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Kota Kinabalu, Sabah (Malaysia) 3 – 5 December Note new date
Submission: see above
Starts: from 1 March 2013
Final Upload into EDAS for checking &
31 October 2013
Credit Card on EDAS
to CPS server & copyright form:
1 November 2013
Dr Ismail Saad, UMS
Dr Rayner Alfred, UMS
Dr Athanasios Pantelous
University of Liverpool
Dr. Khairul Anuar Mohamad, UMS
Dr. Lau Hui Keng, UMS
Dr Zuwairie Ibrahim, UTM
Dr Adam Brentnall, Queen Mary, London University
Dr Alessandra Orsoni
Dr. Mohd Hanafi Ahmad Hijazi, UMS
Dr. Chin Kim On, UMS
Mr Kenneth Teo. UMS
Prof Jasmy Yunus, UTM
Prof Borhanuddin Mohd Bin Ali, UPM
Prof Mahamod Ismail UKM
Prof Philip Sallis, AUT
Prof Rosni Abdullah, USM
Prof Paulus Rihardjo, UNPAR
Prof Rosalam Sarbatly, UMS
CLOSED New extended DEADLINE 25 October 2013 (EDAS remains open till 3 November for late papers)
Write your Paper using these Templates:
Then submit it through EDAS: http://edas.info
Papers are invited on any aspect of the development of concepts, principles, algorithms, their modelling and simulation in Artificial Intelligence and their applications in all areas relevant to system engineering, science, technology, business, management and industry to be presented at AIMS2013. Conference content will be submitted for inclusion into IEEE Xplore as well as other Abstracting and Indexing (A&I) databases. Selected papers will be submitted for publication in the International Journal of Simulation: Systems, Science & Technology, IJSSST (http://ijssst.info). The event provides authors with an outstanding opportunity for networking and presenting their work at a top quality international conference.
AIMS2013 will be held
over 3 day period in
- Algorithms, principles and architectures for Artificial Intelligence (AI)
- emulation to exhibit Natural Intelligence (NI) behaviour
- Neural Networks
- Fuzzy Systems
- Evolutionary Computation
- Autonomous Mental Development
- Adaptive Dynamic Programming and Reinforcement Learning
- Computational Finance and Economics
- Data Mining
- Games, Virtual Reality and Visualization
- Emergent Technologies
- AI Applications
- Intelligent Systems
- Hybrid Intelligent Systems
- Soft Computing and Hybrid Soft Computing
- Computational Intelligence
- Systems Intelligence
- Intelligence Systems
- Control of Intelligent Systems
- Control Intelligence
- e-Science and e-Systems
- Robotics, Cybernetics, Engineering, Manufacturing and Control
- Methodologies, Tools and Operations Research
- Bio-informatics and Bio-Medical Simulation
- Discrete Event and Real Time Systems
- Image, Speech and Signal Processing
- Industry, Business and Management
- Human Factors and Social Issues
- Energy, Power Generation and Distribution
- Transport, Logistics, Harbour, Shipping and Marine Simulation
- Supply Chain Management
- Virtual Reality, Visualization and Computer Games
- Parallel and Distributed Architectures and Systems
- Internet Modelling, Semantic Web and Ontologies
- Mobile/Ad hoc wireless networks, mobicast, sensor placement, target tracking
- Performance Engineering of Computer & Communication Systems
- Circuits, Sensors and Devices
Suggested topics (other topics are also welcome): Artificial Intelligence methodology and practice, languages, tools and techniques. Models and modelling tools. Data/object bases. Analytical and statistical tools. Simulators and simulation hardware, training simulators. Integration of simulation with concurrent engineering, integrated design and simulation systems. AI, intelligent systems, agent-based simulation, decision support systems, philosophical issues, analogies, metaphors, knowledge modelling, acquisition and synthesis of new knowledge/models, intelligent/adaptive behaviour, man/machine interaction, control systems. Parallel and distributed simulation, discrete event systems. Artificial neural networks, computational intelligence.
