategic road
mapping and technological readiness. Competitiveness pressure and trading partner pressure
are the determinants of environment context.
Conclusion: To better anticipate, explain and accelerate the adoption of Industry 4.0 enabling
technology in the manufacturing industry, it is necessary to understand why certain
manufacturers choose to use Industry 4.0 enabling technology while others do not, even when
they face identical market conditions.
Reference: 1. Ooi, K.-B., Lee, V.-H., Tan, G.W.-H., Hew, T.-S. and Hew, J.-J. (2018). Cloud
computing in manufacturing: The next industrial revolution in Malaysia? Expert Systems with
Applications, 93, pp.376–394. doi:10.1016/j.eswa.2017.10.009.
79
Waste Scavenging and the Informal Settlement: A Case of El-Zabballen City
1
Nourhan Sherif Mostafa1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Informal settlements have been established in the urban fabric of cities all over
the globe. Forms of urban informality originate and grow because of various self-organizing
processes. The setting of the study is in a unique informal settlement of Great Cairo, Egypt.
The study investigates “Ezzabet El-Zabbaleen” informal settlement in terms of the physical
environment and socio-economic aspects. The study aims to generate the architectural identity
and highlight the occupants’ potential to sustain the Zabbaleen’s living through recycling
activities.
Methods: In-site observation and interviews are the key methods to conduct the study with the
aid of architecture to be the research base, the study argues that Zabbaleen City can be a
sustainable module for a better livelihood.
Results: The main findings include the humans’ creation of spaces based on their needs, the
unique features of the Zabbaleen’s physical environment, and the capability of upgrading
approaches within the Zabbaleen’s informal living.
Conclusion: Informal settlement should be viewed not as a problem to be fixed, but as a place
with potential, both in terms of physical and human resources. The ecology of the mega-slum
is not urban informality; rather, it is a style of space creation and a planning method.
Unsurprisingly, the dynamics of urban informality differ substantially depending on the
occupants and their living nature.
80
Vacuum Assisted Solution Process for Deposition of High Crystallinity and Uniformity
Methylammonium Lead Iodide Perovskite Film
Yew Hang Soo1, Chai Yan Ng1, Hieng Kiat Jun1, Soo Ai Ng2
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
2
Faculty of Engineering and Green Technology, Universiti Tunku Abdul Rahman, Malaysia
1
Introduction: Methylammonium lead iodide perovskite (MAPbI3) film is an important
photoactive layer in perovskite solar cell (PSC). It can be deposited through various solution
methods, such as spin-coating, doctor blading, air-knife coating, etc. Spin-coating is the most
common method as it offers ease of control on the film’s thickness. In this work, we introduce
vacuum-assisted solution process (VASP) to augment the spin-coating process to produce high
crystallinity and uniformity MAPbI3 film. The VASP requires specialized vacuum equipment
to achieve such low vacuum pressure, which we have made using low-cost parts obtained easily
from online shopping platform.
Methods: A MAPbI3 precursor solution was spin-coated on the SnO2 coated FTO substrate at
4000 rpm for 10 s. Immediately after the spin-coating process ended, the gel-like MAPbI3 film
was exposed to low vacuum environment (<10 Pa) in our homemade VASP equipment for 10
s to evaporate most of the DMF and some DMSO solvents, inducing supersaturation within the
film. Upon annealing at 100 °C for 10 min, the MAPbI3 gel-like film transformed into shiny
and dark-brown in appearance.
Results: The MAPbI3 films were successfully spin-coated using VASP. Preliminary X-ray
diffraction analysis reveals that the VASP-produced MAPbI3 film has high crystallinity.
Compared to the common antisolvent assisted spin coating method, the VASP-produced
MAPbI3 films exhibit crystallinity of at least 3 times higher (Figure 1a). The MAPbI3 films
produced are also highly uniform, reflective and dark brown in appearance (Figure 1b). Such
high-quality film may help our research in producing high performance PSC in near future.
Figure 1: (a) XRD peaks of MAPbI3 films produced from VASP and antisolvent methods. (b)
Picture of MAPbI3 films produced using VASP process showing the reflective, dark-brown
appearance of the films
Conclusion: VASP equipment built by us can produce high quality, high crystallinity and
uniform MAPbI3 films with ease. It is hope that the construction of this VASP equipment can
help further our research into fabrication of high efficiency PSC in near future.
81
Phytoremediation of Zinc in Water for Biosynthesis of Zinc Oxide Nanoparticles using
Hyperaccumulator Plants
1
Hui Wun Tan1, Yean Ling Pang1, Steven Lim1, Woon Chan Chong1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Phytoremediation is an environmental-friendly and sustainable bioremediation
technology which could be used to absorb zinc (Zn) in water using hyperaccumulator plants
through various mechanisms such as phytoextraction, rhizofiltration, phytovolatilization and
phytostabilization [1]. Hyperaccumulator plants are able to tolerate high concentration of heavy
metals without displaying phytotoxicity. After the phytoremediation process, the absorbed and
accumulated Zn ions within the hyperaccumulator plants could be extracted and recycled to
synthesize zinc oxide (ZnO) nanoparticles. This study investigated the feasibility of using
hyperaccumulator plants for green synthesis of zinc oxide (ZnO) nanoparticles.
Methods: Water lettuce and water hyacinth of similar size and weight were selected to perform
phytoremediation of Zn containing synthetic wastewater. Different parameter studies such as
phytoremediation duration, Zn concentration, solution pH and salinity were conducted to
investigate their effects on the phytoremediation performance on each type of plants.
Characterization studies were also conducted to study the morphology of the plants before and
after Zn phytoremediation.
Results: Both water lettuce and water hyacinth were able to undergo phytoremediation of Zn
with great performance within 5 days of experiment. The optimum Zn concentration, solution
pH and salinity concentration were 10ppm, pH 6 as well as 6 and 9ppm for water lettuce and
water hyacinth, respectively. The FTIR results showed that both plants have characteristic
functional groups of a polysaccharide such as O–H, C–H, C–O and C=O bonds which acted as
binder for Zn ions. On the other hand, SEM results suggested the chelation of metal complexes
in the form of tiny granules and agglomerates on plants’ surfaces. EDX results also showed
that the atomic percent of Zn in both plants had increased after phytoremediation with higher
Zn content in the roots than aerial part of plants.
Conclusion: The phytoremediation performance of both plants could be affected by the growth
conditions which include Zn concentration, solution pH and salinity concentration.
