12 resultados para Learning Programming Paradigms
em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"
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The present article describes the challenges programming apprentices face and identifies the elements and processes that set them apart from experienced programmers. And also explains why a conventional programming languages teaching approach fails to map the programming mental model. The purpose of this discussion is to benefit from ideas and cognitive philosophies to be embedded in programming learning tools. Cognitive components are modeled as elements to be handled by the apprentices in tutoring systems while performing a programming task. In this process a mental level solution (the mental model of the program) and an implementation level solution (the program) are created. The mapping between these representations is a path followed by the student explicitly in this approach. © 2011 IEEE.
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The study of function approximation is motivated by the human limitation and inability to register and manipulate with exact precision the behavior variations of the physical nature of a phenomenon. These variations are referred to as signals or signal functions. Many real world problem can be formulated as function approximation problems and from the viewpoint of artificial neural networks these can be seen as the problem of searching for a mapping that establishes a relationship from an input space to an output space through a process of network learning. Several paradigms of artificial neural networks (ANN) exist. Here we will be investigated a comparative of the ANN study of RBF with radial Polynomial Power of Sigmoids (PPS) in function approximation problems. Radial PPS are functions generated by linear combination of powers of sigmoids functions. The main objective of this paper is to show the advantages of the use of the radial PPS functions in relationship traditional RBF, through adaptive training and ridge regression techniques.
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The Backpropagation Algorithm (BA) is the standard method for training multilayer Artificial Neural Networks (ANN), although it converges very slowly and can stop in a local minimum. We present a new method for neural network training using the BA inspired on constructivism, an alphabetization method proposed by Emilia Ferreiro based on Piaget philosophy. Simulation results show that the proposed configuration usually obtains a lower final mean square error, when compared with the standard BA and with the BA with momentum factor.
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ArcTech is a software being developed, applied and improved with the aim of becoming an efficient sensitization tool to support the teaching-learning process of Architecture courses. The application deals initially with the thermal comfort of buildings. The output generated by the software shows if a student is able to produce a pleasant environment, in terms of thermal sensation along a 24-hours period. Although one can find the very same characteristics in fully-developed commercial software, the reason to create ArcTech is related to the flexibility of the system to be adapted by the instructor and also to the need of simple tools for the evaluation of specific topics along the courses. The first part of ArcTech is dedicated to data management and that was developed using the visual programming language Delphi 7 and Firebird as the database management system. The second part contains the parameters that can be changed by the system administrator and those related to project visualization. The interface of the system, in which the student will learn how to implement and to evaluate the project alternatives, was built using Macromedia Flash. The software was applied to undergraduate students revealing its easy-learning and easy-teaching interface.
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One of the most important characteristics of intelligent activity is the ability to change behaviour according to many forms of feedback. Through learning an agent can interact with its environment to improve its performance over time. However, most of the techniques known that involves learning are time expensive, i.e., once the agent is supposed to learn over time by experimentation, the task has to be executed many times. Hence, high fidelity simulators can save a lot of time. In this context, this paper describes the framework designed to allow a team of real RoboNova-I humanoids robots to be simulated under USARSim environment. Details about the complete process of modeling and programming the robot are given, as well as the learning methodology proposed to improve robot's performance. Due to the use of a high fidelity model, the learning algorithms can be widely explored in simulation before adapted to real robots. © 2008 Springer-Verlag Berlin Heidelberg.
Resumo:
This article presents considerations about viability on reutilize existing web based e-Learning systems on Interactive Digital TV environment according to Digital TV standard adopted in Brazil. Considering the popularity of Moodle system in academic and corporative area, such system was chosen as a foundation for a survey into its properties to create a specification of an Application Programming Interface (API) for convergence to t-Learning characteristics that demands efforts in interface design area due the fact that computer and TV concepts are totally different. This work aims to present studies concerning user interface design during two stages: survey and detail of functionalities from an e-Learning system and how to adapt them for the Interactive TV regarding usability context and Information Architecture concepts.
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This paper presents a historical perspective of the Power Electronics education that has lead to the present situation in which such technology is indispensable for the exploitation of almost all type of clean energy primary sources. Some academic initiatives in Brazil are here discussed focusing the institutions grouped in a CAPES-Pró-Engenharia program. The curricula aspects and innovations are presented, emphasizing the multidisciplinary character of this field of Power Electronics application. © 2011 IEEE.
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Studies have demonstrated that nutrient deficiency during pregnancy or in early postnatal life results in structural abnormalities in the offspring hippocampus and in cognitive impairment. In an attempt to analyze whether gestational protein restriction might induce learning and memory impairments associated with structural changes in the hippocampus, we carried out a detailed morphometric analysis of the hippocampus of male adult rats together with the behavioral characterization of these animals in the Morris water maze (MWM). Our results demonstrate that gestational protein restriction leads to a decrease in total basal dendritic length and in the number of intersections of CA3 pyramidal neurons whereas the cytoarchitecture of CA1 and dentate gyrus remained unchanged. Despite presenting significant structural rearrangements, we did not observe impairments in the MWM test. Considering the clear dissociation between the behavioral profile and the hippocampus neuronal changes, the functional significance of dendritic remodeling in fetal processing remains undisclosed. © 2012 ISDN.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Engenharia Mecânica - FEG
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)