863 resultados para "Tracking"
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OBJECTIVE To analyze physical activity during adolescence in participants of the 1993 Pelotas Birth Cohort Study, Brazil. METHODS Data on leisure time physical activity at 11, 15, and 18 years of age were analyzed. At each visit, a cut-off point of 300 min/week was used to classify adolescents as active or inactive. A total of 3,736 participants provided data on physical activity at each of the three age points. RESULTS A significant decline in the proportion of active adolescents was observed from 11 to 18 years of age, particularly among girls (from 32.9% to 21.7%). The proportions of girls and boys who were active at all three age points were 28.0% and 55.1%, respectively. After adjustment for sex, economic status, and skin color, participants who were active at 11 and 15 years of age were 58.0% more likely to be active at 18 years of age compared with those who were inactive at 11 and 15 years of age. CONCLUSIONS Physical activity declined during adolescence and inactivity tended to track over time. Our findings reinforce the need to promote physical activity at early stages of life, because active behavior established early tends to be maintained over time.
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Dissertation presented to obtain a Ph.D degree in Biology, speciality in Molecular Genetics, by Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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Target tracking with bearing-only sensors is a challenging problem when the target moves dynamically in complex scenarios. Besides the partial observability of such sensors, they have limited field of views, occlusions can occur, etc. In those cases, cooperative approaches with multiple tracking robots are interesting, but the different sources of uncertain information need to be considered appropriately in order to achieve better estimates. Even though there exist probabilistic filters that can estimate the position of a target dealing with incertainties, bearing-only measurements bring usually additional problems with initialization and data association. In this paper, we propose a multi-robot triangulation method with a dynamic baseline that can triangulate bearing-only measurements in a probabilistic manner to produce 3D observations. This method is combined with a decentralized stochastic filter and used to tackle those initialization and data association issues. The approach is validated with simulations and field experiments where a team of aerial and ground robots with cameras track a dynamic target.
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In this paper we introduce a formation control loop that maximizes the performance of the cooperative perception of a tracked target by a team of mobile robots, while maintaining the team in formation, with a dynamically adjustable geometry which is a function of the quality of the target perception by the team. In the formation control loop, the controller module is a distributed non-linear model predictive controller and the estimator module fuses local estimates of the target state, obtained by a particle filter at each robot. The two modules and their integration are described in detail, including a real-time database associated to a wireless communication protocol that facilitates the exchange of state data while reducing collisions among team members. Simulation and real robot results for indoor and outdoor teams of different robots are presented. The results highlight how our method successfully enables a team of homogeneous robots to minimize the total uncertainty of the tracked target cooperative estimate while complying with performance criteria such as keeping a pre-set distance between the teammates and the target, avoiding collisions with teammates and/or surrounding obstacles.
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The recent developments on Hidden Markov Models (HMM) based speech synthesis showed that this is a promising technology fully capable of competing with other established techniques. However some issues still lack a solution. Several authors report an over-smoothing phenomenon on both time and frequencies which decreases naturalness and sometimes intelligibility. In this work we present a new vowel intelligibility enhancement algorithm that uses a discrete Kalman filter (DKF) for tracking frame based parameters. The inter-frame correlations are modelled by an autoregressive structure which provides an underlying time frame dependency and can improve time-frequency resolution. The system’s performance has been evaluated using objective and subjective tests and the proposed methodology has led to improved results.
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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores
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Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica
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É possível assistir nos dias de hoje, a um processo tecnológico evolutivo acentuado por toda a parte do globo. No caso das empresas, quer as pequenas, médias ou de grandes dimensões, estão cada vez mais dependentes dos sistemas informatizados para realizar os seus processos de negócio, e consequentemente à geração de informação referente aos negócios e onde, muitas das vezes, os dados não têm qualquer relacionamento entre si. A maioria dos sistemas convencionais informáticos não são projetados para gerir e armazenar informações estratégicas, impossibilitando assim que esta sirva de apoio como recurso estratégico. Portanto, as decisões são tomadas com base na experiência dos administradores, quando poderiam serem baseadas em factos históricos armazenados pelos diversos sistemas. Genericamente, as organizações possuem muitos dados, mas na maioria dos casos extraem pouca informação, o que é um problema em termos de mercados competitivos. Como as organizações procuram evoluir e superar a concorrência nas tomadas de decisão, surge neste contexto o termo Business Intelligence(BI). A GisGeo Information Systems é uma empresa que desenvolve software baseado em SIG (sistemas de informação geográfica) recorrendo a uma filosofia de ferramentas open-source. O seu principal produto baseia-se na localização geográfica dos vários tipos de viaturas, na recolha de dados, e consequentemente a sua análise (quilómetros percorridos, duração de uma viagem entre dois pontos definidos, consumo de combustível, etc.). Neste âmbito surge o tema deste projeto que tem objetivo de dar uma perspetiva diferente aos dados existentes, cruzando os conceitos BI com o sistema implementado na empresa de acordo com a sua filosofia. Neste projeto são abordados alguns dos conceitos mais importantes adjacentes a BI como, por exemplo, modelo dimensional, data Warehouse, o processo ETL e OLAP, seguindo a metodologia de Ralph Kimball. São também estudadas algumas das principais ferramentas open-source existentes no mercado, assim como quais as suas vantagens/desvantagens relativamente entre elas. Em conclusão, é então apresentada a solução desenvolvida de acordo com os critérios enumerados pela empresa como prova de conceito da aplicabilidade da área Business Intelligence ao ramo de Sistemas de informação Geográfica (SIG), recorrendo a uma ferramenta open-source que suporte visualização dos dados através de dashboards.
