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92 articles for “Next-generation operating systems”
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Thermal Effects in High-Power Laser Systems: Modeling and Mitigation
Abstract: High-power laser systems are increasingly employed in industrial manufacturing, defense, medical procedures, and scientific research due to their ability to deliver high energy density with excellent spatial coherence. However, the performance and reliability of these systems are significantly influenced by thermal effects arising from optical absorption, non-radiative recombination, and inefficient heat dissipation within laser gain media and optical components. These thermal phenomena lead to adverse effects such as thermal lensing, …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 2, 2025 · pp. 9–13 Read article
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Design and Development of an Automated Robotic Algorithm for Blasting, Painting, and Barnacle Cleaning of Offshore Structures
Abstract: Marine surface maintenance tasks such as barnacle removal, abrasive blasting, and protective painting are traditionally carried out using manual methods that are labor-intensive, hazardous, and prone to variability in quality. These challenges are particularly significant for offshore structures, where harsh environmental conditions and restricted accessibility increase operational risks and maintenance costs. This paper presents the design and evaluation of an autonomous robotic system for automated surface preparation and coating of …
Published in Journal of Offshore Structure and Technology · Vol. 13, Issue 1, 2026 · pp. 1–12 Read article
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Photosynthetic Living Plant–Integrated Cybernetic Sensors for Autonomous Environmental Intelligence
Abstract: The increasing demand for sustainable and autonomous environmental monitoring systems has motivated the development of biologically integrated sensing technologies that combine living organisms with advanced cybernetic intelligence. This study proposes a novel framework of Photosynthetic Living Plant–Integrated Cybernetic Sensors for Autonomous Environmental Intelligence, where living plants act as self-sustaining sensing platforms capable of continuously monitoring environmental conditions without external energy sources. By integrating bioelectrical signal acquisition modules, flexible nanomaterial electrodes, …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 2, 2026 Read article
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High-Gain Microstrip Patch Antenna for Satellite and Radar Applications
Abstract: The growing demand for high-speed wireless communication, satellite connectivity, and advanced radar systems has increased the necessity for compact and high-performance antenna designs. This study presents the design and analysis of a high-gain microstrip patch antenna intended for satellite and radar applications operating in the microwave frequency range. The proposed antenna structure is developed using a low-loss dielectric substrate to enhance radiation efficiency, bandwidth, and gain characteristics while maintaining a …
Published in Journal of Microwave Engineering and Technologies · Vol. 13, Issue 2, 2026 Read article
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Impact of Partially Observable Markov Decision Process in Next Generation Satellite for Remote Sensing
Abstract: The integration of Partially Observable Markov Decision Processes (POMDPs) in next- generation satellite systems represents a transformative advancement in remote sensing technology. This article explores how POMDP frameworks address the inherent uncertainties and incomplete observability challenges in satellite operations, including dynamic task scheduling, resource allocation, and adaptive sensing strategies. By modeling satellite decision-making under uncertainty, POMDPs enable autonomous systems to optimize mission objectives while managing constraints such as limited power, …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 20–28 Read article
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Power and Area - Aware Recursive Multiplier Architecture Utilizing Polymer Composites for Neural Network Acceleration
Abstract: Approximate computing is widely applied in error - tolerant systems as an effective technique to enhance circuit performance by deliberately allowing occasional inaccuracies instead of strictly ensuring precise results for every computation. Among the fundamental building blocks of digital systems, multipliers play a crucial role in signal processing, control systems, and machine learning applications; however, they demand significant power, silicon area, and timing resources. Leveraging error - tolerant approximate multipliers …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1320–1337 Read article
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Database-Driven Energy Management in Electric Vehicles
Abstract: With the growing concern over environmental pollution, there is an increasing demand for sustainable and eco-friendly technologies. Among these, electric vehicles (EVs) have emerged as a promising alternative to conventional fossil-fuel-based transportation. However, as EV adoption accelerates, efficient energy management becomes critical to enhance vehicle performance, extend battery life, and ensure overall system reliability. This research presents a Database-Driven Energy Management System (DBEMS) that leverages real-time data from EV components …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 19–24 Read article
