RCAAP Repository

An important feature in Distance Education is the personal and intelligent assistance, in which an important aspect is that students may have quite different profiles. Thus, a course designed for a particular student may not be suitable for other students. Because of this, a challenge in research is the development of advanced educational applications that provide some degree of intelligence and adaptivity. An indispensable factor in this type of system is the accurate identification of students learning styles, in order to provide most suited content to their individual needs. The construction of this kind of system through a probabilistic process is an important research problem, because these systems need to deal with incomplete or uncertain information about students. Thus, adaptivity provided by these systems need to consider a certain level of uncertainty. So, we strongly believe that considering stochastic student modeling in these systems is essential. Therefore, the main goal of this work is to present an innovative stochastic approach, based on reinforcement learning, for providing adaptivity through probabilistic modeling of students learning styles, and to investigate its efficiency, effectiveness and reliability through a series of experiments. Specifically, the proposed approach aims to detect and correct, automatically and dynamically, inaccuracies and inconsistencies in learning styles stored in the student model, considering that preferences obtained through psychometric questionnaires may need review, by having some degree of uncertainty. In this context, this work discusses and addresses important issues on automatic and dynamic modeling of learning styles, most of them ignored by approaches developed so far.

The contemporary education has a lot of challenges and among them is the adaptation of using new technologies with classical education paradigm. It hasn\'t been different with distance education. In this context, this work proposes to develop a hybrid tutoring system model with decisions based on the teachers knowledge and help from Self Organizing Maps (SOM) or Kohonen\'s Maps neural networks. The proposed system has a initial teaching method that is set by specialist teacher up and while system is being running this pedagogic method is refined by the neural networks, which use patterns extracted from students that has used the system. The model proposes the utilization of a basic neural network structure with automated training which is capable of train several networks and define the one which represents results that is more coherent with the pattern\'s set, dismissing the intervention of a specialist on the evaluation of the network training performance. The system has adaptive and reactive features related to the apprentice, being able to offer to the students a personalized and dynamic learning. The system was developed in a web environment aiming avail the advantages of this technology. At this work, besides the proposed model developing it also were performed a data gathering with fresh students from integrated learning technical of Federal Institution of Goiás, Luziânia, Goiás, Brazil, to evaluate system\'s applicability. This thesis presents the fundamentals theorists of the virtual education environment, as also the artificial neural networks SOM, used on proposed model. Likewise, it shows the system developing process, the automated training build, in addition with the system tutor structure. The knowledge\'s transmission is inspired in the content\'s didactic transposition, with organization didactic units in levels that aim develop distinct skills. The SOM networks analysis indicate that the automated train was able to train several networks and identify a network with best topologic order. Moreover, this work presents a comparison between students performance when submitted to learn using the system with purely specialized orientation and hybrid orientation. The outcomes of this evaluation points out the viability of the proposed model, since the system has shown to be able to learn from students and adapt the teacher learning method. The apprentices that studied utilizing the system had amplified theirs grades on the learning system evaluations and the hybrid tutor was capable of take decisions which magnify the acceptation of the tutor learning indication.

The face recognition has been shown to be an important technique in automatic identification of persons. It is a biometric image coding characterized by exploring selfsimilarity present in digital images and whose computational effort is significant and has required dedication of researchers in order to increasingly enhance the efficiency of the process. This thesis was presented the state of the art face recognition systems citing different forms of applications and work done by some researchers. It was also shown the methodology used by the classifiers Genetic Algorithm (GA), Artificial Neural Network (ANN) and Principal Component Analysis (PCA). The aim of this study was to test these classifiers for face recognition by analyzing the percentage of accuracy and processing time. The reason to use the GA is that the PCA, traditionally used in such cases, is very slow and the high computational cost, making it impractical in some applications, especially when the database is large images. In tests performed in this study were used the databases of two human photography files, the Olivetti Research Laboratory database today faces the British University of Cambridge (ORL) and Face Recognition Data, University of Essex, UK (UK). The accuracy rate obtained with GA, ANN and PCA were higher than those obtained by the studies reviewed.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

