Search
339 articles for “adaptive learning”
-
Elevating Seamless Housing Navigation with Precise Recommendations for Personalized Rental Experiences
Abstract: The demand for rental housing has increased significantly in recent years, making more effective and individualized methods of housing navigation necessary. Renters become frustrated and ineffective when using traditional ways of researching rental houses since they frequently involve manual searches and little customization. By using sophisticated recommendation systems to deliver exact recommendations catered to user preferences, this research article suggests a novel way to improve house navigation. The proposed approach …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 50–62 Read article
-
Deep Learning for Real-Time Monitoring and Defect Detection in Additive Manufactured Polymer Composites
Abstract: Additives Fiber-reinforced polymer composite ADDs have high utility in making lightweight structural components, but due to process-related defects (interlayer delamination and reinforcement stacking) the integrity of consolidation during extrusion-based deposition is frequently compromised. This paper has presented a physics-informed deep learning framework that is applicable to real-time measurements of reinforced thermoplastic composite fabrication. Multimodal sensing was provided with thermal gradient, optical morphology, and acoustics emission signals being used to assess …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 974–999 Read article
-
AI-Driven Lightning Strike Prediction Using Polymer-Integrated Sensor Platforms for Climate-Resilient Energy Systems in India
Abstract: Lightning strikes are a major climate-related threat to India, resulting in severe human injuries as well as regular damages to the power transmission network and renewable energy infrastructure. This research aims to introduce the concept of an AI-based lightning strike prediction and mitigation system with the integration of polymers for making climate-resilient energy infrastructure. Multidata are collected based on satellite images, climate variables, as well as surface-based sensing modules, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 234–242 Read article
-
Nitro IDE: Exploring Integrated Development Environments: Current Trends and Innovations
Abstract: Integrated Development Environments (IDEs) have become essential in modern software development, offering a centralized platform that brings together source code management, debugging tools, version control, and compilation features. This study offers an in-depth analysis of various IDE platforms, with a particular focus on Eclipse as a widely used open-source integration environment. It also explores specialized IDEs tailored for embedded systems and enterprise-level Java (J2EE) application development. Additionally, the study examines …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 35–40 Read article
-
Trends and Applications of Artificial Intelligence in Mechanical Engineering: A Review
Abstract: Artificial Intelligence (AI) has become a revolutionary force across various fields, including mechanical engineering, where it is redefining traditional approaches to design, manufacturing, maintenance, and overall system optimization. This review aims to provide a comprehensive introduction to AI and explore its diverse applications within the domain of mechanical engineering. The study begins with a foundational overview of AI, including key concepts such as machine learning, neural networks, deep learning, and …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 3, 2025 · pp. 30–35 Read article
-
Current Updates On Employability Of Artificial Intelligence In Healthcare Science & Research
Abstract: Over the centuries, tools have been developed to increase refinement to manipulate different tools in many ways to use human digital computers. It can perform the same types of numerical and symbolic operations that can be done by ordinary people, but faster and more reliable. Artificial intelligence algorithms applied to computer applications and software. Include knowledge-based systems. AI is the science that mimics the mental skills of humans in computers. …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 72–77 Read article
-
Exploring Artificial Intelligence in Operating Systems for Consumer Enhanced Experience: Knowledge-Based Interfaces for Intelligent User Experience and System Optimization
Abstract: The convergence of knowledge-based systems, machine learning algorithms, and natural language interfaces that provide dynamic and context-sensitive behavior is another foundation for this change. AI-based operating systems are important because they can enhance user experiences via automation, self-optimization, and customization. AI signifies a new era of cognitive computing, from adaptive power management for desktops and embedded systems to predictive text and voice recognition on mobile devices. Furthermore, this ability to …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 3, 2025 · pp. 26–30 Read article
-
Deep Reinforcement Learning-Based Intelligent Energy Management Strategy for Battery–Supercapacitor Hybrid Energy Storage Systems in Electric Vehicles
Abstract: As the number of EVs increases, smart solutions for energy management are needed that will optimize energy use, prolong battery life and boost vehicle performance. The application of conventional rule based and optimization-based Energy Management Strategies (EMS) for Battery–Supercapacitor Hybrid Energy Storage Systems (HESS) often leads to sub-optimal power management, supercapacitor mismatch and battery degradation when subjected to varying driving conditions. This study aims to design an intelligent energy management …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 2, 2026 Read article
-
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
-
Quasar: Quantum-Accelerated Sustainable Anomaly Recognition in Climate Systems
Abstract: Accurate detection of climate anomalies is vital for disaster alleviation and policy making in a sustainable manner, but customary detection methods face the challenges of computational inefficiency and physical inconsistency. In this study, we propose a novel approach called Quantum-Optimized Fuzzy Physics-Informed Neural Networks (QFuzzy-PINNs), which integrates quantum computing, fuzzy logic, and physics-informed deep learning. As a first step, we employ quantum annealing for conventional optimization to adjust multiple Gaussian …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 18–27 Read article
-
Using AIML to Enhance Demand Forecasting in Business
