Análise de agrupamentos dos dados de DFA oriundos de perfis elétricos de indução de poços de petróleo

The main objective of this study is to apply recently developed methods of physical-statistic to time series analysis, particularly in electrical induction s profiles of oil wells data, to study the petrophysical similarity of those wells in a spatial distribution. For this, we used the DFA method in order to know if we can or not use this technique to characterize spatially the fields. After obtain the DFA values for all wells, we applied clustering analysis. To do these tests we used the non-hierarchical method called K-means. Usually based on the Euclidean distance, the K-means consists in dividing the elements of a data matrix N in k groups, so that the similarities among elements belonging to different groups are the smallest possible. In order to test if a dataset generated by the K-means method or randomly generated datasets form spatial patterns, we created the parameter Ω (index of neighborhood). High values of Ω reveals more aggregated data and low values of Ω show scattered data or data without spatial correlation. Thus we concluded that data from the DFA of 54 wells are grouped and can be used to characterize spatial fields. Applying contour level technique we confirm the results obtained by the K-means, confirming that DFA is effective to perform spatial analysis

Análise de Agrupamentos Com Base na Teoria da Informação: Uma Abordagem Representativa

Currently, one of the biggest challenges for the field of data mining is to perform cluster analysis on complex data. Several techniques have been proposed but, in general, they can only achieve good results within specific areas providing no consensus of what would be the best way to group this kind of data. In general, these techniques fail due to non-realistic assumptions about the true probability distribution of the data. Based on this, this thesis proposes a new measure based on Cross Information Potential that uses representative points of the dataset and statistics extracted directly from data to measure the interaction between groups. The proposed approach allows us to use all advantages of this information-theoretic descriptor and solves the limitations imposed on it by its own nature. From this, two cost functions and three algorithms have been proposed to perform cluster analysis. As the use of Information Theory captures the relationship between different patterns, regardless of assumptions about the nature of this relationship, the proposed approach was able to achieve a better performance than the main algorithms in literature. These results apply to the context of synthetic data designed to test the algorithms in specific situations and to real data extracted from problems of different fields

Análise de agrupamentos dos dados de DFA oriundos de perfis elétricos de indução de poços de petróleo

The main objective of this study is to apply recently developed methods of physical-statistic to time series analysis, particularly in electrical induction s profiles of oil wells data, to study the petrophysical similarity of those wells in a spatial distribution. For this, we used the DFA method in order to know if we can or not use this technique to characterize spatially the fields. After obtain the DFA values for all wells, we applied clustering analysis. To do these tests we used the non-hierarchical method called K-means. Usually based on the Euclidean distance, the K-means consists in dividing the elements of a data matrix N in k groups, so that the similarities among elements belonging to different groups are the smallest possible. In order to test if a dataset generated by the K-means method or randomly generated datasets form spatial patterns, we created the parameter Ω (index of neighborhood). High values of Ω reveals more aggregated data and low values of Ω show scattered data or data without spatial correlation. Thus we concluded that data from the DFA of 54 wells are grouped and can be used to characterize spatial fields. Applying contour level technique we confirm the results obtained by the K-means, confirming that DFA is effective to perform spatial analysis

Análise de DFA e de agrupamento do perfil de densidade de poços de petróleo

In recent years, the DFA introduced by Peng, was established as an important tool capable of detecting long-range autocorrelation in time series with non-stationary. This technique has been successfully applied to various areas such as: Econophysics, Biophysics, Medicine, Physics and Climatology. In this study, we used the DFA technique to obtain the Hurst exponent (H) of the profile of electric density profile (RHOB) of 53 wells resulting from the Field School of Namorados. In this work we want to know if we can or not use H to spatially characterize the spatial data field. Two cases arise: In the first a set of H reflects the local geology, with wells that are geographically closer showing similar H, and then one can use H in geostatistical procedures. In the second case each well has its proper H and the information of the well are uncorrelated, the profiles show only random fluctuations in H that do not show any spatial structure. Cluster analysis is a method widely used in carrying out statistical analysis. In this work we use the non-hierarchy method of k-means. In order to verify whether a set of data generated by the k-means method shows spatial patterns, we create the parameter Ω (index of neighborhood). High Ω shows more aggregated data, low Ω indicates dispersed or data without spatial correlation. With help of this index and the method of Monte Carlo. Using Ω index we verify that random cluster data shows a distribution of Ω that is lower than actual cluster Ω. Thus we conclude that the data of H obtained in 53 wells are grouped and can be used to characterize space patterns. The analysis of curves level confirmed the results of the k-means

