960 resultados para Unités évolutives significatives
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Architecture and learning algorithm of self-learning spiking neural network in fuzzy clustering task are outlined. Fuzzy receptive neurons for pulse-position transformation of input data are considered. It is proposed to treat a spiking neural network in terms of classical automatic control theory apparatus based on the Laplace transform. It is shown that synapse functioning can be easily modeled by a second order damped response unit. Spiking neuron soma is presented as a threshold detection unit. Thus, the proposed fuzzy spiking neural network is an analog-digital nonlinear pulse-position dynamic system. It is demonstrated how fuzzy probabilistic and possibilistic clustering approaches can be implemented on the base of the presented spiking neural network.
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One of the major challenges in measuring efficiency in terms of resources and outcomes is the assessment of the evolution of units over time. Although Data Envelopment Analysis (DEA) has been applied for time series datasets, DEA models, by construction, form the reference set for inefficient units (lambda values) based on their distance from the efficient frontier, that is, in a spatial manner. However, when dealing with temporal datasets, the proximity in time between units should also be taken into account, since it reflects the structural resemblance among time periods of a unit that evolves. In this paper, we propose a two-stage spatiotemporal DEA approach, which captures both the spatial and temporal dimension through a multi-objective programming model. In the first stage, DEA is solved iteratively extracting for each unit only previous DMUs as peers in its reference set. In the second stage, the lambda values derived from the first stage are fed to a Multiobjective Mixed Integer Linear Programming model, which filters peers in the reference set based on weights assigned to the spatial and temporal dimension. The approach is demonstrated on a real-world example drawn from software development.
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2000 Mathematics Subject Classification: 20C05, 16U60, 16S84, 15A33.
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Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2016
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A cikkben paneladatok segítségével a magyar gabonatermesztő üzemek 2001 és 2009 közötti technikai hatékonyságát vizsgáljuk. A technikai hatékonyság szintjének becslésére egy hagyományos sztochasztikus határok modell (SFA) mellett a látens csoportok modelljét (LCM) használjuk, amely figyelembe veszi a technológiai különbségeket is. Eredményeink arra utalnak, hogy a technológiai heterogenitás fontos lehet egy olyan ágazatban is, mint a szántóföldi növénytermesztés, ahol viszonylag homogén technológiát alkalmaznak. A hagyományos, azonos technológiát feltételező és a látens osztályok modelljeinek összehasonlítása azt mutatja, hogy a gabonatermesztő üzemek technikai hatékonyságát a hagyományos modellek alábecsülhetik. _____ The article sets out to analyse the technical efficiency of Hungarian crop farms between 2001 and 2009, using panel data and employing both standard stochastic frontier analysis and the latent class model (LCM) to estimate technical efficiency. The findings suggest that technological heterogeneity plays an important role in the crop sector, though it is traditionally assumed to employ homogenous technology. A comparison of standard SFA models that assumes the technology is common to all farms and LCM estimates highlights the way the efficiency of crop farms can be underestimated using traditional SFA models.
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Regional climate models (RCMs) provide reliable climatic predictions for the next 90 years with high horizontal and temporal resolution. In the 21st century northward latitudinal and upward altitudinal shift of the distribution of plant species and phytogeographical units is expected. It is discussed how the modeling of phytogeographical unit can be reduced to modeling plant distributions. Predicted shift of the Moesz line is studied as case study (with three different modeling approaches) using 36 parameters of REMO regional climate data-set, ArcGIS geographic information software, and periods of 1961-1990 (reference period), 2011-2040, and 2041-2070. The disadvantages of this relatively simple climate envelope modeling (CEM) approach are then discussed and several ways of model improvement are suggested. Some statistical and artificial intelligence (AI) methods (logistic regression, cluster analysis and other clustering methods, decision tree, evolutionary algorithm, artificial neural network) are able to provide development of the model. Among them artificial neural networks (ANN) seems to be the most suitable algorithm for this purpose, which provides a black box method for distribution modeling.
