Autoavaliação institucional na dimensão do SINAES comunicação com a sociedade : estudo de múltiplos casos em instituições de ensino superior do Rio Grande do Norte

This study is about the institutional self-evaluation in Dimension 4, "Communication with Society", from the National System of Higher Education Evaluation SINAES, mandatory for all universities in Brazil. A multiple cases study was conducted with three institutions from Rio Grande do Norte, and the goal was to know how this evaluation is made, describing the concept for the evaluation of communication proposed by them, identifying controllers or emancipator aspects, categorizing methodological procedures and discussing the difficulties reported in the communication evaluation process. Coordinators of the institutions Evaluating Committees were interviewed and data categorized by means of qualitative content analysis. It was noted characteristics of the current controller, emancipator and hybrid designs in the three institutions for evaluation of communication, revealing the lack of a theoretical corpus that transits in accordance with the systemic perspective and epistemology of complexity from SINAES. It was found that the most frequently reported difficulties in the evaluation processes of communication are in the preparation stage, especially in the definition of indicators and tools and awareness work. The weakness in planning makes their own activities in the sector of communication become targets of assessment, forming goals poorly related with broader organizational goals. It was also concluded that the technical evaluation cannot override the issues associated with the broader issue of the complexity surrounding the assessment paradigm proposed by SINAES because contradictions and imperfections are part of the evaluation process and several references are current in the literature to support this view. Finally, it is said that objectives such as transparency and behavioral changes can rely on methodologies and techniques for research on the question of the construction of meaning

Entre o mercado e a construção social: uma análise da experiência da implantação doPRONAF-infraestrutura e PRONAT nos territórios do Mato Grande-RN e sertão do Apodi-RN (1997 - 2010)

Analyzes the development experience in the Territories of Mato Grande and Sertão do Apodi in the state of Rio Grande do Norte, evaluating the actions of the National Program for Strengthening Family Agriculture, specifically the line of infrastructure (PRONAF-INFRA), and the National Program for Sustainable Development of Rural Territories (PRONAT) in these territories. Summarizes the various rural development approaches and takes the theoretical assumptions of territorial development, the concept of constructed territory and market-plan territory, further the cycle model to analyze public policies selected these experiences. Thus, we propose to test the hypothesis that most of the actions implemented would lead to the formation of market-plan territories, in other words, perceived only as a platform for the presentation of projects. The literature and documents, combined with case studies, interviews and direct observation of the meetings of committees, showed that, despite two boards are under the same laws, rules and formal regulations, have clear differences when considering the theory and concepts that were used as reference. The Apodi s territory is closer to a constructed space thus the search for a broader agenda, more autonomous and more appropriate to the reality experienced by local actors. On other hand the Territory of Mato Grande had the characteristics of a market-plan territory more present. As the result, the territory of Sertão do Apodi accesses not only as part of a greater number of policies and funding sources, ensuring a greater and more diverse investment volume than the territory of Mato Grande. Despite these differences, studies have shown that territorial boards surveyed are still far from becoming the main forum for managing the development from conception planning socially constructed. Showed, finally, that territorial development strategy is relevant, but requires a long walk and a deep and continuous learning process to be successfully implemented in rural areas of Northeast Brazil

Classificação de padrões através de um comitê de máquinas aprimorado por aprendizagem por reforço

Reinforcement learning is a machine learning technique that, although finding a large number of applications, maybe is yet to reach its full potential. One of the inadequately tested possibilities is the use of reinforcement learning in combination with other methods for the solution of pattern classification problems. It is well documented in the literature the problems that support vector machine ensembles face in terms of generalization capacity. Algorithms such as Adaboost do not deal appropriately with the imbalances that arise in those situations. Several alternatives have been proposed, with varying degrees of success. This dissertation presents a new approach to building committees of support vector machines. The presented algorithm combines Adaboost algorithm with a layer of reinforcement learning to adjust committee parameters in order to avoid that imbalances on the committee components affect the generalization performance of the final hypothesis. Comparisons were made with ensembles using and not using the reinforcement learning layer, testing benchmark data sets widely known in area of pattern classification

Engenharia nos sertões nordestinos: o Gargalheiras, a Barragem Marechal Dutra e a comunidade de Acari, 1909-1958

In Brazil, between the late nineteenth and early decades of the twentieth, polytechnic engineers assumed an important role in discussing the establishment of a modern country. The problem of drought in northeastern Brazil gave the professionals performance, within an interventional process more mounts, the conception plans and measures for the purposeful integration of the territory afflicted. With the foundation of Inspetoria de Obras Contra as Secas (IOCS), in 1909, the actions to combat drought and would be institutionalized, them, studies performed out by technical and scientific committees would be systematically applied in the Brazilian Northeast. So, This work was central objective understand the historical process inplantation of a whole infrastructure of modern character by professional technical and their consequences within the Northeast Geographic space, in specific, in the municipality of Acari in the State of Rio Grande do Norte, in the first half of the twentieth century. The politics of the government, through technical education and scientific engineers polytechnics, would emphasize, during the twentieth century, the building of dams, and irrigation canals, wells, railways, highways, between other elements, that would soon transform the physical space-northeast, specifically, the territory acariense. These works began to contribute to the setting of man backcountry their land, promote the regular practice of agriculture even in periods of drought and, the integration, especially, economic of territory acariense the other producing regions of Rio Grande do Norte and the Northeast as well as promoting the modification of the landscape of the world backcountry. These actions functioned as elements of modernity and progress that transformed the space by favoring by favoring the formation of urban networks (urban) in this space

