Modelo matemático para predição do VO2máx em cicloergômetro baseado na análise dos gases expirados

Existem diversas equações para predição do VO2máx a partir de variáveis dentro do teste ergométrico em vários ergômetros, no entanto equação semelhante utilizando os limiares ventilatórios na ergoespirometria em teste sub-máximo no cicloergômetro não está disponível. O objetivo do presente estudo foi avaliar a precisão de modelos de predição do VO2máx com base em indicadores de esforço sub-máximo. Neste sentido foram testados em protocolo incremental máximo no cicloergômetro 7.877 voluntários, sendo 4640 indivíduos do sexo feminino e 3147 do sexo masculino, todos saudáveis não atletas, com idades acima de 20 anos, divididos randomicamente em dois grupos: A de estimação e B de validação. A partir das variáveis independentes massa corporal (MC) em kg, carga de trabalho no limiar 2 (WL2) e freqüência cardíaca no limiar 2 (FCL2) foi possível construir um modelo de regressão linear múltipla para predição do VO2máx. Os resultados demonstram que em indivíduos saudáveis não atletas de ambos os sexos é possível predizer o VO2máx com um erro mínimo (EPE = 1,00%) a partir de indicadores submáximos obtidos em teste incremental. O caráter multidisciplinar do trabalho pôde ser caracterizado pelo emprego de técnicas que envolveram pneumologia, educação física, fisiologia e estatística

Predição da maturação puberal de indivíduos do sexo masculino a partir de variáveis antropométricas

The methods of analysis of the selection system sports talent sometimes do not consider the biological age of the athletes, since that the assessment of maturational moment have several limitations The aim of this work is to develop a predictive equation of pubertal assessment in male subjects, based on anthropometric measurements. We evaluated 206 young boys, aged between eight and 18 years, and studing in public and private schools in Natal, Brazil. The sample selection was done randomly, being used the anthropometric measurements and pubertal maturation evaluation according to the Tanner stages. Statistical analysis followed the presentation of central tendency measures and their derivatives. The inferential analysis was performed according to the ANOVA test, multivariate discriminant analysis and weighted Kappa. The advancement of pubertal stages was accompanied by significant changes in anthropometric variables, demonstrating the relationship presented in both. For this purpose, discriminant analysis selected eight variables with the highest prediction of pubertal maturation, and created an equation with a significance level of 75%. and concordance level of 0.840, considered as excellent. This shows that the prediction of pubertal maturation from anthropometric variables presented as a valid method, being used as a practical tool in sports talents selection

Modelagem e medições de ondas de rádio para predição de perda de propagação em ambientes urbanos

In this dissertation new models of propagation path loss predictions are proposed by from techniques of optimization recent and measures of power levels for the urban and suburban areas of Natal, city of Brazilian northeast. These new proposed models are: (i) a statistical model that was implemented based in the addition of second-order statistics for the power and the altimetry of the relief in model of linear losses; (ii) a artificial neural networks model used the training of the algorithm backpropagation, in order to get the equation of propagation losses; (iii) a model based on the technique of the random walker, that considers the random of the absorption and the chaos of the environment and than its unknown parameters for the equation of propagation losses are determined through of a neural network. The digitalization of the relief for the urban and suburban areas of Natal were carried through of the development of specific computational programs and had been used available maps in the Statistics and Geography Brazilian Institute. The validations of the proposed propagation models had been carried through comparisons with measures and propagation classic models, and numerical good agreements were observed. These new considered models could be applied to any urban and suburban scenes with characteristic similar architectural to the city of Natal

Avaliação da aplicabilidade de correlações matemáticas e redes neurais na predição de parâmetros de especificação do diesel

