Perceções de profissionais do Sistema de Justiça e População em geral quanto à implementação da Lei de Registo e Notificação de Ofensores Sexuais em Portugal

Dissertação apresentada à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de mestre em Psicologia Jurídica

Estudo da prevalência das alterações biológicas e mecânicas associadas à reabilitação com prótese parcial removível nas clínicas pedagógicas de Medicina Dentária da FCS-UFP

Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Medicina Dentária

Integrated Chest Image Analysis System "BU-MIA"

We introduce "BU-MIA," a Medical Image Analysis system that integrates various advanced chest image analysis methods for detection, estimation, segmentation, and registration. BU-MIA evaluates repeated computed tomography (CT) scans of the same patient to facilitate identification and evaluation of pulmonary nodules for interval growth. It provides a user-friendly graphical user interface with a number of interaction tools for development, evaluation, and validation of chest image analysis methods. The structures that BU-MIA processes include the thorax, lungs, and trachea, pulmonary structures, such as lobes, fissures, nodules, and vessels, and bones, such as sternum, vertebrae, and ribs.

Active Blobs

A new region-based approach to nonrigid motion tracking is described. Shape is defined in terms of a deformable triangular mesh that captures object shape plus a color texture map that captures object appearance. Photometric variations are also modeled. Nonrigid shape registration and motion tracking are achieved by posing the problem as an energy-based, robust minimization procedure. The approach provides robustness to occlusions, wrinkles, shadows, and specular highlights. The formulation is tailored to take advantage of texture mapping hardware available in many workstations, PC's, and game consoles. This enables nonrigid tracking at speeds approaching video rate.

Admission Control and Scheduling for High-Performance WWW Servers

In this paper we examine a number of admission control and scheduling protocols for high-performance web servers based on a 2-phase policy for serving HTTP requests. The first "registration" phase involves establishing the TCP connection for the HTTP request and parsing/interpreting its arguments, whereas the second "service" phase involves the service/transmission of data in response to the HTTP request. By introducing a delay between these two phases, we show that the performance of a web server could be potentially improved through the adoption of a number of scheduling policies that optimize the utilization of various system components (e.g. memory cache and I/O). In addition, to its premise for improving the performance of a single web server, the delineation between the registration and service phases of an HTTP request may be useful for load balancing purposes on clusters of web servers. We are investigating the use of such a mechanism as part of the Commonwealth testbed being developed at Boston University.

Example-Based Image Restoration via Boosted Classifiers

We propose a novel image registration framework which uses classifiers trained from examples of aligned images to achieve registration. Our approach is designed to register images of medical data where the physical condition of the patient has changed significantly and image intensities are drastically different. We use two boosted classifiers for each degree of freedom of image transformation. These two classifiers can both identify when two images are correctly aligned and provide an efficient means of moving towards correct registration for misaligned images. The classifiers capture local alignment information using multi-pixel comparisons and can therefore achieve correct alignments where approaches like correlation and mutual-information which rely on only pixel-to-pixel comparisons fail. We test our approach using images from CT scans acquired in a study of acute respiratory distress syndrome. We show significant increase in registration accuracy in comparison to an approach using mutual information.

Fast, Reliable Head Tracking under Varying Illumination

An improved technique for 3D head tracking under varying illumination conditions is proposed. The head is modeled as a texture mapped cylinder. Tracking is formulated as an image registration problem in the cylinder's texture map image. To solve the registration problem in the presence of lighting variation and head motion, the residual error of registration is modeled as a linear combination of texture warping templates and orthogonal illumination templates. Fast and stable on-line tracking is then achieved via regularized, weighted least squares minimization of the registration error. The regularization term tends to limit potential ambiguities that arise in the warping and illumination templates. It enables stable tracking over extended sequences. Tracking does not require a precise initial fit of the model; the system is initialized automatically using a simple 2-D face detector. The only assumption is that the target is facing the camera in the first frame of the sequence. The warping templates are computed at the first frame of the sequence. Illumination templates are precomputed off-line over a training set of face images collected under varying lighting conditions. Experiments in tracking are reported.

Non-Rigid Shape from Image Streams

We present a framework for estimating 3D relative structure (shape) and motion given objects undergoing nonrigid deformation as observed from a fixed camera, under perspective projection. Deforming surfaces are approximated as piece-wise planar, and piece-wise rigid. Robust registration methods allow tracking of corresponding image patches from view to view and recovery of 3D shape despite occlusions, discontinuities, and varying illumination conditions. Many relatively small planar/rigid image patch trackers are scattered throughout the image; resulting estimates of structure and motion at each patch are combined over local neighborhoods via an oriented particle systems formulation. Preliminary experiments have been conducted on real image sequences of deforming objects and on synthetic sequences where ground truth is known.

