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407 results for “Linear Approach”
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Research ArticleOpen accessIn the abstractSimulated Annealing Decoder for Linear Block CodesLahcen Niharmine, Hicham Bouzkraoui, Ahmed Azouaoui, Youssef HadiIn this study, we introduce a novel soft decoder, the first of its kind, for linear block codes, based on Simulated Annealing algorithm (SA). The main enhancement in our contribution which let our decoder over performs with large gain (about 3 dB at 710-4) the classical SA approach, is to take the most reliable information set of the received codeword … …Journal of Computer Science, Vol. 14, Issue 8 · 4 Sep 2018 · 7,810 accessesView PDFCite
Research ArticleOpen accessIn the abstractBidirectional Blockchain-Based Secure Data Transfer Using GALOEEM Routing Protocol in WSNAnitha Rajakumari Ponjothi, Pritee ParwekarData exchange is hampered by the fact that warehouse data are distributed among warehouses. To propose a secure bidirectional blockchain-based data-sharing system that collects warehouse data and controls data sharing through bidirectional transformation. This study is proposed for establishing an efficient bi-directional data warehouse storage for script less blockchains with an infinite lifespan. The sensor provides the data used in … …Journal of Computer Science, Vol. 19, Issue 8 · 20 Jul 2023 · 5,815 accessesView PDFCite
Research ArticleOpen accessIn the abstractRobust Linear Discriminant AnalysisSharipah Soaad Syed Yahaya, Yai-Fung Lim, Hazlina Ali, Zurni OmarLinear Discriminant Analysis (LDA) is the most commonly employed method for classification. This method which creates a linear discriminant function yields optimal classification rule between two or more groups under the assumptions of normality and homoscedasticity (equal covariance matrices). However, the calculation of parametric LDA highly relies on the sample mean vectors and pooled sample covariance matrix which are sensitive … …Journal of Mathematics and Statistics, Vol. 12, Issue 4 · 4 Jan 2017 · 7,649 accessesView PDFCite
Research ArticleOpen accessIn the abstractAssessing Supervised Classification Algorithms for Mangrove Detection and Differentiation from Other Forest Types in Paiton District, Probolinggo RegencyKaruniawan Puji Wicaksono, Fathor Rohman, Yasushi MitsudaRemote sensing provides an effective approach for monitoring forest cover dynamics, yet distinguishing mangroves from other forest types remains challenging in heterogeneous coastal landscapes. This study compares six supervised classification algorithms: Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Mixture Discriminant Analysis (MDA), Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) for mangrove detection in Paiton, … …OnLine Journal of Biological Sciences, Vol. 26, Issue 3 · 1 Sep 2026 · 844 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluation of Machine Learning Models to Predict Student Academic Performance Using Structured Educational DataHardik Ishwarbhai Patel, Dharmendra PatelThis study analyses the use of machine learning for predicting the academic performance of students using their academic information from the institution, combined with socio-economic information that comes from outside sources. The collection of information is done using structured questionnaires as well as through data extraction from the Student Information System (SIS). To increase the reliability of models built, a … …Journal of Computer Science, Vol. 22, Issue 5 · 26 May 2026 · 1,419 accessesView PDFCite
Research ArticleOpen accessIn the abstractLow-Homology Protein Structural Class Prediction from Secondary Structure Based on Visibility and Horizontal Visibility NetworkZhi-Qin Zhao, Liang Luo, Xiao-Yan LiuIn this study, based on the predicted secondary structures of proteins, we propose a new approach to predict protein structural classes (α,β,α/β,α+β) for three widely used low-homology data sets. Fist, we obtain two time siries from the chaos game representation of each predicted secondary structure; second, based on two time series, we construct visibility and horizontal visibility network, respectively and … …American Journal of Biochemistry and Biotechnology, Vol. 14, Issue 1 · 12 Mar 2018 · 9,668 accessesView PDFCite
EditorialOpen accessIn the abstractBig Data and Parkinson’s Disease - from Understanding of Disease to Personalised MedicineYen F. Tai, Nicola PaveseThe advancement of information technology in recent years has generated a huge amount of datasets in all areas of scientific research. This has led to new opportunities to harness the 'Big Data' to improve our understanding of diseases - from investigating disease mechanisms to monitoring treatment responses. The Big Data approach is a data-driven and often hypothesis-free, way of studying … …Neuroscience International, Vol. 7, Issue 1 · 27 Jul 2016 · 7,755 accessesView PDFCite
Research ArticleOpen accessIn the abstractModeling Pan Evaporation for Kuwait using Multiple Linear Regression and Time-Series TechniquesJaber AlmedeijThis study attempts to model evaporation for Kuwait under arid conditions by using a wide range of monthly evaporation data, varying from 0.1 to 40 mm/day, from January 1993 to July 2015. Owing to the reason that the well-known theoretical evaporation models presented in the literature have been justified for a much shorter data range, the paper adopts empirical approaches … …American Journal of Applied Sciences, Vol. 13, Issue 6 · 8 Jun 2016 · 7,089 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Integrative Approach to the Study of Individuality of Subjects of Educational Activity in the Ontogeny from the Positions of Sex and GenderLubov Vladimirovna MishchenkoScientists are trying to study the peculiarities of men and women by adding biological and social components of the human, however since gender is not the natural givenness, but a social construct assuming self-awareness and self-determination, the connections between these components will be refracted through a variety of conditions. The purpose of the article is an integrative study of non-linear … …American Journal of Applied Sciences, Vol. 13, Issue 5 · 27 May 2016 · 7,329 accessesView PDFCite
Research ArticleOpen accessIn the abstractGeneral Linear Models in a Missing Outcome Environment of Clinical Trials Incorporating with Splines for Time-Invariant Continuous AdjustmentMinjeong Park, Dejian Lai, Xianglin L. Du et al.Missing data is a common occurrence in longitudinal studies of health care research. Although many studies have shown the potential usefulness of current missing analyses, e.g., (1) Complete Case (CC) analysis; (2) imputation methods such as Last Observation Carried Forward (LOCF), multiple imputations, Expectation-Maximization algorithm approach; and (3) methods using all available data such as linear mixed model and generalized … …Current Research in Biostatistics, Vol. 5, Issue 1 · 18 Aug 2015 · 7,401 accessesView PDFCite