FRONT PAGE

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CONFERENCE ABSTRACTS

10th International Conference on Computer Modeling and

Simulation (ICCMS 2018)

Workshop

7th International Conference on Intelligent Computing and

Applications (ICICA 2018)

January 8-10, 2018 Sydney, Australia

Published by

Sponsored by

CONTENT

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Welcome Address····························································································3 Tips······································································································4 Venue·····························································································5 Technical Program at a Glance·········································································6

Introduction of Speakers·················································································9 Session Schedule····························································································13 Listeners List·································································································50

WELCOME

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We are pleased to welcome you to ICCMS 2018 (with workshop ICICA 2018), which will be held in Sydney,

Australia during January 8-10, 2018.

We wish to express our sincere appreciation to all individuals and organizations who have contributed to the

conference. Special thanks are extended to our colleagues in the technical program committee for their thorough

review of all the submissions, which is vital to the success of the conference, and also to the members in the

organizing committee who had dedicated their time and efforts in planning, promoting, organizing and helping

the conference. Our special thanks also go to the invited speakers as well as all the authors for contributing their

latest research to the conference.

This conference program is highlighted by the six speakers: Prof. Ghassan Beydoun, University of Technology

Sydney, Australia; Prof. William Guo, Central Queensland University, Australia; Prof. Girija Chetty, University of

Canberra, Australia; Prof. Jun Shen, University of Wollongong, Australia; Prof. Wernhuar Tarng, National Tsing

Hua University, Taiwan; Prof. Eric Jiang, University of San Diego, USA.

Oral presentations are divided into six parallel sessions. One best presentation will be selected from each session,

evaluated for: Originality, Applicability, Technical Merit, Visual Aids, and English Delivery. We wish you the best

of luck with your presentations!

Sydney is the state capital of New South Wales and the most populous city in Australia and Oceania. It is also a

gateway to Australia for many international visitors. Popular destinations include the Sydney Opera House, the

Sydney Harbour Bridge, Watsons Bay, The Rocks, Sydney Tower, Darling Harbour, the State Library of New South

Wales and etc.

We wish you a pleasant and memorable experience in this conference as well as in this city.

Organizing Committee

Sydney, Australia

January 8-10, 2018

TIPS

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General tips: Your punctual arrival and active involvement in each session will be highly appreciated.

You are welcome to register at any working time during the conference.

Certificate of Participation will be awarded after your presentation.

One Best Presentation will be selected from each session and the author of best presentation will be

awarded when the session is over.

Please kindly keep your Paper ID in mind so that the staff can quickly locate your registration information

onsite.

Please kindly make your own arrangements for accommodations.

Please keep your belongings (laptop, phones, and camera etc.) safe and secure in the public places like

places, buses, metro, etc.

Tips for Oral Presentation:

Prepare your presentation PPT or PDF files in advance

Regular oral presentation: 15 minutes (including Q&A)

Keynote speech: 40 minutes (including Q&A)

Laptop (with MS-Office & Adobe Reader), projector & screen, and laser sticks will be provided by the

conference organizer

VENUE

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Rendezvous Hotel Sydney Central https://www.tfehotels.com/brands/rendezvous-hotels/rendezvous-hotel-sydney-central

Add.: Cnr of George & Quay Streets, Sydney NSW 2000, Australia

****************************************************************************************************

AGENDA

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<January 8, 2018, Monday>_Morning

Lobby

10:00-12:00 Registration & Materials Collection

<January 8, 2018, Monday>_Afternoon

State Room

13:30-13:40 Opening Remarks Prof. Ghassan Beydoun

University of Technology Sydney, Australia

13:40-14:20 Keynote Speech I

Prof. William Guo Central Queensland University, Australia

Speech Title: What can a reviewer do on your academic

work?

14:20-15:00 Plenary Speech I

Prof. Wernhuar Tarng

National Tsing Hua University, Taiwan

Speech Title: Applications of Virtual Reality and Gamification

in Learning Nanotechnology

15:00-15:30 Coffee Break

15:30-18:00

Session I - Modeling method and optimization-10 Presentations

SY025, AC023, SY2006, SY055, SY057, SY024, SY074, SY023, SY033, SY085-a

AGENDA

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< January 9, 2018, Tuesday>_Morning

9:00-9:40 Keynote Speech II

Prof. Ghassan Beydoun

University of Technology Sydney, Australia

State Room

Speech Title: Using Agent Based Analysis to Manage

Complexity in Disaster Management Planning

09:40-10:20 Keynote Speech III

Prof. Girija Chetty

University of Canberra, Australia

Speech Title: Towards A Global Collective Intelligence -

Leveraging Advances in AI, Big Data and Multimodal

Science

10:20-10:50 Coffee Break & Group Photo

10:50-11:30 Plenary Speech II

Prof. Jun Shen

University of Wollongong, Australia

State Room

Speech Title: MLaaS(Micro Learning as a Service): taking

advantage of fragmented time for fragmented knowledge

11:30-12:00 Invited Speech

Prof. Eric Jiang

University of San Diego, USA

Speech Title: Integrating Labeled and Unlabeled Data for

Classification

Lunch <12:00-13:30> Location: Restaurant Note: lunch coupon is needed for entering the restaurant.

< January 9, 2018, Tuesday>_Afternoon

13:30-16:00

Session II – System modeling and simulation- 10 Presentations

Enmore SY034, SY030, SY067, SY062, SY087, SY088, SY2001, SY037, SY043, SY073

Session III - Software development and system simulation-10 Presentations

Belvoir AC034, SY003, AC032, SY0O7, SY056, AC029, AC038, SY021, SY059, SY2007

Poster Session

Seymour AC045, AC302, SY040, SY049, SY069, SY031-A, SY051, SY078

AGENDA

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Dinner <19:00-21:00> Location: Restaurant

Note: dinner coupon is needed for entering the restaurant.

< January 10, 2018, Wednesday>

Level 2, Building 11, 81 Broadway, Ultimo NSW 2007 (Please arrive 10

minutes earlier of each group.)

Building 11 is the new IT building in UTS (finished in 2015). The building itself is very technologically advanced, and show cases sustainibility. 1000's censors, solar cellss, etc. Tour guide will take you to various facilities and research labs in building 11.

Each group can be 25-30 people. You can choose a preferable group in advance.

16:00-16:15 Coffee Break

Foyer

16:15-19:00

Session IV- Modeling and dynamic analysis of mechanical system-11 Presentations

Enmore

AC026, SY039-a, SY061, SY008, SY009, SY045, SY011-a, SY012-a, SY081,

SY086-a,SY060

Session V - Computer information engineering and image processing-11

Presentations Belvoir

AC001-A, AC002, AC007-A, AC027, AC028, AC031, SY050, SY058, SY035, SY066, SY2005

Session VI - Communication and information system-11 Presentations

Seymour AC004-A, AC005, AC015, SY048, SY092, SY079, SY2002, SY2004, SY2003, AC024,

AC010

10:00am-12:00am Academic Visiting UTS

10:00am-11:00am Group 1

11:00am-12:00am Group 2

SPEAKERS

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Prof. Ghassan Beydoun

University of Technology Sydney, Australia

Professor Ghassan Beydoun is currently based at the Faculty of Engineering and Information Technology in

University of Technology Sydney, where he is also deputy Head of School (Research) Systems, Management and

Leadership at the University of Technology Sydney. He is also an adjunct senior research fellow at the School of

Information Systems, Management and Technology at the University of New South Wales, an associate editor of

the International Journal of Intelligent Information Technologies (IJIIT) and an Editorial member of the Journal of

Software. He received a degree in computer science and a PhD degree in knowledge systems from the University

of New South Wales in 2000. His research interests include multi agent systems applications, ontologies and their

applications, and knowledge acquisition. He is currently working on a project sponsored by an Australian

Research Council Discovery Grant to investigate the best uses of ontologies in developing methodologies for

complex systems and another project with SES on exploring the use of ontologies for flood management decision

support. He has authored more than 100 journal and conference papers in these areas over the past 15 years. His

most recent publication appeared in IEEE Transactions of Software Engineering, Information Systems journal,

Information and Management, International Journal of Human Computer Studies, Information Processing and

management and others.

Prof. William Guo

Central Queensland University, Australia

Professor William Guo teaches and researches in computation and applied mathematics at Central Queensland

University Australia (CQU). He was the Dean of the School of Engineering and Technology at CQU from Jan

2014-Jan 2015, and the Deputy Dean of the School from Feb 2013-Jan 2014. He has significant experience in

academic governance through his services in various committees and boards since 2009, including CQU Education

Committee (2011-2012), CQU Academic Board (2013-2014), and Australian Council of Deans of ICT (2013-), and

as an Executive Member of Australian Council of Professors and Heads of IS (2012-). His teaching over the past 13

years has covered data structures and algorithms analysis, computational intelligence, systems analysis and

SPEAKERS

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architecture, IT/IS project management, e-Business, digital forensics, information security, research methods, and

engineering mathematics. He was the recipient of CQU Vice-Chancellor’s Award for Good Practice in Learning and

Teaching (2012) and Commendation in Student Voice Awards (2014). His research interests include computational

intelligence, image processing, bioinformatics, big data modelling and simulation. He has published more than

seventy papers in international journals and conference proceedings, and a new text (published by Pearson) in

advanced engineering mathematics in 2014. He has supervised research higher degree students to completion.

He is a member of IEEE, ACM, ACS, and Australian Mathematics Society (AUSTMS ).

Prof. Girija Chetty

University of Canberra, Australia

Dr. Girija Chetty has a Bachelors and Masters degree in Electrical Engineering and Computer Science, and PhD in

Information Sciences and Engineering from Australia. She has more than 25 years of experience in Industry,

Research and Teaching from Universities and Research and Development Companies from India and Australia,

and has held several leadership positions including Head of Software Engineering and Computer Science, and

Course Director for Master of Computing Course. Currently, she is the Head of Multimodal Systems and

Information Fusion Group in University of Canberra, Australia, and leads a research group with several PhD

students, Post Docs, research assistants and regular International and National visiting researchers. She is a Senior

Member of IEEE, USA, and senior member of Australian Computer Society, and her research interests are in the

area of multimodal systems, computer vision, pattern recognition and image processing. She has published

extensively with more than 120 fully refereed publications in several invited book chapters, edited books, high

quality conference and journals, and she is in the editorial boards, technical review committees and regular

reviewer for several IEEE, Elsevier and IET journals in Computer Vision, Pattern Recognition and Image Processing.

Prof. Jun Shen

University of Wollongong, Australia

SPEAKERS

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Dr. Jun Shen was awarded PhD in 2001 at Southeast University, China. He held positions at Swinburne University

of Technology in Melbourne and University of South Australia in Adelaide before 2006. He is an Associate

Professor in School of Computing and Information Technology at University of Wollongong in Wollongong, NSW

of Australia. He is a Senior Member of three institutions: IEEE, ACM and ACS. He has published more than 120

papers in prestigious journals (including IEEE Transactions) and conferences (for example, IEEE Big Data) in CS/IT

areas, in particular on computational intelligence topics. His expertise includes Web services, Cloud computing

and learning technologies including MOOC. He has been Editor, PC Chair, Guest Editor, PC Member for numerous

journals and conferences published by IEEE, ACM, Elsevier and Springer. A/Prof Shen is also a current member of

ACM/AIS Task Force on Curriculum MSIS 2016.

Prof. Wernhuar Tarng

National Tsing Hua University, Taiwan

Wernhuar Tarng is currently a professor at the Institute of Learning Science and Technology, National Tsing Hua

University, Hsinchu, Taiwan. He was the director of Computing and Networking Center, National Hsinchu

University of Education, Taiwan from 1993 to 2004 and the chairman of the Graduate Institute of Computer

Science from 2008 to 2012. From 1980, Prof. Tarng conducted his undergraduate study at National Chiao Tung

University, Hsinchu, Taiwan and he was graduated from the Department of Control Engineering in 1984. He

received his M.S. degree (1987) and Ph.D. degree (1992) from the Department of Electrical and Computer

Engineering, State University of New York at Buffalo, USA. Prof. Tarng has received more than 20 grant projects

funded by Ministry of Science and Technology (MOST), Taiwan and published over 100 research papers in the

field of computer science, engineering, networking, and learning technologies. Prof. Tarng was a visiting professor

of Distant and Online Learning Center, Oxford University, UK in 2002 and a visiting scholar at Hear and Say Centre,

Brisbane, Australia from 2014 to 2015. His current research interests include: e-Learning technologies, virtual

reality, augmented reality, game-based learning, image processing, pattern recognition, computer architecture,

and computer networking.

