Predição de promotores de Bacillus subtilis usando técnicas de aprendizado de máquina

One of the most important goals of bioinformatics is the ability to identify genes in uncharacterized DNA sequences on world wide database. Gene expression on prokaryotes initiates when the RNA-polymerase enzyme interacts with DNA regions called promoters. In these regions are located the main regulatory elements of the transcription process. Despite the improvement of in vitro techniques for molecular biology analysis, characterizing and identifying a great number of promoters on a genome is a complex task. Nevertheless, the main drawback is the absence of a large set of promoters to identify conserved patterns among the species. Hence, a in silico method to predict them on any species is a challenge. Improved promoter prediction methods can be one step towards developing more reliable ab initio gene prediction methods. In this work, we present an empirical comparison of Machine Learning (ML) techniques such as Na¨ýve Bayes, Decision Trees, Support Vector Machines and Neural Networks, Voted Perceptron, PART, k-NN and and ensemble approaches (Bagging and Boosting) to the task of predicting Bacillus subtilis. In order to do so, we first built two data set of promoter and nonpromoter sequences for B. subtilis and a hybrid one. In order to evaluate of ML methods a cross-validation procedure is applied. Good results were obtained with methods of ML like SVM and Naïve Bayes using B. subtilis. However, we have not reached good results on hybrid database

Estudo e implementação de um controlador preditivo generalizado bilinear compensado adaptativo

The present work presents the study and implementation of an adaptive bilinear compensated generalized predictive controller. This work uses conventional techniques of predictive control and includes techniques of adaptive control for better results. In order to solve control problems frequently found in the chemical industry, bilinear models are considered to represent the dynamics of the studied systems. Bilinear models are simpler than general nonlinear model, however it can to represent the intrinsic not-linearities of industrial processes. The linearization of the model, by the approach to time step quasilinear , is used to allow the application of the equations of the generalized predictive controller (GPC). Such linearization, however, generates an error of prediction, which is minimized through a compensation term. The term in study is implemented in an adaptive form, due to the nonlinear relationship between the input signal and the prediction error.Simulation results show the efficiency of adaptive predictive bilinear controller in comparison with the conventional.

Predição da incrustação em um trocador de calor baseada em redes neurais artificiais

A serious problem that affects an oil refinery s processing units is the deposition of solid particles or the fouling on the equipments. These residues are naturally present on the oil or are by-products of chemical reactions during its transport. A fouled heat exchanger loses its capacity to adequately heat the oil, needing to be shut down periodically for cleaning. Previous knowledge of the best period to shut down the exchanger may improve the energetic and production efficiency of the plant. In this work we develop a system to predict the fouling on a heat exchanger from the Potiguar Clara Camarão Refinery, based on data collected in a partnership with Petrobras. Recurrent Neural Networks are used to predict the heat exchanger s flow in future time. This variable is the main indicator of fouling, because its value decreases gradually as the deposits on the tubes reduce their diameter. The prediction could be used to tell when the flow will have decreased under an acceptable value, indicating when the exchanger shutdown for cleaning will be needed

Atividades estruturais de equações polinomiais numa abordagem histórica por meio de e-book

The present study investigates how the inter-relationship of the content of polynomial equations works with structured activities and with the history of mathematics through a sequence of activities presented in an e-book, so that the result of this research will proceed will result in a didactic and pedagogic proposal for the teaching of polynomial equations in a historical approach via the reported e-book. Therefore, we have considered in theoretical and methodological assumptions of the History of Mathematics, in structured activities and new technologies with an emphasis on e-book tool. We used as a methodological approach the qualitative research, as our research object adjusts to the objectives of this research mode. As methodological instruments, we used the e-book as a synthesis tool of the sequence of activities to be evaluated, while the questionnaires, semi-structured interviews and participant observation were designed to register and analyze the evaluation made by the research, participants in the structured activities. The processing and analysis of data collected though the questionnaires were organized, classified and quantified in summary tables to facilitate visualization, interpretation, understanding, and analysis of these data. As for participant observation was used to contribute to the qualitative analysis of the quantified data. The interviews were synthetically transcribed and qualitatively analyzed. The analysis ratified our research objectives and contributed to improve, approve and indicate the use of e-book for the teaching of polynomial equations. Thus, we consider that this educational product will bring significant contributions to the teaching of mathematical content, in Basic Education

