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26 results for “k-Nearest Neighbors”
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Research ArticleOpen accessIn the abstractOptimized Feature Reduction Techniques for Enhanced Network Threat Detection in Wireless Sensor NetworksBikash Kalita, Satyajit SarmahThe security of Wireless Sensor Networks (WSNs) is currently seriously threatened by numerous threats. Consequently, a number of applications are offered to regulate data and information sharing along with the related security features that need to be maintained throughout data transfer. This study suggests an intelligent feature reduction methodology based on machine learning that uses Modified Principal Component Analysis (MPCA) … …Journal of Computer Science, Vol. 21, Issue 8 · 10 Oct 2025 · 2,290 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Indoor Asset Tracking: IoT Integration and Machine Learning Approaches for Optimized PerformanceRafiq Hamadamin Maulud, Sadegh Abdollah AminifarIndoor asset tracking entails the surveillance and governance of the position and movement of tangible assets within enclosed spaces, including warehouses, hospitals, and workplaces. Indoor asset tracking systems employ technologies such as Radio Frequency Identification (RFID), Bluetooth Low Energy (BLE), Wi-Fi, and UWB (Ultra-Wideband) to deliver real-time visibility and precise placement of goods. This research introduces indoor asset tracking with … …Journal of Computer Science, Vol. 21, Issue 7 · 7 Jul 2025 · 3,733 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimizing KNN for Face Recognition and Location Detection in Mobile Employee Attendance Systems Using Machine LearningPainem, Hari Soetanto, Achmad Solichin, Ibnu RamadhanEmployee attendance is critical to company operations, particularly for firms involved in ATM installations collaborating with banks. An effective attendance system enables bank vendors to verify the completion of ATM installations. The current attendance method employed by the company requires employees to send photos of themselves with the installed ATM, including the machine number and installation location. The company's admin … …Journal of Computer Science, Vol. 21, Issue 5 · 14 Apr 2025 · 5,989 accessesView PDFCite
Research ArticleOpen accessIn the abstractBig Data Framework for Predicting Infectious Diseases to Improve Healthcare by Discovering New Symptom PatternsAmal Mohamed Mounir, Mohamed Ibrahim Marie, Laila Abd-ElhamidThe utilization of big data in infectious disease control represents a captivating opportunity, as these novel data streams offer the potential to enhance the timeliness of preventive measures. Various healthcare providers in both the public and private sectors generate, store, and analyse extensive datasets to enhance the quality of services they deliver. Recently, the outbreak of the new coronavirus, COVID-19, … …Journal of Computer Science, Vol. 20, Issue 10 · 2 Aug 2024 · 4,915 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 · 4,998 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Multi-Split Cross-Strategy for Enhancing Machine Learning Algorithms Prediction Results with Data Generated by Conditional Generative Adversarial NetworkAbdelfattah Abassi, Brahim Bakkas et al.In this study, we present a Multi-Split Cross-Strategy (MSC-Strategy) designed to leverage synthetic tabular data generated by a Conditional Generative Adversarial Network (CGAN). Our study aims to investigate the potential of synthetic data in comparison to real-world data for improving machine learning predictive results. Firstly, we develop a CGAN architecture tailored to generate synthetic tabular data, trained on a comprehensive … …Journal of Computer Science, Vol. 20, Issue 7 · 9 Apr 2024 · 6,695 accessesView PDFCite
Research ArticleOpen accessIn the abstractMachine Learning Approaches for the Prediction of Gas Turbine TransientsArnaud Nguembang Fadja, Giuseppe Cota, Francesco Bertasi et al.Gas Turbine (GT) emergency shutdowns can lead to energy production interruption and may also reduce the lifespan of a turbine. In order to remain competitive in the market, it is necessary to improve the reliability and availability of GTs by developing predictive maintenance systems that are able to predict future conditions of GTs within a certain time. Predicting such situations … …Journal of Computer Science, Vol. 20, Issue 5 · 28 Feb 2024 · 7,660 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligent Digital Signal Modulation Recognition using Machine LearningMudhafar Haji Mala Abd, Sadegh AminifarInrecent years, modulation type recognition has received a lot of attentionacross the board. There are several methods to detect modulation types, butthere are only a few effective methods to handle signals with a higher level ofnoise. This study introduces an approach to verify the ability of differentmachine learning algorithms to automatically manage noise in detecting digitalmodulations. This research examines two … …Journal of Computer Science, Vol. 18, Issue 10 · 26 Sep 2022 · 6,095 accessesView PDFCite
Research ArticleOpen accessIn the abstractData Preparation in Machine Learning for Condition-based MaintenanceOns Masmoudi, Mehdi Jaoua, Amel Jaoua, Soumaya YacoutUsing Machine Learning (ML) prediction to achieve a successful, cost-effective, Condition-Based Maintenance (CBM) strategy has become very attractive in the context of Industry 4.0. In other fields, it is well known that in order to benefit from the prediction capability of ML algorithms, the data preparation phase must be well conducted. Thus, the objective of this paper is to investigate … …Journal of Computer Science, Vol. 17, Issue 6 · 4 Jun 2021 · 8,412 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of Data Mining Classifiers on Sunflower Edible Oil Bleaching Process: A Comprehensive Comparative AnalysisÖmer Nedim Kenger, Eren ÖzceylanSunflower oil is widely used as edible oil. It is commonly extracted by solvent extraction method from the sunflower seed. After extraction, crude sunflower oil is obtained. Crude sunflower oil has some undesirable impurities and dark colors. These impurities and dark colors require removal. The bleaching process is applied to remove the color. The bleaching earth is used in the … …Journal of Computer Science, Vol. 17, Issue 4 · 30 Apr 2021 · 6,943 accessesView PDFCite