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328 articles for “Machine learning(ML)”
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Emerging Trends in 5G and Beyond-5G Wireless Networks
Abstract: Wireless networks have evolved in the blink of an eye from 4G to 5G and are progressing towards beyond-5G (B5G) frameworks, leading to revolutionary changes in connectivity, speed, and network smarts. This review discusses trending features, challenges, and future trends of 5G and B5G wireless communications technologies. It presents chief goals of 5G, such as ultra-low latency, high spectral efficiency, massive machine-type communication, and up to 10 Gbps user data …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 3, 2025 · pp. 11–19 Read article
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IOT and algorithmic intelligent motor health monitoring as well as maintenance prediction
Abstract: Manufacturing, transportation, and energy systems rely largely on industrial electric motors, and their untimely failure can result in expensive downtime, safety hazards, and decreased operational efficiency. The majority of traditional motor maintenance procedures rely on reactive methods or routine inspections, which frequently miss early-stage problems and lead to needless maintenance or unexpected breakdowns. This project offers an Intelligent Motor Health Monitoring and Predictive Maintenance System that combines Internet of Things …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 28–37 Read article
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Limits to Knowledge-Sharing by Computers
Abstract: The rapid advancement of artificial intelligence (AI) and machine learning (ML) has significantly enhanced the capabilities of computers in processing, analyzing, and disseminating knowledge. However, despite these advancements, there are inherent limits to the extent that knowledge-sharing can be fully realized through computer systems. This study explores the various barriers that hinder the effective sharing and transfer of knowledge through machines, including technological limitations, ethical concerns, and the complexities of …
Published in Current Trends in Information Technology · Vol. 15, Issue 2, 2025 · pp. 01–05 Read article
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AI-Driven Intelligent Energy Management System for Enhancing Electric Vehicle Efficiency and Range
Abstract: Electric Vehicles (EVs) are crucial in mitigating the emission of greenhouse gases and facilitating sustainable transportation. Their performance is however limited by the capacity of the battery, unpredictable weather conditions and ineffective use of energy. The paper suggests an AI-based Intelligent Energy Management System (IEMS) to increase EV efficiency and driving range. The suggested system combines machine learning (ML), model predictive control (MPC), and real-time data analytics to optimize power …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 2, 2026 Read article
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An innovative antibiotic "Abaucin": Instigated by Artificial Intelligence
Abstract: Nosocomial Gram-negative pathogen, Acinetobacter baumannii repeatedly demonstrates multidrug resistance. Discovering novel antibiotics against A. baumannii has proven thought-provoking through conventional screening tactics. Providentially, machine learning approaches allow for the speedy exploration of chemical space, snowballing the probability of determining new antibacterial molecules. In the following research era, a neural network is accomplished with growth reserve dataset and accomplished in silico predictions for structurally unconventional molecules with commotion in divergence to …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 13, Issue 3, 2023 · pp. 29–33 Read article
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AI and Big Data for Optimized Water Resource Management in Arid Regions
Abstract: Water scarcity in arid regions is an escalating global challenge, driven by climate change, population growth, and increasing demands from urban, industrial, and agricultural sectors. Effective water resource management (WRM) is crucial for sustaining livelihoods, economic stability, and infrastructure resilience. Emerging technologies such as artificial intelligence (AI), machine learning (ML), and big data offer innovative solutions for optimizing water use, enhancing efficiency, and improving sustainability in water-scarce environments. This paper …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 1–5 Read article
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Smart Education through Machine Learning: A Review of Trends, Benefits, and Risks
Abstract: Machine learning (ML) is transforming the contemporary education by transforming it into smarter, data-driven and personalised learning. This review examines the key tendencies, advantages, and possible threats of applying ML in intelligent education. ML promotes adaptive learning, automatization of assessments, and student engagement, which is highly beneficial both to learners and educators. Nonetheless, issues like data privacy, algorithmic bias or unequal access are also a significant concern. The article emphasises …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 · pp. 24–28 Read article
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Virtual Assistant: JarvisAI Using Natural Language Processing
Abstract: This research presents the development of a voice-interactive virtual assistant built upon the JarvisAI framework, integrating advanced technologies such as Natural Language Processing (NLP), Machine Learning (ML), and Speech Recognition. The goal is to enable seamless and intuitive human-computer interaction by allowing users to communicate through natural spoken and written language. The assistant is designed to understand, interpret, and respond to various user commands, aiding in tasks such as information …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 26–39 Read article
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Novel Strategic Framework for AI-Driven Discovery and Development of Smart and Sustainable Polymers in Healthcare
Abstract: The development of new smart and sustainable polymers is emerging as a priority of new health care innovative development, but event before it may be actualized, the usual culprit is the delay and unproductive execution of the old-fashioned R&D efforts. The current paper proposes a strategic plan which will solve all these shortcomings and speed up the material discovery process by using Artificial Intelligence (AI) and Machine Learning (ML). The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1535–1550 Read article
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AI-Driven Prediction of Mechanical and Thermal Properties in Polymer-Based Functionally Graded Composites
