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270 articles for “adaptive machine learning”
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AI – Driven Smart Laboratory for Synthetic Organic Chemistry – A Literature Review
Abstract: The traditional chemistry laboratory is often subjective, time consuming and skill intensive that may lead to inconsistencies in the desired results. The advent of Artificial Intelligence (AI) and its speedy incorporation into the field of chemistry is transforming traditional synthetic laboratories into intelligent, automated systems that combine hardware, software and AI into a unified framework. This paper presents a comprehensive overview of AI – driven laboratory setup for organic synthesis, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Development of Neuromorphic Polymer Composites Using IoT Sensing and Brain-Inspired Learning Algorithms
Abstract: This research aims to develop neuromorphic polymer composites by combining conductive sensing materials, IoT-based sensing data collection and brain-inspired learning models for adaptive response. Hybrid conductive polymer composites were developed by adding carbon nanofibers and graphene Nano platelets to a thermoplastic polymer. IoT sensors (strain, temperature) were employed to collect real-time sensing data that was combined with environmental data. A material-aware neuromorphic learning algorithm was created with event-driven spike coding …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 755–784 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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Wireless Biosensing Polymer Composites for Smart Healthcare Devices
Abstract: The wireless biosensing polymer composites have been found as one of the possible solutions in developing flexible, real-time and intelligent healthcare monitoring systems. Biomimic polymer matrices coupled with conductive nanomaterials can be used to design an understanding of physiological signals (strain, pressure, and temperature) that are highly sensitive and adaptable sensors. The attachment of these sensors to wireless communication systems, such as the Bluetooth Low Energy and Wi-Fi, eases the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 14, 2026 Read article
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AI-Optimized Itinerary Design: Transforming the Future of Travel Planning
Abstract: The travel industry is struggling to meet the rising demand for efficient and personalized trip planning. Traditional methods often lack real-time updates and fail to adapt to individual preferences, necessitating innovative solutions. This study presents an AI-powered travel planner utilizing the Gemini API to enhance itinerary creation. By analyzing user preferences, interests, and real-time data, the system delivers tailored travel recommendations. Leveraging advanced technologies such as cloud computing, machine learning, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 74–82 Read article
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Overview AI-Driven Antenna Technologies and Privacy- Preserving Methods for Next-Generation 6G Wireless Systems
Abstract: The next generation of wireless communications, 6G, will be built on the convergence of artificial intelligence (AI) and advanced antenna systems. AI-driven antennas are poised to address the unprecedented requirements for data rate, reliability, adaptability, and ubiquity in future networks. An overview of current advancements in AI-enabled antenna systems for 6G networks is provided in this study. From traditional base station deployments to distributed, cell-free, and user-centric frameworks, it examines …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 1, 2026 · pp. 28–34 Read article
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Navigating Higher Education: Investigating the Efficacy of College Enquiry Chatbots
Abstract: College Enquiry A chatbot is a kind of online application, and this project's primary goal is to give information about colleges. It only provides information on colleges. Something along the lines of "How many branches in college? "How many pupils are in each branch? "By adding some more features and making some improvements we can embed this project into the working site of the college. A chatbot is a software …
Published in Journal of Instrumentation Technology & Innovations · Vol. 13, Issue 3, 2023 · pp. 7–11 Read article
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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
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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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AI-Based Threat Detection in Cloud Platforms
Abstract: This research work delves into the transformative role AI has come to assume for enhanced threat detection in the cloud ecosystem. The conventional security frameworks, which form the basis for many architectures, are several steps behind actualizing the rapidly evolving cyber threat landscape, exposing critical weaknesses in the areas of accuracy, adaptability, and speed of response. Initially, the study sets forth the problems with the old-school approaches to threat detection …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 01–10 Read article
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Human Following Robot Using Arduino Uno
Abstract: A human-following robot is a mobile autonomous system designed to detect, track, and follow a specific individual in real-time while navigating through dynamic environments. This feature is essential for various applications, including delivery services, healthcare assistance, personal support, and collaborative industrial operations. It enhances efficiency, safety, and user experience by enabling intelligent and responsive interactions, making it an asset in both commercial and personal environments. The robot integrates cameras, LiDAR, …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 3, 2025 · pp. 26–31 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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Federated Learning Framework for Sustainable Multi-Scale Design of Recyclable Thermoplastic Graphene Composites in Smart Manufacturing Environments