Applications: aerospace; remote sensing; electronic circuits and systems; communication and networks; business; management; finance; economics; leisure, games, war/conflict/rebellion modelling; psychology, cognitive functions, behaviour, emotion, subjectivity; humanities, literature, semantics modelling/dynamics; biology; medicine; public health; energy, power generation and distribution, manufacturing; planning; control; robotics; measurement; monitoring; energy; safety critica1 systems; transportation; structural mechanics and civil engineering, oil and gas; education and training; military.
Exhibitors: manufacturers of software and hardware, publishers, etc., are invited to apply to exhibit their products.
The conference is organised and sponsored by UK Simulation Society/Asia Modelling and Simulation Section, and (under consideration) Technically-Co-Sponsored by IEEE Malaysia section and IEEE Region 10. Patrons, Promoters and supporters of the conference include: University of Malaysia in Sabah, University of Malaysia in Pahang, University of Technology Malaysia, Nottingham Trent University, IEEE UK & RI Computer Chapter, EUROSIM and European Council for Modelling & Simulation.
Submissions must be original, unpublished work containing new and interesting results that demonstrate current research in all areas of artificial intelligence, modelling and simulation and their applications in science, technology, business and commerce. Full papers only, 6 pages maximum, are accepted for review.
Submission implies the willingness of at least one of the authors to register and present the paper.
Paper Submission: AIMS2013 is using EDAS for submission, paper processing and registration, authors need to:
- create an account with EDAS by clicking on the link below
- open the list of conferences managed by EDAS & find AIMS2013
- click on Submit button on the right to enter your paper title & abstract
- upload file.
Kai Juslin (SIMS)
Esko Juuso (SIMS)
Khalid Al-Begain (UKSim)
Rashid Mehmood (UKSim)
Gaius Mulley (UKSim)
Miroslav Snorek (CSSS)
Andras Javor (HSS)
Franco Maceri (ISCS)
Peter Schwartz (ASIM)
Charles Patchett (BAE, Warton)
Henri Pierreval (FRANCOSIM)
Yuri Merkuryev (LSS)
Gaby Neumann (ASIM)
Hosam Faiq (Malaysia)
Hissam Tawfik (UK)
Jiri Kunovský (CSSS)
Azian Azamimi Abdullah (Malaysia)
Sanjay Chaudhary (India)
Arijit Bhattacharya (Ireland)
Atulya Nagar (UK)
Gregorio Romero (Spain)
Kenneth Nwizege (UK)
Kathy Garden (NZ)
M Luisa Martinez (Spain)
Suiping Zhou (Singapore)
Mikulas Alexik (CSSS,EUROSIM President)
Borut Zupancic (SLOSIM)
Igor Skrjanc (SLOSIM)
Wan Hussain Wan Ishak (Malaysia)
Nitin Nitin (India)
Ford Gaol (Indonesia)
Philip Sallis (NZ)
Martin Tunnicliffe (UK)
David Murray-Smith (UKSim)
Mahdi Mahfouf (UKSim)
Jimenez Macias (
Alessandra Orsoni (UKSim)
Vlatko Ceric (CROSSIM)Theodoros Kostis (Greece)
Russell Cheng (UKSim)
Angel Piera (
David Al-Dabass (UKSim)
Jadranka Bozikov (CROSSIM)
Richard Cant (UKSim)
Felix Breitenecker (ASIM, SNE)
Eduard Babulak (Canada)
Siegfried Wassertheurer (ASIM)Wolfgang Wiechert (ASIM)S. Wassertheurer (ASIM)
Janos Sebestyen-Janosy (HSS)
Olaf Ruhle (ASIM)
Zuwairie Ibrahim (Malaysia)
Marius Radulescu (ROMSIM)
Leon Bobrowski (PSCS)
Indihar Stemberger (
Rosni Abdulla (Malaysia)
V. Karadimas (
Piers Campbell (UAE)
Fabian Böttinger (Germany)
K.G. Subramanian (Malaysia)
Registration BEFORE deadline of 31 October
IEEE Members: 5% discount is given to author after presentation at conference
Registration AFTER deadline of 31 October
IEEE Members: 5% discount given to author after presentation at conference
Registration: Only one method of payment is available on EDAS:
Credit Card: payment is accepted online and confirmation is instant.