DFA e análise de agrupamento aplicadas a perfis de porosidade neutrônico em poços de petróleo

Peng was the first to work with the Technical DFA (Detrended Fluctuation Analysis), a tool capable of detecting auto-long-range correlation in time series with non-stationary. In this study, the technique of DFA is used to obtain the Hurst exponent (H) profile of the electric neutron porosity of the 52 oil wells in Namorado Field, located in the Campos Basin -Brazil. The purpose is to know if the Hurst exponent can be used to characterize spatial distribution of wells. Thus, we verify that the wells that have close values of H are spatially close together. In this work we used the method of hierarchical clustering and non-hierarchical clustering method (the k-mean method). Then compare the two methods to see which of the two provides the best result. From this, was the parameter � (index neighborhood) which checks whether a data set generated by the k- average method, or at random, so in fact spatial patterns. High values of � indicate that the data are aggregated, while low values of � indicate that the data are scattered (no spatial correlation). Using the Monte Carlo method showed that combined data show a random distribution of � below the empirical value. So the empirical evidence of H obtained from 52 wells are grouped geographically. By passing the data of standard curves with the results obtained by the k-mean, confirming that it is effective to correlate well in spatial distribution

Análise de DFA e de agrupamento do perfil de densidade de poços de petróleo

In recent years, the DFA introduced by Peng, was established as an important tool capable of detecting long-range autocorrelation in time series with non-stationary. This technique has been successfully applied to various areas such as: Econophysics, Biophysics, Medicine, Physics and Climatology. In this study, we used the DFA technique to obtain the Hurst exponent (H) of the profile of electric density profile (RHOB) of 53 wells resulting from the Field School of Namorados. In this work we want to know if we can or not use H to spatially characterize the spatial data field. Two cases arise: In the first a set of H reflects the local geology, with wells that are geographically closer showing similar H, and then one can use H in geostatistical procedures. In the second case each well has its proper H and the information of the well are uncorrelated, the profiles show only random fluctuations in H that do not show any spatial structure. Cluster analysis is a method widely used in carrying out statistical analysis. In this work we use the non-hierarchy method of k-means. In order to verify whether a set of data generated by the k-means method shows spatial patterns, we create the parameter Ω (index of neighborhood). High Ω shows more aggregated data, low Ω indicates dispersed or data without spatial correlation. With help of this index and the method of Monte Carlo. Using Ω index we verify that random cluster data shows a distribution of Ω that is lower than actual cluster Ω. Thus we conclude that the data of H obtained in 53 wells are grouped and can be used to characterize space patterns. The analysis of curves level confirmed the results of the k-means

Autoeficácia, características sociodemográficas e capacitação profissional: um estudo com servidores de uma Universidade Federal

