Analysis of diffusion process in fractured reservoirs using fractional derivative approach

The fractal geometry is used to model of a naturally fractured reservoir and the concept of fractional derivative is applied to the diffusion equation to incorporate the history of fluid flow in naturally fractured reservoirs. The resulting fractally fractional diffusion (FFD) equation is solved analytically in the Laplace space for three outer boundary conditions. The analytical solutions are used to analyze the response of a naturally fractured reservoir considering the anomalous behavior of oil production. Several synthetic examples are provided to illustrate the methodology proposed in this work and to explain the diffusion process in fractally fractured systems.

Estimation of 3D shapes using active surface models

This paper addresses the estimation of surfaces from a set of 3D points using the unified framework described in [1]. This framework proposes the use of competitive learning for curve estimation, i.e., a set of points is defined on a deformable curve and they all compete to represent the available data. This paper extends the use of the unified framework to surface estimation. It o shown that competitive learning performes better than snakes, improving the model performance in the presence of concavities and allowing to desciminate close surfaces. The proposed model is evaluated in this paper using syntheticdata and medical images (MRI and ultrasound images).

Hyperspectral unmixing algorithm via dependent component analysis

This paper introduces a new method to blindly unmix hyperspectral data, termed dependent component analysis (DECA). This method decomposes a hyperspectral images into a collection of reflectance (or radiance) spectra of the materials present in the scene (endmember signatures) and the corresponding abundance fractions at each pixel. DECA assumes that each pixel is a linear mixture of the endmembers signatures weighted by the correspondent abundance fractions. These abudances are modeled as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. The mixing matrix is inferred by a generalized expectation-maximization (GEM) type algorithm. This method overcomes the limitations of unmixing methods based on Independent Component Analysis (ICA) and on geometrical based approaches. The effectiveness of the proposed method is illustrated using simulated data based on U.S.G.S. laboratory spectra and real hyperspectral data collected by the AVIRIS sensor over Cuprite, Nevada.

Tradutor da língua gestual portuguesa modelo de tradução bidireccional

O projeto tem como objetivo desenvolver e avaliar um modelo que facilita o acesso para pessoas surdas ou com deficiência auditiva, o acesso ao conteúdo digital - em particular o conteúdo educacional e objetos de aprendizagem – a criação de condições para uma maior inclusão social de surdos e deficientes auditivos. Pretende-se criar um modelo bidirecional, em que permite a pessoas com deficiências auditivas, possam se comunicar com outras pessoas, com a tradução da Língua Gestual Portuguesa (LGP) para a Língua Portuguesa (LP) e que outras pessoas não portadoras de qualquer deficiência auditiva possam por sua vez comunicar com os surdos ou deficientes auditivos através da tradução da LP para a LGP. Há um conjunto de técnicas que poderíamos nos apoiar para desenvolver o modelo e implementar a API de tradução da LGP em LP. Muitos estudos são feitos com base nos modelos escondidos de Markov (HMM) para efetuar o reconhecimento. Recentemente os estudos estão a caminhar para o uso de técnicas como o “Dynamic Time Warping” (DTW), que tem tido mais sucesso do que outras técnicas em termos de performance e de precisão. Neste projeto optamos por desenvolver a API e o Modelo, com base na técnica de aprendizagem Support Vector Machines (SVM) por ser uma técnica simples de implementar e com bons resultados demonstrados em reconhecimento de padrões. Os resultados obtidos utilizando esta técnica de aprendizagem foram bastante ótimos, como iremos descrever no decorrer do capítulo 4, mesmo sabendo que utilizamos dois dispositivos para capturar dados de descrição de cada gesto. Toda esta tese integra-se no âmbito do projeto científico/ investigação a decorrer no grupo de investigação GILT, sob a coordenação da professora Paula Escudeiro e suportado pela Fundação para Ciência e Tecnologia (FCT).

Spatial analysis of suicide attack incidences in Kabul City

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Digital Divide Across the European Union

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Spatio-temporal analyses of the relationship between armed conflict and climate change in the eastern Africa

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Digital Divide Across the European Union

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Market analysis of a new business opportunity in mobile-casual gaming: Partnership between Nmusic and Rovio Entertainment Ltd

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

A framework for efficient model transformations

The reported productivity gains while using models and model transformations to develop entire systems, after almost a decade of experience applying model-driven approaches for system development, are already undeniable benefits of this approach. However, the slowness of higher-level, rule based model transformation languages hinders the applicability of this approach to industrial scales. Lower-level, and efficient, languages can be used but productivity and easy maintenance seize to exist. The abstraction penalty problem is not new, it also exists for high-level, object oriented languages but everyone is using them now. Why is not everyone using rule based model transformation languages then? In this thesis, we propose a framework, comprised of a language and its respective environment, designed to tackle the most performance critical operation of high-level model transformation languages: the pattern matching. This framework shows that it is possible to mitigate the performance penalty while still using high-level model transformation languages.

