Comportamento do consumidor: um estudo do mercado imobiliário em condomínios verticais fechados na região metropolitana de Natal

The research in question looked for to establish the relation between the motivation (of the proprietor of apartment) to change itself of another one apartment, in closed vertical condominium (residential mobility) in the period of the recognition of the necessity, and the satisfaction with the apartment after consume. The universe or the population chosen for the development of the study was of proprietors of apartment in vertical condominiums located in the region metropolitan of Natal. The analysis of data was made using the techniques of linear regression and logistic regression between variables. The linear regression found relations between the motivations for housing change and the satisfaction in after consume with some attributes of the apartment. The logistic regression showed that relations between the motivations for change and the general satisfaction to the apartment exist as a whole, in the period after consumes. With regard to the motivation to change itself of a apartment for another one, some reasons shown more motivation them the others. The research found different degrees of satisfaction with certain characteristics of the apartment and degrees of no satisfaction with others. Finally the results of the research had contributed for the reply of the problem that guided the present study, therefore had obtained in such a way to find how much logistic not linear relations between the two periods purchase (recognition of the necessity and evaluation after consume) and had elucidated the process that goes since the choice the product until the satisfaction of the necessities

Modelos matemáticos para estimativa do consumo máximo de oxigênio pela ventilometria de esforço em indivíduos saudáveis

The relation between metabolic demand and maximal oxygen consumption during exercise have been investigated in different areas of knowledge. In the health field, the determination of maximal oxygen consumption (VO2max) is considered a method to classify the level of physical fitness or the risk of cardiocirculatory diseases. The accuracy to obtain data provides a better evaluation of functional responses and allows a reduction in the error margin at the moment of risk classification, as well as, at the moment of determination of aerobic exercise work load. In Brasil, the use of respirometry associated to ergometric test became an opition in the cardiorespiratory evaluation. This equipment allows predictions concerning the oxyredutase process, making it possible to identify physiological responses to physical effort as the respiratory threshold. This thesis focused in the development of mathematical models developed by multiple regression validated by the stepwise method, aiming to predict the VO2max based on respiratory responses to physical effort. The sample was composed of a ramdom sample of 181 healthy individuals, men and women, that were randomized to two groups: regression group and cross validation group (GV). The voluntiars were submitted to a incremental treadmill test; objetiving to determinate of the second respiratory threshold (LVII) and the Peak VO2max. Using the método forward addition method 11 models of VO2max prediction in trendmill were developded. No significative differences were found between the VO2max meansured and the predicted by models when they were compared using ANOVA One-Way and the Post Hoc test of Turkey. We concluded that the developed mathematical models allow a prediction of the VO2max of healthy young individuals based on the LVII

Comportamento do consumidor: um estudo do mercado imobiliário em condomínios verticais fechados na região metropolitana de Natal

The research in question looked for to establish the relation between the motivation (of the proprietor of apartment) to change itself of another one apartment, in closed vertical condominium (residential mobility) in the period of the recognition of the necessity, and the satisfaction with the apartment after consume. The universe or the population chosen for the development of the study was of proprietors of apartment in vertical condominiums located in the region metropolitan of Natal. The analysis of data was made using the techniques of linear regression and logistic regression between variables. The linear regression found relations between the motivations for housing change and the satisfaction in after consume with some attributes of the apartment. The logistic regression showed that relations between the motivations for change and the general satisfaction to the apartment exist as a whole, in the period after consumes. With regard to the motivation to change itself of a apartment for another one, some reasons shown more motivation them the others. The research found different degrees of satisfaction with certain characteristics of the apartment and degrees of no satisfaction with others. Finally the results of the research had contributed for the reply of the problem that guided the present study, therefore had obtained in such a way to find how much logistic not linear relations between the two periods purchase (recognition of the necessity and evaluation after consume) and had elucidated the process that goes since the choice the product until the satisfaction of the necessities

Secagem de resíduo de goiaba em secador convectivo de bandejas: modelagem matemática e análise do processo

