38 resultados para IMAGE PATTERN CLASSIFICATION
em Instituto Politécnico do Porto, Portugal
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O documento em anexo encontra-se na versão post-print (versão corrigida pelo editor).
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In the present paper we assess the performance of information-theoretic inspired risks functionals in multilayer perceptrons with reference to the two most popular ones, Mean Square Error and Cross-Entropy. The information-theoretic inspired risks, recently proposed, are: HS and HR2 are, respectively, the Shannon and quadratic Rényi entropies of the error; ZED is a risk reflecting the error density at zero errors; EXP is a generalized exponential risk, able to mimic a wide variety of risk functionals, including the information-thoeretic ones. The experiments were carried out with multilayer perceptrons on 35 public real-world datasets. All experiments were performed according to the same protocol. The statistical tests applied to the experimental results showed that the ubiquitous mean square error was the less interesting risk functional to be used by multilayer perceptrons. Namely, mean square error never achieved a significantly better classification performance than competing risks. Cross-entropy and EXP were the risks found by several tests to be significantly better than their competitors. Counts of significantly better and worse risks have also shown the usefulness of HS and HR2 for some datasets.
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Recently, companies developed strategies which may influence their Corporate Social Responsibility (CSR) image. This paper discusses the image of four different supermarkets with stores in Portugal. The research compares CSR image and brand attitude of the four supermarkets. Empirical evidence shows that different supermarkets belonging to the same company have different CSR image and brand attitude. The research also confirms that there is positive correlation between CSR image and attitude towards the brand. Further, the results offer empirical evidence that CSR image and brand attitude influence purchase intention of supermarket brands. Finally, brand purchase intention is highly influenced by attitude towards the brand than CSR image.
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O documento em anexo encontra-se na versão post-print (versão corrigida pelo editor).
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This paper describes a methodology that was developed for the classification of Medium Voltage (MV) electricity customers. Starting from a sample of data bases, resulting from a monitoring campaign, Data Mining (DM) techniques are used in order to discover a set of a MV consumer typical load profile and, therefore, to extract knowledge regarding to the electric energy consumption patterns. In first stage, it was applied several hierarchical clustering algorithms and compared the clustering performance among them using adequacy measures. In second stage, a classification model was developed in order to allow classifying new consumers in one of the obtained clusters that had resulted from the previously process. Finally, the interpretation of the discovered knowledge are presented and discussed.
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The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.
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Mestrado em Engenharia Electrotécnica e de Computadores
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Mestrado em Engenharia Geotécnica e Geoambiente
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Introduction: Image resizing is a normal feature incorporated into the Nuclear Medicine digital imaging. Upsampling is done by manufacturers to adequately fit more the acquired images on the display screen and it is applied when there is a need to increase - or decrease - the total number of pixels. This paper pretends to compare the “hqnx” and the “nxSaI” magnification algorithms with two interpolation algorithms – “nearest neighbor” and “bicubic interpolation” – in the image upsampling operations. Material and Methods: Three distinct Nuclear Medicine images were enlarged 2 and 4 times with the different digital image resizing algorithms (nearest neighbor, bicubic interpolation nxSaI and hqnx). To evaluate the pixel’s changes between the different output images, 3D whole image plot profiles and surface plots were used as an addition to the visual approach in the 4x upsampled images. Results: In the 2x enlarged images the visual differences were not so noteworthy. Although, it was clearly noticed that bicubic interpolation presented the best results. In the 4x enlarged images the differences were significant, with the bicubic interpolated images presenting the best results. Hqnx resized images presented better quality than 4xSaI and nearest neighbor interpolated images, however, its intense “halo effect” affects greatly the definition and boundaries of the image contents. Conclusion: The hqnx and the nxSaI algorithms were designed for images with clear edges and so its use in Nuclear Medicine images is obviously inadequate. Bicubic interpolation seems, from the algorithms studied, the most suitable and its each day wider applications seem to show it, being assumed as a multi-image type efficient algorithm.