Optimization of these conditions could enhance the phytoremediation performance of the
plants which could be further treated to extract the Zn content from within the plants for
biosynthesis of ZnO.
Reference: 1. Ali, H., Khan, E. and Sajad, M.A. (2013). Phytoremediation of heavy metals —
Concepts
and
applications.
Chemosphere,
91(7),
pp.869–881.
doi:10.1016/j.chemosphere.2013.01.075.
82
Effect of Phase Change Material on the Productivity of a Passive Solar Still
Jia Hui Tan1, Rubina Bahar1, Hieng Kiat Jun1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: The world has been suffering from freshwater crisis due to pollution and global
warming, one of the solutions to solve this problem is solar desalination technology. The cost
of solar desalination is the lowest among all desalination methods. However, the method has
low productivity due to unstable weather conditions. Therefore, in this study, the
implementation of thermal energy storage (TES) is applied to improve the performance. The
common TES used in solar desalination applications is phase change material (PCM).
Methods: The PCM investigated is petroleum jelly and paraffin wax (PW); in addition to
aluminium scrap and aluminium oxide nano powder were explored. Three sets of experiments
were carried out to investigate the effect in the presence of PCM and the addition of metal
scraps or nanoparticles. The first set of experiments was to analyse the presence and types of
PCM; as for the second set of experiments, it was to study between the models with pure PCM
and aluminium scrap mixed PCM; lastly, for the third experiment, the aluminium scrap mixed
PCM was compared with the nanoparticle embedded PCM.
Results: The solar still with PW achieves an efficiency of 26.38 %, which has the highest
efficiency in Experiment 1 when compared with solar stills without PCM or with petroleum
jelly. In Experiment 2, the solar still with aluminium scrap mixed PW has an efficiency of
4.10 % higher than the solar still with only PW. Lastly for Experiment 3, the solar still with
Al2O3 nanoparticle embedded PW has an efficiency of 3.59 % higher than the solar still with
aluminium scrap mixed PW.
Conclusion: PCM enhances the performance of the solar still, giving a higher water yield and
efficiency compared to solar stills without PCM. The addition of aluminum scrap or
nanoparticle in PCMs further improves the results.
83
Development of Magnetic Responsive Polymeric Microcapsules for the Removal of
Methyl Orange
Wei Yang Tan1, Siew Hoong Shuit1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Conventional dye removal techniques are having limitations such as high
consumption of chemicals, high operation cost, and the generation of secondary wastes. These
problems can be overcome by using “Polyethersulfones Encapsulated Poly
(dimethyldiallylammonium chloride) Functionalized Iron Oxide (PDDA/Fe3O4-PES)”
microcapsules that possess adsorption, degradation, and magnetic responsive properties. The
aim of this study is to identify the suitable concentration of formulation parameters for the
synthesis of PDDA/Fe3O4-PES microcapsules. The selected formulation parameters were
concentration of polyethersulfones (1 – 20 wt. %), iron oxide (1 – 10 wt. %), and poly(ethylene
glycol) (PEG) (1 – 10 wt. %).
Methods: Microcapsules with different concentration of formulation parameters were
synthesized through phase inversion method. The microcapsule-forming solution was added
drop wise into deionized water with the help of a peristaltic pump and the microcapsules were
formed through solvent and non-solvent exchange. The microcapsules were then subjected to
the removal of methyl orange (MO) to identify the suitable concentration for each formulation
parameters.
Results: It was found that the MO removal efficiency was higher for microcapsules
synthesized using 15 wt. % PES compared to 10 wt. %. Next, the removal efficiency of MO
dye increased gradually from 30.42 % to 57.45 % when the concentration of PDDA/Fe3O4
increased from 1 to 10 wt. %. Lastly, the increased in the concentration of PEG from 0 to 10
wt. % had significantly enhanced the removal of MO dye with the highest removal was found
on 10 wt. %.
Formulation Parameter
PES
Removal %
PDDA/Fe3O4 Removal %
PEG
Removal %
0
1
30.42
1
25.92
5
3
37.63
3
37.28
10
41.47
5
48.10
5
52.37
15
48.10
7
52.37
7
62.40
20
10
57.45
10
88.06
Table 1: Removal of MO by Microcapsule Synthesized from Different Formulations
Note: ‘-’ indicates no microcapsule was formed
Conclusion: Through the formulation study, the suitable concentration for the synthsis of
microcapsules was found at 15 wt. % of PES, 7 wt. % of PDDA/Fe3O4, and 10 wt. % of PEG.
The highest removal of MO achieved by the microcapsules was 88.06 %.
84
A Short Study on Long Persistent Luminescence Material and Its Application in
Perovskite Solar Cells
Tejas Sharma1, Jun Hieng Kiat1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Abstract: Perovskite materials has potential for use in third-generation solar cells due to its
wide spectrum absorption, low excitation binding energy and long excitation diffusion length.
In this work, room temperature mixed-cation perovskite material FAMAPbI3 for perovskite
solar cells has been reported. Moreover, we have also prepared long persistent luminescence
material and its application in solar cells. X-ray diffraction (XRD), SEM (Scanning electron
microscope), PL (Photoluminescenc) spectroscopy were also done to reveal the phase
identification, morphology nature and emission spectra respectively. Furthermore, we have
proposed a new material polymer electrolyte which has ability to work as a hole-transport
material.
Methods: The MAI/FAI precursor solution was made as follows: First, 31.4 mg/mL MAI and
43.6 mg/mL FAI were mix together and dissolved in the isopropanol, respectively. Secondly,
43.6 mg of PbI2 were dissolved in appropiate amount of DMSO. Finally, both solution were
mixed together to form FAMAPbI3 perovskite. Now, the deposition of FAMAPbI3 on FTO
(Flourine-doped tin oxide). substrates perovskite material has been done via 2-step spin- coting
method. Here, DMF as an additive is introduced in the second step spin-coating stage to
facilitate the perovskite conversion. Additional, for the luminiscence material, we placed a
mixture of TMB and PPT (total 1mmol, 50–60mg) on a quartz substrate and heated it up to
250 °C for 10s in the glovebox. After melting, the substrate was cooled rapidly to room
temperature and encapsulated under a nitrogen atmosphere using ultraviolet-cured epoxy resin
and glass covers.