Abstract: The growing demand for sustainable advanced materials has accelerated the development of recyclable thermoplastic graphene composites for next-generation smart manufacturing systems. The typical central optimization methods have challenges with data privacy, scalability, and poor collaboration between distributed manufacturing sites. By combining material informatics, edge intelligence and distributed artificial intelligence, this study introduces a Federated Learning (FL) framework to design recyclable thermoplastic graphene composites at multiple scales sustainably. The proposed framework …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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AI-Driven Prediction of Square-Hole Laser Trepanning Performance in AA7075/15%SiC/15% Glass Fiber Hybrid Composites Using Taguchi–ANOVA and Deep Neural Networks
Abstract: Hybrid AA7075 composites reinforced with 15% silicon carbide (SiC) and 15% glass fiber were fabricated via the stir casting technique to improve machining and structural performance. The addition of dual reinforcements into the aluminum matrix was aimed at enhancing hardness, thermal stability, and surface quality during non-traditional drilling operations. Square-hole drilling was performed using a laser trepanning process, and the key responses—hole size accuracy, surface roughness, and taper angle—were systematically …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1932–1943 Read article
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The Future of Electronic Communication Systems in the Digital Age
Abstract: Electronic communication networks underpin modern society, offering seamless interaction across geographical, social, and economic borders. These systems are transforming into faster, more reliable, and smarter ones as digital technologies improve. This article discusses the future of Electronic Communication Systems in the context of 5G Technology, IoT, AI, and Quantum Communication. These technologies should revolutionise data transfer by increasing capacity, lowering latency, and enabling real-time communication across platforms. Due to need …
Published in Recent Trends in Electronics Communication Systems · Vol. 13, Issue 1, 2026 · pp. 39–48 Read article
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Develop the Design of Sustainable Polymer Materials: Applying Reinforcement Learning, IoT-Enabled Monitoring, and Data-Driven Manufacturing Approaches
Abstract: Sustainable polymer materials development is a must due to resource constraints, environmental concerns, and the demand for designed materials with high performance. When it comes to material optimization, energy utilization, process unpredictability, and lifecycle sustainability, traditional polymer production methods have their challenges. Reinforcement Learning (RL), Internet of Things (IoT) monitoring, and data-driven production are utilized in the design and manufacturing of sustainable polymer materials. It is recommended to use Internet …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1207–1231 Read article
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Photochemical Materials for Light-responsive Optical Switching: AI-optimized Design of Dynamic Visual Effects
Abstract: This paper presents an in-depth investigation into the design and behavior of photochemical materials that generate optical illusions and dynamic visual effects through light-induced molecular transformations. The study focuses on advanced photoresponsive compounds such as azobenzene and spiropyran derivatives, emphasizing their reversible optical transitions governed by photoisomerization, phase transitions, and photochromism in solid-state and polymeric matrices. Spectroscopic and kinetic analyses are employed to evaluate the influence of light wavelength, material …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 3, Issue 2, 2025 · pp. 13–27 Read article
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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
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Exploring the Landscape of Big Data: Impact, Tools, Challenges, and Opportunities
Abstract: This study explores the constantly changing field of big data, not merely as a repository of enormous amounts of information, but also as a force that is reshaping our world. It sheds light on the ways in which big data stimulates creativity and drives change in a variety of sectors, including urban planning, finance, healthcare, and environmental sustainability. Through the investigation of state-of-the-art analytics, distributed computing, and data visualization tools, …
Published in Current Trends in Information Technology · Vol. 14, Issue 1, 2024 · pp. 1–4 Read article
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An Enhanced Application Oriented Predictive Analytic using Optimal Deep Learning Model
Abstract: In order to presents better Predictiveanalytic models of different data using various machine learning algorithms. The data prediction is developed on various applications. These applications are facing many challenges while collecting data and data selection etc. The proposed prediction model involves several phases like (a) Data acquisition, (b) Data cleaning, (c) Data normalization, (d) Optimal Feature selection, and (e) Prediction. The optimal feature selection will be accomplished by a new …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 7, Issue 2, 2020 · pp. 5–10 Read article