Valores de referência para pressão inspiratória nasal SNIFF na população brasileira

The strength of respiratory muscle are frequently assessed by maximal inspiratory and expiratory pressure, however, the maneuvers to assess PImax and PEmax are difficult for many patients. The sniff nasal inspiratory pressure (SNIP) is a simple and noninvasive technique use to assess inspiratory muscles strength. Reference values have been previous established for SNIP in adults but no previous studies have provided reference values for SNIP in adult Brazilian population. The main objective of this study were propose reference values of SNIP for Brazilian population through establishment of relationship between anthropometric measurements, physical activity profile and SNIP and at the same time compare the values obtained with reference values previously published. We studied 117 subjects (59 male and 58 female) distributed in different age grouped 20-80 years old. The results showed on significant positive relationship between SNIP and height and negative correlation with age (p<0.05). In the multiple linear regression analysis only age continued to have an independent predictive role for the two dependent variables that correlated with SNIP. The values of SNIP found in Brazilian population were higher when compared with predict values of previous studies. The results of this study provide reference equations of SNIP for health Brazilian population from 20 to 80 years old

Equações preditivas para as pressões respiratórias máximas de crianças brasileiras

I ntroduction: The assessment of respiratory muscle strength is important in the diagnosis and monitoring of the respiratory muscles weakness of respiratory and neuromuscular diseases. However, there are still no studies that provide predictive equations and reference values for maximal respiratory pressures for children in our population. Aim: The purpose of this study was to propose predictive equations for maximal respiratory pressures in healthy school children. Method: This is an observational cross-sectional study. 144 healthy children were assessed. They were students from public and private schools in the city of Natal /RN (63 boys and 81 girls), subdivided in age groups of 7-8 and 9-11 years. The students presented the BMI, for age and sex, between 5 and 85 percentile. Maximal respiratory pressures were measured with the digital manometer MVD300 (Globalmed ®). The maximal inspiratory pressure (MIP) and maximal expiratory pressures (MEP) were measured from residual volume and total lung capacity, respectively. The data were analyzed using the SPSS Statistics 15.0 software (Statistical Package for Social Science) by assigning the significance level of 5%. Descriptive analysis was expressed as mean and standard deviation. T'Student test was used for unpaired comparison of averages of the variables. The comparison of measurements obtained with the predicted values in previous studies was performed using the paired t'Student test. The Pearson correlation test was used to verify the correlation of MRP's with the independent variables (age, sex, weight and height). For the equations analysis the stepwise linear regression was used. Results: By analyzing the data, we observed that in the age range studied MIP was significantly higher in boys. The MEP did not differ between boys and girls aged 7 to 8 years, the reverse occurred in the age between 9 and 11 years. The boys had a significant increase in respiratory muscle strength with advancing age. Regardless sex and age, MEP was always higher than the MIP. The reference values found in this study are similar to a sample of Spanish and Canadian children. The two models proposed in previous studies with children from other countries were not able to consistently predict the values observed in this studied population. The variables sex, age and weight correlated with MIP, whereas the MEP was also correlated with height. However, in the regression models proposed in this study, only gender and age were kept exerting influence on the variability of maximal inspiratory and expiratory pressures. Conclusion: This study provides reference values, lower limits of normality and proposes two models that allow predicting, through the independent variables, sex and age, the value of maximal static respiratory pressures in healthy children aged between 7 and 11 years old

Métodos numéricos para resolução de equações diferenciais ordinárias lineares baseados em interpolação por spline

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.