Actually, Brazil is one of the larger fruit producer worldwide, with most of its production being consumed in nature way or either as juice or pulp. It is important to highlig ht in the fruit productive chain there are a lot lose due mainly to climate reasons, as well as storage, transportation, season, market, etc. It is known that in the pulp and fruit processing industy a yield of 50% (in mass) is usually obtained, with the other part discarded as waste. However, since most this waste has a high nutrient content it can be used to generate added - value products. In this case, drying plays an important role as an alternative process in order to improve these wastes generated by the fruit industry. However, despite the advantage of using this technique in order to improve such wastes, issues as a higher power demand as well as the thermal efficiency limitation should be addressed. Therefore, the control of the main variables in t his drying process is quite important in order to obtain operational conditions to produce a final product with the target specification as well as with a lower power cost. M athematical models can be applied to this process as a tool in order to optimize t he best conditions. The main aim of this work was to evaluate the drying behaviour of a guava industrial pulp waste using a batch system with a convective - tray dryer both experimentally and using mathematical modeling. In the experimental study , the dryin g carried out using a group of trays as well as the power consume were assayed as response to the effects of operational conditions (temperature, drying air flow rate and solid mass). Obtained results allowed observing the most significant variables in the process. On the other hand, the phenomenological mathematical model was validated and allowed to follow the moisture profile as well as the temperature in the solid and gas phases in every tray. Simulation results showed the most favorable procedure to o btain the minimum processing time as well as the lower power demand.

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

Um sistema para estimação da vazão de gás de poços produzindo por Plunger Lift para vaso separador de teste em plataformas de petróleo

This work intends to analyze the behavior of the gas flow of plunger lift wells producing to well testing separators in offshore production platforms to aim a technical procedure to estimate the gas flow during the slug production period. The motivation for this work appeared from the expectation of some wells equipped with plunger lift method by PETROBRAS in Ubarana sea field located at Rio Grande do Norte State coast where the produced fluids measurement is made in well testing separators at the platform. The oil artificial lift method called plunger lift is used when the available energy of the reservoir is not high enough to overcome all the necessary load losses to lift the oil from the bottom of the well to the surface continuously. This method consists, basically, in one free piston acting as a mechanical interface between the formation gas and the produced liquids, greatly increasing the well s lifting efficiency. A pneumatic control valve is mounted at the flow line to control the cycles. When this valve opens, the plunger starts to move from the bottom to the surface of the well lifting all the oil and gas that are above it until to reach the well test separator where the fluids are measured. The well test separator is used to measure all the volumes produced by the well during a certain period of time called production test. In most cases, the separators are designed to measure stabilized flow, in other words, reasonably constant flow by the use of level and pressure electronic controllers (PLC) and by assumption of a steady pressure inside the separator. With plunger lift wells the liquid and gas flow at the surface are cyclical and unstable what causes the appearance of slugs inside the separator, mainly in the gas phase, because introduce significant errors in the measurement system (e.g.: overrange error). The flow gas analysis proposed in this work is based on two mathematical models used together: i) a plunger lift well model proposed by Baruzzi [1] with later modifications made by Bolonhini [2] to built a plunger lift simulator; ii) a two-phase separator model (gas + liquid) based from a three-phase separator model (gas + oil + water) proposed by Nunes [3]. Based on the models above and with field data collected from the well test separator of PUB-02 platform (Ubarana sea field) it was possible to demonstrate that the output gas flow of the separator can be estimate, with a reasonable precision, from the control signal of the Pressure Control Valve (PCV). Several models of the System Identification Toolbox from MATLAB® were analyzed to evaluate which one better fit to the data collected from the field. For validation of the models, it was used the AIC criterion, as well as a variant of the cross validation criterion. The ARX model performance was the best one to fit to the data and, this way, we decided to evaluate a recursive algorithm (RARX) also with real time data. The results were quite promising that indicating the viability to estimate the output gas flow rate from a plunger lift well producing to a well test separator, with the built-in information of the control signal to the PCV

