48 resultados para Computer based training


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This paper presents SMarty, a variability management approach for UML-based software product lines (PL). SMarty is supported by a UML profile, the SMartyProfile, and a process for managing variabilities, the SMartyProcess. SMartyProfile aims at representing variabilities, variation points, and variants in UML models by applying a set of stereotypes. SMartyProcess consists of a set of activities that is systematically executed to trace, identify, and control variabilities in a PL based on SMarty. It also identifies variability implementation mechanisms and analyzes specific product configurations. In addition, a more comprehensive application of SMarty is presented using SEI's Arcade Game Maker PL. An evaluation of SMarty and related work are discussed.

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The purpose of the present study was to evaluate the effects of 8 weeks of strength and power training on the expression of genes related to the canonical WNT pathway and beta-catenin protein levels in physically active men. Twenty-five subjects (27.4 +/- A 4.6 years) were balanced based on their relative maximum strength in the squat exercise (squat 1RM/body mass) and randomly assigned to strength training (ST) (n = 10), power training (PT) (n = 10), and control (C) (n = 5) groups. The ST and the PT groups performed high and low intensity squats, respectively, thrice a week, for 8 weeks. Muscle biopsies from the vastus lateralis muscle were collected before and after the training period. Relative strength and power increased similarly in both ST and PT groups (P < 0.001). Fiber cross-sectional area also increased similarly in both ST and PT groups. Gene expression and beta-catenin protein expression levels were assessed by real-time PCR and Western blot. Certain genes were up-regulated in the ST group (WNT1: 6.4-fold, P < 0.0001; SFRP1: 3.3-fold, P < 0.0001 and LEF1: 7.3-fold, P < 0.0001) and also in the PT group (WNT1: 24.9-fold, P < 0.0001; SFRP1: 2.7-fold, P < 0.0001; LEF1: 34.1-fold, P < 0.0001 and Cyclin D1: 7.7-fold, P < 0.001). In addition, the expression of key WNT pathway genes was substantially more responsive to PT than to ST (WNT1: P < 0.0001; LEF1: P < 0.0001 and Cyclin D1: P < 0.001). Finally, the total beta-catenin protein content increased only in the PT group (P < 0.05). Our data indicate that a PT regimen triggers greater responses in key elements of the WNT pathway.

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Introduction: Internet users are increasingly using the worldwide web to search for information relating to their health. This situation makes it necessary to create specialized tools capable of supporting users in their searches. Objective: To apply and compare strategies that were developed to investigate the use of the Portuguese version of Medical Subject Headings (MeSH) for constructing an automated classifier for Brazilian Portuguese-language web-based content within or outside of the field of healthcare, focusing on the lay public. Methods: 3658 Brazilian web pages were used to train the classifier and 606 Brazilian web pages were used to validate it. The strategies proposed were constructed using content-based vector methods for text classification, such that Naive Bayes was used for the task of classifying vector patterns with characteristics obtained through the proposed strategies. Results: A strategy named InDeCS was developed specifically to adapt MeSH for the problem that was put forward. This approach achieved better accuracy for this pattern classification task (0.94 sensitivity, specificity and area under the ROC curve). Conclusions: Because of the significant results achieved by InDeCS, this tool has been successfully applied to the Brazilian healthcare search portal known as Busca Saude. Furthermore, it could be shown that MeSH presents important results when used for the task of classifying web-based content focusing on the lay public. It was also possible to show from this study that MeSH was able to map out mutable non-deterministic characteristics of the web. (c) 2010 Elsevier Inc. All rights reserved.

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This paper presents a framework to build medical training applications by using virtual reality and a tool that helps the class instantiation of this framework. The main purpose is to make easier the building of virtual reality applications in the medical training area, considering systems to simulate biopsy exams and make available deformation, collision detection, and stereoscopy functionalities. The instantiation of the classes allows quick implementation of the tools for such a purpose, thus reducing errors and offering low cost due to the use of open source tools. Using the instantiation tool, the process of building applications is fast and easy. Therefore, computer programmers can obtain an initial application and adapt it to their needs. This tool allows the user to include, delete, and edit parameters in the functionalities chosen as well as storing these parameters for future use. In order to verify the efficiency of the framework, some case studies are presented.