Neurofisiologia hipocampal durante sessões de sono intercaladas por exploração espacial: Reverberação do passado ou predição do futuro?

The ability to predict future rewards or threats is crucial for survival. Recent studies have addressed future event prediction by the hippocampus. Hippocampal neurons exhibit robust selectivity for spatial location. Thus, the activity of hippocampal neurons represents a cognitive map of space during navigation as well as during planning and recall. Spatial selectivity allows the hippocampus to be involved in the formation of spatial and episodic memories, including the sequential ordering of events. On the other hand, the discovery of reverberatory activity in multiple forebrain areas during slow wave and REM sleep underscored the role of sleep on the consolidation of recently acquired memory traces. To this date, there are no studies addressing whether neuronal activity in the hippocampus during sleep can predict regular environmental shifts. The aim of the present study was to investigate the activity of neuronal populations in the hippocampus during sleep sessions intercalated by spatial exploration periods, in which the location of reward changed in a predictable way. To this end, we performed the chronic implantation of 32-channel multielectrode arrays in the CA1 regions of the hippocampus in three male rats of the Wistar strain. In order to activate different neuronal subgroups at each cycle of the task, we exposed the animals to four spatial exploration sessions in a 4-arm elevated maze in which reward was delivered in a single arm per session. Reward location changed regularly at every session in a clockwise manner, traversing all the arms at the end of the daily recordings. Animals were recorded from 2-12 consecutive days. During spatial exploration of the 4-arm elevated maze, 67,5% of the recorded neurons showed firing rate differences across the maze arms. Furthermore, an average of 42% of the neurons showed increased correlation (R>0.3) between neuronal pairs in each arm. This allowed us to sort representative neuronal subgroups for each maze arm, and to analyze the activity of these subgroups across sleep sessions. We found that neuronal subgroups sorted by firing rate differences during spatial exploration sustained these differences across sleep sessions. This was not the case with neuronal subgroups sorted according to synchrony (correlation). In addition, the correlation levels between sleep sessions and waking patterns sampled in each arm were larger for the entire population of neurons than for the rate or synchrony subgroups. Neuronal activity during sleep of the entire neuronal population or subgroups did not show different correlations among the four arm mazes. On the other hand, we verified that neuronal activity during pre-exploration sleep sessions was significantly more similar to the activity patterns of the target arm than neuronal activity during pre-exploration sleep sessions. In other words, neuronal activity during sleep that precedes the task reflects more strongly the location of reward than neuronal activity during sleep that follows the task. Our results suggest that neuronal activity during sleep can predict regular environmental changes

Em direção a uma representação para equações algébricas :uma lógica equacional local

The intervalar arithmetic well-known as arithmetic of Moore, doesn't possess the same properties of the real numbers, and for this reason, it is confronted with a problem of operative nature, when we want to solve intervalar equations as extension of real equations by the usual equality and of the intervalar arithmetic, for this not to possess the inverse addictive, as well as, the property of the distributivity of the multiplication for the sum doesn t be valid for any triplet of intervals. The lack of those properties disables the use of equacional logic, so much for the resolution of an intervalar equation using the same, as for a representation of a real equation, and still, for the algebraic verification of properties of a computational system, whose data are real numbers represented by intervals. However, with the notion of order of information and of approach on intervals, introduced by Acióly[6] in 1991, the idea of an intervalar equation appears to represent a real equation satisfactorily, since the terms of the intervalar equation carry the information about the solution of the real equation. In 1999, Santiago proposed the notion of simple equality and, later on, local equality for intervals [8] and [33]. Based on that idea, this dissertation extends Santiago's local groups for local algebras, following the idea of Σ-algebras according to (Hennessy[31], 1988) and (Santiago[7], 1995). One of the contributions of this dissertation, is the theorem 5.1.3.2 that it guarantees that, when deducing a local Σ-equation E t t in the proposed system SDedLoc(E), the interpretations of t and t' will be locally the same in any local Σ-algebra that satisfies the group of fixed equations local E, whenever t and t have meaning in A. This assures to a kind of safety between the local equacional logic and the local algebras

