Os ateliês (auto)formativos na constituição do sujeito docente da educação matemática

The object of study of this thesis is the use of (self)training workshops as a fundamental process for the constitution of the teaching subject in mathematics education. The central purposes of the study were to describe and analyze a learning process of mathematics teachers supported by the training-research methodology, which procedures have been affected with the practice of (self)training workshops as a way of collaborating to the constitution of the teaching subject in Mathematics Education. The survey was conducted with a group of teachers in the city of Nova Cruz, Rio Grande do Norte through a process of continued education realized in the training workshops having as main goal the realization of the group s (self)training sessions in order to lead participants to the extent of their autonomy in their personal and professional transformations. The results obtained in the formative processes have shown the need to develop activities of mathematics teaching as a contribution to overcome the conceptual difficulties of the teachers, apart from their (self)reflections about themselves and the educational processes in which they belong. The results raised some propositions about (self)training workshops that may be incurred in practices to be included in the curriculum frameworks or materialize as a strategy of pedagogical work in training courses for teachers of mathematics. Also, they can constitute an administrative and educational activity to be instituted in the public schools of Basic Education

A formação de professores surdos de Libras: a centralidade de ambientes bilíngues em sua formação

The study object of this thesis intertwines the history of deaf education in the last 30 years in three schools for the deaf in the cities of Campina Grande, Gado Bravo and Aroeiras, Paraiba, the life stories of six deaf teachers of brasilian sign language (Libras) that have formed and works in these educational institutions for the deaf and our own journey, as a teacher and researcher. The study was conducted on the theoretical-methodological principles of (auto)biographical research in education and socio-historical studies on the social formation of the human. The corpus used for analysis was consisted of six narrative interviews conducted in sign language and transcribed into portuguese, documents and personal files and institutional. The analysis allowed us to define three hinge moments of this story: the creation of the first school for the deaf, within the framework of oralism (1980 - 1991), the passage into the Total Communication (1991 - 1995) and, finally, the introduction of Bilingualism (1995 to today). The analyzes show that the trajectories of teacher formation of the research participants reflect the history of the three schools which have costituted bilingual social spaces of paramount importance to the subjects and the deaf community as a group of linguistic and cultural minority. The evolution of this trajectory has allowed to demarcate between the two generations of research participants. The generation of heirs of oralism, which had delayed access to the Libras and lived an education referenced in oralism, whose reminiscences of childhood and adolescence are strongly marked by suffering for the lack of communication, which hinders their social and professional career until today. And the generation of the sons of bilingualism, the youngest in age, who had childhood access to Libras and education within the framework of bilingualism, whose reminiscences are not marked by suffering and have a positive vision of the future. With respect to your teacher formation, three figures stand out as a teacher. The teacher's improvised, closer to the first generation of teachers who were called to teach without proper training. The figure of the teacher craftsman, which corresponds to the image that most of them have of yourself now, understanding that their knowledge are based on the exchange between peers. And finally the figure of the real teacher, which stands on the horizon of expectations as future graduates in Letters |Libras. The narratives allowed to realize that the evolution between these figures is based on the contributions of the other: hearing teachers of EDAC and the Federal University of Campina Grande and deaf teachers of the two generations who learn from each other. The analyzes and reflections allowed to defend the thesis of the centrality of bilingual environments for the establishment of the deaf person as a citizen with full rights, based on the voice of the deaf, muted by the history of education, conducted by listeners

A auto formação maternal: cenários de uma educação vivencial humanescente

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Trajetória de vida de mulheres mastectomizadas integrantes de um grupo de auto ajuda a luz da História Oral

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Gestão de satisfação e fidelidade do cliente: um estudo dos fatores que afetam a satisfação e fidelidade dos compradores de automóveis

This Master s thesis presents a discussion on customer satisfaction models investigating the relations of antecedent variables service quality, price index, complaint handling, image, affective and calculative commitment, with satisfaction and loyalty. The scope of the research is the influence of service dimensions in the car buyer s satisfaction and loyalty. A sample of 91 customers was surveyed among new cars buyers of one brand in Natal city, Brazil, and the data was analyzed using multiple regression analysis. The literature review covers subjects such as customer satisfaction, management system, customer satisfaction measurement index models. The main findings suggest that satisfaction with the car brand is mainly influenced by customization of the service, time for accomplishing servicing, and the way the dealer handle complains. Regarding the dealer itself the main variable related to satisfaction is also time for accomplishing servicing. Considering customer loyalty, the customer satisfaction with the dealer explain strongly the loyalty with the brand/manufacturer. Also, the satisfaction, affective commitment and complains handling were found related to loyalty, as the stronger variables explaining the loyalty variance. One main conclusion is that service provided by dealers is one key factor influencing the customer satisfaction and loyalty in auto industry