Here is the procedure:
1. go to EDAS at http://edas.info and click on Register yellow tab at the top, a list of conferences will appear
2. Scroll down to conference name (e.g. AIMS2013) line and click on the extreme right green money symbol at the end of this line, a new page will appear
3. click on the extreme right button (Trolley symbol) after USD $595, a new table will immediately appear under a new line “Registered, but no paid”.
4. Under this table a list of credit card symbols and SWIFT. Click on the credit card symbol.
5. A new page will appear, enter all card details, scroll down to the bottom and click Pay for Registration
6. REMEMBER: NO payment received by the set deadline means your paper will NOT be in the Proceedings.
If you have problems meeting this deadline email
Best wishes and look forward to meeting you at the conference.
AI Future Research Issue from Research Experience
Dong Hwa Kim
Hanbat National University, S.Korea
First, this lecture will provide research experience such as, IM (immune system), genetic algorithm, PSO (particle swarm optimization), BA (bacterial foraging), and its hybrid system and application to real system. In detailed description, this lecture describes research results about immune network based parameter estimation method for induction motor, PSO, BA, and Hybrid based optimal selection for PID controller through simulation and experiment in real system such as AVR and motor vector control system.
In the conventional genetic algorithm, it takes a long time to compute and could not include a variety of information of plant because of using sequential computing methods. That is some problem with making an artificial intelligence for optimization. In this lecture, by means of introducing selection algorithm of hybrid system into computing procedure, it will be showed advanced results. That is, it can be calculated simultaneously necessary information, transfer function, time constant, and etc., for plant operation condition. Therefore, computing time is about 30% shorter than that of the conventional genetic algorithm and 10.6% smaller in overshoot when it is applied to controller.
In this lecture we will show results of Rosenbrock function. All hybrid system have a faster computing speed than the previous one genetic or so.
The suggested method is applied to tuning of automatic controller for terminal voltage regulation of AVR (automatic Voltage Regulator) of thermal power plant and motor vector control system. Results in AVR reveal best response at 100 generations and results show 6.8331% error in GA, 5.3828% error (78.8%: reduced) in GA-PSO, in case of overshoot. In case of steady state error, results illustrate reduced error with 0.0028% error (16.4%: reduced) with 0.0171% in GA and 0.0143% in GA-PSO. In settling time, it represents 0.557(sec) in GA and 0.3989(sec) in GA-PSO and it reduce to 0.159(sec) (28.5%) by using GA-PSO. In the case of rise time, results shows 0.2037(sec) in GA and 0.2639(sec) in GA-PSO and tuning results are better than that of conventional method.
However, we have some questions why we have to study not introducing emotion function because emotion function can give an impact on decision making as they mentioned earlier. So, this lecture will mention how we can research for artificial intelligence and robot by using studied materials up to now. Especially, to get an idea for artificial intelligence, we strongly suggest that we had better investigate natural system such as BA, PSO, termites, bee, and so on. Of course, robots are becoming more and more ubiquitous in human environments as emerging technology for economic growth. Artificial intelligence will be decided by our ability to express effectively human’s mind such as intelligence and emotion. That is, emotion-inspired mechanisms will deal with importance for autonomous robots in a human environment, and also related works may be studied.
Herein, we are going to develop the corresponding fusion algorithms or models with learning algorithms including emotion function. Finally, presenter would like to have question; why are you going to research AI, Where are you going to get an idea?
Dong Hwa Kim, Ph.D.
Professor. Dept. of Instrumentation and Control Engineering Hanbat National University, 16-1 Duckmyong dong Yuseong gu Daejeon, South Korea 305-719.
Office Phone: 82-42-821-1170, Cell phone: 82-10-8958-1175, 82-10-4899-1170
Fax: 82-42-821-1164, Department Office: 82-42-821-1165
Ph.D: Dept. of Electronic Engineering, Ajou University in Korea
Ph.D: Dept. of Computational Intelligence and Systems Science, TIT (Tokyo Institute of Technology, K. Hirota Lab.), Tokyo, Japan. (Thesis Title: Genetic Algorithm Combined with Particle Swarm Optimization/Bacterial Foraging and Its Application to PID Controller Tuning)
Advanced Program for International Conference (Fall Semester, 2006), Hallym Institute of Advanced International Studies
Ph.D course, Graduate School International, Korea University, Sept. 2007-
Prof., Dept. of Instrumentation and Control Eng., Hanbat National University, March 2, 1993- Now
President, Institute of Korea HuCARE (President of Hu-CARE (Human-Centered Advanced Technology Research/Education), Nov. 2009-
EU-FP NCP (ICT) in Korea, April 29,2011-
Korea Atomic Energy Research Institute, Nov., 1977-March, 1993.
