40 resultados para Relational Databases

em Universidade do Minho


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Dissertação de Mestrado em Engenharia Informática

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Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

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Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

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Nowadays, the vulgarization of information and communication technologies has reached to a level that the majority of people spend a lot of time using software to do regular tasks, ranging from games and ordinary time and weather utilities to some more sophisticated ones, like retail or banking applications. This new way of life is supported by the Internet or by specific applications that changed the image people had about using information and communication technologies. All over the world, the first cycle of studies of educational systems also has been addressed with the justification that this encourages the development of children. Taking this into consideration, we design and develop a visual explorer system for relational databases that can be used by everyone, from “7 to 77”, in an intuitive and easy way, getting immediate results – a new database querying experience. Thus, in this paper we will expose the main characteristics and features of this visual database explorer, showing how it works and how it can be used to execute the most current data manipulation operations over a database.

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O aumento da quantidade de dados gerados que se tem verificado nos últimos anos e a que se tem vindo a dar o nome de Big Data levou a que a tecnologia relacional começasse a demonstrar algumas fragilidades no seu armazenamento e manuseamento o que levou ao aparecimento das bases de dados NoSQL. Estas estão divididas por quatro tipos distintos nomeadamente chave/valor, documentos, grafos e famílias de colunas. Este artigo é focado nas bases de dados do tipo column-based e nele serão analisados os dois sistemas deste tipo considerados mais relevantes: Cassandra e HBase.

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Modeling Extract-Transform-Load (ETL) processes of a Data Warehousing System has always been a challenge. The heterogeneity of the sources, the quality of the data obtained and the conciliation process are some of the issues that must be addressed in the design phase of this critical component. Commercial ETL tools often provide proprietary diagrammatic components and modeling languages that are not standard, thus not providing the ideal separation between a modeling platform and an execution platform. This separation in conjunction with the use of standard notations and languages is critical in a system that tends to evolve through time and which cannot be undermined by a normally expensive tool that becomes an unsatisfactory component. In this paper we demonstrate the application of Relational Algebra as a modeling language of an ETL system as an effort to standardize operations and provide a basis for uncommon ETL execution platforms.

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The MAP-i Doctoral Programme in Informatics, of the Universities of Minho, Aveiro and Porto

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Tese de Doutoramento em Psicologia Básica

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Due to advances in information technology (e.g., digital video cameras, ubiquitous sensors), the automatic detection of human behaviors from video is a very recent research topic. In this paper, we perform a systematic and recent literature review on this topic, from 2000 to 2014, covering a selection of 193 papers that were searched from six major scientific publishers. The selected papers were classified into three main subjects: detection techniques, datasets and applications. The detection techniques were divided into four categories (initialization, tracking, pose estimation and recognition). The list of datasets includes eight examples (e.g., Hollywood action). Finally, several application areas were identified, including human detection, abnormal activity detection, action recognition, player modeling and pedestrian detection. Our analysis provides a road map to guide future research for designing automatic visual human behavior detection systems.

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Earthworks tasks are often regarded in transportation projects as some of the most demanding processes. In fact, sequential tasks such as excavation, transportation, spreading and compaction are strongly based on heavy mechanical equipment and repetitive processes, thus becoming as economically demanding as they are time-consuming. Moreover, actual construction requirements originate higher demands for productivity and safety in earthwork constructions. Given the percentual weight of costs and duration of earthworks in infrastructure construction, the optimal usage of every resource in these tasks is paramount. Considering the characteristics of an earthwork construction, it can be looked at as a production line based on resources (mechanical equipment) and dependency relations between sequential tasks, hence being susceptible to optimization. Up to the present, the steady development of Information Technology areas, such as databases, artificial intelligence and operations research, has resulted in the emergence of several technologies with potential application bearing that purpose in mind. Among these, modern optimization methods (also known as metaheuristics), such as evolutionary computation, have the potential to find high quality optimal solutions with a reasonable use of computational resources. In this context, this work describes an optimization algorithm for earthworks equipment allocation based on a modern optimization approach, which takes advantage of the concept that an earthwork construction can be regarded as a production line.

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In this paper, we present an integrated system for real-time automatic detection of human actions from video. The proposed approach uses the boundary of humans as the main feature for recognizing actions. Background subtraction is performed using Gaussian mixture model. Then, features are extracted from silhouettes and Vector Quantization is used to map features into symbols (bag of words approach). Finally, actions are detected using the Hidden Markov Model. The proposed system was validated using a newly collected real- world dataset. The obtained results show that the system is capable of achieving robust human detection, in both indoor and outdoor environments. Moreover, promising classification results were achieved when detecting two basic human actions: walking and sitting.

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The MAP-i doctoral program of the Universities of Minho, Aveiro and Porto

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Dissertação de mestrado em Bioinformática

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Dissertação de mestrado em Educação Especial (área de especialização em Intervenção Precoce)

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Tese de Doutoramento em Ciências da Comunicação (Especialidade em Teoria da Cultura)