Sensing Cloud Optimization to Solve ED of Units with Valve-Point Effects and Multi-fuels

In this paper a solution to an highly constrained and non-convex economical dispatch (ED) problem with a meta-heuristic technique named Sensing Cloud Optimization (SCO) is presented. The proposed meta-heuristic is based on a cloud of particles whose central point represents the objective function value and the remaining particles act as sensors "to fill" the search space and "guide" the central particle so it moves into the best direction. To demonstrate its performance, a case study with multi-fuel units and valve- point effects is presented.

Estudo exploratório dos comportamentos interativos mãe – filho(a) e pai – filho(a) aos 15 meses de vida.

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção do grau de Mestre em Intervenção Precoce

Modelo de data mining para deteção de embolias pulmonares

Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Informática e de Computadores

Publicidade interactiva na televisão em Portugal e no mundo

Num contexto de mudança a nível de hábitos sociais em que impera a necessidade de comunicar de uma forma mais natural e instantânea quanto possível, o cada vez mais informado e exigente consumidor tem vindo a adquirir um papel mais participativo na comunicação e construção das marcas. Se outrora assistíamos passivamente a uma comunicação unidirecional e desprovida de interactividade, hoje impera a possibilidade de podermos manipular ou construir conteúdos de acordo com as nossas necessidades e preferências individuais. Neste contexto, a comunicação nos novos meios tecnológicos tem procurado responder à dispersão de atenção por parte do consumidor, que se socorre simultaneamente de diversos ecrãs. Porém, no ecrã em que o novo consumidor mais despende o seu tempo, e com o qual ainda se sente mais à vontade, a televisão, a comunicação interactiva ainda se encontra pouca explorada. Para os profissionais de publicidade, e sobretudo para os anunciantes, o conceito de publicidade interactiva, quando inserida no meio televisivo, é deveras recente, carecendo de um maior aprofundamento teórico e empírico. Tendo em vista este aprofundamento, o objectivo geral deste trabalho consiste na caracterização do panorama da publicidade interactiva na televisão em Portugal tendo como termo de comparação o estrangeiro. A dissertação assumiu a forma de um estudo exploratório e misto sequencial, desenvolvido com base na análise de conteúdo de um conjunto de casos nacionais de Publicidade Interactiva na Televisão fornecidos pelo MEO e de casos estrangeiros publicados na Internet. Assentando a análise numa grelha própria, procurou caracterizar-se o panorama actual da Publicidade Interactiva na Televisão nacional tendo como termo de comparação o que se passa lá fora, do ponto de vista dos conteúdos, da partilha destes, da dependência de um second screen e dos objectivos subjacentes aos anúncios. Foi possível concluir com este estudo que, apesar de a Publicidade Interactiva na Televisão se encontrar mais desenvolvida no estrangeiro, em Portugal observaram-se características singulares e positivas, o que aponta que nos encontramos a evoluir a passos largos para alcançar melhores experiências interactivas.

Espetroscopia (1H) por ressonância magnética do disco intervertebral lombar no adulto e sua aplicação na rotina imagiológica