Uma análise da aplicação do modelo de Rede Neural RePART em Comitês de classificadores

RePART (Reward/Punishment ART) is a neural model that constitutes a variation of the Fuzzy Artmap model. This network was proposed in order to minimize the inherent problems in the Artmap-based model, such as the proliferation of categories and misclassification. RePART makes use of additional mechanisms, such as an instance counting parameter, a reward/punishment process and a variable vigilance parameter. The instance counting parameter, for instance, aims to minimize the misclassification problem, which is a consequence of the sensitivity to the noises, frequently presents in Artmap-based models. On the other hand, the use of the variable vigilance parameter tries to smoouth out the category proliferation problem, which is inherent of Artmap-based models, decreasing the complexity of the net. RePART was originally proposed in order to minimize the aforementioned problems and it was shown to have better performance (higer accuracy and lower complexity) than Artmap-based models. This work proposes an investigation of the performance of the RePART model in classifier ensembles. Different sizes, learning strategies and structures will be used in this investigation. As a result of this investigation, it is aimed to define the main advantages and drawbacks of this model, when used as a component in classifier ensembles. This can provide a broader foundation for the use of RePART in other pattern recognition applications

Comitês de grupamento aplicados a dados de expressão gênica

The main goal of this work is to investigate the suitability of applying cluster ensemble techniques (ensembles or committees) to gene expression data. More specifically, we will develop experiments with three diferent cluster ensembles methods, which have been used in many works in literature: coassociation matrix, relabeling and voting, and ensembles based on graph partitioning. The inputs for these methods will be the partitions generated by three clustering algorithms, representing diferent paradigms: kmeans, ExpectationMaximization (EM), and hierarchical method with average linkage. These algorithms have been widely applied to gene expression data. In general, the results obtained with our experiments indicate that the cluster ensemble methods present a better performance when compared to the individual techniques. This happens mainly for the heterogeneous ensembles, that is, ensembles built with base partitions generated with diferent clustering algorithms

Abordagem de construção de arquitetura homogênea para comitês via meta-aprendizagem

In the world we are constantly performing everyday actions. Two of these actions are frequent and of great importance: classify (sort by classes) and take decision. When we encounter problems with a relatively high degree of complexity, we tend to seek other opinions, usually from people who have some knowledge or even to the extent possible, are experts in the problem domain in question in order to help us in the decision-making process. Both the classification process as the process of decision making, we are guided by consideration of the characteristics involved in the specific problem. The characterization of a set of objects is part of the decision making process in general. In Machine Learning this classification happens through a learning algorithm and the characterization is applied to databases. The classification algorithms can be employed individually or by machine committees. The choice of the best methods to be used in the construction of a committee is a very arduous task. In this work, it will be investigated meta-learning techniques in selecting the best configuration parameters of homogeneous committees for applications in various classification problems. These parameters are: the base classifier, the architecture and the size of this architecture. We investigated nine types of inductors candidates for based classifier, two methods of generation of architecture and nine medium-sized groups for architecture. Dimensionality reduction techniques have been applied to metabases looking for improvement. Five classifiers methods are investigated as meta-learners in the process of choosing the best parameters of a homogeneous committee.

Análise das medidas de boa e má diversidade na construção de comitês de classificadores através de metaheurísticas de otimização multiobjetivo

Committees of classifiers may be used to improve the accuracy of classification systems, in other words, different classifiers used to solve the same problem can be combined for creating a system of greater accuracy, called committees of classifiers. To that this to succeed is necessary that the classifiers make mistakes on different objects of the problem so that the errors of a classifier are ignored by the others correct classifiers when applying the method of combination of the committee. The characteristic of classifiers of err on different objects is called diversity. However, most measures of diversity could not describe this importance. Recently, were proposed two measures of the diversity (good and bad diversity) with the aim of helping to generate more accurate committees. This paper performs an experimental analysis of these measures applied directly on the building of the committees of classifiers. The method of construction adopted is modeled as a search problem by the set of characteristics of the databases of the problem and the best set of committee members in order to find the committee of classifiers to produce the most accurate classification. This problem is solved by metaheuristic optimization techniques, in their mono and multi-objective versions. Analyzes are performed to verify if use or add the measures of good diversity and bad diversity in the optimization objectives creates more accurate committees. Thus, the contribution of this study is to determine whether the measures of good diversity and bad diversity can be used in mono-objective and multi-objective optimization techniques as optimization objectives for building committees of classifiers more accurate than those built by the same process, but using only the accuracy classification as objective of optimization

Em busca do estado participativo: os desafios da participação social na gestão ambiental

The existence of several negative indicators such as deforestation, pollution of rivers and urban growth disorderly suggest a scenario of serious environmental degradation in Brazil, allowing that the model of public management of the environment here is not practiced efficiently, despite to be a recognition-of environmental legislation as one of the best and most comprehensive in the world. One of the main causes of this problem is the low social participation in environmental management that often exists only in the formal plan. Thus, although defined as Democratic State, in practice, it is only a Figurative State. Based on the study of the origin of the state and social participation in the Brazilian State, in general scope, and some environment committees and public hearings in Rio Grande do Norte, as instruments of social control, in particular scope, it is possible to build a real Democratic State in environmental management, a Participative State, in which all players are aware of the responsibility and committed to the duty assigned to them by the constitutional text with the present and future generations