Self-efficacy, the construct developed by Albert Bandura in 1977 and widely studied around the world, means the individual's belief in his own capacity to successfully perform a certain activity. This study aims to determine the degree of association between sociodemographic characteristics and professional training to the levels of Self-Efficacy at Work (SEW) of the Administrative Assistants in a federal university. This is a descriptive research submitted to and approved by the Ethics Committee of UFRN. The method of data analysis, in quantitative nature, was accomplished with the aid of the statistical programs R and Minitab. The instrument used in research was a sociodemographic data questionnaire, variables of professional training and the General Perception of Self-efficacy Scale (GPSES), applied to the sample by 289 Assistants in Administration. Statistical techniques for data analysis were descriptive statistics, cluster analysis, reliability test (Cronbach's alpha), and test of significance (Pearson). Results show a sociodemographic profile of Assistants in Administration of UFRN with well-distributed characteristics, with 48.4% men and 51.6% female; 59.9% of them were aged over 40 years, married (49.3%), color or race white (58%) and Catholics (67.8%); families are composed of up to four people (75.8%) with children (59.4%) of all age groups; the occupation of the mothers of these professionals is mostly housewives (51.6%) with high school education up to parents (72%) and mothers (75.8%). Assistants in Administration have high levels of professional training, most of them composed two groups of servers: the former, recently hired public servants (30.7%) and another with long service (59%), the majority enter young in career and it stays until retirement, 72.4% of these professionals have training above the minimum requirement for the job. The analysis of SEW levels shows medium to high levels for 72% of assistants in administration; low SEWclassified people have shown a high average of 2.7, considered close to the overall mean presented in other studies, which is 2.9. The cluster analysis has allowed us to say that the characteristics of the three groups (Low, Medium and High SEW) are similar and can be found in the three levels of SEW representatives with all the characteristics investigated. The results indicate no association between the sociodemographic variables and professional training to the levels of self-efficacy at work of Assistants in Administration of UFRN, except for the variable color or race. However, due to the small number of people who declared themselves in color or black race (4% of the sample), this result can be interpreted as mere coincidence or the black people addressed in this study have provided a sense of efficacy higher than white and brown ones. The study has corroborated other studies and highlighted the subjectivity of the self-efficacy construct. They are needed more researches, especially with public servants for the continuity and expansion of studies on the subject, making it possible to compare and confirm the results

Percepções de maturidade em gerenciamento de projetos à luz da nova gestão pública: uma investigação com gestores das secretarias estaduais do Rio Grande do Norte

This study aimed to measure the perception of maturity project management of state boards of Rio Grande do Norte by the perception of its managers. Argues that project management has been highlighted as a critical factor for the success of any organization, because the projects are directly related to the set of activities that result in organizational innovation as products, services and processes and the improvement of project management is directly aligned with the main pillars of the New Public Management. Methodologically, this is a quantitative research of a descriptive nature in which 161 forms were applied with coordinators and subcoordinators of state departments of Rio Grande do Norte, culminating in a sampling error of less than 6% to 95% confidence according to the procedures finite sampling. The process of tabulation and analysis was done using the package Statistical Package for Social Sciences - SPSS 18.0 and worked with techniques such as mean, standard deviation, frequency distributions, cluster analysis and factor analysis. The results indicate that the levels of maturity in project management in state departments of Rio Grande do Norte is below the national average and that behavioral skills are the main problem for improving management in these departments. It was possible to detect the existence of two groups of different perceptions about the management of projects, indicating, according to the managers, there are islands of excellence in project management in some sectors of the state departments. It was also observed that there are eight factors that affect maturity in project management: Planning and Control , Development of Management Skills , Project Management Environment , Acceptance of the Subject Project Management , Stimulus to Performance , Project Evaluation and Learning , Project Management Office and Visibility of Project Managers . It concludes that the project management in state departments of Rio Grande do Norte has no satisfactory levels of maturity in project management, affecting the levels of efficiency and effectiveness of the state apparatus, which shows that some of the assumptions that guide the New Public Management are not getting the levels of excellence nailed by this management model

Modelagem estocástica do índice de radiação ultravioleta na costa leste do nordeste do Brasil

