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293 articles for “Automated machine learning”
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Algorithm for the prediction of cardiovascular disease (CVD)
Abstract: cardiovascular diseases (CVD) still claim a significant number of deaths globally and remain the number one killer with an annual death toll of nearly 17.9 million. While several medical advancements have been made, an early diagnosis is still hard to obtain, which often leads to worsening conditions and intricate treatment options. With the advancement of modern technology, Machine learning has demonstrated to be a miraculous tool which can greatly impact …
Published in Research and Reviews : A Journal of Immunology · Vol. 15, Issue 2, 2025 Read article
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Innovative Approaches to Reactive Power Management and Optimization in Modern Power systems
Abstract: Reactive power management and optimization are necessary for the effective, stable, and reliable working of modern power systems. Without proper management, reactive power is responsible for additional losses in transmission, reduced capability of power transfer, and poor voltage stability conditions, thus forming a basis for developing advanced techniques of optimization. This paper discusses the innovative methods in Reactive Power Optimization (RPO) using met heuristic algorithms, namely the Self-Balanced Differential Evolution …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 44–50 Read article
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ICU Health Monitoring System in IoT with Machine Learning
Abstract: The Internet of Things (IoT) allows humans to push to a higher level of automation by developing systems using various sensors, interconnected smart devices, and the Internet. In ICU, patient checking is basic and most vital activity as little deferral in choice related to patients’ treatment may cause lasting permanent disability or maybe death. Most ICU devices are equipped with various sensors to live health parameters but to watch it …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 9, Issue 1, 2021 · pp. 25–34 Read article
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Depression Detection Using Machine Learning: A Comprehensive Review
Abstract: Depression remains one of the most prevalent mental health conditions globally, yet it frequently goes undiagnosed due to the reliance on subjective evaluation methods. With the growing availability of digital behavioral data and significant progress in machine learning (ML), new possibilities have emerged for the automated detection of depression. This review offers a detailed examination of recent advancements in ML-driven approaches to identifying depressive symptoms. It covers a range of …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 27–32 Read article
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Design and Development of Screw Detection System : A case study
Abstract: This study explores the design of a vision-based screw detection and orientation system for industrial automation, inspection, and robot disassembly. By integrating machine learning algorithms like region-based convolutional neural networks (R-CNN) with traditional image processing and impedance sensing, the system performs real-time screw presence detection, head type identification, and alignment. Three key technologies—deep learning classification, edge-based geometric analysis, and impedance verification—are integrated into a single modular system. The findings indicate …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 30–36 Read article
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Solar Empowerment: A Critical Review of Intelligent Home Automation Technologies
Abstract: An innovative way to improve domestic lifestyle is with the Interactive Powered by solar energy Automated Home System, which combines smart technology with renewable energy. This system leverages solar power to sustainably meet energy needs, ensuring an eco- friendly and cost-effective solution. The heart of ISPHAS lies in its intelligent automation, seamlessly interconnecting various household devices and systems to optimize energy consumption and enhance overall efficiency. Through advanced sensors and …
Published in Journal of Nuclear Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 25–31 Read article
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Enhancing Road Safety: A Robotic System for Automatic Pothole Identification and Filling
Abstract: Innovative technologies called automatic pothole detection systems are made to automatically locate and identify potholes on road surfaces. These systems incorporate many components, including sensors such as cameras, LiDAR, and accelerometers, to acquire data on the road conditions. Potholes on roads provide serious risks to passing cars and pedestrians, which can result in collisions, damage to cars, and deterioration of the infrastructure. Automatic pothole detection systems, which make use of …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 3, 2024 · pp. 1–6 Read article
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Optimizing Sampling Techniques Using Fuzzy Set Theory: A Comprehensive Approach
Abstract: Sampling is a critical process in statistics, used to estimate population parameters without needing to examine the entire population. Traditional sampling methods, such as simple random sampling, stratified sampling, and cluster sampling, face limitations when applied to complex or heterogeneous populations with imprecise boundaries. These methods often fail to accurately represent populations with overlapping characteristics or missing data, resulting in sampling bias and reduced accuracy. To address these challenges, this …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 29–43 Read article
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Depression Detection using Machine Learning: A Comprehensive Review
Abstract: Depression is a leading mental health disorder worldwide, often underdiagnosed due to subjective assessment methods. The increasing availability of digital behavioral data and the advancement in machine learning (ML) have opened new avenues for automated depression detection. This review presents a comprehensive overview of recent developments in ML- based approaches for detecting depression. It explores data sources, feature extraction techniques, learning algorithms, evaluation methods, and highlights current challenges and future …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 Read article
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Genomic Selection for Grain Yield in Wheat Using Machine Learning on DArT Molecular Markers: A Comparative Evaluation Across Multi-Environment Trials
