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147 results for “Clustering Method”
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Research ArticleOpen accessIn the abstractOptimizing N-linked Glycosylation Site Prediction in Human Proteins with Ensemble Stacking and Cross-ValidationMubina Malik, Jaimin UndaviaThe most frequent post-translational modification of proteins in all territories is glycosylation which impacts many biological activities. The most significant and critical of these modifications is N-linked glycosylation which is associated with various human diseases including diabetes cancer Inflammation Alzheimers and atherosclerosis. This article illustrates recent advances in knowledge of biology that are eventually targeting the computer science sector. Moreover-identification … …Journal of Computer Science, Vol. 20, Issue 12 · 20 Nov 2024 · 5,005 accessesView PDFCite
Research ArticleOpen accessIn the abstractGlobal Supply Chain: Enhance Production Cost Efficiency Through Machine LearningLoubna Moumeni, Mohammed SaberMachine learning has enabled the discovery of various disciplines and patterns in Supply Chain Management (SCM). The entire industrial sector is striving to harness the contextual intelligence provided by machine learning by exploring new areas within the supply chain network. This article delves into Supply Chain Management (SCM) and its broader implications beyond logistics. SCM involves the resources, methods, and … …Journal of Computer Science, Vol. 20, Issue 9 · 14 Jun 2024 · 5,320 accessesView PDFCite
Research ArticleOpen accessIn the abstractProfiling the Volatile Compound of Indonesian Rendang Using GC-MS/MS AnalysisDaimon Syukri, Abdi, Tuty Anggraini et al.Rendang is an indigenous food from west Sumatra with a distinct flavor and aroma. Different rendang production methods have an impact on its sensory qualities, including flavor and aroma. Finding the volatile substances that distinguish the aroma of each rendang was the aim of this investigation. In this experiment, five distinct Indonesian rendangs were used. Using the Head Space-Solid Phase … …OnLine Journal of Biological Sciences, Vol. 24, Issue 1 · 13 Nov 2023 · 6,361 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalysis of Big Data Football Club Market Value Using K-Means and Linear Regression Mining MethodsJohanes Fernandes Andry, Riama Sibarani, Vlavio Nathanael YeftaFootball clubs store a lot of data about their players, squad, transfer market, and market value, so big data is needed to process this data. This data can be analyzed to gain insight into the club's market value. Changes in player performance, age, and squad size can be analyzed using statistical methods. These digital data will provide information about the … …Journal of Computer Science, Vol. 19, Issue 2 · 10 Feb 2023 · 5,996 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 abstractAUTHORSHIP CATEGORIZATION IN EMAIL INVESTIGATIONS USING FISHER’S LINEAR DISCRIMINANT METHOD WITH RADIAL BASIS FUNCTIONA. Pandian, Md. Abdul Karim SadiqEmail plays a vital role in faster communication. Lots of mails are sent to common public with falsified information that appears to be a realistic. It is mandatory to trace the origin of the email and the authors/systems responsible for generating such emails. Representative signatures of email are to be generated using lexical and syntactic based methods. The signature of … …Journal of Computer Science, Vol. 10, Issue 6 · 31 Jan 2014 · 6,690 accessesView PDFCite
Research ArticleOpen accessIn the abstractOnline Forums Hotspot Prediction Based on Sentiment AnalysisK. Nirmala Devi, V. Murali BhaskarnProblem statement: Online forums hotspot prediction is one of the significant research areas in web mining, which can help people make proper decision in daily life. Online forums, news reports and blogs, are containing large volume of public opinion information. Rapid growth of network arouses much attention on public opinion, it is important to analyse the public opinion in time … …Journal of Computer Science, Vol. 8, Issue 8 · 11 Jul 2012 · 7,363 accessesView PDFCite
Research ArticleOpen accessIn the abstractMemory Convergence and Optimization with Fuzzy PSO and ACSSubhash C. Pandey, Dr. P. MisraAssociative neural memories are models of biological phenomena that allow for the storage of pattern associations and the retrieval of the desired output pattern upon presentation of a possibly noisy or incomplete version of an input pattern. In this study, we introduce fuzzy swarm particle optimization technique for convergence of associative neural memories based on fuzzy set theory. A Fuzzy … …Journal of Computer Science, Vol. 4, Issue 2 · 28 Feb 2008 · 7,176 accessesView PDFCite
Research ArticleOpen accessIn the abstractInvestigation of the Characteristics of Thulium Doped Alumina Nanoparticles for Applications in Silica-Based FibersNur Atiqa Bt Rahmat, Hairul Azhar Abd Rashid, H.Y. Wong, Mukter ZamanIt is reported that during the fabrication of doping RE ions into the silica preform, the distribution of particles is inhomogeneous and becomes uneven throughout the fiber which lead to unwanted spectroscopic characteristics. It is assumed that by using thulium doped with alumina, the problem with the inhomogeneity of the particles inside the fiber can be solved. With the incorporation … …American Journal of Applied Sciences, Vol. 14, Issue 1 · 26 Jan 2017 · 7,413 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of the Artificial Neural Networks Options Pricing Model Under Constant and Time-Variant VolatilitiesHanningtone Meshack Simiyu, Anthony Gichuhi Waititu, Jane Aduda AkinyiOption pricing using artificial neural networks (ANN) model while relaxing the assumption of constant volatility still remains a challenge. The conventional practice for pure ANN models has been to either model volatility using the very ANN model and have the model output fed as an input to the ANN option pricing model, or to make allowances for a large number … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 20 Jul 2019 · 7,015 accessesView PDFCite