Avaliação e modelagem reológica de fluido de perfuração base água

The determination of the rheology of drilling fluids is of fundamental importance to select the best composition and the best treatment to be applied in these fluids. This work presents a study of the rheological behavior of some addictives used as viscosifiers in water-based drilling fluids. The evaluated addictives were: Carboxymethylcellulose (CMC), Xanthan gum (GX), and Bentonite. The main objective was to rheologically characterize suspensions composed by these addictives, by applying mathematical models for fluid flow behavior, in order to determine the best flow equation to represent the system, as well as the model parameters. The mathematical models applied in this research were: the Bingham Model, the Ostwald de Wale Model, and the Herschel-Bulkley Model. A previous study of hydration time for each used addictive was accomplished seeking to evaluate the effect of polymer and clay hydration on rheological behavior of the fluid. The rheological characterization was made through typical rheology experiments, using a coaxial cylinder viscosimeter, where the flow curves and the thixotropic magnitude of each fluid was obtained. For each used addictive the rheological behavior as a function of temperature was also evaluated as well as fluid stability as a function of the concentration and kind of addictive used. After analyses of results, mixtures of polymer and clay were made seeking to evaluate the rheological modifications provided by the polymer incorporation in the water + bentonite system. The obtained results showed that the Ostwald de Waale model provided the best fit for fluids prepared using CMC and for fluids with Xanthan gum and Bentonite the best fit was given by the Herschel-Bulkley one

Estudo da organização funcional do sistema circadiano por meio de ferramentas computacionais e matemáticas

Circadian rhythms are variations in physiological processes that help living beings to adapt to environmental cycles. These rhythms are generated and are synchronized to the dark light cycle through the suprachiasmatic nucleus. The integrity of circadian rhythmicity has great implication on human health. Currently it is known that disturbances in circadian rhythms are related to some problems of today such as obesity, propensity for certain types of cancer and mental disorders for example. The circadian rhythmicity can be studied through experiments with animal models and in humans directly. In this work we use computational models to gather experimental results from the literature and explain the results of our laboratory. Another focus of this study was to analyze data rhythms of activity and rest obtained experimentally. Here we made a review on the use of variables used to analyze these data and finally propose an update on how to calculate these variables. Our models were able to reproduce the main experimental results in the literature and provided explanations for the results of experiments performed in our laboratory. The new variables used to analyze the rhythm of activity and rest in humans were more efficient to describe the fragmentation and synchronization of this rhythm. Therefore, the work contributed improving existing tools for the study of circadian rhythms in mammals

Sinalização cromática da condição reprodutiva de fêmeas de segui comum (Callithrix jacchus)

As social animals, primates use different sensory modalities (acoustic, chemical, tactile and visual) to convey information about social and sexual status to conspecifics. Among these modalities, visual signals are widely used, especially color signals, since primates are the mammalian group that displays the greatest variety of colors in their skin and fur. Studies with Old World primate species suggest that hormonal variations are related to variations in the colors of individual faces and genitals. Therefore, chromatic cues can be used by conspecifics to identify the reproductive condition of an individual. To date, studies with the same approach are unknown for New World species. However, behavioral and physiological studies suggest that different New World primate species seem to perceive reproductive conditions such as the timing of female conception and gestation. Thus, in this study, our aim was to: i) identify whether there are chromatic cues on the skin of female common marmosets, (Callithrix jacchus) that indicate their reproductive condition; ii) define whether this chromatic variation can be perceived by all visual phenotypes known in this species; iii) identify if these chromatic cues can be perceived under different light intensity levels (dim, intermediate and high). For this, we selected 13 female common marmosets in four distinct reproductive conditions: pregnant female preceding parturition, postpartum mothers, noncycling and cycling females. The coloration of the skin in genital and thigh areas in females was measured using a spectrophotometer. Using mathematical models of visual perception, we calculated the values of quantum catch for each photoreceptor type known in this species, the visual opponency channels and color contrast between those body spots. Our results indicate the occurance of chromatic variations in the genital area during the weeks that precede and follow parturition, forming a U-pattern of variation perceptible to males and females in natural conditions of low and high luminosity. Furthermore, we observed distinct color patterns in the genital skin of pregnant and cycling females that indicate their reproductive conditions. Finally, we present evidence of color contrast in noncycling females that is higher than that of pregnant ones. This study suggests that there is a chromatic xii variation in the genital skin of females that can be perceived by conspecifics and that may be related to hormonal changes typical of pregnancy and the ovarian cycle

