17 resultados para Non-linear multiple regression


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This study examines the complex hotel buyer decision process in front of the tourism distribution channels. Its objective is to describe the influence level of the tourism marketing intermediaries, mainly the travel agents and tour operators, over the hotel decision process by the buyer-tourist. The data collection process was done trough a survey with three hundred brazilian tourists hosted in nineteen hotels of Natal, capital of Rio Grande do Norte, Brazil. The data analysis was done using some multivariate statistic techniques as correlation analysis, multiple regression analysis, factor analysis and multiple discriminant analysis. The research characterizes the hotel services consumers profile and his trip, and identifying the distribution channels used by them. Furthermore, the research verifies the intermediaries influence exercised over hotel buyer decision process, looking for identify causality relations between the influence level and the buyer profile. Verifies that information about hotels available on internet reduces the probability that this influence can be practiced; however it was possible identifying those consumers considers this information complementary and non-substitutes than the information from intermediaries. The characteristics of the data do not allow indentifying the factors that constraint the intermediaries influence neither identifying discriminant functions of the specific distribution channel choice by consumers. The study concludes that consumers don t agree in have been influenced by intermediaries or don t know if they have, still considering important to consult them and internet doesn t substitute their function as information source

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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

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This study examines the complex hotel buyer decision process in front of the tourism distribution channels. Its objective is to describe the influence level of the tourism marketing intermediaries, mainly the travel agents and tour operators, over the hotel decision process by the buyer-tourist. The data collection process was done trough a survey with three hundred brazilian tourists hosted in nineteen hotels of Natal, capital of Rio Grande do Norte, Brazil. The data analysis was done using some multivariate statistic techniques as correlation analysis, multiple regression analysis, factor analysis and multiple discriminant analysis. The research characterizes the hotel services consumers profile and his trip, and identifying the distribution channels used by them. Furthermore, the research verifies the intermediaries influence exercised over hotel buyer decision process, looking for identify causality relations between the influence level and the buyer profile. Verifies that information about hotels available on internet reduces the probability that this influence can be practiced; however it was possible identifying those consumers considers this information complementary and non-substitutes than the information from intermediaries. The characteristics of the data do not allow indentifying the factors that constraint the intermediaries influence neither identifying discriminant functions of the specific distribution channel choice by consumers. The study concludes that consumers don t agree in have been influenced by intermediaries or don t know if they have, still considering important to consult them and internet doesn t substitute their function as information source

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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

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This study aimed to evaluate factors associated to orthodontic treatment stability and patient satisfaction in the long-term. A total of 209 patients (88 class I and 121 class II) treated with straight wire fixed appliance were selected at least 5 years post treatment. Six hundred twenty seven dental casts were examined with the PAR Index at pretreatment (T1), end of treatment (T2), and at long-term follow up (T3, mean 8.5 years post treatment). At T3, a Dental Impact on Daily Living questionnaire was used to assess patient satisfaction with the dentition in the long-term. Friedman test and multiple regression analysis were used to evaluate changes among the time points and factors associated with stability and patient satisfaction. Predictive factors used to exam the occlusion were: PAR Index at T1 and T2, age at T1, the amount of time without retainer, length of Hawley retainer wear, length of follow-up, sex, extraction and third molar status. To assess patient satisfaction were considered: changes produced by the orthodontic treatment (PAR T2-T1), post treatment stability (PAR T3), age at the start of treatment (T1), length of treatment (T2-T1), gender, and extraction. Orthodontic treatment produced a significant improvement of 94.2% in the PAR Index (T2-T1), but this change was not associated with the level of satisfaction when the patient was questioned at T3. No significant change was observed between T2 and T3. However, when the sample was divided according to the level of finalization (PAR T2), it was observed that well-finished patients experienced some deterioration (P<.001), whereas the less well-finished ones showed some improvement (P<.05). Even with the deterioration, the well-finished patients still had a better PAR Index at T3 compared to the less well-finished ones (PAR T2- T3). Regression analysis showed that PAR Index at T1 and T2, age at T1, and length of retainer wear had a slight association with occlusal stability (R2 = 0.27). Patient satisfaction was significantly associated only with PAR Index at T3 (r2=0.125, P<.0001). We can conclude that, even thought orthodontic treatment is quite stable, not so well-finished treatments tend to show some improvement and well-finished ones deteriorate some in the long-term. Despite of that, well-finished patients still have better occlusal characteristics. Patient satisfaction is not related to the result of orthodontic treatment; nevertheless, there is a slight association with dentition in the long-term

