Uma arquitetura de referência para o processamento distribuído de stream de dados em soluções analíticas de near real-time

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2015.

Collaboration in Virtual Enterprises through the Smart Vortex Suite

Part 12: Collaboration Platforms

Modelo de um observatório municipal do desporto no concelho de Setúbal

A presente dissertação tem como objetivo geral apresentar uma proposta de um modelo de observatório municipal do desporto na administração local, nomeadamente no concelho de Setúbal. Podem ser verificados alguns estudos sobre a temática dos observatórios no sector do desporto (Leite, 2013; Gaspar 2014). Em plena sociedade de informação, as organizações têm de gerir grandes fluxos de dados. Têm de ter capacidade de adaptação à realidade, mas acima de tudo, uma atitude pró-ativa no sentido de anteciparem novos cenários. Segundo Albornoz e Herschmann (2006), os observatórios costumam recolher, registar, acompanhar, interpretar dados, produzir indicadores estatísticos, criar metodologias para codificar, classificar e categorizar informações, estabelecendo conexões entre pessoas que trabalham em áreas similares, bem como monitorizar e analisar tendências. É exigido à administração local, serviços de qualidade e de transparência na adoção das suas politicas desportivas e a existência de um instrumento de recolha de informação, estruturado com base num modelo de análise que permita conhecer, analisar e compreender o estado de um dado contexto desportivo em tempo real, irá permitir a criação de uma base de dados contendo informação atualizada e confiável. Neste contexto, os sistemas de informação, quando desenvolvidos e aplicados, vão permitir a recolha de informação fundamental sobre o comportamento interno da organização (Claudino, 2005). A presente pesquisa representa uma investigação descritiva, tratando-se de um estudo de caso a aplicar na Câmara Municipal de Setúbal. Em termos da recolha de dados, foram utilizadas fontes primárias, com base numa análise documental. Os resultados deste estudo, permitem apresentar uma primeira abordagem de estrutura e processos de funcionamento de um modelo de observatório municipal do desporto com aplicação prática, tendo sido estabelecidos sete categorias de análise fundamentais: i) Atividades Desportivas; ii) Instalações Desportivas, iii) Associativismo; iv) Recursos Humanos; v) Sector Privado; vi) Consumo Desportivo; vii) Divisão Desporto. As estratégias das políticas públicas desportivas adotadas, o planeamento desportivo ou o acesso ao apoio financeiro, exigem que estejam disponíveis um conjunto de informações rigorosas e fidedignas sobre o desempenho, a evolução e as tendências do sector a nível local pelo que a estrutura de um observatório do desporto, irá permitir de uma forma eficiente, eficaz e participativa que se desenvolvam e projetem as políticas desportivas locais que melhor se ajustem à sua realidade. Acreditamos que a existência de um observatório municipal do desporto acrescenta benefícios para os municípios. As mudanças e os desafios económicos colocados hoje, obrigam a novas dinâmicas competitivas.

Trajectory Privacy Preservation in Mobile Wireless Sensor Networks

In recent years, there has been an enormous growth of location-aware devices, such as GPS embedded cell phones, mobile sensors and radio-frequency identification tags. The age of combining sensing, processing and communication in one device, gives rise to a vast number of applications leading to endless possibilities and a realization of mobile Wireless Sensor Network (mWSN) applications. As computing, sensing and communication become more ubiquitous, trajectory privacy becomes a critical piece of information and an important factor for commercial success. While on the move, sensor nodes continuously transmit data streams of sensed values and spatiotemporal information, known as ``trajectory information". If adversaries can intercept this information, they can monitor the trajectory path and capture the location of the source node. This research stems from the recognition that the wide applicability of mWSNs will remain elusive unless a trajectory privacy preservation mechanism is developed. The outcome seeks to lay a firm foundation in the field of trajectory privacy preservation in mWSNs against external and internal trajectory privacy attacks. First, to prevent external attacks, we particularly investigated a context-based trajectory privacy-aware routing protocol to prevent the eavesdropping attack. Traditional shortest-path oriented routing algorithms give adversaries the possibility to locate the target node in a certain area. We designed the novel privacy-aware routing phase and utilized the trajectory dissimilarity between mobile nodes to mislead adversaries about the location where the message started its journey. Second, to detect internal attacks, we developed a software-based attestation solution to detect compromised nodes. We created the dynamic attestation node chain among neighboring nodes to examine the memory checksum of suspicious nodes. The computation time for memory traversal had been improved compared to the previous work. Finally, we revisited the trust issue in trajectory privacy preservation mechanism designs. We used Bayesian game theory to model and analyze cooperative, selfish and malicious nodes' behaviors in trajectory privacy preservation activities.

Data mining approaches to software fault diagnosis

Automatic identification of software faults has enormous practical significance. This requires characterizing program execution behavior and the use of appropriate data mining techniques on the chosen representation. In this paper, we use the sequence of system calls to characterize program execution. The data mining tasks addressed are learning to map system call streams to fault labels and automatic identification of fault causes. Spectrum kernels and SVM are used for the former while latent semantic analysis is used for the latter The techniques are demonstrated for the intrusion dataset containing system call traces. The results show that kernel techniques are as accurate as the best available results but are faster by orders of magnitude. We also show that latent semantic indexing is capable of revealing fault-specific features.