The increase in ultraviolet radiation (UV) at surface, the high incidence of non-melanoma skin cancer (NMSC) in coast of Northeast of Brazil (NEB) and reduction of total ozone were the motivation for the present study. The overall objective was to identify and understand the variability of UV or Index Ultraviolet Radiation (UV Index) in the capitals of the east coast of the NEB and adjust stochastic models to time series of UV index aiming make predictions (interpolations) and forecasts / projections (extrapolations) followed by trend analysis. The methodology consisted of applying multivariate analysis (principal component analysis and cluster analysis), Predictive Mean Matching method for filling gaps in the data, autoregressive distributed lag (ADL) and Mann-Kendal. The modeling via the ADL consisted of parameter estimation, diagnostics, residuals analysis and evaluation of the quality of the predictions and forecasts via mean squared error and Pearson correlation coefficient. The research results indicated that the annual variability of UV in the capital of Rio Grande do Norte (Natal) has a feature in the months of September and October that consisting of a stabilization / reduction of UV index because of the greater annual concentration total ozone. The increased amount of aerosol during this period contributes in lesser intensity for this event. The increased amount of aerosol during this period contributes in lesser intensity for this event. The application of cluster analysis on the east coast of the NEB showed that this event also occurs in the capitals of Paraiba (João Pessoa) and Pernambuco (Recife). Extreme events of UV in NEB were analyzed from the city of Natal and were associated with absence of cloud cover and levels below the annual average of total ozone and did not occurring in the entire region because of the uneven spatial distribution of these variables. The ADL (4, 1) model, adjusted with data of the UV index and total ozone to period 2001-2012 made a the projection / extrapolation for the next 30 years (2013-2043) indicating in end of that period an increase to the UV index of one unit (approximately), case total ozone maintain the downward trend observed in study period

Convergência ou divergência no desenvolvimento? um estudo multidimensional para o sudeste e o nordeste do Brasil, 1990-2010

The analysis of some aspects of development in Brazil in the past three decades reveals an improvement on a range of indicators isolated in the south east the richest region and north east the poorest region. From a database of twenty variables, the main purpose the study was to verify if there are indications of convergence or divergence in five dimensions of development between the two regions from 1990 to 2010. Aiming to identify the states more similar and different, and to verify changes in the composition of low development groups and high development in the adressed period, was used the analysis of groupings (Cluster Analysis). Additionally, to test equality of distance between states all the time, was used the non-parametric Test of Wilcoxon. This makes it possible to verify IF the distance between the states of two regions has been increasing or has been falling, showing signs of divergence or convergence. The results of Cluster s analysis suggest that there are indications of convergence inside the cluster of north east, but the distance between two regions has not changed. The results of test of Wilcoxon suggests that there have been no changes statistically significant in the distance between the states, in the two regions the standards of development became more homogenous, but the two regions will be far apart

Gestão ambiental na indústria do petróleo :um estudo sobre as práticas de gestão na perspectiva da aprendizagem organizacional

This work discusses the environmental management thematic, on the basis of ISO 14001 standard and learning organization. This study is carried through an exploratory survey in a company of fuel transport, located in Natal/RN. The objective of this research was to investigate the practices of environmental management, carried through in the context of an implemented ISO 14001 environmental management system, in the researched organization, from the perspective of the learning organization. The methodology used in this work is supported in the quantitative method, combining the exploratory and descriptive types, and uses the technique of questionnaires, having as scope of the research, the managers, employee controlling, coordinators, supervisors and - proper and contracted - of the company. To carry through the analysis of the data of this research, it was used software Excel and Statistical version 6.0. The analysis of the data is divided in two parts: descriptive analysis and analysis of groupings (clusters). The results point, on the basis of the studied theory, as well as in the results of the research, that the implemented ISO 14001 environmental system in the searched organization presents elements that promote learning organization. From the results, it can be concluded that the company uses external information in the decision taking on environmental problems; that the employees are mobilized to generate ideas and to collect n environmental information and that the company has carried through partnerships in the activities of the environmental area with other companies. All these item cited can contribute for the generation of knowledge of the organization. It can also be concluded that the company has evaluated environmental errors occurrences in the past, as well as carried through environmental benchmarking. These practical can be considered as good ways of the company to acquire knowledge. The results also show that the employees have not found difficulties in the accomplishment of the tasks when the manager of its sector is not present. This result can demonstrate that the company has a good diffusion of knowledge

