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581 articles for “Machine intelligence”
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The AI Revolution: Transforming Business Decision-Making
Abstract: Industries undergo a transformation thanks to artificial intelligence, which makes machines capable of activities that previously required human intelligence. This interdisciplinary field of computer science models human thought processes, impacting sectors from autonomous vehicles to creative AI tools. Integrating AI into business operations transforms decision-making and enhances corporate performance. AI-driven methodologies analyze vast datasets to provide valuable insights and facilitate decisions beyond human capability. Predictive modeling anticipates consumer behavior, market …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 2, 2024 · pp. 25–32 Read article
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A Comprehensive Review of AI-Driven Strategies for Tailored Wellness and Dietary Recommendations
Abstract: In today’s fast-paced world, health and fitness have become top priorities for many individuals. As a result, people increasingly turn to mobile apps and digital tools to track their wellness goals, follow diet plans, and stay fit. However, most of these apps provide the same set of recommendations for all users, ignoring the fact that everyone has different needs. This one-size-fits-all approach often fails to keep users engaged and motivated, …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 16–20 Read article
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Development of Smart Cooling Optimization System for CNC Machining Applications
Abstract: In modern manufacturing industries, achieving high machining accuracy, improved surface finish, and extended tool life remains a significant challenge, particularly during the machining of hard materials where excessive heat generation at the tool–workpiece interface is inevitable. Conventional coolant systems often suffer from limitations such as manual control, inconsistent flow rates, and inefficient coolant usage, which negatively impact productivity and environmental sustainability. This paper presents the design and development of an …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 2, 2026 · pp. 1–13 Read article
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Identification of Papaya Fruit Ripening Process Using AI
Abstract: Identifying the ripening process of papaya fruit using artificial intelligence involves employing machine learning algorithms to analyze various features such as color changes, texture alterations and chemical compositions. This model is capable of analyzing visual cues to determine the stage of ripeness. The dataset compares images of papaya at various ripening stages, and our AI model demonstrated high accuracy in classifying these stages. Employing machine learning algorithms and image processing …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 13, Issue 2, 2024 · pp. 23–30 Read article
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Harnessing Shell Scripting for Autonomous System Management: A Vision for the Future
Abstract: As IT systems become increasingly complex, the demand for efficient and automated management solutions is more critical than ever. This paper investigates the pivotal role of shell scripting in the development of autonomous systems that can self-manage and optimize their operations. Shell scripting, with its powerful automation capabilities, serves as a foundational tool for orchestrating various tasks, including system monitoring, data analysis, and deployment processes. We begin by examining current …
Published in Journal of Advances in Shell Programming · Vol. 11, Issue 3, 2024 · pp. 17–31 Read article
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Role of Machine Vision in Autonomous Vehicles: A Review
Abstract: The integration of machine vision in autonomous vehicles (AVs) is a critical advancement in the field of intelligent transportation systems. Machine vision systems enable AVs to perceive their environment, understand road conditions, detect obstacles, and make real-time decisions necessary for safe navigation. These systems rely heavily on image processing techniques, which have evolved significantly over the past decade, leading to improved performance in complex driving scenarios. These developments are largely …
Published in Trends in Machine design · Vol. 12, Issue 1, 2025 · pp. 38–43 Read article
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War Between Robots and Humans: Evolution of Robots and Disasters Associated with Them
Abstract: Robotics and artificial intelligence (AI) have transformed the landscape of technology, allowing machines to take on roles that were previously thought to require human intelligence and skill. From industrial automation to military applications, the integration of intelligent robots into human society presents unprecedented benefits and equally significant risks. This paper investigates the historical evolution of robotics, the deepening human dependency on machines, and the emerging threats that suggest a potential …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 2, 2025 · pp. 44–51 Read article
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Revolutionizing Wireless Communication: AI & ; ML in the Era of 6G
Abstract: With rapid technological advancement, sophisticated techniques are significantly enhancing the performance of wireless networks. In parallel, the growth of artificial intelligence (AI) has empowered systems to perform intelligent decision-making, automate processes, analyze data, generate insights, and predict future outcomes. AI systems are now capable of learning and adapting to dynamic environments. Particularly, machine learning and deep learning techniques have achieved remarkable success across a wide range of applications in recent …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 3, 2025 · pp. 29–36 Read article
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AI for Cybersecurity: Deploying Machine Learning for Network Traffic Anomaly Detection
Abstract: The growing sophistication of cyberattacks and the growth of network traffic necessitate sophisticated anomaly detection methods. This study overviews the use of artificial intelligence (AI) and machine learning (ML) to counter these challenges, as noted in current studies. It analyses supervised learning (SVM, Decision Trees), unsupervised learning (K-means, DBSCAN), and deep learning (CNNs, RNNs, Auto-encoders) approaches, considering their strengths and weaknesses. The research integrates current developments in AI/ML-based network anomaly …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article
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Integrating AI and ML in Tribology: A Review of Current Trends and Future Prospects
Abstract: This review paper explores the growing integration of artificial intelligence (AI) and machine learning (ML) within the field of tribology. Tribology, the study of friction, wear, and lubrication, is crucial for Improving the performance and longevity of mechanical systems. This review explores the role of AI and machine learning techniques, including artificial neural networks (ANNs), support vector machines (SVMs), and physics-informed machine learning (PIML)can be used to solve difficult tribological …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 56–60 Read article