Object Detection at the Optimal Scale with Hidden State Shape Models

Hidden State Shape Models (HSSMs) [2], a variant of Hidden Markov Models (HMMs) [9], were proposed to detect shape classes of variable structure in cluttered images. In this paper, we formulate a probabilistic framework for HSSMs which provides two major improvements in comparison to the previous method [2]. First, while the method in [2] required the scale of the object to be passed as an input, the method proposed here estimates the scale of the object automatically. This is achieved by introducing a new term for the observation probability that is based on a object-clutter feature model. Second, a segmental HMM [6, 8] is applied to model the "duration probability" of each HMM state, which is learned from the shape statistics in a training set and helps obtain meaningful registration results. Using a segmental HMM provides a principled way to model dependencies between the scales of different parts of the object. In object localization experiments on a dataset of real hand images, the proposed method significantly outperforms the method of [2], reducing the incorrect localization rate from 40% to 15%. The improvement in accuracy becomes more significant if we consider that the method proposed here is scale-independent, whereas the method of [2] takes as input the scale of the object we want to localize.

Traffic Characteristics and Communication Patterns in Blogosphere

We present a thorough characterization of the access patterns in blogspace -- a fast-growing constituent of the content available through the Internet -- which comprises a rich interconnected web of blog postings and comments by an increasingly prominent user community that collectively define what has become known as the blogosphere. Our characterization of over 35 million read, write, and administrative requests spanning a 28-day period is done from three different blogosphere perspectives. The server view characterizes the aggregate access patterns of all users to all blogs; the user view characterizes how individual users interact with blogosphere objects (blogs); the object view characterizes how individual blogs are accessed. Our findings support two important conclusions. First, we show that the nature of interactions between users and objects is fundamentally different in blogspace than that observed in traditional web content. Access to objects in blogspace could be conceived as part of an interaction between an author and its readership. As we show in our work, such interactions range from one-to-many "broadcast-type" and many-to-one "registration-type" communication between an author and its readers, to multi-way, iterative "parlor-type" dialogues among members of an interest group. This more-interactive nature of the blogosphere leads to interesting traffic and communication patterns, which are different from those observed in traditional web content. Second, we identify and characterize novel features of the blogosphere workload, and we investigate the similarities and differences between typical web server workloads and blogosphere server workloads. Given the increasing share of blogspace traffic, understanding such differences is important for capacity planning and traffic engineering purposes, for example.

Intersubject Regularity in the Intrinsic Shape of Human V1

Previous studies have reported considerable intersubject variability in the three-dimensional geometry of the human primary visual cortex (V1). Here we demonstrate that much of this variability is due to extrinsic geometric features of the cortical folds, and that the intrinsic shape of V1 is similar across individuals. V1 was imaged in ten ex vivo human hemispheres using high-resolution (200 μm) structural magnetic resonance imaging at high field strength (7 T). Manual tracings of the stria of Gennari were used to construct a surface representation, which was computationally flattened into the plane with minimal metric distortion. The instrinsic shape of V1 was determined from the boundary of the planar representation of the stria. An ellipse provided a simple parametric shape model that was a good approximation to the boundary of flattened V1. The aspect ration of the best-fitting ellipse was found to be consistent across subject, with a mean of 1.85 and standard deviation of 0.12. Optimal rigid alignment of size-normalized V1 produced greater overlap than that achieved by previous studies using different registration methods. A shape analysis of published macaque data indicated that the intrinsic shape of macaque V1 is also stereotyped, and similar to the human V1 shape. Previoud measurements of the functional boundary of V1 in human and macaque are in close agreement with these results.