Fatores inibidores do uso de técnicas ambientais nos postos de combustíveis: um estudo de caso em Natal/RN

The objective of this work was to investigate the factors that inhibit the use of Environmental Techniques in the Gas Station of the city of Natal/RN. For this, a survey with the aid of a questionnaire was used like research instrument. It s used a sample for convenience, not probabilistic. For collection of the data, it was used directly application of the questionnaire to the Managers or Assistant managers of the gas station, in accordance with its availability or presence. The data was collected in all the regions of Natal (North, South, East and West). The population in accordance with the data of the ANP of September 2005 is of 111 ranks and the collected sample was of 86. To carry through the analysis of the data of this research had been used softwares Excel and Statistic version 5.0, for Windows. The analysis of data is divided in two parts; descriptive analysis and analysis of groupings (clusters). The results showed that bigger part of the interviewed ones has between 30 and 39 years of age; they have second grade completed; they had declared to have little between and reasonable knowledge how much to the use of Clean Technology (CT) in gas station; and a small part of the interviewed ones had informed to have much knowledge how much the resolutions of the CONAMA established for the Gas Station. Of the searched ranks, the majority is national(76.7%); the most accurate practice environmental used in the gas station are: it collects selective of oil used or contaminated and ecological tanks - coated with strengthened fibre glass; great part of the interviewed ones (33.8%) informed that never the TL makes planning of referring future action; about of the half of the interviewed ones (84.9%) they had more declared that its employees have of none to a reasonable level of training for deal with problems that compromise the environment; the majority of the ranks (72.1%) functions has for more then six years. It is observed that almost all the interviewed ones (96.5%) evaluate as being important or very important the implantation of CT in Gas Station and the great majority (82.1%) evaluates the difficulty in if implanting these technologies in Gas Station as being easy or very easy. In the analysis of cluster, it was verified existence of two groupings (as much in the variable of the barriers and benefits), being that inside of each clusters exists homogeneity and between clusters exists heterogeneity. In reality, everything is important or very important in the opinion of the interviewed ones. There only exists a small significant difference that separates them in clusters

Gestão ambiental em cadeias produtivas agroindustriais: um estudo em um aglomerado produtivo da caprinovinocultura no Estado do Rio Grande do Norte

This thesis aims to investigate the perception and behavior of goat and sheep rural producers from Central Cabugi Region of Rio Grande do Norte state, in terms of the sector competitiveness, the cooperation mechanisms, information and environmental practices integration in the supply chain, including their customers, and also among the local producers and other institutions that support this agribusiness cluster. The research problem is related to the environmental impacts from goat and sheep breeding. This problem can also be intensified by the organization of producers in a cluster. Then, it is important to examine how the environmental issues are considered by the rural producers and their perception of their suppliers, customers and the institutions that support this activity. The methodology used in this work involved literature review of the topics of supply chain management, green supply chain, clusters development and sustainable livestock. An exploratory survey research was also conducted by personal interviews using questionnaires. Three statistic techniques were used to compile the gathered data: descriptive statistics, cluster analysis, and Chi-square tests. Two clusters were found in this study, however, the entire sample believes the sector of goat and sheep breeding is a medium competitive activity. On the other hand, for the variables of the importance of environmental practices for competitiveness , perception of environmental impacts and environmental benefits from farm vegetation management , the research found 2 distinct groups of individuals when those variables were analyzed together the green supply chain management group of variables in the cluster analysis. Beyond competitiveness perception, no degree of difference was found for the use of insecticides too. The chi-square tests present that producers having at least elementary education, lands bigger 100 hectares and located in the cities of Angicos or Lajes tend to have a higher perception to supply chain management and environmental awareness issues than those with no or incomplete first-level education, producing in lands smaller than 100 hectares and located in the cities of Afonso Bezerra or Pedro Avelino. The chi-square tests also show the amount of milk produced, family s income and associational condition are not related with the variables used in the clusters composition. In this context, this work contributes to planning clusters development strategies and enhancing the production chain sustainability. This Master of Science Thesis can also help to introduce the environmental variable in the project, assessment and monitoring of development policies as well

