A satisfação dos clientes internos e o comprometimento organizacional: um estudo à luz do modelo ASH nas indústrias alimentícias no RN

Currently the organizations are passing for continuous cycles of changes due to necessity of survival in the work market. The administration of the future points a way to the organizations of today and tomorrow, the search of the competitiveness from loyalty and motivation of its staff. Of this form, the model of the Auditoria do Sistema Humano (ASH), developed for Spanish researchers and that now it is being applied in Brazil, contemplates a series of dimensions about Human Resources management quality in the companies and the organizational effectiveness, such as the environment where the company is inserted, the strategies, the organizational drawing, the psychological and psychosocial processes, e the reached results. In this direction, the present research analyzed the factors of job satisfaction and organizational commitment, making, also, a relation of causality between the same ones. The quantitative-descriptive research had as population the employees of twenty three nourishing industries of the State of Rio Grande do Norte (Brazil), registered in the Federacy of the Industries of the state. The collection of the data occurred for the months of October of 2005 and March of 2006, by means of the application of questionnaire of model ASH. The sample was composed for 197 employees, however it was observed presence of five outliers, that they had been excluded from the analysis of the data. To extract the dimensions of the satisfaction and the commitment and identification the factorial analysis was used, with extraction method of principal components, rotation Varimax and normalization Kaiser. The gotten dimensions had been evaluated with the calculation of the coefficient Alpha of Cronbach. The factorial analysis of the pointers of the organizational commitment and identification had extracted ten factors. Of these, four had gotten significance of the analyses inside: affective commitment, values commitment, continuance commitment and necessity commitment. The result of the analysis of the pointers of job satisfaction indicated four factors: extrinsic, motivations, relation with the friends and auto-accomplishment. To deal with the data the relation between job satisfaction and organizational commitment it was used technique of multiple regression. The correlation between commitment and satisfaction was satisfactory, detaching the affective commitment with bigger index of correlation, followed of the affective one

Processamento Inteligente de Sinais de Pressão e Temperatura Adquiridos Através de Sensores Permanentes em Poços de Petróleo

Originally aimed at operational objectives, the continuous measurement of well bottomhole pressure and temperature, recorded by permanent downhole gauges (PDG), finds vast applicability in reservoir management. It contributes for the monitoring of well performance and makes it possible to estimate reservoir parameters on the long term. However, notwithstanding its unquestionable value, data from PDG is characterized by a large noise content. Moreover, the presence of outliers within valid signal measurements seems to be a major problem as well. In this work, the initial treatment of PDG signals is addressed, based on curve smoothing, self-organizing maps and the discrete wavelet transform. Additionally, a system based on the coupling of fuzzy clustering with feed-forward neural networks is proposed for transient detection. The obtained results were considered quite satisfactory for offshore wells and matched real requisites for utilization

Análise estatística de impedância da pele

In this work we analyze the skin bioimpedance statistical distribution. We focus on the study of two distinct samples: the statistics of impedance of several points in the skin of a single individual and the statistics over a population (many individuals) but in a single skin point. The impedance data was obtained from the literature (Pearson, 2007). Using the Shapiro-Wilk test and the assymmetry test we conclude that the impedance of a population is better described by an assymetric and non-normal distribution. On the other side, the data concerning the individual impedance seems to follow a normal distribution. We have performed a goodnes of fitting test and the better distribution to fit the data of a population is the log-normal distribution. It is interesting to note that our result for skin impedance is in simtony with body impedance from the literature of electrical engeneering. Our results have an impact over the statistical planning and modelling of skin impedance experiments. Special attention we should drive to the treatment of outliers in this kind of dataset. The results of this work are important in the general discussion of low impedance of points of acupuncture and also in the problem of skin biopotentials used in equipments like the Electrodermal Screen Tests.

