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355 articles for “Main frame”
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Enhancing Maintenance Decision-Making in Thermal Power Plants Using Generative AI-Based Fault Diagnosis
Abstract: The growing complexity of operation and power consumption of thermal power stations involve the need to have intelligent fault diagnosis systems that can be used to guarantee reliability and safety in operation. In this research, a Generative AI (GenAI)-based hybrid architecture of early fault detection and predictive maintenance is proposed to improve the decision-making process of the maintenance team. The data-driven analytic approach combines methods of data-driven analytics, Generative AI …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 25–33 Read article
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A Study on Drone Hacking: Vulnerabilities and Mitigation Techniques
Abstract: This paper explores the current cybersecurity landscape surrounding Unmanned Aerial Systems (UAS), commonly known as drones. With rapid growth in commercial and recreational drone use, the risk of cyber-attacks has also increased. This study highlights real-world vulnerabilities such as GPS spoofing, Wi-Fi hijacking, and firmware exploitation. It also suggests practical mitigation techniques, including encryption, real-time anomaly detection using machine learning, and secure communication protocols. The goal is to support researchers, …
Published in International Journal on Drones · Vol. 1, Issue 2, 2025 · pp. 1–8 Read article
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Optimizing Supply Chain Management: Strategies, Innovations, and Sustainable Practices for Enhanced Operational Efficiency and Global Competitiveness
Abstract: Supply chain management (SCM) is a critical component of modern business operations, directly influencing operational efficiency and global competitiveness. This paper explores strategies, innovations, and sustainable practices aimed at optimizing SCM. It examines the integration of digital technologies, such as artificial intelligence and digital twins, to enhance supply chain performance and adaptability. Additionally, the study delves into sustainable supply chain management (SSCM) practices, including sustainable sourcing, green packaging, and waste …
Published in Journal of Production Research & Management · Vol. 15, Issue 1, 2025 · pp. 1–6 Read article
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Digital Archiving in Higher Education: The Role of Institutional Repositories in Maharashtra’s State Universities
Abstract: Digital archiving plays a pivotal role in the preservation, organization, and dissemination of scholarly materials in the landscape of higher education. With the exponential growth of digital content and the increasing need for open access, institutional repositories (IRs) have emerged as essential platforms for ensuring the long-term accessibility, security, and visibility of academic resources. These repositories facilitate seamless academic collaboration, improve the discoverability of research outputs, and enhance the overall …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 2, 2025 · pp. 31–36 Read article
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AI-Powered Emotion Recognition in Dog
Abstract: Understanding animal emotions is important for improving veterinary care, human animal interaction, and overall pet well-being. Inspired by previous research that utilized a modified EfficientNetB5 model for emotion classification in cats and dogs, our study builds upon this foundation with a focus on real-time emotion recognition in dogs. While earlier approaches achieved high accuracy using Dense Residual and Squeeze-and-Excitation blocks, they often lacked real-time applicability and were not optimized for …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 · pp. 20–32 Read article
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Intelligent Electromagnetic Synthesis: An AI-Driven IoT Framework for Adaptive Antenna Design in Missile Navigation
Abstract: The rapid evolution of hypersonic and long-range tactical missile systems necessitates antenna architecture capable of maintaining robust communication links under extreme thermal, mechanical, and signal-jamming environments. Traditional antenna design methodologies often relying on iterative simulation cycles and static optimization are increasingly insufficient for the real-time requirements of modern aerospace navigation. This paper proposes an AI-driven, IoT- integrated framework that facilitates autonomous antenna design and performance optimization. By deploying a distributed …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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Design and Development of a Smart Automated Packaging System for Poultry Drumsticks
Abstract: The present work aims to design and implement an automated packaging system for poultry drumsticks that enhances operational efficiency, product quality, and adaptability. The integrated system offers a solution that complies with industrial quality and safety standards by sorting products, getting accurate weighing, and efficiently portioning food into 1-kilogram standardized units. By effectively reducing human involvement, operational inefficiencies, workforce requirements, and contamination hazards, the automation system becomes sufficiently adaptable to …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 · pp. 1–7 Read article
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AI-Assisted Optimization of Supersonic Airfoil Shapes Using CFD Coupling
Abstract: This paper presents a novel framework for optimizing supersonic airfoil geometries through integrated artificial intelligence and computational fluid dynamics coupling. Traditional gradient-based optimization methods for high-speed aerodynamic shapes suffer from computational expense and convergence difficulties in non-convex design spaces. The proposed methodology employs a deep neural network surrogate model trained on high-fidelity Reynolds-Averaged Navier-Stokes solutions to approximate aerodynamic performance metrics across the design space. A hybrid particle swarm-genetic algorithm searches …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 8–17 Read article
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Electromechanical Modeling of Microscale Fluidic Systems with Electro Kinetic
Abstract: Due to their capacity to carry out complex fluid manipulations at the microscale, microfluidic systems have become more popular in a variety of applications. For a variety of industries, including biomedical diagnostics, chemical analysis, and environmental monitoring, achieving precise and effective fluid control is essential. The electromechanical modeling of microscale fluidic systems using electro kinetic actuation is the main topic of this research study. We propose a thorough framework for …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 1, Issue 1, 2023 · pp. 18–22 Read article
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Development of Game Theory Strategy for Estimating Mobility Variety in Approaching Wireless Networks