Prof. Eric Jiang

University of San Diego, USA

SPEAKERS

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Eric Jiang is currently a professor of computer science in the school of engineering at University of San Diego, USA.

He served as head of mathematics and computer science of USD from 2014 to 2016. His research interests

include parallel and distributed computing, information retrieval, data analytics and machine learning. Professor

Jiang has published research papers in edited books and journals. He has also given presentations at international

conferences, workshops and invited seminars. Since 2010, he has been serving on the editorial board of

International Journal of Intelligent Data Analysis.

ABSTRACT

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Opening & Keynote Speech Session <January 8, 2018, Monday>_Afternoon

Time: 13:30-15:00 Place : State Room

※Please kindly participate in the whole course of the conference to make sure each session stays on time and keep the agenda runs smoothly.

13:30-13:40

Opening Remarks

Prof. Ghassan Beydoun

University of Technology Sydney, Australia

Keynote

Speech I

13:40-14:20

What can a reviewer do on your academic work?

Prof. William Guo Central Queensland University, Australia

Abstract: In anyone’s academic life, you will definitely serve as the two roles in research

domain, either as an author who receives comments from reviewers on your work, or as a

reviewer who provides comments on other’s work in the same discipline. Although it is

debatable on what is meant to be a good, a fair, or a bad reviewer, this presentation shares

personal experiences in this important peer reviewing process as either an author or a

reviewer. This including examples from magnificent comments from good reviewers who

helped significantly improved the quality of the work, to insane comments from pretended

experts who made all nonsenses on the work.

Plenary

Speech I

14:20-15:00

Applications of Virtual Reality and Gamification in Learning Nanotechnology

Prof. Wernhuar Tarng

National Tsing Hua University, Taiwan

Abstract: Nanotechnology is one of the most advanced technologies in 21st century, and its

applicaitons promote the development of related industries and the global economy. To

increase the national competitiveness, Ministry of Science and Technology (MOST), Taiwan

initiated "National Science and Technology Program for Nanoscience and Nanotechnology"

in 2002. The goal is to establish an effective mechanism for training personnel with special

skills in nanotechnology as well as promoting the development of nanotechnology industry.

Ministry of Education started "Nanotechnology Human Resource Development Program" in

2003 wiht the objective of training talented personnel in all categories to achieve the

popular science education and enhance the technological literacy of the entire people. With

the efforts in recent years, schools at all levels have a variety of teaching materials in

nanotechnology as well as the realted cirriculums. Because nannostructures cannot be seen

with naked eyes or by using general microscopes, it is not an easy task for students to

observe microscopic phenomena in natural environments to understand their principles. In

ABSTRACT

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recent years, many high-tech instruments have been developped for investigating the

nanostructures of materials. However, they are very expensive and not easy to operate such

that most schools cannot provide students with this kind of equipments for teaching

purposes. Based on the research results of advanced nanotechnology and basic concepts of

new scientific knowledge, this study combines the virtual reality technology and the

game-based learning theory to develop course modules for applications in learning

nanotechnology by concretizing and simplifying the abstract and complex knowledge and

making them more interesting. Users can enter the microscopic world to observe nanoscale

phenomena with the apps on mobile devices to enhance their learning motivation and

learning effectiveness through motion-sensing operation and 3D interaction. Therefore, they

are suitable assistant tools for nanotechnology curriculums in elementary and secondary

schools. This study uses innovative learning technologies to cultivate students' scientific

spirits and attitudes as well as their explorative and problem-solving abilities. They can

practice repeatedly anytime and anywhere in learning nanotechnology to understand its

concepts through 3D immersive interaction, and thus very helpful for enhancing the related

knowledge and scientific literacy.

Coffee Break < 15:00-15:30>

Session I - Modeling method and optimization <January 8, 2018, Monday>_Afternoon

Time: 15:30-18:00

Room: State Room

Chair: Prof. Isamu Shioya,

Hosei University, Japan

※Please kindly participate in the whole course of the conference to make sure each session stays on time and keep the agenda runs smoothly.

SY025

15:30-15:45

Effect of Toe Length on Biped Walking Behavior

Van-Tinh. Nguyen and Hiroshi. Hasegawa

Shibaura Institute of Technology, Japan

Abstract: The paper presents the effect of the toe length on the walking behavior of the

humanoid robot. This research is compatible to the certain robot named the KHR-3HV

humanoid robot, belonging to the Kondo Kagaku company. This paper shows that the toe

length sensitively results in the change of the walking distance, side distance and gait pattern

as well. The robot locomotion is considered by varying the length of the toe through

dynamic emulation on the software named Adams (MSC company, USA). The results are

compared in three responses as walking distance, side distance and angle of rotation to find

out the best length of the toe for the robot. The control data generated by a gait function as

a trigonometric function can be used as reference data in control process.

ABSTRACT

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AC023

15:45-16:00

A General Pattern of Town Streets on Map Spaces

Takahiro Suzuki and Isamu Shioya

Hosei University, Japan

Abstract: This paper presents a town street model which is a natural model to describe

general borders of residential sections/blocks in town streets, and discusses the features of

the model. This paper takes the typical residential blocks in Tokyo, presents the features of

the blocks, and reproduces future general block borders which are taking into the updates in

temporal borders based on Schelling model. We employ two features in this paper: one is

the lengths of borders in sections/blocks, and the other is the angles between two borders in

sections/blocks, where the boarders are represented by the piecewise linear. Then, we show

that we can find the human features in the general town street patterns based on a

boundary effect and a fluctuation.

SY2006

16:00-16:15

Workflow for Developing High-Resolution 3D City Models in Korea

JungHee Jo, Insung Jang

Electronics and Telecommunications Research Institute, Korea

Abstract: Recent advanced 3D technologies have increased availability of 3D geospatial data.

With this trend, new opportunities for creating geospatial-based realistic 3D digital contents

are emerging. Among the various options, 3D city models are in particular demand from

various domains. Many developed countries have transitioned from 2D to 3D city models

including Korea. 3D city models using high-resolution geospatial information can be

constructed simulating the real world by incorporating into them virtual reality or

augmented reality. In this paper, we seek to understand the methodologies currently used to

create 3D city models and present our planned research directions based on current trends.

In addition, we briefly present our current implementation of Web 3D service (W3DS)

according to the Open Geospatial Consortium (OGC) standards, as part of services essential

to develop high-resolution 3D city models.

SY055

16:15-16:30

Formal Modeling and Verification of Blockchain System

Zhangbo DUAN, Hongliang MAO, Zhidong CHEN, Xiaomin BAI, Kai HU, Jean-Pierre Talpin

Beihang University, China

Abstract: As a decentralized and distributed secure storage technology, the notion of

blockchain is now widely used for electronic trading in finance, for issuing digital certificates,

for copyrights management, and for many other security-critical applications. With

applications in so many domains with high-assurance requirements, the formalization and

verification of safety and security properties of blockchain becomes essential, and the aim of

the present paper. We present the model-based formalization, simulation and verification of

a blockchain protocol by using the SDL formalism of Telelogic Tau. We consider the

hierarchical and modular SDL model of the blockchain protocol and exercise a methodology

to formally simulate and verify it. This way, we show how to effectively increase the security

ABSTRACT

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and safety of blockchain in order to meet high assurance requirements demanded by its

application domains. Our work also provides effective support for assessing different

network consensus algorithms, which are key components in blockchain protocols, as well as

on the topology of blockchain networks. In conclusion, our approach contributes to setting

up a verification methodology for future blockchain standards in digital trading.

SY057

16:30-16:45

An Intelligent Model Validation Method Based on ECOC SVM

Yuchen Zhou, Ke Fang, Ping Ma, Ming Yang

Harbin Institute of Technology, China

Abstract: This paper develops an intelligent model validation method based on error

correcting output coding support vector machine (ECOC SVM). The similarity analysis

between simulation time series from computerized model and observed time series from

real-world system is formulated as a multi-class classification problem. The ECOC framework,

built on the basis of the error correcting principles of communication theory, decomposes

the multi-class classification task as multiple binary classification problems. The SVM is used

as the base classifier and a set of similarity measure methods is applied to extract the input

features. Compared to conventional methods, the proposed validation method based on

ECOC SVM incorporates multiple similarity measures to a comprehensive similarity measure

and can learn to predict the credibility level from training samples. The application result

reveals that the classification accuracy achieved 82%, which means the proposed method is

promising for the similarity

SY024

16:45-17:00

Sensitivity Analysis of a Causality-Informed Genetic Programming Ensemble for Inferring

Dynamical Systems

Hassan Abdelbari and Kamran Shafi

University of New South Wales, Australia

Abstract: Dynamical system is a mathematical approach to model the non-linear dynamics of

complex systems over space and time. A causality-informed genetic programming (GP)

ensemble methodology has been proposed recently by the authors to automatically infer

dynamical systems from system observations. The method adopts a variable decomposition

approach relies on expert defined causal models. However, in practice these models are

bound to have inconsistencies due to human involvement. Hence, in this paper we evaluate

the sensitivity of the ensemble method to the accuracy of input causal models that are used

as ground truth in the formation of the ensemble. This is done by varying the accuracy of

known causal models through introducing deliberate noise in models' causal relationships.

Three benchmark problems are used to evaluate the performance of the proposed

methodology where the output of different ensembles is compared with a standard GP

algorithm. The empirical results show the effectiveness of the proposed methodology in

inferring closely matching target equations under different levels of noise and learning better

models than the standard GP algorithm in most cases.

SY074

17:00-17:15

Improving Efficiency of TV PCB Assembly Line Using a Discrete Event Simulation Approach –

A Case Study

ABSTRACT

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Mohamed Abdelkhak, Shady Salama and Amr Eltawil

Egypt-Japan University of Science and Technology, Egypt

Abstract: In this paper, discrete event simulation was utilized to gain more insight into the

behavior of a Television Printed Circuit Board (TV PCB) assembly line in one of the leading

companies in the Middle East and Africa. The simulation output shows an imbalance in

workload between workstations that hinder any opportunity for improvement. Therefore,

many scenarios were proposed for rearranging the resources for the sake of eliminating

bottlenecks, and increasing resources utilization by transferring technicians from idle to busy

workstations. The proposed configurations have proven their superiority in significantly

increasing the throughput and improving workload balance throughout the line. Finally, a

cost analysis was carried out to assess the return on investment of each scenario separately

in order to elaborate the credibility of these proposals.

SY023

17:15-17:30

Study on Occlusion-induced Mechanical Force Distribution in Dental Pulp Using 3-D

Modeling Based on Finite Element Analysis

Anon Phanijjiva, Chalida Nakalekha Limjeerajarus, Nuttapol Limjeerajarus

Thai-Nichi Institute of Technology, Thailand

Abstract: The dental pulp plays an important role in maintaining the functional status of the

tooth. Proper masticatory force helped maintaining the dental pulp vitality. However, the

force distributed into the dental pulp could not be directly measured. Currently available

simulation models were single unit and/or unrealistic in shape and dimension. The purpose

of this study was to develop a novel real geometry of whole teeth 3D model based on the CT

scan system and conducted static structural analyses using the finite element analysis (FEA).

The developed model of the mandibular first molar consisted of multicomponent of enamel,

dentin and dental pulp. The masticatory loading condition for simulation was performed in

three conditions at the average biting force of 54.3 MPa. The results showed that the

average occlusal pressure did not cause permanent deformation of the tooth components as

the max Von Mises stress did not exceed its yield strength. Simulation results revealed that

the average normal stresses at the peaks of the dental pulp was only 0.003 MPa, which was

less than 1% of that exerted on the enamel.