Abstract: Genomic selection (GS) predicts complex quantitative traits directly from genome-wide molecular markers, bypassing the need for extensive phenotypic trials and accelerating plant breeding cycles. We conducted a comparative evaluation of seven regression approaches — ridge regression (the machine-learning equivalent of RR-BLUP), Lasso, Elastic Net, Partial Least Squares, linear Support Vector Regression, Random Forest, and Gradient Boosting — for predicting grain yield from 1,279 Diversity Array Technology (DArT) molecular markers genotyped …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
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Artificial Intelligence in Medical Fields
Abstract: Artificial intelligence (AI) is a branch of computer science capable of analyzing complex medical data. This can be used in diagnosis, treatment and predicting outcome in many clinical scenarios. Medicine and internet searches were carried out using the keywords ‘artificial intelligence’ and ‘neural networks’. An overview of different AI techniques is presented in this paper along with the review of importance in clinical applications. The proficiency of AI techniques has …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 8, Issue 1, 2019 · pp. 1–3 Read article
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The Role of AI in Modern Circuit Design and Simulation
Abstract: The integration of artificial intelligence (AI) in circuit design and simulation is revolutionizing the electronics industry by enabling faster, more efficient, and innovative design processes. This article explores the transformative role of AI in automating tasks traditionally reliant on manual expertise, such as schematic generation, component optimization, and fault detection. It highlights how machine learning algorithms and generative AI tools are improving design accuracy, reducing time-to-market, and enabling cost-effective prototyping. …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 1, 2025 · pp. 9–14 Read article
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The Role of Automation in Modern Healthcare: Innovations and Impact.
Abstract: Automation technology encompasses a broad array of systems and tools designed to perform tasks with minimal human intervention, thereby increasing efficiency, reducing errors, and enhancing productivity. This study explores the core components of automation technology, including sensors, actuators, controllers, and software, and examines their applications across various industries. In manufacturing, automation leads to significant improvements in production speed and precision. In healthcare, it enhances patient care and operational efficiency. In …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 2, 2024 · pp. 1–9 Read article
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Hybrid Machine Learning and Finite Element Framework for Predicting Damage Behavior in Fiber-Reinforced Polymer Composites
Abstract: Fiber Reinforced Polymer (FRP) composites have broad spread use in aerospace, automotive, marine and structural applications due to its high specific strength, stiffness and corrosion resistance. The various damage mechanisms such as matrix cracking, fiber breakage, delamination and interfacial failure, however, make the forecasting of damage particularly complex. In this work, a hybrid machine learning (ML) and finite element (FE) system is proposed for predicting the damage behavior of FRP …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 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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AI-Driven DevSecOps Automation: An Intelligent Framework for Continuous Cloud Security and Regulatory Compliance
Abstract: Cloud-native systems, microservices, and infrastructure-as-code (IaC)–oriented CI/CD pipelines have accelerated the pace of software delivery, yet they have also introduced new layers of operational complexity and widened the overall security exposure of modern applications. Traditional DevSecOps workflows still depend heavily on isolated scanners, manual reviews, and static governance processes that are not well-suited for the elasticity and constant change characteristic of multi-cloud environments. To address these limitations, this paper introduces …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 · pp. 01–15 Read article
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Artificial Intelligence in Trigonometry: Innovations, Applications, and Future Prospects
Abstract: Artificial Intelligence (AI) has transformed numerous scientific fields, yet its integration with classical mathematics such as trigonometry is still emerging. This paper explores how AI enhances trigonometric problem solving, learning, and real-world applications. We analyse AI-driven tools for teaching trigonometry, AI in geometric and spatial reasoning, usage in robotics and computer vision, and future directions for research. Key challenges, methodologies, and case studies are discussed to provide a comprehensive overview …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 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 · pp. 1258–1284 Read article
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Advances in Medical Robotics: Surgical Automation and Rehabilitation Systems
Abstract: Medical robotics has emerged as a groundbreaking technology, transforming modern healthcare through advancements in surgical automation and rehabilitation systems. Robotic-assisted procedures machine learning (ML), and artificial intelligence (AI) have all been used to improve patient recovery consequences, reduce invasiveness, and increase surgical precision. These developments have redefined traditional medical techniques by opening the door for more effective, precise, and tailored therapies. By improved dexterity, stability, and vision, surgical robots has …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 1, 2025 · pp. 31–38 Read article
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AbhiGyam: A Machine Learning Model-driven Research Platform for Assessing Accessibility Infrastructure in Indian Cities
Abstract: This work presents AbhiGyam, a machine learning-driven research platform designed to streamline and automate the assessment of accessibility infrastructure in Indian cities. AbhiGyam leverages the Google Maps API to transmit street view images to the backend, where computer vision techniques are implemented using OpenAI's CLIP (Contrastive Language-Image Pre-training) model to identify objects such as ramps, sidewalks, crosswalks, and parking spaces. The accuracy of the model is validated using labeled data …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 84–91 Read article