11 resultados para Facial Object Based Method

em Universidade Federal do Rio Grande do Norte(UFRN)


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AIRES, Kelson R. T. ; ARAÚJO, Hélder J. ; MEDEIROS, Adelardo A. D. . Plane Detection from Monocular Image Sequences. In: VISUALIZATION, IMAGING AND IMAGE PROCESSING, 2008, Palma de Mallorca, Spain. Proceedings..., Palma de Mallorca: VIIP, 2008

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AIRES, Kelson R. T.; ARAÚJO, Hélder J.; MEDEIROS, Adelardo A. D. Plane Detection Using Affine Homography. In: CONGRESSO BRASILEIRO DE AUTOMÁTICA, 2008, Juiz de Fora, MG: Anais... do CBA 2008.

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LOPES-DOS-SANTOS, V. , CONDE-OCAZIONEZ, S. ; NICOLELIS, M. A. L. , RIBEIRO, S. T. , TORT, A. B. L. . Neuronal assembly detection and cell membership specification by principal component analysis. Plos One, v. 6, p. e20996, 2011.

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In this work we have elaborated a spline-based method of solution of inicial value problems involving ordinary differential equations, with emphasis on linear equations. The method can be seen as an alternative for the traditional solvers such as Runge-Kutta, and avoids root calculations in the linear time invariant case. The method is then applied on a central problem of control theory, namely, the step response problem for linear EDOs with possibly varying coefficients, where root calculations do not apply. We have implemented an efficient algorithm which uses exclusively matrix-vector operations. The working interval (till the settling time) was determined through a calculation of the least stable mode using a modified power method. Several variants of the method have been compared by simulation. For general linear problems with fine grid, the proposed method compares favorably with the Euler method. In the time invariant case, where the alternative is root calculation, we have indications that the proposed method is competitive for equations of sifficiently high order.

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This work shows a integrated study of modern analog to fluvial reservoirs of Açu Formation (Unit 3). The modern analog studied has been Assu River located in the same named city, Rio Grande do Norte State, Northeast of Brazil. It has been developed a new methodology to parameterizating the fluvial geological bodies by GPR profile (by central frequency antennas of 50, 100 and 200 MHz). The main parameters obtained were width and thickness. Still in the parameterization, orthophotomaps have been used to calculate the canal sinuosity and braided parameters of Assu River. These information are integrated in a database to supply input data in 3D geological models of fluvial reservoirs. It was made an architectural characterization of the deposit by trench description, GPR profile interpretation and natural expositions study to recognize and describe the facies and its associations, external and internal geometries, boundary surfaces and archtetural elements. Finally, a three-dimensional modeling has been built using all the acquired data already in association with real well data of a reservoir which Rio Assu is considered as analogous. Facies simulations have been used simple kriging (deterministic algorithm), SIS and Boolean (object-based, both stochastics). And, for modeling porosities have used the stochastic algorithm SGS

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The study aims to examine the methodology of realistic simulation as facilitator of the teaching-learning process in nursing, and is justified by the possibility to propose conditions that envisage improvements in the training process with a view to assess the impacts attributed to new teaching strategies and learning in the formative areas of health and nursing. Descriptive study with quantitative and qualitative approach, as action research, and focus on teaching from the realistic simulation of Nursing in Primary Care in an institution of public higher education. . The research was developed in the Comprehensive Care Health discipline II, this is offered in the third year of the course in order to prepare the nursing student to the stage of Primary Health Care The study population comprised 40 subjects: 37 students and 3 teachers of that discipline. Data collection was held from February to May 2014 and was performed by using questionnaires and semi structured interviews. To do so, we followed the following sequence: identification of the use of simulation in the discipline target of intervention; consultation with professors about the possibility of implementing the survey; investigation of the syllabus of discipline, objectives, skills and abilities; preparing the plan for the execution of the intervention; preparing the checklist for skills training; construction and execution of simulation scenarios and evaluation of scenarios. Quantitative data were analyzed using simple descriptive statistics, percentage, and qualitative data through collective subject discourse. A high fidelity simulation was inserted in the curriculum of the course of the research object, based on the use of standard patient. Three cases were created and executed. In the students’ view, the simulation contributed to the synthesis of the contents worked at Integral Health Care II discipline (100%), scoring between 8 and 10 (100%) to executed scenarios. In addition, the simulation has generated a considerable percentage of high expectations for the activities of the discipline (70.27%) and is also shown as a strategy for generating student satisfaction (97.30%). Of the 97.30% that claimed to be quite satisfied with the activities proposed by the academic discipline of Integral Health Care II, 94.59% of the sample indicated the simulation as a determinant factor for the allocation of such gratification. Regarding the students' perception about the strategy of simulation, the most prominent category was the possibility of prior experience of practice (23.91%). The nervousness was one of the most cited negative aspects from the experience in simulated scenarios (50.0%). The most representative positive point (63.89%) pervades the idea of approximation with the reality of Primary Care. In addition, professors of the discipline, totaling 3, were trained in the methodology of the simulation. The study highlighted the contribution of realistic simulation in the context of teaching and learning in nursing and highlighted this strategy while mechanism to generate expectation and satisfaction among undergraduate nursing students