Results: XRD patterns of sample FAPbI3 is
indicate, main peaks are located at around 14.2°,
23.8 °and 30° for the mixed-cation FAMAPbI3
perovskite film which confirms the synthesized
compound is perovskite. The surface morphology
of perovskite was studied by SEM image as shown
in Figure 1 which shows uniform film, and no
pinhole has been found.
Figure 1: SEM image of FAPbI3
Conclusion: In summary, the FAMAPbI3 perovskite material has been fabricated. The
optimized ratio of this material will be used in fabrication of laboratory scale perovskite solar
cell in future (preparation mode). Moreover, the luminiscence material and its application in
solar cells has been studies, and the after-glow effect has been well explained.
85
Colorimetric-based Biodegradable Film for Zero and Near-zero Power Ammonia
Sensing
Thiresamary Kurian1, Pei Song Chee1, Chun Hui Tan1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: The use of ammonia as a green fuel for power generation and energy storage is
increasing rapidly for both vehicles and large-scale power plants. Therefore, there is a growing
demand for ammonia sensors in safety and health monitoring, which would lead to a serious
waste-recycling challenge. However, the rigidity structure, frequent calibration requirement,
high working temperature and power consumption of conventional ammonia sensors have
discouraged end-users from adopting them. Hence, new approaches for rapid in-situ monitoring
of NH are highly desired. Herein, a biodegradable film utilizing a colorimetric platform is
proposed to offer excellent zero and near-zero power ammonia sensing at room temperature.
3
Methods: In this work, the colorimetric ink is fabricated via the amalgamation of commercially
available dyes and sodium carboxymethyl cellulose matrix, followed by spin coating it on
cellulose tape to obtain a flexible colorimetric film. The fabricated colorimetric film was
attached on top of the optical window of the commercial ultra-low power microchip for
continuous optical reflective signal measurement in response to NH gas.
3
Figure 1: (a) Colorimetric film architecture; (b) placement of colorimetric film on the optical
window of microchip
Results: With the weight ratio of bromophenol blue to bromocresol green at 2:1, the fabricated
film exhibits the largest bathochromic shift of 190 nm on the main absorption peak and an
uppermost total color change of 85.701 upon exposure to 450 ppm ammonia. The rapid color
response of the fabricated film from yellow to blue within 5 seconds under an ammonia
environment with a protracted recovery time of 5 minutes is capable of being distinguished by
the naked eyes as a zero-power ammonia sensor. Additionally, the fabricated film integrated
with a commercial ultra-low power showed a discernible optical reflective signal upon
exposure to ammonia.
Conclusion: This study explores feasible and rapid ammonia sensing at zero and near-zero
power using biodegradable materials.
86
Development of Polyethylenimine-Polyacrylic Acid Polymeric Membrane with Water
Responsive Self-Healing Property for Water Filtration
Eng Cheong Wong1, Woon Chan Chong1, Ying Hui Ong1, Yean Ling Pang1
1
Department of Chemical Engineering, Lee Kong Chian Faculty of Engineering and Science,
Universiti Tunku Abdul Rahman, Malaysia
Introduction: As the demand of clean water rises globally, membrane filtration has been
utilized in various industries. However, several disadvantages of this method arise such as
membrane brittleness and fouling effect have become the drawback for the industrial operation.
In the recent years, self-healable membrane has been widely studied for various applications,
but it often requires external external stimuli such as pH, temperature, light to initiate healing
effect. In this study, water-responsive self-healing polymeric membrane will be introduced. A
hydrophobic polyethersulfone (PES) is used as the membrane support while polycation
(polyethylenimine, PEI) and polyanion (polyacrylic acid, PAA) are proposed to serve as the
hydrophilic polyelectrolytes to modify the membrane surface.
Method: Firstly, the PES membrane support is immersed in distilled water to remove
membrane surface impurities. Then, PEI solution of certain concentration is deposited thinly
onto the cleaned membrane support, followed by known concentration of PAA solution. Then,
the fabricated membrane is subjected to a small damage. The damaged membrane is then
immersed in distilled water for different time intervals to initiate healing effect. The flux
performance is analyzed for three different phases, as before damage, after damaged and after
healed.
Results: When the membrane is subjected to flux test right after damaged, the flux showed a
decreasing trend throughout the 15 mins analysis. The flux decreased from around 150 L/m2.h
to about 87 L/m2.h, and similar observation for the rest of the flux test, suggesting the fabricated
membrane exhibits autonomous self-healing without the need to stop filtration. After 2 hours
of healing, the flux is seems to be constant, at around 40 L/m2.h. Besides, the healing efficiency
improved as the healing time increases and reached its maximum at about 72% after 2 hours
of healing time, even after 24 hours of healing. When the membrane is damaged, the bonding
at the damage area is broken. Hydrogen bond can be the basis for self-healing due to their
readily reform after being broken. The reversibility of electrostatic and hydrogen-bonding
interaction resulted in self-healing ability of PEI-PAA. Swelling ability is the mechanism of
healing. Upon exposure to moisture, the water molecules diffuse into the fracture area, and
both the polyelectrolytes absorb the water molecule and swells to fill the damage area.
Conclusion: Polyelectrolytes such as PEI and PAA are feasible for the development of waterresponsive membrane with self-healing property.
87
Synthesis of Renewable Heterogeneous Acid Catalyst from Oil Palm Empty Fruit
Bunch for Glycerol-Free Biodiesel Production
Wan-Ying Wong1, Steven Lim1,2, Yean-Ling Pang1,2
1
Department of Chemical Engineering, Lee Kong Chian Faculty of Engineering and Science,
Universiti Tunku Abdul Rahman, Malaysia
2
Centre for Photonics and Advanced Materials Research, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Interest in biodiesel research has escalated over the years due to dwindling fossil
fuel reserves. The implementation of a carbon-based solid acid catalyst in biodiesel production
eradicates the separation problems associated with homogeneous catalysis. However, its
application in the glycerol-free interesterification process for biodiesel production is still rarely
being studied in the literature. In this study, novel environmentally benign catalysts were
prepared from oil palm empty fruit bunch (OPEFB) derived activated carbon which is
sustainable and low cost via direct sulfonation using concentrated sulfuric acid.
Methods: The effects of synthesizing variables such as carbonization and sulfonation
temperatures with different holding times towards the fatty acid methyl ester yield in
interesterification reaction with oleic acid and methyl acetate were investigated in detail.