TrendMiner: Large-scale Cross-lingual Trend Mining Summarization of Real-time Media Streams

El reciente crecimiento masivo de medios on-line y el incremento de los contenidos generados por los usuarios (por ejemplo, weblogs, Twitter, Facebook) plantea retos en el acceso e interpretación de datos multilingües de manera eficiente, rápida y asequible. El objetivo del proyecto TredMiner es desarrollar métodos innovadores, portables, de código abierto y que funcionen en tiempo real para generación de resúmenes y minería cross-lingüe de medios sociales a gran escala. Los resultados se están validando en tres casos de uso: soporte a la decisión en el dominio financiero (con analistas, empresarios, reguladores y economistas), monitorización y análisis político (con periodistas, economistas y políticos) y monitorización de medios sociales sobre salud con el fin de detectar información sobre efectos adversos a medicamentos.

Data mining for lifetime prediction of metallic components

The ability to accurately predict the lifetime of building components is crucial to optimizing building design, material selection and scheduling of required maintenance. This paper discusses a number of possible data mining methods that can be applied to do the lifetime prediction of metallic components and how different sources of service life information could be integrated to form the basis of the lifetime prediction model

Effective web service discovery using a combination of a semantic model and a data mining technique

With the advent of Service Oriented Architecture, Web Services have gained tremendous popularity. Due to the availability of a large number of Web services, finding an appropriate Web service according to the requirement of the user is a challenge. This warrants the need to establish an effective and reliable process of Web service discovery. A considerable body of research has emerged to develop methods to improve the accuracy of Web service discovery to match the best service. The process of Web service discovery results in suggesting many individual services that partially fulfil the user’s interest. By considering the semantic relationships of words used in describing the services as well as the use of input and output parameters can lead to accurate Web service discovery. Appropriate linking of individual matched services should fully satisfy the requirements which the user is looking for. This research proposes to integrate a semantic model and a data mining technique to enhance the accuracy of Web service discovery. A novel three-phase Web service discovery methodology has been proposed. The first phase performs match-making to find semantically similar Web services for a user query. In order to perform semantic analysis on the content present in the Web service description language document, the support-based latent semantic kernel is constructed using an innovative concept of binning and merging on the large quantity of text documents covering diverse areas of domain of knowledge. The use of a generic latent semantic kernel constructed with a large number of terms helps to find the hidden meaning of the query terms which otherwise could not be found. Sometimes a single Web service is unable to fully satisfy the requirement of the user. In such cases, a composition of multiple inter-related Web services is presented to the user. The task of checking the possibility of linking multiple Web services is done in the second phase. Once the feasibility of linking Web services is checked, the objective is to provide the user with the best composition of Web services. In the link analysis phase, the Web services are modelled as nodes of a graph and an allpair shortest-path algorithm is applied to find the optimum path at the minimum cost for traversal. The third phase which is the system integration, integrates the results from the preceding two phases by using an original fusion algorithm in the fusion engine. Finally, the recommendation engine which is an integral part of the system integration phase makes the final recommendations including individual and composite Web services to the user. In order to evaluate the performance of the proposed method, extensive experimentation has been performed. Results of the proposed support-based semantic kernel method of Web service discovery are compared with the results of the standard keyword-based information-retrieval method and a clustering-based machine-learning method of Web service discovery. The proposed method outperforms both information-retrieval and machine-learning based methods. Experimental results and statistical analysis also show that the best Web services compositions are obtained by considering 10 to 15 Web services that are found in phase-I for linking. Empirical results also ascertain that the fusion engine boosts the accuracy of Web service discovery by combining the inputs from both the semantic analysis (phase-I) and the link analysis (phase-II) in a systematic fashion. Overall, the accuracy of Web service discovery with the proposed method shows a significant improvement over traditional discovery methods.

Improving the management of building life cycle : a data mining approach

The construction industry has adapted information technology in its processes in terms of computer aided design and drafting, construction documentation and maintenance. The data generated within the construction industry has become increasingly overwhelming. Data mining is a sophisticated data search capability that uses classification algorithms to discover patterns and correlations within a large volume of data. This paper presents the selection and application of data mining techniques on maintenance data of buildings. The results of applying such techniques and potential benefits of utilising their results to identify useful patterns of knowledge and correlations to support decision making of improving the management of building life cycle are presented and discussed.

Using Agents for Mining Maintenance Data while interacting in 3D Objectoriented Virtual Environments

This report demonstrates the development of: (a) object-oriented representation to provide 3D interactive environment using data provided by Woods Bagot; (b) establishing basis of agent technology for mining building maintenance data, and (C) 3D interaction in virtual environments using object-oriented representation. Applying data mining over industry maintenance database has been demonstrated in the previous report.