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170 articles for “Artificial intelligence”
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Unlocking the Potential: Machine Learning Driven Explainable AI Applications Across Diverse Domains
Abstract: Explainable artificial intelligence (XAI) aims to make discoveries and output generated by machine learning algorithms accessible to human users in a trustworthy and easy-to-understand manner. It describes the impact of an AI model and any potential biases, helping in characterizing models with accuracy, fairness, transparency, and outcomes in decision-making powered by AI. XAI focuses on understanding the data used to train the model, its predictions, the specific elements involved in …
Published in International Journal of Software Computing and Testing · Vol. 9, Issue 1, 2023 · pp. 24–32 Read article
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An Overview on AI in Thermal Behaviour of Polymers
Abstract: The integration of Artificial Intelligence (AI) and Machine Learning (ML) into the thermalanalysis of polymers and composite materials has transitioned from experimental curiosity to acornerstone of material science. By replacing costly and time-consuming trial-and-errorlaboratory testing with predictive modeling, AI is accelerating the development of advancedthermal interface materials, fire-retardant polymers, and aerospace-grade composites. Theprediction and optimization of the thermal behavior of polymers and composite materialsrepresent a cornerstone of modern materials science, …
Published in International Journal of Composite and Constituent Materials · Vol. 12, Issue 1, 2026 · pp. 12–16 Read article
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CyberSentinel: A Proposed Hybrid AI Framework for Real-Time Cyber Threat Intelligence
Abstract: Modern cyberattacks have grown far more sophisticated, frequent, and fast-moving than the signature-based intrusion detection systems many organizations still rely on. This paper proposes CyberSentinel, a hybrid artificial intelligence framework for real-time cyber threat intelligence (CTI) that combines three complementary techniques into a single detection pipeline: a Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) module for network traffic anomaly detection, a Random Forest ensemble for structured log classification, and a transformer-based …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 2, 2026 Read article
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From Cloud to Edge–The Comprehensive Impact ofEdge AI
Abstract: By bridging the divide between localized device intelligence and centralized cloud computing, edge artificial intelligence (AI) can transform existing businesses and social paradigms. Extreme real-time data processing, enhanced privacy, and decreased latency are among the capabilities. To comprehend how edge AI interacts with hybrid systems that result in full integration with cloud computing, this paper thoroughly examines the whole architecture and important technologies utilized in this technology. Autonomous driving, smart …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 1, 2026 · pp. 1–13 Read article
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Evaluation of Two Distinct AI Control Methods to Enhance Power Quality
Abstract: Artificial Intelligence techniques are the latest techniques utilized for the improvement of electrical performance. This study examines and contrasts various artificial harmonic reduction methods for source current. Artificial Intelligence may include Fuzzy logic and Artificial Neural Network. The goal of the modeling is to improve the power quality through the application of principles that cannot be expressed as "true" or "false" but rather as "partially true" called as Fuzzy logic …
Published in International Journal of Electrical Power System and Technology · Vol. 8, Issue 2, 2022 · pp. 15–26 Read article
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Optimizing Internal Combustion Engine Performance and Fleet Fuel Economy through Machine Learning and AI using Big Data Analytics
Abstract: Abstract This paper presents a software-defined operational intelligence approach for optimizing internal combustion engine performance and fleet fuel economy using Big Data Analytics combined with Machine Learning and Artificial Intelligence. Real-world vehicle data is transformed into engineered features and virtual sensing outputs to estimate fuel consumption, driver behaviour, and component health without additional hardware. The proposed system integrates fuel optimization, predictive maintenance, driver assistance, and sustainability assessment into a unified …
Published in International Journal of I.C. Engines and Gas Turbines · Vol. 12, Issue 1, 2026 · pp. 1–7 Read article
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Health Monitoring System for Fault Identification on Centrifugal Pump Using ML