Results: It was found that the optimum carbonization temperature and duration together with
sulfonation temperature and duration were 600 °C, 3 h, 100 °C and 6 h, respectively. The
catalyst possessed an amorphous structure with a high total acid density of 9.0 mmol NaOH
g−1 due to the well-developed porous framework structure of the carbon support. Attributes of
the prepared catalyst also included excellent sulfur content and the covalently bonded sulfonic
acid groups. Under these optimum conditions, the OPEFB-derived solid acid catalyst recorded
an excellent catalytic activity of 50.5 % methyl oleate yield at 100 °C after 8 h with 50:1 methyl
acetate to oleic acid molar ratio and 10 wt% catalyst dosage.
Conclusion: It was found that carbonization and sulfonation temperatures exhibited a stronger
impact on the interesterification reaction as compared to carbonization and sulfonation
durations. The presented results uncovered a viable synthesis route of an effective catalyst
which equipped with an abundance of biomass resources, mild synthesizing conditions and
simpler biodiesel production routes for sustainable and economical biodiesel production.
88
Functional and Mechanical Properties of Lightweight Foamed Macro Polypropylene
Fibre Reinforced Ferrocement Concrete Incorporating Bio-based and Industrial Waste
Aggregate
Zi Cong Yong1, Ming Kun Yew 1, Ming Chian Yew2, Jing Han Beh3
1
Department of Civil Engineering, Lee Kong Chian Faculty of Engineering and Science,
Universiti Tunku Abdul Rahman, Malaysia
2
Department of Mechanical and Material Engineering, Lee Kong Chian Faculty of
Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia
3
Department of Architecture and Sustainable Design, Lee Kong Chian Faculty of Engineering
and Science, Universiti Tunku Abdul Rahman, Malaysia
Introduction: The green concrete technology was developed rapidly in recent year.
Researchers have replaced the conventional concrete materials with waste materials. This
research is to investigate the effect of macro monofilament polypropylene (PP) fibre into the
lightweight foamed concrete by incorporating the industrial waste and bio-based waste material
as material replacement. The oil palm shell (OPS) and solid polyurethane (SPU) was used as
aggregate replacement material, and the silica fume as cement replacement material.
Methods: There are several tests conducted to evaluate the properties of concrete, which
accordance with the standard testing method, such as compressive strength, splitting tensile
strength, flexural strength, acoustic property, thermal conductivity, and fire resistance test.
Results: The positive result was shown in mechanical and functional properties, when the fibre
proportion increased from 0% to 0.5% of PP fibre. The OPSSPU/0.5 showed the optimum
result with 4.31 MPa 28 days compressive strength, 3.74 MPa residual compressive strength,
0.71 MPa splitting tensile strength, and 1.23 MPa flexural strength. By incorporating 2-mesh
wire into the concrete, it showed 18.92% to 61.11% of increment. It was found that the PP fibre
improved the 12.26% of NRC, 9.79% of STC and 16.31 % reduction of thermal conductivity
properties of concrete. The microstructure of concrete was evaluated by SEM in this research,
it showed the honeycomb structure on OPS surface, the cracking is held along the structure,
however, SPU was mostly covered by cement paste after destructive test.
Conclusion: PP fibre can enhance the properties of concrete except the workability of mortar.
In this research, the combination of industrial waste and bio-based aggregate was successfully
to obtain 3 MPa, which accordance with standard requirement to use in wall panelling of
structure.
89
Energy, Project & Intelligent
Management
90
Recuperation of Regenerative Braking Energy for DC Third Rail System with Energy
Storage
Huoy Lih Bong1, Kein Huat Chua1, Yun Seng Lim1, Li Wang2
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
2
Department of Electrical Engineering, National Cheng Kung University, Taiwan
Introduction: The recuperation of regenerative braking energy for DC third rail system was
investigated. The MATLAB/Simulink model consists interconnection of multiple traction
power substations, a rolling stock model, and battery-based energy storage systems. A control
management system is developed to determine the current flow between the energy storage
device and the DC bus. A comparative study has been carried out for the cases with- and
without the energy storage system. The optimal size and location of the battery are identified.
Methods: The train profiles from the Mass Rapid Transit Line 2 (MRT2) system in Malaysia
are modelled. The simulation model is flexible in that it can accommodate different train;
auxiliary power; and battery parameter changes. These include the non-linear efficiencies of
the motor and the regenerative braking energy, different train acceleration, and the internal
battery resistance which changes relative to the SOC and storage temperature.
Results: Figure 1 shows the average energy consumption without ESS per km at the TPSS for
the northbound travel is 14.3 kWh/km while the southbound travel is 15.3 kWh/km. The
average energy saved with ESS per km for the northbound travel is 3.68 kWh/km while the
southbound travel is 4.29 kWh/km.
Figure 1: Comparison of the energy consumptions and the percentage of energy saved at the
TPSS without ESS and with ESS for the bi-directional travel
.
Conclusion: Recuperation through the battery energy storage system can reduce the electrical
high demands during acceleration and peak travel times. This study has found that an average
of 27% of energy savings was able to be obtained from each of the power substations.
91
Wearable Flexible Antenna for Microwave Wireless Power
1
Xi Liang Chang1, Pei Song Chee1, Eng Hock Lim1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Recently with the rise of 5G technology and beamforming techniques being
massively used, far-field Wireless Power Transfer (WPT) has become a topic of interest to
resolve the power charging problem. Far-field WPT involves a rectenna (antenna + rectifier)
to harness or transfer energy from the ambient RF power in free space or a dedicated RF power
from a power base station/transmitter [1]. Here we proposed a flexible, compact wearable dualband wearable antenna for wireless transfer applications. The antenna’s resonant frequency
was designed at 2.40 GHz and 5.20 GHz, which can be easily available from any
commercialized WiFi modem.
Methods: To evaluate the WPT performance of the proposed wearable antenna, an RF-to-DC
microchip (RFD102a) was connected to the antenna. A 30 dBm input power is provided with
a microwave signal generator to the transmitter antenna at 2.44 GHz and 5.18 GHz. The
proposed antenna was placed on a phantom skin model with a separation distance from the
transmitter antenna of 1.3 m for 2.44 GHz and 2.7 m for 5.18 GHz, according to Fraunhofer’s
far-field distance theory [2].
Results: A load-swept test was conducted from 1 kΩ to 100 kΩ to determine the optimal load
of the proposed wearable antenna. The experiment results show that the proposed antenna can
achieve ⁓ 0.4 V and ⁓ 0.30 mV with maximum power ⁓7.2 µW and ⁓ 0.25 nW with an optimal
load of 20 kΩ at 2.44 GHz and 56 kΩ at 5.18 GHz. A proof-of-concept of the microwave farfield wireless power transfer was demonstrated by successfully lighting an LED.