Abstract: Game theory designed with a set of structured tools with an evaluation tool for the tedious interaction among logical players. This theory approaches for analyzing of communication networks, which functions with autonomous structured networks and the designed network devices can take rational decisions according to network congestion. The proposed structure consists of mixture frame for channel allocation for random probability for accessing channel. The main objective of this work is …
Published in Recent Trends in Electronics Communication Systems Read article
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Revolution of Artificial Intelligence and Machine Learning
Abstract: Artificial Intelligence (AI) and Machine Learning (ML) are profoundly transforming various industries by introducing groundbreaking technologies such as deep learning, federated learning, reinforcement learning, and natural language processing. These innovations are not only reshaping the way organizations operate but are also opening new avenues for solving complex problems across diverse sectors, including healthcare, finance, transportation, and more. This study provides a comprehensive exploration of these emerging technologies, emphasizing their practical …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 38–44 Read article
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Automated Car License Plate Detection and Recognition Using Deep Learning
Abstract: The use of automated license plate detection and recognition (ALPR) systems to automate processes such as number plate detection is gaining popularity in traffic control, security, and law enforcement. This research focuses on achieving more accurate and efficient detection and recognition of number plates by leveraging deep learning techniques. The systems outlined in this study aim to improve the effectiveness of ALPR systems using advanced convolutional neural networks (CNNs) and …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 23–29 Read article
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Early Alzheimer’s Disease Prediction Using Vision Transformers and Attention-Guided MRI Analysis
Abstract: Alzheimer’s Disease (AD) continues to be a major global health concern, with early detection being crucial for effective intervention. While conventional machine learning and convolutional neural network (CNN) approaches have made notable progress in automated AD diagnosis using MRI data, they often struggle with capturing long-range dependencies and maintaining spatial contextual awareness. In this research, we propose a novel framework using Vision Transformers (ViTs) for early Alzheimer’s prediction from 3D …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 30–40 Read article
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Adoption to Big Data Analytics: Privacy Issues and Integration of PPDM to overcome it
Abstract: AbstractIn this emerging era of technology, the amount of data being generated is massive. To deal with such a huge amount of data, development of big data analytics to extract valuable information for making marketing decision is gaining popularity. This data can be either structured, semi-structured or unstructured, so it is very difficult to process such rapidly growing and changing data with the conventional database techniques. As big data is …
Published in Journal of Computer Technology & Applications · Vol. 8, Issue 2, 2017 · pp. 33–38 Read article
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Application-Driven Rule-Based Framework for Lubrication Failure Modes in Industrial Systems
Abstract: Modern lubricants increasingly rely on polymer-based composites, integrating synthetic base oils, polymer thickeners and solid additives like MoS₂ and PTFE for high-performance applications. These formulations not only enhance thermal and mechanical stability but also enable low-friction operation across diverse industrial conditions. Lubrication-related failures represent a critical cause of unplanned downtime and reduced reliability in industrial machinery. This paper presents an application-driven, rule-based framework designed to assess and mitigate lubrication failure …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 522–531 Read article
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Role of Impaired Digestion in Disease Pathogenesis: According to Unani System of Medicine
Abstract: The relationship between digestion and disease occupies a central position in Greco-Arab (Unani) medicine, as emphasized by classical physicians such as Ibn Sina and Al-Razi. In Unani medicine, digestion (Haḍm) is not confined to the gastrointestinal tract alone but represents a comprehensive physiological and metabolic process involving four sequential stages: gastric digestion (Haḍm-e-Mi‘dī), hepatic digestion (Haḍm-e-Kabidī), vascular digestion (Haḍm-e-‘Urūqī), and tissue digestion (Haḍm-e-‘Uḍwī). These stages are governed by Quwwat-e-Hāḍima (digestive …
Published in Research & Reviews : A Journal of Unani, Siddha and Homeopathy · Vol. 13, Issue 2, 2026 Read article
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Role of Impaired Digestion in Disease Pathogenesis: According to Unani System of Medicine
Abstract: The relationship between digestion and disease occupies a central position in Greco-Arab (Unani) medicine, as emphasized by classical physicians such as Ibn Sina and Al-Razi. In Unani medicine, digestion (Haḍm) is not confined to the gastrointestinal tract alone but represents a comprehensive physiological and metabolic process involving four sequential stages: gastric digestion (Haḍm-e-Mi‘dī), hepatic digestion (Haḍm-e-Kabidī), vascular digestion (Haḍm-e-‘Urūqī), and tissue digestion (Haḍm-e-‘Uḍwī). These stages are governed by Quwwat-e-Hāḍima (digestive …
Published in Research & Reviews : A Journal of Unani, Siddha and Homeopathy · Vol. 13, Issue 2, 2026 · pp. 30–36 Read article
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Machine Learning-Assisted Design and Optimization of Lightweight Polymer Composites for IoT-Enabled Automotive Applications
Abstract: This study aims to develop an integrated machine learning and optimization framework for the intelligent design of lightweight polymer composites suited for IoT-enabled automotive applications. The goal is to enhance material performance while satisfying multiple design constraints such as mechanical strength, thermal stability, and process compatibility. A curated dataset of polymer composite formulations was used to train a Random Forest Regression (RFR) model capable of predicting tensile strength, thermal conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 12–27 Read article
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Industrial Prognostics via Ensemble Machine Learning: An Uncertainty Aware Framework for RUL Estimation on NASA FD004 Telemetry
Abstract: Estimating the Remaining Useful Life (RUL) of industrial machinery in real-time is now vital for both operational safety and smart resource management. In the aviation industry, turbofan engines deal with constantly shifting flight conditions, making traditional, scheduled maintenance both expensive and prone to error. This paper addresses the flaws in common “point-prediction” AI models, which offer a single failure date without any margin for error, by introducing a new, uncertainty-aware …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 2, 2026 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