938 resultados para MESOSCOPIC SYSTEMS


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The integrated and process oriented nature of Enterprise Systems (ES) has led organizations to use process modeling as an aid in managing these systems. Enterprise Systems success factor studies explicitly and implicitly state the importance of process modeling and its contribution to overall Enterprise System success. However, no empirical evidence exists on how to conduct process modeling successfully and possibly differentially in the main phases of the ES life-cycle. This paper reports on an empirical investigation of the factors that influence process modeling success. An a-priori model with 8 candidate success factors has been developed to this stage. This paper introduces the research context and objectives, describes the research design and the derived model, and concludes by looking ahead to the next phases of the research design.

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We address robust stabilization problem for networked control systems with nonlinear uncertainties and packet losses by modelling such systems as a class of uncertain switched systems. Based on theories on switched Lyapunov functions, we derive the robustly stabilizing conditions for state feedback stabilization and design packet-loss dependent controllers by solving some matrix inequalities. A numerical example and some simulations are worked out to demonstrate the effectiveness of the proposed design method.

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A range of influences, both technical and organisational, has encouraged the wide spread adoption of Enterprise Systems (ES). Nevertheless, there is a growing consensus that Enterprise Systems have in many cases failed to provide expected benefits. The increasing role of, and dependency on ES (and IT in general), and the ‘uncertainty’ of these large investments, have created a strong need to monitor and measure ES performance. This paper reports on a research project aimed at deriving an ‘Enterprise Systems benefits measurement instrument’. The research seeks to identify how Enterprise Systems benefits can be usefully measured, with a ‘balance’ between qualitative and quantitative factors.