Conclusion: A flexible dual-band wearable antenna (2.44 GHz and 5.18 GHz) was proposed
with experimental data showing that the maximum wireless output power is sufficient for
ultralow-powered wearable applications. A proof-of-concept experiment of the wireless power
transfer wearable antenna has been demonstrated by lighting up an LED.
References: 1. Gu, X., Hemour, S. and Wu, K. (2022). Far-Field Wireless Power Harvesting:
Nonlinear Modeling, Rectenna Design, and Emerging Applications. Proceedings of the IEEE,
[online] 110(1), pp.56–73. doi:10.1109/JPROC.2021.3127930.
2. Selvan, K.T. and Janaswamy, R. (2017). Fraunhofer and Fresnel Distances: Unified
derivation for aperture antennas. IEEE Antennas and Propagation Magazine, [online] 59(4),
pp.12–15. doi:10.1109/MAP.2017.2706648.
92
Development of Disruptive Artificial Intelligence Prototype for Quantity Surveying
Practices
Siak Kor Chew1, Fah Choy Chia1, Ananthan a/l Valitherm1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Construction industry plays significant role in a nation’s Gross Domestic
Product (GDP). Construction project cost is one of the construction project triple constraints.
However, the practice has been worsened with the heavy reliance to manual quantity estimating
which prone construction project cost estimating with greater risks of low reliability, and not
to mention the reliance on high number of professional estimators doing quantity estimation
impose greater cost of the professional services [1].
Methods: Literature studies are conducted and identified that technology implementation
promotes the industry productivity. There are components that play crucial role in successful
implementation of technology. These theoretical found components are focused and used to
develop prototype program code for this research study. Building Information Modelling (BIM)
has considered to associate as part of the prototype to contain project data. Internet connectivity
was then used to connects between BIM with Application Programming Interface (API).
Various Artificial Intelligent (AI) modules were branched into API composition and run online
to analyse BIM. Bills of Quantities (BQ) then been created automatically with the available
descriptions for bill items, respective quantities extracted from BIM, and unit-based pricing to
each bill items.
Results: The research outcome is to utilize DSRP model and literature findings on effective
technology implementation components to develop prototype. The prototype then
demonstrates efficient solution to current practice.
Conclusion: The research results identify solution that possibly improving industry efficiency
in project cost estimating. The implication of this finding demonstrates possibilities to
transform project cost estimating convention practices with technology. Also promotes
effective use of technology with components of implementation.
Reference: 1. Saleh, M.A.E. (1999). Automation of Quantity Surveying in Construction
Projects. Journal of Architectural Engineering, 5(4), pp.141–148. doi:10.1061/(asce)10760431(1999)5:4(141).
93
Long Short-Term Memory Recurrent Neural Network for Estimating State of Charge
of Energy Storage System for Grid Services
Dylon Hao Cheng Lam1, Yun Seng Lim1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Coulomb counting, empirical model, extended Kalman filter, and unscented
Kalman filter are the existing methods for state of charge (SOC) of batteries in energy storage
system. However, these methods require accurate battery models that reduce the speed of
estimating SOC, which makes them unsuitable to be used for batteries in an energy storage
system (ESS). Machine learning (ML) techniques can be used in this aspect as they do not
require a battery model and are immune to initial and cumulative errors. Among the ML-based
techniques, long short-term memory network (LSTM) has a feedback-loop characteristic,
which considers the current and historical SOC when estimating SOC of batteries. At present,
LSTM has not been used for batteries in ESS during peak demand reductions. If the secondlife batteries are used in ESS for any grid services, then they are subject to extreme operating
conditions. Precaution must be taken to monitor SOC of individual batteries to avoid any
potential damage to any batteries.
Methods: The performance of different configurations of LSTM networks with different
network parameters are studied first. Then, the best configuration of LSTM network is chosen
to compare its performance with that of other existing methods.
Results: LSTM network is found to be effective even though the network begins with an
inaccurate SOC, which makes them a suitable technique to be used for second-life batteries in
ESS for grid services. The estimation accuracy of the LSTM network is also higher than
conventional SOC estimation techniques such as coulomb counting and empirical model, and
other ML techniques that do not have a feedback loop such as the feedforward neural network
(FNN).
Conclusion: LSTM network is a machine learning based technique that is shown to be suitable
for SOC estimation compared to other conventional SOC estimation methods.
94
Twin Delayed DDPG Based Dynamic Power Allocation in Internet of Robotic Things
1
Homayun Kabir1, Mau-Luen Tham1, Yoong Choon Chang1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: In order to guarantee the quality of service (QoS) for internet of robotic things
(IoRT), radio resources (RA), for example, transmitting power allocation (PA), interference
management, throughput maximization etc., should be efficiently employed and allocated
among user equipment (UE). Traditionally, RA allocation has been formulated using
optimization problems, that are generally nonconvex and nondeterministic polynomial-time
hardness (NP-hard). In this research, one of the most crucial challenges in RA management is
the antenna emitting power called PA, considering the interfering multiple access channel
(IMAC) has been considered. In addition, UE has a natural movement behavior that directly
impacts the channel condition between the remote radio head (RRH) and UE. Additionally, we
have considered two well-known UE mobility models i) random walk and ii) modified GaussMarkov (GM).
Methodology: Deep reinforcement learning (DRL), which consists of reinforcement learning
(RL) and deep learning (DL), allows an agent to make decisions regularly, monitor the
outcomes, and then automatically modify its approach to achieve at the best possible policy. In
the actor-critic (AC) method of DRL, the advantage of value-based and policy-based have been
implemented combinedly, which handles the continuous and high-dimension action space.
Twin delayed deep deterministic policy gradient (TD3) consists of double DQN, policy
gradient and actor-critic combinedly which considers approximation error function to improve
the performance and stability. As a result, TD3 performed better than other model-free
algorithms.
Results: Fig. 1 compares the proposed TD3 algorithm with respect to two DRL-based
algorithms: traditional DDPG and DQN, and two traditional algorithms: FP and WMMSE,
which are considered benchmarks for evaluating our proposed algorithm in two different
scenarios i) random walk mobility model (Fig.1 (a)), and ii) modified Gauss-Markov mobility
(Fig.1 (b and c)).
