49 resultados para ground reaction vector technique
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Mestrado em Engenharia Geotécnica e Geoambiente
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A new flow-injection analytical procedure is proposed for the determination of the total amount of polyphenols in wines; the method is based on the formation of a colored complex between 4-aminoantipyrine and phenols, in the presence of an oxidizing reagent. The oxidizing agents hexacyanoferrate(III), peroxodisulfate, and tetroxoiodate(VII) were tested. Batch trials were first performed to select appropriate oxidizing agents, pH, and concentration ratios of reagents, on the basis of their effect on the stability of the colored complex. Conditions selected as a result of these trials were implemented in a flow-injection analytical system in which the influence of injection volume, flow rate, and reaction- coil length, was evaluated. Under the optimum conditions the total amount of polyphenols, expressed as gallic acid, could be determined within a concentration range of 36 to 544 mg L–1, and with a sensitivity of 344 L mol–1 cm–1 and an RSD <1.1%. The reproducibility of analytical readings was indicative of standard deviations <2%. Interference from sugars, tartaric acid, ascorbic acid, methanol, ammonium sulfate, and potassium chloride was negligible. The proposed system was applied to the determination of total polyphenols in red wines, and enabled analysis of approximately 55 samples h–1. Results were usually precise and accurate; the RSD was <3.9% and relative errors, by the Folin–Ciocalteu method, <5.1%.
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Absolute positioning – the real time satellite based positioning technique that relies solely on global navigation satellite systems – lacks accuracy for several real time application domains. To provide increased positioning quality, ground or satellite based augmentation systems can be devised, depending on the extent of the area to cover. The underlying technique – multiple reference station differential positioning – can, in the case of ground systems, be further enhanced through the implementation of the virtual reference station concept. Our approach is a ground based system made of a small-sized network of three stations where the concept of virtual reference station was implemented. The stations provide code pseudorange corrections, which are combined using a measurement domain approach inversely proportional to the distance from source station to rover. All data links are established trough the Internet.
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This paper analyzes the signals captured during impacts and vibrations of a mechanical manipulator. To test the impacts, a flexible beam is clamped to the end-effector of a manipulator that is programmed in a way such that the rod moves against a rigid surface. Eighteen signals are captured and theirs correlation are calculated. A sensor classification scheme based on the multidimensional scaling technique is presented.
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Este trabalho visa contribuir para o desenvolvimento de um sistema de visão multi-câmara para determinação da localização, atitude e seguimento de múltiplos objectos, para ser utilizado na unidade de robótica do INESCTEC, e resulta da necessidade de ter informação externa exacta que sirva de referência no estudo, caracterização e desenvolvimento de algoritmos de localização, navegação e controlo de vários sistemas autónomos. Com base na caracterização dos veículos autónomos existentes na unidade de robótica do INESCTEC e na análise dos seus cenários de operação, foi efectuado o levantamento de requisitos para o sistema a desenvolver. Foram estudados os fundamentos teóricos, necessários ao desenvolvimento do sistema, em temas relacionados com visão computacional, métodos de estimação e associação de dados para problemas de seguimento de múltiplos objectos . Foi proposta uma arquitectura para o sistema global que endereça os vários requisitos identi cados, permitindo a utilização de múltiplas câmaras e suportando o seguimento de múltiplos objectos, com ou sem marcadores. Foram implementados e validados componentes da arquitectura proposta e integrados num sistema para validação, focando na localização e seguimento de múltiplos objectos com marcadores luminosos à base de Light-Emitting Diodes (LEDs). Nomeadamente, os módulos para a identi cação dos pontos de interesse na imagem, técnicas para agrupar os vários pontos de interesse de cada objecto e efectuar a correspondência das medidas obtidas pelas várias câmaras, método para a determinação da posição e atitude dos objectos, ltro para seguimento de múltiplos objectos. Foram realizados testes para validação e a nação do sistema implementado que demonstram que a solução encontrada vai de encontro aos requisitos, e foram identi cadas as linhas de trabalho para a continuação do desenvolvimento do sistema global.