Diesel fuel is one of leading petroleum products marketed in Brazil, and has its quality monitored by specialized laboratories linked to the National Agency of Petroleum, Natural Gas and Biofuels - ANP. The main trial evaluating physicochemical properties of diesel are listed in the resolutions ANP Nº 65 of December 9th, 2011 and Nº 45 of December 20th, 2012 that determine the specification limits for each parameter and methodologies of analysis that should be adopted. However the methods used although quite consolidated, require dedicated equipment with high cost of acquisition and maintenance, as well as technical expertise for completion of these trials. Studies for development of more rapid alternative methods and lower cost have been the focus of many researchers. In this same perspective, this work conducted an assessment of the applicability of existing specialized literature on mathematical equations and artificial neural networks (ANN) for the determination of parameters of specification diesel fuel. 162 samples of diesel with a maximum sulfur content of 50, 500 and 1800 ppm, which were analyzed in a specialized laboratory using ASTM methods recommended by the ANP, with a total of 810 trials were used for this study. Experimental results atmospheric distillation (ASTM D86), and density (ASTM D4052) of diesel samples were used as basic input variables to the equations evaluated. The RNAs were applied to predict the flash point, cetane number and sulfur content (S50, S500, S1800), in which were tested network architectures feed-forward backpropagation and generalized regression varying the parameters of the matrix input in order to determine the set of variables and the best type of network for the prediction of variables of interest. The results obtained by the equations and RNAs were compared with experimental results using the nonparametric Wilcoxon test and Student's t test, at a significance level of 5%, as well as the coefficient of determination and percentage error, an error which was obtained 27, 61% for the flash point using a specific equation. The cetane number was obtained by three equations, and both showed good correlation coefficients, especially equation based on aniline point, with the lowest error of 0,816%. ANNs for predicting the flash point and the index cetane showed quite superior results to those observed with the mathematical equations, respectively, with errors of 2,55% and 0,23%. Among the samples with different sulfur contents, the RNAs were better able to predict the S1800 with error of 1,557%. Generally, networks of the type feedforward proved superior to generalized regression.

Fatores críticos de sucesso como antecedentes da aceitação de um sistema de informação em uma universidade federal

In recent decades the public sector comes under pressure in order to improve its performance. The use of Information Technology (IT) has been a tool increasingly used in reaching that goal. Thus, it has become an important issue in public organizations, particularly in institutions of higher education, determine which factors influence the acceptance and use of technology, impacting on the success of its implementation and the desired organizational results. The Technology Acceptance Model - TAM was used as the basis for this study and is based on the constructs perceived usefulness and perceived ease of use. However, when it comes to integrated management systems due to the complexity of its implementation,organizational factors were added to thus seek further explanation of the acceptance of such systems. Thus, added to the model five TAM constructs related to critical success factors in implementing ERP systems, they are: support of top management, communication, training, cooperation, and technological complexity (BUENO and SALMERON, 2008). Based on the foregoing, launches the following research problem: What factors influence the acceptance and use of SIE / module academic at the Federal University of Para, from the users' perception of teachers and technicians? The purpose of this study was to identify the influence of organizational factors, and behavioral antecedents of behavioral intention to use the SIE / module academic UFPA in the perspective of teachers and technical users. This is applied research, exploratory and descriptive, quantitative with the implementation of a survey, and data collection occurred through a structured questionnaire applied to a sample of 229 teachers and 30 technical and administrative staff. Data analysis was carried out through descriptive statistics and structural equation modeling with the technique of partial least squares (PLS). Effected primarily to assess the measurement model, which were verified reliability, convergent and discriminant validity for all indicators and constructs. Then the structural model was analyzed using the bootstrap resampling technique like. In assessing statistical significance, all hypotheses were supported. The coefficient of determination (R ²) was high or average in five of the six endogenous variables, so the model explains 47.3% of the variation in behavioral intention. It is noteworthy that among the antecedents of behavioral intention (BI) analyzed in this study, perceived usefulness is the variable that has a greater effect on behavioral intention, followed by ease of use (PEU) and attitude (AT). Among the organizational aspects (critical success factors) studied technological complexity (TC) and training (ERT) were those with greatest effect on behavioral intention to use, although these effects were lower than those produced by behavioral factors (originating from TAM). It is pointed out further that the support of senior management (TMS) showed, among all variables, the least effect on the intention to use (BI) and was followed by communications (COM) and cooperation (CO), which exert a low effect on behavioral intention (BI). Therefore, as other studies on the TAM constructs were adequate for the present research. Thus, the study contributed towards proving evidence that the Technology Acceptance Model can be applied to predict the acceptance of integrated management systems, even in public. Keywords: Technology