Abstract: Centrifugal pumps are crucial equipment widely used in various industries, and their reliable operation is essential for maintaining production and preventing costly downtimes. This paper proposes a comprehensive health monitoring system for centrifugal pumps that combines model-driven and data- driven approaches, leveraging artificial intelligence (AI) and machine learning (ML) techniques. The system incorporates demand prediction using artificial neural networks and fault diagnosis employing different ML classifiers, such as decision trees …
Published in International Journal of Mechanics and Design · Vol. 10, Issue 2, 2024 · pp. 1–12 Read article
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Biosensors Powered by Nanotechnology forContinuous Insulin Delivery and GlucoseMonitoring in Diabetes Management
Abstract: Diabetes mellitus is a chronic metabolic disorder that necessitates continuous glucose monitoring and precise insulin delivery for effective management. Traditional methods often fall short in maintaining the necessary levels of accuracy and convenience, thereby posing challenges in achieving optimal glycemic control. Nanotechnology-enabled biosensors have revolutionized this field by leveraging the unique properties of nanomaterials, offering significant improvements in sensitivity, selectivity, and biocompatibility. This article delves deeply into the transformative role …
Published in International Journal of Applied Nanotechnology · Vol. 10, Issue 1, 2024 · pp. 13–24 Read article
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Genre Classification of Music Using Machine Learning
Abstract: One of the most important technological advances of the 21st century is artificial intelligence (AI) and machine learning. They are revolutionizing computers, banking, healthcare, agriculture, music and travel. A strong model has mastered many difficult learning tasks. Speech analysis is one area of artificial intelligence. This includes finding information about music, creating music, and categorizing music. Music data is one of the most complex source data available today. This is …
Published in International Journal of Distributed Computing and Technology · Vol. 8, Issue 2, 2022 · pp. 17–28 Read article
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A Study on AI in 7G Mobile Communication
Abstract: The imminent transition from 5G to the seventhgeneration (7G) mobile ecosystem promises to redefine connectivity through unprecedented data rates, pervasive ultralow latency, and holistic integration of terrestrial, aerial, and spaceborne networks. Central to this evolution is Artificial Intelligence (AI), which is poised to become the nervous system that orchestrates, optimizes, and secures the hyperdynamic 7G fabric. This paper surveys the emerging AIdriven paradigms that will underpin 7G, focusing on three …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 1, 2026 · pp. 29–39 Read article
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AI-Based Fraud Detection in Financial Transactions
Abstract: Financial fraud continues to pose a severe danger to individuals, businesses, and the global economy, necessitating the development of effective and innovative detection and prevention approaches. This research study examines the use of artificial intelligence (AI) techniques to detect fraudulent conduct in financial transactions. This paper investigates the advancements, challenges, and courses of AI-based fraud detection in financial transactions through a thorough examination of the research, case studies, and practical …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 10, Issue 1, 2024 · pp. 1–9 Read article
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Impact of AI in HRM Practicing Job Satisfaction in Any other Hospital
Abstract: Artificial Intelligence (AI) is becoming more prevalent in organizations, presenting both opportunities and challenges for Human Resource Management (HRM). The integration of AI in HRM reflects the dual potential for advancement and complexities within organizational dynamics. Striking a balance in leveraging AI's benefits while addressing its challenges is crucial for effective HRM. In the medical field, Artificial Intelligence (AI) in hospitals involves the application of advanced computational algorithms and machine …
Published in International Journal of Broadband Cellular Communication · Vol. 9, Issue 2, 2023 · pp. 18–26 Read article
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AI-Based Noise Reduction Techniques for Digital and Analog Communication Systems
Abstract: Noise is one of the major challenges in modern communication systems because it significantly affects signal quality, transmission efficiency, and overall system reliability. Both digital and analog communication systems are influenced by different types of noise such as thermal noise, impulse noise, quantization noise, atmospheric noise, and channel interference. Conventional noise reduction techniques including filtering, adaptive equalization, and statistical signal processing have been extensively used to improve communication performance. However, …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 1, 2026 · pp. 40–48 Read article
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Improved Programming Model Using AI: Shifting from Imperative Coding to Declarative Intent