SY033

17:30-17:45

Optimal Number of Quay Cranes in Container Terminals with Twin-40-Feet Quay Cranes

Yu Jingjing, Tang Guolei, Li Da

Dalian University of Technology, China

Abstract: To optimize the number of quay cranes in container terminals with twin-40-feet

and common quay cranes, this paper first proposed an optimization model to minimize the

total costs for container terminal operation. Then a queuing model for different berth

throughout capacity is employed considering the characteristic of twin-40-feet quay crane

operation and the random arrival of ships. And a quasi-birth-and death theory is introduced

to obtain the values of system performance indicators. Finally, the proposed optimization

ABSTRACT

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model is applied in a container terminal, and the results prove the effectiveness and

feasibility of this optimization model, which can provide a good reference for optimizing

quay cranes planning.

SY085-a

17:45-18:00

Numerical study on evaluation of effect of liquid density on the dam break flow containing

particle

Min Il Kim and Hyun Sik Yoon

Pusan National University, Republic of Korea

Abstract: The present study investigated the dam break flow containing the particles. The

purpose of this study to investigate the effect of the liquid density on the behavior of the

particles and the free-surface. A wide range of the liquid density in 1000≤ρ_l≤ 2400 is

considered. To simulate the three-phase flow, the fluid flow is solved by Computational Fluid

Dynamics(CFD) and the particle motion is described by Discrete Element Method(DEM). The

present numerical method was validated by comparing the previous results obtained by the

nemerical and experimental methods to investigate the similar relavant problem to the

present study. Particles and free surfaces are governed by time and these flows are classified

into three-regime. At the initial stage of the liquid collapse, the overlapping regime governs

the front head positions of the liquid and the particles, resulting in that the front head

positions of the liquid and the particles are almost identical. The divergent regime contains

two patterns. One is that the liquid front head is faster than that of the particle in the small

density region. Another pattern is opposite to first one.

ABSTRACT

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Keynote & Plenary Speech Session < January 9, 2018, Tuesday>_Morning

Time: 09:00-12:00 Place: State Room

※Please kindly participate in the whole course of the conference to make sure each session stays on time and keep the agenda runs smoothly.

Keynote

Speech II

9:00-9:40

Using Agent Based Analysis to Manage Complexity in Disaster Management Planning

Prof. Ghassan Beydoun

University of Technology Sydney, Australia

Abstract: Over the past eight years, we have undertaken research to enable the unification of

DM knowledge across various disaster types and jurdisctions. In this talk, I will describe our

approach which enables partitioning a DM problem into sub-problems. To partition the

problem, an agent based modelling process is applied in combination with a DM metamodel.

Decision makers can then develop a variety of domain solutions models based on mixing and

matching solutions for sub-problems indentified using the metamodel. In developed

countries, for recurring disasters (e.g. floods), there are dedicated document repositories of

Disaster Management Plans (DMP) that can be accessed as needs arise. I will describe an

agent-based knowledge analysis method to convert DMPs into a collection of knowledge

units that can be stored into a unified repository based on the unifiying metamodel. The

repository of DM actions then enables the mixing and matching knowledge between

different plans. We use the flood management plans used by SES (State Emergency Service),

an authoritative DM agency in NSW (New State Wales) State of Australia to illustrate and give

a preliminary validation of the approach. It is illustrated using DMPs along the flood prone

Murrumbidgee River in central NSW. I will also conclude by examining the opportunities to

generalise the approach to various knowledge integration and sharing in complex domains.

Keynote

Speech III

09:40-10:20

Towards A Global Collective Intelligence - Leveraging Advances in AI, Big Data and

Multimodal Science

Prof. Girija Chetty

University of Canberra, Australia

Abstract: We are currently living in a complex world, with increasing concerns about future

of humanity due to several threats of environmental problems, resource shortage, ethnic

conflicts, terrorism, natural disasters and many other uncertainties. To address these

potentially disastrous consequences , humans and machines need to work collectively at the

global level to change our ways of interacting with one another and with the nature and the

other living species around us. Technology can come to the rescus, and by using advances in

cutting edge information and communication technologies, such as AI, Big Data, Machine

Learning and Information Fusion, it is possible to develop computational collective

intelligence framework for an improved global collective intelligence and better strategies for

ABSTRACT

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Coffee Break & Group Photo <10:20-10:50>

solving the complex problems, the humanity is facing.

Recently, in last few years, we have witnessed some progress in developing collective

intelligence systems as a response to the potential global threats, particularly in fighting

disease, terrorism and natural calamities and disasters. But the scale of these isolated efforts,

do not quite commensurate with large complex problems we face as humanity. What is

needed is an integrated approach, at a global level, by exploiting the benefits of

advancements in information and communication technologies and systems. However, this is

easier said than done. Due to the complex nature of real world phenomena associated with

above mentioned threats, it is often difficult to extract complete knowledge about the

physical process of interest, from one singe modality or information channel.

This is due to multiple layers of complex information and knowledge hidden and embedded

within this natural phenomena, A detailed understanding and characterization of the such

processes is needed, with input from different types of human as well as machine based

sensors, systems and computational intelligence frameworks, providing high quality, efficient

and timely support to humans in dealing with these challenges The concept of

'multi-modality' can often be leveraged in in this context, which in general refers to

information acquisition about the process or phenomena, from multiple information sources

or channels By utilizing multiple different modalities to inform about the same process or

phenomena, it is possible to gain more intelligence, and more degrees of freedom, with

better solutions to complex and challenging problems. However, this has a downside, with

massive data deluge with important information getting buried within the big data stores,

and difficulties in making sense out of it.

The two key questions that need to be addressed in these situations are: “Is it possible to

exploit the complementary, competitive and collective information available from multiple

modalities and sources, and if yes, " how do exploit this rich information synergistically", so

as to solve the complex and difficult problems we face as humanity.

In this talk, a novel computational collective intelligence framework being developed, based

on integration of multisensory fusion, AI and Big Data Science technologies will be presented.

The experimental validation of the proposed algorithmic framework and its implementation

as an open source technology platform, for several publicly available benchmark datasets,

that represent several real world problem scenarios, has resulted in promising outcomes,

leading toward the vision of achieving global collective intelligence, and improved ability to

solve complex challenges we face as humanity.

ABSTRACT

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Plenary

Speech II

10:50-11:30

MLaaS(Micro Learning as a Service): taking advantage of fragmented time for

fragmented knowledge

Prof. Jun Shen

University of Wollongong, Australia

Abstract: Open learning is a rising trend in the educational sector and it attracts millions

of learners to be engaged to enjoy massive latest and free open education resources

(OERs). Through the use of mobile devices, open learning is often carried out in a micro

learning mode, where each unit of learning activity is commonly shorter than 15

minutes. Learners are often at a loss in the process of choosing OER leading to their long

term objectives and short term demands. MLaaS is a smart system to deliver

personalized OER with micro learning to satisfy their real-time needs, while its

decision-making process is scarcely supported due to the lack of historical data. Inspired

by this, MLaaS embeds a new solution to tackle the cold start problem, by opening up a

brand new profile for each learner and delivering them the first resources in their fresh

start learning journey. In this work, we also propose an ontology-based mechanism for

learning prediction and recommendation.

Invited

Speech

11:30-12:00

Integrating Labeled and Unlabeled Data for Classification

Prof. Eric Jiang

University of San Diego, USA

Abstract: Automatic classification is a process of assigning data objects into one or more

predefined categories or classes, based on their contents. It is typically carried out by

applying machine learning algorithms to build models from pre-labeled training samples

and then by deploying the models to classify previously unseen data. In this talk, we

discuss a classification framework for incorporating a clustering based EM algorithm into

machine learning paradigms such as artificial neural networks, which can learn for

classification effectively from both labeled and unlabeled data. The framework involves

a procedure of modulating the influence of unlabeled data in model parameter

estimation in order to adequately balance predictive values between both types of data

and to improve classification performance. Experimental results with several textual

data corpora show that the proper integration of unlabeled data in learning developed

for the framework can reduce classification errors.

Lunch <12:00-13:30> Location: Restaurant Note: lunch coupon is needed for entering the restaurant.

ABSTRACT

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Session II- System modeling and simulation < January 9, 2018, Tuesday>_Afternoon

Time: 13:30-16:00

Room: Enmore

Chair: Prof. Yukio Hiranaka

Yamagata University, Japan

※Please kindly participate in the whole course of the conference to make sure each

session stays on time and keep the agenda runs smoothly.

SY034

13:30-13:45

Standard Values of Service Level of Intersection for Collection and Distribution Roads of

Container Terminals

Li Ningning, Yu Jingjing, Chu Na

Dalian University of Technology, China

Abstract: In the container terminal, the proportion of heavy trucks at the road

intersections for container terminal is large, which is significantly different from the

urban road traffic flow mainly dominated by sedan cars. Therefore, we established a

microscopic traffic simulation model to analyze the dynamic change of service traffic

volume under the different service levels of the large vehicles, and the grading standard

on service level of evacuation road intersections for container terminals could also be

determined. The results showed that the average delay and the queue length could be

effected obviously by the rate of large vehicles when the loading degree was within

0.7~0.9. And the case study demonstrated that compared with the recommended

values of evaluation index for road intersection service level from Code for Planning

Intersections on Urban Roads, the proposed evaluation values would be more

reasonable for container terminals.

SY030

13:45-14:00

Simulation model for analysis and management of the no-show in outpatient clinic

Alessandro Pepino, Ersilia Vallefuoco, Patrizia Cuccaro and Gaetano D'Onofrio

University of Naples Federico II, Italy

Abstract: In outpatient management, the lead-time is a critical issue due to its

important negative effect on healthcare quality perception. In particular, it generates

the phenomenon of “no-show”: when patients do not attend their scheduled

appointments. In this study, we analyze the process of outpatient booking and its critical

issues; in particular, we propose a simulation model to evaluate some different

approaches. From our results, the lists cleaning can be considered a good tool to

manage and reduce the no-show.

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SY067

14:00-14:15

The generalized age maintenance policies with random working times

Shey-Huei Sheu, Tzu-Hsin Liu, Zhe-George Zhang

Providence University, Taiwan

Abstract: The purpose of this paper is to investigate the generalized age maintenance

policies for a system with random working times. When the system fails, it is subject to

one of two types of failures with age-dependent probability: type I failure can be

removed by minimal repair and type II failure must be rectified by replacement. First,

the system is preventively replaced before type II failure at time T or at the completion

of Nth working projects, whichever occurs first. Two modified models, where the system

is preventively replaced before type II failure at time T or at the completion of Nth

working projects, whichever occurs last, and it is preventively replaced at the first

completion of the working project over time T or at the completion of Nth working

projects, whichever occurs first, are considered. By introducing costs due to repairs,

maintenance and replacement, the expected cost per unit time is derived as a criterion

of optimality and the optimal policy that minimizes that cost is discussed analytically.

SY062

14:15-14:30

Self-Adaptive Ensemble Based Differential Evolution

Shir Li Wang, Theam Foo Ng, and Farid Morsidi

Universiti Pendidikan Sultan Idris, Malaysia

Abstract: Differential evolution (DE) is among the more prominent branch of

evolutionary algorithm (EA) innovated for multiple optimization properties. It has been

improvised in various practical solutions, whether it is for benchmark testing or real

world situations. As compared with other stochastic optimization algorithms such as

nature inspired algorithms and evolutionary ones, DE possesses savvy traits in terms of

exploration and exploitation within its own domain. With its motives of locating optimal

points and minimized solution steps for objective functions, DE relied heavily on the

necessity to specify parameter settings that is catered for achieving appropriate

convergence values. The exhibited parameter value is seen directly correlated with the

quality of the solutions for the underlying optimization problem. However, selection of

appropriate parameter values occasionally necessitate for a priori experience and

problem dependent on user. In most cases, users emphasize more on solving the

optimization problem rather than solving the algorithm itself. Besides that, research

work related to parameter study in DE lacks of proper and clear guidance to users.

