950 resultados para Software repository mining. Process mining. Software developer contribution


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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

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Trabalho de Projeto realizado para obtenção do grau de Mestre em Engenharia Informática e de Computadores

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STRIPPING is a software application developed for the automatic design of a randomly packing column where the transfer of volatile organic compounds (VOCs) from water to air can be performed and to simulate it’s behaviour in a steady-state. This software completely purges any need of experimental work for the selection of diameter of the column, and allows a choice, a priori, of the most convenient hydraulic regime for this type of operation. It also allows the operator to choose the model used for the calculation of some parameters, namely between the Eckert/Robbins model and the Billet model for estimating the pressure drop of the gaseous phase, and between the Billet and Onda/Djebbar’s models for the mass transfer. Illustrations of the graphical interface offered are presented.

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Reliable flow simulation software is inevitable to determine an optimal injection strategy in Liquid Composite Molding processes. Several methodologies can be implemented into standard software in order to reduce CPU time. Post-processing techniques might be one of them. Post-processing a finite element solution is a well-known procedure, which consists in a recalculation of the originally obtained quantities such that the rate of convergence increases without the need for expensive remeshing techniques. Post-processing is especially effective in problems where better accuracy is required for derivatives of nodal variables in regions where Dirichlet essential boundary condition is imposed strongly. In previous works influence of smoothness of non-homogeneous Dirichlet condition, imposed on smooth front was examined. However, usually quite a non-smooth boundary is obtained at each time step of the infiltration process due to discretization. Then direct application of post-processing techniques does not improve final results as expected. The new contribution of this paper lies in improvement of the standard methodology. Improved results clearly show that the recalculated flow front is closer to the ”exact” one, is smoother that the previous one and it improves local disturbances of the “exact” solution.

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Este documento consubstancia um trabalho de natureza profissional, submetido a apreciação no âmbito de um pedido de atribuição pelo Instituto Politécnico do Porto do título de Especialista na área científica de Informática, mais concretamente em gestão de projectos e equipas em PMEs de desenvolvimento de software. Nesse sentido, proceder-se-á a uma breve análise do estado da prática relevante, seguida de uma descrição das funções que desempenhei ao longo do meu percurso profissional e dos principais projectos em que tive oportunidade de participar durante o mesmo. Finalmente, o documento procede a uma análise crítica de alguns sucessos e insucessos na aplicação do estado da prática, ilustrados com exemplos reais que vivenciei durante a minha carreira.

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To meet the increasing demands of the complex inter-organizational processes and the demand for continuous innovation and internationalization, it is evident that new forms of organisation are being adopted, fostering more intensive collaboration processes and sharing of resources, in what can be called collaborative networks (Camarinha-Matos, 2006:03). Information and knowledge are crucial resources in collaborative networks, being their management fundamental processes to optimize. Knowledge organisation and collaboration systems are thus important instruments for the success of collaborative networks of organisations having been researched in the last decade in the areas of computer science, information science, management sciences, terminology and linguistics. Nevertheless, research in this area didn’t give much attention to multilingual contexts of collaboration, which pose specific and challenging problems. It is then clear that access to and representation of knowledge will happen more and more on a multilingual setting which implies the overcoming of difficulties inherent to the presence of multiple languages, through the use of processes like localization of ontologies. Although localization, like other processes that involve multilingualism, is a rather well-developed practice and its methodologies and tools fruitfully employed by the language industry in the development and adaptation of multilingual content, it has not yet been sufficiently explored as an element of support to the development of knowledge representations - in particular ontologies - expressed in more than one language. Multilingual knowledge representation is then an open research area calling for cross-contributions from knowledge engineering, terminology, ontology engineering, cognitive sciences, computational linguistics, natural language processing, and management sciences. This workshop joined researchers interested in multilingual knowledge representation, in a multidisciplinary environment to debate the possibilities of cross-fertilization between knowledge engineering, terminology, ontology engineering, cognitive sciences, computational linguistics, natural language processing, and management sciences applied to contexts where multilingualism continuously creates new and demanding challenges to current knowledge representation methods and techniques. In this workshop six papers dealing with different approaches to multilingual knowledge representation are presented, most of them describing tools, approaches and results obtained in the development of ongoing projects. In the first case, Andrés Domínguez Burgos, Koen Kerremansa and Rita Temmerman present a software module that is part of a workbench for terminological and ontological mining, Termontospider, a wiki crawler that aims at optimally traverse Wikipedia in search of domainspecific texts for extracting terminological and ontological information. The crawler is part of a tool suite for automatically developing multilingual termontological databases, i.e. ontologicallyunderpinned multilingual terminological databases. In this paper the authors describe the basic principles behind the crawler and summarized the research setting in which the tool is currently tested. In the second paper, Fumiko Kano presents a work comparing four feature-based similarity measures derived from cognitive sciences. The purpose of the comparative analysis presented by the author is to verify the potentially most effective model that can be applied for mapping independent ontologies in a culturally influenced domain. For that, datasets based on standardized pre-defined feature dimensions and values, which are obtainable from the UNESCO Institute for Statistics (UIS) have been used for the comparative analysis of the similarity measures. The purpose of the comparison is to verify the similarity measures based on the objectively developed datasets. According to the author the results demonstrate that the Bayesian Model of Generalization provides for the most effective cognitive model for identifying the most similar corresponding concepts existing for a targeted socio-cultural community. In another presentation, Thierry Declerck, Hans-Ulrich Krieger and Dagmar Gromann present an ongoing work and propose an approach to automatic extraction of information from multilingual financial Web resources, to provide candidate terms for building ontology elements or instances of ontology concepts. The authors present a complementary approach to the direct localization/translation of ontology labels, by acquiring terminologies through the access and harvesting of multilingual Web presences of structured information providers in the field of finance, leading to both the detection of candidate terms in various multilingual sources in the financial domain that can be used not only as labels of ontology classes and properties but also for the possible generation of (multilingual) domain ontologies themselves. In the next paper, Manuel Silva, António Lucas Soares and Rute Costa claim that despite the availability of tools, resources and techniques aimed at the construction of ontological artifacts, developing a shared conceptualization of a given reality still raises questions about the principles and methods that support the initial phases of conceptualization. These questions become, according to the authors, more complex when the conceptualization occurs in a multilingual setting. To tackle these issues the authors present a collaborative platform – conceptME - where terminological and knowledge representation processes support domain experts throughout a conceptualization framework, allowing the inclusion of multilingual data as a way to promote knowledge sharing and enhance conceptualization and support a multilingual ontology specification. In another presentation Frieda Steurs and Hendrik J. Kockaert present us TermWise, a large project dealing with legal terminology and phraseology for the Belgian public services, i.e. the translation office of the ministry of justice, a project which aims at developing an advanced tool including expert knowledge in the algorithms that extract specialized language from textual data (legal documents) and whose outcome is a knowledge database including Dutch/French equivalents for legal concepts, enriched with the phraseology related to the terms under discussion. Finally, Deborah Grbac, Luca Losito, Andrea Sada and Paolo Sirito report on the preliminary results of a pilot project currently ongoing at UCSC Central Library, where they propose to adapt to subject librarians, employed in large and multilingual Academic Institutions, the model used by translators working within European Union Institutions. The authors are using User Experience (UX) Analysis in order to provide subject librarians with a visual support, by means of “ontology tables” depicting conceptual linking and connections of words with concepts presented according to their semantic and linguistic meaning. The organizers hope that the selection of papers presented here will be of interest to a broad audience, and will be a starting point for further discussion and cooperation.

