995 resultados para Module Modeling


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The potential future distribution of four Mediterranean pines was aimed to be modeled supported by EUFORGEN digital area database (distribution maps), ESRI ArcGIS 10 software’s Spatial Analyst module (modeling environment), PAST (calibration of the model with statistical method), and REMO regional climate model (climatic data). The studied species were Pinus brutia, Pinus halepensis, Pinus pinaster, and Pinus pinea. The climate data were available in a 25 km resolution grid for the reference period (1961-90) and two future periods (2011-40, 2041-70). The climate model was based on the IPCC SRES A1B scenario. The model results show explicit shift of the distributions to the north in case of three of the four studied species. The future (2041-70) climate of Western Hungary seems to be suitable for Pinus pinaster.

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In the following paper a new class of executive information system is suggested. It is based on a selforganization in management and on a module modeling. The system is multifunctional and multidisciplinary. The structure elements of the system and the common features of the modules are discussed.

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The impact of climate change on the potential distribution of four Mediterranean pine species – Pinus brutia Ten., Pinus halepensis Mill., Pinus pinaster Aiton, and Pinus pinea L. – was studied by the Climate Envelope Model (CEM) to examine whether these species are suitable for the use as ornamental plants without frost protection in the Carpathian Basin. The model was supported by EUFORGEN digital area database (distribution maps), ESRI ArcGIS 10 software’s Spatial Analyst module (modeling environment), PAST (calibration of the model with statistical method), and REMO regional climate model (climatic data). The climate data were available in a 25 km resolution grid for the reference period (1961–1990) and two future periods (2011–2040, 2041–2070). The regional climate model was based on the IPCC SRES A1B scenario. While the potential distribution of P. brutia was not predicted to expand remarkably, an explicit shift of the distribution of the other three species was shown. Northwestern African distribution segments seem to become abandoned in the future. Current distribution of P. brutia may be highly endangered by the climate change. P. halepensis in the southern part and P. pinaster in the western part of the Carpathian Basin may find suitable climatic conditions in the period of 2041–2070.

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The future northward expansion of the arthropod vectors of leishmaniasis caused by climate change seems to be essential veterinary and medical problem. Our aim was to build and evaluate a Climate Envelope Model (CEM) to assess the potential effects of climate change on five European sandfly species. The studied species – Phlebotomus ariasi Tonn., P. neglectus Tonn., P. papatasi Scop., P. perfiliewi Parrot, P. perniciosus Newst., P. sergenti Parrot, P. similis Perfiliev, P. tobbi Adler, Theodor et Lourie – are important vectors of the parasite Leishmania infantum or other Leishmania species. The projections were based on REMO regional climate model with European domain. The climate data were available in a 25 km resolution grid for the reference period (1961-90) and two future periods (2011-40, 2041-70). The regional climate model was based on the IPCC SRES A1B scenario. Three types of climatic parameters were used for every month (averaged in the 30-years periods). The model was supported by VBORNET digital area database (distribution maps), ESRI ArcGIS 10 software’s Spatial Analyst module (modeling environment), PAST (calibration of the model with statistical method). Iterative model evaluation was done by summarizing two types of model errors based on an aggregated distribution. The results show that the best model results can be achieved by leaving 5-5 percentiles from the two extrema of the mean temperature, 2-2 percentiles from the two extrema of the minimum temperature, 0 percentile from the minimum of and 8 percentiles from the maximum of the precipitation.

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This paper presents a new approach to improving the effectiveness of autonomous systems that deal with dynamic environments. The basis of the approach is to find repeating patterns of behavior in the dynamic elements of the system, and then to use predictions of the repeating elements to better plan goal directed behavior. It is a layered approach involving classifying, modeling, predicting and exploiting. Classifying involves using observations to place the moving elements into previously defined classes. Modeling involves recording features of the behavior on a coarse grained grid. Exploitation is achieved by integrating predictions from the model into the behavior selection module to improve the utility of the robot's actions. This is in contrast to typical approaches that use the model to select between different strategies or plays. Three methods of adaptation to the dynamic features of the environment are explored. The effectiveness of each method is determined using statistical tests over a number of repeated experiments. The work is presented in the context of predicting opponent behavior in the highly dynamic and multi-agent robot soccer domain (RoboCup).

