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1135 articles for “Proposed”
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Fractal-Entropy Guided Adaptive Signal Reconstruction for Non-Stationary Biomedical and Communication Systems
Abstract: This paper presents a novel Fractal-Entropy Guided Adaptive Signal Reconstruction (FEG- ASR) framework designed for accurate processing of non-stationary signals in biomedical and communication systems. The proposed approach integrates fractal dimension analysis with entropy- based feature evaluation to capture the intrinsic complexity and irregularity of time-varying signals. By dynamically adapting reconstruction parameters based on fractal-entropy measures, the method effectively separates noise from meaningful signal components while preserving critical information. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 Read article
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Integration of Modular Multilevel Converter Topology in the Design and Control of Hybrid Electric Vehicles
Abstract: A back-to-back modular multilevel converter (BMMC) based plug-in hybrid electric vehicle power conversion system is proposed to solve the problems of traditional MMC-EV. The local AC harmonics generated by the operation of MMC-EV accelerate the battery degradation and reduce the battery life. Currently, electric vehicles are in great demand due to the rising oil prices and environmental pollution concerns. Since the backbone of electric vehicles is the energy storage system, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1195–1205 Read article
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Bridging the Gap Between Product Development and Entrepreneurship in Engineering Curriculum: A Framework-Based Approach Aligned with NEP 2020
Abstract: Despite advancements in technical education, Indian engineering graduates frequently enter the workforce lacking critical competencies in product development (PD) and entrepreneurship. This imbalance has drawn scrutiny from industry and policymakers alike, with national directives such as the National Education Policy (NEP 2020) emphasizing a shift toward “experiential, holistic, integrated and inquiry-driven” learning models. Similarly, the All-India Council for Technical Education (AICTE) has embedded innovation labs, internship mandates and entrepreneurship courses …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 87–100 Read article
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Impacts of Climate Change and Anthropogenic Stressors on Marine Ecosystems: A Comparative Study of Coral Reefs, Kelp Forests, and Arctic Fjords
Abstract: The accelerating impacts of climate change and human activities are profoundly reshaping marine ecosystems, threatening biodiversity, and altering trophic dynamics. This study synthesizes recent research on the responses of marine flora and fauna to temperature fluctuations, ocean acidification, pollution, and overfishing, highlighting the cascading effects on primary production, nutrient cycling, and ecosystem resilience. Using a combination of field surveys, remote sensing data, and meta-analytical approaches, we quantified biodiversity shifts across …
Published in International Journal of Marine Life · Vol. 3, Issue 1, 2026 · pp. 17–24 Read article
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Aerodynamic Optimization of UAV Wings Using Machine Learning
Abstract: Unmanned Aerial Vehicles (UAVs) are increasingly deployed across defense, transportation, agriculture, and environmental monitoring, demanding improved aerodynamic efficiency to enhance endurance, stability, and payload capacity. Traditional aerodynamic optimization approaches, relying on computational fluid dynamics (CFD) simulations and wind tunnel experiments, are often time-consuming and computationally expensive. This study proposes a machine learning (ML)-driven framework for the aerodynamic optimization of UAV wing geometries, aiming to significantly reduce design cycles while improving …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 1–7 Read article
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Design and Implementation of a Polymer-Integrated IoT-Based Smart Intravenous Fluid Monitoring System for Patient Safety
Abstract: The intelligent healthcare systems rely more and more on the advanced materials and Internet of Things (IoT) technologies to improve patient safety, patient-centeredness, timeliness of care, clinical efficiency. This paper presents a polymer-enhanced IoT enabled automatic IV Fluid Level monitoring and notification system. The novel system is based on the use of polymer-encapsulated load-cell sensors and polymer-packaged electronic modules, which allow biocompatibility, long-term stability and easy sterilisation in medical environments. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 730–742 Read article
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Performance Analysis of AES Encryption Using LFSR-Based Key Expansion in VLSI
Abstract: Secure data transmission has become increasingly important with the rapid growth of digital communication and embedded systems. Protecting sensitive information from unauthorized access requires reliable cryptographic solutions. Among the available techniques, the Advanced Encryption Standard (AES) is widely recognized for its strong security and efficient implementation in both hardware and software environments. In this work, the design and performance evaluation of an AES-based crypto processor with LFSR-driven key expansion is …
Published in Recent Trends in Electronics Communication Systems · Vol. 13, Issue 1, 2026 Read article
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Very Short-Term Load Forecasting Using Gaussian Process Regression
Abstract: Very Short-Term Load Forecasting (VSTLF) is critical for real-time grid stability, frequency control, and economic dispatch. This study proposes a Gaussian Process Regression (GPR)-based framework for one-hour-ahead load forecasting using hourly data from January 2020 to April 2024 for Delhi, India. The model incorporates meteorological data such as temperature, humidity, and dew point with lagged load values. The research takes into account time-related dependencies and seasonal changes in order to …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 91–104 Read article
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Deep Learning for Real-Time Monitoring and Defect Detection in Additive Manufactured Polymer Composites
Abstract: Additives Fiber-reinforced polymer composite ADDs have high utility in making lightweight structural components, but due to process-related defects (interlayer delamination and reinforcement stacking) the integrity of consolidation during extrusion-based deposition is frequently compromised. This paper has presented a physics-informed deep learning framework that is applicable to real-time measurements of reinforced thermoplastic composite fabrication. Multimodal sensing was provided with thermal gradient, optical morphology, and acoustics emission signals being used to assess …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 974–999 Read article
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IoT-Based Structural Health Monitoring and Damage Detection in Fiber Reinforced Polymer Composite Structures
