907 resultados para Multi-criteria analysis
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This document presents a tool able to automatically gather data provided by real energy markets and to generate scenarios, capture and improve market players’ profiles and strategies by using knowledge discovery processes in databases supported by artificial intelligence techniques, data mining algorithms and machine learning methods. It provides the means for generating scenarios with different dimensions and characteristics, ensuring the representation of real and adapted markets, and their participating entities. The scenarios generator module enhances the MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) simulator, endowing a more effective tool for decision support. The achievements from the implementation of the proposed module enables researchers and electricity markets’ participating entities to analyze data, create real scenarios and make experiments with them. On the other hand, applying knowledge discovery techniques to real data also allows the improvement of MASCEM agents’ profiles and strategies resulting in a better representation of real market players’ behavior. This work aims to improve the comprehension of electricity markets and the interactions among the involved entities through adequate multi-agent simulation.
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The last decade has witnessed a major shift towards the deployment of embedded applications on multi-core platforms. However, real-time applications have not been able to fully benefit from this transition, as the computational gains offered by multi-cores are often offset by performance degradation due to shared resources, such as main memory. To efficiently use multi-core platforms for real-time systems, it is hence essential to tightly bound the interference when accessing shared resources. Although there has been much recent work in this area, a remaining key problem is to address the diversity of memory arbiters in the analysis to make it applicable to a wide range of systems. This work handles diverse arbiters by proposing a general framework to compute the maximum interference caused by the shared memory bus and its impact on the execution time of the tasks running on the cores, considering different bus arbiters. Our novel approach clearly demarcates the arbiter-dependent and independent stages in the analysis of these upper bounds. The arbiter-dependent phase takes the arbiter and the task memory-traffic pattern as inputs and produces a model of the availability of the bus to a given task. Then, based on the availability of the bus, the arbiter-independent phase determines the worst-case request-release scenario that maximizes the interference experienced by the tasks due to the contention for the bus. We show that the framework addresses the diversity problem by applying it to a memory bus shared by a fixed-priority arbiter, a time-division multiplexing (TDM) arbiter, and an unspecified work-conserving arbiter using applications from the MediaBench test suite. We also experimentally evaluate the quality of the analysis by comparison with a state-of-the-art TDM analysis approach and consistently showing a considerable reduction in maximum interference.
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4th International Conference on Climbing and Walking Robots - From Biology to Industrial Applications
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BACKGROUND: Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. METHOD: The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. RESULTS: The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice.
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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Dissertation presented to obtain the Ph.D degree in Biochemistry, Structural Biochemistry
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An energy harvesting system requires an energy storing device to store the energy retrieved from the surrounding environment. This can either be a rechargeable battery or a supercapcitor. Due to the limited lifetime of rechargeable batteries, they need to be periodically replaced. Therefore, a supercapacitor, which has ideally a limitless number of charge/discharge cycles can be used to store the energy; however, a voltage regulator is required to obtain a constant output voltage as the supercapacitor discharges. This can be implemented by a Switched-Capacitor DC-DC converter which allows a complete integration in CMOS technology, although it requires several topologies in order to obtain a high efficiency. This thesis presents the complete analysis of four different topologies in order to determine expressions that allow to design and determine the optimum input voltage ranges for each topology. To better understand the parasitic effects, the implementation of the capacitors and the non-ideal effect of the switches, in 130 nm technology, were carefully studied. With these two analysis a multi-ratio SC DC-DC converter was designed with an output power of 2 mW, maximum efficiency of 77%, and a maximum output ripple, in the steady state, of 23 mV; for an input voltage swing of 2.3 V to 0.85 V. This proposed converter has four operation states that perform the conversion ratios of 1/2, 2/3, 1/1 and 3/2 and its clock frequency is automatically adjusted to produce a stable output voltage of 1 V. These features are implemented through two distinct controller circuits that use asynchronous time machines (ASM) to dynamically adjust the clock frequency and to select the active state of the converter. All the theoretical expressions as well as the behaviour of the whole system was verified using electrical simulations.
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We report on the growth and structural and morphologic characterization of stacked layers of self-assembled GeSn dots grown on Si (100) substrates by molecular beam epitaxy at low substrate temperature T = 350 °C. Samples consist of layers (from 1 up to 10) of Ge0.96Sn0.04 self-assembled dots separated by Si spacer layers, 10 nm thick. Their structural analysis was performed based on transmission electron microscopy, atomic force microscopy and Raman scattering. We found that up to 4 stacks of dots could be grown with good dot layer homogeneity, making the GeSn dots interesting candidates for optoelectronic device applications.
