Research ArticleOpen accessIn the abstractBlockchain: An Efficient Intelligent Agreement for Patents and TrademarksVikram Shirol, Shanmuga RathinamIntellectual property security faces problems in the digital era, with growing piracy, AI-generated works, and global compliance problems, Creations, designs, trademarks, and trade secrets are all protected by Intellectual Property (IP) rights; yet, there are several issues with IP rights management and enforcement around the world. The benefits of blockchain technology include decentralization, transparency, and immutability. Therefore, blockchain offers to … …Journal of Computer Science, Vol. 21, Issue 3 · 20 Feb 2025 · 5,491 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized XGBoost for Ethereum Fraud Detection: A Cost-Sensitive ApproachSupriya P., Rubah Sheriff, Shreya Padaki et al.In today’s technologically advancing world, many fields from finance to healthcare and education are shifting toward a digital and decentralized format. A significant transformation is underway with the currency of the masses. Blockchain-based cryptocurrencies like Bitcoin and Ethereum allow users to generate fungible tokens anonymously through smart contracts. However, these features also facilitate illicit transactions and cybercrimes like fraud, phishing, … …Journal of Computer Science, Vol. 21, Issue 12 · 10 Jan 2026 · 2,770 accessesView PDFCite
Research ArticleOpen accessIn the abstractFractal Dimension for Lung Sound Classification in Multiscale SchemeAchmad Rizal, Risanuri Hidayat, Hanung Adi NugrohoLung sound is a biological signal with the information of respiratory system health. Health lung sound can be differentiated from other pathological sounds by auscultation. This difference can be objectively analyzed by a number of digital signal processing techniques. One method in analyzing the lung sound is signal complexity analysis using fractal dimension. To improve the accuracy of lung sound … …Journal of Computer Science, Vol. 14, Issue 8 · 24 Aug 2018 · 9,279 accessesView PDFCite
Research ArticleOpen accessIn the abstractGAUSSIAN MIXTURE MODEL BASED CLASSIFICATION OF MICROCALCIFICATION IN MAMMOGRAMS USING DYADIC WAVELET TRANSFORMSuman Mishra, Hariharan RanganathanBreast cancer is a serious health related issue for women in the world. Cancer detected at premature stages has a higher probability of being cured, whereas at advanced stages chances of survival are bleak. Screening programs aid in detecting potential breast cancer at early stages of the disease. Among the various screening programs, mammography is the proven standard for screening … …Journal of Computer Science, Vol. 9, Issue 10 · 5 Sep 2013 · 6,867 accessesView PDFCite
Research ArticleOpen accessIn the abstractMass Classification in Digital Mammograms based on Discrete Shearlet TransformJ. Amjath Ali, J. JanetThe most significant health problem in the world is breast cancer and early detection is the key to predict it. Mammography is the most reliable method to diagnose breast cancer at the earliest. The classification of the two most findings in the digital mammograms, micro calcifications and mass are valuable for early detection. Since, the appearance of the masses are … …Journal of Computer Science, Vol. 9, Issue 6 · 1 Jun 2013 · 6,549 accessesView PDFCite