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57 articles for “Synthetic Data”
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Research ArticleOpen accessEvery word in the titleAdaptive 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 · 5,814 accessesView PDFCite
Research ArticleOpen accessIn the keywordsRadial Basis Function Neural Networks Towards Electronic Trust QuantificationSmitha Zacaria, Tiny du ToitTrust is a broad term applicable in various contexts. Trust between electronic entities is complex to quantify, particularly in intricate networks. Traditional trust algorithms rely on historical trust values, requiring storage and access to past transaction details. Contextual variations further complicate trust calculation. Challenges in calculating trust include heightened computational complexities, managing information storage, and securing access to extensive datasets … …Journal of Computer Science, Vol. 20, Issue 11 · 26 Sep 2024 · 4,801 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Comparative Analysis of Smote and CSSF Techniques for Diabetes Classification Using Imbalanced DataBashar Hamad Aubaidan, Rabiah Abdul Kadir, Mohamad Taha IjabDiabetes, a prevalent chronic metabolic disorder, poses a significant burden on healthcare systems worldwide. Accurate and timely diagnosis is crucial for effective management and complication prevention. Machine learning presents a promising solution but often faces challenges due to class imbalance within datasets, particularly the underrepresentation of diabetic cases. To address this issue, we introduce Cluster-based Synthetic Sample Filtering (CSSF), a … …Journal of Computer Science, Vol. 20, Issue 9 · 22 Jul 2024 · 5,005 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSuVashantor: English to Bangla Machine Translation SystemsMahjabeen Akter, M. Shahidur Rahman, Muhammed Zafar Iqbal, Mohammad Reza SelimThis paper presents the system description of Machine Translation (MT) systems for English-Bangla language pair. Our goal was to create two benchmark MT systems that produce a better quality translation and comparatively higher evaluation score than existing MT systems for English to Bangla. In our experiments, we implemented two baseline MT systems using both statistical and neural methods for the … …Journal of Computer Science, Vol. 16, Issue 8 · 16 Aug 2020 · 7,451 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA New Method of Generating Index Label for Dynamic XML DataJayanthi Paramasivam, Tamilarasi AngamuthuProblem statement: The processing of the XML queries needs an efficient indexing method. The index generation includes the labeling of the nodes. But for the dynamic data, when the changes are made, the re-computation of the labeling is needed. Approach: Based on the structural indexing used the performance of the query processing system will be affected. The dynamic XML document … …Journal of Computer Science, Vol. 7, Issue 3 · 9 Mar 2011 · 6,840 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPrediction of Physicochemical Parameters in a Rainwater Harvesting and Treatment System Modeled Using the Yahtun Algorithm in Native Communities of Northern PeruEli Morales-Rojas, Edwin Adolfo Díaz Ortiz, José Emmanuel Cruz de La Cruz et al.The inhabitants of the native communities of northern Peru do not have drinking water systems, generating serious health impacts. In this sense, rainwater harvesting systems have become an alternative for these areas. Therefore, the objective of this study was to predict the physicochemical parameters in a rainwater collection and treatment system, modeled by means of a novel “Yahtun” algorithm. The … …OnLine Journal of Biological Sciences, Vol. 25, Issue 1 · 13 Feb 2025 · 5,158 accessesView PDFCite
Research ArticleOpen accessIn the abstractBridging Innovation and Access: Randomized, Single-Dose, Open-Label, Parallel-Group Bioequivalence Study of Generic and Innovator Injection Semaglutide in IndiaMayur Madhav Mayabhate, Nitin Kapure, Akhilesh Sharma, Radhakrishna VaddemSemaglutide, a long-acting Glucagon-Like Peptide-1 (GLP-1) receptor agonist, is effective in improving glycemic control, reducing body weight, and lowering cardiovascular risk in Type 2 Diabetes Mellitus (T2DM). Limited accessibility of the innovator formulation underscores the need for bioequivalent generic alternatives. To assess the pharmacokinetic bioequivalence of a synthetic Semaglutide Injection (2 mg/1.5 mL) developed by Alkem Laboratories Ltd., India, compared … …American Journal of Pharmacology and Toxicology, Vol. 20, Issue 1 · 20 Apr 2026 · 2,637 accessesView PDFCite
Research ArticleOpen accessIn the abstractMoney Laundering Detection in Financial Institutions Using Machine LearningNoor Samer Masood, Rasha Hassan Sakr, Amal Abou EleneenThis research aims to develop a system based on machine learning techniques for the accurate detection and classification of money laundering transactions. This system utilizes real and synthetic financial data, including the IBM AML dataset and synthetic financial databases. The methodology included data collection and cleaning, feature extraction from transaction behavior, and training several classification algorithms, including Random Forest, Support … …Journal of Computer Science, Vol. 22, Issue 4 · 16 Apr 2026 · 2,333 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized Fractal Fusion Driven Deep Neural Network: An Efficient Hybrid Methodology for Disease Detection and Classification in Plant LeavesDeepkiran Munjal, Mrinal Pandey, Laxman SinghPlant diseases and pest attacks are among the major issues in agriculture, which have a great impact on crop growth and yield. Early and correct detection of these diseases is vital for effective management and keeping plant health at the desired level. This research proposes a new method for detection and classification of plant diseases, the Optimized Fractional Fusion Deep … …Journal of Computer Science, Vol. 21, Issue 12 · 8 Jan 2026 · 2,228 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing the CIC IoT Dataset 2023 for Improved Attack Detection through GANs Augmentation and Federated LearningShahad Alahmari, Noura AleisaThe escalating frequency and sophistication of cyber-attacks on Internet of Things (IoT) devices present a pressing challenge to cybersecurity. With IoT device connections projected to exceed 42 billion by 2025, the vulnerability of these devices to cyber-attacks has never been more evident. This paper investigates the integration of Machine Learning (ML) and data augmentation, specifically Generative Adversarial Networks (GAN) and … …Journal of Computer Science, Vol. 21, Issue 7 · 18 Jul 2025 · 9,122 accessesView PDFCite