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Research ArticleOpen accessIn the abstractPerformance Optimization of Physics Simulations Through Genetic AlgorithmsOksana Shadura, Federico Carminati, Anatoliy PetrenkoThe GeantV R&D approach is revisiting the standard particle transport simulation approach to be able to benefit from “Single Instruction, Multiple Data” (SIMD) computational architectures or extremely parallel systems like coprocessors and GPUs. The goal of this work is to develop a mechanism for optimizing the programs used for High-Energy Physics (HEP) particle transport simulations using a “black-box” optimization approach. … …Journal of Computer Science, Vol. 15, Issue 1 · 8 Jan 2019 · 8,091 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Backpropagation Neural Network for Splitting IdentifiersAhmed Sabah Ahmed AL-Jumaili, Huda Kadhim Tayyeh, Ruqaia Jawad KadhemSplitting identifiers is a task that has been addressed in the past few years in order to contribute toward improving the Feature Location task. Feature Location aims at determining the exact position of a specific feature within a source code. Several research studies have addressed the process of splitting multi-word identifiers. However, one of the endure gaps that still face … …Journal of Computer Science, Vol. 14, Issue 10 · 31 Oct 2018 · 7,227 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Use of Band Selection in Weighted Linear Prediction for Hyperspectral Image ClassificationIbtissam Banit'ouagua, Mounir Ait Kerroum, Ahmed HammouchThe advancement of imaging procedures has made hyperspectral sensors fit for acquiring spectral data in many restricted and bordering bands, which brings about a high relationship between's neighboring bands and high information excess. It is important to decrease these bands previously advance analysis utilizing land cover classification and target location. Going for the classification undertaking, this paper displays another weighted … …Journal of Computer Science, Vol. 14, Issue 8 · 4 Sep 2018 · 8,262 accessesView PDFCite
Research ArticleOpen accessIn the abstractSentiment Analysis: Comparative Study between GSVM and KNNHany Mohamed, Ayman Atia, Mostafa-Sami M. MostafaSentiment classification aims detecting general opinion of users in social media towards business products or daily life events. The classification tells whether sentiment is positive or negative. Techniques of sentiment classification are categorized into lexical analysis and machine learning techniques. In this paper, we propose a comparative study between SVM applied genetics (GSVM) against KNN algorithm in terms of speed … …American Journal of Applied Sciences, Vol. 15, Issue 6 · 1 Aug 2018 · 8,359 accessesView PDFCite
Literature ReviewOpen accessIn the abstractEfficient Morphometric Techniques in Alzheimer’s Disease Detection: Survey and ToolsVinutha N., P. Deepa Shenoy, K.R. VenugopalThe development of advance techniques in the multiple fields such as image processing, data mining and machine learning are required for the early detection of Alzheimer’s Disease (AD) and to prevent the progression of the disease to the later stages. The longitudinal and cross sectional images of elderly subjects were obtained from the standard datasets like ADNI, OASIS, MIRIAD and … …Neuroscience International, Vol. 7, Issue 2 · 4 Oct 2017 · 8,450 accessesView PDFCite
Research ArticleOpen accessIn the abstractStock Trading Using PE Ratio Based on Bayesian InferenceHaizhen Wang, Ratthachat Chatpatanasiri, Pairote SattayathamThe Price Earnings (PE) ratio is one of the most widely applied tool for the firm valuation in a security market. Unfortunately, recent academic developments in financial econometrics and machine learning have rarely looked at this tool. In the paper, we propose to formalize a process of fundamental PE ratio estimation by employing Dynamic Bayesian Network (DBN) methodology. Forward-backward inference … …Journal of Mathematics and Statistics, Vol. 13, Issue 3 · 29 Sep 2017 · 7,425 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Feature Extraction Method for Accuracy Improvement in “Aksara Lontara” TranslationIntan Sari Areni, Asyraful Insan Asry, IndrabayuAn Optical Character Recognition (OCR) of “Aksara Lontara” has been constructed using a novel combination of feature extraction methods in this study. The ancient font of “Lontara” is then translated into Bahasa Indonesia to help non-native language to learn this language. Two powerful extraction feature methods, i.e., Modified Direction Feature (MDF) and Fourier Descriptor (FD) are stages combined to deal … …Journal of Computer Science, Vol. 13, Issue 9 · 27 Aug 2017 · 8,851 accessesView PDFCite
Research ArticleOpen accessIn the abstractNovel Apache Spark based Algorithm to Solve Dirichlet Problem for Poisson Equation in 3D Computational DomainShomanov Aday, Mansurova MadinaParallel computations are essential tool in solving large-scale computationally demanding problems. Due to large diversity and heterogeneity of the currently available parallel processing techniques and paradigms it is usually difficult to find the right solution that will perform well according to every performance metric. As one of the recent developments in parallel computing Apache Spark framework allows to process petabyte-scale … …Journal of Computer Science, Vol. 12, Issue 10 · 15 Dec 2016 · 7,049 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptive Acceptance Criterion (AAC) Algorithm for Optimization ProblemsAnmar AbuhamdahOptimization methods commonly are designed for solving the optimization problems. Local search algorithms are optimization method, which are good candidate in exploiting the search space. However, most of them need parameter tuning and incapable of escaping from local optima. This work proposes non-parametric Acceptance Criterion (AC) that not relies on user-defined, which motivate to propose an Adaptive Acceptance Criterion (AAC). … …Journal of Computer Science, Vol. 11, Issue 4 · 23 Jul 2015 · 6,969 accessesView PDFCite
Research ArticleOpen accessIn the abstractAUTOMATIC MUSIC EMOTION CLASSIFICATION USING ARTIFICIAL NEURAL NETWORK BASED ON VOCAL AND INSTRUMENTAL SOUND TIMBRESMudiana Binti Mokhsin, Nurlaila Binti Rosli, Suzana Zambri et al.Detecting emotion features in a song remains as a challenge in various area of research especially in Music Emotion Classification (MEC). In order to classify selected song with certain mood or emotion, the algorithms of the machine learning must be intelligent enough to learn the data features as to match the features accordingly to the accurate emotion. Until now, there … …Journal of Computer Science, Vol. 10, Issue 12 · 29 Dec 2014 · 8,527 accessesView PDFCite