The clinical utility of FibroScan(®) as a noninvasive diagnostic test for liver disease.

An important aspect of managing chronic liver disease is assessing for evidence of fibrosis. Historically, this has been accomplished using liver biopsy, which is an invasive procedure associated with risk for complications and significant sampling and observer error, limiting the accuracy for determination of fibrosis stage. Hence, several serum biomarkers and imaging methods for noninvasive assessment of liver fibrosis have been developed. In this article, we review the current literature on an important noninvasive imaging modality to measure tissue elastography (FibroScan(®)). This ultrasound-based technique is now increasingly available in many countries and has been shown to be a reliable and safe noninvasive means of assessing disease severity in chronic liver disease of varying etiology.

Sharing in the Rain: Secure and Efficient Data Sharing for the Cloud

Cloud storage has rapidly become a cornerstone of many businesses and has moved from an early adopters stage to an early majority, where we typically see explosive deployments. As companies rush to join the cloud revolution, it has become vital to create the necessary tools that will effectively protect users' data from unauthorized access. Nevertheless, sharing data between multiple users' under the same domain in a secure and efficient way is not trivial. In this paper, we propose Sharing in the Rain – a protocol that allows cloud users' to securely share their data based on predefined policies. The proposed protocol is based on Attribute-Based Encryption (ABE) and allows users' to encrypt data based on certain policies and attributes. Moreover, we use a Key-Policy Attribute-Based technique through which access revocation is optimized. More precisely, we show how to securely and efficiently remove access to a file, for a certain user that is misbehaving or is no longer part of a user group, without having to decrypt and re-encrypt the original data with a new key or a new policy.

Coupled diusion and mechanics in battery electrodes

Thesis (Ph.D.)--University of Washington, 2016-08

Ant Colony Optimization for Requirement selection in Incremental Software development

This proposal shows that ACO systems can be applied to problems of requirements selection in software incremental development, with the idea of obtaining better results of those produced by expert judgment alone. The evaluation of the ACO systems should be done through a compared analysis with greedy and simulated annealing algorithms, performing experiments with some problems instances

Multi-objective ant colony optimization for requirements selection

The selection of a set of requirements between all the requirements previously defined by customers is an important process, repeated at the beginning of each development step when an incremental or agile software development approach is adopted. The set of selected requirements will be developed during the actual iteration. This selection problem can be reformulated as a search problem, allowing its treatment with metaheuristic optimization techniques. This paper studies how to apply Ant Colony Optimization algorithms to select requirements. First, we describe this problem formally extending an earlier version of the problem, and introduce a method based on Ant Colony System to find a variety of efficient solutions. The performance achieved by the Ant Colony System is compared with that of Greedy Randomized Adaptive Search Procedure and Non-dominated Sorting Genetic Algorithm, by means of computational experiments carried out on two instances of the problem constructed from data provided by the experts.

HOLDING DECISIONS FOR CORRELATED VEHICLE ARRIVALS AT INTERMODAL FREIGHT TRANSFER TERMINALS

A vehicle holding method is proposed for mitigating the effect of service disruptions on coordinated intermodal freight operations. Existing studies are extended mainly by (1) modeling correlations among vehicle arrivals and (2) considering decision risks with a mean-standard deviation optimization model. It is shown that the expected value of the total cost in the proposed formulation is not affected by the correlations, while the variance can be miscomputed when arrival correlations are neglected. Some implications of delay propagation are also identified when optimizing vehicle holding decisions in real-time. General criteria are provided for determining the boundary of the affected region and length of the numerical search, based on the frequency of information updates. Theoretical analyses are supported by three numerical examples.

Hybrid Graph Heuristics within a Hyper-heuristic Approach to Exam Timetabling Problems

This paper is concerned with the hybridization of two graph coloring heuristics (Saturation Degree and Largest Degree), and their application within a hyperheuristic for exam timetabling problems. Hyper-heuristics can be seen as algorithms which intelligently select appropriate algorithms/heuristics for solving a problem. We developed a Tabu Search based hyper-heuristic to search for heuristic lists (of graph heuristics) for solving problems and investigated the heuristic lists found by employing knowledge discovery techniques. Two hybrid approaches (involving Saturation Degree and Largest Degree) including one which employs Case Based Reasoning are presented and discussed. Both the Tabu Search based hyper-heuristic and the hybrid approaches are tested on random and real-world exam timetabling problems. Experimental results are comparable with the best state-of-the-art approaches (as measured against established benchmark problems). The results also demonstrate an increased level of generality in our approach.