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Purpose: To describe and compare the content of instruments that assess environmental factors using the International Classification of Functioning, Disability and Health (ICF). Methods: A systematic search of PubMed, CINAHL and PEDro databases was conducted using a pre-determined search strategy. The identified instruments were screened independently by two investigators, and meaningful concepts were linked to the most precise ICF category according to published linking rules. Results: Six instruments were included, containing 526 meaningful concepts. Instruments had between 20% and 98% of items linked to categories in Chapter 1. The highest percentage of items from one instrument linked to categories in Chapters 2–5 varied between 9% and 50%. The presence or absence of environmental factors in a specific context is assessed in 3 instruments, while the other 3 assess the intensity of the impact of environmental factors. Discussion: Instruments differ in their content, type of assessment, and have several items linked to the same ICF category. Most instruments primarily assess products and technology (Chapter 1), highlighting the need to deepen the discussion on the theory that supports the measurement of environmental factors. This discussion should be thorough and lead to the development of methodologies and new tools that capture the underlying concepts of the ICF.
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A Sequência de Movimento de Sentado para de Pé (SMSP) é um marco importante na independência funcional da criança, sendo a sua qualidade afetada em casos de alteração do controlo postural do tronco. É por isso motivo de especial foco neste estudo, como elemento avaliativo e interventivo. Este estudo tem como objetivo a análise da modificação de componentes motores relacionados com o controlo postural, durante a SMSP, em 5 crianças com alterações neuromotoras, face à aplicação de um programa de intervenção baseado no Tratamento de Neuro Desenvolvimento (TND). Foi para tal utilizada a análise cinemática da SMSP - nomeadamente as variáveis “variação do deslocamento dos segmentos cabeça e tronco” e “variação do ângulo perna-pé” entre o momento inicial e o seat-off – complementada com a aplicação do Teste de Medida da Função Motora 88 (TMFM-88) e a Classificação Internacional da Funcionalidade Incapacidade e Saúde-Versão Crianças e Jovens (CIF-CJ), bem como a avaliação de componentes de movimento com recurso a registo de imagem. A análise cinemática demonstrou uma diminuição do deslocamento dos segmentos cabeça e tronco na maioria dos casos, bem como uma maior mobilidade da tíbia sobre pé. Verificou-se um aumento do score final do TMFM-88, em todos os casos. A CIF-CJ não evidenciou alterações entre o início e o término do período de intervenção. O registo de imagem demonstrou alterações positivas visíveis no alinhamento de segmentos, nível de atividade, controlo postural, e recurso a estratégias compensatórias no conjunto postural sentado e na SMSP. Após o período de intervenção as crianças deste estudo evidenciaram modificações positivas nas variáveis em estudo, nomeadamente 1) diminuição do deslocamento dos segmentos cabeça e tronco na fase inicial da SMSP, 2) aumento da variação do ângulo perna-pé na fase inicial da SMSP, 3) aumento do score total da TMFM-88, 4) alteração positiva dos componentes de movimento alinhamento de segmentos e nível de atividade e 5) redução do recurso a estratégias compensatórias de movimento na SMSP. Estas modificações sugerem um controlo postural mais eficiente.