Korea-Hungary Joint Work : Aug.1,2010-Feb.28,2011, Participation in the research of Robot motion related topics of the ETOCOM project(TAMOP4.2.2-08/1/KMR-2008-2007) including consultation with research staff members and giving related lectures)
President, Daedeok Korea-India Forum, March 1, 2010 – Now.
Vice President, Daedeok Korea-Japan Forum, March 1, 2010 – Now.
President of Science Culture Research Institute, Korea Science Foundation, Sept. 8, 2006 - Jan. 31, 2008.
Vice-president of the recognition board of the world congress of arts, sciences and communications, IBC, Sept. 1, 2007, UK.
Marquis Who’s Who selected great minds in 21 Century, Aug. 2007/2008/2009.
ABI 200 International Scientist, Publishing in 2008.
Great minds of 21 Century to dedication in IBC, 2008.
UNESCO-APEC Asia Region Forum Held, Nov. 21, 2007.
Korean Science Forum Held, Oct. 22, 2007.
Science and Technology forum of the deputy Prime Minister of Korean Science and Technology, Operation, Aug. 1, 2006 – Nov. 30, 2007. (8 -round)
Fundamental Enhancements of Particle Swarm Optimization in Asynhronous, Discrete, and Multi-Objective Optimization
Univerisyt of Malaysia in Pahang
Particle Swarm Optimization (PSO) is a population based stochastic optimization algorithm, inspired by the social behavior of bird flocking and fish schooling. PSO has been introduced by Kennedy and Eberhart and contains a group of particles that move in a search space searching for an optimum solution according to a particular objective function. The movement of a particle is subjected to its own best found solution, pBest, and the best found solution in the neighborhood, gBest.
This lecture presents the latest fundamental enhancements of PSO in asynchronous update, discrete, and multi-objective problems.
Synchronous Asynchronous Particle Swarm Optimization
Particle swarm optimization (PSO) is one of the successful members of swarm intelligence family. The particles in PSO look for optimal solution by updating their velocity and position using two simple mathematical equations. Originally, the algorithm was introduced as a synchronous update algorithm (S-PSO), where the particles velocity and position are updated after the whole swarm performance is evaluated. Asynchronous update in PSO has been explored recently. A particle in asynchronous PSO (A-PSO) updates its velocity and position as soon after its own performance is evaluated. In this paper, we attempt to improve PSO by merging both synchronous and asynchronous update in the search process. The proposed algorithm, which is named as, Synchronous – Asynchronous PSO (SA-PSO), divides the particles into smaller groups. The best member of the group and the swarm’s best are chosen to lead the search. The members of the group are updated synchronously while the groups are asynchronously updated. Five well known unimodal functions and four multimodal functions are used here to study the performance of the proposed algorithm. The performance of the algorithm is compared with three existing PSO algorithms. The results show that the proposed algorithm is able to consistently produce good optimal solutions.
Multi-State Particle Swarm Optimization
The conventional binary particle swarm optimization (BPSO) algorithm is suffering from the problem of stagnation in local optimum and complexity. In updating current state to next state, the BPSO algorithm requires a high dimensional bit vector. Due to these challenging problems, in recent years, several attempts have been reported to improve BPSO algorithm. In this paper, a multi-state particle swarm optimization algorithm for solving discrete optimization problems is proposed. The proposed algorithm works based on a simplified mechanism of transition between two states. In order to avoid the repetitive states, a rule is embedded in the multi-state particle swarm optimization algorithm. In this paper, performance of multi-state particle swarm optimization with embedded rule (MSPSOER) is emperically compared to original and improved BPSO algorithms based on six sets of selected benchmarks instances of traveling salesman problem (TSP). The experimental results showed the effectiveness of the newly introduced approach, regarding its ability to consistently outperforms the binary-based algorithms in solving the discrete optimization problem.
