Associativismo nos municípios rurais: uma alternativa de desenvolvimento local em Portalegre/RN

This work aims to study the associations as mediating the process of social change and its importance for local development. The hypothesis is that associations, but bring dynamism to the smaller cities and improve the living conditions of their members, relegated to the background social sustainability, understood this as a permanent exercise of mobilization and participation in community life. The assumptions of the study are that the practice group has influenced the processes of local development in Brazilian rural municipalities through the mediation of government programs and projects aimed at combating rural poverty require social organization for their achievement. The concept of local development in this work was rescued from studies of political economy and sociology. But the concepts of collective action and partnerships advêem studies of political participation and social development of the theory of alternative or solidarity. The party consisted of an empirical case study conducted with four associations of farmers in the municipality of Portalegre-RN. Why choose qualitative study was used the technique of semi-structured interviews with the chairmen I members of associations and other actors considered essential to understanding the study (religious leaders, local political power and chairman of the union of rural workers), a total of 20 interviews, in addition to the observations of field and documentary research in records of the.ir own organizations. The survey results show that the performance of groups of farmers are key components and determinants for the production I marketing of agricultural products and for boosting the economy, as well as security for minimum levels of citizenship. Yet we are still in a space purpose of social change, which comes to confirm the initial hypothesis of this work

Políticas públicas para o turismo e desenvolvimento local: reflexões a partir dos "caminhos de fé" no semi-árido potiguar

This study analyzes the event of the Feast of Our Lady of Grace, located in the municipality of Florania / RN as a tourism product, inserted in a process of transformation of a sacred place, in principle determined by religious motives, in a destination "tourist-religious". We seek to understand to what extent state intervention, with policies aimed at boosting the tourism sector as well as the interactions among key actors in the space, are able to modify and streamline the city of Florania, particularly Feast of Our Lady of Grace. The methodology also includes the review of the literature using the deductive method the application of questionnaires to the pilgrims, tourists and pilgrims totaling 150 questionnaires. Along with the economic agents of the municipality, 36 questionnaires were administered according to the model adopted by REDESIST. Complement this research interviews with key Officials of the Municipal Government and the Church. Despite the recognition by the actors of the importance of tourism to the economy of the city of Florania, encouraging the development of the sector is still lagging, some worked and policies / programs listed actually pass by the "Paths of Faith" of Florania. Concerning the Feast of Our Lady of Grace, the bottlenecks reported by researchers and economic agents are very partially affected by the policies / programs and when this occurs, the effort seems to be only reactive, resulting from the pressures experienced by the municipal government (mayor)

O Cariri cearense: da ocupação do território à institucionalização da região metropolitana do Cariri

Urbanization in their mearing simpler, the agglomeration of people, occurred from the time that the productive activities have to be based on trade. The first cities arose when the evolution of agriculture allowed the production and storage of surpluses. However, with industrialization was that urbanization becomes intense, according to Singer (1987), the industrial revolution was to stage, from the beginning, the urban area. It requires, in its proximity, the presence of a large number of workers. With respect to the Cariri cearense, the occupation of its territory is associated with the movement of agricultural surpluses produced and reproduced under the hegemony of merchant capital and due to the development of extensive cattle that promoted the territorial occupation of Ceará. From the 1960s, the region has undergone changes in its productive structure due to industrial planning policies of the government of Ceará. However it was in the 1990s that the region itself as economic and urban polo because policies to attract investments from the state government of Ceará. This policy led to boosting trade and services marking the predominance of tertiary activities in the region, especially the retail, wholesale , medical services and education. Investments also consolidated the industrial park area making it diverse, especially the footwear industries, mining, non-metallic minerals, transport equipment, pharmaceutical chemical, food and beverages, rubber and leather and construction. Thus, the aim of this study was to review the region of Cariri cearense occupation of its territory institutionalizing its metropolitan region, to understand what factors influenced the Cariri cearense become an important area in urban and economic terms in the interior of Ceará. In order to develop this research in that refers to the methodological perspective, research is guided by bibliographic studies and also makes use of secondary data analysis (population, GDP, urbanization rate, employment) of the main databases the country, as IBGE, IPEADATA and RAIS - MTE

Aplicação de sistemas multi-classificadores no diagnóstico de falhas em motores de indução trifásicos