FERRITINA: intervalos de referência para adultos no Estado do Rio Grande do Norte

Ferritin is a protein composed of heavy and light chains, non-covalently linked and which accommodates, in its core, thousands of atoms of iron. Furthermore, this protein represents the stock of iron in the body and it is characterized as an acute marker and predictor of diseases, such as iron deficiency anemia, hereditary hemochromatosis and others. Considering the variability of reference values and the analytical methods currently available, the aim of this work was to propose 95% confidence intervals for adults in the State of Rio Grande do Norte, Brazil, after determining the average concentration of serum ferritin for both sexes, beyond its correlation with the age. We analyzed 385 blood samples, collected by venipuncture from individuals residing in the State, after 12-14 hours of fast. The populational sample had 169 men and 216 women between 18-59 years old, which filled a questionnaire on socioeconomic, food habits and accounts about previous and current diseases. The sample collections were itinerant and the results of erythrogram, fasting glucose, alanine aminotransferase, aspartate aminotransferase, γ-glutamyl transferase, urea, creatinine, leukocyte count and platelets, beyond C-reactive protein, were issued to each participant, so that, after selection of the apparently healthy individuals, the dosage of serum ferritin was carried out. Statistical analysis was performed using the softwares SPSS 11.0 Windows version, Epi Info 3.3.2 and Graf instant pad (version 3.02), and the random population sample was single (finite population), for which the test of linear correlation and diagram of dispersion were also made. After selection of individuals and determination of serum ferritin, the most discrepant outliers were disregarded (N = 358, Men = 154/Women = 207) and the average value determined for the masculine sex individuals was 167,18 ng / dL; for the feminine sex individuals, the average value obtained was 81,55 ng / dL. Moreover, we found that 25% of men had values < 90,30 ng / dL; 50% ≤ 156,25 ng / dL and 75% ≤ 229,00 ng / dL. In the group of women, 25% had values < 38,80 ng / dL; 50% ≤ 65,00 ng / dL and 75% ≤ 119,00 ng / dL. Through the correlation coefficient (r = 0,23 with p = 0,003), it is possible to suggest the existence of positive linear correlation between age and serum ferritin for men. The correlation coefficient for women (r = 0,16 with p = 0,025) also confirms the existence of positive linear correlation between serum ferritin and age. Considering the analysis carried out and specific methods corroborating with the proposed benchmarks, we concluded that the average value found for men is higher than that found for women. Furthermore, this scenario rises with age for both sexes, and the 95% confidence intervals obtained were 74 ng/dL ≤ μ ≤ 89 ng/dL and 152ng/dL ≤ μ ≤183ng/dL for the feminine and masculine sex individuals respectively

Eficiência nos gastos públicos em educação fundamental: uma análise nos municípios do estado do Rio Grande do Norte, 2007 e 2011

This paper aims to measure the degree of efficiency in the allocation of public resources in education from the FUNDEB in elementary education in the towns of Rio Grande do Norte in 2007 and 2011. To do so, we must determine to evaluate the efficiency in the allocation of public resources in municipal education in the early and last grades of elementary education; verify that the towns that achieved higher levels of efficiency that were allocated the largest volumes of resources in primary education and analyze which towns reached the worst and the best levels of efficiency in the allocation of public resources in education. This is on the assumption that the relation between the educational policies of local governments and concern for efficiency in the allocation of resources in education is limited only to increase spending on education. It is intended from the model of Data Envelopment analysis, (DEA), with Variable Returns to Scale (VRS), estimate the efficiency of spending on education and municipal pubic purging the problem of outliers. Estimations show that the municipalities of Rio Grande do Norte do not allocate their resources in public elementary education efficiently

Detecção e diagnóstico de falhas não-supervisionados baseados em estimativa de densidade recursiva e classificador fuzzy auto-evolutivo

