934 resultados para Graphical passwords


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INTRODUCTION: Self-reported weight and height were compared with direct measurements in order to evaluate the agreement between the two sources. METHOD: Data were obtained from a cross-sectional study on health status from a probabilistic sample of 1,183 employees of a bank, in Rio de Janeiro State, Brazil. Direct measurements were made of 322 employees. Differences between the two sources were evaluated using mean differences, limits of agreement and intraclass correlation coefficient (ICC). RESULTS AND CONCLUSIONS: Men and women tended to underestimate their weight while differences between self-reported and measured height were insignificant. Body mass index (BMI) mean differences were smaller than those observed for weight. ICC was over 0.98 for weight and 0.95 for BMI, expressing close agreement. Combining a graphical method with ICC may be useful in pilot studies to detect populational groups capable of providing reliable information on weight and height, thus minimizing resources needed for field work.

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In this paper we present a methodology which enables the graphical representation, in a bi-dimensional Euclidean space, of atmospheric pollutants emissions in European countries. This approach relies on the use of Multidimensional Unfolding (MDU), an exploratory multivariate data analysis technique. This technique illustrates both the relationships between the emitted gases and the gases and their geographical origins. The main contribution of this work concerns the evaluation of MDU solutions. We use simulated data to define thresholds for the model fitting measures, allowing the MDU output quality evaluation. The quality assessment of the model adjustment is thus carried out as a step before interpretation of the gas types and geographical origins results. The MDU maps analysis generates useful insights, with an immediate substantive result and enables the formulation of hypotheses for further analysis and modeling.

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In this paper we present a user-centered interface for a scheduling system. The purpose of this interface is to provide graphical and interactive ways of defining a scheduling problem. To create such user interface an evaluation-centered user interaction development method was adopted: the star life cycle. The created prototype comprises the Task Module and the Scheduling Problem Module. The first one allows users to define a sequence of operations, i.e., a task. The second one enables a scheduling problem definition, which consists in a set of tasks. Both modules are equipped with a set of real time validations to assure the correct definition of the necessary data input for the scheduling module of the system. The usability evaluation allowed us to measure the ease of interaction and observe the different forms of interaction provided by each participant, namely the reactions to the real time validation mechanism.

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We describe a novel approach to explore DNA nucleotide sequence data, aiming to produce high-level categorical and structural information about the underlying chromosomes, genomes and species. The article starts by analyzing chromosomal data through histograms using fixed length DNA sequences. After creating the DNA-related histograms, a correlation between pairs of histograms is computed, producing a global correlation matrix. These data are then used as input to several data processing methods for information extraction and tabular/graphical output generation. A set of 18 species is processed and the extensive results reveal that the proposed method is able to generate significant and diversified outputs, in good accordance with current scientific knowledge in domains such as genomics and phylogenetics.

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Proteins are biochemical entities consisting of one or more blocks typically folded in a 3D pattern. Each block (a polypeptide) is a single linear sequence of amino acids that are biochemically bonded together. The amino acid sequence in a protein is defined by the sequence of a gene or several genes encoded in the DNA-based genetic code. This genetic code typically uses twenty amino acids, but in certain organisms the genetic code can also include two other amino acids. After linking the amino acids during protein synthesis, each amino acid becomes a residue in a protein, which is then chemically modified, ultimately changing and defining the protein function. In this study, the authors analyze the amino acid sequence using alignment-free methods, aiming to identify structural patterns in sets of proteins and in the proteome, without any other previous assumptions. The paper starts by analyzing amino acid sequence data by means of histograms using fixed length amino acid words (tuples). After creating the initial relative frequency histograms, they are transformed and processed in order to generate quantitative results for information extraction and graphical visualization. Selected samples from two reference datasets are used, and results reveal that the proposed method is able to generate relevant outputs in accordance with current scientific knowledge in domains like protein sequence/proteome analysis.

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Mestrado em Engenharia Electrotécnica e de Computadores

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Mestrado em Engenharia Electrotécnica e de Computadores

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Mestrado em Engenharia Informática

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Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. In this paper, a new computer-aided diagnosis (CAD) system for steatosis classification, in a local and global basis, is presented. Bayes factor is computed from objective ultrasound textural features extracted from the liver parenchyma. The goal is to develop a CAD screening tool, to help in the steatosis detection. Results showed an accuracy of 93.33%, with a sensitivity of 94.59% and specificity of 92.11%, using the Bayes classifier. The proposed CAD system is a suitable graphical display for steatosis classification.

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Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. Steatosis is usually a diffuse liver disease, since it is globally affected. However, steatosis can also be focal affecting only some foci difficult to discriminate. In both cases, steatosis is detected by laboratorial analysis and visual inspection of ultrasound images of the hepatic parenchyma. Liver biopsy is the most accurate diagnostic method but its invasive nature suggest the use of other non-invasive methods, while visual inspection of the ultrasound images is subjective and prone to error. In this paper a new Computer Aided Diagnosis (CAD) system for steatosis classification and analysis is presented, where the Bayes Factor, obatined from objective intensity and textural features extracted from US images of the liver, is computed in a local or global basis. The main goal is to provide the physician with an application to make it faster and accurate the diagnosis and quantification of steatosis, namely in a screening approach. The results showed an overall accuracy of 93.54% with a sensibility of 95.83% and 85.71% for normal and steatosis class, respectively. The proposed CAD system seemed suitable as a graphical display for steatosis classification and comparison with some of the most recent works in the literature is also presented.

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Mestrado em Engenharia Electrotécnica e de Computadores. Área de Especialização em Sistemas Autónomos

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Mestrado em Ciências Económicas e Empresariais.

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

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Projecto Final de Mestrado para obtenção do grau de Mestre em Engenharia Informática e de Computadores

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Dissertação para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Vias de Comunicação e Transportes