Multi Non-Dominated Leaders Vector Evaluated Particle Swarm Optimization
The Vector Evaluated Particle Swarm Optimisation (VEPSO) algorithm has been widely used in solving multi-objective optimisation problems. In the VEPSO algorithm, particles of a swarm use the best solution found by their neighbourhood swarm to guide their movement. However, it has been found that the VEPSO mechanism is not capable of producing good solutions for multi-objective optimisation problems. Hence, non-dominated solutions and the concept of multi non-dominated leaders are incorporated to improve the VEPSO algorithm. The improved VEPSO is measured by the number of non-dominated solutions found, Generational Distance, Spread, and Hypervolume. This analysis shows that improved VEPSO signicantly improves upon the original VEPSO algorithm.
Dr Zuwairie Ibrahim received his B.Eng (Mechatronics) and M.Eng. (Image Processing) from Universiti Teknologi Malaysia, in 2000 and 2002,respectively. In 2006, he has been awarded a PhD (DNA Computing) from Meiji University, Japan. In 2002 to 2012, he was engaged with the Department of Mechatronics and Robotics, Faculty of Eletrical Engineering, Universiti Teknologi Malaysia, as a lecturer. Dr Zuwairie Ibrahim is currently an Associate Professor in the Faculty of Electrical and Electronic Engineering, Universiti Malaysia Pahang. He is the co-author of the book entitled Bioevaluation of World Transport Networks, published by World Scientific in 2012. He has been appointed to the Editorial of International Journal of Simulation: Systems, Science, and Technology (IJSSST) by UK Simulation Society and Jurnal Elektrika by Faculty of Electrical Engineering, Universiti Technologi Malaysia. He is also has been appointed as visiting researchers in universities in Japan and Malaysia. He is an author/co-author of more than 50 publications in international journals and more than 100 publications in conferences. His research interests include computational intelligence, image processing, and unconventional computation such as molecular or DNA computing.
 Shahriar Badsha, Norrima Mokhtar, Hamzah Arof, Yvonne Ai Lian Lim, Marizan Mubin and Zuwairie Ibrahim, Automatic Cryptosporidium and Giardia Viability Detection in Treated Water, EURASIP Journal on Image and Video Processing (accepted)
 Mohd Saberi Mohamad, Sigeru Omatu, Safaai Deris, Michifumi Yoshioka, Afnizanfaizal Abdullah, Zuwairie Ibrahim, An enhancement of binary particle swarm optimization for gene selection in classifying cancer classes, Algorithms for Molecular Biology, 2013, Vol. 8, No. 15.
 Kian Sheng Lim, Zuwairie Ibrahim, Salinda Buyamin, Anita Ahmad, Faradila Naim, Kamarul Hawari Ghazali, and Norrima Mokhtar, Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions, The Scientific World Journal, 2013, Vol. 2013, pp. 1-19.
 Andrew Adamatzky, Selim Akl, Ramon Alonso-Sanz, Wesley van Dessel, Zuwairie Ibrahim, Andrew Ilachinski, Jeff Jones, Anne V.D.M. Kayem, Genaro J. Martı´nez, Pedro de Oliveira, Mikhail Prokopenko, Theresa Schubert, Peter Sloot, Emanuele Strano and Xin-She Yang, Are motorways rational from slime mould’s point of view? International Journal of Parallel, Emergent and Distributed Systems, 2013, Vol. 28, No. 3, pp. 230-248.
73 Papers + 2 keynotes, Program. 8pm Monday 2 December KL Time
Session Chairs & Co-Chairs are urgently needed, kindly email firstname.lastname@example.org ASAP
1. Non Presentation does not affect publication, it only affects inclusion in I-Xplore 10 weeks after the conference.
2. Authors who find it impossible to attend must upload their Powerpoint file to EDAS for review by the committee to approve inclusion in I-Xplore.
3. Authors who state their intention to present but do not show up will not have the proceedings CD sent to them.
4. The program must be accurate to avoid time waste.
Program: Would Presenters upload their Powerpoint files to EDAS to have them ready & minimise switch-over time between presenters
Last minute changes: Removed: N1, F2, Taba, C3 New time: X4, Z7, ,