Implantação de tecnologia da informação no ensino fundamental público: estudo da confiança em redes de organizações

O objetivo deste trabalho é analisar a confiança entre os parceiros que prestam serviços de Tecnologia da Informação (TI) em uma escola municipal de ensino fundamental de São Caetano do Sul (SP). A pesquisa descritiva-qualitativa foi desenvolvida por meio de estudo de caso único, com a análise da importância de confiar-se nos parceiros que prestam serviços de TI nessa escola. Para a coleta de dados, além de observação direta e pesquisa documental, foi utilizado questionário semiestruturado. Constatou-se que as parcerias existentes na pesquisa realizada resultam na formação de uma rede de organizações no setor público, e que o estabelecimento de confiança é fenômeno complexo. Os atores envolvidos respondentes desta pesquisa não creditam confiança ao relacionamento com os parceiros, mesmo com certa dependência; uma vez que 80% assinalaram respostas negativas em relação a esse conceito; o que não é benéfico, de acordo com o que se vê na teoria. Observou-se ainda que a disponibilidade dos parceiros em colaborar, facilita o estabelecimento da confiança e de relacionamento de longo prazo; visando assim, ao objetivo maior da relação, que é auxiliar o aprendizado dos alunos.

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

Protocolo de roteamento para redes oportunistas utilizando otimização por enxame de partículas

In this research work, a new routing protocol for Opportunistic Networks is presented. The proposed protocol is called PSONET (PSO for Opportunistic Networks) since the proposal uses a hybrid system composed of a Particle Swarm Optimization algorithm (PSO). The main motivation for using the PSO is to take advantage of its search based on individuals and their learning adaptation. The PSONET uses the Particle Swarm Optimization technique to drive the network traffic through of a good subset of forwarders messages. The PSONET analyzes network communication conditions, detecting whether each node has sparse or dense connections and thus make better decisions about routing messages. The PSONET protocol is compared with the Epidemic and PROPHET protocols in three different scenarios of mobility: a mobility model based in activities, which simulates the everyday life of people in their work activities, leisure and rest; a mobility model based on a community of people, which simulates a group of people in their communities, which eventually will contact other people who may or may not be part of your community, to exchange information; and a random mobility pattern, which simulates a scenario divided into communities where people choose a destination at random, and based on the restriction map, move to this destination using the shortest path. The simulation results, obtained through The ONE simulator, show that in scenarios where the mobility model based on a community of people and also where the mobility model is random, the PSONET protocol achieves a higher messages delivery rate and a lower replication messages compared with the Epidemic and PROPHET protocols.

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

Predição não-linear de curvas de produção de petróleo via redes neurais recursivas

One of the main activities in the petroleum engineering is to estimate the oil production in the existing oil reserves. The calculation of these reserves is crucial to determine the economical feasibility of your explotation. Currently, the petroleum industry is facing problems to analyze production due to the exponentially increasing amount of data provided by the production facilities. Conventional reservoir modeling techniques like numerical reservoir simulation and visualization were well developed and are available. This work proposes intelligent methods, like artificial neural networks, to predict the oil production and compare the results with the ones obtained by the numerical simulation, method quite a lot used in the practice to realization of the oil production prediction behavior. The artificial neural networks will be used due your learning, adaptation and interpolation capabilities

Classificação de distúrbios em folhas de macieiras utilizando redes neurais convolucionais.

2016

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.

Tradução & aprendizado de língua estrangeira: o ponto de vista do aluno

This paper reports some exemplary data related to a research project on the role of translation in foreign language teaching-learning. The data were collected through a questionnaire administered to 47 Brazilian ESL learners. Specifically, the points of the analysis are: how the translation process is conceived by the students; why and when the translation is used by the learners in classroom situations; mother tongue/foreign language relationships in this specific context, among other aspects. The findings reveal that translation, when used a mediating resource for foreign language teaching-learning, can promote target language management.

Curva de aprendizado e flutuações a curto e longo prazos com perimetria de freqüência dupla (FDT)

OBJECTIVE: To evaluate the learning effect, short-term fluctuation and long-term fluctuation in healthy subjects undergoing frequency doubling perimetry (FDP). METHODS: Twenty healthy young subjects underwent FDT (program N30, full threshold) in one eye (right). Each subject was tested once in the first three sessions and three times in the fourth session. Both short- and long-term fluctuations were studied as the average fluctuation of all the tested points or as a point-to-point fluctuation. To study the learning effect, the MDs values of the first session were compared to the second, third and fourth sessions. RESULTS: In the short-term analysis (3 examination done in the last session), the total mean sensitivity was 31.91 ± 1.20 dB and the mean MD and PSD were 0.84 ± 1.85 and 3.73 ± 1.55 dB, respectively. The average short-term fluctuation was 1.72 ± 0.38 dB. When the four examination, performed at different visits, were compared, the average mean sensitivity of all sessions and the average long-term fluctuation were 31.75 ± 1.11 and 2.16 ± 0.26 dB, respectively. The MD averages of the first, second, third and fourth tests were 0.11 ± 2.14 dB, 0.47 ± 1.64 dB, 1.16 ± 1.62 dB and 0.98 ± 1.92 dB respectively. The MD difference between the first and the third and between the first and the fourth examinations were statistically significant (p<0.05). CONCLUSION: The threshold sensitivity detected by FDP is influenced by both short- and long-term fluctuations. We observed a mild learning effect that shoud be taken into account whenever a patient undergoes this test for the first time.