Therefore, there is a need to develop a DE which can adaptively determine the

appropriate parameters to solve different optimization problems with minimum

guidance from users. In this research, we take the opportunity to develop a DE model

which combines self-adaptive and ensemble mechanisms to dynamically change the

control parameters as well as mutation strategy during evolution with minimum

intervention from users. The experimental results have shown that the proposed model

is able to perform adequately well in twenty different benchmark problems without

depending on user to determine the parameters explicitly.

ABSTRACT

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SY087

14:30-14:45

Forecasting of Incoming Calls in a Commercial Bank Service Call Center

Sirithep Chanbunkaew and Wipawee Tharmmaphornphilas

Chulalongkorn University, Thailand

Abstract: In this study, we develop forecast models for incoming calls at a call center of

a commercial bank in Thailand. We found that incoming calls are non-stationary.

Normally, the number of calls is low during holiday and high during the beginning and

ending of each month. Various time series models are applied for monthly forecast and

an algorithm based on seasonal pattern is proposed for daily forecast. MAPE (Mean

Absolute Percentage Error) and RMSE (Root Mean Square Error) are used for comparing

the proposed methodology and the current model that the bank uses. The results show

that the proposed methodology is better than the current model. MAPE reduces from

9.79% to 8.12% and RMSE reduces from 960.37 to 861.88.

SY088

14:45-15:00

A Development of a Prediction Model for Ungauged Catchment in the North of Thailand

Nutthanon Sa-ngonsub, Supattra Visessri, Pisit jarumaneeroj

Chulalongkorn University, Thailand

Abstract: Flow data are essential for hydrological study, planning, and management to

prevent drought and flood in a region. In catchments where flow data are not recorded

or of poor quality, hydrological indices could be an alternative for predicting flow in

ungauged catchments. This study demonstrates the methodology for predicting flow in

ungauged catchments through the case study of 37 sub-catchments of the upper Ping

catchment in northwest Thailand from 2006-2014. The regression method was applied

to investigate the relationship between three flow indices including runoff coefficient,

base flow index, and 95th percentile of flow, and catchment properties. The prediction

interval of the regression relationship was used to condition rainfall-runoff model

parameters. The model performance was tested by NSE* and reliability. The 95th

percentile of flow was found to be the most informative index to regionalize flow

followed by RC. The BFI had least contribution to the prediction of flow with poor NSE*

and large uncertainty. The 95th percentile of flow and RC generally worked well for

small sub-catchments.

SY2001

15:00-15:15

Finite Element Modeling and Analysis of Ultrasonically-Assisted Drilling of Bone

Khurshid Alam, Mushtaq Khan, Vadim Silberschmidt

Sultan Qaboos University, Sultanate of Oman

Abstract: Drilling in bone is a common surgical procedure in orthopedics for fixation and

reconstructive surgeries. Research in this area is largely focused on investigating

alternate drilling techniques for minimal destruction to the bone tissue. This study

measured temperature and force generated during conventional drilling (CD) and

ultrasonically-assisted drilling (UAD) using Finite Element (FE) simulations.

Three-dimensional FE model of bone drilling was developed and analyzed to simulate

the dynamic processes involved in the process. Numerical simulation predicted lower

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drilling force and temperature in UAD compared to CD using controlled ultrasonic

parameters (frequency – 20kHz, amplitude = 10 micrometers). Drilling tests are

performed on fresh bovine femur using surgical drills in the presence of ultrasonic

vibrations imposed on the drill in the cutting direction. Force and temperature

generation at various depths are calculated and compared for the prescribed drilling

techniques. The results obtained from numerical simulations are compared with bone

drilling experiments.

SY037

15:15-15:30

Dynamic Modeling of Discrete Event Simulation

Rodrigo Ferro, Gabrielly A. Cordeiro, Robert E. Cooper Ordoñez

University of Campinas, Brazil

Abstract: This study shows the contribution of Discrete Event Simulation (DES) for

improvement of statics production scheduling process in the environment of dynamic

demand. Using simulation software - Tecnomatix Plant Simulation 13 ® by Siemens,

makes it possible to structure a digital factory model. It defines and validates the

operating logic of this model and enables the automatic reconfiguration of production

planning. This virtual model represents the operations of eyewear industry starting

from placing customer request till collecting final product. The primary purpose is to

automate most of the production planning process and enable automatic execution in

virtual settings, which will potentially guide the physical operation. The result is to

provoke integration between production management systems with simulation tools,

therefore increase productivity, reduce waste and improve the use of labor.

SY043

15:30-15:45

Numerical Modelling and Simulation of Ferro Casting Ductile Shear Keys for Precast

Concrete Girders

Heru Purnomo, Mulia Orientilize, Rosi Nursani, Fauzi Hardjanto

Universitas Indonesia, Indonesia

University of Tasmania, Australia

Abstract: This paper discusses the numerical modelling and simulation of Ferro casting

ductile (FCD) metal shear key, or connector, without epoxy used for joining segmental

precast concrete girders. In contrast to other types of cast iron, FCD metals exhibit

higher level of ductility. In an effort to identify an optimum shape of an FCD metal shear

key the numerical study in this paper investigates the response of four different

geometries of full scale FCD metal shear key to shearing force from the concrete

members and prestressing force acting in the centreline of the connector. Nonlinear

finite element analysis of the shear key and the adjoining concrete members are

conducted using ANSYS academic package. The appropriate constitutive relations for

the FCD metal and concrete materials are obtained from test results and published

values in the literature. The study considers two different magnitudes of prestressing

force and two different concrete compressive strengths. Numerical results indicate that

introducing a taper onto the forward ring plate of the male part of the shear key results

in a significant increase in its load-bearing capacity.

ABSTRACT

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SY073

15:45-16:00

A Virtual Collaborative Simulation-based Training System

P. K. Kwok, Bill K. P. Chan, Henry Y. K. Lau

The University of Hong Kong,

Abstract: Emergencies can occur at any location and time, so all stakeholders should get

themselves prepared for providing emergency actions and responses. Such actions are

especially important in sophisticated but vulnerable systems, e.g., mass transport

systems, hospitals and power plants. Crichton and Flin [1] showed multiple examples

that the performance of incident management teams in the initial stage of a crisis could

affect the development of the incident. Therefore, regular training should be provided

to the stakeholders, particularly the operators of the organisation, so that they can work

together to deal with the emergencies effectively. Although conducting a drill in the real

system may be the most direct way for stakeholders to practice their emergency

response abilities, performing a drill usually requires many resources and a disruption of

the real system. Therefore, this paper introduces an approach to conduct the drill in a

virtual environment. It proposes a virtual collaborative simulation-based training system

with an aim to improve the emergency management ability of the staff in sophisticated

but vulnerable systems. There are four major advantages of the proposed system: 1). It

is off-line from the real system so that there is no space or time constraint to carry out

the training. 2). It requires fewer physical resources to carry out the training, which

makes the training much cost-effective. 3.) The managers, as well as the operators, can

have a better understanding of the real operations by looking at the 3D simulation

model. 4.) It provides flexibility to train the operators in various hypothetical scenarios,

including some rarely occurred ones. To better illustrate the ideas, this paper takes the

mass transport system as an example. However, it should be stressed that the proposed

system can be applied to other areas like exhibition centres, emergency rooms of the

hospitals and nuclear plants.

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Session III - Software development and system

simulation < January 9, 2018, Tuesday>_Afternoon

Time: 13:30-16:00

Room: Belvoir

Chair: Prof. Girija Chetty,

University of Canberra, Australia

※Please kindly participate in the whole course of the conference to make sure each session stays on time and keep the agenda runs smoothly.

AC034

13:30-13:45

Machine Learning Architectures for the Estimation of Predicted Occupancy Grids in Road

Traffic

Parthasarathy Nadarajan, Michael Botsch, Sebastian Sardina

Technische Hochschule Ingolstadt, Germany

Abstract: This paper introduces a novel machine learning architecture for an efficient

estimation of the probabilistic space-time representation of complex traffic scenarios. A

detailed representation of the future traffic scenario is of significant importance for

autonomous driving and for all active safety systems. In order to predict the future

space-time representation of the traffic scenario, first the type of traffic scenario is

identified and then the machine learning algorithm maps the current state of the scenario

to possible future states. The input to the machine learning algorithms is the current state

representation of a traffic scenario, termed as the Augmented Occupancy Grid (AOG). The

output is the probabilistic space-time representation which includes uncertainties regarding

the behaviour of the traffic participants and is termed as the Predicted Occupancy Grid

(POG). The novel architecture consists of two Stacked Denoising Autoencoders (SDAs) and a

set of Random Forests. It is then compared with the other two existing architectures that

comprise of SDAs and DeconvNet. The architectures are validated with the help of

simulations and the comparisons are made both in terms of accuracy and computational

time. Also, a brief overview on the applications of POGs in the field of active safety is

presented.

SY003

13:45-14:00

Process Automation in Intelligent Transportation Systems (ITS)

Koorosh Gharehbaghi and Kenneth Farnes

RMIT University, Australia

Abstract: Collectively, while process simulation is an intricate element within the Intelligent

Transport Systems (ITS); a range of modeling techniques and subsequent transition

operations are also complicated components of such system. While, the ITS incorporates a

ABSTRACT

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set of process automations such as, systematic prototypes and simulation, it also integrates

computational modeling and thus efficient operation transitions. Such process as

automation, modeling, and operation transitions are at the core of a fastidious ITS.

Accordingly, these system elements need to be holistically integrated as well as

amalgamated through effective computationally based methods. Fittingly, the main

objective of this paper is to examine the utilization of process automation and

computational based methods as the basis of the ITS integration perspectives. In doing so,

Sydney Metro will be included as a case study to further elucidate such integration

processes.

AC032

14:00-14:15

Deployment and Evaluation of a Continues Integration Process in Agile Development

Hsin-Ke Lu, Peng-Chun Lin, Pin-Chia Huang, An Yuan

Chinese Culture University, Taiwan

Abstract: In addition to the strong market demands, software development projects are

facing constantly change of requirements from dynamic business context. Striving to meet

the project deadline, in budget and maintain quality of systems brings up the importance of

development automation. The benefits of continuous integration of agile development

have been reported in the academic literatures, however, the consideration on determining

the necessary procedures during the implementation and how to quantify the performance

and effectiveness on the implementation is not widely discussed. An automation continues

integration process was developed in this study. For evaluating on the performance and

acceptance of the process implemented, a new evaluation framework was constructed as

measurement tool. The analysis and discussions of research result will serve as a reference

for the rear researches and for the system development practice on transitioning to agile

development.

SY007

14:15-14:30

Computational Fluid Dynamics Application for Analysis of Centrifugal Compressor Stage

Stator Part

Lubov Marenina, Yuri Galerkin, Kristina Soldatova

Peter the Great, St. Petersburg Polytechnic University, Russia

Abstract: The known information of satisfactory correlation of calculated and measured

stator part performances is a foundation for the numerical investigation. Stator parts «Vane

(vaneless) diffuser + crossover + return channel» of stages with different specific speed

were designed in accordance with standard recommendations and investigated by CFD

calculations. Flow structure demonstrated advantages and disadvantages of design. Flow

separation in crossovers was eliminated by its shape modification for stages with diffusers

relative width of diffusers. The stage with medium flow rate and low loading factor was

designed with traditional and modified crossovers. Calculated efficiency performance

becomes better. The information obtained is useful for design method better calibration.

SY056

14:30-14:45

An Architecture for SaaS-Oriented VV&A

Ke Fang, Wei-Tek Tsai, Ming Yang

Harbin Institute of Technology, China

Abstract: VV&A (Verification, Validation & Accreditation) involves many types of jobs to

ABSTRACT

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achieve the credibility of a simulation system, which needs software tools to speed the

process. SaaS (Software as a Service) can provide workflow-driven, programmable and

extendable services in cloud to satisfy VV&A requirements. Based on this point, after

proposing the services which are required in VV&A, the SOVA (Saas-Oriented VV&A

Architecture) scheme and architecture are proposed, and a case study of PA-23 piloting

simulation system is given, which describes a walkthrough of SOVA application.