Aplicação para pesquisa de clip arts em dispositivos móveis baseada em esboços

Trabalho Final de Mestrado para obtenção do Grau de Mestre em Engenharia de Redes de Comunicação e Multimédia

Prática de ensino supervisionada em educação pré-escolar e 1º ciclo do ensino básico: ensinar para aprender - gerindo a heterogeneidade, o currículo e rumando à diferenciação pedagógica

O presente relatório surge no âmbito do Mestrado em Educação Pré-escolar e Ensino do 1º Ciclo do Ensino Básico e visa a obtenção do grau de mestre nos níveis de escolaridade referidos. Neste descrevo o projeto de investigação-ação desenvolvido nos contextos da Prática de Ensino Supervisionado (PES) em Educação Pré-escolar e 1º Ciclo do Ensino Básico (CEB). A investigação-ação realizada visava, sobretudo, ajudar-me a compreender quais as condições que deveria reunir de modo a responder de forma adequada às necessidades das crianças e a perceber como poderia melhorar a minha ação e intervenção promovendo aprendizagens significativas e de qualidade, salientando que o propósito não era fornecer o mesmo a todas as crianças, mas sim, a cada uma aquilo de que necessitava. A minha aposta na Diferenciação Pedagógica e numa gestão flexível do currículo surge orientada pelo princípio do direito de todos à aprendizagem e como resposta intencional à heterogeneidade dos grupos de crianças que frequentam atualmente as instituições. Assim, de modo a atingir os objetivos propostos, planeei algumas sugestões de interação que permitiam a utilização de estratégias diversificadas e a observação das crianças durante a utilização das mesmas. A metodologia utilizada contemplou uma pesquisa bibliográfica com base em vários referenciais teóricos e a recolha e análise de dados. Esta investigação possibilitou constatar que a Diferenciação Pedagógica subjacente às propostas apresentadas proporciona o desenvolvimento das crianças tanto a nível social como cognitivo; ABSTRACT: The present report reflects the research develop in the context of the Master Degree in Preschool Education and Teaching of the Primary School at University of Évora, and aims to obtain the degree of master in the levels mention above. This research was held in two different contexts, the first one in a pre-school classroom, and later in a classroom of fourth year of Primary School. The research performed aimed mainly to help me to understand what conditions must be gathered in order to respond appropriately to children's needs and to see how it could improve my actions and intervention by promoting meaningful and quality learnings, stressing that the purpose was not to provide the same for all children, but to each one what they needed. My bet on Pedagogical Differentiation and a flexible management of the curriculum comes to the principle of the right of all to learning and as an intentional response to the heterogeneity of the groups of children who currently attend institutions. Thus, in order to achieve the proposed objectives, I planned some suggestions for interacting with groups of children’s which allowed me to use multiple strategies and to do observation of the individuals while they were being applied. The methodology included a literature search based on various theoretical frameworks and data collection and the respective analysis. This research led us to confirm that the proposals based on pedagogical differentiation provide children's development both socially and cognitive and it is essential to ensure it since the earliest years of school, in order to build a rich differentiated pedagogical action and to promote learning for all students in pre-school and 1st cycle contexts by using diverse strategies.

Characterization of microplastics ingested by marine benthos - a methodological and field-experimental study

Microplastics have become ubiquitous pollutants in the marine environment. Ingestion of microplastics by a wide range of marine organisms has been recorded both in laboratory and field studies. Despite growing concern for microplastics, few studies have evaluated their concentrations and distribution in wild populations. Further, there is a need to identify cost-effective standardized methodologies for microplastics extraction and analysis in organisms. In this thesis I present: (i) the results of a multi-scale field sampling to quantify and characterize microplastics occurrence and distribution in 4 benthic marine invertebrates from saltmarshes along the North Adriatic Italian coastal lagoons; (ii) a comparison of the effects and cost-effectiveness of two extraction protocols for microplastics isolation on microfibers and on wild collected organisms; (iii) the development of a novel field- based technique to quantify and characterize the microplastic uptake rates of wild and farmed populations of mussels (Mytilus galloprovincialis) through the analysis of their biodeposits. I found very low and patchy amounts of microplastics in the gastrointestinal tracts of sampled organisms. The omnivorous crab Carcinus aestuarii was the species with the highest amounts of microplastics, but there was a notable variation among individuals. There were no substantial differences between enzymatic and alkaline extraction methods. However, the alkaline extraction was quicker and cheaper. Biodeposit traps proved to be an effective method to estimate mussel ingestion rates. However their performance differed significantly among sites, suggesting that the method, as currently designed, is sensible to local environmental conditions. There were no differences in the ingestion rates of microplastics between farmed and wild mussels. The estimates of microplastic ingestion and the validated procedures for their extraction provide a strong basis for future work on microplastic pollution.

