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791 articles for “Ratings”
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Evolution of Mobile Wireless Generations and the Architectural Foundations of AI-Integrated 6G Networks
Abstract: Wireless communication has moved through five complete technology generations in roughly four decades, and each transition has reshaped how societies exchange information, run businesses, and design cities. This paper is the first instalment of a two-part review and concentrates on the historical arc of that journey, tracing the defining traits, benefits, and shortcomings of 1G through 5G before turning to the architectural groundwork on which sixth-generation (6G) networks are being …
Published in International Journal of Digital Communication and Analog Signals · Vol. 12, Issue 2, 2026 Read article
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Enhancing Facial Expression Analysis Using CNNs: Insights from ML and Deep Learning Comparisons
Abstract: Emotion recognition from facial manifestations increases the interaction between humans and computers by enabling the interaction between humans and computers to effectively explain human feelings. This study presents a comparative analysis of three approaches to the emotional recognition of faces: a custom Convolutional Neural Network (CNN) model, Traditional Machine Learning (ML) methods, and other deep learning architectures such as VGG, ResNet, and Hybrid CNN–RNN models. The proposed CNN-based system, developed …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 23–31 Read article
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Adaptive Production Scheduling in Multi-Machine Manufacturing Environments
Abstract: For manufacturing processes to meet evolving market demands, they must be executed in the most efficient manner while maintaining flexibility against unanticipated disruptions. Often, traditional scheduling methods overlook dynamic variability and real-time interruptions. An inverse scheduling framework for a multi-machine flowshop system is proposed in this research with the primary objective of makespan minimisation. Several issue situations are analysed to validate the algorithmic efficacy, and metaheuristic techniques are used to …
Published in International Journal of Manufacturing and Materials Processing · Vol. 12, Issue 1, 2026 · pp. 32–42 Read article
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Conversion of Heat Absorbed (Waste Heat) in a Building for Electricity Generation Using a Thermoelectric Generator
Abstract: This study investigates the feasibility of thermoelectric generators (TEGs) for recovering waste heat from building systems and converting it into electrical energy through the Seebeck effect. A journal-scale simulation framework integrating ANSYS thermal modeling with MATLAB/Simulink electrical analysis was developed to evaluate TEG deployment on building envelope surfaces at the Federal Polytechnic Nyak Shendam, Nigeria. Results demonstrate a proportional increase in electrical output with rising temperature gradients, confirming predictable thermoelectric …
Published in International Journal of Renewable Energy and its Commercialization · Vol. 12, Issue 1, 2026 · pp. 8–16 Read article
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A Study on Machine-Learning-Driven Insight into theThermal Behavior of Polymers and Composite Materials
Abstract: The thermal performance of polymeric and composite systems underpins their suitability for aerospace, electronics, and energy‑storage applications, yet reliable prediction of temperature‑dependent properties remains a formidable challenge. In this work we present a data‑driven framework that harnesses modern machine‑learning (ML) techniques to forecast key thermal metrics – glass‑transition temperature (Tg), melting point (Tm), thermal conductivity (k), and decomposition onset (Td) – from a chemically informed descriptor space. A curated database …
Published in International Journal of Polymer Science and Engineering · Vol. 12, Issue 1, 2026 · pp. 1–11 Read article
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Performance Evaluation of EV Charging Station with Bidirectional Power Flow for Grid Support Applications
Abstract: The swift increase in the number of electric vehicles (EVs) brings considerable prospects and difficulties for contemporary power distribution networks. This paper presents the performance evaluation of a 20 kW bidirectional EV charging station designed to facilitate both Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) power flow for enhanced smart grid support applications. The proposed topology integrates an AC/DC bidirectional converter interfaced to the 415 V, 50 Hz three-phase utility grid through …
Published in International Journal of Power Electronics Controllers and Converters · Vol. 12, Issue 1, 2026 · pp. 21–28 Read article
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Deep Reinforcement Learning-Based MPPT for PV Systems Under Partial Shading: A Hybrid Metaheuristic-Optimized Control Framework.
