Tatiana Escovedo

GPF-CLASS: A Genetic Fuzzy model for classification

This work presents a Genetic Fuzzy Classification System (GFCS) called Genetic Programming Fuzzy Classification System (GPF-CLASS). This model differs from the traditional approach of GFCS, which uses the metaheuristic as a way to learn “if-then” fuzzy rules. This classical approach needs several changes and constraints on the use of genetic operators, evaluation and selection, which depends primarily on the metaheuristic used. Genetic Programming makes this implementation costly and explores few of its characteristics and potentialities. The GPF-CLASS model seeks for a greater integration with the metaheuristic: Multi-Gene Genetic Programming (MGGP), exploring its potential of terminals selection (input features) and functional form and at the same time aims to provide the user with a comprehension of the classification solution. Tests with 22 benchmarks datasets for classification have been performed and, as well as statistical analysis and comparisons with others Genetic Fuzzy Systems proposed in the literature.

NEVE++: A neuro-evolutionary unlimited ensemble for adaptive learning

In our previous works [1, 2], we proposed NEVE, a model that uses a weighted ensemble of neural network classifiers for adaptive learning, trained by means of a quantum-inspired evolutionary algorithm (QIEA). We showed that the neuro-evolutionary classifiers were able to learn the dataset and to quickly respond to any drifts on the underlying data. Now, we are particularly interested on analyzing the influence of an unlimited ensemble, instead of the limited ensemble from NEVE. For that, we modified NEVE to work with unlimited ensembles, and we call this new algorithm NEVE++. To verity how the unlimited ensemble influences the results, we used four different datasets with concept drift in order to compare the accuracy of NEVE and NEVE++, using two other existing algorithms as reference.

NEVE: A Neuro-Evolutionary Ensemble for Adaptive Learning

This work describes the use of a quantum-inspired evolutionary algorithm (QIEA-R) to construct a weighted ensemble of neural network classifiers for adaptive learning in concept drift problems. The proposed algorithm, named NEVE (meaning Neuro-EVolutionary Ensemble), uses the QIEA-R to train the neural networks and also to determine the best weights for each classifier belonging to the ensemble when a new block of data arrives. After running eight simulations using two different datasets and performing two different analysis of the results, we show that NEVE is able to learn the data set and to quickly respond to any drifts on the underlying data, indicating that our model can be a good alternative to address concept drift problems. We also compare the results reached by our model with an existing algorithm, Learn++.NSE, in two different nonstationary scenarios.

Combining Forecasts: A Genetic Programming Approach

Combining forecasts is a common practice in time series analysis. This technique involves weighing each estimate of different models in order to minimize the error between the resulting output and the target. This work presents a novel methodology, aiming to combine forecasts using genetic programming, a metaheuristic that searches for a nonlinear combination and selection of forecasters simultaneously. To present the method, the authors made three different tests comparing with the linear forecasting combination, evaluating both in terms of RMSE and MAPE. The statistical analysis shows that the genetic programming combination outperforms the linear combination in two of the three tests evaluated.

Applying a methodology for collaborative assessment in learning groups

Collaborative evaluation is still a less explored subject within the collaboration field. This paper proposes a methodology to collaborative evaluation based on the 3C collaboration model, which can be applied both in learning or working groups. This paper also presents two case studies run on graduate courses of the Computer Science Department of Catholic University of Rio de Janeiro for collaborative evaluation of the students work. The case studies suggest that the methodology is appropriate for this type of assessment. In addition, students participating in the experiment rated the experience as positive, confirming the premise that students value and miss the collaborative evaluation.

Using Business Processes in System Requirements Definition

The relevance of business process modeling and information technology is growing. That happens because, in general, information systems automate, assist and control those processes. So, the business understanding can be crucial for an appropriate requirements definition. However, there are still few methods that exploit the contributions that the Business Process Engineering can provide for requirements elicitation to produce results more compliant to the company needs. Thus, this work presents a method and its application in a real case that uses the business processes as a way to extract the requirements.

