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Modelling Methodology and Optimization
Continuous, discrete and hybrid simulation methodology, Simulation environments, Multi-paradigm simulation, Simulation uncertainty, Simulation visualisation, Integration of simulation and geographical information systems, Object-oriented programming and Languages, Multi-paradigm Languages, Software comparisons. Numerical Methods for Simulation, Mathematical Analysis in Simulation, Parallel Simulation Methodology, Discrete Event Simulation, Simulation Fidelity and Performance Evaluation, Advanced Training and Simulation Concepts for Education, Multiparameter Sequential Optimization Methods in Simulation, Verification, Validation, and Control in Complex Systems Simulation, Distributed and Parallel Systems Simulation, Combined Continuous and Discrete Event Models, Symbol Analysis and Manipulation of Equation-Based Models, Simultaneous vs Modular Simulation Methods, Standardization Issues.
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Modelling Tools, Development and Deployment
Simulation languages; Object oriented modeling languages; UML and simulation; Model libraries and modularity; Component-oriented simulation; Special simulation tools and environments; Meta-models and automatic model generation; Graphical simulation environments and simulation software tools; Intelligent simulation environments; Database management of models and results; Java and Web enabled simulations, UML and OO Simulation.
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Analysis Methodology and Systems Performance
Advanced Input Modeling, Simulation Optimization, Cross Entropy, Output Analysis, Input Modeling, Simulation Optimization, Input Analysis, Difficult Queueing Problems, New Output Analysis.
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Simulation of Secure Networks and Communications; Autonomic and Autonomous systems
Modeling and simulation of analogue circuits; Modeling and simulation of digital circuits at switch and/or at logic level; Hardware accelerators for circuit-level simulation; Hardware accelerators for logic simulation; Distributed simulation of circuits, components, and systems; Modeling and simulation of computer systems; Fault simulation; Parallel and distributed systems; High-speed networks; Network simulation software; Computer and telecommunication systems; Telecommunication devices and systems; Intelligent telecommunication networks; ISDN; ATM communications.
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Electronics Simulation
Cleanroom Manufacturing, Manufacturing Technologies, Information Technology, Surface Engineering, Coating Technology and Simulation of Complex Multiprocessor Systems.
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Complex Systems Simulation
Design and Simulation, - Process Control and Optimisation, - Information Technology Systems, - Space and Airborne Systems - Communication Networks, - Cybernetics and Control, - Building Engineering and Urban Infrastructures - Nonlinear Systems, Integration of AI Techniques and Simulation, Knowledge Elicitation and Representation for Complex Models, Drawing Understanding and Pattern Recognition, Machine Learning, Neural Networks and Genetic Algorithms, Simulation in Robotics and Automation, Continuous Simulation of Technical Processes, Fuzzy Models in Simulation, Wireless Communication, Mobile Communication Networks, Satellite Communication, LAN and WAN Protocols, Simulation of Switching Equipment, Design and Coding of Communication Handling Software.
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Simulation of Digital Information and Image Processing
Modelling and simulation are powerful tools in image and signal processing applications. For example, the modelling and simulation of communication networks enable the analysis and evaluation of data communication techniques in a much more time and cost efficient way than field tests. Modelling and simulations are also extensively used in biomedical signal processing to study and predict physical behaviour. Mathematical models such as Markov random fields and optical flows have been successfully used to solve a variety of image processing problems, including image restoration, reconstruction, segmentation, and classification as well as texture analysis.
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Energy Systems Simulation
Simulators: Real-Time simulation methods, GUI, Advanced modelling tools, Trainees' performance evaluation, Simulator Projects Simulation Studies: Simulation during design, Safety and environmental hazard estimation, Production optimisation. Methodology: Real-time simulation and visualisation tools, Parallel and distributed simulation.
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Simulation in the Chemical and Petrochemical Industry
Simulation of Chemical Plants, Flow simulation, Plant control systems, network simulation, geological simulations, drilling simulations, oil transport simulations.