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The purpose of this study was to determine the emergency department (ED) length of stay (LOS) of patients admitted to inpatient telemetry and critical care units and to identify the factors that contribute to a prolonged ED LOS. It also examined whether there was a difference in ED LOS between clients evaluated by an ED physician, an Advanced Registered Nurse Practitioner (ARNP) or a Physician's Assistant (PA).^ A data collection tool was devised and used to record data obtained by retrospectively reviewing 110 charts of patients from this sample. The mean ED LOS was 286.75 minutes. Multiple factors were recorded as affecting the ED LOS of this sample, including: age, diagnosis, consultations, multiple radiographs, pending admission orders, nurse unable to call report/busy, relatives at bedside, observation or stabilization necessary, bed not ready and infusion in progress. No significant difference in ED LOS was noted between subjects initially evaluated by a physician, an ARNP or a PA. ^
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Requirements for space based monitoring of permafrost features had been already defined within the IGOS Cryosphere Theme Report at the start of the IPY in 2007 (IGOS, 2007). The WMO Polar Space Task Group (PSTG, http://www.wmo.int/pages/prog/sat/pstg_en.php) identified the need to review the requirements for permafrost monitoring and to update these requirements in 2013. Relevant surveys with focus on satellite data are already available from the ESA DUE Permafrost User requirements survey (2009), the United States National Research Council (2014) and the ESA - CliC - IPA - GTN -P workshop in February 2014. These reports have been reviewed and specific needs discussed within the community and a white paper submitted to the WMO PSTG. Acquisition requirements for monitoring of especially terrain changes (incl. rock glaciers and coastal erosion) and lakes (extent, ice properties etc.) with respect to current satellite missions have been specified. About 50 locations ('cold spots') where permafrost (Arctic and Antarctic) in situ monitoring has been taking place for many years or where field stations are currently established have been identified. These sites have been proposed to the WMO Polar Space Task Group as focus areas for future monitoring by high resolution satellite data. The specifications of these sites including meta-data on site instrumentation have been published as supplement to the white paper (Bartsch et al. 2014, doi:10.1594/PANGAEA.847003). The representativity of the 'cold spots' around the arctic has been in the following assessed based on a landscape units product which has been developed as part of the FP7 project PAGE21. The ESA DUE Permafrost service has been utilized to produce a pan-arctic database (25km, 2000-2014) comprising Mean Annual Surface Temperature, Annual and summer Amplitude of Surface Temperature, Mean Summer (July-August) Surface Temperature. Surface status (frozen/unfrozen) related products have been also derived from the ESA DUE Permafrost service. This includes the length of unfrozen period, first unfrozen day and first frozen day. In addition, SAR (ENVISAT ASAR GM) statistics as well as topographic parameters have been considered. The circumpolar datasets have been assessed for their redundancy in information content. 12 distinct units could be derived. The landscape units reveal similarities between North Slope Alaska and the region from the Yamal Peninsula to the Yenisei estuary. Northern Canada is characterized by the same landscape units like western Siberia. North-eastern Canada shows similarities to the Laptev coast region. This paper presents the result of this assessment and formulates recommendations for extensions of the in situ monitoring networks and categorizes the sites by satellite data requirements (specifically Sentinels) with respect to the landscape type and related processes.
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Acknowledgments We thank Edoardo Del Pezzo, Ludovic Margerin, Haruo Sato, Mare Yamamoto, Tatsuhiko Saito, Malcolm Hole, and Seth Moran for the valuable suggestions regarding the methodology and interpretation. Greg Waite provided the P wave velocity model of MSH. An important revision of the methods was done after two blind reviews performed before submission. The suggestions of two anonymous reviewers greatly enhanced our ability of imaging structures, interpreting our results, and testing their reliability. The facilities of the IRIS Data Management System, and specifically the IRIS Data Management Center, were used for access to waveform and metadata required in this study, and provided by the Cascades Volcano Observatory – USGS. Interaction with geologists and geographers part of the Landscape Dynamics Theme of the Scottish Alliance for Geoscience, Environment and Society (SAGES) has been important for the interpretation of the results.
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Funding was provided by the Leibniz Association (SAW-2012-IGB 4167) within the International Leibniz Graduate School: Aquatic boundaries and linkages- Aqualink. We would like to thank the NRI staff for their help during field work.
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Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.