Discrete event simulation tool for analysis of qualitative models of continuous processing systems

An artificial intelligence design and qualitative modeling tool is disclosed for creating computer models and simulating continuous activities, functions, and/or behavior using developed discrete event techniques. Conveniently, the tool is organized in four modules: library design module, model construction module, simulation module, and experimentation and analysis. The library design module supports the building of library knowledge including component classes and elements pertinent to a particular domain of continuous activities, functions, and behavior being modeled. The continuous behavior is defined discretely with respect to invocation statements, effect statements, and time delays. The functionality of the components is defined in terms of variable cluster instances, independent processes, and modes, further defined in terms of mode transition processes and mode dependent processes. Model construction utilizes the hierarchy of libraries and connects them with appropriate relations. The simulation executes a specialized initialization routine and executes events in a manner that includes selective inherency of characteristics through a time and event schema until the event queue in the simulator is emptied. The experimentation and analysis module supports analysis through the generation of appropriate log files and graphics developments and includes the ability of log file comparisons

A theory of structural model validity in simulation.

During the last decennia, the practice of simulation has become increasingly popular among many system analysts, model builders and general scientists for the purpose of studying complex systems that surpass the operability of analytical solution techniques. As a consequence of the pragmatic orientation of simulation, a vital stage for a successful application is the issue of validating a constructed simulation model. Employing the model as an effective instrument for assessing the benefit of structural changes or for predicting future observations makes validation an essential part of any productive simulation study. The diversity of the employment field of simulation however brings about that there exists an irrefutable level of ambiguity concerning the principal subject of this validation process. Further, the literature has come up with a plethora of ad hoc validation techniques that have mostly been inherited from standard statistical analysis. It lies within the aim of this paper to reflect on the issue of validation in simulation and to present the reader with a topological parallelism of the classical philosophical polarity of objectivism versus relativism. First, we will position validation in relation to verification and accreditation and elaborate on the prime actors in validation, i.e. a conceptual model, a formal model and behaviour. Next, we will formally derive a topological interpretation of structural validation for both objectivists and relativists. As will be seen, recent advances in the domain of fuzzy topology allow for a valuable metaphor of a relativistic attitude towards modelling and structural validation. Finally, we will discuss several general types of modelling errors that may occur and examine their repercussion on the natural topological spaces of objectivists and relativists. We end this paper with a formal, topological oriented definition of structural model validity for both objectivists and relativists. The paper is concluded with summarising the most important findings and giving a direction for future research.Model; Simulation; Theory; Scientists; Processes; Statistical analysis;

CSP design model and tool support

The CSP paradigm is known as a powerful concept for designing and analysing the architectural and behavioural parts of concurrent software. Although the theory of CSP is useful for mathematicians, the programming language occam has been derived from CSP that is useful for any engineering practice. Nowadays, the concept of occam/CSP can be used for almost every object-oriented programming language. This paper describes a tree-based description model and prototype tool that elevates the use of occam/CSP concepts at the design level and performs code generation to Java, C, C++, and machine-readable CSP for the level of implementation. The tree-based description model can be used to browse through the generated source code. The tool is a kind of browser that is able to assist modern workbenches (like Borland Builder, Microsoft Visual C++ and 20-SIM) with coding concurrency. The tool will guide the user through the design trajectory using support messages and several semantic and syntax rule checks. The machine-readable CSP can be read by FDR, enabling more advanced analysis on the design. Early experiments with the prototype tool show that the browser concept, combined with the tree-based description model, enables a user-friendly way to create a design using the CSP concepts and benefits. The design tool is available from our URL, http://www.rt.el.utwente.nl/javapp

Simulation of networks of spiking neurons: A review of tools and strategies

We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented. We next review the precision of those simulation strategies, in particular in cases where plasticity depends on the exact timing of the spikes. We overview different simulators and simulation environments presently available (restricted to those freely available, open source and documented). For each simulation tool, its advantages and pitfalls are reviewed, with an aim to allow the reader to identify which simulator is appropriate for a given task. Finally, we provide a series of benchmark simulations of different types of networks of spiking neurons, including Hodgkin-Huxley type, integrate-and-fire models, interacting with current-based or conductance-based synapses, using clock-driven or event-driven integration strategies. The same set of models are implemented on the different simulators, and the codes are made available. The ultimate goal of this review is to provide a resource to facilitate identifying the appropriate integration strategy and simulation tool to use for a given modeling problem related to spiking neural networks.Comment: 49 pages, 24 figures, 1 table; review article, Journal of Computational Neuroscience, in press (2007

ROOT - A C++ Framework for Petabyte Data Storage, Statistical Analysis and Visualization

ROOT is an object-oriented C++ framework conceived in the high-energy physics (HEP) community, designed for storing and analyzing petabytes of data in an efficient way. Any instance of a C++ class can be stored into a ROOT file in a machine-independent compressed binary format. In ROOT the TTree object container is optimized for statistical data analysis over very large data sets by using vertical data storage techniques. These containers can span a large number of files on local disks, the web, or a number of different shared file systems. In order to analyze this data, the user can chose out of a wide set of mathematical and statistical functions, including linear algebra classes, numerical algorithms such as integration and minimization, and various methods for performing regression analysis (fitting). In particular, ROOT offers packages for complex data modeling and fitting, as well as multivariate classification based on machine learning techniques. A central piece in these analysis tools are the histogram classes which provide binning of one- and multi-dimensional data. Results can be saved in high-quality graphical formats like Postscript and PDF or in bitmap formats like JPG or GIF. The result can also be stored into ROOT macros that allow a full recreation and rework of the graphics. Users typically create their analysis macros step by step, making use of the interactive C++ interpreter CINT, while running over small data samples. Once the development is finished, they can run these macros at full compiled speed over large data sets, using on-the-fly compilation, or by creating a stand-alone batch program. Finally, if processing farms are available, the user can reduce the execution time of intrinsically parallel tasks - e.g. data mining in HEP - by using PROOF, which will take care of optimally distributing the work over the available resources in a transparent way

Model-based groupware solution for distributed real-time collaborative 4D planning via teamwork

Construction planning plays a fundamental role in construction project management that requires team working among planners from a diverse range of disciplines and in geographically dispersed working situations. Model-based four-dimensional (4D) computer-aided design (CAD) groupware, though considered a possible approach to supporting collaborative planning, is still short of effective collaborative mechanisms for teamwork due to methodological, technological and social challenges. Targeting this problem, this paper proposes a model-based groupware solution to enable a group of multidisciplinary planners to perform real-time collaborative 4D planning across the Internet. In the light of the interactive definition method, and its computer-supported collaborative work (CSCW) design analysis, the paper discusses the realization of interactive collaborative mechanisms from software architecture, application mode, and data exchange protocol. These mechanisms have been integrated into a groupware solution, which was validated by a planning team in a truly geographically dispersed condition. Analysis of the validation results revealed that the proposed solution is feasible for real-time collaborative 4D planning to gain a robust construction plan through collaborative teamwork. The realization of this solution triggers further considerations about its enhancement for wider groupware applications