Objetivos – Demonstrar o potencial da espetroscopia (1H) por ressonância magnética na doença degenerativa discal lombar e defender a integração desta técnica na rotina clínico‑imagiológica para a precisa classificação da involução vs degenerescência dos discos L4‑L5 e L5‑S1 em doentes com lombalgia não relacionável com causa mecânica. Material e métodos – O estudo incluiu 102 discos intervertebrais lombares de 123 doentes. Foram estudados 61 discos de L4‑L5, 41 discos de L5‑S1 e 34 discos de D12‑L1. Utilizou‑se um sistema de ressonância magnética de 1,5 T e técnica monovoxel. Obtiveram‑se os rácios [Lac/Nacetyl] e [Nacetyl/(Lac+Lípidos)] e aplicou‑se a ressonância de lípidos para avaliar a bioquímica do disco com o fim de conhecer o estado de involução vs degenerescência que o suscetibilizam para a instabilidade e sobrecarga. Avaliou‑se o comportamento dos rácios e do teor lipídico dos discos L4‑L5‑S1 e as diferenças apresentadas em relação a D12‑L1. Foi também realizada a comparação entre os discos L4‑L5, L5‑S1 e D12‑L1 na ponderação T2 (T2W), segundo a classificação ajustada (1‑4) de Pfirrmann. Resultados – Verificou‑se que os rácios e o valor dos lípidos dos discos L4‑L5‑S1 apresentaram diferenças estatisticamente significativas quando relacionados com os discos D12‑L1. O rácio [Lac/Nacetyl] em L4‑L5‑S1 mostrou‑se aumentado em relação a D12‑L1 (p=0,033 para os discos com grau de involução [1+2] e p=0,004 para os discos com grau [3+4]). Estes resultados sugerem que a involução vs degenerescência dos discos nos graus mais elevados condiciona um decréscimo do pico do Lactato. O rácio [Nacetyl/(Lac+Lip)] discrimina os graus de involução [1+2] do [3+4] no nível L4‑L5, apresentando os valores dos rácios (média 0,65 e 0,5 respetivamente com p=0,04). O rácio médio de [Nacetyl/(Lac+Lip)] dos discos L4‑L5 foi 1,8 vezes mais elevado do que em D12‑L1. O espetro lipídico em L4‑L5‑S1 nos graus mais elevados não mostrou ter uma prevalência constante quanto às frequências de ressonância. Conclusão – A espetroscopia (1H) dos discos intervertebrais poderá ter aplicação na discriminação dos graus de involução vs degenerescência e representar um contributo semiológico importante em suplemento à ponderação T2 convencional. As ressonâncias de lípidos dos discos L4‑L5 e L5‑S1, involuídos ou degenerados, devem ser avaliadas em relação a D12‑L1, utilizando este valor como referência, pois este último é o nível considerado estável e com baixa probabilidade de degenerescência.

Feature selection for clustering categorical data with an embedded modelling approach

Research on the problem of feature selection for clustering continues to develop. This is a challenging task, mainly due to the absence of class labels to guide the search for relevant features. Categorical feature selection for clustering has rarely been addressed in the literature, with most of the proposed approaches having focused on numerical data. In this work, we propose an approach to simultaneously cluster categorical data and select a subset of relevant features. Our approach is based on a modification of a finite mixture model (of multinomial distributions), where a set of latent variables indicate the relevance of each feature. To estimate the model parameters, we implement a variant of the expectation-maximization algorithm that simultaneously selects the subset of relevant features, using a minimum message length criterion. The proposed approach compares favourably with two baseline methods: a filter based on an entropy measure and a wrapper based on mutual information. The results obtained on synthetic data illustrate the ability of the proposed expectation-maximization method to recover ground truth. An application to real data, referred to official statistics, shows its usefulness.

Fuzzy clustering applied to a demand response model in a smart grid contingency scenario

This paper focus on a demand response model analysis in a smart grid context considering a contingency scenario. A fuzzy clustering technique is applied on the developed demand response model and an analysis is performed for the contingency scenario. Model considerations and architecture are described. The demand response developed model aims to support consumers decisions regarding their consumption needs and possible economic benefits.

ECG Biometrics: A Template Selection Approach

Electrocardiography (ECG) biometrics is emerging as a viable biometric trait. Recent developments at the sensor level have shown the feasibility of performing signal acquisition at the fingers and hand palms, using one-lead sensor technology and dry electrodes. These new locations lead to ECG signals with lower signal to noise ratio and more prone to noise artifacts; the heart rate variability is another of the major challenges of this biometric trait. In this paper we propose a novel approach to ECG biometrics, with the purpose of reducing the computational complexity and increasing the robustness of the recognition process enabling the fusion of information across sessions. Our approach is based on clustering, grouping individual heartbeats based on their morphology. We study several methods to perform automatic template selection and account for variations observed in a person's biometric data. This approach allows the identification of different template groupings, taking into account the heart rate variability, and the removal of outliers due to noise artifacts. Experimental evaluation on real world data demonstrates the advantages of our approach.

Efficient Implementation Of A Single-Precision Floating-Point Arithmetic Unit on FPGA

This paper presents a single precision floating point arithmetic unit with support for multiplication, addition, fused multiply-add, reciprocal, square-root and inverse squareroot with high-performance and low resource usage. The design uses a piecewise 2nd order polynomial approximation to implement reciprocal, square-root and inverse square-root. The unit can be configured with any number of operations and is capable to calculate any function with a throughput of one operation per cycle. The floatingpoint multiplier of the unit is also used to implement the polynomial approximation and the fused multiply-add operation. We have compared our implementation with other state-of-the-art proposals, including the Xilinx Core-Gen operators, and conclude that the approach has a high relative performance/area efficiency. © 2014 Technical University of Munich (TUM).