In this work, we propose a two-stage algorithm for real-time fault detection and identification of industrial plants. Our proposal is based on the analysis of selected features using recursive density estimation and a new evolving classifier algorithm. More specifically, the proposed approach for the detection stage is based on the concept of density in the data space, which is not the same as probability density function, but is a very useful measure for abnormality/outliers detection. This density can be expressed by a Cauchy function and can be calculated recursively, which makes it memory and computational power efficient and, therefore, suitable for on-line applications. The identification/diagnosis stage is based on a self-developing (evolving) fuzzy rule-based classifier system proposed in this work, called AutoClass. An important property of AutoClass is that it can start learning from scratch". Not only do the fuzzy rules not need to be prespecified, but neither do the number of classes for AutoClass (the number may grow, with new class labels being added by the on-line learning process), in a fully unsupervised manner. In the event that an initial rule base exists, AutoClass can evolve/develop it further based on the newly arrived faulty state data. In order to validate our proposal, we present experimental results from a level control didactic process, where control and error signals are used as features for the fault detection and identification systems, but the approach is generic and the number of features can be significant due to the computationally lean methodology, since covariance or more complex calculations, as well as storage of old data, are not required. The obtained results are significantly better than the traditional approaches used for comparison

Estudo Comparativo de gráaficos de probabilidade normal para Anáalise de experimentos fatoriais não replicados

Two-level factorial designs are widely used in industrial experimentation. However, many factors in such a design require a large number of runs to perform the experiment, and too many replications of the treatments may not be feasible, considering limitations of resources and of time, making it expensive. In these cases, unreplicated designs are used. But, with only one replicate, there is no internal estimate of experimental error to make judgments about the significance of the observed efects. One of the possible solutions for this problem is to use normal plots or half-normal plots of the efects. Many experimenters use the normal plot, while others prefer the half-normal plot and, often, for both cases, without justification. The controversy about the use of these two graphical techniques motivates this work, once there is no register of formal procedure or statistical test that indicates \which one is best". The choice between the two plots seems to be a subjective issue. The central objective of this master's thesis is, then, to perform an experimental comparative study of the normal plot and half-normal plot in the context of the analysis of the 2k unreplicated factorial experiments. This study involves the construction of simulated scenarios, in which the graphics performance to detect significant efects and to identify outliers is evaluated in order to verify the following questions: Can be a plot better than other? In which situations? What kind of information does a plot increase to the analysis of the experiment that might complement those provided by the other plot? What are the restrictions on the use of graphics? Herewith, this work intends to confront these two techniques; to examine them simultaneously in order to identify similarities, diferences or relationships that contribute to the construction of a theoretical reference to justify or to aid in the experimenter's decision about which of the two graphical techniques to use and the reason for this use. The simulation results show that the half-normal plot is better to assist in the judgement of the efects, while the normal plot is recommended to detect outliers in the data

Estrutura e desempenho organizacional: uma análise na Universidade Federal do Rio Grande do Norte

This research analyses the components of the organizational structure of the UFRN (Rio Grande do Norte Federal University) and to what extent they affect organizational performance. The study, classified as exploratory and descriptive, was conducted in two phases. The first phase consists of a pilot test to refine the research instrument and to identify the latent components of the organizational structure, and the second to characterize these components and thereby establish relationships with organizational performance. In the first phase, the research was conducted in 20 UFRN organizational units with the participation of 84 employees between technical-administrative and teachers, after considering missing values and outliers, while the second phase occurred in two stages: one conducted with 279 valid cases, consisting of technical-administrative and teachers of 37 UFRN units, and another with 112 managers of the institution in the 49 units identified in this research. The instrument adopted in the first phase was composed of 36 indicators of organizational structure, with six extracted and adapted from the instrument developed by Medeiros (2003) and 30 prepared based on the literature review, from Mintzberg (2012), Hall (1984), Vasconcellos and Hemsley (1997) and Seiffert and Costa (2007) and 7 performance indicators adapted from Fleury and Mills (2006), Vieira and Vieira (2003) and Kaplan and Norton (1997) from the self-assessment instrument in use by the university. In this stage the data were analyzed using the techniques of factor analysis and reliability analysis by means of Cronbach’s alpha, aiming to extract the factors representing the components of the organizational structure. In step 1 of the second phase, the instrument, refined and reduced in the previous phase, with 24 variables of organizational structure and 6 for performance was used, while in step 2, a semi-structured interview guide with questions, organized into nine organizational structure elements, was adopted aiming to gather information to understand the relationship of structure to performance of the UFRN. The techniques used in the second phase, as a whole, were factor analysis and reliability analysis to characterize the components extracted in the previous phase and to validate the performance variables and correlation analysis, regression and content analysis to establish and understand the relationship between structure and performance. The results showed, in the two stages, six latent components of organizational structure in the context under study: training and internalization, communication, hierarchy, decentralization, formalization and departmentalization - with high levels of Cronbach's alpha indexes - which can thereby be characterized as components of UFRN structure. Six performance indicators were validated in this study, showing them as efficient and highly reliable. Finally, it was found that the formalization, communication, decentralization, training and internalization components positively affect UFRN performance, while departmentalization has an adverse affect and hierarchy did not show a significant relationship. The results achieved in this work are important in future studies to support the development of a model structure that represents the specifics of the university

