Neural network based on adaptive resonance theory with continuous training for multi-configuration transient stability analysis of electric power systems

This work presents a methodology to analyze electric power systems transient stability for first swing using a neural network based on adaptive resonance theory (ART) architecture, called Euclidean ARTMAP neural network. The ART architectures present plasticity and stability characteristics, which are very important for the training and to execute the analysis in a fast way. The Euclidean ARTMAP version provides more accurate and faster solutions, when compared to the fuzzy ARTMAP configuration. Three steps are necessary for the network working, training, analysis and continuous training. The training step requires much effort (processing) while the analysis is effectuated almost without computational effort. The proposed network allows approaching several topologies of the electric system at the same time; therefore it is an alternative for real time transient stability of electric power systems. To illustrate the proposed neural network an application is presented for a multi-machine electric power systems composed of 10 synchronous machines, 45 buses and 73 transmission lines. (C) 2010 Elsevier B.V. All rights reserved.

Does bench model fidelity interfere in the acquisition of suture skills by novice medical students?

OBJETIVO: Embora vários modelos de bancada inanimados tenham sido descritos para o treinamento de habilidades de sutura, até o momento, não existe um método ideal para esse ensino e aprendizagem durante a formação médica. O objetivo foi avaliar se a fidelidade dos modelos de bancada interfere na aquisição de habilidades de sutura em estudantes de medicina iniciantes na prática cirúrgica. MÉTODOS: 36 estudantes de medicina sem exposição prévia a habilidades cirúrgicas foram randomizados em três grupos (n = 12): treinamento de suturas baseado em materiais didáticos (controle); treinamento de suturas em modelo de baixa-fidelidade (modelo de bancada de etileno vinil acetato); ou treinamento de suturas em modelo de alta-fidelidade (modelo de bancada de pele de pata de porco). Foram aplicados pré e pós-testes (realização de pontos simples e pontos subdérmicos invertidos em língua de boi). Três ferramentas (Global Rating Scale com avaliação cega, tamanho do efeito e autopercepção da confiança baseada em uma escala de Likert) foram utilizadas para mensurar todas as performances de sutura. RESULTADOS: A análise após o treinamento demonstrou que os estudantes que treinaram nos modelos tiveram um melhor (p < 0.0000) desempenho na avaliação pela Global Rating Scale, quando comparados com o controle, independente da fidelidade do modelo. A magnitude do efeito (treinamento) foi considerada grande (> 0.80) em todas as mensurações. Após o treinamento os alunos sentiram-se mais confiantes (p < 0.0000) para executarem os dois tipos de suturas. CONCLUSÃO: A aquisição de habilidades de suturas no modelo de baixa fidelidade foi semelhante à prática no modelo de alta fidelidade, sendo que a melhora no desempenho dos participantes que treinaram nesses dois modelos foi superior à aprendizagem baseada em materiais didáticos.

Avaliação de programas de treinamento em manejo racional de bovinos em frigoríficos para melhoria do bem-estar animal

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise da estabilidade transitória via rede neural Art-Artmap fuzzy Euclidiana modificada com treinamento continuado

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Morphological analysis of colon goblet cells and submucosa in type I diabetic rats submitted to physical training

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Histochemical and ultrastructural analysis of hepatic glycogen and collagen fibers in alloxan-induced diabetic rats submitted to long-term physical training

Alterations in liver functions are common among diabetic patients, and many symptoms in the liver have been reported, including changes in glycogen stores and in the amount of collagen fibers. The practice of physical training and its morphological effects in this organ, however, are scarcely studied. In order to observe the morphological effects of alloxan-induced diabetes and the alterations arising from the practice of long-term chronic physical training in the liver, samples were collected and processed, and then analyzed by means of the histochemical techniques Periodic Acid-Schiff and Picrosirius-Hematoxylin, and ultrastructural cytochemical test of Afzelius. Through evaluation of the tissue, it was observed a drastic reduction in hepatic glycogen stores of sedentary diabetics, recovered in trained diabetic rats. Furthermore, it was detected a decrease in the content of perisinusoidal collagen fibers in the diabetic liver, also recovered due to the development of a training protocol. On ultrastructural level, cytochemical analysis confirmed the loss of glycogen and the recovery obtained by training. In conclusion, the practice of a long-term chronic physical training protocol may be considered an important assistant in the treatment of diabetes, mitigating the occurrence of possible damages to liver tissue. © 2011 Elsevier Ltd.

Therapist’s directive and nondirective behavior: analysis of their effects in a parent training group

The study described the interaction between therapist and clients in a group intervention with two mothers and a grandmother. Five out of thirteen taped sessions were designated for analysis. Main results: a) therapist’s categories that stood out: approval, recommendation, interpretation, information and information request; b) clients’ categories that stood out: report, agreement, relation, and opposition, c) the probability for recommendation coupled with use of approval exceeded the probability of occurrence of other combinations. Possible explanations for the results were offered and new research questions were raised.

Corrective shoeing in horses: analysis of the adaptation period to the new condition imposed

O ferrageamento corretivo é um método comumente ma Dvideow. O nível de significância adotado foi de 5%. No utilizado para alterar o padrão do andamento dos animais, presente estudo, não houve diferença significativa entre os assim como na terapêutica de diversas afecções do siste-dias avaliados, a elevação em seis graus da pinça ou talões ma locomotor dos equinos. No entanto, não existem, até não gerou desconforto durante a passada, portanto, os ani o momento, estudos científicos que revelem o período de mais podem retornar às atividades regulares de exercício e adaptação do andamento dos animais a este tipo de in-treinamento imediatamente após o ferrageamento. tervenção.O objetivo deste estudo foi avaliar o período de adaptação à ferraduras com elevação em seis graus da pinça ou talões em equinos caminhando em esteira rolante. O período de adaptação à ferradura foi avaliado nos tempos 0, 48 e 96 horas após cada tipo de ferrageamento proposto. Os animais foram gravados caminhando em esteira rolante. O comprimento da passada e a análise qualitativa do andamento foram realizados com o auxílio do programa Dvideow. O nível de significância adotado foi de 5%. No presente estudo, não houve diferença significativa entre os dias avaliados, a elevação em seis graus da pinça ou talões não gerou desconforto durante a passada, portanto, os animais podem retornar às atividades regulares de exercício e treinamento imediatamente após o ferrageamento.

Endurance training stimulates growth and survival pathways and the redox balance in rat pancreatic islets

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A computational tool to assist the analysis of the transformer behavior related to lightning

This paper proposes the application of computational intelligence techniques to assist complex problems concerning lightning in transformers. In order to estimate the currents related to lightning in a transformer, a neural tool is presented. ATP has generated the training vectors. The input variables used in Artificial Neural Networks (ANN) were the wave front time, the wave tail time, the voltage variation rate and the output variable is the maximum current in the secondary of the transformer. These parameters can define the behavior and severity of lightning. Based on these concepts and from the results obtained, it can be verified that the overvoltages at the secondary of transformer are also affected by the discharge waveform in a similar way to the primary side. By using the tool developed, the high voltage process in the distribution transformers can be mapped and estimated with more precision aiding the transformer project process, minimizing empirics and evaluation errors, and contributing to minimize the failure rate of transformers. (C) 2011 Elsevier Ltd. All rights reserved.

Transient stability analysis of electric energy systems via a fuzzy ART-ARTMAP neural network

This work presents a methodology to analyze transient stability (first oscillation) of electric energy systems, using a neural network based on ART architecture (adaptive resonance theory), named fuzzy ART-ARTMAP neural network for real time applications. The security margin is used as a stability analysis criterion, considering three-phase short circuit faults with a transmission line outage. The neural network operation consists of two fundamental phases: the training and the analysis. The training phase needs a great quantity of processing for the realization, while the analysis phase is effectuated almost without computation effort. This is, therefore the principal purpose to use neural networks for solving complex problems that need fast solutions, as the applications in real time. The ART neural networks have as primordial characteristics the plasticity and the stability, which are essential qualities to the training execution and to an efficient analysis. The fuzzy ART-ARTMAP neural network is proposed seeking a superior performance, in terms of precision and speed, when compared to conventional ARTMAP, and much more when compared to the neural networks that use the training by backpropagation algorithm, which is a benchmark in neural network area. (c) 2005 Elsevier B.V. All rights reserved.

Sensitivity analysis by neural networks applied to power systems transient stability

This work presents a procedure for transient stability analysis and preventive control of electric power systems, which is formulated by a multilayer feedforward neural network. The neural network training is realized by using the back-propagation algorithm with fuzzy controller and adaptation of the inclination and translation parameters of the nonlinear function. These procedures provide a faster convergence and more precise results, if compared to the traditional back-propagation algorithm. The adaptation of the training rate is effectuated by using the information of the global error and global error variation. After finishing the training, the neural network is capable of estimating the security margin and the sensitivity analysis. Considering this information, it is possible to develop a method for the realization of the security correction (preventive control) for levels considered appropriate to the system, based on generation reallocation and load shedding. An application for a multimachine power system is presented to illustrate the proposed methodology. (c) 2006 Elsevier B.V. All rights reserved.

Identification of lubricant contamination by biodiesel using vibration analysis and neural network

Purpose - The purpose of this paper is to provide information on lubricant contamination by biodiesel using vibration and neural network.Design/methodology/approach - The possible contamination of lubricants is verified by analyzing the vibration and neural network of a bench test under determinated conditions.Findings - Results have shown that classical signal analysis methods could not reveal any correlation between the signal and the presence of contamination, or contamination grade. on other hand, the use of probabilistic neural network (PNN) was very successful in the identification and classification of contamination and its grade.Research limitations/implications - This study was done for some specific kinds of biodiesel. Other types of biodiesel could be analyzed.Practical implications Contamination information is presented in the vibration signal, even if it is not evident by classical vibration analysis. In addition, the use of PNN gives a relatively simple and easy-to-use detection tool with good confidence. The training process is fast, and allows implementation of an adaptive training algorithm.Originality/value - This research could be extended to an internal combustion engine in order to verify a possible contamination by biodiesel.

Training on synthetic ethylene-vinyl acetate bench model allows novice medical students to acquire suture skills

PURPOSE: To assess the acquisition of suture skills by training on ethylene-vinyl acetate bench model in novice medical students.METHODS: Sixteen medical students without previous surgery experience (novices) were randomly divided into two groups. During one hour group A trained sutures on ethylene-vinyl acetate (EVA) bench model with feedback of instructors, while group B (control) received a faculty-directed training based on books and instructional videos. All students underwent a both pre-and post-tests to perform two-and three-dimensional sutures on ox tongue. All recorded performances were evaluated by two blinded evaluators, using the Global Rating Scale.RESULTS: Although both groups have had a better performance (p<0.05) in the post-test when compared with the pre-test, the analysis of post-test showed that group A (EVA) had a better performance (p<0.05) when compared with group B (control).CONCLUSION: The ethylene vinyl acetate bench model allowed the novice students to acquire suture skills faster when compared to the traditional model of teaching.