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Hormone therapy is an important tool in the treatment of breast cancer and tamoxifen represents one of the most important drugs used in this type of treatment. Recently other drugs based on the inhibition of aromatase had been developed, this enzyme is responsible for the synthesis of estrogenic esteroids from the androgenic ones. The objective of this study would be the development of a quantitative cytological model of murine estral analysis that allowed the characterization of different hormone drugs effect over vaginal epithelium. The technique of monochromatic staining with Evans blue (C.I. 23860) showed to be efficient in the qualitative and quantitative classification of the cycle. It had been observed differences in the cytological standard of animals submitted to the studied drugs; tamoxifen presented a widening of phases of lesser maturation (diestrais), while anastrozole and exemestane increased the duration of the phases of larger maturation (estrais). The data were analysed through a cubical non linear regression (spline) which allowed a better characterization of the drugs, suggesting a proper cytological profile to the antagonism of the estrogen receptor (tamoxifen), aromatase competition (anastrozole) and inhibition of the enzyme (exemestane)

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This work aims to study the problem of the formal job in the Brazilian Northeast region and its effect in the social inclusion, taking for base the analysis of variables defined in the Atlas of Social Exclusion, which is based on the 2000 Brazilian Census, choosing the county as unit of analysis. As methodological options, an exploratory data analysis was performed, followed by multivariate statistical techniques, such as weighted multiple regression analysis, cluster analysis and exploratory analysis of spatial data. The results pointed out to low rates of formal job for the active age population as well as low indexes of social inclusion in the Northeast region of Brazil. A strong association of the formal job with the indicators of social inclusion under investigation, was evidenced (schooling, inequality, poverty, youth and income form government transfers), as well as a strong association of the formal job with the new index of social inclusion (IIS), modified from the IES. At the Federative Units, in which better levels of formal job had been found, good indexes of social inclusion are also observed. Highlights for the state of the Rio Grande do Norte, with the best conditions of life, and for the states of the Maranhão and Piauí, with the worst conditions. The situation of the Northeast region, facing the indicators under study, is very precarious, claiming for the necessity of emphasizing programs and governmental actions, specially directed to the raise of formal job levels of the region, reflecting, thus, in improvements on the income inequality, as well as in the social inclusion of the population of Northeastern natives.

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This study focuses on the central Brazilian historiography of science, focusing specifically on the life and work of a contemporaneous mathematician-physicist, and becomes part of the set of research results that investigate, organize and describe personal, intellectual and professional itineraries of Brazilian scientists and educators. The theme chosen for the study ran from seminars on Mathematics in Pará and is up to organize and describe the life history, education, professional experience and scientific production of William Mauricio Souza Marcos de La Penha (Guilherme de La Penha), considering their academic, professional and intellectual life history, so that their academic and intellectual production be spread over the Brazilian scientific and academic community. We adopted the historical research as theoretical and methodological base for the development of this study, rising arguments about the profile of Guilherme de La Penha to characterize him as a multiskill intellectual and to reveal that his thoughts about science, technology, training scientists and educators were in accordance with their writings and their professional practice in order to build a first story about the life and work of William de La Penha. In this sense, we took the theoretical aspects related to historical research, biographies, intellectual itineraries, files and inventories as sources and historical construction vehicles in order to point out the essential elements to form a profile of the transdisciplinary intellectual historians, ie a profile scientist who carries out the research, management and administration, as well as a committed educator to the on-going training and forming process. The results pointed in different directions, among which we highlight the creation of Seção Guilherme de La Penha at Universidade da Amazonia, producing several articles about the life and work of William de La Penha presented at national and international conferences and the proposal for documentary displays which could contribute to understanding the implementation of a scientific area in Pará State, an area that would not only be restricted to the production of knowledge, but more than that, it would include the spreading, which provides various means, primarily through education. Thus it was possible to ensure that La Penha has an intellectual profile that can be considered a multi-and transdisciplinary intellectual who defends the possibility of forming a scientist one and multiple, non-linear attitudes and dialogues with all other areas in order to be understood under a model scientist for the twenty-first century based on the model clearly inspired by the scientist authors with which he identified throughout their training and professional activities, like the three that stood out in their relationship science: Archimedes, Leonhard Euler and Cliford Ambrose Truesdell

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The ability to work, considered as resulting from a dynamic process between the individual resources in relation to their work, influenced from various factors such as sociodemographic, lifestyle, aging process and requirements of work. Aiming analyze the ability to work in a population of public servants, the study analyzed 132 public servants volunteers of the infrastructure sector, in a Federal Institution of Higher Education of the state of Rio Grande do Norte, Northeast, Brazil. Data were collected through a questionnaire called the Index of Capacity for Work - ICT. The variable analysis was done by using descriptive statistics of means, standard deviations, median minimum and maximum values of the scores of quantitative variables. The joint analysis of the variables was performed by multiple linear regression. The server had low capacity to work 11 (8.33%), moderate 31 (23.48%), good 54 (40.91), and Great 28 (21.21). Multiple regression analysis, adjusted for age, sex, education, age started to work, length of service, current capacity and full of disease, showed that best explained the variation of the CTI were age, current capacity and full of disease. The survey showed that 75% of the servers showed ICT below 43, so capacity low, moderate or good and only 25% of respondents had the CTI servers over 43 points, so great capacity for work. According to the recommendations of FIOH - Finnish Institute of Occupational Health, for servers that have these scores be implemented whose objective is to restore the ability to work which is low, improving the capacity for moderate work, support the capacity for the good work and maintain the ability to work great. Therefore, we recommend that the ICT is implemented in other units of the IFES survey in the perspective of achieving a real situation of all its servers, enabling the implementation of these measures as necessary to promote recovery and health of its employees.

