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Research ArticleOpen accessIn the keywordsAnalysis of Resistance to Human Immunodeficiency Virus Protease Inhibitors Using Molecular Mechanics and Machine Learning StrategiesA. Harishchander, D. Alex Anand, Sanjib SenapatiProblem statement: Drug resistance is the most important factor, which influences the failure of current HIV therapies. So, the ability to predict the drug resistance of HIV-1 protease mutants will be useful in developing more effective and longer lasting treatment regimens. Approach: Drug resistance of HIV-1 protease is predicted with two current protease inhibitors (Indinavir and Saquinavir). The problem was … …Current Research in Medicine, Vol. 1, Issue 2 · 31 Oct 2010 · 7,204 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Novel Linear-Polynomial Kernel to Construct Support Vector Machines for Speech RecognitionBalwant A. Sonkamble, D.D. DoyeProblem statement: To accept the inputs as spoken word utterances uttered by various speakers, recognize the corresponding spoken words and initiate action pertaining to that word. Approach: A novel Linear-Polynomial (LP) Kernel function was used to construct support vector machines to classify the spoken word utterances. The support vector machines were constructed using various kernel functions. The use of well … …Journal of Computer Science, Vol. 7, Issue 7 · 28 Jun 2011 · 7,009 accessesView PDFCite
Research ArticleOpen accessIn the abstractAssessing Supervised Classification Algorithms for Mangrove Detection and Differentiation from Other Forest Types in Paiton District, Probolinggo RegencyKaruniawan Puji Wicaksono, Fathor Rohman, Yasushi MitsudaRemote sensing provides an effective approach for monitoring forest cover dynamics, yet distinguishing mangroves from other forest types remains challenging in heterogeneous coastal landscapes. This study compares six supervised classification algorithms: Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Mixture Discriminant Analysis (MDA), Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) for mangrove detection in Paiton, … …OnLine Journal of Biological Sciences, Vol. 26, Issue 3 · 1 Sep 2026 · 844 accessesView PDFCite
Research ArticleOpen accessIn the abstractImplementing a Hybrid VMD–BiTCN–BiGRU Architecture With Intelligent Optimization for Agricultural Commodity Price Prognostication in Gujarat MarketsJignesh Hirapara, Ratnesh Kumar Namdeo, Ankit Kumar Dubey et al.In the agricultural sector, the prices of pulses require adequate forecasting to plan farming activities, store and market, and guide policy-making. However, the pulse price series is highly volatile, seasonal, nonstationary, and nonlinear, and thus conventional linear time series models are not necessarily very effective. In the suggested framework, the raw price data series is decomposed using Variational Mode Decomposition … …Journal of Computer Science, Vol. 22, Issue 7 · 1 Aug 2026 · 1,021 accessesView PDFCite
Research ArticleOpen accessIn the abstractLeveraging Machine Learning Techniques to Analyze Consumer Mindset Metrics Embedded in Arabic Dialect Texts Across Social Media PlatformsSafa Khaled Al Sarairah, Mohd Heikal Husin, Noor Farizah IbrahimAs social media grows in popularity around the world, analyzing Arabic texts on these platforms can provide important insights into consumer attitudes and behavior. The complexity and diversity of Arabic and its dialects, however, make it a challenging task. This research raises these challenges by using and comparing the performance of Machine Learning (ML) models for classifying social media comments … …Journal of Computer Science, Vol. 22, Issue 5 · 5 Jun 2026 · 1,301 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluation of Machine Learning Models to Predict Student Academic Performance Using Structured Educational DataHardik Ishwarbhai Patel, Dharmendra PatelThis study analyses the use of machine learning for predicting the academic performance of students using their academic information from the institution, combined with socio-economic information that comes from outside sources. The collection of information is done using structured questionnaires as well as through data extraction from the Student Information System (SIS). To increase the reliability of models built, a … …Journal of Computer Science, Vol. 22, Issue 5 · 26 May 2026 · 1,419 accessesView PDFCite
Research ArticleOpen accessIn the abstractCrop Yield Prediction in Niger Using Machine Learning TechniquesMahaman Lawali Inoussa Garba, Naroua Harouna, Chaibou Kadri et al.Agriculture is the most impactful sector on Niger's economic growth. Stresses related to climate change and the environment are leading to a continuous decline in crop yield. Accurate crop yield forecasting is of paramount importance for farmers, government, policy makers, and other stakeholders to make most appropriate decisions regarding resource allocation and food security. This study examines the power of … …Journal of Computer Science, Vol. 21, Issue 8 · 16 Sep 2025 · 5,792 accessesView PDFCite
Research ArticleOpen accessIn the abstractTwitter Sentiment Analysis Using Machine Learning and Deep Learning TechniquesSafa Khalid Al Sarayrah, Noor Mahmoud Alkudah, Hesham Yousef Al-kharabshehThis research investigates the use of Machine Learning (ML) and Deep Learning, including BiLSTM approaches, for Sentiment Analysis (SA) of consumer reviews on social media sites. Businesses are increasingly depending on online reviews to determine customer satisfaction due to social media's explosive growth. We used three classification models, the assessment of these attitudes uses Naive Bayes (NB), Support Vector Machine … …Journal of Computer Science, Vol. 21, Issue 8 · 1 Sep 2025 · 6,813 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligent Intrusion Detection System Using RF, SVM, and DT: A Comparison-Based KDD Data SetWalaa Hassan Elashmawi, Alaa Sheta, Ahmad Al-QeremThe rapid growth of technology has brought about many advantages, but has also made networks more susceptible to security threats. Intrusion Detection Systems (IDS) play a vital role in protecting computer networks against malicious activities. Given the dynamic and constantly evolving nature of cyber threats, these systems must continuously adapt to maintain their effectiveness. Machine Learning (ML) methods have gained … …Journal of Computer Science, Vol. 21, Issue 8 · 28 Aug 2025 · 5,818 accessesView PDFCite
Research ArticleOpen accessIn the abstractBeatbox Classification to Distinguish User Experiences Using Machine Learning ApproachesJason Martanto, Iman Herwidiana KartowisastroResearch regarding beatbox classification has generated a relatively significant growth in the past decade. Although the differences between contributors’ expertise within a vocal percussion dataset have been mentioned in previous works, the impact of those discrepancies has not been thoroughly investigated. In this study, the authors explore performances of machine learning algorithms for beatbox classification, with an emphasis on prior … …Journal of Computer Science, Vol. 21, Issue 4 · 18 Mar 2025 · 5,208 accessesView PDFCite