Medição de desempenho organizacional nas imobiliárias: um estudo na cidade do Natal-RN

The purpose of this paper is to identify how real estate companies from the city of Natal measure their organizational performance. Traditionally these companies measure their performance using financial measures; however, the technological improvement, the internationalization of the economy and the change in consumer behavior all demand better products and services, and other measuring models. Those changes motivate organizations to continually improve the quality of their products and services. In this way, these companies need to associate their financial results to their global performance. Therefore, it is necessary to have organizational performance models that associate financial and non-financial measures to the strategies of the companies. The research also tries to identify which performance indicators are used by these companies, as well as to test a model who questions: a) if there is any relationship between managers´ characteristics and performance measuring systems´ characteristics; b) if there is any relationship between the company s characteristics and the characteristics of the measuring system used to evaluate its organizational performance and c) finally to verify if there is a relationship between the characteristics of the measuring system and the company s performance. The information which served as a basis for the study was obtained through an empirical research, with questionnaires, answered by 66 (sixty six) companies from the city of Natal, capital of the state of Rio Grande do Norte. The results show that none of the companies investigated use any of the performance measurement models proposed in the modern literature. However, they use on an isolated way some of the measures those models, including some measures from adopted in the Balanced Scorecard, as well as the benchmarking process, making comparisons with the performance of their competitors. The research also reveals that either bigger companies, companies with more experienced managers or with better performance show better performance measurement systems

Modelagem matemática e experimental da perda de injetividade em poços canhoneados

Water injection in oil reservoirs is a recovery technique widely used for oil recovery. However, the injected water contains suspended particles that can be trapped, causing formation damage and injectivity decline. In such cases, it is necessary to stimulate the damaged formation looking forward to restore the injectivity of the injection wells. Injectivity decline causes a major negative impact to the economy of oil production, which is why, it is important to foresee the injectivity behavior for a good waterflooding management project. Mathematical models for injectivity losses allow studying the effect of the injected water quality, also the well and formation characteristics. Therefore, a mathematical model of injectivity losses for perforated injection wells was developed. The scientific novelty of this work relates to the modeling and prediction of injectivity decline in perforated injection wells, considering deep filtration and the formation of external cake in spheroidal perforations. The classic modeling for deep filtration was rewritten using spheroidal coordinates. The solution to the concentration of suspended particles was obtained analytically and the concentration of the retained particles, which cause formation damage, was solved numerically. The acquisition of the solution to impedance assumed a constant injection rate and the modified Darcy´s Law, defined as being the inverse of the normalized injectivity by the inverse of the initial injectivity. Finally, classic linear flow injectivity tests were performed within Berea sandstone samples, and within perforated samples. The parameters of the model, filtration and formation damage coefficients, obtained from the data, were used to verify the proposed modeling. The simulations showed a good fit to the experimental data, it was observed that the ratio between the particle size and pore has a large influence on the behavior of injectivity decline.

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

Fatores que influenciam a intenção de compra online: aplicação de um modelo adaptado de aceitação da tecnologia para o comércio eletrônico