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This paper aims to investigate the factors that influence the satisfaction and fidelity of tennis´s users with the region southern city of Natal, capital of Rio Grande do Norte as the area of analyzing , using the national satisfaction index models as a tool to study. In this study was used the questionnaire as a tool for collecting data based on the new Norwegian customer satisfaction barometer model proposed by Johnson et. al. (2001). The data collection took place during the months of May and June 2008, when 450 tennis´s users were interviewed. The main results obtained by multiple regression analysis and logistic regression showed that the users' satisfaction with the tennis´s brand is influenced by the quality, comfort, material used in the manufacture and price, while fidelity is potentized by the image of the brand and the satisfaction degree with the user's tennis and with the brand of tennis. In relation to user satisfaction with the tennis, that satisfaction is influenced by the quality, comfort, weight and the material used, while fidelity is potentized by the satisfaction with the tennis´s brand, with the possibility of paying the same amount again and the emotional commitment. As the processing of claims there was no direct influence on satisfaction and consumers fidelity due to the low number complaints

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This work presents a modelling and identification method for a wheeled mobile robot, including the actuator dynamics. Instead of the classic modelling approach, where the robot position coordinates (x,y) are utilized as state variables (resulting in a non linear model), the proposed discrete model is based on the travelled distance increment Delta_l. Thus, the resulting model is linear and time invariant and it can be identified through classical methods such as Recursive Least Mean Squares. This approach has a problem: Delta_l can not be directly measured. In this paper, this problem is solved using an estimate of Delta_l based on a second order polynomial approximation. Experimental data were colected and the proposed method was used to identify the model of a real robot

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Slugging is a well-known slugging phenomenon in multiphase flow, which may cause problems such as vibration in pipeline and high liquid level in the separator. It can be classified according to the place of its occurrence. The most severe, known as slugging in the riser, occurs in the vertical pipe which feeds the platform. Also known as severe slugging, it is capable of causing severe pressure fluctuations in the flow of the process, excessive vibration, flooding in separator tanks, limited production, nonscheduled stop of production, among other negative aspects that motivated the production of this work . A feasible solution to deal with this problem would be to design an effective method for the removal or reduction of the system, a controller. According to the literature, a conventional PID controller did not produce good results due to the high degree of nonlinearity of the process, fueling the development of advanced control techniques. Among these, the model predictive controller (MPC), where the control action results from the solution of an optimization problem, it is robust, can incorporate physical and /or security constraints. The objective of this work is to apply a non-conventional non-linear model predictive control technique to severe slugging, where the amount of liquid mass in the riser is controlled by the production valve and, indirectly, the oscillation of flow and pressure is suppressed, while looking for environmental and economic benefits. The proposed strategy is based on the use of the model linear approximations and repeatedly solving of a quadratic optimization problem, providing solutions that improve at each iteration. In the event where the convergence of this algorithm is satisfied, the predicted values of the process variables are the same as to those obtained by the original nonlinear model, ensuring that the constraints are satisfied for them along the prediction horizon. A mathematical model recently published in the literature, capable of representing characteristics of severe slugging in a real oil well, is used both for simulation and for the project of the proposed controller, whose performance is compared to a linear MPC

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The production of roof tiles in the state of Rio Grande do Norte accounts for around 60% of the total of ceramic pieces produced. There is a need for investment to improve quality and productivity, thereby promoting technological innovations. Accordingly, the aim of this study is to determine the effect of kaolin, potassium feldspar and quartz in two standard formulations, as well as the effect of sintering temperature on the technological properties of linear firing shrinkage, water absorption and bending rupture stress, by fitting the statistical model and using multiple linear regression to assess the relationship between technological properties and independent variables. The raw materials were characterized using the following techniques: X-ray fluorescence (XRF), X-ray diffraction (XRF), rational analysis (RA), differential thermal analysis (DTA) and granulometric analysis (GA). The test specimens were compacted by uniaxial pressure (25 MPa), dried in a stove at 110 ºC for 24 hours and sinterized at 850 ºC, 950 ºC and 1050 ºC and held isothermal for 30 minutes. The results obtained indicate that the addition of kaolin to two standard formulations (M and R) promoted a reduction in water absorption values and an increase in bending rupture stress values. The sintering temperatures for group M that resulted in the lowest linear firing shrinkage and water absorption values were 850 ºC and 950 ºC, respectively, and the highest bending rupture stress values were reached at a temperature of 950 ºC. In the case of group R, the sintering temperature that obtained the lowest water absorption and linear firing shrinkage values was 850 ºC, and the highest bending rupture stress values were attained at a temperature of 1050 ºC. This work explains the statistical approach used to fit the model that describes the relationship between the technological properties and percentage of kaolin, quartz and feldspar, as well as the models that enable predictions, provided that the lower and upper limits of the percentage of clay minerals, flux and quartz used in this study are respected. Statistica 6 software was used and results were obtained by stepwise forward regression

