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Research ArticleOpen accessIn the abstractA Context-Aware Temporal Convolutional Network for Water Replacement Prediction in Catfish Biofloc Ponds With Imbalanced Event HandlingYaddarabullah, Inanpi Hidayati Sumiasih, Mutiara Dewi PuspitawatiWater replacement is a biologically critical yet under-automated decision in biofloc-based aquaculture systems. Mistimed actions can destabilize microbial ecosystems, elevate fish mortality, and compromise sustainability through excessive water usage. Traditional rule-based heuristics often fail to account for the nonlinear and multiscale dynamics of pond environments. To address this, we propose a Context-Aware Temporal Convolutional Network (CA-TCN), a rare-event classification framework … …Journal of Computer Science, Vol. 22, Issue 3 · 5 Mar 2026 · 1,664 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Deep Learning Approach for Tomato Leaf Disease Detection Using Optimized CNN ArchitectureSunil K. Vithalani, Vipul K. DabhiEarly disease detection in plants is essential for sustaining agricultural yield and guaranteeing food security. A comparative analysis of transformer-based and convolutional based deep learning models for classifying tomato leaf diseases is presented. Specifically, it examines the performance of a Vision Transformer (ViT), tested both in a form of scratch training setup and through transfer learning, against well-known CNN architectures … …Journal of Computer Science, Vol. 22, Issue 1 · 7 Feb 2026 · 3,917 accessesView PDFCite
Review ArticleOpen accessIn the abstractBibliometric Analysis of Missing Value Imputation (MVI) Research Using Python and VOSviewer: Trends and Future DirectionsSamsul Arifin, Muhammad Faisal, Edwin Kristianto Sijabat et al.Incomplete data is a pervasive issue in data science, posing significant challenges for statistical analysis and machine learning applications. Missing Value Imputation (MVI) has thus emerged as a critical area of research aimed at mitigating data quality issues and improving decision-making accuracy. This study presents a comprehensive bibliometric analysis of MVI research using Scopus-indexed publications from 2000 to 2024. The … …Journal of Computer Science, Vol. 21, Issue 12 · 20 Jan 2026 · 1,961 accessesView PDFCite
Research ArticleOpen accessIn the abstractRF-CNNS: Thin Deep Learning Networks For Accelerating Traffic Signs RecognitionBtissam Bousarhane, Driss BouzidiRoad scene analysis is a wide domain of research that aims to ameliorate the environmental perception in intelligent transportation systems, including autonomous vehicles and advanced driver-assistance systems. It also plays a crucial role in road safety improvement, by contributing to the reduction of traffic accidents' rate. Ensuring an efficient recognition of traffic signs contributes enormously to making cars safer, which … …Journal of Computer Science, Vol. 19, Issue 10 · 18 Sep 2023 · 5,335 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting of Multistep Multivariate Financial Data Through GSO Algorithm Infused Vanilla LSTM ModelNikhitha Pai, Ilango Velchamy, Nithya B RameshPredicting time series in the financial domain requires using models that can do sequence processing tasks. One such model is the LSTM model which belongs to the family of deep learning networks. The performance measure of LSTM in a regression task is to bring down the error in the predicted values. In this study, a novel fused LSTM model integrating … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 6,074 accessesView PDFCite
Research ArticleOpen accessIn the abstractFunctional Non-Inferiority Hypothesis Testing for Longitudinal DataArsène Brunelle Sandie, Anthony Wanjoya, Jules Brice Tchatchueng-MbouguaThe study pattern of non-inferiority trials is increasingly used to show the non-inferiority of new health intervention. Although in such studies the data are longitudinally collected (data held over a period of time), the conclusion of these non-inferiority trials is based on data observed at a specific time during the study period (usually at the end of the study period). … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 29 Aug 2019 · 6,933 accessesView PDFCite
Research ArticleOpen accessIn the abstractONCObc-ST: An Improved Clinical Reasoning Algorithm Based on Select and Test (ST) Algorithm for Diagnosing Breast CancerOlaide Nathaniel Oyelade, Sunday Adeyemi AdewuyiThe need for an accurate reasoning algorithm is usually necessitated by the sensitivity of domain of (medicine as example) application of such algorithms. Most reasoning algorithms for medical diagnosis are either limited by their techniques or accuracy and efficiency. Even the Select and Test (ST) algorithm which is considered a more approximate reasoning algorithm is also limited by its approach … …Current Research in Bioinformatics, Vol. 8, Issue 1 · 15 Apr 2019 · 7,162 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutomating Paddy Crop Disease Classification With Deep Learning ModelsShiva Shankar J, S. Palanivel, S. China VenkateswarluRice is a staple food crop for more than 10 countries. High consumption of rice demands better yield of crop. Timely disease diagnosis in paddy is fundamental to preventing yield losses and ensuring an adequate supply of rice for a rapidly rising worldwide population. Agriculture and modern farming is one of the fields where IoT and automation can have a … …Journal of Computer Science, Vol. 21, Issue 8 · 1 Sep 2025 · 5,696 accessesView PDFCite
Research ArticleOpen accessIn the abstractMultivalent Optimizer-Based Hybrid Genetic Algorithm for Task Scheduling in Cloud ApplicationsMeena Malik, Bhavna Gupta, Chander Prabha et al.Cloud computing platforms provide on-demand online services without the need for direct user management. Generally, big clouds distribute functions over multiple data centers at distant locations. The major facilities offered by clouds are based upon virtual machines which provide benefits in terms of low scheduling cost, improved accessibility and availability of cloud services. While transferring the tasks for effective scheduling, … …Journal of Computer Science, Vol. 21, Issue 2 · 31 Dec 2024 · 4,900 accessesView PDFCite
Research ArticleOpen accessIn the abstractImage Binarization Using Block Boundary Pixels MeanO. Imocha Singh, T. Romen SinghInput image pixels classification into two intensities like black and white as foreground and background respectively refers to image binarization. Binarization with a local threshold value is termed as adaptive image binarization. Locally adaptive thresholding techniques are local pixels dependent process. Local environment dependent process is normally time consuming one and hence its computational time complexity is also local region … …Journal of Computer Science, Vol. 13, Issue 11 · 28 Nov 2017 · 7,811 accessesView PDFCite