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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21st Annual Conference of the International Group for Lean Construction – IGLC 21 – Fortaleza, Brazil
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This paper is mainly concerned with the tracking accuracy of Exchange Traded Funds (ETFs) listed on the London Stock Exchange (LSE) but also evaluates their performance and pricing efficiency. The findings show that ETFs offer virtually the same return but exhibit higher volatility than their benchmark. It seems that the pricing efficiency, which should come from the creation and redemption process, does not fully hold as equity ETFs show consistent price premiums. The tracking error of the funds is generally small and is decreasing over time. The risk of the ETF, daily price volatility and the total expense ratio explain a large part of the tracking error. Trading volume, fund size, bid-ask spread and average price premium or discount did not have an impact on the tracking error. Finally, it is concluded that market volatility and the tracking error are positively correlated.
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Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.
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Hospitals have multiple data sources, such as embedded systems, monitors and sensors. The number of data available is increasing and the information are used not only to care the patient but also to assist the decision processes. The introduction of intelligent environments in health care institutions has been adopted due their ability to provide useful information for health professionals, either in helping to identify prognosis or also to understand patient condition. Behind of this concept arises this Intelligent System to track patient condition (e.g. critic events) in health care. This system has the great advantage of being adaptable to the environment and user needs. The system is focused in identifying critic events from data streaming (e.g. vital signs and ventilation) which is particularly valuable for understanding the patient’s condition. This work aims to demonstrate the process of creating an intelligent system capable of operating in a real environment using streaming data provided by ventilators and vital signs monitors. Its development is important to the physician because becomes possible crossing multiple variables in real-time by analyzing if a value is critic or not and if their variation has or not clinical importance.
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Dissertação de mestrado em Média Interativos
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FUNDAMENTO: A alta e crescente prevalência de Cardiomiopatia Dilatada (CMD) representa sério problema de saúde pública. Novas tecnologias vêm sendo utilizadas objetivando diagnósticos mais sofisticados, que melhorem a abordagem terapêutica. Nesse cenário, o Speckle Tracking (STE) utiliza marcadores miocárdicos naturais para analisar a deformação sistólica do Ventrículo Esquerdo (VE). OBJETIVO: Mensurar o strain transmural longitudinal global (SG) do VE através do STE em pacientes com CMD grave, comparando os resultados com indivíduos normais e com parâmetros ecocardiográficos consagrados para análise da função sistólica do VE, validando o método nessa população. MÉTODOS: Foram estudados 71 pacientes com CMD grave, (53 ± 12a, 72% homens) e 20 controles (30 ± 8a, 45% homens). Foram obtidos os volumes e a FEVE pela ecocardiografia bi e tridimensional, parâmetros do Doppler, Doppler tecidual e o SG pelo STE. RESULTADOS: Comparados ao grupo controle, os volumes do VE foram maiores no grupo CMD; entretanto, a FEVE e velocidade de pico da onda E foram menores neste último. O índice de performance miocárdica foi maior entre os pacientes. As velocidades do miocárdio pelo Doppler tecidual (S', e', a') foram consideravelmente menores e a relação E/e' foi maior no grupo CMD. O SG apresentou-se diminuído no grupo CMD (-5,5% ± 2,3%), em relação aos controles (-14,0% ± 1,8%). CONCLUSÃO: No presente estudo, o SG foi significativamente menor nos pacientes com CMD grave, abrindo novas perspectivas para abordagens terapêuticas nessa população específica.