(a)
(b)
(c)
Fig. 1: Simulation results of proposed TD3 algorithm in PA by maximizing average sum-rate
Conclusions: For the dynamic PA issue of two different scenarios i) random walk mobility
model, and ii) modified Gauss-Markov mobility in IoRT, our suggested TD3 algorithm have
been outperformed model-based algorithms like FP and WMMSE as well as model-free
methods DQN and DDPG in terms of simulation results. In future, we will investigate user
association by applying a hybrid action space DRL algorithm.
95
Intelligent Reservoir Operation System Based on Artificial Intelligence and Metaheuristics Models
1
1
Karim Sherif Mostafa Hassan Ibrahim, 1Yuk Feng Huang, 1Chai Hoon Koo
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Climate change is a long-term alteration in normal weather patterns that has an
impact on local, regional, and global climates. Managing water resources more effectively is
one of the main strategies for overcoming this problem. Because the reservoir is an important
piece of infrastructure for water resource management, it needs precise water resource forecasts.
Artificial Intelligence and Machine Learning models (AI & ML) approaches are increasingly
popular for reservoir inflow predictions.
Methods: In this study, the multilayer perceptron neural network (MLP), Support Vector
Regression (SVR), Adaptive Neuro-Fuzzy Inference System (ANFIS), and the Extreme
Gradient Boosting (XG-Boost), were adopted to forecast reservoir inflows for monthly and
daily timeframes. while real coded genetic algorithms (RCGA), particle swarm optimization
(PSO), Firefly (FA), and nuclear reactor optimization (NRO) integrated the forecasting models
output to derive an optimal strategy for the reservoir operations. A total of eight performances
metrics were used to test the machine learning and optimization algorithm models namely Root
Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Average Error
(MAE), coefficient of correlation (R), Resiliency, Reliability, Vulnerability, and sustainability.
Results: XG-Boost scored a R² of 0.8831 surpassing the other 3 models while firefly algorithm
scored a sustainability score of 0.331 and 0.41 for conventional and integrated system
respectively.
Conclusion: All the machine learning model were able to forecast the reservoir inflow with
XG-BOOST outperforming the other three models. Similarly, all the metaheuristic algorithms
generated a release policy with Firefly generating the most optimal and sustainable release
curves.
96
Initiating Innovative Technology-based Health and Safety Management for
Construction Projects during COVID-19 Pandemic
1
Yi Tong Kum1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: The global construction industry has experienced a terrible turn due to the
COVID-19 viruses. For the sake of economic rejuvenation, no doubt that reoperation of
construction operations is essential despite the fact that the contagious disease has not been
eliminated. However, a portentous number of construction-related infection cases is reported,
causing productivity losses on construction sites. Therefore, this study discussed the
capabilities of innovative technologies in transforming construction health and safety (H&S)
management in the pandemic using partial least squares structural equation modelling (PLSSEM) approach. Figure 1 depicted the conceptual framework of the study.
Table 1: Conceptual framework
Methods: Following an extensive literature review, a questionnaire survey is developed to
collect affirmative responses. A total of 203 valid responses are returned from Malaysian
construction professionals. The data is checked and further analysed through exploratory factor
analysis (EFA) to group the challenges. Then, PLS-SEM approach was engaged to investigate
the relationships between the H&S measures, challenges and the innovative technologies.
Results: EFA results indicate that the underlying challenges are lack of resources and inherent
nature of construction, negligence and ignorance, low-wage blue-collar workforce, ineffective
H&S management, and poor sanitizing and disinfecting strategies on site. The PLS-SEM
results illustrated 3 significant relationships: 1) the challenges have negative influences on the
COVID-19 H&S preventive measures, 2) innovative technologies positively influence H&S
management for construction projects during COVID-19 pandemic and 3) technology-based
H&S management positively influences the challenges is implementing COVID-19 H&S
guidelines on construction sites.
Conclusion: This study highlighted the contribution of innovative technologies in construction
H&S management during the pandemic.
97
Comprehensive Modelling for Analyzing the Power Conversion Efficiency of
Polycrystalline Silicon Photovoltaic Device under Indoor Operating Conditions
1
Son Qian Liew1, Kok-Keong Chong1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Recently, most of the studies were mainly focused on the variation between
outdoor solar spectral irradiance and standard AM1.5G spectrum, as well as their effects
towards the performances of different PV technologies. Interestingly, limited studies have been
conducted to study the effect of artificial lighting on the power conversion efficiency of the
photovoltaic (PV) device. The spectral irradiance produced by indoor lighting differs
significantly as compared to the that of standard AM1.5G spectrum, which inevitably leads to
different performances of the PV under standard test conditions and under artificial lighting
exposure. In this study, the performance modelling has been carried out based on the
comprehensive method proposed by Chong et al. to predict the PCE of organic solar cell
devices. From the measurement results, the spectrum of LED illumination has been compared
with that of AM1.5G, in which the LED shows a relatively narrow band with significant peaks
at 450 and 560 nm. Furthermore, the theoretical model has been successfully validated by
comparing the simulated PCE and the measured PCE at reasonable deviations in the range of
3.0 – 23.3%.
Methods: The initial step of the process is to acquire J-V curves of the PV devices under
various LED intensities. A few parameters can be extracted from the measured J–V curves,
such as short-circuit current density (Jsc), open-circuit voltage (Voc), and fill factor (FF). The
extracted results are summarized and plotted as Voc vs. Jsc and FF vs. Jsc graphs to obtain the
relationship of Voc and FF in the function of Jsc. These results are inputted to the proposed
model and the deviation between experiment and modelled results are compared respectively.
Results: Based on the collected data, the values for ∆PCE and ∆Jsc are in the range of 2.8 –
22.2% and 2.8 – 26.3% respectively. The variation between theoretical and experimental results
are considered as random error, which is mainly caused by the measurement error, i.e., the
uncertainty of the lux meter that is used to measure the LED intensities. In short, the prediction
is reasonably accurate for LED lighting conditions (low light intensity).
Conclusion: In this work, the J–V curves of the polycrystalline PV device have been measured
under different LED irradiances. The measured PCEs under LED lighting show a decreasing
trend when the intensities of LED illumination are decreased. The spectrum of LED
illumination has been investigated and compared with the spectrum of AM1.5G, in which the
LED shows a relatively narrow band with significant peaks at 450 and 560 nm. The empirical
formulas were computed for Voc vs. Jsc and FF vs. Jsc, which served as input values for the
theoretical modelling. Finally, the theoretical modelling has been successfully validated by
comparing the between the measured and the simulated PCE values for different LED
intensities in the range of 2.3 – 9.3 Wm–2, whereby the prediction is reasonably accurate with
∆PCE in the range of 2.8 – 22.2%.
