Research ArticleOpen accessIn the abstractMemoryless Modified Symmetric Rank-One Method for Large-Scale Unconstrained OptimizationFarzin Modarres, Malik Abu Hassan, Wah June LeongProblem statement: Memoryless QN methods have been regarded effective techniques for solving large-scale problems that can be considered as one step limited memory QN methods. In this study, we present a scaled memoryless modified Symmetric Rank-One (SR1) algorithm and investigate the numerical performance of the proposed algorithm for solving large-scale unconstrained optimization problems. Approach: The basic idea is to apply … …American Journal of Applied Sciences, Vol. 6, Issue 12 · 31 Dec 2009 · 7,986 accessesView PDFCite
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 · 8,096 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Empirical Criterion for Transitive ClosureMarius OrlowskiThe paper establishes a simple and computationally economical criterion for determining whether a given adjacency matrix represents a transitive closure or not. The criterion is based on a new iterative method for finding the transitive closure adjacency matrix. This method is equivalent to but computationally more efficient than the traditional Boolean sum of successive powers of the original adjacency matrix … …Journal of Computer Science, Vol. 18, Issue 12 · 23 Dec 2022 · 5,422 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of Data Enhancement Method Based on Generative Adversarial Networks for Soybean Leaf Disease IdentificationXiao Yu, Cong Chen, Qi Gong, Lina LuSoybean leaf disease data collection is an expensive and time-consuming task. Convolutional neural network training requires a large amount of data, but traditional data enhancement methods (such as rotation, flipping, translation) are restricted by fixed rules and cannot generate images with diversity and variability. Aiming at the problem of the lack of soybean leaf disease data set, this study proposes … …American Journal of Biochemistry and Biotechnology, Vol. 18, Issue 4 · 26 Nov 2022 · 5,208 accessesView PDFCite
Research ArticleOpen accessIn the abstractProtein Secondary Structure Prediction using Hybrid Recurrent Neural NetworksRomana Rahman Ema, Akhi Khatun, Md. Alam Hossain et al.The most important and challenging problem in bioinformatics is protein secondary structure prediction. The molecules of all protein organisms have three-dimensional (primary, secondary, 3-D) structures which are completely recognized by the sequence of amino acids. Protein secondary structure attributes to the polypeptide backbone of the local configuration of proteins. Most generally, the second-level prediction is indicated such as: If there … …Journal of Computer Science, Vol. 18, Issue 7 · 14 Jul 2022 · 7,339 accessesView PDFCite
Research ArticleOpen accessIn the abstractMetabolic Potential Versus Genome SizeAtanas Todorov Atanasov, Dimitar Todorov ValevAlberch, P. (1983). Development and Evolution: Embryos, Genes, and Evolution. The Developmental-Genetic Basis of Evolutionary Change. Science, 221(4607), 257–258. https://doi.org/10.1126/science.221.4607.257 Andrews, C. B., Mackenzie, S. A., & Gregory, T. R. (2009). Genome size and wing parameters in passerine birds. Proceedings of the Royal Society B, 276(1654), 55–61. https://doi.org/10.1098/rspb.2008.1012 Atanasov, A. T. (2005). The linear alometric relationship between total metabolic energy … …Physics International, Vol. 13, Issue 1 · 15 Jun 2022 · 7,233 accessesView PDFCite
Research ArticleOpen accessIn the abstractSmart Agriculture and Food Industry with Blockchain and Artificial IntelligenceN. Nasurudeen Ahamed, R. VigneshHorticulture is one of the most major human exercises everywhere. Brilliant horticulture incorporates a bunch of advances, gadgets, conventions and computational ideal models to improve farming cycles. Blockchain, Big information, man-made consciousness, cloud and edge processing give capacities and answers for keeping, storing and investigating the huge information created by parts. The entry of a yield from the maker to … …Journal of Computer Science, Vol. 18, Issue 1 · 14 Jan 2022 · 10,399 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetection of Plant Leaf Diseases Using K‒mean++ Intermeans Thresholding AlgorithmKittipol Wisaeng, Worawat Sa–NgiamviboolIn the field of agricultural information, the plant leaf disease detection is highly important for both farmer life and environment. To improve the accuracy of plant leaf disease detection and reduce the image processing time, the improved K‒mean++ clustering and intermeans thresholding method are proposed in this study. The proposed algorithms are used for training and testing diseases in plant … …Journal of Computer Science, Vol. 16, Issue 9 · 21 Sep 2020 · 6,760 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntegrated Modeling Framework for Highway Traffic Pollution Estimation and DispersionShu Yang, Yao-Jan Wu, John WoolschlagerAir quality is of great concern to the public. Airborne pollutants, such as carbon monoxide (CO), carbon dioxide (CO2) and Particulate Matter (PM), negatively impact people’s living conditions. In particular, vehicular exhaust is a major source of these pollutants. Extensive previous research has contributed to modeling traffic pollutant emission. Popular approaches include computational simulation-based methods, which have been dominant in … …American Journal of Environmental Sciences, Vol. 12, Issue 3 · 13 May 2016 · 7,439 accessesView PDFCite
Research ArticleOpen accessIn the abstractCONSTRUCTION OF GENERAL SUBSUMPTIVE SOLUTIONS OF BOOLEAN EQUATIONS VIA COMPLETE-SUM DERIVATIONAli Muhammad Ali Rushdi, Hussain Mobarak AlbarakatiBoolean-equation solving permeates many diverse areas of modern science. To solve a system of Boolean equations, one usually combines them into an equivalent single Boolean equation {f(X) = 0} whose set of solutions is exactly the same as that of the original system of equations. One of the general classes of solutions for Boolean equations is the subsumptive general solution, … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 13 Mar 2014 · 7,112 accessesView PDFCite