Abstract: Applications of fiber-reinforced polymer (FRP) composite in the aerospace, civil infrastructure and renewable energy systems are increasing due to the fact that the composite possesses high ratio of strength to weight and can resist corrosion. However, processes of internal damages such as the cracking of the matrix, delamination and fiber fracture, are likely to take place without being visible on the surface and therefore a periodic check of the structure …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1076–1100 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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An Adaptive and Privacy-Aware Federated Learning Framework for Efficient and Secure Model Training Across Heterogeneous Datasets
Abstract: The problem of efficiency and privacy regarding heterogeneous data in modern distributed machine learning systems is a vital point that should be taken into account. The absence of IID data distribution, client heterogeneity, and privacy invasion during the aggregation model are the bane of conventional federated learning (FL) approaches to learning like FedAvg and FedProx. The paper proposes that the adaptive and privacy-aware FL framework (AFL-P) can be used to …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 16–25 Read article
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A Technical Blueprint for AI-Driven Localization in 6G Mobile Networks
Abstract: The advent of sixth-generation (6G) wireless systems promises unprecedented spatial resolution, ultra-low-latency, and pervasive connectivity, turning mobile localization from a peripheral service into a core enabler of immersive extended reality (XR), autonomous logistics, and digital twins. Yet, the sheer scale of dense terahertz (THz) deployments, the stochastic nature of reconfigurable intelligent surfaces (RIS), and the dynamic interference landscape render traditional model-based positioning techniques inadequate. This work investigates how artificial intelligence …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 26–34 Read article
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Modelling, Simulation & Optimization of Renewable Energy-Based Hybrid Microgrid for Electrification of Rural Areas
Abstract: Rural electrification in India faces persistent challenges due to unreliable grid connectivity, elevated transmission and distribution costs, and the geographical isolation of remote communities. Insufficient access to reliable electricity constrains economic development, educational opportunities, healthcare delivery, and overall quality of life in these areas. This study details the design and simulation of an off-grid, renewable-based hybrid micro grid for two rural villages: Khirgitola in Chhattisgarh, which has an electrification rate …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1206–1218 Read article
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Design of an ArUco Marker-Guided Smart Trolley with Integrated Billing Estimation
Abstract: The growing adoption of automation in retail environments has increased the need for intelligent systems that improve user convenience and reduce manual effort. This paper presents the design and development of a human-following smart shopping trolley with an integrated automatic billing system based on computer vision. The proposed system employs ArUco marker–based human tracking to achieve reliable and real-time following behaviour. A Raspberry Pi serves as the central processing unit, …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 1, 2026 Read article
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Analysis of a Communication Link Performance Across Various Rayleigh Channels in Tropical Climates
Abstract: Tropical regions are characterized by intense and persistent rainfall throughout most of the year, and this environmental condition significantly influences wireless communication performance. The continuous presence of heavy precipitation weakens, scatters, and disrupts radio frequency signals, causing noticeable attenuation during transmission from the source to the destination. As a result, reliable communication becomes challenging, particularly for modern high-speed systems such as 5G networks. To address this limitation and enhance communication …
Published in Journal of Communication Engineering & Systems · Vol. 16, Issue 1, 2026 · pp. 06–12 Read article
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Multi-Layered AI-Driven Paradigm Shift in IoT Ecosystem Security
Abstract: As the Internet of Things (IoT) continues to weave itself into the fabric of modern life – from smart homes and industrial automation to healthcare and urban infrastructure – the associated security vulnerabilities have become increasingly apparent. Traditional security mechanisms, often built on static rules and perimeter-based defenses, struggle to keep pace with the scale, heterogeneity, and dynamic nature of IoT ecosystems. In response, artificial intelligence (AI) has emerged as …
Published in Journal of Communication Engineering & Systems · Vol. 16, Issue 1, 2026 · pp. 13–21 Read article
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E-Commerce Clothing Platform with Virtual Try-On
Abstract: The inability to physically evaluate garments remains a major limitation in online clothing commerce. Customers often depend on static product images and generalized sizing charts, which do not accurately represent individual body proportions. This frequently leads to uncertainty during purchase decisions and increased product return rates. To address this limitation, this research proposes a web-based clothing e-commerce platform integrated with an intelligent virtual try-on mechanism. The system allows users to …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 1, 2026 · pp. 17–24 Read article
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Image-Based Crack Morphology Characterisation for Electrical Failure Analysis in Conductive Polymer Composites
Abstract: Electrical performance in conductive polymer composites is strongly governed by crack-network evolution, yet failure analysis typically relies on qualitative image inspection or electrical anomaly detection in isolation. This work proposes an end-to-end framework that converts optical/SEM crack imagery into a standardised crack morphology signature and quantitatively links it to electrical degradation indicators. A two-stage learning strategy is adopted: crack-representation pretraining using the public Concrete Crack Images for Classification dataset, followed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1375-1386 Read article
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Parallel Privacy-Preserving Adaptive Federated Learning on GPU-Enabled Multi-Core Architectures
Abstract: The increasing deployment of parallel and distributed intelligent systems has intensified the need for privacy-preserving learning frameworks that can exploit multi-core and GPU-based architectures without centralizing sensitive data. This work proposes a parallel Adaptive Federated Learning (AFL) framework that integrates Differential Privacy and Secure Aggregation over heterogeneous multi-core and GPU platforms to enhance both data confidentiality and convergence efficiency. The framework dynamically adjusts client participation, learning rates, and aggregation weights …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article