Desenvolvimento de um algoritmo para identificação e correção de spikes em espectroscopia Raman de imagem

Raman imaging spectroscopy is a highly useful analytical tool that provides spatial and spectral information on a sample. However, CCD detectors used in dispersive instruments present the drawback of being sensitive to cosmic rays, giving rise to spikes in Raman spectra. Spikes influence variance structures and must be removed prior to the use of multivariate techniques. A new algorithm for correction of spikes in Raman imaging was developed using an approach based on comparison of nearest neighbor pixels. The algorithm showed characteristics including simplicity, rapidity, selectivity and high quality in spike removal from hyperspectral images.

Identificação eletrônica para avaliação do comportamento dos suínos na fase de gestação

The efficiency of swine production performance depends on the herd administration, such as good nutrition, sanitary control, facilities and appropriate environmental conditions. The concept of this production model is directly related with the reduction of selective losses and the process control. Each production segment is controlled to reach the optimization in the system totality, it is necessary to apply animals handling concepts, environmental control implementation, diseases control, nutrition control, information concerning in guaranteeing the animal welfare and individual identification. The present work presents as objective the development of the mathematical model to evaluate interactions among the internal atmosphere of the installation and the thermal animals preference, in the expectation of detecting a relationship among the frequency access to the drinking fountain and the atmosphere conditions - temperature, black globe temperature and relative humidity, using as tool the electronic identification. The results obtained by the mathematical model, allowed to conclude accurately the evaluation of the swine thermal preference correlating with the climatic variables in the pregnancy stage.

Avaliação do uso de identificadores eletrônicos em suínos

Nowadays the consumer market demands a gradually increase in the products' quality control. The manual control that exits, used in animal production, shows ineficiency in warrating an increasing percentual of the desirable quality, so this can only be reached when an effective animal tracebility system is applied, from birth to slaughter. Individual electronic identification presents high importance in this focus, providing information recorded directly from the animal. Electronic traceability uses electronic devices that emit a signal activated by a fixed reader placed where it is needed to record a certain event, or uses a manual reader which allows a higher independence of the operator. Knowing the importance of the electronic identification as a tool for applying traceability in animal production, this research had as objective to evaluate the use of transponders in order to garantee the manual reading as well as the fixed antenna reading. The following implant places were analized in piglet, just after their birth: 1) forehead, 2) external ear lobule, 3) the posterior auricular base, and 4) a transponder inserted in a earing implanted in the ear lobule. The factors of skin damage and migration were analized, as well as the reading efficiency. It was found that the best implant place was the posterior ear base.

Uso de redes neurais artificiais na identificação de vocalização de suínos

Animal welfare has been an important research topic in animal production mainly in its ways of assessment. Vocalization is found to be an interesting tool for evaluating welfare as it provides data in a non-invasive way as well as it allows easy automation of process. The present research had as objective the implementation of an algorithm based on artificial neural network that had the potential of identifying vocalization related to welfare pattern indicatives. The research was done in two parts, the first was the development of the algorithm, and the second its validation with data from the field. Previous records allowed the development of the algorithm from behaviors observed in sows housed in farrowing cages. Matlab® software was used for implementing the network. It was selected a retropropagation gradient algorithm for training the network with the following stop criteria: maximum of 5,000 interactions or error quadratic addition smaller than 0.1. Validation was done with sows and piglets housed in commercial farm. Among the usual behaviors the ones that deserved enhancement were: the feed dispute at farrowing and the eventual risk of involuntary aggression between the piglets or between those and the sow. The algorithm was able to identify through the noise intensity the inherent risk situation of piglets welfare reduction.

Consensos em tireoide: guias para a prática clínica

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Pedagogia do esporte : identificação, discussão e aplicação de procedimentos pedagogicos no processo de ensino-vivencia aprendizagem da modalidade basquetebol

Universidade Estadual de Campinas . Faculdade de Educação Física

A configuração do lazer no espaço das Universidades da Terceira Idade

Universidade Estadual de Campinas . Faculdade de Educação Física

Identificação das causas subjetivas da ansiedade competitiva e das estrategias de superação de atletas de equipes adultas masculinas de basquetebol

Universidade Estadual de Campinas . Faculdade de Educação Física

O perfil fisico e tecnico de atletas de basquetebol feminino : contribuições para identificação do talento esportivo multiplo

Universidade Estadual de Campinas. Faculdade de Educação Física