Abstract: Partial shade and quickly changing environmental conditions make Maximum Power Point Tracking (MPPT) in photovoltaic (PV) arrays particularly difficult. In these situations, traditional algorithms frequently fail to find the global optimum or experience sluggish convergence and steady-state oscillations. To obtain reliable, real-time MPPT under non-uniform irradiance, this research suggests a hybrid control architecture that combines a deep recurrent reinforcement learning (DRL) agent with metaheuristic-based parameter optimization and a digital-twin training …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 1, 2026 · pp. 35–46 Read article
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An Advanced Framework for Energy Harvesting in Device-to-Device Communication within 5G-Enabled IoT Healthcare Networks
Abstract: The healthcare sector is forever advancing, and one of the key technologies that have started playing a part in better patient care and management is Internet of Things (IoT) devices. The Device-to-Device (D2D) communication in 5G-enabled IoT healthcare networks provide better data transmission rate and very low latency. But despite all that, IoT devices still have over-the-top energy consumptions requiting attention. In this work, an innovative energy harvesting framework is …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 12, Issue 1, 2026 · pp. 22–30 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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Microwave Frequency Optimization Techniques for High-Speed Wireless Communication
Abstract: The rapid growth of mobile devices, cloud computing, Internet of Things (IoT), smart applications, and high-definition multimedia services has significantly increased the demand for high-speed wireless communication systems. Microwave communication technologies play a vital role in modern wireless networks because they provide large bandwidth, high data transmission rates, low latency, and efficient spectrum utilization. Microwave and millimeter- wave frequencies are widely used in satellite communication, radar systems, wireless broadband, and …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 1, 2026 · pp. 14–21 Read article
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Performance Analysis of Hybrid Signal Processing Methods in Modern Communication Networks
Abstract: Modern communication networks require high-speed, reliable, and energy-efficient signal transmission for applications such as wireless communication, satellite systems, Internet of Things (IoT), smart healthcare, and next-generation 5G/6G networks. Traditional signal processing techniques often face limitations in dynamic communication environments due to interference, noise, latency, and bandwidth constraints. Hybrid signal processing methods combine multiple techniques including analog-digital processing, adaptive filtering, beamforming, machine learning, and intelligent optimization to enhance communication performance and …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 1, 2026 · pp. 22–35 Read article
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A Study of Delta Modulation Techniques for Bandwidth- Efficient Signal Transmission
Abstract: Delta modulation is an important signal processing technique widely used in digital communication systems for efficient analog-to-digital signal conversion and bandwidth reduction. With the increasing demand for high-speed and low-complexity communication systems, bandwidth-efficient transmission methods have become essential in modern telecommunication networks. This study presents a comprehensive analysis of delta modulation techniques and their role in improving signal transmission efficiency in digital communication environments. The paper examines the operating principles …
Published in International Journal of Digital Communication and Analog Signals · Vol. 12, Issue 1, 2026 · pp. 31–43 Read article
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Utility of Corrosion Inhibitors for the Corrosion Protection of Materials in Hostile Environments
Abstract: The term “inhibitor” refers to a material that reduces the rate of corrosion in an environment when added in trace amounts. As a result, the inhibitor functions as a catalyst for those delays. Inhibitors come in a wide variety of forms and formulations. The two most crucial considerations when choosing materials for industrial applications are cost and safety. Physical criteria are typically simple to achieve, but corrosion resistance presents significant …
Published in International Journal of Energetic Materials · Vol. 12, Issue 1, 2026 · pp. 27–34 Read article
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Intelligent Trajectories: Harnessing Artificial Intelligence for Next Generation Missile and Propellant Design
Abstract: The rapid evolution of artificial intelligence (AI) has unlocked transformative pathways for high-performance aerospace engineering, yet its integration into missile and propellant design remains nascent. This study investigates a hybrid AI-driven framework that unites physics-based modeling, data-centric learning, and multi-objective optimization to accelerate the conception, validation, and refinement of missile airframes and solid-propellant formulations. First, a physics-informed neural network (PINN) is trained on a curated database of historic missile geometries, …
Published in International Journal of Energetic Materials · Vol. 12, Issue 1, 2026 · pp. 20–26 Read article
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DEVELOPING A DRIVER DROWSINESS DETECTION SYSTEM (DDDS)
Abstract: Driver drowsiness accounts for over 18% of all traffic accidents in India, making it a major contributing factor. This study proposes a real-time, edge-based Driver Drowsiness Detection System (DDDS) that detects early fatigue signs and alerts drivers prior to accidents. The system employs a multimodal, bimodule strategy. In order to track face traits such eye closure, blink rate, yawning, head position, and gaze direction, the first module uses computer vision. …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 2, 2026 Read article
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Spermmediated gene transfer revisited: optimizing delivery, integration, and germline transmissionin large animal models
Abstract: Spermmediated gene transfer (SMGT) exploits the natural role of spermatozoa as DNA vectors to deliver exogenous genetic material to oocytes, potentially enabling economical production of transgenic large animals without complex embryo micromanipulation (1). Early proofofconcept studies established that mammalian sperm can bind, internalize, and protect exogenous DNA, leading to integration, expression, and germline transmission in various species, including pigs (24). Subsequent mechanistic work has challenged the traditional view of sperm …
Published in International Journal of Animal Biotechnology and Applications · Vol. 12, Issue 1, 2026 Read article
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Public Infrastructure and Urban Rent Inequality in Kaduna Metropolis
Abstract: Rental values in major cities worldwide have increased at a rate never before seen due to the growing demand for residential properties in metropolitan areas. The connections between residential property rental values and all of these location-specific and physical dwelling attributes, amenities, and so forth are valued by valuers, planning authorities, and policymakers. For example, valuers will receive assistance in assigning values to different housing and locational qualities once all …
Published in International Journal of Housing and Human Settlement Planning · Vol. 12, Issue 1, 2026 · pp. 26–35 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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Traffic Safety in Indore: Analysis of Accident Trends, Causes, and Preventive Measures
Abstract: Abstract Traffic safety has emerged as a significant concern in rapidly growing urban cities like Indore due to increasing population, rising vehicle ownership, and expanding infrastructure. This study focuses on analyzing traffic safety conditions in Indore by examining accident trends, major causes, high-risk zones, and existing safety measures over the period from 2020 to 2026. The analysis reveals a continuous increase in road accidents and fatalities, indicating a growing risk …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 1, 2026 · pp. 18–25 Read article
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Deep Reinforcement Learning-Based MPPT for PV Systems Under Partial Shading: A HybridMetaheuristic-Optimized Control Framework.
Abstract: Partial shade and quickly changing environmental conditions make Maximum Power Point Tracking (MPPT) in photovoltaic (PV) arrays particularly difficult. In these situations, traditional algorithms frequently fail to find the global optimum or experience sluggish convergence and steady-state oscillations. To obtain reliable, real-time MPPT under non-uniform irradiance, this research suggests a hybrid control architecture that combines a deep recurrent reinforcement learning (DRL) agent with metaheuristic-based parameter optimization and a digital-twin training …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 1, 2026 Read article