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Multimedia, Virtual Reality Systems and Knowledge Virtualization
This track covers simulation programmes used in Multimedia and VR systems enhanced simulation
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Decision Processing in Management and Knowledge Data Systems
Business process engineering and simulation, Simulation in customer-oriented service processes, Decision support systems, Simulation in Finance and Risk Management, Simulation in workflow management, Process mapping and simulation, Simulation of production processes and equipment, Business Information Modeling Methods and Methodologies, UML and UP in Business Modelling, UML and UP for Enterprise Modeling.
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Image/Speech Processing
This track looks at how simulation can be used in the fields of Digital Imgae Processing and Speech Processing.
Digital image processing allows for Classification, Feature extraction, Pattern recognition, Projection and Multi-scale signal analysis of data using Pixelation, Linear filtering, Principal components analysis, Independent component analysis, Hidden Markov models, Anisotropic diffusion, Partial differential equations, Self-organizing maps, Neural networks and Wavelets.
While Speech processing using both acoustic modeling and language modeling, Hidden Markov models (HMMs), Language modeling, Dynamic time warping (DTW)-based speech recognition, Neural networks and Deep Neural networks are used inevery day life applications, the military, healthcare et al.
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Wireless/Mobile Communications
This track looks at data and infrastructure simulation for Mobile telephones, Wireless data communications, Wireless energy transfer, Wireless Medical Technologies and Computer interface devices.
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Modelling and Simulation in Biomedical Systems and Biotechnology
Topics are biological systems, medical systems and ecosystems with the domain specific topics such as molecular modelling, genetic algorithms in biosystems, fuzzy sets and neural nets in biosystems, physiology, cardiology, anesthesia, cancer, circulatory system, respiratory system, renal system, biomechanics, agricultural production, simulation of global change, ecotechnology and eco-engineering, GIS, population dynamics, etc Simulation of Patient Care,Quality of Service, Hospital Logistics, Simulation of Disease Proliferation, Virtual Reality in Surgical Procedures, Simulating Biological Phenomena and Organs, Simulation as a Tool for Diagnosis, Simulation of Emergency Procedures (Disaster Gaming), General Medical Simulations, Pharmacometric Modelling, Physiological Simulations.
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Modelling and Simulation for Industrial Applications and Systems
The application section covers: Automation, CAD/CAM/CAE, Defense Electronics, Design Automation, Simulation in industrial Design, Industrial Engineering, Industrial and Process Simulation, Manufacturing, Simulations, Logistics and Transport, Power Plants, Multibody Systems, Aerospace, etc..
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Simulation in Logistics, Traffic, Transport and Harbour Simulation
Factory and Logistics Planning
Strategies and Concepts for Production and Logistics, Technical and Organizations Planning of Production and Logistics Systems, Value Stream Mapping, In-Plant Logistics, Integrated Factory and Logistics Planning, Innovative Planning Methods, tools and systems.
Production Scheduling and sequencing, Optimization of Production and Assembly Lines Design, Robust Supply Chain Management, Demand Driven Supply Networks, Inventory and routing
Logistics
Supply Chain Optimization and Network Design, Logistics supply chains, inbound logistics, materials management, Manufacturing Supply Chain Management, physical distribution, production planning and control, outbound and inbound logistics, Simulation of regional logistic systems, distribution centres, inventory theory and management, warehousing decisions, strategic inventory management, materials management, handling and packaging, logistics information systems, information management in logistics systems, logistics network design and facility location, cost modelling, Merge-in-Transit and Consolidation Centers, Inter-Firm Collaborations for Logistics, Web based logistics, Military Logistics, Strategic and Operational Carrier Selection in Transportation Auctions
Traffic
Traffic flows, multi-modal systems, transit, transportation modes, urban city transport, transportation in logistics, transportation management, traffic demand, traffic control, traffic telematics, traffic performance, safety, macroscopic, mesoscopic and microscopic simulations. Tools for risk assessment analysis and monitoring of container traffic.
Port Simulation
Bulk Terminals, Container Terminals, Harbour Services, Industrial Facilities, Navigation Lines, Multimodal Transports, Oil Terminals, Passenger Terminals, Railways, Ro-Ro Terminals, Ships and Platforms, Supply Chains and Warehouses, Harbour Management, Safety in Maritime Environments, Vessel Traffic Systems.
