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Research ArticleOpen accessIn the abstractComparative Study: Algorithms for Short Message Service ClassificationEvaristus Didik Madyatmadja, Aldi, Fiona Fheren et al.This research aims to classify Short Message Service (SMS) data by applying classification models that have studied SMS data to classify SMS data into SMS spam and SMS ham. The classification model is made from data mining algorithms: Naive Bayes and support vector machine. Before implementing the two algorithms, the SMS data will go through a text preprocessing stage, including … …Journal of Computer Science, Vol. 19, Issue 11 · 29 Sep 2023 · 4,992 accessesView PDFCite
Research ArticleOpen accessIn the abstractDynamic Relationship Between Rupee-Dollar Exchange Rate and Major Economic IndicatorsAbhinandan Kulal, Deepak Kallige Vishwanath, Sanath Kumar KanthilaIt is very likely that dollar to rupee exchange rate has an influence on the major economic indicators of India like the GDP of India, the NIFTY 50 index, gold prices in India, import prices in India, and crude oil prices in India. The quarterly time series data of the seven variables have been used. The time considered for the … …American Journal of Economics and Business Administration, Vol. 15, Issue 1 · 17 Aug 2023 · 6,448 accessesView PDFCite
Research ArticleOpen accessIn the abstractToxicity of Dinoflagellate (Gonyaulax verior) from Makassar Strait Waters on Medaka Fish (Oryzias javanicus) Embryo DevelopmentNita Rukminasari, Khusnul Yaqin, Jamaluddin Fitrah AlamThis study investigates the toxic effects of the dinoflagellate Gonyaulax verior on the embryonic development of medaka fish (Oryzias javanicus) sourced from four distinct aquatic environments in the Makassar Strait. Given the increasing presence of harmful algal blooms in marine ecosystems, understanding the impact of toxic dinoflagellates is crucial for assessing risks to fish populations. Embryos were exposed to varying … …OnLine Journal of Biological Sciences, Vol. 25, Issue 3 · 20 Nov 2025 · 2,123 accessesView PDFCite
Research ArticleOpen accessIn the abstractUnveiling the Performance: A Comparative Study of HMAC and RSA Encryption on SHA-512Louis Leonardo, RojaliThe study evaluates critical operations including token signing, verification, and decoding, as well as data transfer efficiency, utilizing the jsonwebtoken library. By benchmarking these operations, we provide insights into the trade-offs between symmetric (HMAC) and asymmetric (RSA) encryption methods, highlighting their impact on performance and security. The results serve as a guideline for developers to make informed decisions when choosing … …Journal of Computer Science, Vol. 21, Issue 12 · 22 Jan 2026 · 1,788 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 · 5,207 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Ensemble of Gaussian Mixture Model and Support Vector Machines for Network Intrusion DetectionOlujimi Daniel Alao, Sheriff Alimi, Shade Oluwakemi Kuyoro et al.NetworkIntrusion Detection Systems (NIDS) can protect computer networks and computersystems by detecting abnormal network packets and taking agreed action plans,such as notifying an administrator or rejecting the network packets. In this study,the aim is the implementation of NIDS with improved performance using anensemble of Support Vector Machines (SVMs) and the Gaussian Mixture Model(GMM). Four SVMs with Radial Basis Function (RBF), … …Journal of Computer Science, Vol. 18, Issue 9 · 21 Sep 2022 · 6,114 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassify Breast Cancer Patients using Hybrid Data-Mining TechniquesFaris E. Mohammed, Nadia Smaoui Zghal, Dalinda Ben Aissa, Mostafa Mahmoud El-GayarAccording to the World Health Organization (WHO), breast cancer is a disease that leads to death, especially for women who have neglected or ignored the risk factors. Doctors can classify patients according to clinical information, famous disease symptoms, or similar cases. But, some cases are difficult to detect early or diagnose accurately. Therefore, the most important challenge faced by researchers … …Journal of Computer Science, Vol. 18, Issue 4 · 12 May 2022 · 6,526 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparative Study on the Reproductive Performance of South African Indigenous Sheep Breeds Following Oestrus SynchronizationJabulani Nkululeko Ngcobo, Tshimangadzo Lucky Nedambale, Tlou Caswell Chokoe, Fhulufhelo Vincent RamukhithiThe aim of the study was to compare the effect of age and live body weight on the oestrus response, duration, pregnancy rate and lambing rate among South African indigenous sheep breeds (Zulu sheep = 36, Bapedi sheep = 26, Damara sheep = 10 and Namaqua Afrikaner sheep = 9). Control Intravaginal Drug Release Dispensers (CIDR’s) were inserted into the … …American Journal of Animal and Veterinary Sciences, Vol. 17, Issue 1 · 14 Jan 2022 · 7,862 accessesView PDFCite
Research ArticleOpen accessIn the abstractUncertainty-Aware Ensemble Models for Improved Defect Detection in Noisy DataMadhavi Perla, Gadi Lava Raju, A Radha Krishna et al.Software defect prediction plays a crucial role in ensuring software quality and reliability, especially as modern systems become more complex and data rich. This study introduces an uncertainty-aware ensemble learning framework aimed at improving defect classification performance in noisy and imbalanced datasets, particularly those from the PROMISE and NASA KC1 repositories. The proposed model integrates multiple classifiers in a multi-learner … …Journal of Computer Science, Vol. 22, Issue 4 · 27 Apr 2026 · 1,542 accessesView PDFCite
Research ArticleOpen accessIn the abstractIoT-Integrated CNN Deep Learning for Automated Breast Cancer Detection and DiagnosisYamini Kalva, R. Ganesh Babu, Sindhu V. et al.Breast cancer continues to be a primary cause of death in women, requiring prompt and accurate diagnosis to enhance treatment results. Traditional diagnostic techniques depend on manual assessment, which leads to possible misclassification, significant inter-observer variability, and delays in decision-making. Current deep learning models, including CNNs, frequently experience feature loss, gradient declining and restricted adaptability to real-time data. To overcome … …Journal of Computer Science, Vol. 22, Issue 4 · 30 Mar 2026 · 1,753 accessesView PDFCite