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Software transactional memory is a promising programming model that adapts many concepts borrowed from the databases world to control concurrent accesses to main memory (RAM) locations. This paper discusses how to support apparently irreversible operations, such as memory allocation and deallocation, within software libraries that will be used in (software memory) transactional contexts, and propose a generic and elegant approach based on a handler system, which provide the means to create and execute compensation actions at key moments during the life-time of a transaction.

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Mecânica

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Informática

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Dissertação apresentada no âmbito do Mestrado em Engenharia Informática na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática

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Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica.

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More than ever, there is an increase of the number of decision support methods and computer aided diagnostic systems applied to various areas of medicine. In breast cancer research, many works have been done in order to reduce false-positives when used as a double reading method. In this study, we aimed to present a set of data mining techniques that were applied to approach a decision support system in the area of breast cancer diagnosis. This method is geared to assist clinical practice in identifying mammographic findings such as microcalcifications, masses and even normal tissues, in order to avoid misdiagnosis. In this work a reliable database was used, with 410 images from about 115 patients, containing previous reviews performed by radiologists as microcalcifications, masses and also normal tissue findings. Throughout this work, two feature extraction techniques were used: the gray level co-occurrence matrix and the gray level run length matrix. For classification purposes, we considered various scenarios according to different distinct patterns of injuries and several classifiers in order to distinguish the best performance in each case described. The many classifiers used were Naïve Bayes, Support Vector Machines, k-nearest Neighbors and Decision Trees (J48 and Random Forests). The results in distinguishing mammographic findings revealed great percentages of PPV and very good accuracy values. Furthermore, it also presented other related results of classification of breast density and BI-RADS® scale. The best predictive method found for all tested groups was the Random Forest classifier, and the best performance has been achieved through the distinction of microcalcifications. The conclusions based on the several tested scenarios represent a new perspective in breast cancer diagnosis using data mining techniques.

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This paper consists in the characterization of medium voltage (MV) electric power consumers based on a data clustering approach. It is intended to identify typical load profiles by selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The best partition is selected using several cluster validity indices. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ behavior. The data-mining-based methodology presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partitions. To validate our approach, a case study with a real database of 1.022 MV consumers was used.

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This paper presents an electricity medium voltage (MV) customer characterization framework supportedby knowledge discovery in database (KDD). The main idea is to identify typical load profiles (TLP) of MVconsumers and to develop a rule set for the automatic classification of new consumers. To achieve ourgoal a methodology is proposed consisting of several steps: data pre-processing; application of severalclustering algorithms to segment the daily load profiles; selection of the best partition, corresponding tothe best consumers’ segmentation, based on the assessments of several clustering validity indices; andfinally, a classification model is built based on the resulting clusters. To validate the proposed framework,a case study which includes a real database of MV consumers is performed.

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Biomédica