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Web Based Information Simulation
Web-based Simulation Environments (WSE), Web-based Distributed Interactive Simulation (WDIS) Sharing and reuse of simulation models and tools in WSE, Techniques and Standards for model integration, Communication interoperability in WSE and WDIS, WSE and WDIS applications to education, training and learning, Simulation visualization/animation in WSE and WDIS, Web-based Distributed Simulation (distributed modelling via the Web, Java based, Federated, and so on)
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Simulation in Information Processing and Software Development
Topics covered by this track are: Agile Methods, Computer Supported Cooperative Software Engineering, Configuration Management, Dependable and Secure Computing, DevOps and Operations (esp. in Distributed/Cloud Environment), Domain-specific Models and Languages, and Model Driven Development, Domain-specific Applications for Logistics, Finance, Health Care,Manufacturing, Defense etc., Empirical Research in Software Engineering, Engineering Big Data and Analytics Applications, Engineering Cloud Applications, Engineering/operating Large-Scale Distributed Systems, Formal Methods, Knowledge-Based Software Engineering, Legacy Systems, Software Maintenance and Reverse Engineering, Measurement, Metrics, Experimentation, Mobile Computing and Apps Development, Modularisation Techniques, including Component-Based Software Engineering and Aspect-Oriented Programming, Open Source Software Development, Programming Languages and Techniques such as Dynamic Languages, Concurrent and Functional Programming, Quality Assurance, Real-Time and Embedded Software, Requirements Engineering, Service Oriented Architectures and Services Engineering, Software Analysis and Visualisation, Software Architecture, Design and Patterns, Software Documentation, Software Ecosystem and Ultra-Large-Scale Systems, Software Engineering of Multi-Agent Systems, Software Engineering of Services, Software for Internet of Things and Ubiquitous Computing, Software Modelling Approaches, Software Performance Engineering, Software Processes and Quality, Software Project Management and Risk Management, Software Reuse and Product Lines, Software Security, Safety and Reliability, Software Verification and Validation, Usability, Web Applications and REST.
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Computational Cognition and Distance Learning
The computational cognition and learning" (CCL) track covers studies of the computational basis of human learning and inference by using mathematical modeling, computer simulation and behavioral experiments. Aim of such studies is to uncover the basis behind the processing of information. Fields of the CCL track includes
Bayesian Networks, Bayesian Estimation, Bayesian Inference, Bayesian Statistics, Conditional Independence, Factor Analysis, Hidden Markov Models, Maximum Likelihood Estimation, Principle Components Analysis, Hebbian Learning, Reinforcement Learning, Model-Based and Model-Free Learning, Sensory Integration and Kalman Filtering.
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Intelligent Agent Based Simulation
Agent Based Simulation is an inter-disciplinary area which brings together researchers from different areas, the social simulation and the Multi-agent Systems. The focus of Agent Based Simulation is on simulating and organization social behaviours in order to understand real social systems via the development and testing of new concepts.
The following topic areas (although this list should not be treated as exclusive), will be object of interest:
- Agent-based simulation techniques and methodologies
- Agent Architectures, Model Specification and Languages
- Decision making and Strategies
- Game Theory and Fuzzy logic for agent-based modeling
- Discrete-event simulation in Multi-Agent Systems
- Multi-Level Simulation and Emergence
- Simulation toolkits and frameworks
- Applications in Ecology and Environment, Psychology, Cognitive Science and AI, Economics and Market Systems, Business Process Management, Industry, Manufacturing and Logistics and Transport and Healthcare with the emphasis on simulation and modeling
- Agent-based modeling (ABM) within geographical systems
The aim of this track is to allow the debate on emerging issues, gathering the scientific community researching in these areas. This workshop is a forum for discussion and presentation of new contributions on Agent-based simulation
Thus, it is intended:
• to identify the critical points of the use of Agent-based simulation as well as processes and the areas where is needed an urgent action;
• to present and discuss new approaches, trends and innovative aspects of the Agent-based simulation;
• to promote the use of Agent-based simulation and to explore ways to overcome resistance to change;
• to analyze the level of use of Agent-based simulation in Europe and to compare with the world situation.
