873 resultados para Multi-scale modeling


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Thesis (Ph.D.)--University of Washington, 2016-06

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The advantages of antennas that can resemble the shape of the body to which they are attached are obvious. However, electromagnetic modeling of such unusually shaped antennas can be difficult. In this paper, the commercially available software SolidWorks(TM) is used for accurately drawing complex shapes in conjunction with the electromagnetic software FEKO(TM) to model the EM behavior of conformal antennas. The application of SolidWorks and custom-written software allows all the required information that forms the analyzed structure to be automatically inserted into FEKO, and gives the user complete control over the antenna being modeled. This approach is illustrated by a number of simulation examples of single, wideband, multi-band planar and curved patch antennas.

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The reconstructed cellular metabolic network of Mus musculus, based on annotated genomic data, pathway databases, and currently available biochemical and physiological information, is presented. Although incomplete, it represents the first attempt to collect and characterize the metabolic network of a mammalian cell on the basis of genomic data. The reaction network is generic in nature and attempts to capture the carbon, energy, and nitrogen metabolism of the cell. The metabolic reactions were compartmentalized between the cytosol and the mitochondria, including transport reactions between the compartments and the extracellular medium. The reaction list consists of 872 internal metabolites involved in a total of 1220 reactions, whereof 473 relate to known open reading frames. Initial in silico analysis of the reconstructed model is presented.

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The purpose of this paper was to evaluate the psychometric properties of a stage-specific selfefficacy scale for physical activity with classical test theory (CTT), confirmatory factor analysis (CFA) and item response modeling (IRM). Women who enrolled in the Women On The Move study completed a 20-item stage-specific self-efficacy scale developed for this study [n = 226, 51.1% African-American and 48.9% Hispanic women, mean age = 49.2 (67.0) years, mean body mass index = 29.7 (66.4)]. Three analyses were conducted: (i) a CTT item analysis, (ii) a CFA to validate the factor structure and (iii) an IRM analysis. The CTT item analysis and the CFA results showed that the scale had high internal consistency (ranging from 0.76 to 0.93) and a strong factor structure. Results also showed that the scale could be improved by modifying or eliminating some of the existing items without significantly altering the content of the scale. The IRM results also showed that the scale had few items that targeted high self-efficacy and the stage-specific assumption underlying the scale was rejected. In addition, the IRM analyses found that the five-point response format functioned more like a four-point response format. Overall, employing multiple methods to assess the psychometric properties of the stage-specific self-efficacy scale demonstrated the complimentary nature of these methods and it highlighted the strengths and weaknesses of this scale.

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This study offers a new perspective on the nature, content and structure of perceived service quality. The Nordic and Gap schools of quality assessment are integrated with recent advances in the literature to develop and test a multidimensional, hierarchical scale. The scale provides a framework for assessing service quality within a high involvement, high contact, ongoing service environment. Empirical results indicated that service quality conforms to a multidimensional, hierarchical structure consisting of four primary dimensions, which in turn comprise nine sub-dimensions. The results obtained extend our understanding of service evaluation and have important implications for service providers seeking to improve the quality of the services they provide.

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In this paper, we present a new scheme for off-line recognition of multi-font numerals using the Takagi-Sugeno (TS) model. In this scheme, the binary image of a character is partitioned into a fixed number of sub-images called boxes. The features consist of normalized vector distances (gamma) from each box. Each feature extracted from different fonts gives rise to a fuzzy set. However, when we have a small number of fonts as in the case of multi-font numerals, the choice of a proper fuzzification function is crucial. Hence, we have devised a new fuzzification function involving parameters, which take account of the variations in the fuzzy sets. The new fuzzification function is employed in the TS model for the recognition of multi-font numerals.

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Sentiment analysis has long focused on binary classification of text as either positive or negative. There has been few work on mapping sentiments or emotions into multiple dimensions. This paper studies a Bayesian modeling approach to multi-class sentiment classification and multidimensional sentiment distributions prediction. It proposes effective mechanisms to incorporate supervised information such as labeled feature constraints and document-level sentiment distributions derived from the training data into model learning. We have evaluated our approach on the datasets collected from the confession section of the Experience Project website where people share their life experiences and personal stories. Our results show that using the latent representation of the training documents derived from our approach as features to build a maximum entropy classifier outperforms other approaches on multi-class sentiment classification. In the more difficult task of multi-dimensional sentiment distributions prediction, our approach gives superior performance compared to a few competitive baselines. © 2012 ACM.

