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3 articles for “software maintainability prediction”
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Strategy for Improving Software Maintenance Using Machine Learning for Security Requirements: A Review
Abstract: Within the area of software technical education, the significance of software defect discovery has increased as a research focus to enhance program reliability. By maximizing testing resources and assisting developers in identifying potential problems using program defect predictions, program dependability is increased. Applying software engineering (SE) techniques to critical and intricate systems, like networking and security systems, is imperative. Traditional methods of predicting software maintainability have limitations, particularly in balancing …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 2, 2024 · pp. 36–48 Read article
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AI-driven Flood Surveillance and Dam Control: Advancing Resilience Through Data Science
Abstract: This study presents the development and real-world deployment of an intelligent system for flood monitoring and automated dam gate control using artificial intelligence (AI) and internet of things (IoT) sensors. Supervised machine learning models are developed to predict floods up to 48 h in advance. An automated dam gate operation system is designed to leverage the flood forecasts and real-time stream water levels for emergency control. The complete end-to-end infrastructure …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 2, 2023 · pp. 9–17 Read article
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Breast Feeding Practices Among Rural Women
Abstract: Introduction: Breastfeeding is an unequalled way of providing ideal food for the healthy growth and development of infants. As per the national family health survey-3 (NFHS-3), only 46% of the Indian infants between 0 and 6 months are exclusively breastfed. Hence the following study was done to know the practice of breastfeeding in mothers of rural and urban areas of India. Method- The study was carried out in a rural …
Published in International Journal of Women's Health Nursing And Practices · Vol. 1, Issue 1, 2023 · pp. 01–08 Read article