Análise de métodos de predição de conforto térmico de habitação em clima quente-úmido com condicionamento passivo

The assessment of building thermal performance is often carried out using HVAC energy consumption data, when available, or thermal comfort variables measurements, for free-running buildings. Both types of data can be determined by monitoring or computer simulation. The assessment based on thermal comfort variables is the most complex because it depends on the determination of the thermal comfort zone. For these reasons, this master thesis explores methods of building thermal performance assessment using variables of thermal comfort simulated by DesignBuilder software. The main objective is to contribute to the development of methods to support architectural decisions during the design process, and energy and sustainable rating systems. The research method consists on selecting thermal comfort methods, modeling them in electronic sheets with output charts developed to optimize the analyses, which are used to assess the simulation results of low cost house configurations. The house models consist in a base case, which are already built, and changes in thermal transmittance, absorptance, and shading. The simulation results are assessed using each thermal comfort method, to identify the sensitivity of them. The final results show the limitations of the methods, the importance of a method that considers thermal radiance and wind speed, and the contribution of the chart proposed

Mapeamento acústico como ferramenta para predição de ruído urbano na área de influência do estádio Arena das Dunas, Natal/ RN

The Noise Pollution causes degradation in the quality of the environment and presents itself as one of the most common environmental problems in the big cities. An Urban environment present scenario and their complex acoustic study need to consider the contribution of various noise sources. Accordingly to computational models through mapping and prediction of acoustic scene become important, because they enable the realization of calculations, analyzes and reports, allowing the interpretation of satisfactory results. The study neighborhood is the neighborhood of Lagoa Nova, a central area of the city of Natal, which will undergo major changes in urban space due to urban mobility projects planned for the area around the stadium and the consequent changes of urban form and traffic. Thus, this study aims to evaluate the noise impact caused by road and morphological changes around the stadium Arena das Dunas in the neighborhood of Lagoa Nova, through on-site measurements and mapping using the computational model SoundPLAN year 2012 and the scenario evolution acoustic for the year 2017. For this analysis was the construction of the first acoustic mapping based on current diagnostic acoustic neighborhood, physical mapping, classified vehicle count and measurement of sound pressure level, and to build the prediction of noise were observed for the area study the modifications provided for traffic, urban form and mobility work. In this study, it is concluded that the sound pressure levels of the year in 2012 and 2017 extrapolate current legislation. For the prediction of noise were numerous changes in the acoustic scene, in which the works of urban mobility provided will improve traffic flow, thus reduce the sound pressure level where interventions are expected

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

Avaliação das pressões respiratórias máximas em crianças e adolescentes da grande Natal: elaboração de uma equação preditiva