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Deploying Fuzzy Logic for Self-Tuning Regulator Design for Motion Control in Modern Electrical Machines
Abstract: Modern electrical machines require sophisticated motion control systems capable of adapting to varying operating conditions, load disturbances, and parameter uncertainties. Traditional self-tuning regulators (STR) based on classical control theory often struggle with nonlinearities, time-varying dynamics, and complex operational environments characteristic of contemporary electric drives. This article presents a comprehensive framework for deploying fuzzy logic in self-tuning regulator design to address these challenges in motion control applications. Fuzzy logic controllers leverage …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 11–21 Read article
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Neuromorphic Self-Learning Polymer–MXene Photovoltaic Composites with Embedded Memristive Energy Routing for Adaptive Solar Energy Harvesting
Abstract: This dynamic and fast-growing intelligent renewable energy system requires photovoltaic materials that can autonomously adapt to fast-changing environmental conditions. In this study, a novel system is proposed for adaptive harvesting of solar energy based on Neuromorphic Self-Learning Polymer–MXene Photovoltaic Composites (NSPMPCs) with embedded memristive energy routing networks. To boost the charge generation and charge transport in the polymer–MXene heterostructure, the flexibility and processability of conductive polymers are integrated with the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Polymer Phase Change Materials: Innovations, Applications, and Future Directions
Abstract: Polymer-based phase change materials represent a significant advancement in energy storage and thermal management technologies due to their ability to absorb, store, and release heat during phase transitions. This article reviews recent innovations in polymer phase change materials, focusing on the synthesis, characterization, and performance enhancement techniques. The development of polymer composites with enhanced thermal conductivity, improved phase change enthalpy, and extended thermal cycling stability is discussed. Additionally, the integration …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 11, Issue 2, 2024 · pp. 1–7 Read article
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Advancements In Energy Storage Materials Are Overcoming Challenges and Shaping Future Innovations
Abstract: The pursuit of efficient energy storage technologies is critical for advancing renewable energy systems and improving the performance of electric vehicles. This review emphasizes the synergistic contributions of polymers and composite materials in phase change materials (PCMs), zinc-based batteries (ZnBs), lithium-ion batteries (LIBs), and graphene-based systems. PCMs, particularly polymer-encapsulated and polymer-stabilized composites, demonstrate a remarkable ability to store and release thermal energy, enabling improved thermal management and operational stability. In …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 704–723 Read article
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Role of Beowulf Clusters in Next-Generation Military Applications: A Comprehensive Study
Abstract: Beowulf clusters, which utilize cost-effective commodity hardware combined with open-source software for parallel computing, have emerged as a viable and efficient solution for high-performance computing needs. This paper explores their growing relevance and practical applications in modern and future military technologies. Contemporary military operations increasingly rely on rapid data processing, real-time intelligence, high-fidelity simulations, and autonomous decision-making systems. Beowulf clusters offer scalable and adaptable computational power that supports these demands …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 01–07 Read article
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A Survey of Role-Based Access Control Implementation in HMI Systems for Industrial Automation
Abstract: The convergence of Role-Based Access Control (RBAC) and Human-Machine Interface (HMI) systems presents a transformative approach to secure and efficient industrial automation in Industry 4.0. By integrating RBAC with Multi-Factor Authentication (MFA), this framework enhances cybersecurity while maintaining operational flexibility, mitigating both external threats and internal vulnerabilities. Modern adaptive HMIs further optimize user experience through personalized and intuitive interfaces, though challenges remain in balancing functionality with simplicity in complex industrial …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 2, 2025 · pp. 10–19 Read article
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RF Energy Harvesting Techniques for Wireless Sensor Networks