98
ANN-based Load Controller with Robust Input Normalization for Energy Saving
and Peak Demand Reduction
Xie Cherng Miow1, Yun Seng Lim1, Lee Cheun Hau1, Boon Han Lim1, Wai Meng Chin2
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
2
Daikin Research & Development Malaysia, Daikin Malaysia, Malaysia
1
Introduction: Demand response is used to promote energy saving by reducing power
consumption and peak demand. Typical demand response controllers use predetermined
conditions such as time, demand levels, and temperature. However, such controllers are unable
to respond to new power demands effectively. The existing machine learning controllers are
also unable to respond to future demands as they are trained with historical data. Thus, an
artificial neural network (ANN)-based load controller with robust input normalization is
proposed in this study to provide energy saving and peak demand reduction.
Methods: Refrigerators and air-conditioners at Daikin Research & Development Malaysia
(Figure 1) are being controlled using the proposed controller. The loads are monitored and
controlled by Internet-of-Things (IoT) devices in the LabVIEW program through the local
network. The real-time power demand, indoor temperature, outdoor temperature, and solar
irradiance are closely monitored to provide effective control to maintain the comfortability
indoors while reducing power consumption.
Results: The recorded data is categorized into meteorological conditions from extremely sunny
to extremely cloudy to determine the load power consumption under different weather
conditions. Results between the controlled and non-controlled are collected and compared
statistically. Results show that the proposed controller can increase energy saving daily by
11.6%.
Figure 1: Setup of refrigerators and air-conditioners control at Daikin
Conclusion: The proposed controller can respond to the new demands while providing energy
savings and reducing peak demands.
99
Application of Artificial Intelligence in Optimization Reservoir Management
Mohammad Omar Hamid Wagiealla1
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Water scarcity has become a major worldwide concern and a source of
numerous disputes across the world. Full control and the optimal management and distribution
of water are becoming more critical than ever. Reservoir operation optimization is a crucial
sector in managing and allocating surface water resources and ensuring the optimal usage of
water stored behind dams. It is considered a complicated engineering challenge because of the
stochastic nature of the input, such as inflow and required supplies for different uses, and their
unpredictability. The challenge is to find the optimal releasing policy that meets the
requirements and not violating the restrictions. Artificial intelligence provided reservoir
management with powerful models in the past decades, including models based on Linear
programming, nonlinear, etc. This research is studying metaheuristic algorithm models due to
their high capability in solving such problems. The research presents an optimization model
based on a population-based optimization algorithm.
Methods: The methodology depends on the continuity equation to produce water releasing
curve. The performance of the proposed model will be tested against two models based on the
particle swarm algorithm (PSO) and artificial bee colony (ABC). The research includes testing
of model performance, which includes the system indicators, such as reliability, resiliency,
vulnerability, and root mean square error, and the cross-checking with the mentioned two
models, which are highly recognized in both the reservoir management field and publication.
Results: Currently, the results are still being gathered and prepared. The early findings
exhibited that the proposed algorithm is surpassing the other algorithm's performance. It
demonstrated a higher capability to reduce water deficits, and supply the downstream. More
outcomes are being processed at the moment.
Conclusion: The proposed method shows superiority over the other methods. Its primary
findings suggest that it will over perform the PSO and ABC algorithms.
100
Application of Convolution Neural Network for Adaptive Traffic Controller System
1
Muaid Abdulkareem Alnazir Ahmed1, Hooi Ling Khoo1, Oon-Ee Ng1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: This paper presents an adaptive traffic control system based on deep
convolution neural network (DCNN) technique for a multimodal traffic environment. The deep
learning controller technique is based on feature mapping to estimate the optimal state-action
value function. The controller executes acyclic phase assignment based on minimum green
time duration for traffic signal operation. Moreover, the research implements Discrete Lane
Cells (DLC) approach for state representation.
Methods: The DCNN agent is used to develop adaptive logic for isolated intersection. The
state inputs comprise of vehicle’s position, travel speed and traffic light state. The reward
policy is based on optimising waiting time at intersection level. The test scenarios consist of
four (4) micro-models representing various traffic flow conditions.
Results: The findings indicate that the DCNN system has superior performance in oversaturated traffic condition. The DCNN agent has achieved significant 85% to 95% lower
waiting time, l7% to 38% shorter travel time, and it has mitigated the highest median flow rate
at 295 veh/s in comparison to other controller systems. For under-saturated test scenarios, a
fair comparable performance is measured for the proposed controller.
Conclusion: The proposed DCNN system provides stable performance across all the tested
signal junction scenarios in comparison to other controller systems. Two design parameters
have contributed to this stability characteristic including the feature mapping of convolution
layers and Discrete Lane Cells (DLC) technique which simplifies the state-space problem in
traffic environment.
101
Why You’re Here COVID-19? You’re Affecting My Company’s Operation: How it
Impacting Malaysia Main Contractor’s Working from Home
Wei Heng Ong1, Ooi Kuan Tan1,2, Ming Han Lim1
1
Centre for Disaster Risk Reduction (CDRR), Lee Kong Chian Faculty of Engineering and
Science, Universiti Tunku Abdul Rahman, Malaysia
2
Belt & Road Strategic Research Centre, Lee Kong Chian Faculty of Engineering and
Science, Universiti Tunku Abdul Rahman, Malaysia
Introduction: The COVID-19 pandemic is an unpredictable event that has had unexpected
effects on many countries, including Malaysia. The Government of Malaysia implemented the
Movement Control Order (MCO) to restrain the outbreak of the pandemic. As a result, MCO
has had a huge impact on various industries in Malaysia, especially the construction industry.
Therefore, time and cost become critical components in order to successfully deliver the project
and are the factors most affecting by the COVID-19. Thus, this paper attempts to explore the
impact of the main contractor’s awareness, perceptions and readiness for the Covid-19
pandemic. In order to get real and accurate data and quick feedback from the respondents. Data
were collected and analysed using SPSS software.
Methods: The quota and snowball samplings were the sampling method used to collect data
for analysis in this paper. The questionnaire was sent through email and google form to the
main contractors in Klang Valley area projects. There was a total of 167 samples collected and
analyzed by SPSS software. The findings of this study summarize the characteristics of the
main contractor’s response to the COVID-19 pandemic.