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Resumo: Em busca de novos metodos que auxiliem no aprendizado de portadores de necessidades especiais, um jogo utilizando a tecnologia de agentes virtuais foi criado, atraves da linguagem brasileira de sinais, LIBRAS, o modelo grafico repassa toda informacao necessaria a manipulacao do jogo didatico, despertando no aluno a autonomia e o interesse pelo conteudo abordado. Abstract: Looking for new methods to help learning, a game using the technology of virtual agent was created, a graphic model using the LIBRAS language to transmit all information that is necessary to the student to manipulate the game, increasing his will of learning and self improving.Resumo: Tem sido ampla e intensamente divulgado e aplicado o uso do computador para fins de aprendizagem em diversos dominios. Partindo dessa perspectiva, deu-se inicio a um trabalho na Casa de Saude Paulo de Tarso, o qual tem como objetivo primordial auxiliar na melhoria da coordenacao motora dos pacientes da referida Instituicao e, por consequencia, aumentar a auto-estima, contribuir com o aprendizado, dentre outros. Abstract: The use of the computer has been wide and intensely divulged and applied in the learning process in diverse dominions. In agreement with this perspective, it was started a work at the Health Institution “Paulo de Tarso”, which has as its major goal to assistant in the improvement of the patients motor coordination in the above-mentioned Institution and, by consequence, to augment the self-esteem, to contribute to apprenticeship, among others.Resumo: A Universidade Federal de Mato Grosso (UFMT) - Campus de Rondonopolis, atraves de alguns estudantes, do 4o ano do curso de Licenciatura em Informatica, em pleno exercicio de seu estagio supervisionado, firmou uma parceria com a EEMOP (Escola Estadual Major Otavio Pitaluga) em maio de 2005 para que juntos realizassem um trabalho, onde os estagiarios estariam auxiliando a utilizacao da Internet durante o processo de ensino-aprendizagem na referida escola. Abstract: Mato Grosso’s Federal University (UFMT) Rondonopolis’s Campus, through some students, of the fourth year of the Graduation Course of Degreee in Informatics, in full exercise of their supervised probation period, established a partnership with EEMOP (Major Otavio Pitaluga State School) in may of 2005 so that together they could accomplish a work, where the trainees would be assisting the use of Internet during the teaching- learning process at the above-mentioned school.Resumo: A educacao a distância (EAD) se apresenta no seculo XXI como um novo espaco de trabalho docente, trazendo mudancas nos papeis tradicionais, requerendo um preparo especial do professor. Para verificar se as IES que oferecem EAD formam seus docentes para ensinar a distância e como fazem este trabalho, foi feita uma pesquisa atraves de questionarios enviados por e- mail para 15 IES de Santa Catarina. O presente artigo discute os resultados encontrados que mostraram que as IES catarinenses nao apenas se preocupam com a producao de materiais didaticos, mas estao criando estruturas de apoio para formar seus professores para ensinar a distância. Abstract: Distance education (DE) is presenting, in the 21st century, a new challenge for teachers, asking for a change in their traditional roles, and requiring them to be specially trained for it. In order to find out if the Higher Education Institutions offering DE are training their teachers to work at a distance and how this preparation has been done, a research was conducted in the state of Santa Catarina, Brazil, using a questionnaire, sent by e-mail to 15 institutions. This article presents and discuss the results, showing that the Higher Education Institutions offering DE are not concerned only about the production of the course materials but are, also, creating support structures to prepare their professionals to teach at a distance.Resumo: Este artigo apresenta resultados iniciais de uma pesquisa visando diagnosticar a situacao da informatica educativa no municipio de Belem(PA). Esse diagnostico foi feito tendo-se como referencia um conjunto de criterios propostos para o planejamento e a avaliacao de experiencias em informatica educativa. Entre os resultados apresentados pode-se destacar o contraste entre a rede publica e a privada e o baixo investimento na formacao docente para essa atividade. Abstract: This paper presents the initial results of a diagnostic of the current state of educative informatics in Belem, Para. To perform such analysis, we used a set of criteria that aimed to evaluate the different educative informatics experiences reported. Among the results it is possible to notice clearly the contrast between the public and private school system and the low investment in the teaching personnel.

A2D2: A pre-event abrupt drift detection

Most drift detection mechanisms designed for classification problems works in a post-event manner: after receiving the data set completely (patterns and class labels of the train and test set), they apply a sequence of procedures to identify some change in the class-conditional distribution - a concept drift. However, detecting changes after its occurrence can be in some situations harmful for the process under supervision. This paper proposes a pre-event approach for abrupt drift detection, called by A2D2. Briefly, this method is composed of three steps: (i) label the patterns from the test set, using an unsupervised method; (ii) compute some statistics from the train and test set, conditioned on the given class labels; and (iii) compare the train and test statistics using a multivariate hypothesis test. Also, it has been proposed a procedure for creating datasets with abrupt drift. This procedure was used in the sensivity analysis of A2D2, in order to understand the influence degree of each parameter on its final performance.

GPFIS-Control: A fuzzy Genetic model for Control tasks

This work presents a Genetic Fuzzy Controller (GFC), called Genetic Programming Fuzzy Inference System for Control tasks (GPFIS-Control). It is based on Multi-Gene Genetic Programming, a variant of canonical Genetic Programming. The main characteristics and concepts of this approach are described, as well as its distinctions from other GFCs. Two benchmarks application of GPFIS-Control are considered: the Cart-Centering Problem and the Inverted Pendulum. In both cases results demonstrate the superiority and potentialities of GPFIS-Control in relation to other GFCs found in the literature.

Using ensembles for adaptive learning: A comparative approach

This work describes the use of a weighted ensemble of neural network classifiers for adaptive learning. We train the neural networks by means of a quantum-inspired evolutionary algorithm (QIEA). The QIEA is also used to determine the best weights for each classifier belonging to the ensemble when a new block of data arrives. We show that the neuroevolutionary classifiers are able to learn the data set and to quickly respond to any drifts on the underlying data. We also compare the results reached by our model with an existing algorithm, Learn++.NSE, in two different nonstationary scenarios.