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This paper proposes an analytical Incident Traffic Management framework for freeway incident modeling and traffic re-routing. The proposed framework incorporates an econometric incident duration model and a traffic re-routing optimization module. The incident duration model is used to estimate the expected duration of the incident and thus determine the planning horizon for the re-routing module. The re-routing module is a CTM-based Single Destination System Optimal Dynamic Traffic Assignment model that generates optimal real-time strategies of re-routing freeway traffic to its adjacent arterial network during incidents. The proposed framework has been applied to a case study network including a freeway and its adjacent arterial network in South East Queensland, Australia. The results from different scenarios of freeway demand and incident blockage extent have been analyzed and advantages of the proposed framework are demonstrated.

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Visual tracking has been a challenging problem in computer vision over the decades. The applications of Visual Tracking are far-reaching, ranging from surveillance and monitoring to smart rooms. Mean-shift (MS) tracker, which gained more attention recently, is known for tracking objects in a cluttered environment and its low computational complexity. The major problem encountered in histogram-based MS is its inability to track rapidly moving objects. In order to track fast moving objects, we propose a new robust mean-shift tracker that uses both spatial similarity measure and color histogram-based similarity measure. The inability of MS tracker to handle large displacements is circumvented by the spatial similarity-based tracking module, which lacks robustness to object's appearance change. The performance of the proposed tracker is better than the individual trackers for tracking fast-moving objects with better accuracy.

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AIM: To investigate the interaction between human CCR5 receptors (CCR5) and HIV-1 envelope glycoprotein gp120 (HIV-1 gp120) and HIV-1 receptor CD4 antigens (CD4). METHODS: The structurally con served regions (SCR) of human CCR5 was built by the SYBYL/Biopolymer module using the corresponding transmembrane (TM) domain of bacteriorhodopsin (bR) as the template. The coordinates for amino-ter minal residue sequence, and carboxyl-terminal residue sequence, extracellular and cytoplasmic loops were generated using LOOP SEARCH algorithm. Subsequently the structural model was merged into the complex with HIV-1 gp120 and CD4. RESULTS: Human CCR5 interacted with both an HIV-1 gp120 and CD4. The N-terminal residues (especially Met1 and Gln4) of human CCR5, contacted with CD4 residues, mainly 7Nith one span (56 - 59) of CD4 in electrostatic interaction and hydrogen-bonds. The binding sites of human CCR5 were buried in a hydrophobic center surrounded by a highly basic periphery. On the other hand, direct interatomic contacts were made between ? CCR5 residues and 6 gp120 amino-acid residues, which included van der Waals contacts, hydrophobic interaction, and hydrogen bonds. CONCLUSION: The interaction model should be helpful for rational design of novel anti-HIV drugs.

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AMPS (Analysis of microelectronic and photonic structures) mode,which was developed by Pennsylvania State University, has been used to module the light J-V characteristics of a-Si solar cells with a structure of TCO/p-a-SiC:H/i-a-Si:H/n-a-Si:H/ metal. The effects of valence band offset and contact barriers at p/i and TOC/p, n/metal interfaces on the light J-V characteristics have been examined. The modeling has qualitatively categorized and explained the non-ideal J-V behaviors (rollover, crossover, Voc shift,and rollunder) observed in a-Si based solar cells.

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For the design of affinity membranes, protein adsorption in membrane affinity chromatography (MAC) was studied by frontal analysis. According to fast mass transfer, small thickness of affinity membranes and high affinity between the protein and the ligand, an ideal adsorption (IA) model was proposed for MAC and was used together with equilibrium-dispersive (E-D) model to describe the adsorption of bovine serum albumin (BSA) onto cellulose diacetate/polyethyleneimine (CA/PEI) blend membranes with and without Cu2+ chelating. E-D model was found to better describe the initial region of experimental breakthrough curves. The influence of axial dispersion was revealed and it showed the importance of design of the module to homogenously distribute feed solution. IA model was found to be better for the whole experimental breakthrough curve. According to it, the capacity of affinity membranes and the specificity of the interaction are of equal importance for the design of affinity membranes. An optimum feed concentration was also found in the operation of MAC. The discrepancy between experimental optimum feed concentrations and predicted ones from IA model may be due to the ignorance of some experimental effects such as axial dispersion.

