908 resultados para computer-based instrumentation


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Dissertation presented at Faculty of Sciences and Technology of the New University of Lisbon to attain the Master degree in Electrical and Computer Science Engineering

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Dissertation presented at Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa to obtain the Master degree in Electrical and Computer Engineering

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Currently, the teaching-learning process in domains, such as computer programming, is characterized by an extensive curricula and a high enrolment of students. This poses a great workload for faculty and teaching assistants responsible for the creation, delivery, and assessment of student exercises. The main goal of this chapter is to foster practice-based learning in complex domains. This objective is attained with an e-learning framework—called Ensemble—as a conceptual tool to organize and facilitate technical interoperability among services. The Ensemble framework is used on a specific domain: computer programming. Content issues are tacked with a standard format to describe programming exercises as learning objects. Communication is achieved with the extension of existing specifications for the interoperation with several systems typically found in an e-learning environment. In order to evaluate the acceptability of the proposed solution, an Ensemble instance was validated on a classroom experiment with encouraging results.

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The paper presents a multi-robot cooperative framework to estimate the 3D position of dynamic targets, based on bearing-only vision measurements. The uncertainty of the observation provided by each robot equipped with a bearing-only vision system is effectively addressed for cooperative triangulation purposes by weighing the contribution of each monocular bearing ray in a probabilistic manner. The envisioned framework is evaluated in an outdoor scenario with a team of heterogeneous robots composed of an Unmanned Ground and Aerial Vehicle.

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Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Informática pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

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work presented in the context of the European Master’s program in Computational Logic, as the partial requirement for obtaining Master of Science degree in Computational Logic

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Based on the report for the “Project III” unit of the PhD programme on Technology Assessment under the supervision of Prof. António B. Moniz. This report was discussed also at the 2nd Winter School on Technology Assessment held at Universidade Nova de Lisboa, Caparica Campus, Portugal on December 2011.

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A presente dissertação foi desenvolvida nas instalações do laboratório de massa da extinta Direção Regional da Economia do Norte (DRE-Norte), no âmbito da unidade curricular de Dissertação/Projeto/Estágio Profissional (DPEPR) do curso de Mestrado de Instrumentação e Metrologia (MEIM) do Instituto Superior de Engenharia do Porto (ISEP). O laboratório de massa da DRE-Norte dedicava-se, entre outras atividades, à calibração de pesos das classes de exatidão F1 e inferior, definidas na recomendação R111-1:2004 da Organização Internacional de Metrologia Legal (OIML), para valores nominais desde 1 mg até 1 000 kg. Foi implementado um sistema real de calibração de pesos utilizando dois comparadores de massa, com interface de comunicação de dados, com fios e sem fios, para o PC (Personal Computer), com aquisição automática dos dados. Desenvolveu-se uma aplicação informática em Visual Basic com o objetivo de ligar os dois comparadores de massa ao PC e automatizar o processo de calibração de pesos com base no método ABBA. O software desenvolvido foi aplicado num caso real de calibração de pesos em ambiente de intercomparação laboratorial com a participação de sete laboratórios nacionais, entre os quais, o laboratório de massa da DRE-Norte.

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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BACKGROUND: Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. METHOD: The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. RESULTS: The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice.

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Dissertation to obtain the degree of Master in Electrical and Computer Engineering

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Based on the report for “Project IV” unit of the PhD programme on Technology Assessment (Doctoral Conference) at Universidade Nova de Lisboa (December 2011). This thesis research has the supervision of António Moniz (FCT-UNL and ITAS-KIT) and Armin Grunwald (Karlsruhe Institute of Technology-ITAS, Germany). Other members of the thesis committee are Mário Forjaz Secca (FCT-UNL) and Femke Nijboer (University of Twente, Netherlands).

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Dissertação para obtenção do Grau de Mestre em Biotecnologia