Results: This study found that the main contractor’s perception and readiness consist of
correlation to the pandemic disruption in Malaysia while the main contractor’s awareness
showing no correlation. The position level with main contractor’s traits as the moderation has
to be found with non-significant to the pandemic disruption. These results can indicate which
traits in main contractor are most correlation with pandemic disruption in order to focus on the
traits that need strengthening and cultivation.
Figure 1: Conceptual Framework of the Study
Conclusion: This study has provided better understanding in which personality traits in main
contractor are the most affect to the impact of pandemic disruption in Malaysia by studying
awareness, perception and readiness characteristic.
102
Exploring Agile Project Management in the Malaysian Construction Industry
1
Tung Yew Hou1, Chia Fah Choy1, Felicia Yong Yan Yan1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
Introduction: Agile project management (APM) has been widely used in recent years as a
mean to counter the dangers of predictive, front-end planning methods that often lead to
downstream development pathologies. APM emphasises on individuals and interactions over
processes, practical deliverables over comprehensive documentation, customer collaboration
over contracts negotiation, and responsiveness over rigid planning. Although agile has its roots
in software and information technology, agile adoption is growing and expanding in a wide
range of industries including construction. Little research has been conducted regarding APM
in the construction industry. This research explores the application of APM by the Malaysian
construction practitioners.
Methods: This research was based on a survey conducted using an online questionnaire. The
data collection exercises were held in Malaysia from July 2020 until October 2022. A ninepage structured questionnaire was distributed to the four target groups: developers, consultants,
contractors, and suppliers through LinkedIn professional networking. This is exploratory
research as a questionnaire is designed to explore the application of APM by the Malaysian
construction practitioners. Following a thorough literature search, 70 agile practices were
consolidated. All these practices were then assembled into a questionnaire distributed to the
construction practitioners. The collected data were analysed and interpreted using quantitative
analysis, in which both descriptive and factor analysis.
Results: 252 respondents out of approximately 1500 construction practitioners or 15.8%
answered the online questionnaire. This research reveals 74.2% of total responses agreed that
agile practices would help to deliver construction projects more successfully. Factor analysis
identifies 11 underlying factors to be the agile project management of construction projects to
relate to effective dialogue, resilient team, adaptive development, tailored processes,
continuous improvement, practical delivery, trusting environment, self-organising team,
collaborative stakeholders, supportive environment, and progressive estimate.
Conclusion: Understanding these 11 factors of agile project management could help
construction practitioners to deliver construction projects effectively.
103
Operation of Klang Gate Dam: A Comparison of Reservoir Simulation and Reservoir
Optimisation under Climate Change Impact
Vivien Lai1, Huang Yuk Feng1, Koo Chai Hoon1, Al-Mahfood Ali Najah Ahmed2
1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman,
Malaysia
2
Institute of Engineering Infrastructure, Universiti Tenaga Nasional, Malaysia
Introduction: A reservoir or dam stores excess water to avoid downstream flooding and to
prepare for drought. Whale Optimisation Algorithm (WOA) balances exploration and
exploitation during global optima searches and avoids trapping in local optima. In 1998,
extreme climate change caused a major water crisis at Klang Gate Dam (KGD). Climate
change's impact on the future KGD reservoir was barely investigated. This paper investigates
the impact of climate change under RCP 2.6, RCP 4.5, and RCP 8.5 via sim-heuristic concepts
using ANN for simulations and WOA for optimisation to obtain optimal water releases at KGD
from 2020 to 2099. This analysis should assist policymakers in improving KGD water resource
management.
Methods: The analysis begins with the climate data preparations in which the data is obtained
from the Coupled Model Intercomparison Project 5 (CMIP5) under RCP 2.6, RCP 4.5, and
RCP 8.5 for maximum temperature scenario of future water demand for years 2020 to 2099. In
the reservoir simulation process, an artificial neural network (ANN) was utilised. The findings
were then compared to the reservoir optimisation by WOA in terms of the storage failure
percentage.
Results: The results obtained throughout the simulation and optimisation phases are depicted
in Table 1. The average storage failure rate for all RCPs in reservoir optimisation was 34.93 %,
on the other hand the average storage failure rate in reservoir simulation was 97.29 %. Since
the average storage failure for reservoir simulation was significantly higher than reservoir
optimisation, this indicates that the reservoir operating system should be managed using the
optimisation approach. WOA demonstrated the periodic reliability of 37.60% and 13.96%,
respectively under scenario of RCP 2.6, and RCP 4.5.
Maximum Temperature Water Demand
Indices
RCP 2.6
RCP 4.5
RCP 8.5
Storage failure, in Simulation only- ANN (%)
98.02
97.19
96.77
Storage failure, in Optimization- WOA (%)
28.44
45.42
30.94
Resilience, max. number of water deficit (month)
11
92
205
Vulnerability
0.609
0.478
0.191
Shortage index
0.0018
0.0021
0.0003
Periodic reliability, in exact period (%)
37.60%
13.96%
0
Table 1: Reservoir Risk Performance in Maximum Temperature Scenario of Future Water
Demand
Conclusion: By implementing reservoir optimisation via WOA generates an optimal reservoir
management strategy for policymakers under various RCPs rather than using ANN.
104
105
The 4th postgraduate colloquium was participated by LKC FES postgraduate students from
five research areas, namely: Applied Engineering; Applied Mathematics, Simulation &
Computing; Health Science & Technology; Green Technology & Sustainable
Development; and Energy, Project & Intelligent Management.
The purpose of the colloquium is mainly to provide a platform for the postgraduate
students in Lee Kong Chian Faculty of Engineering and Science (LKC FES) to present
their recent works or findings in their fields of research. In addition, this event also serves
as a platform for postgraduate students and academic staff of LKC FES to exchange ideas
and gather feedback on their research works.
Keynote speakers for this colloquium are:
1. Prof Dr Zhou Jinyuan, Professor, Department of Radiology, Johns Hopkins
University School of Medicine, USA
2. Prof Dr Chong Kok Keong, Professor, Department of Electrical and Electronic
Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku
Abdul Rahman, Malaysia
3. Prof Ts Dr Yau Kok Lim, Professor, Department of Internet Engineering and
Computer Science, Lee Kong Chian Faculty of Engineering and Science, Universiti
Tunku Abdul Rahman, Malaysia
4. Dr Steven Lim, Assistant Professor, Department of Chemical Engineering, Lee Kong
Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia
106