Metodologia estatística na solução do problema do caixeiro viajante e na avaliação de algoritmos : um estudo aplicado à transgenética computacional

The problems of combinatory optimization have involved a large number of researchers in search of approximative solutions for them, since it is generally accepted that they are unsolvable in polynomial time. Initially, these solutions were focused on heuristics. Currently, metaheuristics are used more for this task, especially those based on evolutionary algorithms. The two main contributions of this work are: the creation of what is called an -Operon- heuristic, for the construction of the information chains necessary for the implementation of transgenetic (evolutionary) algorithms, mainly using statistical methodology - the Cluster Analysis and the Principal Component Analysis; and the utilization of statistical analyses that are adequate for the evaluation of the performance of the algorithms that are developed to solve these problems. The aim of the Operon is to construct good quality dynamic information chains to promote an -intelligent- search in the space of solutions. The Traveling Salesman Problem (TSP) is intended for applications based on a transgenetic algorithmic known as ProtoG. A strategy is also proposed for the renovation of part of the chromosome population indicated by adopting a minimum limit in the coefficient of variation of the adequation function of the individuals, with calculations based on the population. Statistical methodology is used for the evaluation of the performance of four algorithms, as follows: the proposed ProtoG, two memetic algorithms and a Simulated Annealing algorithm. Three performance analyses of these algorithms are proposed. The first is accomplished through the Logistic Regression, based on the probability of finding an optimal solution for a TSP instance by the algorithm being tested. The second is accomplished through Survival Analysis, based on a probability of the time observed for its execution until an optimal solution is achieved. The third is accomplished by means of a non-parametric Analysis of Variance, considering the Percent Error of the Solution (PES) obtained by the percentage in which the solution found exceeds the best solution available in the literature. Six experiments have been conducted applied to sixty-one instances of Euclidean TSP with sizes of up to 1,655 cities. The first two experiments deal with the adjustments of four parameters used in the ProtoG algorithm in an attempt to improve its performance. The last four have been undertaken to evaluate the performance of the ProtoG in comparison to the three algorithms adopted. For these sixty-one instances, it has been concluded on the grounds of statistical tests that there is evidence that the ProtoG performs better than these three algorithms in fifty instances. In addition, for the thirty-six instances considered in the last three trials in which the performance of the algorithms was evaluated through PES, it was observed that the PES average obtained with the ProtoG was less than 1% in almost half of these instances, having reached the greatest average for one instance of 1,173 cities, with an PES average equal to 3.52%. Therefore, the ProtoG can be considered a competitive algorithm for solving the TSP, since it is not rare in the literature find PESs averages greater than 10% to be reported for instances of this size.

Algoritmos de agrupamento aplicados a dados de expressão gênica de câncer: um estudo comparativo

The use of clustering methods for the discovery of cancer subtypes has drawn a great deal of attention in the scientific community. While bioinformaticians have proposed new clustering methods that take advantage of characteristics of the gene expression data, the medical community has a preference for using classic clustering methods. There have been no studies thus far performing a large-scale evaluation of different clustering methods in this context. This work presents the first large-scale analysis of seven different clustering methods and four proximity measures for the analysis of 35 cancer gene expression data sets. Results reveal that the finite mixture of Gaussians, followed closely by k-means, exhibited the best performance in terms of recovering the true structure of the data sets. These methods also exhibited, on average, the smallest difference between the actual number of classes in the data sets and the best number of clusters as indicated by our validation criteria. Furthermore, hierarchical methods, which have been widely used by the medical community, exhibited a poorer recovery performance than that of the other methods evaluated. Moreover, as a stable basis for the assessment and comparison of different clustering methods for cancer gene expression data, this study provides a common group of data sets (benchmark data sets) to be shared among researchers and used for comparisons with new methods