Strategic design of There App’s business model: From product to multi-sided platform

The following work project illustrates the strategic issues There App, a mobile application, faces regarding the opportunity to expand from its current state as a product to a multisided platform. Initially, a market analysis is performed to identify the ideal customer groups to be integrated in the platform. Strategic design issues are then discussed on how to best match its value proposition with the identified market opportunity. Suggestions on how the company should organize its resources and operational processes to best deliver on its value proposition complete the work.

Albuterol delivery in an in vitro pediatric ventilator lung model: comparison of jet, ultrasonic, and mesh nebulizers.

OBJECTIVE: : To determine the influence of nebulizer types and nebulization modes on bronchodilator delivery in a mechanically ventilated pediatric lung model. DESIGN: : In vitro, laboratory study. SETTING: : Research laboratory of a university hospital. INTERVENTIONS: : Using albuterol as a marker, three nebulizer types (jet nebulizer, ultrasonic nebulizer, and vibrating-mesh nebulizer) were tested in three nebulization modes in a nonhumidified bench model mimicking the ventilatory pattern of a 10-kg infant. The amounts of albuterol deposited on the inspiratory filters (inhaled drug) at the end of the endotracheal tube, on the expiratory filters, and remaining in the nebulizers or in the ventilator circuit were determined. Particle size distribution of the nebulizers was also measured. MEASUREMENTS AND MAIN RESULTS: : The inhaled drug was 2.8% ± 0.5% for the jet nebulizer, 10.5% ± 2.3% for the ultrasonic nebulizer, and 5.4% ± 2.7% for the vibrating-mesh nebulizer in intermittent nebulization during the inspiratory phase (p < 0.01). The most efficient nebulizer was the vibrating-mesh nebulizer in continuous nebulization (13.3% ± 4.6%, p < 0.01). Depending on the nebulizers, a variable but important part of albuterol was observed as remaining in the nebulizers (jet and ultrasonic nebulizers), or being expired or lost in the ventilator circuit (all nebulizers). Only small particles (range 2.39-2.70 µm) reached the end of the endotracheal tube. CONCLUSIONS: : Important differences between nebulizer types and nebulization modes were seen for albuterol deposition at the end of the endotracheal tube in an in vitro pediatric ventilator-lung model. New aerosol devices, such as ultrasonic and vibrating-mesh nebulizers, were more efficient than the jet nebulizer.

Generating controlled image sets in cognitive neuroscience research.

The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann et al., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimuli.

Comparing Multilevel Clustering Methods on Weighted Graphs : The Case of Worldwide Air Passenger Traffic 2000-2004

Specific properties emerge from the structure of large networks, such as that of worldwide air traffic, including a highly hierarchical node structure and multi-level small world sub-groups that strongly influence future dynamics. We have developed clustering methods to understand the form of these structures, to identify structural properties, and to evaluate the effects of these properties. Graph clustering methods are often constructed from different components: a metric, a clustering index, and a modularity measure to assess the quality of a clustering method. To understand the impact of each of these components on the clustering method, we explore and compare different combinations. These different combinations are used to compare multilevel clustering methods to delineate the effects of geographical distance, hubs, network densities, and bridges on worldwide air passenger traffic. The ultimate goal of this methodological research is to demonstrate evidence of combined effects in the development of an air traffic network. In fact, the network can be divided into different levels of âeurooecohesionâeuro, which can be qualified and measured by comparative studies (Newman, 2002; Guimera et al., 2005; Sales-Pardo et al., 2007).

A methodology to event reconstruction from trace images

The widespread use of digital imaging devices for surveillance (CCTV) and entertainment (e.g., mobile phones, compact cameras) has increased the number of images recorded and opportunities to consider the images as traces or documentation of criminal activity. The forensic science literature focuses almost exclusively on technical issues and evidence assessment [1]. Earlier steps in the investigation phase have been neglected and must be considered. This article is the first comprehensive description of a methodology to event reconstruction using images. This formal methodology was conceptualised from practical experiences and applied to different contexts and case studies to test and refine it. Based on this practical analysis, we propose a systematic approach that includes a preliminary analysis followed by four main steps. These steps form a sequence for which the results from each step rely on the previous step. However, the methodology is not linear, but it is a cyclic, iterative progression for obtaining knowledge about an event. The preliminary analysis is a pre-evaluation phase, wherein potential relevance of images is assessed. In the first step, images are detected and collected as pertinent trace material; the second step involves organising and assessing their quality and informative potential. The third step includes reconstruction using clues about space, time and actions. Finally, in the fourth step, the images are evaluated and selected as evidence. These steps are described and illustrated using practical examples. The paper outlines how images elicit information about persons, objects, space, time and actions throughout the investigation process to reconstruct an event step by step. We emphasise the hypothetico-deductive reasoning framework, which demonstrates the contribution of images to generating, refining or eliminating propositions or hypotheses. This methodology provides a sound basis for extending image use as evidence and, more generally, as clues in investigation and crime reconstruction processes.