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Artificial Intelligence–Driven Decision Support Systems for Smart and Efficient Data Analysis
Abstract: Artificial Intelligence (AI) has emerged as a transformative technology reshaping the way organizations process information, analyze data, and support decision-making. With the rapid growth of digital data across sectors, traditional analytical methods often face limitations in handling large, complex, and dynamic datasets. AI-based techniques, particularly machine learning and intelligent decision support systems, provide advanced capabilities for identifying hidden patterns, predicting outcomes, and assisting in data-driven decisions. This paper examines the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 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
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A Review of Torque Ripple Reduction Techniques in Switched Reluctance Motors
Abstract: Switched Reluctance Motors (SRMs) have emerged as a promising alternative to conventional motor technologies due to their rugged structure, low manufacturing cost, high-temperature capability, and suitability for harsh environments. Despite these advantages, the widespread adoption of SRMs in applications such as electric vehicles, household appliances, industrial drives, and aerospace systems is significantly restricted by the issue of torque ripple. Torque ripple manifests as periodic fluctuations in the developed electromagnetic torque, …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 45–50 Read article
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GenChrome-ML: A Machine Learning Framework for Early Detection of Chromosomal Disorders Using Genomic Data
Abstract: The increasing burden of chronic disease and cancer demands innovative, more rapid and effective diagnostic tools in the field of healthcare. The majority of current diagnostic tools are dependent upon clinical symptomology and manual evaluation, leading to delays in early detection and treatment. The development of artificial intelligence (AI) and machine learning (ML), in recent years, has offered opportunities for the enhancement of disease prediction, diagnosis and personalization of treatment …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Leveraging AI and Machine Learning for Early Prediction and Prevention of Non- Communicable Diseases in Resource-Limited Settings
Abstract: Populations in these regions face persistent structural barriers, such as underdeveloped healthcare infrastructure, shortages of trained health professionals, and fragmented or incomplete health information systems. These limitations delay timely diagnosis, restrict access to preventive care, and compromise effective disease management. In recent years, rapid progress in artificial intelligence (AI) and machine learning (ML) has opened promising avenues to mitigate these challenges. Practical applications already emerging include mobile health platforms for …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 1, 2026 · pp. 9–15 Read article
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Machine Learning-Based Quantification of Polymer Structure Property Relationships for Predictive Material Design
Abstract: Polymer structures exhibit complex, hierarchical arrangements that strongly influence macroscopic properties, yet consistent quantification remains challenging due to nonlinear interactions and limited unified modeling strategies. Existing approaches inadequately capture generalized structure–property mappings across diverse polymer systems. This research aims to establish a machine learning-based quantification model for polymer structure–property relationships to support predictive material design. A Polymer Structure Property Dataset of 5,000 polymer samples includes structural descriptors and experimentally measured …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 737–754 Read article
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Failed Component Image Acquisition Quality Optimization for Machine Vision System
Abstract: AbstractWith the rapid development of the global semiconductor industry, electronic products are required to have new ideas, diversified functions, and thinness and shortness. The ball grid array (BGA) packaging technique arranges solder balls in a matrix mode on the bottom of the component substrate, so as to increase the functional density. The dye stain test is extensively used for array component failure analysis; however, the operation takes time and extends …
Published in Current Trends in Signal Processing · Vol. 10, Issue 2, 2020 · pp. 17–25 Read article
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Machine Learning Revolutionizing Server Management and Performance
Abstract: The modern data center is a complex and dynamic environment, grappling with ever-increasing workloads, stringent performance demands, and the constant pressure for cost optimization. As such, applying machine learning (ML) directly to the server infrastructure offers a powerful avenue for achieving advanced automation, resource optimization, and proactive problem resolution. This article explores the transformative potential of integrating machine learning into server systems, leveraging insights gleaned from the abstract and conclusion …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 36–44 Read article
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Role of Artificial Intelligence in Quantum Materials Research
Abstract: Quantum materials have emerged as a transformative class of advanced materials due to their extraordinary electronic, magnetic, optical, and topological properties governed by quantum mechanical phenomena. These materials are expected to revolutionize next-generation technologies such as quantum computing, spintronics, superconducting electronics, nanoelectronics, intelligent sensing systems, and energy-efficient devices. However, conventional methods for discovering and optimizing quantum materials are often expensive, time-consuming, and computationally intensive because of the enormous complexity of …
Published in Journal of Materials & Metallurgical Engineering · Vol. 16, Issue 2, 2026 · pp. 13–27 Read article
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Applications of Artificial Intelligence in Agriculture
Abstract: Every day, farms produce thousands of information points on temperature, soil, usage of water, atmospheric phenomenon, etc. With the assistance of computer science and machine learning models, this data is leveraged in real-time for obtaining useful insights like choosing the correct time to plant seeds, determining the crop choices, hybrid seed choices etc.Keywords: Artificial intelligence, agriculture robots, agriculture, intelligent spraying, temperature, soil, water, machine learningCite this Article G. Ramachandran, T. …
Published in Journal of Computer Technology & Applications · Vol. 11, Issue 1, 2020 · pp. 1–3 Read article