This research aims to understand the factors that influence intention to online purchase of consumers, and to identify between these factors those that influence the users and the nonusers of electronic commerce. Thus, it is an applied, exploratory and descriptive research, developed in a quantitative model. Data collection was done through a questionnaire administered to a sample of 194 graduate students from the Centre for Applied Social Sciences of UFRN and data analysis was performed using descriptive statistics, confirmatory factorial analysis and simple and multiple linear regression analysis. The results of descriptive statistics revealed that respondents in general and users of electronic commerce have positive perceptions of ease of use, usefulness and social influence about buying online, and intend to make purchases on Internet over the next six months. As for the non-users of electronic commerce, they do not trust the Internet to transact business, have negative perceptions of risk and social influence over purchasing online, and does not intend to make purchases on Internet over the next six months. Through confirmatory factorial analysis six factors were set up: behavioral intention, perceived ease of use, perceived usefulness, perceived risk, trust and social influence. Through multiple regression analysis, was observed that all these factors influence online purchase intentions of respondents in general, that only the social influence does not influence the intention to continue buying on the Internet from users of electronic commerce, and that only trust and social influence affect the intention to purchase online from non-users of electronic commerce. Through simple regression analysis, was found that trust influences perceptions of ease of use, usefulness and risk of respondents in general and users of electronic commerce, and that trust does not influence the perceptions of risk of non-users of electronic commerce. Finally, it was also found that the perceived ease of use influences perceived usefulness of the three groups. Given this scenario, it was concluded that it is extremely important that organizations that work with online sales know the factors that influence consumers purchasing intentions in order to gain space in their market

Uma janela tropical: análise do desempenho luminoso de ambientes com aberturas sombreadas para o clima de Natal/RN

This master thesis introduces assessment procedures of daylighting performance in office rooms with shaded opening, recommendations for Natal-RN (Latitude 05,47' S, Longitude 35,11' W). The studies assume the need of window exterior shading in hot and humid climate buildings. The daylighting performance analyses are based on simulated results for three levels of illuminance (300,500 e 1000 lux) between 08h00 e 16h00, in rooms with 2,80 m height, 6 m large and 4 m, 6 m e 8 m depths, with a centered single opening, window wall ratio (20%, 40% e 60%), four orientations (North, East, South and West), and two types of sky (clear and partially cloudy). The sky characteristics were statistically determined based on hourly data from INPE-CRN solar and daylighting weather station. The lighting performance is resulted from dynamic computer simulation of 72 models using Troplux 3.12. The simulation results were assessed using a new parameter to quantify the use of interior daylighting, the useful percentage of daylight (PULN), which corresponds to the time fraction with satisfactory light, in accordance with the illuminance design. The passive zone depths are defined based on the PULN. Despite the failures of illuminance data from the weather station, the analyses ratified the high potential of daylighting for shaded rooms. The most influential variables on the lighting performance are the opening size and the illuminance of design, while the orientation is a little influential

Análise comparativa entre simuladores de linha de fluxo e diferenças finitas para um reservatório de petróleo submetido a injeção de água

Water injection is the most widely used method for supplementary recovery in many oil fields due to various reasons, like the fact that water is an effective displacing agent of low viscosity oils, the water injection projects are relatively simple to establish and the water availability at a relatively low cost. For design of water injection projects is necessary to do reservoir studies in order to define the various parameters needed to increase the effectiveness of the method. For this kind of study can be used several mathematical models classified into two general categories: analytical or numerical. The present work aims to do a comparative analysis between the results presented by flow lines simulator and conventional finite differences simulator; both types of simulators are based on numerical methods designed to model light oil reservoirs subjected to water injection. Therefore, it was defined two reservoir models: the first one was a heterogeneous model whose petrophysical properties vary along the reservoir and the other one was created using average petrophysical properties obtained from the first model. Comparisons were done considering that the results of these two models were always in the same operational conditions. Then some rock and fluid parameters have been changed in both models and again the results were compared. From the factorial design, that was done to study the sensitivity analysis of reservoir parameters, a few cases were chosen to study the role of water injection rate and the vertical position of wells perforations in production forecast. It was observed that the results from the two simulators are quite similar in most of the cases; differences were found only in those cases where there was an increase in gas solubility ratio of the model. Thus, it was concluded that in flow simulation of reservoirs analogous of those now studied, mainly when the gas solubility ratio is low, the conventional finite differences simulator may be replaced by flow lines simulator the production forecast is compatible but the computational processing time is lower.