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The goal of the power monitoring in electrical power systems is to promote the reliablility as well as the quality of electrical power.Therefore, this dissertation proposes a new theory of power based on wavelet transform for real-time estimation of RMS voltages and currents, and some power amounts, such as active power, reactive power, apparent power, and power factor. The appropriate estimation the of RMS and power values is important for many applications, such as: design and analysis of power systems, compensation devices for improving power quality, and instruments for energy measuring. Simulation and experimental results obtained through the proposed MaximalOverlap Discrete Wavelet Transform-based method were compared with the IEEE Standard 1459-2010 and the commercial oscilloscope, respectively, presenting equivalent results. The proposed method presented good performance for compact mother wavelet, which is in accordance with real-time applications.

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The great interest in nonlinear system identification is mainly due to the fact that a large amount of real systems are complex and need to have their nonlinearities considered so that their models can be successfully used in applications of control, prediction, inference, among others. This work evaluates the application of Fuzzy Wavelet Neural Networks (FWNN) to identify nonlinear dynamical systems subjected to noise and outliers. Generally, these elements cause negative effects on the identification procedure, resulting in erroneous interpretations regarding the dynamical behavior of the system. The FWNN combines in a single structure the ability to deal with uncertainties of fuzzy logic, the multiresolution characteristics of wavelet theory and learning and generalization abilities of the artificial neural networks. Usually, the learning procedure of these neural networks is realized by a gradient based method, which uses the mean squared error as its cost function. This work proposes the replacement of this traditional function by an Information Theoretic Learning similarity measure, called correntropy. With the use of this similarity measure, higher order statistics can be considered during the FWNN training process. For this reason, this measure is more suitable for non-Gaussian error distributions and makes the training less sensitive to the presence of outliers. In order to evaluate this replacement, FWNN models are obtained in two identification case studies: a real nonlinear system, consisting of a multisection tank, and a simulated system based on a model of the human knee joint. The results demonstrate that the application of correntropy as the error backpropagation algorithm cost function makes the identification procedure using FWNN models more robust to outliers. However, this is only achieved if the gaussian kernel width of correntropy is properly adjusted.

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AIRES, Kelson R. T. ; ARAÚJO, Hélder J. ; MEDEIROS, Adelardo A. D. . Plane Detection from Monocular Image Sequences. In: VISUALIZATION, IMAGING AND IMAGE PROCESSING, 2008, Palma de Mallorca, Spain. Proceedings..., Palma de Mallorca: VIIP, 2008

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AIRES, Kelson R. T.; ARAÚJO, Hélder J.; MEDEIROS, Adelardo A. D. Plane Detection Using Affine Homography. In: CONGRESSO BRASILEIRO DE AUTOMÁTICA, 2008, Juiz de Fora, MG: Anais... do CBA 2008.

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LOPES-DOS-SANTOS, V. , CONDE-OCAZIONEZ, S. ; NICOLELIS, M. A. L. , RIBEIRO, S. T. , TORT, A. B. L. . Neuronal assembly detection and cell membership specification by principal component analysis. Plos One, v. 6, p. e20996, 2011.