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Background: Obesity impairment to the pulmonary function related to the magnitude of adiposity and is associated with excessive daytime sleepiness (EDS) and snoring, among others symptoms of respiratory disorders related to sleep. It is possible that obese individuals with excessive daytime sleepiness may make changes in lung function on spirometry monitored during the day as a consequence of fragmented sleep or episodes of nocturnal hypoventilation that cause respiratory and changes that can persist throughout the day. The combination of these findings alone sleepiness observed by subjective scales with pulmonary function in obese patients is unknown. Objective: To assess the influence of EDS and snoring on pulmonary function in morbidly obese and distinguish between different anthropometric markers, the snoring and sleepiness which the best predictors of spirometric function and respiratory muscle strength and endurance of these patients. Methods: We evaluated 40 morbidly obese markers on the anthropometric, spirometric respiratory variables, maximal inspiratory and expiratory pressures (MIP and MEP) and maximal voluntary ventilation (MVV) and the measured excessive daytime sleepiness (the Epworth sleepiness scale) and snoring (snoring scale of Stanford). The data were treated when the differences between the groups of obese patients with and without sleepiness, whereas the anthropometric variables, respiratory and snoring. Pearson's correlation was performed, and multiple regression analysis assessed the predictors of pulmonary function. For this we used the software SPSS 15.0 for windows and p <0.05. Results: 39 obese patients were included (28 women), age 36.92+11.97y, body mass index (BMI) 49.3+5.1kg/m², waist-hip ratio (WHR) 0.96+0.07 and neck circumference (NC) 44.1+4.2 cm. Spirometric values and respiratory pressures were up 80% of predicted values, except for endurance (MVV <80%). Obese with EDS have lower tidal volume. Positive correlation was observed between BMI and EDS, EDS and NC and between snoring and BMI, and negative correlation between EDS and tidal volume (TV), and between snoring and snoring FVC and FEV1. In linear regression the best predictor of pulmonary function was snoring, followed by NC. NC has more obese with higher strength (MEP, p = 0.031) and endurance (MVV p = 0.018) respiratory muscle. Conclusion: Obese with EDS tend to have lower TV. In addition, snoring and NC can better predict pulmonary function in obese when compared with other anthropometric markers or EDS. Obese patients with higher NC tend to have greater capacity for overall strength of respiratory muscles, but may have low muscle endurance

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In this work, the quantitative analysis of glucose, triglycerides and cholesterol (total and HDL) in both rat and human blood plasma was performed without any kind of pretreatment of samples, by using near infrared spectroscopy (NIR) combined with multivariate methods. For this purpose, different techniques and algorithms used to pre-process data, to select variables and to build multivariate regression models were compared between each other, such as partial least squares regression (PLS), non linear regression by artificial neural networks, interval partial least squares regression (iPLS), genetic algorithm (GA), successive projections algorithm (SPA), amongst others. Related to the determinations of rat blood plasma samples, the variables selection algorithms showed satisfactory results both for the correlation coefficients (R²) and for the values of root mean square error of prediction (RMSEP) for the three analytes, especially for triglycerides and cholesterol-HDL. The RMSEP values for glucose, triglycerides and cholesterol-HDL obtained through the best PLS model were 6.08, 16.07 e 2.03 mg dL-1, respectively. In the other case, for the determinations in human blood plasma, the predictions obtained by the PLS models provided unsatisfactory results with non linear tendency and presence of bias. Then, the ANN regression was applied as an alternative to PLS, considering its ability of modeling data from non linear systems. The root mean square error of monitoring (RMSEM) for glucose, triglycerides and total cholesterol, for the best ANN models, were 13.20, 10.31 e 12.35 mg dL-1, respectively. Statistical tests (F and t) suggest that NIR spectroscopy combined with multivariate regression methods (PLS and ANN) are capable to quantify the analytes (glucose, triglycerides and cholesterol) even when they are present in highly complex biological fluids, such as blood plasma