AC029

14:45-15:00

Expert System for Further Training Management in SMEs

Marcel Randermann, Roland Jochem, Stephan Siek, Thanh Thuy Nguyen

Technische Universität Berlin, Germany

Abstract: The purpose of this paper is to define and describe an expert system for

decision-support in further training management in small and medium-sized enterprises

(SME). This will be achieved by evaluating the interrelation of the methodological-didactic

characteristics of further training activities on the one hand and, on the other hand, linking

them with individual learning preferences in order to recommend high-quality and

individual measures when selecting continuing vocational training. The approach takes into

account both the teaching-learning-arrangement and the learning style of a learner for

algorithm-based decision support. For this purpose inherent characteristics of training

activities were determined and interrelations identified by qualitative content analysis of

educational literature and expert interviews among training managers of SMEs.

AC038

15:00-15:15

Machine Learning Based Prediction of Crash Severity Distributions for Mitigation Strategies

Marcus Müller, Michael Botsch, Dennis Böhmländer, Wolfgang Utschick

Technische Hochschule Ingolstadt, Germany

Abstract: In road traffic, critical situations pass by as quickly as they appear. Within the

blink of an eye, one has to come to a decision, which can make the difference between a

low severity, high severity or fatal crash. Because time is important, a machine learning

driven Crash Severity Predictor (CSP) is presented which provides the estimated crash

severity distribution of an imminent crash in less than 0.2 ms. This is times faster

compared to predicting the same distribution through computationally expensive

numerical simulations. With the proposed method, even very complex crash data, like the

results of Finite Element Method (FEM) simulations, can be made available ahead of a

collision. Knowledge, which can be used to prepare occupants and vehicle to an imminent

crash, activate and adjust safety measures like airbags or belt tensioners before of a

collision or let self-driving vehicles go for the maneuver with the lowest crash severity.

Using a real-world crash test it is shown that significant safety potential is left unused if

instead of the CSP-proposed driving maneuver, no or the wrong actions are taken.

SY021

15:15-15:30

DEVELOPMENT OF A FLIGHT DYNAMICS MODEL FOR FIXED WING AIRCRAFT

Nguyen Tien Dat, Tran Ngoc Son, Duong Anh Tra

ABSTRACT

30 / 51

Viettel Institute of Modeling & Simulation, Vietnam

Abstract: Flight simulators play an important role in pilot training and education. They are

used widely in aerospace industry and have diverse functionalities. However, there is no

university that has a process of teaching and learning to build a full flight simulation. Flight

simulation is a combination of mathematical, computer science, control theory, and

mechatronics.

The present study provides the basis of methodology that is used to build a flight dynamics

model with entire flight envelope. The model consists of the interaction between the

landing gear, wheels and ground. Some results of aircraft’s response to some basic actuator

deflections will be discussed and analyzed.

SY059

15:30-15:45

An Improved Three-stage-DEA for Benchmarking International Tourist Hotels with

Environmental Effect

LongFei Chen

NanFang College of Sun Yat-Sen University, China

Abstract: An improved three-stage slack-based DEA method is proposed to overcome

independently identically distributed (i.i.d.) restriction on sample size in popular

three-stage DEA proposed by Fried. Later, it is applied to find relative efficiencies for

international hotels. By treating environmental variable (near airport) as a

non-discretionary input, each hotel can consider a non-discretionary input as exogenous

variable to adjust input by filtering out environmental effect and statistical noise. Improved

relative efficiencies can be resulted from referred hotels. The results show the

environmental effect is significant.

SY2007

15:45-16:00

A Smart IoT-Based Irrigation System with Automated Plant Recognition using Deep Learning

Jessica Kwok, Yu Sun

California State Polytechnic University, Canada

Abstract: Machine Learning allows systems to learn and improve automatically from

experiences without hand-coding. Thus, in recent years, many technology companies have

been developing such application if Artificial Intelligence, from face recognition by

Facebook, to the AlphaGo program by Google. The irrigation systems in the market

nowadays mostly allow users to set them to a certain amount of water and at specific time

intervals. However, there are usually more than one type of plants in a garden, and each

species requires different amount of water. In order to resolve this issue, in this paper, we

have developed an irrigation system, with the use of deep learning, that is able to adjust

the amounts of water foe each type pf plant through plants recognition. There are two

main parts of the solution, the software and the hardware. The prior is connected with

cameras to undergo plant recognition, and utilizes database to find the suitable amount of

water; the latter controls the amount of water that is able to flow out.

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Poster Session < January 9, 2018, Tuesday>_Afternoon

Time: 13:30-16:00 Room: Seymour

AC045

Using a Separable Convolutional Neural Network for Large-Scale Transportation Network

Speed Prediction

Arnold Loaiza Fabian, José Herrera Quispe, and Luis Mantilla Santa Cruz

Universidad Nacional de San Agustin, Peru

Abstract: This paper proposes the reduction of the convergence time on a Convolutional

Neural Network (CNN) method for traffic speed prediction, without reducing the

performance of speed prediction method. The proposed method contains two procedures:

The first one is to convert the traffic network data to images; in this case the speed variable

will be transformed. The second step of the procedure presents a modification of the CNN

method for speed prediction in which a separable convolution is used to reduce the number

of parameters. This separable convolution helps to reducing the convergence time of speed

predictions for large-scale transportation network. The proposal is evaluated with real data

from the Caltrans Performance Measurement Syste (PeMS), obtained through sensors. The

results show that Separable Convolutional Neural Network (SCNN) reduces convergence time

of CNN method whithout losing the performance of the predictions of traffic speed in a

large-scale transportation network.

AC032

Deployment and Evaluation of a Continues Integration Process in Agile Development

Hsin-Ke Lu, Peng-Chun Lin, Pin-Chia Huang, An Yuan

Chinese Culture University, Taiwan

Abstract: In addition to the strong market demands, software development projects are

facing constantly change of requirements from dynamic business context. Striving to meet

the project deadline, in budget and maintain quality of systems brings up the importance of

development automation. The benefits of continuous integration of agile development have

been reported in the academic literatures, however, the consideration on determining the

necessary procedures during the implementation and how to quantify the performance and

effectiveness on the implementation is not widely discussed. An automation continues

integration process was developed in this study. For evaluating on the performance and

acceptance of the process implemented, a new evaluation framework was constructed as

measurement tool. The analysis and discussions of research result will serve as a reference

for the rear researches and for the system development practice on transitioning to agile

development.

SY040

Proposing novel measures to alleviate the risks of migration to open source software

Ehsan Noroozi, Habib Seifzadeh

Islamic Azad University, Iran

Abstract: Nowadays, companies and organizations pay more attention to the use of open

source software. In this regard, organizations can benefit from the advantages of this kind of

software, such as less cost and more flexibility. However, migration to open source

ABSTRACT

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migration process as much as possible. It also provides a new categorization of the risks by

which each risk is classified based on its type (organizational, technical, and environmental),

and its time of occurrence (before, during, and after migration). Moreover, this paper

proposes a number of conceivable measures to mitigate each risk; some of them are

proposed for the first time in this area of research. The results of this study can help

organizations’ decision makers to make better decisions in the open source migration process.

SY049

A Sensor Node Lossless Compression Algorithm based on Linear Fitting Residuals Coding

REN Xuejun, REN Zhongyuan

Engineering University of PAP, China

Northwestern University of China, China

Abstract: According to the theory of linear regression model, this paper designed a sensor

data lossless compression algorithm. The algorithm calculates the sensor data’s fitting values

and fitting residuals, which are input to a content-based entropy coder to perform

compression. The algorithm achieves lossless transform by rounding operation, and realizes

positive sequence decoding by prediction fitting. The efficient entropy coding is realized by

calculating the mean bit number of input data. Compared with the typical lossless

compression algorithms, the proposed algorithm indicated better compression ratios with a

small computational overhead.

SY069

Linearized Longitudinal Dynamic Model for Tractor Cruise Control System

Zhixiang Liu, Zhuo Wang, Xiaoping Bai and Lei Gao

Institute of Automation, the Chinese Academy of Sciences (CAS), China

Abstract: It is necessary to establish the longitudinal dynamic model of the tractor for the

cruise control system to design a fixed speed control algorithm according to the

characteristics of the model and the external disturbance characteristics. Aiming at the

complexity of the longitudinal power transmission system of the tractor, this paper uses the

modular mechanism modeling and the experimental data modeling to establish the

longitudinal dynamic model of the tractor. Due to the nonlinearity of the longitudinal

dynamics system, the inverse model method is used to linearize the model, which is

convenient for the design of control structure and control algorithm of the standard cruise

control system. The longitudinal dynamics model is simulated on Simulink, and the model is

verified by real vehicle under driving condition. Comparing the simulation data with the

experimental data, the results show that the model can accurately reflect the longitudinal

dynamics characteristics of tractor, and can meet the requirements for the design of cruise

control system.

SY031-A

Simulation Analysis of Economic Partnership Network Formation and Economic Growth

Tomoya Sakagami, Yasuhiko Kato, Hiroki Inoue, and Hiroki Unoki

Kyoto University, Japan

Abstract: The United Kingdom has decided to withdraw from the European Union (EU) as the

result of a referendum in 2016. On the other hand, the United States also announced its

withdrawal from the Trans-Pacific Partnership (TPP) in the same year. Meanwhile lively

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discussions are being held on those reason and those pros and cons. We incorporate network

externalities into an economic growth model to analysis the formation process of an

economic partnership network among countries such as Economic Partnership Agreement

(EPA).

In this study, we consider economic partnership within three countries as a network

formation. Each country obtains profit (positive externality) depending on the network

formation, while connecting a link needs to pay network costs proportional to their economic

power, Gross Domestic Product (GDP) per capita. If each country has no incentive to change a

link, then the state of the link is called pairwise stable.

We simulate how the network formation to the steady states changes by making each

country’s decision on whether to connect or disconnect links with other countries at every

term. Each country aims to maximize per capita GDP in each period. As a result, we show that

network changes are different depending on the magnitude of the link maintenance cost.

Through the simulation analysis, we observe not only cases which the stable network in the

steady-state are "complete" or "empty", but also the case of periodic solutions which repeat

the complete and the empty networks in turn. The latter occurs when the network cost is in a

certain range.

SY051

An Indoor Airflow Simulation and Airborne Dust Concentration Analysis

Anyang Yu, Haonan Zhao, Changjiang Zhang, Yu Meng

Wenzhou-Kean University, China

Abstract: Indoor air condition is paid attention by people because of its direct relation to

human health. The Computational Fluid Dynamics (CFD) simulation is broadly used in

architectural ventilating system design. Here, the commercial simulation software Ansys is

used to predict the indoor airborne dust contribution. Based on a model of college students’

dormitory, the CFD simulated air velocity distribution and air flow duct to predict the airborne

dust distribution. Meanwhile, this study examined the dust concentration in the same room

via the dust sensor. Integrating results from both the simulation and the dust sensor, we

concluded the distribution of dust particles in the room.

This study integrates the sensor network with simulation, allowing for computing the airborne

dust distribution with a border range. In the future the system could predict a variety of

airborne particles contributing to the air pollution by applying different sensors.

SY078

Drone Simulator Development for Low Altitude Air Traffic Control

Hyo Hyun Choi and Jongjin Won

Inha Technical College, Republic of Korea

Abstract: We are developing a drone simulator for the low altitude air traffic control. Our

research is on the air traffic control scheme for the collision prevention in dense environment

that a lot of drones fly near each other. To lower the collision possibility outstandingly, we

research on the air traffic infrastructure and the collision-free route establishment method. To

verify and visualize our research findings, we are developing a simulator that drones fly

according to the path information. It can be used for the various purposes for animating the

drones’ flight because the simulator uses the independent path information that is generated

by another simulation program or analysis. This simulator is being developed by Unity and we

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Coffee Break <16:00-16:15>

named it as IUDS (Inhatc Unity Drone Simulator). This simulator can contribute to verification

and visualization of drone research. This research was supported by Basic Science Research

Program through the National Research Foundation of Korea (NRF) funded by the Ministry of

Education (NRF-2015R1D1A1A01061155).

