4 resultados para Database System for Alumni Tracking

em Universidade Federal do Rio Grande do Norte(UFRN)


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As a contemporary tendency, it is been evidenced that the environmental changes theme, already admitted as a concernment to international economical and political reality, is also gaining repercussion on industrial and business sector. Firms are implementing actions on trial to minimize their own greenhouse gases (GHG) emissions impacts. However, the great majority of those actions of Corporative Social-Environmental Responsibility (CSR) are referred only to direct emissions of the main production systems. Direct emissions are those derived of an isolate process, without considering the upstream and downstream processes emissions, which respond for the majority of emissions originated because of respective firm‟s production system existence. Because the greenhouse effect occurs globally and the GHG emissions contribute to the environmental changes independently of their origin, it must be taken into account the whole productive life cycle of products and systems, since the energy invested on resources extraction and necessary materials to the final disposal. To do so, it must be investigated all relevant steps of a product/production system life cycle, tracking all activities which emit greenhouse gases, directly or indirectly. This amount of emissions consists in the firm‟s Carbon Footprint. This research purpose is to defend the Carbon Footprint relevance and its adoption viability to be used as an Environmental Indicator on measurement/assessment of CSR. It has been realized a study case on Petrobras‟s seat unity at Natal-Brazil, assessing part of its Carbon Footprint. It has been used the software GEMIS 4.6 to do the emissions quantifying. The items measured were the direct emissions of the own unity vehicles and indirect emissions of offset paper (A4), energy and disposable plastic cups consumed. To 2009, these emissions were 3.811,94 tCO2eq. We may conclude that Carbon Footprint quantification is indispensable to the knowledge of real emissions caused by a productive process existence, must serving as basis to CSR decisions about the environmental changes reversion challenge

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In order to guarantee database consistency, a database system should synchronize operations of concurrent transactions. The database component responsible for such synchronization is the scheduler. A scheduler synchronizes operations belonging to different transactions by means of concurrency control protocols. Concurrency control protocols may present different behaviors: in general, a scheduler behavior can be classified as aggressive or conservative. This paper presents the Intelligent Transaction Scheduler (ITS), which has the ability to synchronize the execution of concurrent transactions in an adaptive manner. This scheduler adapts its behavior (aggressive or conservative), according to the characteristics of the computing environment in which it is inserted, using an expert system based on fuzzy logic. The ITS can implement different correctness criteria, such as conventional (syntactic) serializability and semantic serializability. In order to evaluate the performance of the ITS in relation to others schedulers with exclusively aggressive or conservative behavior, it was applied in a dynamic environment, such as a Mobile Database Community (MDBC). An MDBC simulator was developed and many sets of tests were run. The experimentation results, presented herein, prove the efficiency of the ITS in synchronizing transactions in a dynamic environment

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Visual attention is a very important task in autonomous robotics, but, because of its complexity, the processing time required is significant. We propose an architecture for feature selection using foveated images that is guided by visual attention tasks and that reduces the processing time required to perform these tasks. Our system can be applied in bottom-up or top-down visual attention. The foveated model determines which scales are to be used on the feature extraction algorithm. The system is able to discard features that are not extremely necessary for the tasks, thus, reducing the processing time. If the fovea is correctly placed, then it is possible to reduce the processing time without compromising the quality of the tasks outputs. The distance of the fovea from the object is also analyzed. If the visual system loses the tracking in top-down attention, basic strategies of fovea placement can be applied. Experiments have shown that it is possible to reduce up to 60% the processing time with this approach. To validate the method, we tested it with the feature algorithm known as Speeded Up Robust Features (SURF), one of the most efficient approaches for feature extraction. With the proposed architecture, we can accomplish real time requirements of robotics vision, mainly to be applied in autonomous robotics

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The northern portion of the Rio Grande do Norte State is characterized by intense coastal dynamics affecting areas with ecosystems of moderate to high environmental sensitivity. In this region are installed the main socioeconomic activities of RN State: salt industry, shrimp farm, fruit industry and oil industry. The oil industry suffers the effects of coastal dynamic action promoting problems such as erosion and exposure of wells and pipelines along the shore. Thus came the improvement of such modifications, in search of understanding of the changes which causes environmental impacts with the purpose of detecting and assessing areas with greater vulnerability to variations. Coastal areas under influence oil industry are highly vulnerable and sensitive in case of accidents involving oil spill in the vicinity. Therefore, it was established the geoenvironmental monitoring of the region with the aim of evaluating the entire coastal area evolution and check the sensitivity of the site on the presence of oil. The goal of this work was the implementation of a computer system that combines the needs of insertion and visualization of thematic maps for the generation of Environmental Vulnerability maps, using techniques of Business Intelligence (BI), from vector information previously stored in the database. The fundamental design interest was to implement a more scalable system that meets the diverse fields of study and make the appropriate system for generating online vulnerability maps, automating the methodology so as to facilitate data manipulation and fast results in cases of real time operational decision-making. In database development a geographic area was established the conceptual model of the selected data and Web system was done using the template database PostgreSQL, PostGis spatial extension, Glassfish Web server and the viewer maps Web environment, the GeoServer. To develop a geographic database it was necessary to generate the conceptual model of the selected data and the Web system development was done using the PostgreSQL database system, its spatial extension PostGIS, the web server Glassfish and GeoServer to display maps in Web