The Worldwide Interoperability for Microwave Access (WiMAX) technology, based on the IEEE 802.16 standard, is a solution for broadband wireless access metropolitan networks, developed to support a wide variability of real-time and non-real time applications. Different from the traditional wireless networks, the IEEE 802.16 standard defines, in the medium access layer, mechanisms to support the Quality of Service (QoS) for the applications. Among these mechanisms, we highlight the scheduling and the Connection Admission Control (CAC). However, the IEEE 802.16 does not define the policies that must be used in the implementation of the scheduling and CAC mechanisms. The scheduling mechanism aims at guarantying the efficient utilization of the bandwidth resources, and thus, promotes the effective use of the wireless link. The CAC mechanism aims at restricting the number of existing connections simultaneously in order to avoid that the wireless link is saturated. This thesis shows a new and efficient scheduling algorithm to uplink traffic in the Base Station (BS). The proposed algorithm is developed to be totally dynamic, mainly in networks that use adaptive modulation functions. Using a cross-layer approach, a deadline based scheme was developed, aiming at minimizing the end-to-end delay for the real-time applications. Moreover, the proposed algorithm interacts with the polling mechanism of the BS, and controls the periodicity of unicast polling to real-time and non-real-time applications, in accordance with the QoS requirements of the applications. Moreover, to avoid the wireless link being saturated for an excessive number of connections, a CAC mechanism that interacts with the proposed scheduling algorithm was developed. The CAC mechanism was also developed using a cross-layer approach. Simulations results show the efficiency of the proposed scheduling algorithm and of the CAC mechanism, mainly in environments where an adaptive modulation was used.

The improvement of computer systems has benefited the development of many research areas in medicine. Analysis and interpretation of medical images represent an important part in computer vision and pattern recognition. It\'s essential for many researchers and medical centers to develop a diagnosis system aided by computer for diseases such as breast cancer, in order to assist doctors in hospitals. The polynomial classifier developed in this work is a supervised classification method and can sort two or more classes. This classifier expands the feature vector projected into the space Rd into a higher dimensional space where the classification is possible. The polynomial classifier proves to be an important method of classification mainly on treatment with non-linearly separable classes. In this thesis, the classifier was used to recognize patterns from the database IRIS Fisher 1936, which is composed by the flowers setosa, versicolor and virginica. Several tests were performed on this basis and by using three or four features the polynomial classifier managed to sort all these flowers. An application was also performed with the polynomial classifier for the identification of partial pixels in regions of interest in mammographic images. Compared with SVM classifiers and decision tree, the results were better using the polynomial classifier.

Universidade de Uberaba

The Lumbago or commonly called "low back pain" is a frequent cause of morbidity and disability work, only surpassed by headache (headache) in the range of painful disorders affecting modern society, and the treatment is based on medication (painkillers) to relieve the symptoms of pain and recommending therapeutic exercise. However, when these exercises are performed and no longer perceived pain, the patient drops the treatment, and in many cases, having its range of movement fully reestablished. To mitigate this index abandoned therapies motivators several techniques have been employed, such as the use of digital games and entertainment interfaces. However, these approaches only emerge the playful part of treatment showing no concrete data on the occupational or even exercise performance and its efficiency in treatment. Therefore, this work describes a rehabilitation system based on motion capture techniques for the treatment of a type of low back pain, mechanical low back pain. This thesis presents techniques use motion capture environments applied to motor rehabilitation with some devices such as electrogoniometer, extensometer, accelerometer and other common interaction devices such as webcams, video game console (Nintendo WiiTM) and motion sensor MS-KinectTM. The motivation of the work is based on the fact that motion capture systems for video devices tend to be more economically viable, however the systems capture current video showed the following limitations: the overlap and occlusion of the markers, the disparity optical cameras the field of view and their geometric constraints. Therefore, this work presents an alternative proposal capture by multiple cameras in conjunction with the analysis of the intrinsic parameters of the cameras involved in the process to mitigate these limitations. For the analysis of motion captured was prototyped a system that meets the specifications on the biotype of the patient and an adapted questionnaire about their inability to move that, from these, form a set of information that supports the decision about treatment with exercise suggestions . In order to validate the information in the system as well as your business rules, an evaluation has made with a group of five therapists, and presented an analysis of the interface has performed by 20 patients. Those patients were surveyed volunteers. Through this analysis was possible to identify the potential of the prototype, as well as highlight the strategies for implementing even small physiotherapy clinics. Especially those that have no spaces or volume of investment in infrastructure for systems acquisition motion capture large - very important for analysis and recommendation of new exercises during a rehabilitative therapy.