With this track it is expected that the scientific community gets some
directions from what has been done and what can be done by motivating the
researching and the search for new solutions in the area of Agent Based Simulation
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Evolutionary Computation, Simulation in Fuzzy Systems
Classification, Data analysis, Fault tolerance, Forecasting, Knowledge acquisition, Economics and Finance, Planning, Pre-treatment of data, Process control, Robotics, Speech and image recognition, Web intelligence, involving methodologies such as: Hybrid systems (GA, fuzzy, symbolic representation), Methods or tools for evaluating ANN performance, Reinforcement Learning, Simulation tools (research, education, development).
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Neural Networks and Genetic Algorithms
Neural nets for simulation: modelling of parts (components) of the system simulated by neural networks, evaluation of simulation models using neural nets, decision support in simulation models by neural nets; Simulation of neural nets: systems of pre-designed neural networks, techniques and tools for simulation and programming of neural networks. Expert Controllers and Genetic Algorithms in Simulation, Knowledge Based Simulation Tools, AI and Expert Systems in Simulation.
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Simulation in the Built Environment
The built environment is a complicated and many-faceted energy system encompassing many different yet synergistic energy flow paths. Each flow path changes its own (and hence the system's) characteristics. tics dynamically as time progresses. To accurately model such phenomena a simulation model must take into account all relevant energy subsystems and the interrelationships between them.
The areas covered by building simulation models are numerous and varied and include conduction modelling, air/fluid flow modelling, plant side modelling, insulation analysis, lighting studies and building climatic interaction.
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Simulation in Defense
Simulation and Visualization (2D and 3D visualization of simulations). Advanced concepts and Requirements (simulation of new concepts, requirements development, predicted impacts of technology integration, intelligent systems simulation). Advanced Integrative Multiscale Modelling. Military Entertainment Convergence (wargaming, serious games). Research, Development and Acquisition (Design, development and acquisition for new weapons systems and equipment, Simulation and Modeling for acquisition, requirements, and training (SMART), Simulation-based acquisition). Training, Exercises and Military Operations (simulation in training, simulator/exercise Integration and Management, Mission Planning and Rehearsal, Embedded Training, Assessment. Physical Modelling and Effects (Lethality, vulnerability and survivability, impact and penetration modelling, computational fluid and molecular dynamics, structural and solid mechanics modelling, ballistics and propellant simulation). Entity and System Modelling and Behaviours (human performance modelling, entity behaviours, computer generated forces, agent-based combat modelling, flock modelling and behaviour). Domains (sea, Land, Air and Space (synthetic environments (f ex.DAWARS, JWARS), virtual realities, surface and sub-surface warfare, unmanned robotic land, sea and aerial vehicle simulation (UAV, UCAV), avionics, flight control, flight simulation, simulation and control for spacecraft). Operations, Command and Control and Interoperability (battle field, battle theatre simulation, simulation during operations, CAI simulation, counterforce operations, airspace management, campaign analysis). Military Networking (network modelling and simulation, network centric warfare, information assurance modelling and simulation, simulations and the Global Information Grid). Terrain Recognition and Analysis Simulation Software, Image Analysis and Image Recognition, Asymmetric Warfare and threats. Modelling the "Cloud" concept of ever ready "orbital" units.
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Simulation in Archaeology
Archaeologists commonly use theoretical models, experiments, and observations of the world as it is today to try to explain what happened in the past. They have attempted to explain, for example, why people first began to walk upright and why civilizations that once flourished suddenly collapsed. Good explanations come from well-thought-out theoretical models that propose ways in which the existing archaeological record might have been formed. Explanations can include factors such as environmental changes, demographic shifts (changes in population makeup and size), migrations, and patterns of thought and behavior.
In recent years, many archaeologists have begun to use geographic information systems (GIS) to aid in mapping sites. These computer-based systems allow the collection, storage, and manipulation of environmental, geographic, and geologic data, together with archaeological information, in a single database. Using this technology, archaeologists can create maps that simulate different environments and ways in which people might have used land, living space, and material goods.
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Simulation Projects in the Arab World
Roundtable discussion on present projects in the Arab World. If you have a topic proposal.
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