Sustainable Tourism and Agriculture Multifunctionality by PAR: A Variable Selection Approach

Copyright © 2013 Springer Netherlands.

Data analysis model selection for estimating local population size of the Risso’s dolphin (Grampus griseus) in the Azores

27th Annual Conference of the European Cetacean Society. Setúbal, Portugal, 8-10 April 2013.

FMRI 3D registration based on Fourier space subsets using neural networks

In this work, we present a neural network (NN) based method designed for 3D rigid-body registration of FMRI time series, which relies on a limited number of Fourier coefficients of the images to be aligned. These coefficients, which are comprised in a small cubic neighborhood located at the first octant of a 3D Fourier space (including the DC component), are then fed into six NN during the learning stage. Each NN yields the estimates of a registration parameter. The proposed method was assessed for 3D rigid-body transformations, using DC neighborhoods of different sizes. The mean absolute registration errors are of approximately 0.030 mm in translations and 0.030 deg in rotations, for the typical motion amplitudes encountered in FMRI studies. The construction of the training set and the learning stage are fast requiring, respectively, 90 s and 1 to 12 s, depending on the number of input and hidden units of the NN. We believe that NN-based approaches to the problem of FMRI registration can be of great interest in the future. For instance, NN relying on limited K-space data (possibly in navigation echoes) can be a valid solution to the problem of prospective (in frame) FMRI registration.

3D-2D image registration by nonlinear regression

We propose a 3D-2D image registration method that relates image features of 2D projection images to the transformation parameters of the 3D image by nonlinear regression. The method is compared with a conventional registration method based on iterative optimization. For evaluation, simulated X-ray images (DRRs) were generated from coronary artery tree models derived from 3D CTA scans. Registration of nine vessel trees was performed, and the alignment quality was measured by the mean target registration error (mTRE). The regression approach was shown to be slightly less accurate, but much more robust than the method based on an iterative optimization approach.

Integração e contextualização de modelos 3D no ensino da área da saúde

Mestrado em Engenharia Informática. Sistemas Gráficos e Multimédia.

Modelo generalista de páginas Web para motores de pesquisa com interface 3D

Web tornou-se uma ferramenta indispensável para a sociedade moderna. A capacidade de aceder a enormes quantidades de informação, disponível em praticamente todo o mundo, é uma grande vantagem para as nossas vidas. No entanto, a quantidade avassaladora de informação disponível torna-se um problema, que é o de encontrar a informação que precisamos no meio de muita informação irrelevante. Para nos ajudar nesta tarefa, foram criados poderosos motores de pesquisa online, que esquadrinham a Web à procura dos melhores resultados, segundo os seus critérios, para os dados que precisamos. Actualmente, os motores de pesquisa em voga, usam um formato de apresentação de resultados simples, que consiste apenas numa caixa de texto para o utilizador inserir as palavras-chave sobre o tema que quer pesquisar e os resultados são dispostos sobre uma lista de hiperligações ordenada pela relevância que o motor atribui a cada resultado. Porém, existem outras formas de apresentar resultados. Uma das alternativas é apresentar os resultados sobre interfaces em 3 dimensões. É nestes tipos de sistemas que este trabalho vai incidir, os motores de pesquisa com interfaces em 3 dimensões. O problema é que as páginas Web não estão preparadas para serem consumidas por este tipo de motores de pesquisa. Para resolver este problema foi construído um modelo generalista para páginas Web, que consegue alimentar os requisitos das diversas variantes destes motores de pesquisa. Foi também desenvolvido um protótipo de instanciação automático, que recolhe as informações necessárias das páginas Web e preenche o modelo.

Caracterização e modelação de fissuras em edifícios utilizando 3D laser scanning, com vista à sua reabilitação