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OBJECTIVE: To determine the most sensitive criterion for the detection of left ventricular hypertrophy according to echocardiographically defined left ventricular mass. METHODS: The Sokolow-Lyon voltage, Sokolow-Lyon-Rappaport, Cornell voltage duration product, White-Bock, and Romhilt-Estes point scoring criteria were compared with left ventricular mass index, corrected for body surface, obtained from the echocardiograms of 306 outpatients (176 females, 130 males), of all age groups. RESULTS: The Cornell voltage duration product criteria index had the greatest sensitivity in women (54.90%), and the Sokolow-Lyon-Rappaport index was most sensitive in men (73.53%). When applied to men at the same voltage amplitude (20mm) as that in women, the Cornell index showed increased sensitivity relative to the conventional index (28mm) of 67.65% (P<=0.01) and a sensitivity similar to that of the Sokolow-Lyon-Rappaport index, with higher specificity (P<=0.01). The White-Bock and Romhilt-Estes criteria were the least sensitive in men and women, despite their high specificity. The electrocardiographic criteria were more efficient when dilatation predominated over left ventricular hypertrophy. CONCLUSION: The Cornell index had greater sensitivity in women, and the Sokolow-Lyon-Rappaport index was more sensitive in men. When applied to men at the same voltage amplitude as that of women, the Cornell index had an increase in sensitivity similar to that of the Sokolow-Lyon-Rappaport index.
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Magdeburg, Univ., Fak. für Wirtschaftswiss., Diss., 2013
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Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2014
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Otto-von-Guericke-Universtität Magdeburg, Fakultät für Wirtschaftswissenschaft, Univ., Dissertation, 2015
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L’objectiu d’aquest estudi, que correspon a un projecte de recerca sobre la pèrdua funcional i la mortalitat de persones grans fràgils, és construir un procés de supervivència predictiu que tingui en compte l’evolució funcional i nutricional dels pacients al llarg del temps. En aquest estudi ens enfrontem a l’anàlisi de dades de supervivència i mesures repetides però els mètodes estadístics habituals per al tractament conjunt d’aquest tipus de dades no són apropiats en aquest cas. Com a alternativa utilitzem els models de supervivència multi-estats per avaluar l’associació entre mortalitat i recuperació, o no, dels nivells funcionals i nutricionals considerats normals. Després d’estimar el model i d’identificar els factors pronòstics de mortalitat és possible obtenir un procés predictiu que permet fer prediccions de la supervivència dels pacients en funció de la seva història concreta fins a un determinat moment. Això permet realitzar un pronòstic més precís de cada grup de pacients, la qual cosa pot ser molt útil per als professionals sanitaris a l’hora de prendre decisions clíniques.
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This paper presents an outline of rationale and theory of the MuSIASEM scheme (Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism). First, three points of the rationale behind our MuSIASEM scheme are discussed: (i) endosomatic and exosomatic metabolism in relation to Georgescu-Roegen’s flow-fund scheme; (2) the bioeconomic analogy of hypercycle and dissipative parts in ecosystems; (3) the dramatic reallocation of human time and land use patterns in various sectors of modern economy. Next, a flow-fund representation of the MUSIASEM scheme on three levels (the whole national level, the paid work sectors level, and the agricultural sector level) is illustrated to look at the structure of the human economy in relation to two primary factors: (i) human time - a fund; and (ii) exosomatic energy - a flow. The three levels representation uses extensive and intensive variables simultaneously. Key conceptual tools of the MuSIASEM scheme - mosaic effects and impredicative loop analysis - are explained using the three level flow-fund representation. Finally, we claim that the MuSIASEM scheme can be seen as a multi-purpose grammar useful to deal with sustainability issues.
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In this study we propose an application of the MuSIASEM approach which is used to provide an integrated analysis of Laos across different scales. With the term “integrated analysis across scales” we mean the generation of a series of packages of quantitative indicators, characterizing the performance of the socioeconomic activities performed in Laos when considering: (i) different hierarchical levels of organization (farming systems described at the level of household, rural villages, regions of Laos, the whole country level); and (ii) different dimensions of analysis (economic dimension, social dimension, ecological dimension, technical dimension). What is relevant in this application is that the information carried out by these different packages of indicators is integrated in a system of accounting which establishes interlinkages across these indicators. This is a essential feature to study sustainability trade-offs and to build more robust scenarios of possible changes. The multi-scale integrated representation presented in this study is based on secondary data (gathered in a three year EU project – SEAtrans and integrated by other available statistical sources) and it is integrated in GIS, when dealing with the spatial representation of Laos. However, even if we use data referring to Laos, the goal of this study is not that of providing useful information about a practical policy issue of Laos, but rather, to illustrate the possibility of using a multipurpose grammar to produce an integrated set of sustainability indicators at three different levels: (i) local; (ii) meso; (iii) macro level. The technical issue addressed is the simultaneous adoption of two multi-level matrices – one referring to a characterization of human activity over a set of different categories, and another referring to a characterization of land uses over the same set of categories. In this way, it becomes possible to explain the characteristics of Laos (an integrated set of indicators defining the performance of the whole country) in relation to the characteristics of the rural Laos and urban Laos. The characteristics of rural Laos, can be explained using the characteristics of three regions defined within Laos (Northern Laos, Central Laos and Southern Laos), which in turn can be defined (using an analogous package of indicators), starting from the characteristics of three main typologies of farming systems found in the regions.