Understandability of Hybrid Process Models Using DCR Graphs

While the understandability of process models has been extensively investigated for different process modeling notations, it has not been yet broadened to cover hybrid models. This paper proposes a new research model to investigate the understandability of hybrid model representations using a variety of psycho-physiological measurements including eye tracking and galvanic skin response (GSR) together with verbal data analysis. The aim of this research is to ensure a smooth integrationof hybrid modelling technologies in public administrations by investigating the way end-users (i.e., case workers) rely on the different parts of the hybrid process model representation in DCR Graphs, i.e., the graph, the textual annotations describing the law, and the simulation tools to interpret the process model

A framework for modeling and analysis of dynamical properties of spiking neurons

A hybrid systems framework for modeling and analysis of robust stability of spiking neurons is proposed. The framework is developed for a population of n interconnected neurons. Several well-known neuron models are studied within the framework, including both excitatory and inhibitory simplified Hodgkin-Huxley, Hopf, and SNIPER models. For each model, we characterize the sets that the solutions to each system converge to. Using Lyapunov stability tools for hybrid systems, the stability properties for each case are established. An external stimuli is introduced to the simplified Hodgkin-Huxley model to achieve a global asymptotic stability property. Due to the regularity properties of the data of the hybrid models considered, the asserted stability properties are robust to small perturbations. Simulations provide insight on the results and the capabilities of the proposed framework. © 2014 American Automatic Control Council

Characterization and modelling of electromagnetic interactions in aircraft

This article describes the development of modelling techniques and simulation tools for the electromagnetic (EM) analysis of aircraft. It is shown that hybrid solvers and multi-scale techniques can be used effectively to analyse the EM response of aircraft. The importance of supplementing models with appropriate measurement and characterization techniques for parameter extraction and for validation is also demonstrated

StocHy: automated verification and synthesis of stochastic processes

StocHy is a software tool for the quantitative analysis of discrete-time stochastic hybrid systems (SHS). StocHy accepts a high-level description of stochastic models and constructs an equivalent SHS model. The tool allows to (i) simulate the SHS evolution over a given time horizon; and to automatically construct formal abstractions of the SHS. Abstractions are then employed for (ii) formal verification or (iii) control (policy, strategy) synthesis. StocHy allows for modular modelling, and has separate simulation, verification and synthesis engines, which are implemented as independent libraries. This allows for libraries to be easily used and for extensions to be easily built. The tool is implemented in C++ and employs manipulations based on vector calculus, the use of sparse matrices, the symbolic construction of probabilistic kernels, and multi-threading. Experiments show StocHy's markedly improved performance when compared to existing abstraction-based approaches: in particular, StocHy beats state-of-the-art tools in terms of precision (abstraction error) and computational effort, and finally attains scalability to large-sized models (12 continuous dimensions). StocHy is available at www.gitlab.com/natchi92/StocHy

Spatio-temporal stochastic hybrid models of biological excitable membranes

A large number of biological systems are intrinsically random, in particular, biological excitable membranes, such as neuronal membranes, cardiac tissue or models for calcium dynamics. The present thesis is concerned with hybrid stochastic models of spatio-temporal dynamics of biological excitable membranes using Piecewise Deterministic Markov Processes (PDMPs). This class of processes allows a precise mathematical description of the internal noise structure of excitable membranes. Overall the aim of the thesis is two-fold: On the one hand, we establish a general hybrid modelling framework for biological excitable membranes and, on the other hand, we are interested in a general advance of PDMP theory which the former necessitates. Regarding the first aim we exemplify the modelling framework on the classical Hodgkin-Huxley model of a squid giant axon. Regarding the latter we present a general PDMP theory incorporating spatial dynamics and present tools for their analysis. Here we focus on two aspects. Firstly, we consider the approximation of PDMPs by deterministic models or continuous stochastic processes. To this end we derive as general theoretical tools a law of large numbers for PDMPs and martingale central limit theorems. The former establishes a connection of stochastic hybrid models to deterministic models given, e.g., by systems of partial differential equations. Whereas the latter connects the stochastic fluctuations in the hybrid models to diffusion processes. Furthermore, these limit theorems provide the basis for a general Langevin approximation to PDMPs, i.e., certain stochastic partial differential equations that are expected to be similar in their dynamics to PDMPs. Secondly, we also address the question of numerical simulation of PDMPs. We present and analyse the convergence in the pathwise sense of a class of simulation methods for PDMPs in Euclidean space.Engineering and Physics Research Council (EPRC) EP/E03635X/1ANR project MANDy (ANR-09-BLAN-0008-01)BC/DAAD ARC project Nr 1349/50021880ARC project Nr. 133

Application and modelling of hybrid stereolithography injection mould tooling

The use of stereolithography (SL) to make injection moulding tools has been shown previously to be an efficient way of producing rapid tools for simple geometries, aiming at small lot sizes with an acceptable degree of accuracy. This paper highlights the unexplored potential of using SL inserts in hybrid tools using practical experiments and FEA mould filling models. The practical experiments reveal problems incurred by uneven flow as a result of differential thermal conductivity between dissimilar mould materials in a hybrid tool. The FEA flow models confirm that this uneven flow would be anticipated when using FEA software. A further FEA stress analysis predicts that catastrophic mould failure will be expected under some conditions and these reflect the results found in the practical experiments. The use of a homogeneous SL tool eliminates the issues caused by uneven mould filling but results in thermal distortion of the female mould. Ultimately a SL tool backfilled with low melt point alloy provides a solution that eliminates the problems of uneven filling and thermal distortion

A Social Analysis of Software Development Teams: Three Models and their Differences

In this paper we analyze the socio-technical activity called software development by focusing on the social perspective. We do so to pursue two questions: What can we learn about software development by focusing on its social aspects and what insight does a social perspective give us regarding the production methods, techniques and tools uses in software development? From the social perspective, this analysis suggests three models of software teams. For each of these we outline, compare, and comment on issues with the way the task, methods and tools are conceptualized. We include a brief discussion of hybrid models such as those used at Microsoft and other packaged software vendors