Research ArticleOpen accessIn the keywordsA Gene Selection Algorithm using Bayesian Classification ApproachAlok Sharma, Kuldip K. PaliwalIn this study, we propose a new feature (or gene) selection algorithm using Bayes classification approach. The algorithm can find gene subset crucial for cancer classification problem. Problem statement: Gene identification plays important role in human cancer classification problem. Several feature selection algorithms have been proposed for analyzing and understanding influential genes using gene expression profiles. Approach: The feature selection … …American Journal of Applied Sciences, Vol. 9, Issue 1 · 24 Nov 2011 · 8,307 accessesView PDFCite
Research ArticleOpen accessIn the abstractRefining Chest X-ray Interpretation with Deep Transfer Learning TechniquesR. Sriramkumar, K. Selvakumar, J. JeganChest X-rays are essential diagnostic tools for thoracic diseases, but different doctors' interpretations can differ greatly, which frequently results in inconsistent diagnoses. By using deep transfer learning techniques, this study seeks to improve the accuracy of Chest X-ray interpretations. More accurate and effective analysis can be accomplished with the growing potential of artificial intelligence (AI) in medical imaging, especially through … …Journal of Computer Science, Vol. 21, Issue 10 · 27 Nov 2025 · 2,644 accessesView PDFCite
Review ArticleOpen accessIn the abstractUnveiling Skin Cancer: A Review of Deep Learning Techniques for DetectionGoutham Lal Shanmughamadom Harilal, Tamilselvi PanneerselvamEarly identification is essential for successful treatment and better patient outcomes since skin cancer is caused by damage to DNA in skin cells, which can result in genetic abnormalities and the possibility of metastasis. The present systematic review scrutinizes the efficacy and obstacles of early detection techniques, which differentiate between benign and malignant lesions by examining lesion attributes such as … …Journal of Computer Science, Vol. 21, Issue 9 · 23 Oct 2025 · 2,602 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Data Encryption for Securing HDFS Using DQN-Enhanced Deep Reinforcement Learning TechniquesShivani Awasthi, Narendra KohliIn the era of big data, ensuring the security of large-scale distributed storage systems like the Hadoop Distributed File System (HDFS) is critical. Traditional encryption methods often struggle to balance robust security with system performance, leading to vulnerabilities and inefficiencies. This study presents the design and implementation of an efficient data encryption algorithm for securing HDFS using Deep Q-Network (DQN) … …Journal of Computer Science, Vol. 21, Issue 4 · 4 Mar 2025 · 6,376 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhanced Hybrid Spectrum Sensing Method Using TCDT and IEDT for Cognitive RadioNeha Chaudhary, Rashima Mahajan, Richa Adlakha et al.The development of efficient spectrum sensing techniques has witnessed progressive growth for optimum utilization of spectrum resources in cognitive radio. The primary objective of spectrum sensing is the identification and proper utilization of the spectrum holes. Nowadays, due to the advancement of wireless technologies, the demand for spectrum is also increasing and thus in turn, the requirement for better spectrum … …Journal of Computer Science, Vol. 20, Issue 11 · 20 Nov 2024 · 4,301 accessesView PDFCite
Research ArticleOpen accessIn the abstractAlternative Monitoring Approach for IPTVAngel Ignatov, Hristo Toshkov Hristov, Jan Latal et al.IPTV emerged in the late 1990s as a solution for delivering Video on Demand (VoD) and live television over managed networks. Its widespread adoption accelerated after the expansion of broadband internet and the introduction of web technologies such as HTML5 and adaptive streaming protocols (MPEG-DASH and HLS), which enabled television content to be streamed directly through web browsers. Across Europe, … …Journal of Computer Science, Vol. 22, Issue 11 · 8 Oct 2026 · 430 accessesView PDFCite
Research ArticleOpen accessIn the abstractEpileptic Seizure Detection from EEG Signal Using Progressive Channel Selection and Deep LearningSuraiya Akter Mumu, Shupta Das, M. A. H. Akhand et al.Epileptic Seizures (ES), marked by abrupt abnormal electrical discharges in the brain, represent the primary symptom of epilepsy, making timely and accurate detection critical because of their unpredictable recurrence and potentially severe consequences. The Electroencephalogram (EEG), a widely used, non-invasive, and economical method for monitoring brain activity, plays a key role in automated ES detection through Machine Learning (ML) and … …Journal of Computer Science, Vol. 22, Issue 6 · 8 Jul 2026 · 1,393 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Facial Expression Recognition Accuracy Through Haar Cascade-Based Feature ExtractionThambusamy Velmurugan, Lakshminarayanan MeenaFacial Expression Recognition (FER) has a significant interest because of its increased applications in Human-Computer Interaction (HCI), like video interactions, emotion analysis, image indexing, and retrieval and many more. In the discipline of computer vision, pattern recognition, and artificial intelligence FER has become an extremely active research topic. A crucial component of FER systems is feature extraction, which involves identifying … …Journal of Computer Science, Vol. 21, Issue 12 · 21 Jan 2026 · 1,656 accessesView PDFCite
Research ArticleOpen accessIn the abstractHindi Poetry Translation Using Neural Machine TranslationPragya Tewari, Anurag Singh BaghelNeural Machine Translation (NMT) has become an essential tool in Natural Language Processing (NLP), enabling the automatic translation of text across languages. However, translating poetry remains a relatively unexplored and complex task. Unlike general text, poetry carries multiple layers of meaning, emotion, rhythm, and cultural nuance, making it difficult to capture in another language through standard translation techniques. This study … …Journal of Computer Science, Vol. 22, Issue 1 · 16 Feb 2026 · 1,773 accessesView PDFCite
Research ArticleOpen accessIn the abstractTomato Leaf Disease Detection by Hybrid Ai and Ml TechnologyP. Loganathan, M. John Britto, Vinston RajaDiseases that affect plants contribute to productivity decline, but they can be managed with ongoing monitoring. It is time-consuming and prone to error to track plant diseases manually. Early disease detection using Artificial Intelligence (AI) and machine vision can lessen negative impacts while also overcoming some of the limitations of continuous human monitoring. Therefore, this study uses both Deep Learning … …Journal of Computer Science, Vol. 21, Issue 12 · 12 Feb 2026 · 1,881 accessesView PDFCite