Gráfico de controle modificado para processos com estruturas complexas de autocorrelação

This work proposes a modified control chart incorporating concepts of time series analysis. Specifically, we considerer Gaussian mixed transition distribution (GMTD) models. The GMTD models are a more general class than the autorregressive (AR) family, in the sense that the autocorrelated processes may present flat stretches, bursts or outliers. In this scenario traditional Shewhart charts are no longer appropriate tools to monitoring such processes. Therefore, Vasilopoulos and Stamboulis (1978) proposed a modified version of those charts, considering proper control limits based on autocorrelated processes. In order to evaluate the efficiency of the proposed technique a comparison with a traditional Shewhart chart (which ignores the autocorrelation structure of the process), a AR(1) Shewhart control chart and a GMTD Shewhart control chart was made. An analytical expression for the process variance, as well as control limits were developed for a particular GMTD model. The ARL was used as a criteria to measure the efficiency of control charts. The comparison was made based on a series generated according to a GMTD model. The results point to the direction that the modified Shewhart GMTD charts have a better performance than the AR(1) Shewhart and the traditional Shewhart.

Estudo do balanço de umidade por meio de modelos regionais para o clima do passado e do futuro sobre a América do Sul

In the context of climate change over South America (SA) has been observed that the combination of high temperatures and rain more temperatures less rainfall, cause different impacts such as extreme precipitation events, favorable conditions for fires and droughts. As a result, these regions face growing threat of water shortage, local or generalized. Thus, the water availability in Brazil depends largely on the weather and its variations in different time scales. In this sense, the main objective of this research is to study the moisture budget through regional climate models (RCM) from Project Regional Climate Change Assessments for La Plata Basin (CLARIS-LPB) and combine these RCM through two statistical techniques in an attempt to improve prediction on three areas of AS: Amazon (AMZ), Northeast Brazil (NEB) and the Plata Basin (LPB) in past climates (1961-1990) and future (2071-2100). The moisture transport on AS was investigated through the moisture fluxes vertically integrated. The main results showed that the average fluxes of water vapor in the tropics (AMZ and NEB) are higher across the eastern and northern edges, thus indicating that the contributions of the trade winds of the North Atlantic and South are equally important for the entry moisture during the months of JJA and DJF. This configuration was observed in all the models and climates. In comparison climates, it was found that the convergence of the flow of moisture in the past weather was smaller in the future in various regions and seasons. Similarly, the majority of the SPC simulates the future climate, reduced precipitation in tropical regions (AMZ and NEB), and an increase in the LPB region. The second phase of this research was to carry out combination of RCM in more accurately predict precipitation, through the multiple regression techniques for components Main (C.RPC) and convex combination (C.EQM), and then analyze and compare combinations of RCM (ensemble). The results indicated that the combination was better in RPC represent precipitation observed in both climates. Since, in addition to showing values be close to those observed, the technique obtained coefficient of correlation of moderate to strong magnitude in almost every month in different climates and regions, also lower dispersion of data (RMSE). A significant advantage of the combination of methods was the ability to capture extreme events (outliers) for the study regions. In general, it was observed that the wet C.EQM captures more extreme, while C.RPC can capture more extreme dry climates and in the three regions studied.