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The number of interoperable research infrastructures has increased significantly with the growing awareness of the efforts made by the Global Earth Observation System of Systems (GEOSS). One of the Societal Benefit Areas (SBA) that is benefiting most from GEOSS is biodiversity, given the costs of monitoring the environment and managing complex information, from space observations to species records including their genetic characteristics. But GEOSS goes beyond simple data sharing to encourage the publishing and combination of models, an approach which can ease the handling of complex multi-disciplinary questions. It is the purpose of this paper to illustrate these concepts by presenting eHabitat, a basic Web Processing Service (WPS) for computing the likelihood of finding ecosystems with equal properties to those specified by a user. When chained with other services providing data on climate change, eHabitat can be used for ecological forecasting and becomes a useful tool for decision-makers assessing different strategies when selecting new areas to protect. eHabitat can use virtually any kind of thematic data that can be considered as useful when defining ecosystems and their future persistence under different climatic or development scenarios. The paper will present the architecture and illustrate the concepts through case studies which forecast the impact of climate change on protected areas or on the ecological niche of an African bird.

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Menorrhagia, or heavy menstrual bleeding (HMB), is a common gynaecological condition. As the aim of treatment is to improve women's wellbeing and quality of life (QoL), it is necessary to have effective ways to measure this. This study investigated the reliability and validity of the menorrhagia multi-attribute scale (MMAS), a menorrhagia-specific QoL instrument. Participants (n = 431) completed the MMAS and a battery of other tests as part of the baseline assessment of the ECLIPSE (Effectiveness and Cost-effectiveness of Levonorgestrel-containing Intrauterine system in Primary care against Standard trEatment for menorrhagia) trial. Analyses of their responses suggest that the MMAS has good measurement properties and is therefore an appropriate condition-specific instrument to measure the outcome of treatment for HMB. © 2011 The Authors BJOG An International Journal of Obstetrics and Gynaecology © 2011 RCOG.

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A new generation of surface plasmonic optical fibre sensors is fabricated using multiple coatings deposited on a lapped section of a single mode fibre. Post-deposition UV laser irradiation using a phase mask produces a nano-scaled surface relief grating structure, resembling nano-wires. The overall length of the individual corrugations is approximately 14 μm with an average full width half maximum of 100 nm. Evidence is presented to show that these surface structures result from material compaction created by the silicon dioxide and germanium layers in the multi-layered coating and the surface topology is capable of supporting localised surface plasmons. The coating compaction induces a strain gradient into the D-shaped optical fibre that generates an asymmetric periodic refractive index profile which enhances the coupling of the light from the core of the fibre to plasmons on the surface of the coating. Experimental data are presented that show changes in spectral characteristics after UV processing and that the performance of the sensors increases from that of their pre-UV irradiation state. The enhanced performance is illustrated with regards to change in external refractive index and demonstrates high spectral sensitivities in gaseous and aqueous index regimes ranging up to 4000 nm/RIU for wavelength and 800 dB/RIU for intensity. The devices generate surface plasmons over a very large wavelength range, (visible to 2 μm) depending on the polarization state of the illuminating light. © 2013 SPIE.

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Novel surface plasmonic optical fiber sensors have been fabricated using multiple coatings deposited on a lapped section of a single mode fiber. UV laser irradiation processing with a phase mask produces a nano-scaled surface relief grating structure resembling nano-wires. The resulting individual corrugations produced by material compaction are approximately 20 μm long with an average width at half maximum of 100 nm and generate localized surface plasmons. Experimental data are presented that show changes in the spectral characteristics after UV processing, coupled with an overall increase in the sensitivity of the devices to surrounding refractive index. Evidence is presented that there is an optimum UV dosage (48 joules) over which no significant additional optical change is observed. The devices are characterized with regards to change in refractive index, where significantly high spectral sensitivities in the aqueous index regime are found, ranging up to 4000 nm/RIU for wavelength and 800 dB/RIU for intensity. © 2013 Optical Society of America.

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Decision making and technical decision analysis demand computer-aided techniques and therefore more and more support by formal techniques. In recent years fuzzy decision analysis and related techniques gained importance as an efficient method for planning and optimization applications in fields like production planning, financial and economical modeling and forecasting or classification. It is also known, that the hierarchical modeling of the situation is one of the most popular modeling method. It is shown, how to use the fuzzy hierarchical model in complex with other methods of Multiple Criteria Decision Making. We propose a novel approach to overcome the inherent limitations of Hierarchical Methods by exploiting multiple criteria decision making.