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Session IV- Modeling and dynamic analysis of

mechanical system < January 9, 2018, Tuesday>_Afternoon

Time: 16:15-19:00

Room: Enmore

Chair: Prof. Harumi Watanabe

Tokai University, Japan

※Please kindly participate in the whole course of the conference to make sure each session stays on time and keep the agenda runs smoothly.

AC026

16:15-16:30

The mathematically describable ILD patterns

Balemir Uragun

Monash University, Australia

Abstract: These This is a mathematical modelling study in computational science that

recognized patterns used based on the biological data. The biological data were obtained

through the number of clusters and the shape of each clustered means Interaural Level

Differences (ILD) and were both analytically examined by the data classification study. Then

the result of the classification study trained by the Artificial Neural Networks to build a

master-template for a single array. Here, these typified single array patterns were

exclusively tested for several curve fitted functions and the outcome was the probability

density functions “pdf” with the linear regression parameters. This initial evaluation

confirms two Gaussian functions were both suitable models for the data sets, and then

coefficients of these functions verified for a correlation to be validated. In conclusion, a

parameterized first-order Gaussian function can be used as the mathematical model for all

ILD patterns; the energy efficiency is also discussed.

SY039-a

16:30-16:45

Towards a Testable Context-Oriented Software Framework for IoT Robot Systems

Harumi Watanabe and Nobuhiko Ogura

Tokai University, Japan

Tokyo City University, Japan

Abstract: The presentation introduces a preliminary framework based on Context-Oriented

Software for IoT robot systems. In the IoT robot system, a large number of robots connect

with each other. Accordingly, an each robot must deal with bigger and more complex

contextual information than single robot systems. Context-Oriented Programming (COP)

techniques are well-known for suitable to those systems. We have also proposed a

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software architecture (RT-COA: Real-Time Context-Oriented Architecture) based on COP.

Additionally, we have been constructing a Colored Petri-Nets simulation environment. The

feature of COP is that layers make dynamically rewrite behavior on changing contexts. Each

layer contains a whole system that consists of object-oriented classes. However, the

dynamic feature of COP makes be difficult for generating test cases. In embedded system

industry area, we think testability is one of the most significant capabilities.

To overcome this problem, we focus on individual robot features. Firstly, the number of the

sensors and actuators controlled by one robot is usually small. Secondly, the

communication messages are based on a protocol. Thus the inputs and outputs alphabets

are a limited number. If we give an adequate rule for making a pair of inputs and outputs,

we will generate a practical number of test scenarios. To realize the testable

context-oriented software framework, we expand RT-COA. The inputs and outputs of the

software of RT-COA are contextual events and contextual behavior on a layer. In RT-COA,

the contextual layer manager distinguishes a context based on contextual events. Then, the

RT-COA scheduler decides a layer (de-) activation. Thus, the inputs are communication

messages and sensor states. On the other hand, the output is motor behavior on a layer. In

the presentation, we will discuss the test scenarios generation on RT-COA from a state

machine model of a cooperative cleaner robot system.

SY061

16:45-17:00

Analysis Noise Vibration of the Gearboxes using Mathematical Models

Cao Hung Phi, Trinh Minh Hoang, Tran Thanh Tung

Vinh Long University of Technology Education, Vietnam

Abstract: The paper will review practical techniques and procedures employed to quiet

gearboxes units. The gearbox noise problem solution is focused on improvement of gear

design, on verification of its mathematical models on the radiated noise and determination

of the gears contribution to the vehicle overall noise levels and on analytical and/or

numerical computer-based tools needed to perform signal processing and diagnostics of

geared axis systems. This paper prefers solving the gear noise problem that enclosure as a

means to reduce radiated noise, which using math model to estimate effect on the sound

pressure level. All the analytical methods are based on the way to build up modal

parameter of gear box. The paper will review the progress in technique of the gear angular

vibration analysis and its effect on gear noise due to the self excited vibration. The

presentation will include some sample of model in 3D and the real one.

SY008

17:00-17:15

The Application of Mathematical Models for Industrial Centrifugal Compressor Optimal

Design

Yuri Galerkin, Kristina Soldatova and Aleksandr Drozdov

Peter the Great, St. Petersburg Polytechnic University, Russia

Abstract: The authors present the design approach aiming to reach maximum possible

efficiency of an industrial centrifugal compressor. To reach the goal the flow coefficient of

stages must lie within the range where velocity at an impeller inlet are not more than 0,7 of

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blade speed. Flow path channels must not be less than 0,05 of an impeller diameter. A

loading factor must vary between 0,4 and 0,5. Design limitations are important too. The

Universal Modeling Method of effective design and reliable calculation is shortly described.

The original two-zone model is being processed by implemented in PC programs to

optimize basic dimensions of a flow path and to calculate gas dynamic performances. Q3D

calculations are applied to optimize 2D and 3D blade cascades. CFD calculations are used as

a finishing operation. Two samples of high effective compressors developed in cooperation

with PAO SMPO (Sumy city, Ukraine) are presented. 16 MW booster compressor

demonstrated efficiency close to 88% due to proper choice of number of stages’. 32 MW

single-stage compressor design was based on most effective scheme and parameters

offered by PAO SMPO. The Industrial partner designed, manufactured and tested 1:2 scale

model. The tests have verified the project gas dynamic performances with high accuracy.

Polytropic efficiency of 90% was reached for the first time in the Authors’ design practice.

SY009

17:15-17:30

Mathematical Modelling and Analysis of an Axial Compressor Supersonic Stage Impeller

Yuri Galerkin, Kristina Soldatova and Alexey Rekstin

Peter the Great, St. Petersburg Polytechnic University, Russia

Abstract: There is an evident trend to elevate pressure ratio of a single stage of a turbo

compressors - axial compressors in particular. Q-3-D computer program based on wind

tunnel test data was applied to research possible parameters of axial stage candidates with

pressure ratio 3,0. Influence of two main design parameters on expected efficiency,

periphery blade speed and flow structure was studied. Acceptable level of efficiency and

inlet Mach number are expected at flow rate coefficient = 0.35 and flow deflection angle =

12 degrees. The calculation results have led to a stage candidate for further analysis and

improvement by field type and CFD programs.

SY045

17:30-17:45

Symbolic backward simulation of Java bytecode program

Tetsuya Inafune, Shinichi Miura, Toshihiro Taketa, Yukio Hiranaka

Yamagata University, Japan

Abstract: We present a new method, symbolic backward simulation, for detecting bugs in

Java bytecode programs. In order to find bugs comprehensively, the method determines

conditions on the input side by tracing back from the tail of the program while performing

reverse execution for each bytecode. Generally, reverse execution is difficult, especially for

instructions of two-input-one-output operations and branches. Our method solves the

problem symbolically with essentially fewer simulation cases than numerical testing and

forward symbolic analysis. We also show simulation results which detected a branch

condition error and a real number processing error.

SY011-a

17:45-18:00

Validating a Computational Fluid Dynamics Model of Vegetation Effects on Microclimates

Ted Eckmann

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University of Portland, USA

Abstract: This study applied a microscale Computational Fluid Dynamics (CFD) model to

simulate effects of vegetation on microclimates, and validated results using an extensive

field measurement campaign. This study also developed new methods for making these

field measurements. Few previous studies, if any, have validated CFD microclimate

modeling of vegetation with as many measurements as were made by this study. Results

show model simulations of plant metabolic processes and their influence on variables such

as air temperature, surface temperature, relative humidity, and carbon dioxide

concentrations were close to measured values, with a coefficient of determination for

many parameters of 0.99, and other statistical measures ranking model performance

comparable to or superior to similar studies. Applications include new methods for

validating microclimate models and for applying them to make better decisions about what

kinds of vegetation to plant where, such as for use in urban planning and sustainable

building design.

SY012-a

18:00-18:15

Desalination Performance Prediction of Low-Dimensional Material Membranes using

Empirical Molecular Dynamics

Elisa Y. M. Ang, Teng Yong Ng, K. R. Geethalakshmi, Rongming Lin, Jingjie Yeo and Zishun Liu

Nanyang Technological University of Singapore, Singapore

Abstract: With the rising challenge of water scarcity, increasing efforts are made to increase

water production rate while reducing the energy required. Low dimensional materials

membrane shows promise in providing a sustainable solution to this global water scarcity

challenge. As the physical fabrication of low dimensional materials membrane is still

technically challenging, computer modeling and simulation provides a well-needed

alternative to study and optimize its performance. In this presentation, we will discuss how

molecular dynamics (MD) simulation is used as a tool to understand, analyze and optimize

low dimensional materials membrane for desalination. We will share how the findings from

MD simulations helped to shape our two new membrane designs: the two-dimensional slit

membrane and the one-dimensional transverse flow nanotube membrane. In addition, we

will talk about how MD allows the prediction of the performance of low dimensional

materials membrane in different operating scenarios, which could prove difficult to achieve

in physical experiments. All in all, MD can be an invaluable and cost-effective tool for the

detailed investigation and design of emerging technologies, as demonstrated in this case in

the context of low dimensional materials membrane.

SY081

18:15-18:30

A comparison between discrete analysis and a multiphase approach for predicting heat

conduction in packed beds

Edoardo Copertaro, Alvaro Antonio Estupinan Donoso, Bernhard Peters

University of Luxembourg, Luxembourg

Abstract: The Discrete Element Method (DEM) is a Lagrangian approach initially developed

for predicting particles flow. The eXtended Discrete Element Method (XDEM) framework,

developed at the LuXDEM Research Centre of the University of Luxembourg, extends DEM

by including the thermochemical state of particles, as well as their interaction with a

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Computational Fluid Dynamics (CFD) domain. The level of detail of its predictions makes

the XDEM suite a powerful tool for predicting complex industrial processes like steel

making, powder metallurgy and additive manufacturing. Like in any other DEM software,

the critical aspect of the simulations is the computation requirement that grows rapidly as

the number of particles increases. Indeed, such burden currently represents the main

bottleneck to its full exploitation in large-scale scenarios. Digital Twin, a research project

founded by the European Regional Development Fund (ERDF), aims at drastically accelerate

XDEM through different approaches and make it an effective tool for numerical predictions

in industry as well as virtual prototyping. The Multiphase Particle-In-Cell (MP-PIC) method

has been introduced for reducing the computation burden of DEM. It has been initially

developed for predicting particles flow and uses a two-way transfer of information between

the Lagrangian entities and a computation grid. The method avoids explicit contact

detection and can potentially achieve a drastic reduction of the time-to-solution respect to

DEM. The present contribution introduces a multiphase approach for predicting the

conductive heat transfer within a static packed bed of particles. Results from a test case are

qualitatively and quantitatively compared against reference XDEM predictions. The method

can be effectively exploited in combination with MP-PIC for predicting the thermochemical

state of particles.

SY086-a

18:30-18:45

Reynolds number effect on the flow and heat transfer around a bio-inspired cylinder

Hyo Ju Kim and Hyun Sik Yoon

Pusan National University, Republic of Korea

Abstract: The present study is an original research for the forced convection heat transfer

around a harbor seal vibrissa shaped (HSV) cylinder inspired by a geometry of the harbor

seal’s vibrissa. Also, this study is an initial investigation to find the effect of the Reynolds

number (Re) based on the hydraulic diameter in the laminar flow regime (50≤Re≤500). .

This characteristic of the heat transfer is comparable to the unique ability of the HSV to

suppress the lift fluctuation and to role as a detecting device to capture the water

movement induced by prey fish. We carried out numerical simulations to investigate the

flow and heat transfer around the HSV in and Prandtl number (Pr) of 0.7. The circular and

elliptic cylinder with same hydraulic diameter are considered for the purpose of the

comparison. The time histories of the surface-averaged Nusselt number showed that the

HSV provided the stable behavior of the heat transfer by the significant suppression of its

fluctuation. Also, the time- and surface averaged Nusselt number for the HSV, regardless of

the Re, is smaller than that of the circular and elliptic cylinder. The Strouhal number,

vortical structures and thermal fields are compared among those three different cylinders.