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Learning music, mostly through musical scores, is a difficult task, even for people who do not have visual problems. Learning musical demands years of effort and dedication. Moreover, the music learning tasks for a blind is much more complex. Besides the complexity of the Braille code for music (musicografia Braille), there are few people trained to teach music by this method. This work presents a solution that seeks to simplify the coding of both writing and reading music through cells of raised dots, as also make teaching and learning more attractive, requiring visually impaired and their assistants, less effort, less time and less dedication. This work presents a computational solution that seeks to give the visually impaired, accessibility to the songs as they are posted on the same internet. Unfortunately, the biggest barrier to be faced, it is still a lack of professionals to teach the blind to read such encoding. The proposed system, prototyped and now presents a new simplified coding, presenting the music score in basic cells of 4 points in relief (4 raised dots arranged in cells), musical, textual and Numerofonia format. The proposed method is based on the paradigm of decimal encoding proposed by Braille and the paradigm number already used in international encoding of musical events. The method of this research presents a paradigm that allows, with less effort and less dedication, training of teachers, family members and assistants of visually impaired in learning musical notation proposed here. Learning to read music is relevant due to the fact that, since the assistant learn the paradigm and he can read music, it will be easier to teach visually impaired under his tutelage, the new musicografia. Software was designed and implemented in functional language for generating the codes of this work, as well as other paradigms focused on use by accompanying of visually impaired.

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Fundação de Amparo a Pesquisa do Estado de Minas Gerais

This work shows a contribution to the study of the Switched Reluctance Machine driven as a generator to connecting in the grid to inject active power. The main objective is show the Switched Reluctance Generator behavior under various operating conditions, as well as the development of an electronic converter to connect it to the low voltage grid. Thus, it presents a mathematical model for the Switching Reluctance Generator which includes the magnetic circuit saturation and a computational model for analyzing steady state and transient. Also it is presented a strategy of generated voltage control by the magnetization angle variation acting only in the top switch of the Asymmetrical Half Bridge converter. An intermediate stage was added in the switching control strategy to reduce the energy amount provided by the excitation source and get better utilization of electromechanical conversion. A detailed description of the control system equations of the DC-AC stage, PLL algorithm and design of injected current compensator are presented and discussed. Finally, it was constructed in laboratory a experimental platform for verification of the theoretical and simulation.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

In this thesis, it is presented a planar point location algorithm. The algorithm was developed on top of two elements: - the method of slabs to divide the planar subdivision, is represented by a graph, allowing the fast identification of the region where the point being recalled is; - the Interval Multi-B-tree, a data structure derived from the B-tree, prepared with an interval search structure and disposed in layers. The algorithm is essentially dynamic since the search structure keeps changing dynamically during the process, while the planar subdivision is being built; new events of segment insertion or removal keep appearing. The algorithm was implemented in OCaml, but could be carried out in any other programming language. To increase the algorithm efficiency, some improvements can be introduced, as an example, the substitution of the Interval Multi-B-tree core by other types of balanced trees. Moreover, it was discussed some aspects of the assembling process of the finite element meshing, where it is inserted, mainly, the planar point location problem.

This work presents an approach to teaching based on Theory of Signification Learning by David P. Ausubel using a Category Theory. This study begins on utilization of Category Theory, more specifically on Functors. This work uses a metaphor adhering to effective communication between instructor and learner, teacher and student. The effectiveness of the proposed is demonstrated through the algebraic mathematical proof of Functors unchallenged as a solution to the objectives of education in general. The knowledge transmission is dynamic, so that, a successfully transmitted foreground was designed and implemented as unique strategy to provide the learner/student, whenever deemed necessary, the objects and morphisms central to the establishment of new functors that will ensure the effective communication between the categories teacher/instructor and student/learner. The work presents a methodology which applied with functors and the methodology mentioned guarantees memorization and sedimentation of learning, even for people who not endowed with such skill and expertise.

The main task of this work is to provide a contribution to help a more deep understanding on the operation of the asymmetrical twophase induction motor with return for applications in places where a possibility of a two-phase network feeding exists. important contributions where obtained with the help of a time domain dynamic model for symmetrical and asymmetrical two-phase machines developed as part of this work. With such contributions it was possible to show that a threephase induction motor can work as a two-phase asymmetrical induction motor with return through a phase or neutral conductor, without the need of some starting devices, such as, centrifugal switch and capacitors. this was proved through load and no-load tests and by way of comparisons between theoretical and experimental results. Hence, with such a work, we are seeking for the revitalization of the asymmetrical two-phase induction motor theory, a machine that presents a non-uniform magnetomotive force and electromagnetic torque.