The human respiratory system was so designed that would allow efficient ventilation, regardless of variations in the external environment that may hinder the act of breathing, such an act involves dozens of variables, among them we find the respiratory depression, which is nothing more than respiratory muscle strength. The pressures are widely used in several cases: Neuro-muscular; evolution of pulmonary dysfunction and a predictor for discontinuation of mechanical ventilation. Therefore it was proposed to carry out evaluations of these respiratory pressures for children and adolescents aged 10 to 16 years and propose a predictive equation that involves the anthropometric variables age (A, years), body mass (BM, kilograms) and height (H, meters) with maximal respiratory pressures (maximum inspiratory and expiratory pressure). Evaluations were performed in this age group of students in public and private schools of the Grande Natal , measurements were performed using the analogue manometer, were children and adolescents and their parents gave informed consent. 517 samples were taken, and 250 for males (M), 255 for females (F) and 12 were excluded according to our exclusion criteria. The sample was subdivided into three age groups (10-11, 12-13 and 14 to 16 years old). It was found through the student s t test (p ≤ 0.05) for all variables studied, children and male adolescents had higher means than females, except for the MC. For the correlation between the variables found significant correlation (p <0.05) among all the variables when analyzed as pairs except between MIP and height for females. The development of predictive equations (for p ≤ 0.05) based on three types of strategies adopted were restricted to two association between anthropometric variables isolated, resulting in: for males: MIP = -32.29 + (-2.11*A) + (-0.52*BM), MIP = 9.99 + (-0.36*BM) + (-49.40*H); MEP = 18.54 + 3.53*A + 0, 42*BM, MEP = -33.37 + 2.78*A + 52.18* H, MEP = -17.39 + 0.33*BM + 55.04*H; and, for females we find: MEP = 24.32 + 2.59 * A + 0.24*BM

Estimativas de mortalidade para a região nordeste do Brasil em 2010: uma associação do método demográfico equação geral de balanceamento, com o estimador bayesiano empírico

One of the greatest challenges of demography, nowadays, is to obtain estimates of mortality, in a consistent manner, mainly in small areas. The lack of this information, hinders public health actions and leads to impairment of quality of classification of deaths, generating concern on the part of demographers and epidemiologists in obtaining reliable statistics of mortality in the country. In this context, the objective of this work is to obtain estimates of deaths adjustment factors for correction of adult mortality, by States, meso-regions and age groups in the northeastern region, in 2010. The proposal is based on two lines of observation: a demographic one and a statistical one, considering also two areas of coverage in the States of the Northeast region, the meso-regions, as larger areas and counties, as small areas. The methodological principle is to use the General Equation and Balancing demographic method or General Growth Balance to correct the observed deaths, in larger areas (meso-regions) of the states, since they are less prone to breakage of methodological assumptions. In the sequence, it will be applied the statistical empirical Bayesian estimator method, considering as sum of deaths in the meso-regions, the death value corrected by the demographic method, and as reference of observation of smaller area, the observed deaths in small areas (counties). As results of this combination, a smoothing effect on the degree of coverage of deaths is obtained, due to the association with the empirical Bayesian Estimator, and the possibility of evaluating the degree of coverage of deaths by age groups at counties, meso-regions and states levels, with the advantage of estimete adjustment factors, according to the desired level of aggregation. The results grouped by State, point to a significant improvement of the degree of coverage of deaths, according to the combination of the methods with values above 80%. Alagoas (0.88), Bahia (0.90), Ceará (0.90), Maranhão (0.84), Paraíba (0.88), Pernambuco (0.93), Piauí (0.85), Rio Grande do Norte (0.89) and Sergipe (0.92). Advances in the control of the registry information in the health system, linked to improvements in socioeconomic conditions and urbanization of the counties, in the last decade, provided a better quality of information registry of deaths in small areas

Modelo 2,5D de predição de propagação para ambientes interiores utilizando o método do traçado de raios

A 2.5D ray-tracing propagation model is proposed to predict radio loss in indoor environment. Specifically, we opted for the Shooting and Bouncing Rays (SBR) method, together with the Geometrieal Theory of Diffrartion (GTD). Besides the line-of-sight propagation (LOS), we consider that the radio waves may experience reflection, refraction, and diffraction (NLOS). In the Shooting and Bouncing Rays (SBR) method, the transmitter antenna launches a bundle of rays that may or may not reach the receiver. Considering the transmitting antenna as a point, the rays will start to launch from this position and can reach the receiver either directly or after reflections, refractions, diffractions, or even after any combination of the previous effects. To model the environment, a database is built to record geometrical characteristics and information on the constituent materials of the scenario. The database works independently of the simulation program, allowing robustness and flexibility to model other seenarios. Each propagation mechanism is treated separately. In line-of-sight propagation, the main contribution to the received signal comes from the direct ray, while reflected, refracted, and diffracted signal dominate when the line-of-sight is blocked. For this case, the transmitted signal reaches the receiver through more than one path, resulting in a multipath fading. The transmitting channel of a mobile system is simulated by moving either the transmitter or the receiver around the environment. The validity of the method is verified through simulations and measurements. The computed path losses are compared with the measured values at 1.8 GHz ftequency. The results were obtained for the main corridor and room classes adjacent to it. A reasonable agreement is observed. The numerical predictions are also compared with published data at 900 MHz and 2.44 GHz frequencies showing good convergence