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This study aimed to describe the benefits of memory training for older adults with low education. Twenty-nine healthy older adults with zero to two years of formal education participated. Sixteen participants received training based on categorization (categorization group = CATG) and 13 received training based on mental images (imagery group = IMG). One group served as control for the other because they trained with different strategies. Training was offered in eight sessions of 90 minutes. The participants were evaluated pre- and posttraining. IMG improved performance in episodic memory tests and had reduced depressive symptoms. CATG increased the use of categorization but did not increase performance in episodic memory tests. Results suggest that the strategy based on the creation of mental images was more effective for older adults with low formal education.

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Intense physical training and dietary energy restriction have been associated with consequences such as nutritional amenorrhea. We investigated the effects of intense physical training, food restriction or the combination of both strategies on estrous cyclicity in female rats, and the relationship between leptin ad these effects. Twenty-seven female Wistar rats were distributed into four groups: SF: sedentary, fed ad libitum; SR: sedentary subjected to 50% food restriction (based on the food intake of their fed counterparts); TF: trained (physical training on a motor treadmill with a gradual increase in speed and time), fed ad libitum; TR; trained with 50% food restriction. We analysed estrous cyclicity, plasma leptin and estradiol as well as chemical composition of the carcass, body weight variation. and weight of ovaries and perirenal adipose tissue. Data demonstrate that physical training alone was not responsible for significant modifications in either carcass chemical composition or reproductive function. Food restriction reduced leptin levels in all animals and interrupted the estrous cyclicity in some animals, but only the combination of food restriction and physical training was capable of interrupting the estrous cyclicity in all animals. Leptin was not directly related to estrous cyclicity. From our findings, it may be concluded that there is an additive or synergistic effect of energy intake restriction and energy expenditure by intense physical training on estrous cyclicity. Leptin appears to be one among others factors related to estrous cycle, but it probably acts indirectly.

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Exercise training is known to promote relevant changes in the properties of skeletal muscle contractility toward powerful fibers. However, there are few studies showing the effect of a well-established exercise training protocol on Ca(2+) handling and redox status in skeletal muscles with different fiber-type compositions. We have previously standardized a valid and reliable protocol to improve endurance exercise capacity in mice based on maximal lactate steady-state workload (MLSSw). The aim of this study was to investigate the effect of exercise training, performed at MLSSw, on the skeletal muscle Ca(2+) handling-related protein levels and cellular redox status in soleus and plantaris. Male C57BL/6J mice performed treadmill training at MLSSw over a period of eight weeks. Muscle fiber-typing was determined by myosin ATPase histochemistry, citrate synthase activity by spectrophotometric assay, Ca(2+) handling-related protein levels by Western blot and reduced to oxidized glutathione ratio (GSH:GSSG) by high-performance liquid chromatography. Trained mice displayed higher running performance and citrate synthase activity compared with untrained mice. Improved running performance in trained mice was paralleled by fast-to-slow fiber-type shift and increased capillary density in both plantaris and soleus. Exercise training increased dihydropyridine receptor (DHPR) alpha 2 subunit, ryanodine receptor and Na(+)/Ca(2+) exchanger levels in plantaris and soleus. Moreover, exercise training elevated DHPR beta 1 subunit and sarcoplasmic reticulum Ca(2+)-ATPase (SERCA) 1 levels in plantaris and SERCA2 levels in soleus of trained mice. Skeletal muscle GSH content and GSH:GSSG ratio was increased in plantaris and soleus of trained mice. Taken together, our findings indicate that MLSSw exercise-induced better running performance is, in part, due to increased levels of proteins involved in skeletal muscle Ca(2+) handling, whereas this response is partially dependent on specificity of skeletal muscle fiber-type composition. Finally, we demonstrated an augmented cellular redox status and GSH antioxidant capacity in trained mice.

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Support for interoperability and interchangeability of software components which are part of a fieldbus automation system relies on the definition of open architectures, most of them involving proprietary technologies. Concurrently, standard, open and non-proprietary technologies, such as XML, SOAP, Web Services and the like, have greatly evolved and been diffused in the computing area. This article presents a FOUNDATION fieldbus (TM) device description technology named Open-EDD, based on XML and other related technologies (XLST, DOM using Xerces implementation, OO, XMIL Schema), proposing an open and nonproprietary alternative to the EDD (Electronic Device Description). This initial proposal includes defining Open-EDDML as the programming language of the technology in the FOUNDATION fieldbus (TM) protocol, implementing a compiler and a parser, and finally, integrating and testing the new technology using field devices and a commercial fieldbus configurator. This study attests that this new technology is feasible and can be applied to other configurators or HMI applications used in fieldbus automation systems. (c) 2008 Elsevier B.V. All rights reserved.