Abstract: Artificial intelligence machine learning (AIML) can play a significant role in enhancing demand forecasting in business. AIML is a programming language designed for creating chatbots and conversational agents, but its application extends beyond simple interactions. In the context of demand forecasting, AIML can be utilized to analyze historical data, customer interactions, and market trends. By implementing AIML algorithms, businesses can create intelligent models that learn from past demand patterns, customer …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 35–40 Read article
-
Real-Time Sign Language to Speech Conversion Glove Using Arduino and Wearable Sensors
Abstract: This research work presents the design and development of a low-cost, wearable glove system for real- time sign language to speech conversion. The system employs an Arduino microcontroller integrated with flex sensors and an accelerometer to accurately detect hand gestures. The system translates hand gestures into audible speech through Bluetooth communication, enabling seamless interaction for hearing-impaired individuals. By converting sign language into speech in real-time, it significantly enhances communication accessibility …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 14, Issue 3, 2025 · pp. 10–18 Read article
-
Improving The Accuracy of Medical Diagonosis Detection Using Machine Learning
Abstract: While accurate and timely medical diagnosis is a fundamental aspect of effective health care delivery, traditional methods have not been able to overcome major hurdles such as inefficiencies in data analysis with Gi Human Error as well as limitations in scalability. The “Improved Accuracy of Medical Diagnosis Detection Using Machine Learning” project seamlessly integrates advanced machine learning (M L) technologies with efficient preprocessing and feature selection techniques to outperform all …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 1–8 Read article
-
AI Hindi Poem Generator
Abstract: The Hindi Poetry Generator project represents a pioneering initiative in the domain of computational creativity, blending machine learning algorithms and natural language processing methodologies to craft poetic expressions in the Hindi language. Rooted in the vast landscape of Hindi literature, this project harnesses the power of deep learning models to generate evocative and culturally significant poetry. At its core, the system relies on neural networks and sophisticated language modeling techniques …
Published in Recent Trends in Programming languages · Vol. 11, Issue 2, 2024 · pp. 10–16 Read article
-
From Differential Equations to Data Science: A Survey on Analytical Methods in Contemporary Problems
Abstract: The integration of differential equations and data science methods represents a dynamic and evolving approach to solving contemporary challenges across a wide range of disciplines, including engineering, physics, biology, economics, and finance. Differential equations have long served as fundamental tools for modeling continuous systems and processes, offering powerful insights into the behavior of natural and man-made phenomena. For example, they describe how heat diffuses through materials, how populations grow in …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 1–6 Read article
-
Advancements in Smart Manufacturing: A Review of Industry 4.0 Technologies and Integration Strategies
Abstract: A new era of production known as “Smart Manufacturing,” which is primarily motivated by the ideas of Industry 4.0, has been brought about by the quick development of digital technologies. The goal of this technology revolution is to develop intelligent, adaptive, and networked production systems that react instantly to shifting supply, demand, and operating circumstances. The Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), cyber-physical systems (CPS), big …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 1, 2025 · pp. 31–36 Read article
-
A Detailed Survey of Machine Learning Applications, Methods, and Future Prospects in Agriculture
Abstract: Agriculture is undergoing a digital transformation driven by machine learning (ML) and artificial intelligence. The integration of ML techniques with data from sensors, drones, satellites, and IoT devices has enabled precision agriculture, early disease detection, optimized resource use, and improved yield prediction. This paper presents a comprehensive review of machine learning applications in modern agriculture, covering key areas such as crop monitoring, soil analysis, irrigation scheduling, pest, and disease detection, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 39–45 Read article
-
Smart Education in the Context of Puducherry India
Abstract: This paper explores the concept of smart education and presents its conceptual framework in the context of Puducherry. It aims to enhance the understanding of smart education by analysing its fundamental components, including educational challenges, technological innovations, management strategies, policy frameworks, historical evolution, and emerging trends. The adoption of smart education has accelerated significantly in recent years, particularly during the COVID-19 pandemic, when educational institutions worldwide transitioned from traditional classroom-based …
Published in Emerging Trends in Languages · Vol. 2, Issue 2, 2025 · pp. 10–17 Read article
-
Reduce Traffic Congestion Using Automated Traffic Navigation System
Abstract: The concept of activity routing without reliance on traditional activity signals is gaining significant traction. This innovative approach aims to enhance urban vehicular movement by eliminating the need for conventional traffic signal systems. This summary delves into the intricate realm of signal-free activity routing, incorporating advanced technologies such as artificial intelligence, machine learning, and sensor networks. The benefits, including reduced congestion, increased fuel efficiency, and improved traffic flow, are thoroughly …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 34–40 Read article
-
AI-Driven Multi-Objective Optimization of Conductive Polymer Composites for High-Performance Flexible Electronics
Abstract: The development of conductive polymer composites (CPCs) is critical for advancing flexible and wearable electronic technologies. However, the conventional trial-and-error approach to material formulation is time-consuming and often inefficient due to the high-dimensional nature of the design space. This study introduces a novel AI-driven framework that integrates machine learning (ML) with multi-objective optimization to accelerate the discovery of high-performance CPCs. A dataset of 1,000 experimentally reported formulations was compiled, capturing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 734–745 Read article