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 abstractComplex SQL-NoSQL Query Translation for Data Lake ManagementNurhadi, Rabiah Abdul Kadir, Ely Salwana Mat SurinA data lake refers to an extremely large data resource or repository. Data lakes store large amounts of data and use advanced analytics to pair data from multiple sources with different types of structured, semi-structured, and unstructured information. NoSQL databases such as Mongodb, Redis, Neo4j, and Cassandra are nontabular and they store data differently rather than use relational tables. NoSQL … …Journal of Computer Science, Vol. 18, Issue 12 · 19 Dec 2022 · 9,277 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptive Synthetic Oversampling Algorithm for Handling Class Imbalance in Multi-Class Data Stream ClassificationPriya S., Annie UthraConcept drift and class imbalanced data are major challenging processes involved in modern streaming data classification. Particularly, when integrated with difficult factors like the existence of noise, overlapping class distribution, concept drift, and data imbalance can considerably affect the classifier results. In addition, various challenges affect the performance of the existing oversampling schemes such as SMOTE and its derivatives. Regardless … …Journal of Computer Science, Vol. 18, Issue 7 · 26 Jul 2022 · 5,809 accessesView PDFCite
Research ArticleOpen accessIn the abstractSoft Marking Scheme of SVM Hierarchical Classifiers for Attack ClassificationAzizi Abdullah, Warhamni Jani@MokhtarClassification is a predictive modelling problem that involves assigning a class label to an instance correctly. There exist several strategies in machine learning to deal with the multi-class classification problems for attack detection. One of the popular strategies is the one-vs-one that decomposes the multi-class problem into multiple binary ones. The approach has been applied in many popular supervised learning … …Journal of Computer Science, Vol. 17, Issue 9 · 27 Sep 2021 · 6,000 accessesView PDFCite
EditorialOpen accessIn the abstractThe Timeless Contribution of Rootstocks towards Successful Horticultural Farming: From Ancient Times to the Climate Change EraIoannis E. PapadakisGrafting is a horticultural practice by which living vegetative plant organs (root, stem and/or buds) of either the same genotype or, usually, different genotypes belonging to the same species, genus, subfamily and/or family, are tightly connected to each other to form a double-compound plant. In fact, it is a method of asexual (clonal-vegetative) propagation of plants. The basal part of … …American Journal of Agricultural and Biological Sciences, Vol. 11, Issue 4 · 16 Dec 2016 · 9,521 accessesView PDFCite
Research ArticleOpen accessIn the abstractCLUSTER BASED DUPLICATE DETECTIONA. Venkatesh Kumar, S. VengataasalamWe propose a clustering technique for entropy based text dis-similarity calculation of de-duplication system. Improve the quality of grouping; in this study we propose a Multi-Level Group Detection (MLGD) algorithm which produces a most accurate group with most closely related object using Alternative Decision Tree (ADT) technique. Our propose a two new algorithm; first one is Multi-Level Group Detection (MLGD) … …Journal of Computer Science, Vol. 9, Issue 11 · 28 Sep 2013 · 7,035 accessesView PDFCite
Research ArticleOpen accessIn the abstractSteel Plates Faults Diagnosis with Data Mining ModelsMahmoud Fakhr, Alaa M. ElsayadProblem statement: Over the last two decades, Fault Diagnosis (FD) has a major importance to enhance the quality of manufacturing and to lessen the cost of product testing. Actually, quick and correct FD system helps to keep away from product quality problems and facilitates precautionary maintenance. FD may be considered as a pattern recognition problem. It has been gaining more … …Journal of Computer Science, Vol. 8, Issue 4 · 31 Jan 2012 · 11,378 accessesView PDFCite
Research ArticleOpen accessIn the abstractThree Dimensional Multidirectional Geographical IP Traceback: Direction Ratio Sampling AlgorithmA. Rajiv Kannan, K. Duraiswamy, K. SangeethaProblem statement: An important and challenging problem is that of tracing DOS/DDOS attack source. IP traceback is the process of identifying the actual source(s) of attack packets, So that the attackers can be held accountable as also in mitigating them, either by isolating the attack sources or by filtering packets for away from the victim. Several IP traceback schemes have … …Journal of Computer Science, Vol. 5, Issue 2 · 28 Feb 2009 · 7,233 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