85 resultados para Mineração de dados (Computação)


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Sustainability has been moving up on the business agenda in recent decades, and many methods to assess corporate sustainability have already been created. One of the most used and reliable methods is the Sustainability Reporting Guidelines of the Global Reporting Initiative (GRI). Given the importance of sustainability for society and organizations, this study examined sustainability reports published by mining companies – Alcoa, Vale and Samarco – since 2006. The objective was to verify the indicators that contribute most to the minimization of environmental impacts and the improvement of environmental performance. The methodology consisted of collecting and analyzing data from the GRI sustainability reports. It was discovered that the sustainability reports helped the companies to identify improvement opportunities and it is essential companies provide in their reports an economic, environmental and social context of their activities. Furthermore, it was found out that the indicators related to atmospheric emissions, solid waste generation, environmental protection expenditure, and the consumption of raw materials, energy and water are the ones more attached to the production process, which means they are the main contributors for the environmental performance improvement

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This work aims viewing weather information, by building isosurfaces enabling enjoy the advantages of three-dimensional geometric models, to communicate the meaning of the data used in a clear and efficient way. The evolving technology of data processing makes possible the interpretation of masses of data increasing, through robust algorithms. In meteorology, in particular, we can benefit from this fact, due to the large amount of data required for analysis and statistics. The manipulation of data, by users from other areas, is facilitated by the choice of algorithm and the tools involved in this work. The project was further developed into distinct modules, increasing their flexibility and reusability for future studies

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The transportation of oil through polyducts implies a concern related to safety and environmental impacts they may cause, especially when exposed to risks that affect their integrity. Among the various anthropogenic activities included in this scenario, mining can aggravate, increase the risks and degrade the environment. Since these polyducts go through significant extensions, remote sensing has great applicability as a tool for data acquisition. For this, change detection techniques were used to monitor mining activities in a defined study area in the state of Rio de Janeiro, along the duct ORBEL. The characterization of the study area and the mining activities were developed through bibliographical data. The satellite images processing and the application of change detection technique were performed in two scenes for the years 2002 and 2010. The growth in the mining area was about 6.67 times and it was possible to identify types of extraction involved which can represent direct risks to the pipeline

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In this project the Pattern Recognition Problem is approached with the Support Vector Machines (SVM) technique, a binary method of classification that provides the best solution separating the data in the better way with a hiperplan and an extension of the input space dimension, as a Machine Learning solution. The system aims to classify two classes of pixels chosen by the user in the interface in the interest selection phase and in the background selection phase, generating all the data to be used in the LibSVM library, a library that implements the SVM, illustrating the library operation in a casual way. The data provided by the interface is organized in three types, RGB (Red, Green and Blue color system), texture (calculated) or RGB + texture. At last the project showed successful results, where the classification of the image pixels was showed as been from one of the two classes, from the interest selection area or from the background selection area. The simplest user view of results classification is the RGB type of data arrange, because it’s the most concrete way of data acquisition

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Changes are occurring worldwide, including the area of positioning using Global Navigation Satellite Systems in mobile devices such as mobile phones or laptops. This is due to the great improvement and availability of Internet services to these mobile devices. The accuracy and speed of data transmission for these devices makes the technology of sending / receiving data via an internet targeted for optimization. The optimization could allow obtaining, in real-time, coordinates (latitude, longitude and altitude) of suitable quality for users of GPS (Global Positioning System) devices that have wireless Internet access, such as those used to control the eet, locomotion, navigation, agriculture, etc. . The use of the protocol NTRIP (Networked Transport of RTCM via Internet Protocol) in GPS applications is growing every day. Applications are available in C, which creates an opportunity for development with a focus on multiplatform environments. In this context, we propose an application, implemented in a multiplatform environment and the use of NTRIP, able to run on a mobile device for receiving GNSS data

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T he people’s daily lives are surrounded by computing devices, with increasing resources (sensors) and, with increasing processing. How these devices communicate is still not natural and This retards the growth of Ubiquitous Computing. This paper presents a way in which these devices can communicate using Jini technology and concepts of Service Oriented Architecture, applying these concepts in a test case of Ubiquitous Computing. To conduct the test case was constructed a fictitious system for management of a soccer championship, where users can interact with each other and with the system in a simplified way, have access to data in real time of the championship during the event. This communication is performed by services built using Jini technology, which were based on key SOA concepts, such as modularity and reusability

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Pós-graduação em Ciência da Computação - IBILCE

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Pós-graduação em Ciência da Computação - IBILCE

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Pós-graduação em Ciência da Computação - IBILCE

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Ciência da Computação - IBILCE