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The future success of many electronics companies will depend to a large extent on their ability to initiate techniques that bring schedules, performance, tests, support, production, life-cycle-costs, reliability prediction and quality control into the earliest stages of the product creation process. Earlier papers have discussed the benefits of an integrated analysis environment for system-level thermal, stress and EMC prediction. This paper focuses on developments made to the stress analysis module and presents results obtained for an SMT resistor. Lifetime predictions are made using the Coffin-Manson equation. Comparison with the creep strain energy based models of Darveaux (1997) shows the shear strain based method to underestimate the solder joint life. Conclusions are also made about the capabilities of both approaches to predict the qualitative and quantitative impact of design changes.

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A numerical modeling method for the prediction of the lifetime of solder joints of relatively large solder area under cyclic thermal-mechanical loading conditions has been developed. The method is based on the Miner's linear damage accumulation rule and the properties of the accumulated plastic strain in front of the crack in large area solder joint. The nonlinear distribution of the damage indicator in the solder joints have been taken into account. The method has been used to calculate the lifetime of the solder interconnect in a power module under mixed cyclic loading conditions found in railway traction control applications. The results show that the solder thickness is a parameter that has a strong influence on the damage and therefore the lifetime of the solder joint while the substrate width and the thickness of the baseplate are much less important for the lifetime

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In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.

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La douleur est une expérience perceptive comportant de nombreuses dimensions. Ces dimensions de douleur sont inter-reliées et recrutent des réseaux neuronaux qui traitent les informations correspondantes. L’élucidation de l'architecture fonctionnelle qui supporte les différents aspects perceptifs de l'expérience est donc une étape fondamentale pour notre compréhension du rôle fonctionnel des différentes régions de la matrice cérébrale de la douleur dans les circuits corticaux qui sous tendent l'expérience subjective de la douleur. Parmi les diverses régions du cerveau impliquées dans le traitement de l'information nociceptive, le cortex somatosensoriel primaire et secondaire (S1 et S2) sont les principales régions généralement associées au traitement de l'aspect sensori-discriminatif de la douleur. Toutefois, l'organisation fonctionnelle dans ces régions somato-sensorielles n’est pas complètement claire et relativement peu d'études ont examiné directement l'intégration de l'information entre les régions somatiques sensorielles. Ainsi, plusieurs questions demeurent concernant la relation hiérarchique entre S1 et S2, ainsi que le rôle fonctionnel des connexions inter-hémisphériques des régions somatiques sensorielles homologues. De même, le traitement en série ou en parallèle au sein du système somatosensoriel constitue un autre élément de questionnement qui nécessite un examen plus approfondi. Le but de la présente étude était de tester un certain nombre d'hypothèses sur la causalité dans les interactions fonctionnelle entre S1 et S2, alors que les sujets recevaient des chocs électriques douloureux. Nous avons mis en place une méthode de modélisation de la connectivité, qui utilise une description de causalité de la dynamique du système, afin d'étudier les interactions entre les sites d'activation définie par un ensemble de données provenant d'une étude d'imagerie fonctionnelle. Notre paradigme est constitué de 3 session expérimentales en utilisant des chocs électriques à trois différents niveaux d’intensité, soit modérément douloureux (niveau 3), soit légèrement douloureux (niveau 2), soit complètement non douloureux (niveau 1). Par conséquent, notre paradigme nous a permis d'étudier comment l'intensité du stimulus est codé dans notre réseau d'intérêt, et comment la connectivité des différentes régions est modulée dans les conditions de stimulation différentes. Nos résultats sont en faveur du mode sériel de traitement de l’information somatosensorielle nociceptive avec un apport prédominant de la voie thalamocorticale vers S1 controlatérale au site de stimulation. Nos résultats impliquent que l'information se propage de S1 controlatéral à travers notre réseau d'intérêt composé des cortex S1 bilatéraux et S2. Notre analyse indique que la connexion S1→S2 est renforcée par la douleur, ce qui suggère que S2 est plus élevé dans la hiérarchie du traitement de la douleur que S1, conformément aux conclusions précédentes neurophysiologiques et de magnétoencéphalographie. Enfin, notre analyse fournit des preuves de l'entrée de l'information somatosensorielle dans l'hémisphère controlatéral au côté de stimulation, avec des connexions inter-hémisphériques responsable du transfert de l'information à l'hémisphère ipsilatéral.