Predição em modelos de tempo de falha acelerado com efeito aleatório para avaliação de riscos de falha em poços petrolíferos

We considered prediction techniques based on models of accelerated failure time with random e ects for correlated survival data. Besides the bayesian approach through empirical Bayes estimator, we also discussed about the use of a classical predictor, the Empirical Best Linear Unbiased Predictor (EBLUP). In order to illustrate the use of these predictors, we considered applications on a real data set coming from the oil industry. More speci - cally, the data set involves the mean time between failure of petroleum-well equipments of the Bacia Potiguar. The goal of this study is to predict the risk/probability of failure in order to help a preventive maintenance program. The results show that both methods are suitable to predict future failures, providing good decisions in relation to employment and economy of resources for preventive maintenance.

Equações de segundo grau e mudança de variáveis

In this work are presented, as a review and in a historical context, the most used methods to solve quadratic equations. It is also shown the simplest type of change of variables, namely: x = Ay + B where A;B 2 R, and some changes of variables that were used to solve quadratic equations throughout history. Finally, a change of variable, which has been used by the author in the classroom as an alternative method, is presented and the result of this methodoly is illustrated by the responses of a test that was done by the students in classroom

Contribuições de modelagem de equações estruturais na análise de dados em modelos comportamentais de destino turístico

A fragilidade brasileira quanto à competitividade turística é um fato observável nos dados da Organização Mundial do Turismo. O Brasil caiu em 2011, da 45ª para a 52ª posição, apesar de liderar no atributo recursos naturais e estar colocado na 23° em recursos culturais. Assim, grandes interesses e esforços têm sido direcionados para o estudo da competitividade dos produtos e destinos turísticos. O destino turístico é caracterizado por um conjunto complexo e articulado de fatores tangíveis e intangíveis, apresentando alta complexidade, dados de elevada dimensionalidade, não linearidade e comportamento dinâmico, tornando-se difícil a modelagem desses processos por meio de abordagens baseadas em técnicas estatísticas clássicas. Esta tese investigou modelos de equações estruturais e seus algoritmos, aplicados nesta área, analisando o ciclo completo de análise de dados, em um processo confirmatório no desenvolvimento e avaliação de um modelo holístico da satisfação do turista; na validação da estrutura do modelo de medida e do modelo estrutural, por meio de testes de invariância de múltiplos grupos; na análise comparativa dos métodos de estimação MLE, GLS e ULS para a modelagem da satisfação e na realização de segmentação de mercado no setor de destino turístico utilizando mapas auto-organizáveis de Kohonen e sua validação com modelagem de equações estruturais. Aplicações foram feitas em análises de dados no setor de turismo, principal indústria de serviços do Estado do Rio Grande do Norte, tendo sido, teoricamente desenvolvidos e testados empiricamente, modelos de equações estruturais em padrões comportamentais de destino turístico. Os resultados do estudo empírico se basearam em pesquisas com a técnica de amostragem aleatória sistemática, efetuadas em Natal-RN, entre Janeiro e Março de 2013 e forneceram evidências sustentáveis de que o modelo teórico proposto é satisfatório, com elevada capacidade explicativa e preditiva, sendo a satisfação o antecedente mais importante da lealdade no destino. Além disso, a satisfação é mediadora entre a geração da motivação da viagem e a lealdade do destino e que os turistas buscam primeiro à satisfação com a qualidade dos serviços de turismo e, posteriormente, com os aspectos que influenciam a lealdade. Contribuições acadêmicas e gerenciais são mostradas e sugestões de estudo são dadas para trabalhos futuros.