Uma Aplicação de Redes Neurais Auto-Organizaveis à Reconstrução Tridimensional de Superfícies

We propose a multi-resolution approach for surface reconstruction from clouds of unorganized points representing an object surface in 3D space. The proposed method uses a set of mesh operators and simple rules for selective mesh refinement, with a strategy based on Kohonen s self-organizing map. Basically, a self-adaptive scheme is used for iteratively moving vertices of an initial simple mesh in the direction of the set of points, ideally the object boundary. Successive refinement and motion of vertices are applied leading to a more detailed surface, in a multi-resolution, iterative scheme. Reconstruction was experimented with several point sets, induding different shapes and sizes. Results show generated meshes very dose to object final shapes. We include measures of performance and discuss robustness.

Algoritmos inteligentes para auto-correção, auto-verificação e auto-validação de medidas em sensores

This work presents a set of intelligent algorithms with the purpose of correcting calibration errors in sensors and reducting the periodicity of their calibrations. Such algorithms were designed using Artificial Neural Networks due to its great capacity of learning, adaptation and function approximation. Two approaches willbe shown, the firstone uses Multilayer Perceptron Networks to approximate the many shapes of the calibration curve of a sensor which discalibrates in different time points. This approach requires the knowledge of the sensor s functioning time, but this information is not always available. To overcome this need, another approach using Recurrent Neural Networks was proposed. The Recurrent Neural Networks have a great capacity of learning the dynamics of a system to which it was trained, so they can learn the dynamics of a sensor s discalibration. Knowingthe sensor s functioning time or its discalibration dynamics, it is possible to determine how much a sensor is discalibrated and correct its measured value, providing then, a more exact measurement. The algorithms proposed in this work can be implemented in a Foundation Fieldbus industrial network environment, which has a good capacity of device programming through its function blocks, making it possible to have them applied to the measurement process

Análise de antenas utilizando substrato cerâmico, zpt, produzido por síntese auto propagante para aplicações em sistemas de micro-ondas

Ceramic substrates have been investigated by researchers around the world and has achieved a high interest in the scientific community, because they had high dielectric constants and excellent performance in the structures employed. Such ceramics result in miniaturized structures with dimensions well reduced and high radiation efficiency. In this work, we have used a new ceramic material called lead zinc titanate in the form of Zn0,8Pb0,2TiO3, capable of being used as a dielectric substrate in the construction of various structures of antennas. The method used in constructing the ceramic combustion synthesis was Self- Sustained High Temperature (SHS - "Self-Propagating High-Temperature Synthesis") which is defined as a process that uses highly exothermic reactions to produce various materials. Once initiated the reaction area in the reaction mixture, the heat generated is sufficient to become self-sustaining combustion in the form of a wave that propagates converting the reaction mixture into the product of interest. Were analyzed aspects of the formation of the composite Zn0,8Pb0,2TiO3 by SHS powders and characterized. The analysis consisted of determining the parameters of the reaction for the formation of the composite, as the ignition temperature and reaction mechanisms. The production of composite Zn0,8Pb0,2TiO3 by SHS performed in the laboratory, was the result of a total control of combustion temperature and after obtaining the powder began the development of ceramics. The product was obtained in the form of regular, alternating layers of porous ceramics and was obtained by uniaxial pressing. 10 The product was characterized by analysis of dilatometry, X-ray diffraction analysis and scanning electron microscopy. One of the contributions typically defined in this work is the development of a new dielectric material, nevertheless presented previously in the literature. Therefore, the structures of the antennas presented in this work consisted of new dielectric ceramics based Zn0,8Pb0,2TiO3 usually used as dielectric substrate. The materials produced were characterized in the microwave range. These are dielectrics with high relative permittivity and low loss tangent. The Ansoft HFSS, commercial program employee, using the finite element method, and was used for analysis of antennas studied in this work