Equipment maintenance is the major cost factor in industrial plants, it is very important the development of fault predict techniques. Three-phase induction motors are key electrical equipments used in industrial applications mainly because presents low cost and large robustness, however, it isn t protected from other fault types such as shorted winding and broken bars. Several acquisition ways, processing and signal analysis are applied to improve its diagnosis. More efficient techniques use current sensors and its signature analysis. In this dissertation, starting of these sensors, it is to make signal analysis through Park s vector that provides a good visualization capability. Faults data acquisition is an arduous task; in this way, it is developed a methodology for data base construction. Park s transformer is applied into stationary reference for machine modeling of the machine s differential equations solution. Faults detection needs a detailed analysis of variables and its influences that becomes the diagnosis more complex. The tasks of pattern recognition allow that systems are automatically generated, based in patterns and data concepts, in the majority cases undetectable for specialists, helping decision tasks. Classifiers algorithms with diverse learning paradigms: k-Neighborhood, Neural Networks, Decision Trees and Naïves Bayes are used to patterns recognition of machines faults. Multi-classifier systems are used to improve classification errors. It inspected the algorithms homogeneous: Bagging and Boosting and heterogeneous: Vote, Stacking and Stacking C. Results present the effectiveness of constructed model to faults modeling, such as the possibility of using multi-classifiers algorithm on faults classification

Predição de promotores de Bacillus subtilis usando técnicas de aprendizado de máquina

One of the most important goals of bioinformatics is the ability to identify genes in uncharacterized DNA sequences on world wide database. Gene expression on prokaryotes initiates when the RNA-polymerase enzyme interacts with DNA regions called promoters. In these regions are located the main regulatory elements of the transcription process. Despite the improvement of in vitro techniques for molecular biology analysis, characterizing and identifying a great number of promoters on a genome is a complex task. Nevertheless, the main drawback is the absence of a large set of promoters to identify conserved patterns among the species. Hence, a in silico method to predict them on any species is a challenge. Improved promoter prediction methods can be one step towards developing more reliable ab initio gene prediction methods. In this work, we present an empirical comparison of Machine Learning (ML) techniques such as Na¨ýve Bayes, Decision Trees, Support Vector Machines and Neural Networks, Voted Perceptron, PART, k-NN and and ensemble approaches (Bagging and Boosting) to the task of predicting Bacillus subtilis. In order to do so, we first built two data set of promoter and nonpromoter sequences for B. subtilis and a hybrid one. In order to evaluate of ML methods a cross-validation procedure is applied. Good results were obtained with methods of ML like SVM and Naïve Bayes using B. subtilis. However, we have not reached good results on hybrid database

Aplicação de técnicas de aprendizado de máquina no reconhecimento de classes estruturais de proteínas

Nowadays, classifying proteins in structural classes, which concerns the inference of patterns in their 3D conformation, is one of the most important open problems in Molecular Biology. The main reason for this is that the function of a protein is intrinsically related to its spatial conformation. However, such conformations are very difficult to be obtained experimentally in laboratory. Thus, this problem has drawn the attention of many researchers in Bioinformatics. Considering the great difference between the number of protein sequences already known and the number of three-dimensional structures determined experimentally, the demand of automated techniques for structural classification of proteins is very high. In this context, computational tools, especially Machine Learning (ML) techniques, have become essential to deal with this problem. In this work, ML techniques are used in the recognition of protein structural classes: Decision Trees, k-Nearest Neighbor, Naive Bayes, Support Vector Machine and Neural Networks. These methods have been chosen because they represent different paradigms of learning and have been widely used in the Bioinfornmatics literature. Aiming to obtain an improvment in the performance of these techniques (individual classifiers), homogeneous (Bagging and Boosting) and heterogeneous (Voting, Stacking and StackingC) multiclassification systems are used. Moreover, since the protein database used in this work presents the problem of imbalanced classes, artificial techniques for class balance (Undersampling Random, Tomek Links, CNN, NCL and OSS) are used to minimize such a problem. In order to evaluate the ML methods, a cross-validation procedure is applied, where the accuracy of the classifiers is measured using the mean of classification error rate, on independent test sets. These means are compared, two by two, by the hypothesis test aiming to evaluate if there is, statistically, a significant difference between them. With respect to the results obtained with the individual classifiers, Support Vector Machine presented the best accuracy. In terms of the multi-classification systems (homogeneous and heterogeneous), they showed, in general, a superior or similar performance when compared to the one achieved by the individual classifiers used - especially Boosting with Decision Tree and the StackingC with Linear Regression as meta classifier. The Voting method, despite of its simplicity, has shown to be adequate for solving the problem presented in this work. The techniques for class balance, on the other hand, have not produced a significant improvement in the global classification error. Nevertheless, the use of such techniques did improve the classification error for the minority class. In this context, the NCL technique has shown to be more appropriated