Enhancing Multimodal Silent Speech Interfaces With Feature Selection

In research on Silent Speech Interfaces (SSI), different sources of information (modalities) have been combined, aiming at obtaining better performance than the individual modalities. However, when combining these modalities, the dimensionality of the feature space rapidly increases, yielding the well-known "curse of dimensionality". As a consequence, in order to extract useful information from this data, one has to resort to feature selection (FS) techniques to lower the dimensionality of the learning space. In this paper, we assess the impact of FS techniques for silent speech data, in a dataset with 4 non-invasive and promising modalities, namely: video, depth, ultrasonic Doppler sensing, and surface electromyography. We consider two supervised (mutual information and Fisher's ratio) and two unsupervised (meanmedian and arithmetic mean geometric mean) FS filters. The evaluation was made by assessing the classification accuracy (word recognition error) of three well-known classifiers (knearest neighbors, support vector machines, and dynamic time warping). The key results of this study show that both unsupervised and supervised FS techniques improve on the classification accuracy on both individual and combined modalities. For instance, on the video component, we attain relative performance gains of 36.2% in error rates. FS is also useful as pre-processing for feature fusion. Copyright © 2014 ISCA.

A simulation of integrated photovoltaic conversion into electric grid

This paper presents a systemic modeling for a PV system integrated into an electric grid. The modeling includes models for a DC-DC boost converter and a DC-AC two-level inverter. Classical or fuzzy PI controllers with pulse width modulation by space vector modulation associated with sliding mode control is used for controlling the PV system and power factor control is introduced at the output of the system. Comprehensive performance simulation studies are carried out with the modeling of the DC-DC boost converter followed by a two-level power inverter in order to compare the performance with the experimental results obtained during in situ operation with three commercial inverters. Also, studies are carried out to assess the quality of the energy injected into the electric grid in terms of harmonic distortion. Finally, conclusions regarding the integration of the PV system into the electric grid are presented. (C) 2014 Elsevier Ltd. All rights reserved.

Fifth harmonic and sag impact on PMSG wind turbines with a balancing new strategy for capacitor voltages

This paper deals with the computing simulation of the impact on permanent magnet synchronous generator wind turbines due to fifth harmonic content and grid voltage decrease. Power converter topologies considered in the simulations are the two-level and the three-level ones. The three-level converters are limited by unbalance voltages in the DC-link capacitors. In order to lessen this limitation, a new control strategy for the selection of the output voltage vectors is proposed. Controller strategies considered in the simulation are respectively based on proportional integral and fractional-order controllers. Finally, a comparison between the results of the simulations with the two controller strategies is presented in order to show the main advantage of the proposed strategy. (C) 2014 Elsevier Ltd. All rights reserved.

Fuzzy clustering applied to a demand response model in a smatr grid contingency scenario

This paper focus on a demand response model analysis in a smart grid context considering a contingency scenario. A fuzzy clustering technique is applied on the developed demand response model and an analysis is performed for the contingency scenario. Model considerations and architecture are described. The demand response developed model aims to support consumers decisions regarding their consumption needs and possible economic benefits.

Layered smart grid architecture approach and field tests by ZigBee technology

This paper presents a layered Smart Grid architecture enhancing security and reliability, having the ability to act in order to maintain and correct infrastructure components without affecting the client service. The architecture presented is based in the core of well design software engineering, standing upon standards developed over the years. The layered Smart Grid offers a base tool to ease new standards and energy policies implementation. The ZigBee technology implementation test methodology for the Smart Grid is presented, and provides field tests using ZigBee technology to control the new Smart Grid architecture approach. (C) 2014 Elsevier Ltd. All rights reserved.

Logarithmically proportional objective function for planar surfaces recognition in 3D point cloud

3D laser scanning is becoming a standard technology to generate building models of a facility's as-is condition. Since most constructions are constructed upon planar surfaces, recognition of them paves the way for automation of generating building models. This paper introduces a new logarithmically proportional objective function that can be used in both heuristic and metaheuristic (MH) algorithms to discover planar surfaces in a point cloud without exploiting any prior knowledge about those surfaces. It can also adopt itself to the structural density of a scanned construction. In this paper, a metaheuristic method, genetic algorithm (GA), is used to test this introduced objective function on a synthetic point cloud. The results obtained show the proposed method is capable to find all plane configurations of planar surfaces (with a wide variety of sizes) in the point cloud with a minor distance to the actual configurations. © 2014 IEEE.