Abstract: In contemporary applications like environmental monitoring, healthcare systems, industrial automation, agriculture, military surveillance, and smart cities, Wireless Sensor Networks (WSNs) are crucial. However, the limited battery life of sensor nodes remains a major challenge because many sensor devices are deployed in remote or difficult-to-access locations. Frequent battery replacement or recharging increases maintenance cost, reduces network reliability, and limits long-term operation. In contemporary applications like environmental monitoring, healthcare systems, industrial automation, …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 2, 2026 Read article
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A Physics-Informed Graph Neural Network Framework for Real- Time Thermal-Aware Fault Prediction and Adaptive Power Optimization in Heterogeneous System-on-Chip Architectures
Abstract: Heterogeneous System-on-Chip (SoC) architectures are increasingly adopted in edge computing, artificial intelligence, autonomous systems, and high-performance embedded platforms due to their superior computational efficiency and flexibility. However, increasing integration density and workload diversity introduce severe thermal hotspots, accelerated device degradation, and unexpected hardware faults that adversely affect system reliability and energy efficiency. This study proposes a Physics-Informed Graph Neural Network (PI-GNN) framework for real-time thermal- aware fault prediction and adaptive …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 Read article
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Federated Learning for Energy Management in Next Generation Smart Cities
Abstract: Federated learning has emerged as a promising approach for addressing the challenges of energy management in next-generation smart cities. This decentralized approach to machine learning allows collaborative model training among distributed data sources, while safeguarding data privacy and security. In this study, we explore the application of federated learning techniques to optimize energy consumption, enhance grid stability, and promote sustainability in smart city environments. By aggregating data from diverse sources …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 1, 2024 · pp. 19–27 Read article
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Hybrid Intelligence in Cyber Security: A Study
Abstract: The digital landscape is a battlefield of escalating complexity, where the volume, velocity, and sophistication of cyber threats have exponentially outpaced human-centric defense models. Traditional rule-based security systems and siloed artificial intelligence (AI) solutions, while valuable, are increasingly brittle, overwhelmed by zero-day exploits, polymorphic malware, and coordinated, state-sponsored campaigns that operate in the shadows of big data. This paper posits that the paradigm of cybersecurity must fundamentally shift from one …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 01–09 Read article
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Ferroelectric Materials for Next-Generation Non-Volatile Memory Applications
Abstract: The continuous scaling of conventional memory technologies is increasingly constrained by limitations in power consumption, speed, endurance, and integration density. As data-intensive applications such as artificial intelligence, Internet of Things, and edge computing demand fast and energy-efficient memory solutions, alternative non-volatile memory technologies have gained significant attention. Ferroelectric materials, characterized by their reversible spontaneous polarization, offer a promising pathway toward next-generation non-volatile memory due to their intrinsic non-volatility, low operating …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 1–9 Read article
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Spintronic Logic Circuits for Ultrafast Processing
Abstract: Spintronic logic has emerged as one of the most promising post-CMOS paradigms capable of addressing the speed, density, and energy challenges of deeply scaled silicon technologies. By relying on the intrinsic properties of electron spin and magnetization dynamics, spintronic devices—particularly Magnetic Tunnel Junctions (MTJs), Spin-Transfer Torque (STT), and Spin–Orbit Torque (SOT) structures—enable ultrafast, non-volatile data processing with significantly reduced energy consumption. Despite remarkable device-level advancements, circuit- level realization of high-speed, …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 35–43 Read article
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Green AI-Enabled Opto-Electronic Communication Systems for Carbon-Neutral Digital Networks
Abstract: The rapid expansion of digital communication infrastructure, driven by cloud computing, Internet of Things (IoT), 6G networks, and artificial intelligence applications, has significantly increased the energy consumption and carbon footprint of modern communication systems. Conventional optical communication networks often rely on static resource allocation and energy-intensive signal processing mechanisms, resulting in inefficient utilization of network resources and elevated operational costs. This study proposes a Green Artificial Intelligence (Green AI)-Enabled Opto-Electronic …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 2, 2026 Read article