915 resultados para centric fusion
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Knowing exactly where a mobile entity is and monitoring its trajectory in real-time has recently attracted a lot of interests from both academia and industrial communities, due to the large number of applications it enables, nevertheless, it is nowadays one of the most challenging problems from scientific and technological standpoints. In this work we propose a tracking system based on the fusion of position estimations provided by different sources, that are combined together to get a final estimation that aims at providing improved accuracy with respect to those generated by each system individually. In particular, exploiting the availability of a Wireless Sensor Network as an infrastructure, a mobile entity equipped with an inertial system first gets the position estimation using both a Kalman Filter and a fully distributed positioning algorithm (the Enhanced Steepest Descent, we recently proposed), then combines the results using the Simple Convex Combination algorithm. Simulation results clearly show good performance in terms of the final accuracy achieved. Finally, the proposed technique is validated against real data taken from an inertial sensor provided by THALES ITALIA.
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The foot and the ankle are small structures commonly affected by disorders, and their complex anatomy represent significant diagnostic challenges. SPECT/CT Image fusion can provide missing anatomical and bone structure information to functional imaging, which is particularly useful to increase diagnosis certainty of bone pathology. However, due to SPECT acquisition duration, patient’s involuntary movements may lead to misalignment between SPECT and CT images. Patient motion can be reduced using a dedicated patient support. We aimed at designing an ankle and foot immobilizing device and measuring its efficacy at improving image fusion. Methods: We enrolled 20 patients undergoing distal lower-limb SPECT/CT of the ankle and the foot with and without a foot holder. The misalignment between SPECT and CT images was computed by manually measuring 14 fiducial markers chosen among anatomical landmarks also visible on bone scintigraphy. Analysis of variance was performed for statistical analysis. Results: The obtained absolute average difference without and with support was 5.1±5.2 mm (mean±SD) and 3.1±2.7 mm, respectively, which is significant (p<0.001). Conclusion: The introduction of the foot holder significantly decreases misalignment between SPECT and CT images, which may have clinical influence in the precise localization of foot and ankle pathology.
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Based on the paper presented at the International Conference “Autonomous Systems: inter-relations of technical and societal issues”, organized by IET with the support of the Portuguese-German collaboration project on “Technology Assessment of Autonomous Robotics” (DAAD/CRUP) at FCT-UNL, Biblioteca da UNL, Campus de Caparica on 5-6 November 2009.
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In the last decade, local image features have been widely used in robot visual localization. In order to assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image with those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, in this paper we compare several candidate combiners with respect to their performance in the visual localization task. For this evaluation, we selected the most popular methods in the class of non-trained combiners, namely the sum rule and product rule. A deeper insight into the potential of these combiners is provided through a discriminativity analysis involving the algebraic rules and two extensions of these methods: the threshold, as well as the weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. Furthermore, we address the process of constructing a model of the environment by describing how the model granularity impacts upon performance. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance, confirming the general agreement on the robustness of this rule in other classification problems. The voting method, whilst competitive with the product rule in its standard form, is shown to be outperformed by its modified versions.
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Nowadays the incredible grow of mobile devices market led to the need for location-aware applications. However, sometimes person location is difficult to obtain, since most of these devices only have a GPS (Global Positioning System) chip to retrieve location. In order to suppress this limitation and to provide location everywhere (even where a structured environment doesn’t exist) a wearable inertial navigation system is proposed, which is a convenient way to track people in situations where other localization systems fail. The system combines pedestrian dead reckoning with GPS, using widely available, low-cost and low-power hardware components. The system innovation is the information fusion and the use of probabilistic methods to learn persons gait behavior to correct, in real-time, the drift errors given by the sensors.
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Nowadays there is an increase of location-aware mobile applications. However, these applications only retrieve location with a mobile device's GPS chip. This means that in indoor or in more dense environments these applications don't work properly. To provide location information everywhere a pedestrian Inertial Navigation System (INS) is typically used, but these systems can have a large estimation error since, in order to turn the system wearable, they use low-cost and low-power sensors. In this work a pedestrian INS is proposed, where force sensors were included to combine with the accelerometer data in order to have a better detection of the stance phase of the human gait cycle, which leads to improvements in location estimation. Besides sensor fusion an information fusion architecture is proposed, based on the information from GPS and several inertial units placed on the pedestrian body, that will be used to learn the pedestrian gait behavior to correct, in real-time, the inertial sensors errors, thus improving location estimation.
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In-network storage of data in wireless sensor networks contributes to reduce the communications inside the network and to favor data aggregation. In this paper, we consider the use of n out of m codes and data dispersal in combination to in-network storage. In particular, we provide an abstract model of in-network storage to show how n out of m codes can be used, and we discuss how this can be achieved in five cases of study. We also define a model aimed at evaluating the probability of correct data encoding and decoding, we exploit this model and simulations to show how, in the cases of study, the parameters of the n out of m codes and the network should be configured in order to achieve correct data coding and decoding with high probability.
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The design and development of the swordfish autonomous surface vehicle (ASV) system is discussed. Swordfish is an ocean capable 4.5 m long catamaran designed for network centric operations (with ocean and air going vehicles and human operators). In the basic configuration, Swordfish is both a survey vehicle and a communications node with gateways for broadband, Wi-Fi and GSM transports and underwater acoustic modems. In another configuration, Swordfish mounts a docking station for the autonomous underwater vehicle Isurus from Porto University. Swordfish has an advanced control architecture for multi-vehicle operations with mixed initiative interactions (human operators are allowed to interact with the control loops).
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Demo in Workshop on ns-3 (WNS3 2015). 13 to 14, May, 2015. Castelldefels, Spain.
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A Smart TV é um equipamento novo e em evolução que incorpora um computador e acesso à Internet em ecrãs de grande qualidade. Permite a implementação de serviços interactivos, acesso à Internet e televisão. À medida que a tecnologia melhora, muitos equipamentos estão a tornar-se tão capazes quanto os computadores normais quando se trata de navegação na web e até mesmo vídeo na Internet (Video-on-Demand e streaming de vídeo). O projecto de estágio “NONIUS.TV na Smart TV LG Pro:Centric” foi desenvolvido na empresa Nonius Software que está inserida no ramo das telecomunicações. Uma das suas áreas de actividade está relacionada com o desenvolvimento de plataformas de entretenimento para o mercado hoteleiro, combinando diversos serviços e funcionalidades a pensar no hóspede. Este projecto teve como finalidade implementar alguns dos serviços e funcionalidades já existentes em plataformas que usam uma Set-Top Box da Nonius Software, numa Smart TV, aproveitando também para inovar e criar novos serviços. Nesse conjunto está incluída a implementação de uma Caixa de Mensagens, Serviço de Quartos, Serviço de Desporto e Lazer, Serviços Informativos, um cliente RTSP, um despertador, um sistema de mudança de idioma e outras pequenas funcionalidades desenvolvidas ao longo de toda a aplicação. Esta dissertação apresenta um estudo sobre as tecnologias Smart TV existentes no mercado, assim como as vantagens e desvantagens da sua utilização para este projecto. Após uma análise de requisitos de forma a estruturar e desenhar os serviços e funcionalidades a serem criados para a aplicação, implementou-se um conjunto de serviços, usando a linguagem de programação ActionScript 2.0, que permitiram à empresa disponibilizar um novo produto baseado na televisão Pro:Centric da LG.
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia