848 resultados para Training of


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From 2003-2006, an EU network project ‘Sustaining Animal Health and Food Safety in Organic Farming' (SAFO), was carried out with 26 partners from 20 EU-countries and 4 related partners from 4 candidate or new member states. The focus was the integration of animal health and welfare issues in organic farming with food safety aspects. Four very consistent conclusions became apparent: 1) The climatic, physical and socio-economic conditions vary considerably throughout Europe, leading to different livestock farming systems. This limits the possibility for technology transfer between regions, and creates several challenges for a harmonised regulation, 2) Implementing organic standards at farm level does not always ensure that animal health and welfare reach the high ideals of the organic principles, 3) To overcome these deficiencies, organic farmers and farmer organisations need to take ownership of organic values and, 4) In all participating countries, a strong need for training of farmers and in particular veterinarians in animal health promotion and organic principles was identified. The article presents a summary of papers presented at the five SAFO workshops.

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Recently major processor manufacturers have announced a dramatic shift in their paradigm to increase computing power over the coming years. Instead of focusing on faster clock speeds and more powerful single core CPUs, the trend clearly goes towards multi core systems. This will also result in a paradigm shift for the development of algorithms for computationally expensive tasks, such as data mining applications. Obviously, work on parallel algorithms is not new per se but concentrated efforts in the many application domains are still missing. Multi-core systems, but also clusters of workstations and even large-scale distributed computing infrastructures provide new opportunities and pose new challenges for the design of parallel and distributed algorithms. Since data mining and machine learning systems rely on high performance computing systems, research on the corresponding algorithms must be on the forefront of parallel algorithm research in order to keep pushing data mining and machine learning applications to be more powerful and, especially for the former, interactive. To bring together researchers and practitioners working in this exciting field, a workshop on parallel data mining was organized as part of PKDD/ECML 2006 (Berlin, Germany). The six contributions selected for the program describe various aspects of data mining and machine learning approaches featuring low to high degrees of parallelism: The first contribution focuses the classic problem of distributed association rule mining and focuses on communication efficiency to improve the state of the art. After this a parallelization technique for speeding up decision tree construction by means of thread-level parallelism for shared memory systems is presented. The next paper discusses the design of a parallel approach for dis- tributed memory systems of the frequent subgraphs mining problem. This approach is based on a hierarchical communication topology to solve issues related to multi-domain computational envi- ronments. The forth paper describes the combined use and the customization of software packages to facilitate a top down parallelism in the tuning of Support Vector Machines (SVM) and the next contribution presents an interesting idea concerning parallel training of Conditional Random Fields (CRFs) and motivates their use in labeling sequential data. The last contribution finally focuses on very efficient feature selection. It describes a parallel algorithm for feature selection from random subsets. Selecting the papers included in this volume would not have been possible without the help of an international Program Committee that has provided detailed reviews for each paper. We would like to also thank Matthew Otey who helped with publicity for the workshop.

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The Plaut, McClelland, Seidenberg and Patterson (1996) connectionist model of reading was evaluated at two points early in its training against reading data collected from British children on two occasions during their first year of literacy instruction. First, the network’s non-word reading was poor relative to word reading when compared with the children. Second, the network made more non-lexical than lexical errors, the opposite pattern to the children. Three adaptations were made to the training of the network to bring it closer to the learning environment of a child: an incremental training regime was adopted; the network was trained on grapheme– phoneme correspondences; and a training corpus based on words found in children’s early reading materials was used. The modifications caused a sharp improvement in non-word reading, relative to word reading, resulting in a near perfect match to the children’s data on this measure. The modified network, however, continued to make predominantly non-lexical errors, although evidence from a small-scale implementation of the full triangle framework suggests that this limitation stems from the lack of a semantic pathway. Taken together, these results suggest that, when properly trained, connectionist models of word reading can offer insights into key aspects of reading development in children.

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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.

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CONTEXTUALIZAÇÃO: A dor e a disfunção no complexo articular do ombro é comumente encontrada na prática fisioterapêutica. Essas anormalidades musculoesqueléticas estão relacionadas à instabilidade e inadequado funcionamento cinemático, que dependem da integridade dos tecidos musculares. Assim, no sentido de prevenir e reabilitar esses sintomas, o uso da haste oscilatória vem sendo implantado para melhorar os resultados de técnicas cinesioterapêuticas. OBJETIVOS: Analisar a atividade eletromiográfica (EMG) dos músculos que estabilizam a articulação do ombro durante a realização de exercícios com haste oscilatória e haste não-oscilatória. MÉTODOS: Participaram do estudo 12 voluntárias com idade de 20,4±1,9 anos. Os dados EMG foram coletados nos músculos trapézio superior (TrS), trapézio inferior (TrI) e deltoide médio (DM) durante três diferentes exercícios realizados com haste oscilatória e haste não-oscilatória. O sinal EMG foi analisado no domínio do tempo pelo cálculo do Root Mean Square (RMS). Os valores de RMS foram normalizados pelo valor de pico obtido em todas as tentativas por cada músculo. A análise estatística foi feita com os testes ANOVA para medidas repetidas e post-hoc de Bonferroni. RESULTADOS: A atividade EMG dos músculos TrS, TrI e DM foi significativamente maior nos exercícios com haste oscilatória do que com haste não-oscilatória (todos p<0,001). Não foram significativas as diferenças na ativação desses músculos entre os exercícios. CONCLUSÃO: Os resultados do presente estudo indicaram que a haste oscilatória requisitou maior atividade EMG dos músculos do ombro e, assim, pode ser um instrumento útil no treinamento desses músculos.

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We present a checklist of feather mites known from native birds in Brazil. The list was compiled from a survey of Brazilian records published in indexing databases (e.g. Zoological Records) and from the available literature. To date, 185 nominal species representing 21 families have been recorded from Brazilian birds. Associations with 15 bird orders were found: Anseriformes, Apodiformes, Caprimulgiformes, Ciconiiformes, Columbiformes, Cuculiformes, Falconiformes, Galliformes, Gruiformes, Opisthocomiformes, Passeriformes, Piciformes, Psittaciformes, Tinamiformes and Trogoniformes. These birds sum to 218 species, which represent only 12.4% of all bird species occurring in Brazil. The feather mite fauna of several species-rich and important bird orders in Brazil remain unexplored, including Cathartiformes, Charadriiformes, Coraciiformes, Galbuliformes and Strigiformes. We estimate that between 900 and 5300 feather mite species are expected to occur on Brazilian birds, which is at least five times greater than current records. The training of researchers with expertise in the taxonomy of this group of mites should be stimulated so that there is a compatible number of taxonomists to discover and describe the almost unexplored feather mite fauna in Brazil.

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

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The training and the application of a neural network system for the prediction of occurrences of secondary metabolites belonging to diverse chemical classes in the Asteraceae is described. From a database containing about 604 genera and 28,000 occurrences of secondary metabolites in the plant family, information was collected encompassing nine chemical classes and their respective occurrences for training of a multi-layer net using the back-propagation algorithm. The net supplied as output the presence or absence of the chemical classes as well as the number of compounds isolated from each taxon. The results provided by the net from the presence or absence of a chemical class showed a 89% hit rate; by excluding triterpenes from the analysis, only 5% of the genera studied exhibited errors greater than 10%. Copyright (C) 2004 John Wiley Sons, Ltd.

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This paper is derived from the PhD research entitled "The initial training of Geography teacher in school cartography: a reflective analysis", developed by the program of Post-graduation in Geography of UNESP, campus of Rio Claro. The research is in the final phase, focused on data analysis and final writing of thesis. In this context, it may be stated that the research orientates in the problematic focused at the understanding of how the recent knowledge produced by the school cartography unfolds in the practices of Geography licentiate students. However, at this time, we will discuss about issues related to the research by the theoretical and practical point of view.

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This work presents an investigation into the use of the finite element method and artificial neural networks in the identification of defects in industrial plants metallic tubes, due to the aggressive actions of the fluids contained by them, and/or atmospheric agents. The methodology used in this study consists of simulating a very large number of defects in a metallic tube, using the finite element method. Both variations in width and height of the defects are considered. Then, the obtained results are used to generate a set of vectors for the training of a perceptron multilayer artificial neural network. Finally, the obtained neural network is used to classify a group of new defects, simulated by the finite element method, but that do not belong to the original dataset. The reached results demonstrate the efficiency of the proposed approach, and encourage future works on this subject.

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Includes bibliography

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The advance in the graphic computer's techniques and computer's capacity of processing made possible applications like the human anatomic structures modeling, in order to investigate diseases, surgical planning or even provide images for training of Computer Aided Diagnosis (CAD). On this context, this work exhibits an anatomical model of cardiac structures represented in a tridimensional environment. The model was represented with geometrical elements and has anatomical details, as the different tunics that compose the cardiac wall and measures that preserves the characteristics found on real structures. The validation of the anatomical model was made through quantitative comparations with real structures measures, available on specialized literature. The results obtained, evaluated by two specialists, are compatible with real anatomies, respecting the anatomical particularities. This degree of representation will allow the verification of the influence of radiological parameters, morphometric peculiarities and stage of the cardiac diseases on the quality of the images, as well as on the performance of the CAD. © 2010 IEEE.

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Includes bibliography

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Background: Because of ethical and medico-legal aspects involved in the training of cutaneous surgical skills on living patients, human cadavers and living animals, it is necessary the search for alternative and effective forms of training simulation. Aims: To propose and describe an alternative methodology for teaching and learning the principles of cutaneous surgery in a medical undergraduate program by using a chicken-skin bench model. Materials and Methods: One instructor for every four students, teaching materials on cutaneous surgical skills, chicken trunks, wings, or thighs, a rigid platform support, needled threads, needle holders, surgical blades with scalpel handles, rat-tooth tweezers, scissors, and marking pens were necessary for training simulation. Results: A proposal for simulation-based training on incision, suture, biopsy, and on reconstruction techniques using a chicken-skin bench model distributed in several sessions and with increasing levels of difficultywas structured. Both feedback and objective evaluations always directed to individual students were also outlined. Conclusion: The teaching of a methodology for the principles of cutaneous surgery using a chicken-skin bench model versatile, portable, easy to assemble, and inexpensive is an alternative and complementary option to the armamentarium of methods based on other bench models described. © Indian Journal of Dermatology 2013.