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Research ArticleOpen accessIn the keywordsReliability of Axially Loaded Fiber-Reinforced-Polymer Confined Reinforced Concrete Circular ColumnsVenkatarman Nagaradjane, Pulipaka Narasimharao Raghunath, Kannan SugunaMonte-Carlo simulation based procedure was applied for assessing the reliability of Fiber Reinforced Polymer (FRP) confined reinforced concrete columns. Assessment of reliability provides a quantitative measure of effectiveness of repair. Problem Statement: The procedure presented in the paper could be used for assessing the reliability of reinforced concrete columns before and after the application of FRP wrap, thus helping to … …American Journal of Engineering and Applied Sciences, Vol. 2, Issue 1 · 31 Jan 2009 · 7,974 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Approach for Differentiating AI-Generated and Real Images Using Gabor and Color Layout Filters (GF and CLF)G. Ayyappan, A. Thankaraj, S. Surendran et al.The emergence of generative AI images has profoundly upended the art world. Distinguishing AI-generated images from human-created artwork is increasingly challenging. If this issue remains unresolved, dishonest individuals may exploit those who are willing to pay more for original artwork and businesses whose stated policies exclude AI graphics. There are a number of methods for differentiating AI photos from human … …Journal of Computer Science, Vol. 22, Issue 2 · 3 Mar 2026 · 1,751 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis on Prediction of Chronic KidneyDisease by various Machine Learning ModelsNikhil Verma, Tripti Sharma, Bobbinpreet Kaur, Ayush DograChronic Kidney Disease (CKD) is a prevalent global healthconcern, which is affecting a number of people in the whole world. Earlydetection & precise checking of CKD are really important for essentialsupervision & intervention to prevent disease progression and associatedcomplications. Machine learning (ML) models have emerged as favourabletools for CKD detection due to their ability to analyse complex data patternsand provide … …Journal of Computer Science, Vol. 21, Issue 6 · 24 May 2025 · 5,939 accessesView PDFCite
Research ArticleOpen accessIn the abstractExploring Data Augmentation for Gender-Based Hate Speech DetectionMuhammad Amien Ibrahim, Samsul Arifin, Eko Setyo PurwantoSocial media moderation is a crucial component to establish healthy online communities and ensuring online safety from hate speech and offensive language. In many cases, hate speech may be targeted at specific gender which could be expressed in many different languages on social media platforms such as Indonesian Twitter. However, difficulties such as data scarcity and the imbalanced gender-based hate … …Journal of Computer Science, Vol. 19, Issue 10 · 29 Sep 2023 · 5,550 accessesView PDFCite
Research ArticleOpen accessIn the abstractUsing Background Knowledge and Random Sampling in Genetic Programming: A Case Study in Learning Boolean Parity FunctionsLappoon R. TangThe Boolean even-N-parity function returns T (i.e., true) if an even number of its Boolean arguments for N arguments are T and otherwise returns NIL (i.e., false). Learning Boolean even-N-parity functions has been recognized as a difficult problem for evolutionary computation (such as genetic programming) especially when N is large (e.g., 20+). A number of approaches have been proposed for … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 5,481 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligent Digital Signal Modulation Recognition using Machine LearningMudhafar Haji Mala Abd, Sadegh AminifarInrecent years, modulation type recognition has received a lot of attentionacross the board. There are several methods to detect modulation types, butthere are only a few effective methods to handle signals with a higher level ofnoise. This study introduces an approach to verify the ability of differentmachine learning algorithms to automatically manage noise in detecting digitalmodulations. This research examines two … …Journal of Computer Science, Vol. 18, Issue 10 · 26 Sep 2022 · 6,095 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting the Remaining Lifetime of Distribution Transformers using Machine LearningNtiminity Abontakoyah Enoch, Puguo Gbene George, Justice AningDistribution Transformer is a crucial element in deciding the power flow in large power systems. Their better performance implies high power system efficiency and enhanced power transfer capability. However, various Distribution Transformer failures in the recent past lead to power supply disturbance and have acquired much attention from the electrical intellectuals. It is of considerable significance to accurately get the … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 4 · 1 Jan 2021 · 6,644 accessesView PDFCite
Research ArticleOpen accessIn the abstractRandomness Analysis on Lightweight Block Cipher, PRESENTIsma Norshahila Binti Mohammad Shah, Eddie Shahril Bin IsmailLightweight cryptography is an area of current research conducted by academicians and cryptographic experts to ensure the security of data in limited-resource devices such as RFID tags, medical and health care devices and sensor networks. One of the lightweight algorithms built is the PRESENT algorithm. To this day, PRESENT has been a reference for lightweight block cipher algorithms and is … …Journal of Computer Science, Vol. 16, Issue 11 · 26 Nov 2020 · 6,889 accessesView PDFCite
Research ArticleOpen accessIn the abstractMulti-Satellite Custody of Moving Ground TargetsDavid SchusterMaintaining persistent custody of ground targets from Low Earth Orbit (LEO) is a key challenge in space-based surveillance and reconnaissance. Traditional rule-based tasking strategies struggle with scalability as the number of assets and targets grows. In this paper, we present a centralized Reinforcement Learning (RL) approach using Proximal Policy Optimization (PPO) to coordinate four LEO satellites tasked with tracking two … …Journal of Computer Science, Vol. 22, Issue 3 · 25 Mar 2026 · 1,575 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Test on the Multivariate Behrens–Fisher Problem in High–Dimensional Data by Block Covariance EstimationParanut Sukcharoen, Samruam ChongcharoenIn this paper, we proposed a new testing statistic for testing the equality of mean vectors from two multivariate normal populations when the covariance matrices are unknown and unequal in high–dimensional data. A new test is proposed based on the idea of keeping more information from the sample covariance matrices as much as possible. A proposed test is invariant under … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 2 Apr 2019 · 7,369 accessesView PDFCite