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313 articles for “data-driven learning”
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Advancements in AI-Driven Diagnostics for Dental Health: A Comprehensive Review
Abstract: Dental diseases, also known as oral diseases or dental conditions, encompass a range of health problems affecting the teeth, gums, mouth, and associated structures. These conditions can lead to pain, discomfort, and severe complications if left untreated. Early detection and accurate diagnosis are crucial for effective treatment and prevention of further complications. This comprehensive literature review aims to identify common dental problems such as Tooth Decay (Cavities), Gingivitis, Periodontitis, and …
Published in Current Trends in Signal Processing · Vol. 14, Issue 2, 2024 · pp. 1–7 Read article
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Machine Learning Pipelines: A Survey on Automation, Scalability, and Deployment Strategies
Abstract: Machine learning (ML) has become a critical enabler of intelligent applications across domains, requiring robust, efficient, and scalable deployment workflows. This review paper provides an in-depth overview of machine learning pipelines, emphasizing three key dimensions: automation, scalability, and deployment methodologies. It begins by exploring automation techniques that reduce manual effort in data ingestion, preprocessing, model selection, and hyperparameter tuning. Tools such as AutoML, TFX, and workflow orchestration platforms are examined …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 17–28 Read article
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Electronic Resources of University Libraries: AI-Driven Management and Optimization
Abstract: In order to maximize accessibility, utilization, and efficiency, university libraries’ growing reliance on electronic resources (ER) has prompted the creation of sophisticated management techniques. The difficulty of handling enormous volumes of data has increased as educational institutions move from conventional physical collections to massive digital repositories. A key instrument in revolutionizing library operations, artificial intelligence (AI) offers creative ways to improve retrieval methods, manage digital resources more effectively, and customize …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 3, 2025 · pp. 8–15 Read article
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Artificial Intelligence in Robotics: Current Trends, Applications, and Future Challenges
Abstract: The incorporation of artificial intelligence (AI) into robotics has transformed the industry by greatly improving robots' capacity to carry out complex and autonomous functions in a wide range of sectors. This paper explores the evolution, applications, and challenges associated with AI-driven robotics. It examines key AI methodologies employed in robotics, including machine learning, natural language processing (NLP), computer vision, and planning/control algorithms, which enable robots to perceive, learn, and interact …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 2, 2025 · pp. 31–43 Read article
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IoT-Based Industrial Safety Management Systems
Abstract: The integration of the Internet of Things (IoT) in industrial safety management has transformed workplace safety by enabling real-time monitoring, predictive analytics, and automated hazard mitigation. IoT-Based Industrial Safety Management Systems utilize interconnected sensors, wearable devices, and intelligent analytics platforms to proactively detect and respond to potential risks in high-risk environments such as manufacturing, oil and gas, and construction. These systems continuously monitor critical safety parameters, including temperature, pressure, gas …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 1, 2025 · pp. 18–22 Read article
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Library Science Education in India: Evolution, Emerging Trends, and Challenges
Abstract: Library and Information Science (LIS) education in India has undergone significant transformation over the past century, evolving from traditional library training to a dynamic academic discipline shaped by technological advancements and changing information needs. This study examines the origin, development, and current status of LIS education in India, with particular emphasis on its evolution in the contemporary digital environment. The research adopts a qualitative and exploratory approach and is based …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 75–87 Read article
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A Study on “Clean" in Beauty: A Machine LearningApproach to Ingredient Transparency and ConsumerTrust
Abstract: The burgeoning "clean beauty" market, while driven by consumer demand for safer and more sustainable products, is plagued by ambiguous definitions and the pervasive challenge of "greenwashing". This ambiguity hinders informed consumer choices and complicates brand authenticity. This study addresses these complexities by developing a novel machine learning (ML) framework designed to objectively analyze cosmetic ingredient lists, classify products based on their "cleanliness" profile, and identify key ingredient attributes that …
Published in Recent Trends in Cosmetics · Vol. 3, Issue 1, 2026 · pp. 1–12 Read article
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Antimicrobial Resistance and AI-Based Strategies for Rapid Pathogen Detection
Abstract: Antimicrobial resistance (AMR) has become a major global health threat, significantly reducing the effectiveness of antimicrobial therapies and increasing the burden of infectious diseases worldwide. The rapid emergence of multidrug-resistant pathogens has created an urgent need for faster, more accurate, and scalable diagnostic approaches to support timely treatment and effective infection control. Artificial intelligence (AI) has emerged as a promising technology capable of transforming pathogen detection and AMR surveillance through …
Published in Recent Trends in Infectious Diseases · Vol. 3, Issue 2, 2026 · pp. 26–36 Read article
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A Study on AI-Driven Multi-Layered Defense in 6G Ecosystems
Abstract: The 6G networks bring about new degrees of possible functions related to connectivity, latency, data throughput, and integration with artificial intelligence (AI). This enables advances within healthcare, autonomous systems, and smart cities. The positive impact of rapid advancements must also be balanced with heightened risks due to the sheer volume of gaps that can be exploited, and the complex nature of the alignments and breaches. This results in the breaches …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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Multi-Scale Analysis of Polymer Based Energy Storage Systems for High Performance Battery Applications
Abstract: The energy storage systems based on polymers are becoming promising materials for the next generation of high performance batteries because of their excellent mechanical flexibility, improved safety, and favorable electrochemical properties. Even with computational tools in Python, polymer-based energy storage systems remain plagued by poor ionic conductivity, complicated electrochemical reactions and potential thermal runaway. Therefore, a multi-scale model is proposed to improve battery performance, thermal stability, reliability, and large-scale deployment …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1035–1048 Read article