Imigrantes bolivianos em São Paulo : a Praça Kantuta e o futebol

Universidade Estadual de Campinas . Faculdade de Educação Física

Avaliação postural em escolares das redes estadual e particular de ensino de primeiro grau

Universidade Estadual de Campinas . Faculdade de Educação Física

As enchentes em Santa Catarina e o aprendizado em pol??ticas p??blicas

O estudo de caso aborda o gerenciamento das crises decorrentes do fen??meno das inunda????es no Vale do Itaja??, em Santa Catarina. Na narrativa apresentada, h?? informa????es sobre a evolu????o da ocupa????o do territ??rio e os respectivos desdobramentos na din??mica ambiental, com ??nfase nas a????es que o setor p??blico adotou para enfrentar os desastres. Os eventos clim??ticos ocorridos em 2008 e 2011 s??o detalhados, com o objetivo de caracterizar a preven????o e a capacidade de resposta que o governo e a sociedade demonstraram

Programa dinheiro direto na escola: PDDE

Trata-se de experi??ncia pioneira na modalidade de descentraliza????o, envolvendo numeroso grupo de cidad??os que n??o tinham experi??ncia com a gest??o dos recursos p??blicos. Este fato vem tendo importante influ??ncia na mudan??a de cultura, dentre outros, na motiva????o participativa da comunidade e no aprendizado dos procedimentos para lidar com dinheiro p??blico. Refor??ou, em alguns estados e munic??pios, seus pr??prios projetos e iniciativas de descentraliza????o de recursos e autonomia das escolas, acelerando tend??ncias em curso nas redes de ensino. A participa????o social na escola, segundo pesquisas, tem se mostrado como importante mecanismo de eleva????o da qualidade do ensino e o PDDE refor??a tal participa????o. A ader??ncia, o engajamento e a aprova????o do PDDE pela comunidade escolar converteram o Programa de governo em uma a????o da sociedade

Redes de capacita????o: a experi??ncia da Escola de Governo e das universidades p??blicas do estado do Paran??

No Estado do Paran??, o movimento de forma????o e desenvolvimento dos servidores p??blicos ?? difundido a partir da cria????o da Escola de Governo, em 2004. Este artigo tem como objetivo apresentar a experi??ncia da constru????o de uma rede de capacita????o em pol??ticas p??blicas voltada ?? qualifica????o dos quadros de carreira de n??vel superior, analisando os desdobramentos e os fatores limitadores da rede. Apresenta a rede de capacita????o constru??da em parceria entre a Escola de Governo do Paran?? e seis Institui????es P??blicas de Ensino Superior (Universidade Estadual de Londrina, Universidade Estadual de Maring??, Universidade Estadual de Ponta Grossa, Universidade do Centro-Oeste do Paran??, Universidade do Oeste do Paran??, e a Universidade Federal do Paran??). A metodologia utilizada neste paper ?? o estudo de caso que relatar?? a constru????o da rede de capacita????o com as seguintes etapas: identifica????o dos diversos atores e a institui????o de c??mara t??cnica para a discuss??o e formata????o de curso de especializa????o que atendesse ??s necessidades e especificidades da Escola de Governo do Paran??; o processo seletivo; o desenvolvimento do Curso de P??s-Gradua????o, pelas Universidades p??blicas parceiras; o acompanhamento do Curso pela equipe da Escola de Governo do Paran??; os projetos de interven????o feitos pelos alunos; a dissemina????o do conhecimento produzido. O ponto alto do trabalho em rede se deu com as discuss??es do Curso na C??mara T??cnica: tem??tica do curso, fontes de recursos, projeto do curso, o p??blico-alvo, o ambiente de aprendizagem, o acesso ?? tecnologia, o suporte acad??mico e administrativo, o acompanhamento e avalia????o, a difus??o/dissemina????o do conhecimento. Dos resultados obtidos a partir da intera????o entre os integrantes da rede destacam-se: 19 turmas de um curso de P??s-Gradua????o em Formula????o e Gest??o de Pol??ticas P??blicas num total de 572 especialistas, al??m da realiza????o de um Semin??rio de Gest??o P??blica no Paran??, da cria????o do Reposit??rio Institucional SabeRES em Gest??o P??blica de acesso livre e da publica????o de livros sobre Gest??o de Pol??ticas P??blicas no Paran??, contendo artigos publicados pelos alunos sobre tem??ticas relacionadas ?? gest??o p??blica. Com isso, o Estado do Paran?? iniciou um processo de constru????o de saberes em gest??o p??blica a partir da reflex??o de suas pr??prias viv??ncias e experi??ncias, e de uma rela????o harmoniosa e inovadora entre produtores de saberes ??? a institui????o acad??mica e a administra????o p??blica ??? os quais criaram condi????es para a constru????o do conhecimento, o que n??o teria sido poss??vel de maneira isolada. Essa rede de conhecimento em pol??ticas p??blicas, por ter sido coletivamente constru??da, revelou que mais importante que o conhecimento em si e o processo da sua constru????o, foi a transposi????o desses resultados para a realidade n??o apenas dos produtores desse conhecimento, mas para todos os que atuam e s??o beneficiados pela gest??o p??blica