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The goal of this paper is to study and propose a new technique for noise reduction used during the reconstruction of speech signals, particularly for biomedical applications. The proposed method is based on Kalman filtering in the time domain combined with spectral subtraction. Comparison with discrete Kalman filter in the frequency domain shows better performance of the proposed technique. The performance is evaluated by using the segmental signal-to-noise ratio and the Itakura-Saito`s distance. Results have shown that Kalman`s filter in time combined with spectral subtraction is more robust and efficient, improving the Itakura-Saito`s distance by up to four times. (C) 2007 Elsevier Ltd. All rights reserved.

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The crossflow filtration process differs of the conventional filtration by presenting the circulation flow tangentially to the filtration surface. The conventional mathematical models used to represent the process have some limitations in relation to the identification and generalization of the system behaviour. In this paper, a system based on artificial neural networks is developed to overcome the problems usually found in the conventional mathematical models. More specifically, the developed system uses an artificial neural network that simulates the behaviour of the crossflow filtration process in a robust way. Imprecisions and uncertainties associated with the measurements made on the system are automatically incorporated in the neural approach. Simulation results are presented to justify the validity of the proposed approach. (C) 2007 Elsevier B.V. All rights reserved.

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Voltage and current waveforms of a distribution or transmission power system are not pure sinusoids. There are distortions in these waveforms that can be represented as a combination of the fundamental frequency, harmonics and high frequency transients. This paper presents a novel approach to identifying harmonics in power system distorted waveforms. The proposed method is based on Genetic Algorithms, which is an optimization technique inspired by genetics and natural evolution. GOOAL, a specially designed intelligent algorithm for optimization problems, was successfully implemented and tested. Two kinds of representations concerning chromosomes are utilized: binary and real. The results show that the proposed method is more precise than the traditional Fourier Transform, especially considering the real representation of the chromosomes.

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The purpose of this paper is to propose a multiobjective optimization approach for solving the manufacturing cell formation problem, explicitly considering the performance of this said manufacturing system. Cells are formed so as to simultaneously minimize three conflicting objectives, namely, the level of the work-in-process, the intercell moves and the total machinery investment. A genetic algorithm performs a search in the design space, in order to approximate to the Pareto optimal set. The values of the objectives for each candidate solution in a population are assigned by running a discrete-event simulation, in which the model is automatically generated according to the number of machines and their distribution among cells implied by a particular solution. The potential of this approach is evaluated via its application to an illustrative example, and a case from the relevant literature. The obtained results are analyzed and reviewed. Therefore, it is concluded that this approach is capable of generating a set of alternative manufacturing cell configurations considering the optimization of multiple performance measures, greatly improving the decision making process involved in planning and designing cellular systems. (C) 2010 Elsevier Ltd. All rights reserved.

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In this article a novel algorithm based on the chemotaxis process of Echerichia coil is developed to solve multiobjective optimization problems. The algorithm uses fast nondominated sorting procedure, communication between the colony members and a simple chemotactical strategy to change the bacterial positions in order to explore the search space to find several optimal solutions. The proposed algorithm is validated using 11 benchmark problems and implementing three different performance measures to compare its performance with the NSGA-II genetic algorithm and with the particle swarm-based algorithm NSPSO. (C) 2009 Elsevier Ltd. All rights reserved.

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Distributed control systems consist of sensors, actuators and controllers, interconnected by communication networks and are characterized by a high number of concurrent process. This work presents a proposal for a procedure to model and analyze communication networks for distributed control systems in intelligent building. The approach considered for this purpose is based on the characterization of the control system as a discrete event system and application of coloured Petri net as a formal method for specification, analysis and verification of control solutions. With this approach, we develop the models that compose the communication networks for the control systems of intelligent building, which are considered the relationships between the various buildings systems. This procedure provides a structured development of models, facilitating the process of specifying the control algorithm. An application example is presented in order to illustrate the main features of this approach.

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One of the e-learning environment goal is to attend the individual needs of students during the learning process. The adaptation of contents, activities and tools into different visualization or in a variety of content types is an important feature of this environment, bringing to the user the sensation that there are suitable workplaces to his profile in the same system. Nevertheless, it is important the investigation of student behaviour aspects, considering the context where the interaction happens, to achieve an efficient personalization process. The paper goal is to present an approach to identify the student learning profile analyzing the context of interaction. Besides this, the learning profile could be analyzed in different dimensions allows the system to deal with the different focus of the learning.