51,511 research outputs found

    Decision support system for the long-term city metabolism planning problem

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    A Decision Support System (DSS) tool for the assessment of intervention strategies (Alternatives) in an Urban Water System (UWS) with an integral simulation model called “WaterMetÂČ” is presented. The DSS permits the user to identify one or more optimal Alternatives over a fixed long-term planning horizon using performance metrics mapped to the TRUST sustainability criteria (Alegre et al., 2012). The DSS exposes lists of in-built intervention options and system performance metrics for the user to compose new Alternatives. The quantitative metrics are calculated by the WaterMetÂČ model and further qualitative or user-defined metrics may be specified by the user or by external tools feeding into the DSS. A Multi-Criteria Decision Analysis (MCDA) approach is employed within the DSS to compare the defined Alternatives and to rank them with respect to a pre-specified weighting scheme for different Scenarios. Two rich, interactive Graphical User Interfaces, one desktop and one web-based, are employed to assist with guiding the end user through the stages of defining the problem, evaluating and ranking Alternatives. This mechanism provides a useful tool for decision makers to compare different strategies for the planning of UWS with respect to multiple Scenarios. The efficacy of the DSS is demonstrated on a northern European case study inspired by a real-life urban water system for a mixture of quantitative and qualitative criteria. The results demonstrate how the DSS, integrated with an UWS modelling approach, can be used to assist planners in meeting their long-term, strategic level sustainability objectives

    Search based software engineering: Trends, techniques and applications

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    © ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is available from the link below.In the past five years there has been a dramatic increase in work on Search-Based Software Engineering (SBSE), an approach to Software Engineering (SE) in which Search-Based Optimization (SBO) algorithms are used to address problems in SE. SBSE has been applied to problems throughout the SE lifecycle, from requirements and project planning to maintenance and reengineering. The approach is attractive because it offers a suite of adaptive automated and semiautomated solutions in situations typified by large complex problem spaces with multiple competing and conflicting objectives. This article provides a review and classification of literature on SBSE. The work identifies research trends and relationships between the techniques applied and the applications to which they have been applied and highlights gaps in the literature and avenues for further research.EPSRC and E

    Methods of Technical Prognostics Applicable to Embedded Systems

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    HlavnĂ­ cĂ­lem dizertace je poskytnutĂ­ ucelenĂ©ho pohledu na problematiku technickĂ© prognostiky, kterĂĄ nachĂĄzĂ­ uplatněnĂ­ v tzv. prediktivnĂ­ ĂșdrĆŸbě zaloĆŸenĂ© na trvalĂ©m monitorovĂĄnĂ­ zaƙízenĂ­ a odhadu Ășrovně degradace systĂ©mu či jeho zbĂœvajĂ­cĂ­ ĆŸivotnosti a to zejmĂ©na v oblasti komplexnĂ­ch zaƙízenĂ­ a strojĆŻ. V současnosti je technickĂĄ diagnostika poměrně dobƙe zmapovanĂĄ a reĂĄlně nasazenĂĄ na rozdĂ­l od technickĂ© prognostiky, kterĂĄ je stĂĄle rozvĂ­jejĂ­cĂ­m se oborem, kterĂœ ovĆĄem postrĂĄdĂĄ větĆĄĂ­ mnoĆŸstvĂ­ reĂĄlnĂœch aplikaci a navĂ­c ne vĆĄechny metody jsou dostatečně pƙesnĂ© a aplikovatelnĂ© pro embedded systĂ©my. DizertačnĂ­ prĂĄce pƙinĂĄĆĄĂ­ pƙehled zĂĄkladnĂ­ch metod pouĆŸitelnĂœch pro Ășčely predikce zbĂœvajĂ­cĂ­ uĆŸitnĂ© ĆŸivotnosti, jsou zde popsĂĄny metriky pomocĂ­, kterĂœch je moĆŸnĂ© jednotlivĂ© pƙístupy porovnĂĄvat aĆ„ uĆŸ z pohledu pƙesnosti, ale takĂ© i z pohledu vĂœpočetnĂ­ nĂĄročnosti. Jedno z dizertačnĂ­ch jader tvoƙí doporučenĂ­ a postup pro vĂœběr vhodnĂ© prognostickĂ© metody s ohledem na prognostickĂĄ kritĂ©ria. DalĆĄĂ­m dizertačnĂ­m jĂĄdrem je pƙedstavenĂ­ tzv. částicovĂ©ho filtrovanĂ­ (particle filtering) vhodnĂ© pro model-based prognostiku s ověƙenĂ­m jejich implementace a porovnĂĄnĂ­m. HlavnĂ­ dizertačnĂ­ jĂĄdro reprezentuje pƙípadovou studii pro velmi aktuĂĄlnĂ­ tĂ©ma prognostiky Li-Ion baterii s ohledem na trvalĂ© monitorovĂĄnĂ­. PƙípadovĂĄ studie demonstruje proces prognostiky zaloĆŸenĂ© na modelu a srovnĂĄvĂĄ moĆŸnĂ© pƙístupy jednak pro odhad doby pƙed vybitĂ­m baterie, ale takĂ© sleduje moĆŸnĂ© vlivy na degradaci baterie. SoučástĂ­ prĂĄce je zĂĄkladnĂ­ ověƙenĂ­ modelu Li-Ion baterie a nĂĄvrh prognostickĂ©ho procesu.The main aim of the thesis is to provide a comprehensive overview of technical prognosis, which is applied in the condition based maintenance, based on continuous device monitoring and remaining useful life estimation, especially in the field of complex equipment and machinery. Nowadays technical prognosis is still evolving discipline with limited number of real applications and is not so well developed as technical diagnostics, which is fairly well mapped and deployed in real systems. Thesis provides an overview of basic methods applicable for prediction of remaining useful life, metrics, which can help to compare the different approaches both in terms of accuracy and in terms of computational/deployment cost. One of the research cores consists of recommendations and guide for selecting the appropriate forecasting method with regard to the prognostic criteria. Second thesis research core provides description and applicability of particle filtering framework suitable for model-based forecasting. Verification of their implementation and comparison is provided. The main research topic of the thesis provides a case study for a very actual Li-Ion battery health monitoring and prognostics with respect to continuous monitoring. The case study demonstrates the prognostic process based on the model and compares the possible approaches for estimating both the runtime and capacity fade. Proposed methodology is verified on real measured data.

    Developing a distributed electronic health-record store for India

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    The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India
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