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61 results for “Feature Optimization”
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Research ArticleOpen accessIn the abstractAdvanced Hierarchical Deep Learning Approach for Intrusion Detection: Hyperparameter Tuning and Performance Evaluation on the CICIDS DatasetAjeet Singh, Azath M, Shahazad Niwazi Qurashi et al.Intrusion Detection Systems (IDS) are essential in the communication security and integrity of contemporary network architectures. This study introduces a novel advanced hierarchical deep learning model for network intrusion detection using the CICIDS dataset-2019. To improve the detection accuracy, the proposed model architecture builds several deep learning layers embedded with hyperparameters' optimization. Additional preprocessing steps, including over-sampling and min-max scaling, … …Journal of Computer Science, Vol. 21, Issue 11 · 26 Dec 2025 · 2,148 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Approaches for Early Detection of Skin Cancer Disease Detection Using Segmentation and Classification with Severity AnalysisPunam R. Patil, Ritu TandonThe utmost prevalent type of the disease, skin cancer claims millions of lives every year, poses a serious public health threat particularly melanoma, which is often fatal if not detected early. Early diagnosis is crucial, yet traditional methods frequently fall short due to image quality limitations and the complexity of visual differentiation. With an emphasis on severity analysis, this study … …Journal of Computer Science, Vol. 21, Issue 9 · 24 Nov 2025 · 2,051 accessesView PDFCite
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 abstractCloud Privacy Preservation Using Improved Squeezenet Based Data Sanitization and Improved Lyrebird Optimization-Based Optimal Key GenerationSmita Sharma, Sanjay TyagiMaintaining privacy in the cloud is critical, which implies reliable and effective models that are adapted to the difficulties presented by cloud settings. This paper introduces a comprehensive privacy preservation model tailored specifically for cloud environments, comprising five important phases such as data acquisition, normalization, feature extraction, sanitization and restoration. It begins with the meticulous collection of data from diverse … …Journal of Computer Science, Vol. 21, Issue 7 · 20 Aug 2025 · 3,190 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Antigenic Peptides Using a Multi-Level Transformer Model with Enhanced Feature SelectionAshwini S., Minu R. I., Jeevan KumarThis Antigenic Peptide (APs) prediction is one of the most important roles to improve vaccine design and interpret immune responses. This paper develops a Multi-Level Pooling-based Transformer model, which improves the accuracy and efficiency of predicting T-cell epitopes. The model utilizes peptide sequences from the Immune Epitope Database, employing a refined Kolaskar and Tongaonkar algorithm for feature extraction and a … …Journal of Computer Science, Vol. 21, Issue 7 · 17 Jul 2025 · 3,443 accessesView PDFCite
Research ArticleOpen accessIn the abstractNovel Depression Classification Framework Using Optimal Feature Integration with Hybrid Convolution (1D/3D) Based Adaptive Residual DenseNetB. Manjulatha, Suresh PabbojuThis study introduces a novel depression classification method by incorporating multimodal data to reduce this limitation and improve the accuracy of depression diagnosis. In the beginning, the multimodal data such as speech signal, Electroencephalographic (EEG), and text data is obtained from the benchmark datasets. These acquired text data are subjected to the text pre-processing phase, where the stemming, character removal, … …Journal of Computer Science, Vol. 21, Issue 3 · 25 Feb 2025 · 5,860 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimizing Mobile Edge Computing Efficiency through Multidimensional Generative Adversarial NetworkAnitha Premkumar, Sowmya Vemagal Lakshminarayana, Shankar Rajagopal et al.Big data Processing and the IoT have recently gained popularity as study topics in MEC and thorough research is sought for well-informed decisions. Mobile edge equipment, such as base stations, routers, and edge servers, usually have limited processing capabilities compared to traditional data centers. According to this perspective, this research constructs MEC using Intelligent Outlier Detection with a Multidimensional Generative … …Journal of Computer Science, Vol. 21, Issue 2 · 18 Jan 2025 · 4,686 accessesView PDFCite
Research ArticleOpen accessIn the abstractQuantum-Enhanced IoT-Cloud Security: Integrating SHAP and Variational Quantum ClassifiersVeena Antony, Nainan ThangarasuIn the current Internet era, there are now trillions of gadgets online, and the Internet of Things is becoming a necessary part of daily life. IoT devices are connected, but this also makes them vulnerable to cyberattacks. Cyberattacks targeting Internet of Things (IoT) systems have increased dramatically in both volume and sophistication in the last year. Determining the importance and … …Journal of Computer Science, Vol. 21, Issue 1 · 20 Dec 2024 · 4,951 accessesView PDFCite
Review ArticleOpen accessIn the abstractMachine Learning Integration for Precise Facial Micro-Expression RecognitionViola Bakiasi Shtino, Markela Muça, Senada BushatiThis study advances facial micro-expression recognition through innovative machine-learning techniques, addressing critical needs in psychology, security, and human-computer interaction. The purpose of this study is to improve micro-expression recognition through the optimization of feature transformation and machine learning algorithms. We introduce a novel approach combining Kernel Principal Component Analysis (KPCA) and Uniform Manifold Approximation and Projection (UMAP) for dimensionality reduction, … …Journal of Computer Science, Vol. 20, Issue 11 · 22 Oct 2024 · 5,592 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproved SVM with Hyperparameter Tuning for Fake News DetectionAtcharaporn Nachaithong, Kittipol WisaengIn today’s digital age, accessing information has become effortless. An abundance of resources is available online, from trustworthy news outlets providing factual information to unverified opinions shared by anonymous individuals. With the advent of modern technology, social media platforms have revolutionized interaction and staying informed, providing instant access to news and information related to a wide range of topics. They … …Journal of Computer Science, Vol. 20, Issue 10 · 28 Aug 2024 · 5,636 accessesView PDFCite