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75 articles for “Data preprocessing”
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Research ArticleOpen accessIn the abstractStrengthening Image Security with Unimodular Hill Cipher and Advanced Encryption StandardSamsul Arifin, Dwi Wijonarko, Monica Mayeni Manurung et al.Digital data security has become increasingly important with the growth of digital image usage, which often contains sensitive information. This study aims to enhance the security of digital images by combining Unimodular Hill Cipher (UHC) and Advanced Encryption Standard (AES) methods. UHC, a matrix-based symmetric encryption algorithm, is used for image matrix encryption, while AES provides an additional layer of … …Journal of Computer Science, Vol. 21, Issue 5 · 22 Apr 2025 · 5,419 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Prediction Model for Predictive Maintenance Based on K-Nearest Neighbor Method for Air Navigation Equipment FacilitiesRachmat Hidayat, Ditdit Nugeraha UtamaThe aging of air navigation facilities leads to a decline in equipment performance and reliability, posing significant challenges for aviation organizations in the large-scale replacement of outdated systems, as well as in managing budgets and resources. To address these issues, a performance prediction model for equipment was developed using the K-Nearest Neighbor (KNN) method, aimed at enhancing maintenance planning and … …Journal of Computer Science, Vol. 21, Issue 4 · 4 Mar 2025 · 5,661 accessesView PDFCite
Research ArticleOpen accessIn the abstractTransforming Retinal Diagnostics: Advanced Detection of Diabetic Retinopathy Using Vision Transformers and Capsule NetworksVishal Sharma, Rishu, Vinay Kukreja et al.Diabetic Retinopathy (DR), nowadays is one of the leading causes of blindness worldwide, it is a severe complication of diabetes mellitus that affects the retina blood vessels. Accurate diagnosis depends on early detection of DR. The study aims to develop a hybrid model that is the combination of a Vision Transformer and Capsule Network (ViT-CapsNet) to classify the DR at … …Journal of Computer Science, Vol. 21, Issue 2 · 14 Jan 2025 · 6,765 accessesView PDFCite
Research ArticleOpen accessIn the abstractA 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 abstractNon-Hodgkin Lymphoma Risk Grading Through the Pathological Data by Using the Optimized Convolutional Lymphnet ModelSivaranjini Nagarajan, Gomathi MuthuswamyDiagnosing Non-Hodgkin Lymphoma (NHL) is difficult and often requires specialised training and expertise as well as extensive morphological investigation and, in certain cases, costly immunohistological and genetic techniques. Computational approaches enabling morphological-based decision making are necessary for bridging the existing gaps. Histopathological images can be accurately classified using deep learning approaches, however data on NHL subtyping is limited. However, there … …Journal of Computer Science, Vol. 20, Issue 5 · 28 Feb 2024 · 4,551 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Efficient Cluster Head Selection in IoV-Enabled VANETs Using a Federated Diffusion Convolutional Recurrent Neural Networks FrameworkP Subhash, Madana Srinivas, A. Ranjith et al.The IoV enables the formation of VANETs that require a strong selection of CHs for effective communication within high-velocity changing traffic scenarios. Existing approaches often face issues related to scalability, privacy, and adaptability. To meet the aforementioned urgent needs, we design a decentralized scheme for intelligent CH selection based on Federated Learning with Diffusion Convolutional Recurrent Neural Networks (DCRNNs). According … …Journal of Computer Science, Vol. 22, Issue 10 · 1 Oct 2026 · 612 accessesView PDFCite
Research ArticleOpen accessIn the abstractChronic Lung Disease Identification in Chest CT Scans Through Hybrid Deep Transfer Learning FrameworkGarima Jain, Amit Kumar Goel, Rahul KumarAccurate and timely diagnosis is essential for successful treatment of chronic pulmonary conditions, particularly lung tumours. To capture more complicated pathological characteristics, diagnostic algorithms based on current data sets are restricted to using older databases and single branch systems. This research introduces a new solution: A hybrid deep learning model applied to a recently released quantitative database of CT scans … …Journal of Computer Science, Vol. 22, Issue 8 · 9 Sep 2026 · 657 accessesView PDFCite
Review ArticleOpen accessIn the abstractImproving Classification and Clustering Accuracy of Palembang Duku Fruit Quality via CNN-K-Means IntegrationHenny Hartono, Francka Sakti Lee, Herlina Herlina et al.Duku Palembang (Lansium domesticum Corr.) is a leading commodity from South Sumatra with high economic value. The quality assessment process for duku has traditionally relied on manual visual inspection, which is subjective, time-consuming, and inconsistent, especially at large production scales. This study proposes an integrative framework combining Convolutional Neural Network (CNN) and K-Means Clustering to improve the accuracy of classification … …OnLine Journal of Biological Sciences, Vol. 26, Issue 2 · 8 May 2026 · 1,479 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intelligent Hybrid Machine Learning Model for Paddy Disease DetectionS. Hrushikesava Raju, S. Adinarayna, U. Sesadri et al.Most countries rely on paddy/rice as a preferred staple crop due to its desirable agronomic characteristics. However, during the growth cycle, undetected or delayed identification of diseases can significantly reduce crop yield. To address this, machine learning approaches are increasingly employed for early-stage disease detection. Traditional Recurrent Neural Networks (RNNs), while useful for sequential data, suffer from limitations such as … …Journal of Computer Science, Vol. 22, Issue 4 · 29 Apr 2026 · 1,754 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Social Media Face Emotion Recognition Using a Fuzzy ELM ApproachShuchi Gupta, K. Viswanath, S. Gokul Pran et al.Our computational tools for searching, exploring, and sharing personal photographs are falling behind the rapid pace at which these images are being captured digitally. The use of automatic face recognition to categorize images according to the people in them is one potential solution. Accurate recognition on the Internet scale, however, presents the seemingly insurmountable challenge of picking out specific people … …Journal of Computer Science, Vol. 22, Issue 3 · 20 Mar 2026 · 1,991 accessesView PDFCite