Contribuições ao estudo de modelagem de equações estruturais na avaliação da satisfação do cliente de serviços de comunicações móveis

No mercado de telecomunicações as transformações tecnológicas das últimas décadas aliaram-se a um cenário formado por empresas de alta tecnologia que caracterizam o setor de comunicações móveis pessoais em todo mundo. Neste contexto, as empresas deste setor preocupam-se cada vez mais com a competitividade, oferta de serviços, área de atendimento, demanda reprimida e a lealdade do cliente. Estudos de comportamento do consumidor pesquisam a satisfação e lealdade de clientes como fatores básicos para relações bem sucedidas e duradouras com as empresas. A complexidade das relações entre variáveis na avaliação da satisfação do cliente em comunicações móveis pode ser adequadamente pesquisada com a utilização de métodos estatísticos multivariados. Essa tese analisou as relações causais envolvendo os antecedentes e consequentes associados à satisfação do cliente, no segmento de comunicações móveis, bem como desenvolveu e validou um modelo comportamental do cliente no uso deste serviço, buscando explicar as relações entre os construtos envolvidos: satisfação, qualidade dos serviços, valor percebido, imagem da marca, lealdade e reclamação. Foi estabelecida uma ampla base teórica para avaliar a importância estratégica do modelo que relaciona a influência na satisfação do serviço com as percepções dos clientes e avaliada a precisão deste modelo, por meio de uma análise comparativa a utilização de três métodos de estimação dos seus parâmetros, MLE, GLS, e ULS, com o emprego de modelagem de equações estruturais. Foram feitas aplicações em análises de dados, sendo testada e avaliada empiricamente, a influência do gênero na satisfação do cliente deste setor, além de uma segmentação de mercado utilizando mapas auto-organizáveis e a correspondente validação deste processo, com modelagem de equações estruturais.Os resultados do estudo empírico produziram uma boa qualidade de ajustamento para o modelo teórico proposto, com evidências do estabelecimento de uma adequada capacidade explicativa e preditiva, destacando-se a relevância da relação causal entre a satisfação e lealdade, em consonância com diversos estudos realizados para os mercados de comunicações móveis.

Utilizando comitês de classificadores para predição de rendimento escolar

Educational Data Mining is an application domain in artificial intelligence area that has been extensively explored nowadays. Technological advances and in particular, the increasing use of virtual learning environments have allowed the generation of considerable amounts of data to be investigated. Among the activities to be treated in this context exists the prediction of school performance of the students, which can be accomplished through the use of machine learning techniques. Such techniques may be used for student’s classification in predefined labels. One of the strategies to apply these techniques consists in their combination to design multi-classifier systems, which efficiency can be proven by results achieved in other studies conducted in several areas, such as medicine, commerce and biometrics. The data used in the experiments were obtained from the interactions between students in one of the most used virtual learning environments called Moodle. In this context, this paper presents the results of several experiments that include the use of specific multi-classifier systems systems, called ensembles, aiming to reach better results in school performance prediction that is, searching for highest accuracy percentage in the student’s classification. Therefore, this paper presents a significant exploration of educational data and it shows analyzes of relevant results about these experiments.

Predição de séries temporais de parâmetros de redes HSPA - WCDMA

With the growing demand of data traffic in the networks of third generation (3G), the mobile operators have attempted to focus resources on infrastructure in places where it identifies a greater need. The channeling investments aim to maintain the quality of service especially in dense urban areas. WCDMA - HSPA parameters Rx Power, RSCP (Received Signal Code Power), Ec/Io (Energy per chip/Interference) and transmission rate (throughput) at the physical layer are analyzed. In this work the prediction of time series on HSPA network is performed. The collection of values of the parameters was performed on a fully operational network through a drive test in Natal - RN, a capital city of Brazil northeastern. The models used for prediction of time series were the Simple Exponential Smoothing, Holt, Holt Winters Additive and Holt Winters Multiplicative. The objective of the predictions of the series is to check which model will generate the best predictions of network parameters WCDMA - HSPA.