Exact Search Directions for Optimization of Linear and Nonlinear Models Based on Generalized Orthonormal Functions

A novel technique for selecting the poles of orthonormal basis functions (OBF) in Volterra models of any order is presented. It is well-known that the usual large number of parameters required to describe the Volterra kernels can be significantly reduced by representing each kernel using an appropriate basis of orthonormal functions. Such a representation results in the so-called OBF Volterra model, which has a Wiener structure consisting of a linear dynamic generated by the orthonormal basis followed by a nonlinear static mapping given by the Volterra polynomial series. Aiming at optimizing the poles that fully parameterize the orthonormal bases, the exact gradients of the outputs of the orthonormal filters with respect to their poles are computed analytically by using a back-propagation-through-time technique. The expressions relative to the Kautz basis and to generalized orthonormal bases of functions (GOBF) are addressed; the ones related to the Laguerre basis follow straightforwardly as a particular case. The main innovation here is that the dynamic nature of the OBF filters is fully considered in the gradient computations. These gradients provide exact search directions for optimizing the poles of a given orthonormal basis. Such search directions can, in turn, be used as part of an optimization procedure to locate the minimum of a cost-function that takes into account the error of estimation of the system output. The Levenberg-Marquardt algorithm is adopted here as the optimization procedure. Unlike previous related work, the proposed approach relies solely on input-output data measured from the system to be modeled, i.e., no information about the Volterra kernels is required. Examples are presented to illustrate the application of this approach to the modeling of dynamic systems, including a real magnetic levitation system with nonlinear oscillatory behavior.

Fast 2D to 3D conversion using a clustering-based hierarchical search in a machine learning framework

Automatic 2D-to-3D conversion is an important application for filling the gap between the increasing number of 3D displays and the still scant 3D content. However, existing approaches have an excessive computational cost that complicates its practical application. In this paper, a fast automatic 2D-to-3D conversion technique is proposed, which uses a machine learning framework to infer the 3D structure of a query color image from a training database with color and depth images. Assuming that photometrically similar images have analogous 3D structures, a depth map is estimated by searching the most similar color images in the database, and fusing the corresponding depth maps. Large databases are desirable to achieve better results, but the computational cost also increases. A clustering-based hierarchical search using compact SURF descriptors to characterize images is proposed to drastically reduce search times. A significant computational time improvement has been obtained regarding other state-of-the-art approaches, maintaining the quality results.

Peptide design by artificial neural networks and computer-based evolutionary search

A technique for systematic peptide variation by a combination of rational and evolutionary approaches is presented. The design scheme consists of five consecutive steps: (i) identification of a “seed peptide” with a desired activity, (ii) generation of variants selected from a physicochemical space around the seed peptide, (iii) synthesis and testing of this biased library, (iv) modeling of a quantitative sequence-activity relationship by an artificial neural network, and (v) de novo design by a computer-based evolutionary search in sequence space using the trained neural network as the fitness function. This strategy was successfully applied to the identification of novel peptides that fully prevent the positive chronotropic effect of anti-β1-adrenoreceptor autoantibodies from the serum of patients with dilated cardiomyopathy. The seed peptide, comprising 10 residues, was derived by epitope mapping from an extracellular loop of human β1-adrenoreceptor. A set of 90 peptides was synthesized and tested to provide training data for neural network development. De novo design revealed peptides with desired activities that do not match the seed peptide sequence. These results demonstrate that computer-based evolutionary searches can generate novel peptides with substantial biological activity.

Structuring the pre-search reference interview: a useful technique for handling clinical questions*

Objectives: To explore whether structuring a literature search request form according to an evidence-based medicine (EBM) anatomy elicits more information, improves precision of search results, and is acceptable to participating librarians.

Genetic algorithm based distance spectrum technique for performance union bound of space-time trellis coded OFDM

This paper derives the performance union bound of space-time trellis codes in orthogonal frequency division multiplexing system (STTC-OFDM) over quasi-static frequency selective fading channels based on the distance spectrum technique. The distance spectrum is the enumeration of the codeword difference measures and their multiplicities by exhausted searching through all the possible error event paths. Exhaustive search approach can be used for low memory order STTC with small frame size. However with moderate memory order STTC and moderate frame size the computational cost of exhaustive search increases exponentially, and may become impractical for high memory order STTCs. This requires advanced computational techniques such as Genetic Algorithms (GAS). In this paper, a GA with sharing function method is used to locate the multiple solutions of the distance spectrum for high memory order STTCs. Simulation evaluates the performance union bound and the complexity comparison of non-GA aided and GA aided distance spectrum techniques. It shows that the union bound give a close performance measure at high signal-to-noise ratio (SNR). It also shows that GA sharing function method based distance spectrum technique requires much less computational time as compared with exhaustive search approach but with satisfactory accuracy.