Identificação de nematóides através de técnicas de processamento inteligentes de imagens

abstract

Algoritmo SOM com estrutura hierárquica e dinâmica aplicado a compressão de imagens

ln this work the implementation of the SOM (Self Organizing Maps) algorithm or Kohonen neural network is presented in the form of hierarchical structures, applied to the compression of images. The main objective of this approach is to develop an Hierarchical SOM algorithm with static structure and another one with dynamic structure to generate codebooks (books of codes) in the process of the image Vector Quantization (VQ), reducing the time of processing and obtaining a good rate of compression of images with a minimum degradation of the quality in relation to the original image. Both self-organizing neural networks developed here, were denominated HSOM, for static case, and DHSOM, for the dynamic case. ln the first form, the hierarchical structure is previously defined and in the later this structure grows in an automatic way in agreement with heuristic rules that explore the data of the training group without use of external parameters. For the network, the heuristic mIes determine the dynamics of growth, the pruning of ramifications criteria, the flexibility and the size of children maps. The LBO (Linde-Buzo-Oray) algorithm or K-means, one ofthe more used algorithms to develop codebook for Vector Quantization, was used together with the algorithm of Kohonen in its basic form, that is, not hierarchical, as a reference to compare the performance of the algorithms here proposed. A performance analysis between the two hierarchical structures is also accomplished in this work. The efficiency of the proposed processing is verified by the reduction in the complexity computational compared to the traditional algorithms, as well as, through the quantitative analysis of the images reconstructed in function of the parameters: (PSNR) peak signal-to-noise ratio and (MSE) medium squared error

Técnicas visuais de localização e mapeamento simultâneos sem extração de primitivas geométricas da imagem

In Simultaneous Localization and Mapping (SLAM - Simultaneous Localization and Mapping), a robot placed in an unknown location in any environment must be able to create a perspective of this environment (a map) and is situated in the same simultaneously, using only information captured by the robot s sensors and control signals known. Recently, driven by the advance of computing power, work in this area have proposed to use video camera as a sensor and it came so Visual SLAM. This has several approaches and the vast majority of them work basically extracting features of the environment, calculating the necessary correspondence and through these estimate the required parameters. This work presented a monocular visual SLAM system that uses direct image registration to calculate the image reprojection error and optimization methods that minimize this error and thus obtain the parameters for the robot pose and map of the environment directly from the pixels of the images. Thus the steps of extracting and matching features are not needed, enabling our system works well in environments where traditional approaches have difficulty. Moreover, when addressing the problem of SLAM as proposed in this work we avoid a very common problem in traditional approaches, known as error propagation. Worrying about the high computational cost of this approach have been tested several types of optimization methods in order to find a good balance between good estimates and processing time. The results presented in this work show the success of this system in different environments

Análise da imagem digital para estimativa da área foliar em plantas de laranja Pêra

Objetivou-se, com o trabalho, avaliar dois métodos de estimativa da área foliar, em plantas de laranja Pêra, pela análise da imagem digital obtida com scanner e câmera fotográfica digital. Para determinar a área das folhas, um grupo de discos foi colocado sobre um leitor de scanner, sendo que a imagem obtida foi armazenada. Os mesmos grupos de discos foram fixados sobre cartolina branca e fotografados com câmera fotográfica digital. As imagens obtidas da câmera fotográfica e do scanner foram processadas utilizando ferramentas de um editor de imagem que permite a contagem de pixels de determinada cor, no caso verde. Para a comparação dos métodos, os discos foram submetidos a integrador óptico de área foliar modelo LICOR-3100, utilizando os mesmos agrupamentos. Foram coletadas 20 folhas (cinco em cada quadrante da planta) por parcela de um experimento para comparação de fertilizantes comerciais e doses de zinco, aplicados via foliar, em plantas de sete anos de idade. O experimento foi composto de sete tratamentos e quatro repetições, num total de 28 parcelas. Os dois métodos apresentaram alta correlação com a área estimada pelo integrador óptico de área, considerado como método de referência. O método da análise da imagem obtida com câmera fotográfica, na resolução de 5.0 megapixel, foi mais precisa quando comparada à área estimada pelo integrador óptico de área.

