COMP 763 Reading Phase Presentation Notes I 12 March 2008 Presentation 1. Solving Dynamic Non-causal Algebraic Equation Sets Andrew Casey Simplification of Equations: Procedure: 1)move everything to the LHS; 2)re-express with fewer operators; 3)fold constant: sorintg them nicer. Rules for simplification Issue: Not performed; Not morphiform; no best way of simplificaton Canonical: order the variables and operators Causality Assignment: fllow graph What we want? One to one relation between equation and set of varibales Maximise the flow from the source to the sink How? Repeatly do Find the path from source to sink Reverse the edges (make unaviable for search) Then we find a matching (1-to-1) between equation and variables Issue: non-deterministic Order Equation Dependency Issue: Multiple solutions Runtime Add/Edit Equation ¨C Dynamic Set ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Presentation 2.State chart modeling of Tank Wars Silvia Mur Blanch Model characters (tanks) using class diagram Model detailed bahavior using state chart formalism Model the components of tanks and assemble ==Class relations +++ event sequences +++ == Time slicing vs Event Driven Time slicing vs Continuous (model freedom) Choose the level of abstraction Events; layers; data (filtering) Choose a formalism State/event-based; Avialability of simulators; well-known; modularity; antomanous/reactive behvior; notion of itme. ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Presentation 3.Hybrid Modeling in AnyLogic Alexandre Denault Different application needs different level of modeling Hybrid logic Discrete/continuous modeling in a nice way Angent based modeling: decentralised and individual centric (Pros and Cons: simulation is costly) Disceret Event Modeling AnyLogic implement this by state chart; timer; plain variable. Continuous Time System Sonething is not suitable cing discrete system (like ¡°swing¡±) Use various variables and equations Flows Equation to flow Table of function Missing variable AnyLogic all back to Java Equation System: solving equations (certain threshold. Diceret)<-Hybrid model Example: Tennis Ball in the water ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Presentation 4.Testing Modeling Tranformation Amr Al Mallah OO vs MDA OO MDA Proble/Domain Domain UML DS-L Lanaguage UML Running Program Running Program How to Transform LHS -> RHS graphic or DEVS MOF ¨C MetaModel Meta-object facility Testing transformation Aim: error & Confidence How?: white box (MTP) & black box MetaModel coverage: Coverage item Systematic approach Bacterio logical approach Challenge Generation of test data automatically Compring the expectedmodel to actual model(model difference, semantic difference) ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ COMP 763 Reading Phase Presentation Notes II 17 March 2008 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Presentation 5. User Interface for Xmulator developed using Aton3 Sina Meraji Area: Interconnection networks & Topology Background: Interconnection network (IN) means ¡°Share memory and processor¡±. In an interconnection network, Toplogy -> Direct & Undirected Routing alg: answer ¡°who¡± -> simple and regular topology -> low delay, high bandwidth Switching algo: answer ¡°when¡± ->store and forward packeting (trans. whole packet, slow) -> wormhole (fast but prone to deadlock) Xmulator: XML + Simulator Features: Designed for developing interconenction networks; Object Oriented Listener-based network simulator Xmulator is multi layered, whose 4 layers are¡­ Listener based integration Structure of listener is as figure below ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Presentation 6. Modeling of Aspect Weaving Wisam Al Abed Aspect Oriented Modeling Model ¡®concerns¡¯ so that they are modular and reusable Aspect model: Linking Weaving: make ¡­ classify ¡­ tracable When and how to weave? Base aspect (target) Bind/instantiate bind temporary parameter to model element thus create a context-specific aspect model. Different configuration model Temporary weaved (parameters) <- used in reusable aspect model as generic place holder the value need in target model. Inter-Aspect dependency declaration Copy and put into tracable .. ASPECTS ARE REUSABLE Template parameter preserving aspect-aspect weaving Weave to 2 aspect together Late dependency approaches ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Prsentation 7. Heterogeneous Modeling and Simulation in Ptolemy YanwarAsrigo Issue: Systems are usually modeled from the components and each model only represents part of the entire system. This situation raise a problem, which is HOW TO EVALUATE the behavior of the WHOLE system. Solution is to use Heterogeneous Modeling and Simulation. The Ptolemy adopt Hierarchically Heterogeneous idea to address the problem. It introduce the idea of Actor Oriented Design. Ptolemy define Actor (an agent, reusable) as the basic block of the system. The actors are concurrent components communicating through ports. Instead of transmitting a sequential control (which is used in Object Oriented Design), Actor Oriented Design decoupled the data flow from the control flow (which is the idea from hardware design). Ptolemy has an Model of Computation (MoC) to define the scheduling and communication. The problem we mentioned before is solved as A composition of actors governed by some MoC can more easily be analyzed and understood More on the ptolemy Actor and Domain (MoC) Actor is atomic, composite (self-contained) and executable (state only changes at certain stage) Domain: Network -> we can define its bahavior like a formalism (has Director and Receiver) Polymorphism: both component and domain, both data and behavior ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Presentation 8. City Map Riry Pheng Issue: generate content and images Procedual technique: Used in CG for 2 decades -> to generate different CG effects The key concept are entity(description) and call instrcution(providing parameter for objects) Techniques: 1.Fractal (large degree of self similarity) 2.L system (Lindermayer) 3.Perlin noise ¨C natural looking textual, tile-able output to minimise storage 4.Tiling 5.VoronoiTexure Basis City Generation: (please find corresponding techniques above) 1.buildings 2.obtain an coherent map 3.4.5.techique decides the architechture (bahavior realisticly) ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ COMP 763 Reading Phase Presentation Notes III 19 March 2008 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Presentation 9. Model based Generation Yuan Jin Develop a Personal Universal Controler to control domestic appliances from handset. Main Job: Interface geneartion Exsiting problem: Abstract of XML Consistency in layout: different design of interfaces for similar devices ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Presentation 10. Meta Edit+ Willer trovassos Motivation: To slove problems like, 1.Lack of model integrity ->consistency check 2.Lack of multi user access 3.lack of varied object representation 4.lack of reportary technique Meta Edit+ is a true meta-model environment 5 different categories of tools Design Principle: Object Oriented Modeling, (class, relation) Data Independence Object Repository Architecture: Meta Engine Easier and integration Duplication Database -> save models in the database GOPRRR Language