SY060

18:45-19:00

Material Handling System Modeling of a Modern FAB

Kwanwoo Lee, DaeSoon Chang and Sang C. Park

Ajou University, Republic of Korea

Abstract: This paper presents a modeling methodology for a material handling system of a

modern FAB. These days, a system of the modern FAB is complex owing to reentrant

process characteristic of the semiconductor FAB process. This research introduces briefly

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about AMHS and the notion about DEV&DESS (Discrete Event System and Differential

Equation System Specification). It presents the OHT (Overhead Hoist Transport) movement

model has described using the DEV&DESS formalism. The reason for using DEV&DESS in

this research is that it is suitable formalism to describe complex systems. Specially, we had

to avoid a collision between OHT vehicles while performing a simulation. Finally, it shows

the implementation result of the OHT in sample semiconductor FAB model to validate a

model which we had modeled.

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Session V - Computer information engineering and

image processing < January 9, 2018, Tuesday>_Afternoon

Time:16:15-19:00

Room: Belvoir

Chair: Prof. Shubhamoy Dey

Indian Institute of Management, India

※Please kindly participate in the whole course of the conference to make sure each session stays on time and keep the agenda runs smoothly.

AC001-A

16:15-16:30

An investigation of the effects of sports sponsorship engagement on social media

Kapil Kaushik and Shubhamoy Dey

Indian Institute of Management, India

Abstract: Social media is a popular tool used by event sponsors to engage their customers.

By engaging customers on digital platforms, sponsors aim to leverage the return on their

sponsorship investments. Sponsors post messages about their involvement, offers, and

activities related to the event for stimulating online participation among users. This study

aims to examine which characteristics of sponsors’ messages lead to higher popularity of

sponsorship-related content among customers. Event related tweets from the sponsors of

four tennis grand slams were collected for analysis using a web crawler. Tweet

characteristics such as interactivity, message focus (customer, product, or player),

vividness (availability of image or video), and volume (number of other tweets posted

simultaneously) were coded for each tweet. Using negative binomial regression, we

studied the effect of the aforementioned characteristics on the number likes a tweet

attracts. Findings suggest that sponsors’ messages focusing on players are likely to receive

a larger number of likes on the social media. Similarly vividness i.e. presence of image or

video increases the popularity of tweets. It was also observed that congestion in tweet

space, such as posting of a larger number of tweets by sponsors during a given period of

time, leads to lowering of the popularity of all the tweets. Findings from this study will

help digital marketing managers design and deliver content for engaging customers on

social media.

AC002

16:30-16:45

Hybrid Index Structure based on MBB Approximation for Linked Data

Yongju Lee and Sun YuXiang

Kyungpook National University, Korea

Abstract: Although a pragmatic approach towards achieving Semantic Web has gained

some traction with Linked Data, there are still a lot of open problems in the area of Linked

Data. Because Linked Data are modeled as RDF graphs, we cannot directly adopt existing

solutions from database systems or Web technologies. This paper presents a hybrid

method between the centralized approach and the distributed approach based on query

processing to increase the join query performance. Using auxiliary indexes we can retrieve

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distributed data resources participating on a query result, rapidly reducing the amount of

data that are really needed to be accessed on-demand. The performance of the proposed

index structure is compared with some existing methods on a real RDF dataset. Our

method outperforms the existing methods due to its ability to reduce a large amount of

irrelevant resources.

AC007-A

16:45-17:00

Sentiment Mining from Blog Reviews at Features Level

Prabin Kumar Panigrahi and Nishikant Bele

Indian Institute of Management Indore, India

Abstract: Sentiment mining is a text categorization problem where positive, negative and

neutral categories are assigned to the unstructured documents. Unlike English language,

limited research is done on sentiment mining of non-English language. Hindi, the national

language of India is extensively used and the information is available on social networking

sites. Feature level sentiment involves identifying features of objects in the blog review

and then extraction of sentiments of particular object feature as a negative, positive or

neutral. In this paper, we extract sentiment of people from Hindi blog reviews on a

political personality at the feature level, which is unique in nature. Feature level sentiment

mining is used to find the weak and strong influential characteristics of the political

personality. We develop political blog reviews corpus in Hindi language and used Hindi

subjective lexicon and WordNet.

AC027

17:00-17:15

Neural Machine Translation Enhancements through Lexical Semantic Network

Quang-Phuoc Nguyen, Anh-Dung Vo, Joon-Choul Shin, Cheol-Young Ock

University of Ulsan, Republic of Korea

Abstract: In most languages, many words have multiple senses, thus machine translation

systems have to choose between several candidates representing different senses of an

input word. Although neural machine translation has recently become a dominant

paradigm and achieved great progress, it still has to confront with the challenge of word

sense disambiguation. Neural machine translation models are trained to identify the

correct sense of a word as part of an end-to-end translation task, and their performances

on word sense disambiguation are not satisfactory. This paper presents a case study of

machine translation for Korean language. We have manually built a Korean lexical

semantic network - UWordMap - as a large-scale lexical semantic knowledge-based in

which each sense of every polysemous word is associated with a sense-code constituting

a network node. Then, based on UWordMap, we determine the correct sense and tag the

appropriated sense-code for polysemous words of the training corpus before training

neural machine translation models. Experiments on translation from Korean to English

and Vietnamese show that UWordMap can significantly improve quality of Korean neural

machine translation systems in terms of BLEU and TER cores.

AC028

17:15-17:30

Automatic Knowledge Extraction for Aspect-based Sentiment Analysis of Customer

Reviews

Anh-Dung Vo, Quang-Phuoc Nguyen, Cheol-Young Ock

University of Ulsan, Republic of Korea

Abstract: It is challenging to figure out the most common appraisal of an online product

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since there are too many reviews about it uploaded on the internet. Several research

methods using opinion mining in the context of the online reviews have been suggested

to solve this issue. The existing research on opinion mining can be classified into three

general levels: document-level, sentence-level, and aspect-level sentiment analysis.

Aspect-based evaluation is the most meaningful application in opinion mining, and

researchers are getting more interested in product aspect extraction; however, more

complex algorithms are needed to address this issue precisely with larger corpora. This

paper introduces a method to automatically gain a knowledge-based system, which then

is used to capture product aspects and corresponding opinions from a large number of

product reviews in a specific domain. Our efforts tend to improve accuracy and the

usefulness of review summaries by leveraging knowledge of product aspect extraction

and provide both appropriate level of detail and richer representation capabilities.

AC031

17:30-17:45

A computation modification for multi-layered neural network using Extended Kalman filter

Kyungsup Kim, Hui-Joon Kim and Yu-Jae Won

Chungnam National University, Korea

Abstract: A lot of learning algorithms for deep layered network are sincerely suffered from

complex computation and slow convergence because of a very large number of free

parameters. We need to develop an efficient algorithm for deep neural network. The

Kalman filter concept can be applied to parameter estimation of neural network to

improve computation performance. The algorithms based extended Kalman filter has a

serious drawback in its computational complexity. We discuss how a fast algorithm should

be developed for reduction in computation time.

SY050

17:45-18:00

Methods of Pornography Detection: Review

Sasan Karamizadeh and Abouzar Arabsorkhi

Faculty of Iran Telecommunication Research Center, Iran

Abstract: In recent years, prone images and other such indecent matter are available on

the social media and the Internet for children. Filtering of image porn has become one of

the big changes for searches; they are tied to finding methods to filter porn images. Social

media network is interested in filter porn images from normal ones. Analysis method uses

the bright image to automatically detect and filter images in the media. In this paper, we

have reviewed methods such as color based, shape based, local and global feature

approach, deep learning and bag-of-words for filtering porn images which include

comparing with the advantages and disadvantages.

SY058

18:00-18:15

SW: a blind LSBR image steganalysis technique

Saman Shojae Chaeikar and Ali Ahmadi

Khaje Nasir Toosi University of Technology, Iran

Abstract: Blind image steganalysis is exploring body of digital images for the likely

presence of hidden secret messages without knowledge of the employed steganographic

technique. This paper proposes a novel image steganalysis technique to attack spatial

domain LSBR stego images. The chosen steganalytic feature is the relation between length

of the embedded message and the regressed proportion of intensity identical pixels and

color channels. A trained SVM analyzes the pixels and the final decision is made based on

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union of the pixel analysis results. In SW, a number of innovative contributions are made

to the field of blind image steganalysis. First, measuring pixel and cannel color correlativity

as steganalytic feature. Second, defining pixel membership degree, thereby the pixels gain

different level of influence on the process. Third, generating six references for statistical

patterns of cover and stego pixels. And fourth, achieving 99.626% steganalyzer sensitivity

on 0.25bpp stego images by only two analysis dimensions.

SY035

18:15-18:30

Analyzing Human Visual Perception of Streetscape Elements through Taxonomic Diagrams

G. M. W. L Gunawardena

University of Moratuwa, Sri Lanka

Abstract: Any element is made of several sub elements and they have complex

connections on the physical world. It shows a hierarchy. The complexity caused due to this

hierarchical structure of variety and connections is called structural hierarchical

complexity. However, in the visual world, these physical elements will be perceived based

on their visual qualities like color, shapes, size, and distance. During the course of visual

perception, some elements will be highlighted while some elements will be suppressed.

Visual perception has an order of viewing objects. This order of visual perception creates

invisible connections among the viewing objects and it leads to have an invisible

hierarchical structure of perception. This phenomenon can be explained as structural

hierarchical visual perception.

Therefore, this research was carried out with the objective of representing this structural

hierarchical visual perception as diagrams to show these invisible connections among

visual elements in human perception. To achieve this objective, the Gestalt's explanation

on figure and background classification was applied. For this analysis, a survey was carried

out with 60 subjects. Subjects were asked to travel along 100 streetscapes in Colombo

District while explaining the most eye catching elements in an orderly way. The

explanations were recorded as video clips. Later those video clips were analyzed and the

subjects’ explanations were arranged as taxonomic diagrams to display order of visual

perception by each subject. The ordering of visual elements by sixty subjects for different

streetscapes displayed unique patterns such as residential streetscapes resulted one

common pattern and this pattern was different from the viewing pattern of commercial

streetscapes. Thus the structural hierarchical visual perception for different streetscapes

was different to each streetscape type. The taxonomic diagrams drawn to different

streetscape types were varied in their lengths and the widths attesting this difference in

visual perception in varied streetscape types. Thus by analyzing taxonomic diagrams, it

was very straightforward to understand the structural hierarchical visual complexity on

different streetscape types. Thus taxonomic diagrams are a best representation of

structural hierarchical visual perception as well as the structural hierarchical complexity.

SY066

18:30-18:45

Estimating Parameter for the Mixture Generalized Gamma Distribution

Wikanda Phaphan

King Mongkut’s University of Technology North Bangkok, Thailand

Abstract: Mixture generalized gamma distribution is a combination of two distributions --

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Generalized gamma distribution and length biased generalized gamma distribution. This

distribution is presented by Suksaengrakcharoen and Bodhisuwan in 2014. The findings

showed that probability density function (pdf) had fairly complexities, so it made

problems in estimating parameters. The problem occurred in parameter estimation was

that we were unable to calculate estimators in the form of critical expression. Thus, we

will use numerical estimation to find the estimators. In this study, we presented a new

method of the parameter estimation by using the expectation – maximization algorithm

(EM), the conjugate gradient method, and the quasi-Newton method. The data was

generated by acceptance-rejection method which is used for estimating , ,α β λ and

p . λ is the scale parameter, p is the weight parameter, α and β are the shape

parameters. We will use Monte Carlo technique to find the estimator's performance.

Determining the size of sample equals 30, 100 and the simulation were repeated 20

times in each case. We evaluated the effectiveness of the estimators which was

introduced by considering values of the mean squared errors and the bias. The findings

revealed that the EM-algorithm had proximity to the actual values determined. Also, the

maximum likelihood estimators via the conjugate gradient and the quasi-Newton method

are less precision than the maximum likelihood estimators via the EM-algorithm.