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TiO2 films have been deposited on ITO substrates by dc reactive magnetron sputtering technique. It has been found that the sputtering pressure is a very important parameter for the structure of the deposited TiO2 films. When the pressure is lower than 1 Pa, the deposited has a dense structure and shows a preferred orientation along the [101] direction. However, the nanorod structure has been obtained as the sputtering pressure is higher than 1 Pa. These nanorods structure TiO2 film shows a preferred orientation along the [110] direction. The x-ray diffraction and the Raman scattering measurements show both the dense and the nanostructure TiO2 films have only an anatase phase, no other phase has been obtained. The results of the SEM show that these TiO2 nanorods are perpendicular to the ITO substrate. The TEM measurement shows that the nanorods have a very rough surface. The dye-sensitized solar cells (DSSCs) have been assembled using these TiO2 nanorod films prepared at different sputtering pressures as photoelectrode. And the effect of the sputtering pressure on the properties of the photoelectric conversion of the DSSCs has been studied.
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Mestrado em Engenharia da Computação e Instrumentação Médica
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Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which simulates the electricity markets environment. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. This paper presents the application of a Support Vector Machines (SVM) based approach to provide decision support to electricity market players. This strategy is tested and validated by being included in ALBidS and then compared with the application of an Artificial Neural Network, originating promising results. The proposed approach is tested and validated using real electricity markets data from MIBEL - Iberian market operator.
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This paper presents several forecasting methodologies based on the application of Artificial Neural Networks (ANN) and Support Vector Machines (SVM), directed to the prediction of the solar radiance intensity. The methodologies differ from each other by using different information in the training of the methods, i.e, different environmental complementary fields such as the wind speed, temperature, and humidity. Additionally, different ways of considering the data series information have been considered. Sensitivity testing has been performed on all methodologies in order to achieve the best parameterizations for the proposed approaches. Results show that the SVM approach using the exponential Radial Basis Function (eRBF) is capable of achieving the best forecasting results, and in half execution time of the ANN based approaches.
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Wind speed forecasting has been becoming an important field of research to support the electricity industry mainly due to the increasing use of distributed energy sources, largely based on renewable sources. This type of electricity generation is highly dependent on the weather conditions variability, particularly the variability of the wind speed. Therefore, accurate wind power forecasting models are required to the operation and planning of wind plants and power systems. A Support Vector Machines (SVM) model for short-term wind speed is proposed and its performance is evaluated and compared with several artificial neural network (ANN) based approaches. A case study based on a real database regarding 3 years for predicting wind speed at 5 minutes intervals is presented.
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O projeto tem como objetivo desenvolver e avaliar um modelo que facilita o acesso para pessoas surdas ou com deficiência auditiva, o acesso ao conteúdo digital - em particular o conteúdo educacional e objetos de aprendizagem – a criação de condições para uma maior inclusão social de surdos e deficientes auditivos. Pretende-se criar um modelo bidirecional, em que permite a pessoas com deficiências auditivas, possam se comunicar com outras pessoas, com a tradução da Língua Gestual Portuguesa (LGP) para a Língua Portuguesa (LP) e que outras pessoas não portadoras de qualquer deficiência auditiva possam por sua vez comunicar com os surdos ou deficientes auditivos através da tradução da LP para a LGP. Há um conjunto de técnicas que poderíamos nos apoiar para desenvolver o modelo e implementar a API de tradução da LGP em LP. Muitos estudos são feitos com base nos modelos escondidos de Markov (HMM) para efetuar o reconhecimento. Recentemente os estudos estão a caminhar para o uso de técnicas como o “Dynamic Time Warping” (DTW), que tem tido mais sucesso do que outras técnicas em termos de performance e de precisão. Neste projeto optamos por desenvolver a API e o Modelo, com base na técnica de aprendizagem Support Vector Machines (SVM) por ser uma técnica simples de implementar e com bons resultados demonstrados em reconhecimento de padrões. Os resultados obtidos utilizando esta técnica de aprendizagem foram bastante ótimos, como iremos descrever no decorrer do capítulo 4, mesmo sabendo que utilizamos dois dispositivos para capturar dados de descrição de cada gesto. Toda esta tese integra-se no âmbito do projeto científico/ investigação a decorrer no grupo de investigação GILT, sob a coordenação da professora Paula Escudeiro e suportado pela Fundação para Ciência e Tecnologia (FCT).