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The 21st century has brought new challenges for forest management at a time when globalization in world trade is increasing and global climate change is becoming increasingly apparent. In addition to various goods and services like food, feed, timber or biofuels being provided to humans, forest ecosystems are a large store of terrestrial carbon and account for a major part of the carbon exchange between the atmosphere and the land surface. Depending on the stage of the ecosystems and/or management regimes, forests can be either sinks, or sources of carbon. At the global scale, rapid economic development and a growing world population have raised much concern over the use of natural resources, especially forest resources. The challenging question is how can the global demands for forest commodities be satisfied in an increasingly globalised economy, and where could they potentially be produced? For this purpose, wood demand estimates need to be integrated in a framework, which is able to adequately handle the competition for land between major land-use options such as residential land or agricultural land. This thesis is organised in accordance with the requirements to integrate the simulation of forest changes based on wood extraction in an existing framework for global land-use modelling called LandSHIFT. Accordingly, the following neuralgic points for research have been identified: (1) a review of existing global-scale economic forest sector models (2) simulation of global wood production under selected scenarios (3) simulation of global vegetation carbon yields and (4) the implementation of a land-use allocation procedure to simulate the impact of wood extraction on forest land-cover. Modelling the spatial dynamics of forests on the global scale requires two important inputs: (1) simulated long-term wood demand data to determine future roundwood harvests in each country and (2) the changes in the spatial distribution of woody biomass stocks to determine how much of the resource is available to satisfy the simulated wood demands. First, three global timber market models are reviewed and compared in order to select a suitable economic model to generate wood demand scenario data for the forest sector in LandSHIFT. The comparison indicates that the ‘Global Forest Products Model’ (GFPM) is most suitable for obtaining projections on future roundwood harvests for further study with the LandSHIFT forest sector. Accordingly, the GFPM is adapted and applied to simulate wood demands for the global forestry sector conditional on selected scenarios from the Millennium Ecosystem Assessment and the Global Environmental Outlook until 2050. Secondly, the Lund-Potsdam-Jena (LPJ) dynamic global vegetation model is utilized to simulate the change in potential vegetation carbon stocks for the forested locations in LandSHIFT. The LPJ data is used in collaboration with spatially explicit forest inventory data on aboveground biomass to allocate the demands for raw forest products and identify locations of deforestation. Using the previous results as an input, a methodology to simulate the spatial dynamics of forests based on wood extraction is developed within the LandSHIFT framework. The land-use allocation procedure specified in the module translates the country level demands for forest products into woody biomass requirements for forest areas, and allocates these on a five arc minute grid. In a first version, the model assumes only actual conditions through the entire study period and does not explicitly address forest age structure. Although the module is in a very preliminary stage of development, it already captures the effects of important drivers of land-use change like cropland and urban expansion. As a first plausibility test, the module performance is tested under three forest management scenarios. The module succeeds in responding to changing inputs in an expected and consistent manner. The entire methodology is applied in an exemplary scenario analysis for India. A couple of future research priorities need to be addressed, particularly the incorporation of plantation establishments; issue of age structure dynamics; as well as the implementation of a new technology change factor in the GFPM which can allow the specification of substituting raw wood products (especially fuelwood) by other non-wood products.