Research ArticleOpen accessIn the abstractContributions Concerning Muscle Training in Professionnal VolleyballNiculescu Mugurel, Niculescu Ionela, Amzăr Elena LuminiţaProblem statement: Complex muscle training, less known to our specialists, has proved that, by complying with all the stages proposed, high level results may be achieved. The performances, weaker and weaker, obtained by the Romanian teams call for measures of optimization and Specific Physical Training (SPT) in accordance to technical -tactical training. Physical training should be individualized and multiplied, under … …Journal of Social Sciences, Vol. 7, Issue 3 · 16 Jul 2011 · 7,315 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimization of Coaching Using Six SigmaDumitru Colibaba-Evulet, Andrei EvuletProblem statement: In today’s sports world, coaching and training methods are the subject of intensive competition amongst rivals. Innovative technologies, methodologies and preparation methods are employed to achieve a sustainable competitive advantage. Effective performance measurement, statistical analysis and data based decision taking have been identified as key elements towards efficient performance management. The statistical approach has been emphasized in order … …Journal of Social Sciences, Vol. 7, Issue 3 · 16 Jul 2011 · 8,057 accessesView PDFCite
Research ArticleOpen accessIn the abstractFeature Subset Selection for Hot Method Prediction using Genetic Algorithm wrapped with Support Vector MachinesSandra Johnson, Valli ShanmugamProblem statement: All compilers have simple profiling-based heuristics to identify and predict program hot methods and also to make optimization decisions. The major challenge in the profile-based optimization is addressing the problem of overhead. The aim of this work is to perform feature subset selection using Genetic Algorithms (GA) to improve and refine the machine learnt static hot method predictive … …Journal of Computer Science, Vol. 7, Issue 5 · 7 May 2011 · 7,238 accessesView PDFCite
Research ArticleOpen accessIn the abstractIdentification of Pecan Weevils through Image ProcessingS.M. Al-Saqer, P. Weckler, J. Solie et al.Abstract: Problem Statement: Pecan weevil is one of the most destructive pests of Oklahoma. The scope of this study is to develop a recognition system that can serve in a wireless imaging network for monitoring pecan weevils. Approach: The recognition methods used in this study are based on template matching. Five recognition methods were implemented: Normalized cross-correlation, Fourier descriptors, Zernike … …American Journal of Agricultural and Biological Sciences, Vol. 6, Issue 1 · 15 Dec 2010 · 8,776 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptive Resonance Theory Training Parameters: Pretty Good SetsTaisir Mohammad Eldos, Abdulaziz Suleiman AlmazyadProblem statement: ART1 artificial neural networks offer good tools for test clustering, where no expert is needed if the system is well trained. However, having no output reference for the input patterns makes it hard to judge the quality of the training. Moreover, the performance depends to a great extent on a set of training parameters. Designers follow some recommendations … …Journal of Computer Science, Vol. 6, Issue 12 · 6 Nov 2010 · 7,161 accessesView PDFCite
Research ArticleOpen accessIn the abstractAcoustic Model Adaptation for Indonesian Language Utterance Training SystemLinda Indrayanti, Yoshifumi Chisaki, Tsuyoshi UsagawaProblem statement: In order to build an utterance training system for Indonesian language, a speech recognition system designed for Indonesian is necessary. However, the system hardly works well due to the pronunciation variants of non-native utterances may lead to substitution/deletion error. This research investigated the pronunciation variant and proposes acoustic model adaptation to improve performance of the system. Approach: The … …Journal of Computer Science, Vol. 6, Issue 11 · 23 Oct 2010 · 7,173 accessesView PDFCite
Research ArticleOpen accessIn the abstractNew Constructive Neural Network Architecture for Pattern ClassificationS. S. Sridhar, M. PonnavaikkoProblem statement: Constructive neural network learning algorithms provide optimal ways to determine the architecture of a multi layer perceptron network along with learning algorithms for determining appropriate weights for pattern classification problems. These algorithms initially start with small network and dynamically allow the network to grow by adding and training neurons as needed until a satisfactory solution is found. The … …Journal of Computer Science, Vol. 5, Issue 11 · 30 Nov 2009 · 6,570 accessesView PDFCite
Research ArticleOpen accessIn the abstractBoosting Kernel Discriminative Common Vectors for Face RecognitionC. Lakshmi, M. PonnavaikkoProblem statement: Kernel discriminative common vector (KDCV) was one of the most effective non-linear techniques for feature extraction from high dimensional data including images and text data. Approach: This study presented a new algorithm called Boosting Kernel Discriminative Common Vector (BKDCV) to further improve the overall performance of KDCV by integrating the boosting and KDCV techniques. Results: In BKDCV, the … …Journal of Computer Science, Vol. 5, Issue 11 · 30 Nov 2009 · 6,579 accessesView PDFCite
Research ArticleOpen accessIn the abstractSupervised Machine Learning Model-Based Approach for Performance Prediction of StudentsAbdul Razaque, Abrar M. AlajlanPredicting students’ performance is one of the crucial issue for learning contexts, since it helps to develop alternative recommendation systems for academically weak students. Thus, several methods and practices have been applied for educational improvement. However, most of the existing methods do not determine the performance of the students. In this study, we have studied the execution of six machine … …Journal of Computer Science, Vol. 16, Issue 8 · 28 Aug 2020 · 7,089 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptic Disc Segmentation in Fundus Images with Deep Learning Object DetectorManal AlGhamdiThe Optic Disc (OD) is an important anatomical landmark in the fundus image to diagnose a myriad of diseases, such as glaucoma and Diabetic Retinopathy (DR) and to locate structures such as the macula and the main vascular arcade. However, locating and segmenting the OD are not easy tasks. Previous methods have employed a deep Convolutional Neural Network (CNN) without … …Journal of Computer Science, Vol. 16, Issue 5 · 14 May 2020 · 7,377 accessesView PDFCite