Searching the Sky with CONFIGR-STARS

SyNAPSE program of the Defense Advanced Projects Research Agency (HRL Laboratories LLC, subcontract #801881-BS under DARPA prime contract HR0011-09-C-0001); CELEST, a National Science Foundation Science of Learning Center (SBE-0354378)

ART-EMAP: A Neural Network Architecture for Learning and Prediction by Evidence Accumulation

This paper introduces ART-EMAP, a neural architecture that uses spatial and temporal evidence accumulation to extend the capabilities of fuzzy ARTMAP. ART-EMAP combines supervised and unsupervised learning and a medium-term memory process to accomplish stable pattern category recognition in a noisy input environment. The ART-EMAP system features (i) distributed pattern registration at a view category field; (ii) a decision criterion for mapping between view and object categories which can delay categorization of ambiguous objects and trigger an evidence accumulation process when faced with a low confidence prediction; (iii) a process that accumulates evidence at a medium-term memory (MTM) field; and (iv) an unsupervised learning algorithm to fine-tune performance after a limited initial period of supervised network training. ART-EMAP dynamics are illustrated with a benchmark simulation example. Applications include 3-D object recognition from a series of ambiguous 2-D views.

Not thinking straight? A critical discourse analysis of the 2006 Irish High Court ruling in Zappone and Gilligan v. Revenue Commissioners and Attorney General

The recognition and protection of constitutional rights is a fundamental precept. In Ireland, the right to marry is provided for in the equality provisions of Article 40 of the Irish Constitution (1937). However, lesbians and gay men are denied the right to marry in Ireland. The ‘last word’ on this issue came into being in the High Court in 2006, when Katherine Zappone and Ann Louise Gilligan sought, but failed, to have their Canadian marriage recognised in Ireland. My thesis centres on this constitutional court ruling. So as to contextualise the pursuit of marriage equality in Ireland, I provide details of the Irish trajectory vis-à-vis relationship and family recognition for same-sex couples. In Chapter One, I discuss the methodological orientation of my research, which derives from a critical perspective. Chapter Two denotes my theorisation of the principle of equality and the concept of difference. In Chapter Three, I discuss the history of the institution of marriage in the West with its legislative underpinning. Marriage also has a constitutional underpinning in Ireland, which derives from Article 41 of our Constitution. In Chapter Four, I discuss ways in which marriage and family were conceptualised in Ireland, by looking at historical controversies surrounding the legalisation of contraception and divorce. Chapter Five denotes a Critical Discourse Analysis of the High Court ruling in Zappone and Gilligan. In Chapter Six, I critique text from three genres of discourse, i.e. ‘Letters to the Editor’ regarding same-sex marriage in Ireland, communication from legislators vis-à-vis the 2004 legislative impediment to same-sex marriage in Ireland, and parliamentary debates surrounding the 2010 enactment of civil partnership legislation in Ireland. I conclude my research by reflecting on my methodological and theoretical considerations with a view to answering my research questions. Author’s Update: Following the outcome of the 2015 constitutional referendum vis-à-vis Article 41, marriage equality has been realised in Ireland.

Transport energy demand: techno-economic modelling and scenarios for Irish climate policy

The case for energy policy modelling is strong in Ireland, where stringent EU climate targets are projected to be overshot by 2015. Policy targets aiming to deliver greenhouse gas and renewable energy targets have been made, but it is unclear what savings are to be achieved and from which sectors. Concurrently, the growth of personal mobility has caused an astonishing increase in CO2 emissions from private cars in Ireland, a 37% rise between 2000 and 2008, and while there have been improvements in the efficiency of car technology, there was no decrease in the energy intensity of the car fleet in the same period. This thesis increases the capacity for evidenced-based policymaking in Ireland by developing techno-economic transport energy models and using them to analyse historical trends and to project possible future scenarios. A central focus of this thesis is to understand the effect of the car fleet‘s evolving technical characteristics on energy demand. A car stock model is developed to analyse this question from three angles: Firstly, analysis of car registration and activity data between 2000 and 2008 examines the trends which brought about the surge in energy demand. Secondly, the car stock is modelled into the future and is used to populate a baseline “no new policy” scenario, looking at the impact of recent (2008-2011) policy and purchasing developments on projected energy demand and emissions. Thirdly, a range of technology efficiency, fuel switching and behavioural scenarios are developed up to 2025 in order to indicate the emissions abatement and renewable energy penetration potential from alternative policy packages. In particular, an ambitious car fleet electrification target for Ireland is examined. The car stock model‘s functionality is extended by linking it with other models: LEAP-Ireland, a bottom-up energy demand model for all energy sectors in the country; Irish TIMES, a linear optimisation energy system model; and COPERT, a pollution model. The methodology is also adapted to analyse trends in freight energy demand in a similar way. Finally, this thesis addresses the gap in the representation of travel behaviour in linear energy systems models. A novel methodology is developed and case studies for Ireland and California are presented using the TIMES model. Transport Energy