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AI-Driven Optimization of Biopolymer Composite Formulations Using IoT Data Streams
Abstract: Biodegradable polymer composites have emerged as a sustainable alternative to petroleum-based materials in packaging, biomedical, and structural applications. However, traditional formulation techniques for reinforced polymer composites often lack precision and fail to adapt to real-time variations during processing, resulting in suboptimal material performance. This research proposes a real-time AI-IoT-enabled framework to optimize biopolymer composite formulations. The goal is to intelligently tune composite properties such as mechanical strength, moisture resistance, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 85–100 Read article
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Prediction of Mechanical Properties for Advanced Engineering Applications utilizing Polymer Composite Materials by Machine Learning
Abstract: Polymer composites show great promise as engineering materials because of their mechanical performance, resistance to corrosion, lightweight nature, and adaptability in design. Aerospace, automotive, biomedical, maritime, and civil engineers all rely on mechanical property prediction to cut down on trial expenses, expedite product development, and optimize material selection. Speedy design optimization is not possible using traditional numerical and experimental methods due to the high costs associated with material characterisation, computational …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Exploring Artificial Intelligence in the Finance Sector
Abstract: Artificial intelligence (AI), machine learning (ML), and progressive algorithms illustrate a substantial technological leap with wide applications across sectors like automobiles, healthcare, gaming, finance, entertainment, and more. The foremost objective of AI is to produce intelligent, independent systems capable of self-sustaining decision-making. This study delivers a concise summary of AI, concentrating on its transformative influence on finance, especially within banking, asset firms, derivatives markets, and insurance enterprises. It summarizes the …
Published in E-Commerce for Future & Trends · Vol. 11, Issue 3, 2024 · pp. 16–23 Read article
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Diabetes Risk & Al Nutrition Assistant
Abstract: The rising prevalence of diabetes mellitus has emerged as a major global health challenge. Early identification of individuals at risk, combined with personalized lifestyle-based interventions, can significantly reduce future complications. This study presents an AI-driven Nutrition Assistant integrated with a Diabetes Risk Prediction model. The system uses a machine learning classification approach to estimate the likelihood of diabetes based on clinical and nutritional factors, including body mass index, glucose levels, …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 31–38 Read article
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An AI-Driven IoT Framework for Autonomous Quality Assurance in Optical Lens Manufacturing
Abstract: The evolution of high-precision optics—ranging from smartphone micro-lenses to high-end astronomical glass—demands unprecedented accuracy in manufacturing. Traditional inspection methods, reliant on manual sampling or static automated optical inspection (AOI), often fail to bridge the gap between high-speed production and the detection of microscopic surface aberrations. This paper introduces an integrated architecture combining the Internet of Things (IoT) and Deep Learning-based decision-making systems to revolutionize lens quality control. By deploying an …
Published in International Journal of Optical Innovations & Research · Vol. 4, Issue 1, 2026 · pp. 36–41 Read article
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Enhancing Robot Autonomy: Integrating AI for Advanced Decision-making in Autonomous Robotic Systems
Abstract: The capabilities of autonomous robotic systems have been drastically changed by the rapid progress in artificial intelligence (AI) technologies. In this work, we investigate the integration of AI approaches to improve robot autonomy by presenting even more advanced mechanisms for decision-making. Almost all traditional robotic systems involve predefined algorithms, making them unable to cope with dynamic environments. They can also help with learning based on machine learning and deep learning …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 3, 2024 · pp. 28–37 Read article
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A Thorough Examination of How Artificial Intelligence is Affecting the Transformation of Agriculture in India and Throughout the World
Abstract: By providing creative ways to increase crop yields, maximize resource usage, and advance sustainability, artificial intelligence (AI) is revolutionizing agriculture. AI technologies, such as machine learning, computer vision, and robotics, are being increasingly used in precision farming, crop monitoring, disease detection, and decision-making as the global agricultural sector faces pressing challenges like food security, population growth, and climate change. AI enables farmers to make data-driven decisions, optimize irrigation systems, monitor …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 39–45 Read article
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Integrating Genetic Algorithms with Lean Manufacturing for Enhanced Production Efficiency
Abstract: Lean manufacturing is a well-established philosophy focusing on the systematic reduction of waste and the ongoing development of value supplied to the customer. It emphasizes efficiency, quality, and adaptability through ideas such as just-in-time production, continuous improvement (Kaizen), and value stream optimization. However, the increased complexity of modern production systems, driven by global rivalry, product variety, and rapid technology innovation, has shown the limitations of classic lean tools in achieving …
Published in Journal of Production Research & Management · Vol. 15, Issue 3, 2025 · pp. 38–43 Read article
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A Lightweight Cost-Sensitive Explainable Ensemble Framework for Early Heart Disease Risk Prediction
Abstract: Cardiovascular disease is still one of the leading causes of death, and hence, the early prediction of risk is a very important task in preventive medicine. Although recent studies have shown encouraging results in the application of machine learning algorithms to the prediction of heart disease, it has been noticed that most of the algorithms are more concerned with accuracy-driven optimization than the concerns of safety and false negatives. In …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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A review on polyhouse monitoring system
Abstract: The integration of Internet of Things (IoT) technology in agriculture has revolutionized traditional farming practices, offering innovative solutions to enhance productivity, sustainability, and resource efficiency. This study explores the role of loT-based systems in smart agriculture, focusing on applications such as environmental monitoring, automated irrigation, crop health prediction, and precision farming. The reviewed systems utilize advanced sensors to monitor parameters like temperature, humidity, soil moisture, and light intensity, transmitting real-time …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 2, 2025 · pp. 1–9 Read article