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil

Visualização e manipulação de informação em ambientes 3D imersivos

Ainda antes da invenção da escrita, o desenho foi utilizado para descrever a realidade, tendo evoluído ao longo dos tempos, ganhando mais qualidade e pormenor e recorrendo a suportes cada vez mais evoluídos que permitissem a perpetuação dessa imagem: dessa informação. Desde as pinturas rupestres, nas paredes de grutas paleolíticas, passando pelos hieróglifos, nos templos egípcios, nas gravuras das escrituras antigas e nos quadros sobre tela, a intenção sempre foi a de transmitir a informação da forma mais directa e perceptível por qualquer indivíduo. Nos dias de hoje as novas tecnologias permitem aceder à informação com uma facilidade nunca antes vista ou imaginada, estando certamente ainda por descobrir outras formas de registar e perpetuar a informação para as gerações vindouras. A fotografia está na origem das grandes evoluções da imagem, permitindo capturar o momento, tornando-o “eterno”. Hoje em dia, na era da imagem digital, além de se mostrar a realidade, é possível incorporar na imagem informação adicional, de modo a enriquecer a experiência de visualização e a maximizar a aquisição do conhecimento. As possibilidades da visualização em três dimensões (3D) vieram dar o realismo que faltava ao formato de fotografia original. O 3D permite a imersão do espectador no ambiente que, a própria imagem retrata, à qual se pode ainda adicionar informação escrita ou até sensorial como, por exemplo, o som. Esta imersão num ambiente tridimensional permite ao utilizador interagir com a própria imagem através da navegação e exploração de detalhes, usando ferramentas como o zoom ou ligações incorporados na imagem. A internet é o local onde, hoje em dia, já se disponibilizam estes ambientes imersivos, tornando esta experiência muita mais acessível a qualquer pessoa. Há poucos anos ainda, esta prática só era possível mediante o recurso a dispositivos especificamente construídos para o efeito e que, por isso, apenas estavam disponíveis a grupos restritos de utilizadores. Esta dissertação visa identificar as características de um ambiente 3D imersivo e as técnicas existentes e possíveis de serem usadas para maximizar a experiência de visualização. Apresentar-se-ão algumas aplicações destes ambientes e sua utilidade no nosso dia-a-dia, antevendo as tendências futuras de evolução nesta área. Serão apresentados exemplos de ferramentas para a composição e produção destes ambientes e serão construídos alguns modelos ilustrativos destas técnicas, como forma de avaliar o esforço de desenvolvimento e o resultado obtido, comparativamente com formas mais convencionais de transmitir e armazenar a informação. Para uma avaliação mais objectiva, submeteram-se os modelos produzidos à apreciação de diversos utilizadores, a partir da qual foram elaboradas as conclusões finais deste trabalho relativamente às potencialidades de utilização de ambientes 3D imersivos e suas mais diversas aplicações.

Helical tomotherapy versus 3D conformal radiotherapy in dosimetric planning for patients with localized prostate cancer

Radiotherapy is one of the therapeutics selected for localized prostate cancer, in cases where the tumour is confined to the prostate, penetrates the prostatic capsule or has reached the seminal vesicles (T1 to T3 stages). The radiation therapy can be administered through various modalities, being historically used the 3D conformal radiotherapy (3DCRT). Other modality of radiation administration is the intensity modulated radiotherapy (IMRT), that allows an increase of the total dose through modulation of the treatment beams, enabling a reduction in toxicity. One way to administer IMRT is through helical tomotherapy (TH). With this study we intent to analyze the advantages of helical tomotherapy when compared with 3DCRT, by evaluating the doses in the organs at risk (OAR) and planning target volumes (PTV).

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.

QoS-based surrogates selection and service proposal formulation in offloading environments

Resource constraints are becoming a problem as many of the wireless mobile devices have increased generality. Our work tries to address this growing demand on resources and performance, by proposing the dynamic selection of neighbor nodes for cooperative service execution. This selection is in uenced by user's quality of service requirements expressed in his request, tailoring provided service to user's speci c needs. In this paper we improve our proposal's formulation algorithm with the ability to trade o time for the quality of the solution. At any given time, a complete solution for service execution exists, and the quality of that solution is expected to improve overtime.

Supplier's selection model based on an empirical study

The problem of selecting suppliers/partners is a crucial and important part in the process of decision making for companies that intend to perform competitively in their area of activity. The selection of supplier/partner is a time and resource-consuming task that involves data collection and a careful analysis of the factors that can positively or negatively influence the choice. Nevertheless it is a critical process that affects significantly the operational performance of each company. In this work, there were identified five broad selection criteria: Quality, Financial, Synergies, Cost, and Production System. Within these criteria, it was also included five sub-criteria. After the identification criteria, a survey was elaborated and companies were contacted in order to understand which factors have more weight in their decisions to choose the partners. Interpreted the results and processed the data, it was adopted a model of linear weighting to reflect the importance of each factor. The model has a hierarchical structure and can be applied with the Analytic Hierarchy Process (AHP) method or Value Analysis. The goal of the paper it's to supply a selection reference model that can represent an orientation/pattern for a decision making on the suppliers/partners selection process

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.

Analysis of the domain of applicability of an algorithm for a resources system selection problem for Distributed/Agile/Virtual Enterprises integration

The process of resources systems selection takes an important part in Distributed/Agile/Virtual Enterprises (D/A/V Es) integration. However, the resources systems selection is still a difficult matter to solve in a D/A/VE, as it is pointed out in this paper. Globally, we can say that the selection problem has been equated from different aspects, originating different kinds of models/algorithms to solve it. In order to assist the development of a web prototype tool (broker tool), intelligent and flexible, that integrates all the selection model activities and tools, and with the capacity to adequate to each D/A/V E project or instance (this is the major goal of our final project), we intend in this paper to show: a formulation of a kind of resources selection problem and the limitations of the algorithms proposed to solve it. We formulate a particular case of the problem as an integer programming, which is solved using simplex and branch and bound algorithms, and identify their performance limitations (in terms of processing time) based on simulation results. These limitations depend on the number of processing tasks and on the number of pre-selected resources per processing tasks, defining the domain of applicability of the algorithms for the problem studied. The limitations detected open the necessity of the application of other kind of algorithms (approximate solution algorithms) outside the domain of applicability founded for the algorithms simulated. However, for a broker tool it is very important the knowledge of algorithms limitations, in order to, based on problem features, develop and select the most suitable algorithm that guarantees a good performance.