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A Realidade Aumentada veio alterar a percepção que o ser humano tem do mundo real. A expansão da nossa realidade à Realidade Virtual possibilita a criação de novas experiencias, cuja aplicabilidade é já tida como natural em diversas situações. No entanto, potenciar este tipo de interacção pode ser um processo complexo, quer por limitações tecnológicas, quer pela gestão dos recursos envolvidos. O desenvolvimento de projectos com realidade aumentada para fins comerciais passa assim muitas vezes pela optimização dos recursos utilizados tendo em consideração as limitações das tecnologias envolventes (sistemas de detecção de movimento e voz, detecção de padrões, GPS, análise de imagens, sensores biométricos, etc.). Com a vulgarização e aceitação das técnicas de Realidade Aumentada em muitas áreas (medicina, educação, lazer, etc.), torna-se também necessário que estas técnicas sejam transversais aos dispositivos que utilizamos diariamente (computadores, tablets, telemóveis etc.). Um dominador comum entre estes dispositivos é a internet uma vez que as aplicações online conseguem abarcar um maior número de pessoas. O objectivo deste projecto era o de criar uma aplicação web com técnicas de Realidade Aumentada e cujos conteúdos fossem geridos pelos utilizadores. O processo de investigação e desenvolvimento deste trabalho passou assim por uma fase fundamental de prototipagem para seleccionar as tecnologias que melhor se enquadravam no tipo de arquitectura pretendida para a aplicação e nas ferramentas de desenvolvimento utilizadas pela empresa onde o projecto foi desenvolvido. A aplicação final é composta por um FrontOffice, responsável por mostrar e interpretar as aplicações criadas e possibilitar a integração com outras aplicações, e um BackOffice que possibilita aos utilizadores, sem conhecimentos de programação, criar novas aplicações de realidade aumentada e gerir os conteúdos multimédia utilizados. A aplicação desenvolvida pode servir de base para outras aplicações e ser reutilizável noutros âmbitos, sempre com o objectivo de reduzir custos de desenvolvimento e de gestão de conteúdos, proporcionando assim a implementação de uma Framework que permite a gestão de conteúdos em diferentes áreas (medicina, educação, lazer, etc.), onde os utilizadores podem criar as suas próprias aplicações, jogos e ferramentas de trabalho. No decorrer do projecto, a aplicação foi validada por especialistas garantindo o cumprimento dos objectivos propostos.
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Background and aim: Cardiorespiratory fitness (CRF) and diet have been involved as significant factors towards the prevention of cardio-metabolic diseases. This study aimed to assess the impact of the combined associations of CRF and adherence to the Southern European Atlantic Diet (SEADiet) on the clustering of metabolic risk factors in adolescents. Methods and Results: A cross-sectional school-based study was conducted on 468 adolescents aged 15-18, from the Azorean Islands, Portugal. We measured fasting glucose, insulin, total cholesterol (TC), HDL-cholesterol, triglycerides, systolic blood pressure, waits circumference and height. HOMA, TC/HDL-C ratio and waist-to-height ratio were calculated. For each of these variables, a Z-score was computed by age and sex. A metabolic risk score (MRS) was constructed by summing the Z scores of all individual risk factors. High risk was considered when the individual had 1SD of this score. CRF was measured with the 20 m-Shuttle-Run- Test. Adherence to SEADiet was assessed with a semi-quantitative food frequency questionnaire. Logistic regression showed that, after adjusting for potential confounders, unfit adolescents with low adherence to SEADiet had the highest odds of having MRS (OR Z 9.4; 95%CI:2.6e33.3) followed by the unfit ones with high adherence to the SEADiet (OR Z 6.6; 95% CI: 1.9e22.5) when compared to those who were fit and had higher adherence to SEADiet.
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The goal of this study is to analyze the dynamical properties of financial data series from nineteen worldwide stock market indices (SMI) during the period 1995–2009. SMI reveal a complex behavior that can be explored since it is available a considerable volume of data. In this paper is applied the window Fourier transform and methods of fractional calculus. The results reveal classification patterns typical of fractional order systems.
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Wireless Sensor Networks (WSNs) are increasingly used in various application domains like home-automation, agriculture, industries and infrastructure monitoring. As applications tend to leverage larger geographical deployments of sensor networks, the availability of an intuitive and user friendly programming abstraction becomes a crucial factor in enabling faster and more efficient development, and reprogramming of applications. We propose a programming pattern named sMapReduce, inspired by the Google MapReduce framework, for mapping application behaviors on to a sensor network and enabling complex data aggregation. The proposed pattern requires a user to create a network-level application in two functions: sMap and Reduce, in order to abstract away from the low-level details without sacrificing the control to develop complex logic. Such a two-fold division of programming logic is a natural-fit to typical sensor networking operation which makes sensing and topological modalities accessible to the user.