Otimização de modelos de predição da perda de propagação aplicáveis em 3,5GHZ utilizando algoritmos genéticos

The telecommunications industry has experienced recent changes, due to increasing quest for access to digital services for data, video and multimedia, especially using the mobile phone networks. Recently in Brazil, mobile operators are upgrading their networks to third generations systems (3G) providing to users broadband services such as video conferencing, Internet, digital TV and more. These new networks that provides mobility and high data rates has allowed the development of new market concepts. Currently the market is focused on the expansion of WiMAX technology, which is gaining increasingly the market for mobile voice and data. In Brazil, the commercial interest for this technology appears to the first award of licenses in the 3.5 GHz band. In February 2003 ANATEL held the 003/2002/SPV-ANATEL bidding, where it offered blocks of frequencies in the range of 3.5 GHz. The enterprises who purchased blocks of frequency were: Embratel, Brazil Telecom (Vant), Grupo Sinos, Neovia and WKVE, each one with operations spread in some regions of Brazil. For this and other wireless communications systems are implemented effectively, many efforts have been invested in attempts to developing simulation methods for coverage prediction that is close to reality as much as possible so that they may become believers and indispensable tools to design wireless communications systems. In this work wasm developed a genetic algorithm (GA's) that is able to optimize the models for predicting propagation loss at applicable frequency range of 3.5 GHz, thus enabling an estimate of the signal closer to reality to avoid significant errors in planning and implementation a system of wireless communication

Avaliação dos modelos de predição de propagação para telefonia móvel celular na cidade do Natal

The development of wireless telecommunication in the last years has been great. It has been taking academics to conceive new ideas and techniques. Their aims are to increase the capacity and the quality of the system s services. Cells that are smaller every time, frequencies that are every time higher and environments that get more and more complex, all those facts deserve more accurate models the propagation prediction techniques are inserted in this context and results with a merger of error that is compatible with the next generations of communication systems. The objective of this Work is to present results of a propagation measurement campaign, aiming at pointing the characteristics of the mobile systems covering in the city of Natal (state of Rio Grande do Norte, Brazil). A mobile laboratory was set up, using the infra-structure available and frequently used by ANATEL. The measures were taken in three different areas: one characterized by high buildings, high relief, presence of trees and towers of different highs. These areas covered the city s central zone, a suburban / rural zone and a section of coast surrounded by sand dunes. It is important to highlight that the analysis was made taking into consideration the actual reality of cellular systems with covering ranges by reduced cells, with the intent of causing greater re-use of frequencies and greater capacity of telephone traffic. The predominance of telephone traffic by cell in the city of Natal occurs within a range inferior to 3 (three) km from the Radio-Base Station. The frequency band used was 800 MHz, corresponding to the control channels of the respective sites, which adopt the FSK modulation technique. This Dissertation starts by presenting a general vision of the models used for predicting propagation. Then, there is a description of the methodology used in the measuring, which were done using the same channels of control of the cellular system. The results obtained were compared with many existing prediction models, and some adaptations were developed by using regression techniques trying to obtain the most optimized solutions. Furthermore, according to regulations from the old Brazilian Holding Telebrás, a minimum covering of 90% of a determined previously area, in 90% of the time, must be obeyed when implanting cellular systems. For such value to be reached, considerations and studies involving the specific environment that is being covered are important. The objective of this work is contribute to this aspect

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

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