DSpace Community:

Preliminaries

Thu, 16 Oct 2025 00:00:00 GMT

Title: Preliminaries

A security-enhanced IOT-based personalized self-care management system for children with special needs

Thu, 16 Oct 2025 00:00:00 GMT

Title: A security-enhanced IOT-based personalized self-care management system for children with special needs Authors: Ahamed Sabani, M. J.; Edirisinghe, E. H. S.; Hanan, M. R. M. Abstract: The children with special needs find it especially difficult to cope with healthcare problems, in particular with taking medications. They are more likely to require more personalization and security that is not possible with traditional systems. In this paper, the researchers develop an Internet of Things (IoT)-based self-care system that is tailored to such children. The literature review and a data collection of the caregivers, health care professionals and parents demonstrate that individual reminders and safe systems are needed. The proposed product will include a mobile-based application containing personalized alerts and an IoT-enabled medicine box enabling the management of medication in real-time and safely. This study will help to promote the development of health technology in children with special needs through the promotion of medication compliance and health outcomes.

AI-Driven cyber threats: unraveling deepfakes, autonomous malware, and defensive strategies

Thu, 16 Oct 2025 00:00:00 GMT

Title: AI-Driven cyber threats: unraveling deepfakes, autonomous malware, and defensive strategies Authors: Anoshan, Yoganathan; Ahamed Sabani, M. J.; Hanan, M. R. M. Abstract: Cyber threats are now more complicated and harder than ever with the swift development of artificial intelligence (AI). This study focuses on three key aspects of AI-driven cyber threats: social engineering with fake personal media, self modifying malware that attacks automatically and the tough challenges in defending systems against AI-backed cyberweapons. Because deepfake technology uses generative AI, it can make it simple and very convincing for criminals to carry out phishing and deceitful impersonation attacks on humans. Because it is driven by AI, autonomous malware can quickly transform to bypass usual anti-malware systems. Cyberweapons that incorporate AI such as automated creation of vulnerabilities, are a huge threat to computer networks. A comprehensive review of literature, as well as proposing a mixed methodology, this study studies how these threats work, their effects and the ways to control them. The results suggest that AI-based attacks are becoming more hidden and can be used on a large scale, so new defense methods are required. Participants cover the effectiveness of AI in detecting hackers, certain problems with today’s cybersecurity methods and what is and is not ethical when using AI in cybersecurity. To address these developing hazards, this paper proposes a multi-layered defense system that uses machine learning, deep learning and metaheuristic algorithms. The study urges the use of quick, flexible and ethical cybersecurity methods to defend vital systems in a world dominated by AI. This study supports current ongoing conversations by providing new findings for researchers, policymakers cybersecurity.

Evaluation of quality parameter variations and aflatoxin contamination of corn seeds (Zea mays) stored in Purdue improved crop storage (PICS) bags in North Central Province, Sri Lanka

Thu, 16 Oct 2025 00:00:00 GMT

Title: Evaluation of quality parameter variations and aflatoxin contamination of corn seeds (Zea mays) stored in Purdue improved crop storage (PICS) bags in North Central Province, Sri Lanka Authors: Jayasinghe, P. A. K. T.; Abdul Majeed, U. L.; Shyama, Rajapaksha; Shireen, M. F. R. Abstract: Post-harvest grain storage is crucial for maintaining the grain quality and ensuring food security. This study assesses the variation in quality parameters and aflatoxin contamination of corn seeds under two storage conditions. Treatments included Poly Propylene (PP) Woven bags (T0), and Purdue Improved Crop Storage (PICS) bags (T1), evaluated as a safer and cost effective alternative. Dried corn seeds (Jet 999 variety, <13% moisture) were stored under warehouse conditions (Temperature: 31-37 0C and Relative Humidity (RH): 55-70%) in Ihalagama, Kekirawa, North Central Province, Sri Lanka. A total number of 54 corn seed samples (27 per treatment) were evaluated to measure changes in moisture content, seed color, and aflatoxin contamination during an eight week storage period in PICS and PP woven bags. A significant (p <0.05) increase in aflatoxin content was observed in PP woven bag by the eighth week (2.87±0.25), whereas it aflatoxin levels remained lowest in PICS bag (0.90±0.10). Moisture content in T0 (PP woven bags) significantly increased from 12.37% to 13.01%, compared to a smaller increase in T1 (PICS bags) from 12.34% to 12.50%. No significant differences were observed in L, a, or b color values between treatments over time (p >0.05). These findings confirm that PICS bags provide a chemical-free, cost-effective, and sustainable alternative for safer corn storage in Sri Lanka, with important implications for food safety, postharvest policy, and industry adoption.