Estudo avaliativo de um algoritmo genético auto-organizável e multiobjetivo utilizando aprendizado de máquina para aplicações de telecomunicações

This paper presents an evaluative study about the effects of using a machine learning technique on the main features of a self-organizing and multiobjective genetic algorithm (GA). A typical GA can be seen as a search technique which is usually applied in problems involving no polynomial complexity. Originally, these algorithms were designed to create methods that seek acceptable solutions to problems where the global optimum is inaccessible or difficult to obtain. At first, the GAs considered only one evaluation function and a single objective optimization. Today, however, implementations that consider several optimization objectives simultaneously (multiobjective algorithms) are common, besides allowing the change of many components of the algorithm dynamically (self-organizing algorithms). At the same time, they are also common combinations of GAs with machine learning techniques to improve some of its characteristics of performance and use. In this work, a GA with a machine learning technique was analyzed and applied in a antenna design. We used a variant of bicubic interpolation technique, called 2D Spline, as machine learning technique to estimate the behavior of a dynamic fitness function, based on the knowledge obtained from a set of laboratory experiments. This fitness function is also called evaluation function and, it is responsible for determining the fitness degree of a candidate solution (individual), in relation to others in the same population. The algorithm can be applied in many areas, including in the field of telecommunications, as projects of antennas and frequency selective surfaces. In this particular work, the presented algorithm was developed to optimize the design of a microstrip antenna, usually used in wireless communication systems for application in Ultra-Wideband (UWB). The algorithm allowed the optimization of two variables of geometry antenna - the length (Ls) and width (Ws) a slit in the ground plane with respect to three objectives: radiated signal bandwidth, return loss and central frequency deviation. These two dimensions (Ws and Ls) are used as variables in three different interpolation functions, one Spline for each optimization objective, to compose a multiobjective and aggregate fitness function. The final result proposed by the algorithm was compared with the simulation program result and the measured result of a physical prototype of the antenna built in the laboratory. In the present study, the algorithm was analyzed with respect to their success degree in relation to four important characteristics of a self-organizing multiobjective GA: performance, flexibility, scalability and accuracy. At the end of the study, it was observed a time increase in algorithm execution in comparison to a common GA, due to the time required for the machine learning process. On the plus side, we notice a sensitive gain with respect to flexibility and accuracy of results, and a prosperous path that indicates directions to the algorithm to allow the optimization problems with "η" variables

Contribuições a técnicas de agrupamento e visualização de dados multivariados utilizando mapas auto-organizáveis

Self-organizing maps (SOM) are artificial neural networks widely used in the data mining field, mainly because they constitute a dimensionality reduction technique given the fixed grid of neurons associated with the network. In order to properly the partition and visualize the SOM network, the various methods available in the literature must be applied in a post-processing stage, that consists of inferring, through its neurons, relevant characteristics of the data set. In general, such processing applied to the network neurons, instead of the entire database, reduces the computational costs due to vector quantization. This work proposes a post-processing of the SOM neurons in the input and output spaces, combining visualization techniques with algorithms based on gravitational forces and the search for the shortest path with the greatest reward. Such methods take into account the connection strength between neighbouring neurons and characteristics of pattern density and distances among neurons, both associated with the position that the neurons occupy in the data space after training the network. Thus, the goal consists of defining more clearly the arrangement of the clusters present in the data. Experiments were carried out so as to evaluate the proposed methods using various artificially generated data sets, as well as real world data sets. The results obtained were compared with those from a number of well-known methods existent in the literature

Controle feedback de nível baseado em sensor de imagem aplicado ao equipamento misturador-decantador à inversão de fases (MDIF®)

The treatment of wastewaters contaminated with oil is of great practical interest and it is fundamental in environmental issues. A relevant process, which has been studied on continuous treatment of contaminated water with oil, is the equipment denominated MDIF® (a mixer-settler based on phase inversion). An important variable during the operation of MDIF® is the water-solvent interface level in the separation section. The control of this level is essential both to avoid the dragging of the solvent during the water removal and improve the extraction efficiency of the oil by the solvent. The measurement of oil-water interface level (in line) is still a hard task. There are few sensors able to measure oil-water interface level in a reliable way. In the case of lab scale systems, there are no interface sensors with compatible dimensions. The objective of this work was to implement a level control system to the organic solvent/water interface level on the equipment MDIF®. The detection of the interface level is based on the acquisition and treatment of images obtained dynamically through a standard camera (webcam). The control strategy was developed to operate in feedback mode, where the level measure obtained by image detection is compared to the desired level and an action is taken on a control valve according to an implemented PID law. A control and data acquisition program was developed in Fortran to accomplish the following tasks: image acquisition; water-solvent interface identification; to perform decisions and send control signals; and to record data in files. Some experimental runs in open-loop were carried out using the MDIF® and random pulse disturbances were applied on the input variable (water outlet flow). The responses of interface level permitted the process identification by transfer models. From these models, the parameters for a PID controller were tuned by direct synthesis and tests in closed-loop were performed. Preliminary results for the feedback loop demonstrated that the sensor and the control strategy developed in this work were suitable for the control of organic solvent-water interface level