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In recent years, vehicular cloud computing (VCC) has emerged as a new technology which is being used in wide range of applications in the area of multimedia-based healthcare applications. In VCC, vehicles act as the intelligent machines which can be used to collect and transfer the healthcare data to the local, or global sites for storage, and computation purposes, as vehicles are having comparatively limited storage and computation power for handling the multimedia files. However, due to the dynamic changes in topology, and lack of centralized monitoring points, this information can be altered, or misused. These security breaches can result in disastrous consequences such as-loss of life or financial frauds. Therefore, to address these issues, a learning automata-assisted distributive intrusion detection system is designed based on clustering. Although there exist a number of applications where the proposed scheme can be applied but, we have taken multimedia-based healthcare application for illustration of the proposed scheme. In the proposed scheme, learning automata (LA) are assumed to be stationed on the vehicles which take clustering decisions intelligently and select one of the members of the group as a cluster-head. The cluster-heads then assist in efficient storage and dissemination of information through a cloud-based infrastructure. To secure the proposed scheme from malicious activities, standard cryptographic technique is used in which the auotmaton learns from the environment and takes adaptive decisions for identification of any malicious activity in the network. A reward and penalty is given by the stochastic environment where an automaton performs its actions so that it updates its action probability vector after getting the reinforcement signal from the environment. The proposed scheme was evaluated using extensive simulations on ns-2 with SUMO. The results obtained indicate that the proposed scheme yields an improvement of 10 % in detection rate of malicious nodes when compared with the existing schemes.
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Selenium modified ruthenium electrocatalysts supported on carbon black were synthesized using NaBH4 reduction of the metal precursor. Prepared Ru/C electrocatalysts showed high dispersion and very small averaged particle size. These Ru/C electrocatalysts were subsequently modified with Se following two procedures: (a) preformed Ru/carbon catalyst was mixed with SeO2 in xylene and reduced in H2 and (b) Ru metal precursor was mixed with SeO2 followed by reduction with NaBH4. The XRD patterns indicate that a pyrite-type structure was obtained at higher annealing temperatures, regardless of the Ru:Se molar ratio used in the preparation step. A pyrite-type structure also emerged in samples that were not calcined; however, in this case, the pyrite-type structure was only prominent for samples with higher Ru:Se ratios. The characterization of the RuSe/C electrocatalysts suggested that the Se in noncalcined samples was present mainly as an amorphous skin. Preliminary study of activity toward oxygen reduction reaction (ORR) using electrocatalysts with a Ru:Se ratio of 1:0.7 indicated that annealing after modification with Se had a detrimental effect on their activity. This result could be related to the increased particle size of crystalline RuSe2 in heat-treated samples. Higher activity of not annealed RuSe/C catalysts could also be a result of the structure containing amorphous Se skin on the Ru crystal. The electrode obtained using not calcined RuSe showed a very promising performance with a slightly lower activity and higher overpotential in comparison with a commercial Pt/C electrode. Single wall carbon nanohorns (SWNH) were considered for application as ORR electrocatalysts' supports. The characterization of SWNH was carried out regarding their tolerance toward strong catalyzed corrosion conditions. Tests indicated that SWNH have a three times higher electrochemical surface area (ESA) loss than carbon black or Pt commercial electrodes.
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JORNADAS DE ELECTROQUÍMICA E INOVAÇÃO 2013
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13th International Conference on Autonomous Robot Systems (Robotica), 2013