Abstract: The contemporary software development lifecycle is burdened by significant cognitive friction, characterized by high demands for syntax recall, boilerplate management, and painstaking manual debugging. This paper proposes and examines a novel programming model built upon deeply embedded artificial intelligence, moving beyond simple code completion tools to establish a truly intent-based, declarative development environment. The proposed model leverages specialized large language models and domain-specific generative agents (Cognitive Programming Assistants, or CPAs) …
Published in International Journal of Software Computing and Testing · Vol. 11, Issue 2, 2025 · pp. 1–9 Read article
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A Review of Energy-Efficient Base StationManagement in Heterogeneous Cellular Networks
Abstract: The amount of energy used of cellular networks for communication has dramatically grown due to the quick expansion of mobile data usage and the extensive use of next-generation wireless technologies. Among various network components, base stations account for the largest share of power usage, making energy-efficient management an important research area in heterogeneous cellular networks (HetNets). This review paper presents a comprehensive overview of recent developments in energy-efficient base station …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 1, 2026 · pp. 1–13 Read article
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A Comprehensive Review of Smart Parking Systems: Technologies, Challenges, and Future Directions
Abstract: Abstract Smart Parking Systems (SPS) are gaining significant attention as a critical solution to address the growing concerns of urban congestion, inefficient use of parking spaces, and environmental sustainability. This paper presents a comprehensive review of SPS, focusing on the key technologies, challenges, and future directions. We explore the integration of advanced technologies, such as the Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), and sensor networks in …
Published in International Journal of Manufacturing and Materials Processing · Vol. 11, Issue 1, 2025 · pp. 1–13 Read article
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AI-Enabled IV Infusion Monitoring Device for Real-Time Nursing Care Optimization
Abstract: Intravenous (IV) infusion therapy is an essential component of modern healthcare, widely used for administering fluids, medications, and nutrients in clinical settings. However, traditional infusion monitoring methods rely heavily on manual observation by nursing staff, which increases the risk of human error, delayed interventions, and excessive workload. The integration of Artificial Intelligence (AI) into IV infusion systems has introduced a transformative approach to real-time monitoring, predictive analytics, and automated alert …
Published in International Journal of Nursing Critical Care · Vol. 12, Issue 1, 2026 · pp. 10–18 Read article
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Future-Ready Library Buildings: AI and IoT for Equity and Compliance
Abstract: Libraries are buildings presenting unique challenges when integrating different types of spaces under a single roof, like quiet reading spaces, central lobbies, book staging areas, archival rooms, discussion zones, seminar rooms, e-resources labs, etc. These spaces require specialized norms related to construction and involve varied daylighting requirements, anthropometric needs, indoor air environment requirements, and other specific functional needs. Moreover, libraries must follow various requirements mentioned in relevant IS codes, fire …
Published in International Journal of Sustainable Building Technology · Vol. 9, Issue 1, 2026 · pp. 19–24 Read article
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Audio & Video Translate System
Abstract: With the increasing expansion of digital media and globalization, there is a rising need for sophisticated audio and video translation systems to overcome language and cultural barriers. This paper explores the role of these systems in localizing multimedia content, ensuring accessibility, and complying with global standards, including those focused on individuals with disabilities. The research aims to investigate how various translation technologies, such as dubbing, subtitling, and audio descriptions, contribute …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 2, 2025 · pp. 6–12 Read article
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Discovery of Materials through Applied Machine Learning and General Machine Learning Architecture
Abstract: Advances in artificial intelligence technologies, especially machine learning, have generated possibilities in the material sciences to facilitate material exploration and to achieve a profound understanding of the relationship between the constituent elements of the material and the properties represented by the material. The application of machine learning to the exploration of experimental materials is sluggish due to the monetary and temporal costs of experimental data, however parallel methods, such as …
Published in International Journal of Analog Integrated Circuits · Vol. 6, Issue 2, 2020 · pp. 48–57 Read article