Novas abordagens para configurações automáticas dos parâmetros de controle em comitês de classificadores

Significant advances have emerged in research related to the topic of Classifier Committees. The models that receive the most attention in the literature are those of the static nature, also known as ensembles. The algorithms that are part of this class, we highlight the methods that using techniques of resampling of the training data: Bagging, Boosting and Multiboosting. The choice of the architecture and base components to be recruited is not a trivial task and has motivated new proposals in an attempt to build such models automatically, and many of them are based on optimization methods. Many of these contributions have not shown satisfactory results when applied to more complex problems with different nature. In contrast, the thesis presented here, proposes three new hybrid approaches for automatic construction for ensembles: Increment of Diversity, Adaptive-fitness Function and Meta-learning for the development of systems for automatic configuration of parameters for models of ensemble. In the first one approach, we propose a solution that combines different diversity techniques in a single conceptual framework, in attempt to achieve higher levels of diversity in ensembles, and with it, the better the performance of such systems. In the second one approach, using a genetic algorithm for automatic design of ensembles. The contribution is to combine the techniques of filter and wrapper adaptively to evolve a better distribution of the feature space to be presented for the components of ensemble. Finally, the last one approach, which proposes new techniques for recommendation of architecture and based components on ensemble, by techniques of traditional meta-learning and multi-label meta-learning. In general, the results are encouraging and corroborate with the thesis that hybrid tools are a powerful solution in building effective ensembles for pattern classification problems.

Efeitos de fungicidas alternativos em folhas de Carthamus tinctorius L. (Asteraceae), potencial espécie para cultivo em agricultura familiar

The currently main development model on global society is driven by an economic rationality that endangers the environment and social justice. More and more, attention to this way of production and consumption is increasing, boosting research for sustainable development, with an environmental rationality that can harmonize nature preservation and welfare of all socioeconomic classes. One of the efforts on this sense is changing the sources supplying the energy demand, replacing fossil fuels for renewable and cleaner sources, such as biofuels. Carthamus tinctorius (safflower) is an oilseed crop with potential for biodiesel production, with good oil yield and chemical profile, allied to good adaptation to climates such like the northeastern semiarid lands of Brazil. With public policies fomentation, the use of this species may be an interesting alternative for family farming. In farming in general, the use of pesticides to prevent and combat diseases and plagues is common, which is not a sustainable practice. Thus, there are researched alternative, less dangerous substances. In this study, it was aimed to assess if neem (Azadirachta indica) leaf extract (20% m/v) and Bordeaux mixture (copper sulfate) have effects on safflower. It was also aimed to verify acceptance of farmers on safflower crop in Apodi, a municipality in Rio Grande do Norte state, Brazil, in view of it being localized in the aimed region for this crop cultivation. Besides that, understanding that the farmers’ knowledge and inclination to adopt the crop is fundamental for the introduction of this species and socioeconomic growth due to its exploration. In addition, a booklet with basic information on safflower was produced. In the field experiment, the fungicides were pulverized on plants cultivated in field experimental plots, with collection of leaf samples for analysis on anatomy, cuticle, and epicuticular wax morphology, the protective layer that interfaces with the surrounding ambient. In Apodi, forty-five farmers from Potiguar Cooperative of Apiculture and Sustainable Rural Development (COOPAPI) underwent semi-structured interviews, which also addressed their assessment on currently cultivated crops and perception of pesticide uses and sustainable alternatives. After comparing using analysis of variance, it was found that there was no difference between treatments in the experiment, as well as no anatomical or morphological modifications. Safflower acceptation among farmers was wide, with 84% of interviewees believing in a perspective of good incomes. The current scenario, comprised of low crop diversity, fragile in face of droughts and plagues, can partially explain this opinion. The booklet was effective in catching people attention for the species potential. There was wide acknowledgement on the importance of alternative pesticides, justified by health security. Based on the assessed parameter in the results of this research, the treatments here utilized may be recommended as fungicides for safflower. Given the crop susceptibility to fungi in heavy rainy period, it is advised that its potential introduction on the region shall be focused on semiarid areas.