Critério de correntropia no treinamento de redes fuzzy wavelet neural networks para identificação de sistemas dinâmicos não lineares

The great interest in nonlinear system identification is mainly due to the fact that a large amount of real systems are complex and need to have their nonlinearities considered so that their models can be successfully used in applications of control, prediction, inference, among others. This work evaluates the application of Fuzzy Wavelet Neural Networks (FWNN) to identify nonlinear dynamical systems subjected to noise and outliers. Generally, these elements cause negative effects on the identification procedure, resulting in erroneous interpretations regarding the dynamical behavior of the system. The FWNN combines in a single structure the ability to deal with uncertainties of fuzzy logic, the multiresolution characteristics of wavelet theory and learning and generalization abilities of the artificial neural networks. Usually, the learning procedure of these neural networks is realized by a gradient based method, which uses the mean squared error as its cost function. This work proposes the replacement of this traditional function by an Information Theoretic Learning similarity measure, called correntropy. With the use of this similarity measure, higher order statistics can be considered during the FWNN training process. For this reason, this measure is more suitable for non-Gaussian error distributions and makes the training less sensitive to the presence of outliers. In order to evaluate this replacement, FWNN models are obtained in two identification case studies: a real nonlinear system, consisting of a multisection tank, and a simulated system based on a model of the human knee joint. The results demonstrate that the application of correntropy as the error backpropagation algorithm cost function makes the identification procedure using FWNN models more robust to outliers. However, this is only achieved if the gaussian kernel width of correntropy is properly adjusted.

A satisfação dos clientes internos e o comprometimento organizacional: um estudo à luz do modelo ASH nas indústrias alimentícias do RN

Currently the organizations are passing for continuous cycles of changes due to necessity of survival in the work market. The administration of the future points a way to the organizations of today and tomorrow, the search of the competitiveness from loyalty and motivation of its staff. Of this form, the model of the Auditoria do Sistema Humano (ASH), developed for Spanish researchers and that now it is being applied in Brazil, contemplates a series of dimensions about Human Resources management quality in the companies and the organizational effectiveness, such as the environment where the company is inserted, the strategies, the organizational drawing, the psychological and psychosocial processes, e the reached results. In this direction, the present research analyzed the factors of job satisfaction and organizational commitment, making, also, a relation of causality between the same ones. The quantitative-descriptive research had as population the employees of twenty three nourishing industries of the State of Rio Grande do Norte (Brazil), registered in the Federacy of the Industries of the state. The collection of the data occurred for the months of October of 2005 and March of 2006, by means of the application of questionnaire of model ASH. The sample was composed for 197 employees, however it was observed presence of five outliers, that they had been excluded from the analysis of the data. To extract the dimensions of the satisfaction and the commitment and identification the factorial analysis was used, with extraction method of principal components, rotation Varimax and normalization Kaiser. The gotten dimensions had been evaluated with the calculation of the coefficient Alpha of Cronbach. The factorial analysis of the pointers of the organizational commitment and identification had extracted ten factors. Of these, four had gotten significance of the analyses inside: affective commitment, values commitment, continuance commitment and necessity commitment. The result of the analysis of the pointers of job satisfaction indicated four factors: extrinsic, motivations, relation with the friends and auto-accomplishment. To deal with the data the relation between job satisfaction and organizational commitment it was used technique of multiple regression. The correlation between commitment and satisfaction was satisfactory, detaching the affective commitment with bigger index of correlation, followed of the affective one

Processamento Inteligente de Sinais de Pressão e Temperatura Adquiridos Através de Sensores Permanentes em Poços de Petróleo

Originally aimed at operational objectives, the continuous measurement of well bottomhole pressure and temperature, recorded by permanent downhole gauges (PDG), finds vast applicability in reservoir management. It contributes for the monitoring of well performance and makes it possible to estimate reservoir parameters on the long term. However, notwithstanding its unquestionable value, data from PDG is characterized by a large noise content. Moreover, the presence of outliers within valid signal measurements seems to be a major problem as well. In this work, the initial treatment of PDG signals is addressed, based on curve smoothing, self-organizing maps and the discrete wavelet transform. Additionally, a system based on the coupling of fuzzy clustering with feed-forward neural networks is proposed for transient detection. The obtained results were considered quite satisfactory for offshore wells and matched real requisites for utilization