Abstract: The proposed architecture of the current paper is an artificial intelligence (AI)-driven model of forecasting mechanical and thermal aspects of polymer-based functionally-graded composites (FGCs). Traditional micromechanical and finite element models, which are practical in homogeneous composites, might not be able to account in nonlinear interaction that is caused by compositional gradient. To overcome the challenge, machine learning (ML) models like artificial neural network (ANN), support vectors regression (SVR), and gradient-boosted …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 70–89 Read article
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Artificial Intelligence Techniques for Smart Polymer Nanocomposite Materials and Industrial Applications
Abstract: Protecting sensitive material data, manufacturing processes, and intelligent monitoring platforms is essential for the fast development of innovative polymer nanocomposite systems in fields such as aerospace, medicine, electronics, automobiles, and energy. In order to safeguard, consistently enhance, and optimize distributed industrial systems that consist of polymer nanocomposite materials, this study presents an AI-driven cybersecurity and cloud computing architecture. The suggested solution employs artificial intelligence (AI), machine learning (ML), cloud computing, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1109–1134 Read article
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Revolutionizing Product Marketing: Harnessing the Power of AI/ML
Abstract: The rapid convergence of artificial intelligence (AI) and machine learning (ML) technologies in marketing has ushered in a new era of product promotion and engagement. This study delves into the many ways in which AI/ML can revolutionize product marketing strategies, showing a comprehensive range of methods and tools available. The presented high-level architecture illustrates the interconnectedness of AI-based marketing components, ranging from personalized recommendations and chatbots to sentiment analysis and …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 3, 2023 · pp. 45–52 Read article
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The Influence of Artificial Intelligence on Literary Criticism
Abstract: Artificial Intelligence (AI) has emerged as a significant force in reshaping contemporary literary criticism. Traditionally, the interpretation of literature has relied primarily on human-centered methods such as close reading, contextual analysis, and theoretical framing. However, the integration of AI-based techniques including Natural Language Processing (NLP), Machine Learning (ML), stylometry, and sentiment analysis has introduced new possibilities for examining literary texts at both micro and macro levels. These computational approaches allow …
Published in International Journal of Trends in Humanities · Vol. 3, Issue 2, 2026 · pp. 22–29 Read article
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AI-Driven Handwriting Identification and Verification Using Textural Features
Abstract: The last few decades have seen handwriting recognition and verification earn their mark in areas like forensics, healthcare, education, and digital security. This study delves into the role of artificial intelligence (AI), machine learning (ML), and deep learning techniques in handwriting analysis. It highlights the extraction of textural features as a precursor to identifying narrows between original handwriting and its forgery, whereby a few distinctive patterns such as stroke width, …
Published in International Journal of Electronics Automation · Vol. 3, Issue 1, 2025 · pp. 35–44 Read article
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A Review of AI-Based Intrusion Detection Systems for Mobile Ad Hoc Networks (MANETs)
Abstract: Mobile Ad Hoc Networks (MANETs) comprise wireless networks that lack any conventional infrastructure . Their chief features include highly changing network topologies, lack of centralized administration, and open nature of communication, which collectively result in making MANETs of the wireless kind very susceptible to a diverse range of cyber-attacks like blackhole, greyhole, wormhole, flooding, Sybil and denial-of-service (DoS) among others. Conventionally, Intrusion Detection Systems (IDS) relying on static rule-based methods …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Improving Polymer Composite Properties Through Reinforcement Learning Guided Prototyping A Novel Approach for Material Engineering
Abstract: Innovative approaches integrating reinforcement learning (RL) and machine learning (ML) into the fields of polymer composite prototyping and soft actuator manufacturing for applications. This new an algorithm utilizing RL optimizes polymer composite fabrication parameters to enhance material properties efficiently. By iteratively adjusting parameters based on predefined objectives, the RL agent guides the prototyping process, promising to revolutionize polymer composite engineering. A finest control method for locked loop control of Shape …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 208–218 Read article
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APPLICATION OF ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY
Abstract: The application of artificial intelligence (AI) in medicine, especially through machine learning (ML), is revolutionizing new-age drug discovery research. AI is found as an efficient and powerful tool to narrow the gap between disease detection and developing and identifying potential therapeutic agents for a cure. This review provides a summary of the latest developments in AI and its potential application in drug discovery for untreatable diseases. The review also examines …
Published in Emerging Trends in Chemical Engineering · Vol. 12, Issue 3, 2025 · pp. 22–29 Read article
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Multimodal Disease Detection Using Deep Learning
Abstract: Artificial Intelligence (AI) is playing an increasingly pivotal role in modern healthcare, particularly in improving the speed and accuracy of disease detection. With the evolution of Machine Learning (ML), Deep Learning (DL), and high-performance computing, AI-based solutions are now capable of processing extensive medical datasets, ranging from patient records to diagnostic images, with remarkable efficiency. These systems offer immense potential for early intervention, improved clinical decision-making, and alleviating pressure on …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 129–139 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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The Impact of Artificial Intelligence on the Sales and Marketing of Pharmaceutical Products
Abstract: The rapid development of computing and technology has permeated all branches of science, with artificial intelligence (AI) emerging as a pivotal field in computer science. AI has significantly influenced disciplines ranging from basic engineering to pharmaceuticals. In healthcare and medicinal chemistry, AI applications have become indispensable. Traditional drug discovery approaches are gradually being overtaken by computer-aided drug design. In recent years, artificial intelligence (AI) and machine learning (ML) have become …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 1, 2025 · pp. 10–18 Read article