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194 articles for “conventional frame”
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Development and Application of Advanced Materials for Oil Spill Cleanup and Contaminant Removal
Abstract: Oil spills and environmental contaminants representing critical challenges to ecosystems and human health, demanding innovative and effective solutions. Advanced materials have emerged as transformative tools in addressing these issues, offering superior efficiency and sustainability compared to conventional methods. They are environmental and ecological threats, necessitating effective cleanup and removal strategies. The development and application of advanced materials are developing promising solutions for addressing the challenges. This study focuses on the …
Published in Journal of Water Pollution & Purification Research · Vol. 13, Issue 1, 2026 · pp. 17–25 Read article
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A Review on Artificial Intelligence Techniques for Analyzing Deforestation and Illegal Logging Using Satellite Imagery
Abstract: Deforestation and illegal logging remain critical environmental threats, driving biodiversity loss, climate change, and socio-economic disruption. Conventional monitoring techniques frequently do not yield real-time, large-scale insights. Recent developments in Artificial Intelligence (AI), especially in deep learning and computer vision, have revolutionized the ability to analyze high-resolution satellite images for detecting deforestation and monitoring illegal logging. This review synthesizes recent developments in AI-driven approaches, highlighting convolutional neural networks (CNNs), anomaly detection …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
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Diffusion-Based Enhancement of Low-SNR Time- Frequency Signals
Abstract: Traditional enhancing techniques are useless in low signal-to-noise ratio (LSNR) situations because noise drastically interferes with communication signals. Based on an enhanced DiffBIR model, this paper suggests a dual-stage signal improvement approach that combines diffusion with deep learning. By combining the Inception module for multi-scale feature extraction with the Pixel Fusion Attention (PFA) module for significant region highlighting, the model improves signal recovery in the time- frequency domain. Experiments show …
Published in Current Trends in Signal Processing · Vol. 17, Issue 2, 2026 Read article
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Effects of Cluster Computing on Big Data Analysis and Network Topology
Abstract: The rapid expansion of big data has posed substantial difficulties for conventional computing systems. As a result, cluster computing has grown to be a potent method for effective large data processing. Cluster computing involves multiple interconnected nodes functioning as a unified system, pooling together their processing, storage, and memory resources. These nodes are typically connected through high-speed networks such as ethernet or InfiniBand, facilitating efficient data sharing and communication among …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 1, 2023 · pp. 31–39 Read article
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Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Bio-Inspired FGPCs for Biomedical and Structural Applications
Abstract: Bio-inspired functionally graded polymer composites (FGPCs) represent a new class of smart materials that use gradient material distributions to enhance mechanical and biological properties, mimicking natural systems like bones, shells, and plant stems. FGPCs exhibit smooth gradient distributions across interfaces, which improves biocompatibility and reduces the risk of failure under complex loading and environmental conditions. In this study, bio-inspired FGPCs were designed, fabricated, and validated using a combined experimental and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 456–481 Read article
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Application of MCDM Techniques for Selection of Battery for Electric Vehicle
Abstract: An electric vehicle (EV) operates using an electric motor, which differs from traditional vehicles powered by internal combustion enginesElectric motors are used to power EVs rather than gasoline and gasses. These motors are powered by fuel cells, solar panels, or battery packs that recharge. As a result, EVs are increasingly considered as potential replacements for conventional automobiles, aiming to combat issues such as pollution, global warming, and resource depletion. Electric …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 3, 2024 · pp. 33–40 Read article
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Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article
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Smart Environmental Noise Monitoring System Using IoT and Machine Learning for Urban Pollution Control
Abstract: Human race has steadily evolved over past centuries. Development of new technology, vigorous research, consistent efforts, indomitable will to find solutions for the problems, are the key factors to shape our future in way that everyone gets safe, secure and satisfactory life. Construction industries provides basic but most valuable service or product or we can say that construction industries fulfill the basic needs of individual and group of people by …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 3, 2025 Read article
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Critical Review of Study of Conventional and Pre Engineered Building
Abstract: Human race has steadily evolved over past centuries. Development of new technology, vigorous research, consistent efforts, indomitable will to find solutions for the problems, are the key factors to shape our future in way that everyone gets safe, secure and satisfactory life. Construction industries provides basic but most valuable service or product or we can say that construction industries fulfill the basic needs of individual and group of people by …
Published in Recent Trends in Civil Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 48–53 Read article