SY2005

18:45-19:00

An Overview on the Application of Self-Adaptive Differential Evolution

Sarah Hazwani Adnan, Shir Li Wang, Haidi Ibrahim and Ng Theam Foo

Universiti Sains Malaysia, Malaysia

Abstract: Differential Evolution (DE) is possibly the most current powerful stochastic

real-parameter optimization algorithm and has been used in multiple diverse area such as

neural networks, logistics, scheduling, modelling and others. Its simplicity, ease of

implementation and reliability had captures many practitioners and scientists in

implementing the algorithm. As different problems require different parameter setting,

the implementation of DE in tackling complex computational optimization problem is

quite challenging. Nevertheless, success of the algorithm depends on the ability to choose

the right parameter setting based on problems in hand. Thus, extra attention is needed in

order to fine tune the perfect parameter for each problem. Self-adaptive Differential

Evolution (SADE) algorithm had been introduced in order to simplify the search for the

right parameter to be used in DE algorithm. With the introduction of SADE in optimization

areas, where the choice of learning strategy and parameter setting do not require

predefining, parameter tuning has become less confusing. This paper aims at providing an

overview on significant application that have benefited from SADE implementation. SADE

had been applied in numerous discipline such as electromagnetics, power system,

computer performance, fermentation, polyester process and more. SADE has also proven

to achieve better performance compared to conventional DE algorithm. By collecting

and analyzing related articles that have implemented SADE in solving problem, a

significant trends on the application of SADE will be provided.

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Session VI - Communication and information system < January 9, 2018, Tuesday>_Afternoon

Time: 16:15-19:00

Room: Seymour

Chair: Assoc. Prof. Takeshi Tsuchiya

Tokyo University of Science, Japan

※Please kindly participate in the whole course of the conference to make sure each session stays on time and keep the agenda runs smoothly.

AC004-A

16:15-16:30

A Crowdsourcing Indoor Navigation System for Smartphone Users

Meng-Shiuan Pan and Kuan-Ying Lee

Tamkang University, Taiwan

Abstract: Recently, researchers have paid attention to designing indoor navigation

services for smartphone users. We observe that conventional indoor navigation systems

highly rely on well-known indoor information and prior training phase for localization.

However, a plug-and-play indoor navigation system without too much bootstrapping

configuration would be more practical. In this work, we propose a system, which exploits

pedestrian dead reckoning (PDR) and crowdsourcing technologies to provide indoor

navigation services. The proposed system consists of a front-end mobile APP and a

back-end server. The mobile APP infers users' walking trajectories according to sensory

values from smartphones. The back-end server handles crowdsourced trajectories with

the help of deployed beacon devices, and then produces pathways of the indoor

environment. Our evaluations reveals that the CrdNavi can effectively derive users'

walking trajectories, produce indoor pathways, and indicate directions for users.

AC005

16:30-16:45

A Novel Non-Stationary Multipath Fading Channel Model Based on Propagation

Measurements Using SDR and FPGA

Martin Tomis, Radek Martinek, Petr Koudelka, Libor Michalek, Marek Dvorsky, Radana

Kahankova

VSB-Technical University of Ostrava, Czech Republic

Abstract: Non-stationary multipath fading channel models are necessary for the design

and optimization of communications systems (the 5th generation mobile networks—5G,

the (Industrial) Internet of Things, etc.). These models are considered as essential

components of channel simulators which are similar to physical radio channels. This

article describes a progressive novel method of adaptive non-stationary multipath fading

channel models based on a real measurement of Channel Impulse Response (CIR). The

designed system measures, classifies and subsequently adaptively changes the

parameters of a transmission channel model. The proposed concept is based on the

Software Defined Radio (SDR) and Field Programmable Gate Array (FPGA) which are

implemented on the modular platform of PCI Extensions for Instrumentation (PXI). This

approach enables to approximate and subsequently adaptively model any transmission

environment. Thanks to the application of the adaptive parameter setting approach we

ABSTRACT

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can create unique dynamic models of real transmission channels which can be used for

designing, testing and optimizing new trends in the field of wireless communications

systems (new modulation formats, algorithm testing, channel equalization, optimization

of source and channel coding, guard interval adaptation, etc.)

AC015

16:45-17:00

Speech Quality Assessment Based on Virtual Instrumentation

Radek Martinek, Radana Kahankova, Petr Bilik, Jan Nedoma, Marcel Fajkus, and Petr

Blaha

VSB-Technical University of Ostrava, Czech Republic

Abstract: This paper introduces a program for objective and subjective evaluation of

speech quality. Using this environment, a lot of speech recordings and various indoor and

outdoor noises were processed. As a subjective speech evaluation method, the Dynamic

time warping (DTW) method was selected, with PARCOR coefficients being chosen as

symptom vectors. For the filtration of the noise in the recording, adaptive filtering based

on LMS and RLS algorithms was used and the performance of the adaptive filtering was

assessed. Similarity ranged from 70% to 95% for both algorithms. In terms of signal to

noise ratio, the RLS algorithm ranged from 36 dB to 42 dB, while the LMS algorithm only

varied from 20 dB to 29 dB.

SY048

17:00-17:15

The User Acceptance Test of An “ICT Adoption for Education” Framework

Sofiana Nurjanah, Harry Budi Santoso, Zainal Arifin Hasibuan

Universitas Indonesia, Indonesia

Abstract: Improving the quality of education continuously and sustainably is the task of

the whole communities, but in particular the government can take over the policy on the

important components by providing the best support and contribution in order to

improve the quality of education and achieve the expected Information and

Communication Technology (ICT) adoption goals. This study conducts user acceptance

test of ICT adoption framework in schools to ensure actual system use. In this context,

school is a potential user of the framework to be assessed for its acceptance of the

framework by exploring acceptance characteristics such as performance expectancy,

effort expectancy, social influence and facilitating conditions which mapped into

perceived usefulness and perceived ease-of-use. This test also has a behavior analysis

part by using Technology Acceptance Model (TAM) and Unified Theory of Acceptance and

Use of Technology (UTAUT) combination. This test is a research final phase in small scale

representative sampling in order to strengthen future implementation plans. Involving

about 60 schools to use the framework in the context of the preparation of adoption ICT

in school. The result shows that average school responses revealed that the school

administrators' lack of understanding identified needs and linked them to the intended

objectives. It concludes that framework can be accepted with some suggestions.

SY092

17:15-17:30

Microstrip Grid Antenna Array for 5G Mobile Devices

Saif Aldeen Saad Obayes Al-Kadhim, Ibtesam R. K. Al-Saedi, Basil Jabir Shanshool

University of Technology, Iraq

Abstract: This paper focused on the development of Microstrip Antenna Array, which

operates at 28 GHz where this frequency suggested as operating frequency for 5th

Generation mobile technology. The proposed antenna structure is constructed with a

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single patch located in an array configuration within one plane. The antenna is fed from

the backside via a coaxial fed. Normally in array antenna technology, researchers use full

ground plane approach in order to meet a good antenna performance. The development

of proposed antenna involved simulation, optimization, fabrication and measurement to

get the best antenna performance at desired frequency. Simulation and optimization

phase was done using Computer Simulation Technology (CST) software, which has the

capability of giving a better look on performance of antenna in simplest way.

SY079

17:30-17:45

Signal Timing Simulation of Single Intersection based on Fuzzy-Genetic Algorithm

LUO Qin, HOU Yufei, WANG Zhuoqun

Shenzhen University, China

Abstract: Intersection is an important component of the urban transport network, in

where traffic congestion usually takes place. One of the key to solve urban transport

problems is to organize the traffic in the intersection reasonably and effectively. This

paper does research on a specific single intersection, using the video traffic data

collection technology, considering signal cycle and phase time which are decided by a

real-time traffic flow. The paper developed a self-adaptive timing model on the single

target constraint to reduce intersection delay. The model is carried out through

fuzzy-genetic algorithm. Matlab simulation analysis and a series of comparison show that

the methods of optimization models and genetic algorithm are effective and feasible.

SY2002

17:45-18:00

Speech Signal Processing using Microphones NI 9234 and LabVIEW

Radek Martinek, Radana Kahankova, Petr Bilik, Jan Nedoma, Marcel Fajkus, Michal Skacel

VSB - Technical University of Ostrava, Czech Republic

Abstract: The paper deals with the speech processing and adaptive filtration. Introduced

application is implemented in both online and offline mode in LabVIEW. The online mode

program is used to create a database of speech recordings and various interferences from

the outdoor environment as well as from the home. The offline application then serves to

test adaptive algorithms for the needs of speech processing. The criterion for comparing

the efficiency of individual algorithms is primarily to increase the signal to noise ratio. To

test the filtration rate, a global SNR method was chosen.

SY2004

18:00-18:15

Fetal ECG Preprocessing Using Wavelet Transform

Radek Martinek, Radana Kahankova, Jan Nedoma, Marcel Fajkus, Kristyna Cholevova

VSB - Technical University of Ostrava, Czech Republic

Abstract: Fetal electrocardiography is one of the most promising methods of Electronic

fetal monitoring, which helps physicians to assess the fetal well-being diagnose the

hypoxic states. This paper focuses on introducing Wavelet Transform as an effective tool

to suppress the most frequent types of fetal electrocardiogram interferences, such as

powerline or myopotential interference. We also suggest optimal type of the wavelet and

threshold for this purpose.

SY2003

18:15-18:30

Comparison of LMS, NLMS, RLS, and QR-RLS Algorithms for Vehicle Noise Suppression

Radek Martinek, Radana Kahankova, Jan Nedoma, Marcel Fajkus, Michal Skacel

ABSTRACT

49 / 51

VSB - Technical University of Ostrava, Czech Republic

Abstract: The paper deals with the speech processing and adaptive filtration. For the

analysis we used application implemented in both online and offline mode in LabVIEW.

The experiments included comparison of the noise caused by electric car and diesel car

which was measured and analyzed by means of Microphones NI 9234 and our

application. We tested four different adaptive filters to cancel the noise and compared

their efficiency. The criterion for comparing the efficiency of individual algorithms is

primarily to increase the global signal to noise ratio (GSNR).

AC024

18:30-18:45

Improving Network Throughput on Application by Weighting Subflows of Muti-Path TCP

Adapted to Conditions

Takeshi Tsuchiya, HIROSE Hiroo, MIYOSAWA Tadashi, YAMADA Tetsuyasu, SAWANO

Hiroaki, KOYANAGI Keiichi

Tokyo University of Science, Japan

Abstract: This paper is discussed and proposed the weighting manner of MPTCP

(Multi-Path TCP) subflow adapted to network conditions, and it improves network

throughput efficiency. In our proposal, subflows are controlled expansion and suppression

of congestion window size according to state of subflow under the environment which

communications among subflows does not affect each other. From the results of

simulation, it shows improvement of average throughput on application layer, and

increase of packet arrival rate between sessions.

AC010

18:45-19:00

Fiber-optic Bragg sensors for the rail applications

Radek Martinek, Jan Nedoma, Marcel Fajkus, and Radana Kahankova

VSB-Technical University of Ostrava, Czech Republic

Abstract: The publication describes the use of fiber-optic sensors in the rail applications.

We created a measuring system and sensor based on the fiber Bragg gratings (FBG). The

basic tracked parameters of vehicles are detection and speed. The proposed system was

tested in the real tram traffic. The system is characterized by a detection capability of

100 %, speed measurement is characterized by an absolute error of + - 3 kph. Sensors can

be connected to existing city fiber networks. Information could be remotely processing

because the spectral evaluation of sensors is not limited by the output power of the

radiation source.

Dinner <19:00-21:00> Location: Restaurant Note: dinner coupon is needed for entering the restaurant.

LISTENERS LIST

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LISTENERS LIST

Kolawole Olakiitan Naga Venkata Ram Kiran Yalamanchili

Jae-Hyun Seo Dae-Won Kim

Joon-Choul Shin Miyoung Lee

Hyun Chul Shin Jameel Almalki

Jeongjin Lee Xiaowen Yang

Agugu Chisom Justice Hyun Sik Yoon

Tran Ngoc Son Kai HU

DaeSoon Chang

NOTE

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