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User Review-Driven Recommendation Model for E-Scooter Selection
Abstract: In the era of rising environmental awareness and the growing emphasis on sustainable mobility practices, electric scooters (e-scooters) have gained significant popularity as an efficient and eco-friendly alternative to conventional modes of transport. Their ability to reduce carbon emissions, minimize traffic congestion, and offer cost-effective commuting solutions has made them highly attractive, particularly in urban environments. However, with the rapid expansion of the e-scooter market, consumers are faced with an …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 6–16 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
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Crossroads of Ecology and Medicine: Evaluating Pollutant-Induced Risks to Biodiversity and Human Health
Abstract: Environmental pollution has emerged as a central challenge at the crossroads of ecology and human medicine. The rapid pace of industrialization, urbanization, and agricultural intensification has led to an unprecedented release of pollutants into the air, water, and soil—triggering cascading effects on ecosystems and human health. Pollutants such as particulate matter, heavy metals, pesticides, microplastics, endocrine-disrupting chemicals, and persistent organic pollutants not only degrade biodiversity but also exert multifaceted health …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 1, 2025 · pp. 41–53 Read article
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Comprehensive Review of Composite Materials: Classification, Manufacturing Methods, Mechanical Behavior, Failure Modes, and Emerging Applications
Abstract: Composite materials have emerged as one of the most significant classes of engineered materials due to their ability to deliver high strength to weight ratios, enhanced durability, and tailored multifunctionality. Over the past two decades, rapid progress in polymer chemistry, advanced reinforcement architectures, additive manufacturing, and automated fabrication has expanded the applicability of composites across aerospace, automotive, biomedical, civil, and renewable energy sectors. This paper provides a comprehensive review of …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 923–939 Read article
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Harnessing Bacteria for Next-Generation Data Storage Technologies – A Review
Abstract: The exponential increase in global digital information has created a pressing need for storage technologies that are more durable, compact, and sustainable than conventional electronic media. While hard drives, solid-state drives, and cloud-based systems have transformed information management, they face severe limitations related to storage density, energy consumption, maintenance costs, and long-term preservation. Researchers have, therefore, begun exploring biological systems as alternative information storage platforms. Among these, bacteria have emerged …
Published in International Journal of Molecular Biotechnological Research · Vol. 4, Issue 2, 2026 Read article
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English Literature in the Digital Era: Transformations and Trends
Abstract: English literature context has been changed significantly with modernisation of the digital age that is creating a massive impact on creation, dissemination, and interpretation of literature. When one considers the relationship between literature and digital innovation, one may summarize these disruptive forces as both a challenge to and opportunity for literature — a hybridization of past forms. It explores how digital technologies have transformed reading practices, textual analysis, and the …
Published in Emerging Trends in Languages · Vol. 2, Issue 2, 2025 · pp. 27–32 Read article
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Reinforcement Learning for Adaptive Sensing with Shape Memory Polymer-Based IoT Nodes
Abstract: The rapid expansion of intelligent sensing in the Internet of Things (IoT) has revealed the pressing need for materials and algorithms capable of self-adaptation in volatile environments. Conventional polymer-based sensors and static control strategies often fail to capture nonlinear thermo-mechanical dynamics, leaving them unsuitable for unpredictable operating conditions. Although prior studies have improved polymer composites or introduced algorithmic optimization independently, few attempts have coupled the adaptability of smart materials with …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 370–391 Read article
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Catalyst-Driven Innovations in Waste Management: From Degradation to Resource Recovery for Circular Economy
Abstract: Waste management has long been a critical challenge for modern societies, with the dual goals of minimizing environmental impact and maximizing resource recovery. Due to their large ecological footprints, conventional waste disposal techniques like landfilling and incineration have been shown to be unsustainable. In response, the focus has shifted toward innovative solutions that not only degrade waste but also recover valuable resources. Catalysts, with their remarkable ability to accelerate chemical …
Published in Journal of Catalyst & Catalysis · Vol. 11, Issue 2, 2024 · pp. 08–16 Read article
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Automated Vehicle Entry Monitoring System Using YOLOv5
Abstract: This project showcases an innovative You Only Look Once (YOLO) object detection model-based Automated Vehicle Entry Monitoring System for community gates. By using YOLO, the system transforms conventional access control paradigms by accurately and in real-time detecting vehicles that are seeking to gain entry. Unlike traditional approaches, the project leverages YOLO's effectiveness in vehicle recognition, classification and Number Plate Detection to improve residential security. By providing communities with a cutting-edge …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 2, Issue 2, 2024 · pp. 34–38 Read article
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Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 Read article