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1850 articles for “extractant”
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AI Driven IoT based Satellite remote sensing system: KSK Approach in Satellite Remote Sensing
Abstract: The convergence of the Internet of Things (IoT) and satellite remote sensing has traditionally been bottlenecked by massive data latency and limited downlink bandwidth. This paper proposes a decentralized framework for an "AI-Driven IoT-based Satellite Remote Sensing System," which shifts the paradigm from raw data transmission to onboard edge-intelligence. By integrating lightweight convolutional neural networks (CNNs) directly into satellite payloads, the system performs real-time feature extraction and anomaly detection before …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 50–57 Read article
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A Hybrid model of ResNet50 integrated U-Net for image Denoising for Polymer and Composite Microstructure Analysis
Abstract: In digital era a high-quality imaging plays a very important role in polymer and composite material characterization features such as fiber-matrix interfaces, voids, microcracks cause problems in mechanical and functional properties. Polymer imaging includes optical microscopy and scanning electron microscopy, due to sensor limitation, environmental conditions add noise to the image and reduce quality of image. The noise degrades image quality, and it leads to reduce reliability in material analysis. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 592–602 Read article
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Innovations in Mineral Science and Engineering for Sustainable Resource Development
Abstract: The growing global demand for mineral resources, coupled with increasing environmental and social concerns, has intensified the need for sustainable approaches in mineral science and engineering. Traditional mining and mineral processing practices, while essential for industrial development, are often associated with high energy consumption, resource depletion, and environmental degradation. In response, recent innovations in mineral science and engineering have focused on improving resource efficiency, minimizing environmental impact, and ensuring long-term …
Published in International Journal of Minerals · Vol. 3, Issue 1, 2026 · pp. 31–36 Read article
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Eco-Efficient Skies: Life Cycle Assessment and Carbon Footprint Minimization of Fiber-Reinforced Polymer Composites in Aerospace Application
Abstract: The increasing integration of fiber-reinforced polymer (FRP) composites in aerospace structures necessitates a rigorous evaluation of their environmental sustainability throughout their entire life cycle. This study presents a comprehensive life cycle assessment (LCA) and carbon footprint analysis of carbon fiber-reinforced polymer (CFRP) and glass fiber-reinforced polymer (GFRP) composites applied to structural and semi-structural components in commercial aerospace applications. Following ISO 14040/14044 standards and employing the ReCiPe 2016 Midpoint (H) impact …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 147–160 Read article
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IoT-Enabled Self-Monitoring Polymer Composites for Solar Facade Systems with Cloud-Based Thermal Analytics
Abstract: The increasing demand for intelligent and energy-efficient building systems has hastened the production of smart solar facade systems. This paper presents an IoT-based self-monitoring polymer composite system, which includes thermal analytics running on the cloud to provide real-time assessments of the performance of the facade. The artificial composite panel has sensing capability built in which the material is able to measure both surface and internal thermal behavior simultaneously in dynamic …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 657–681 Read article
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Disaster Impact Assessment Using Multi-Sensor Satellite Data: An AI-Based Remote Sensing Approach
Abstract: Natural disasters such as floods, earthquakes, and wildfires cause significant damage to human life and infrastructure every year. Rapid and accurate assessment of the affected areas is essential for effective disaster response and recovery planning. Traditional image-based analysis using single-sensor data often fails under adverse conditions such as cloud cover, smoke, or poor lighting. To overcome these limitations, this study proposes a novel framework for disaster impact assessment using multi-sensor …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 10–22 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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Study of the Antibacterial Activity of Artemisia Absinthium against E. coli bacteria Isolated from Urinary Tract Infections
Abstract: Twenty clinically diagnosed samples were collected using transport medium swabs from the operating room at Al-Amal Specialized Laboratory in Iraq between November 2025 and February 10, 2026. Antibiotic susceptibility testing was performed on the 20 Escherichia coli samples. The results showed a clear difference in the bacterial isolates' response to the tested antibiotics. Imipenem demonstrated the highest inhibition rate, reaching 24.55% (100%), compared to the other antibiotics used in the …
Published in Recent Trends in Infectious Diseases · Vol. 3, Issue 2, 2026 · pp. 17–25 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Heavy Metal Removal from Textile Industrial Effluent using Banana Exocarp Derived Cellulose Acetate Graphene Nanocomposite Membranes
Abstract: The disposal of textile effluent is responsible for serious human health concerns and above all environmental concerns to all kind of species. This indicates that there is immediate and urgent need of emerging, efficient with sustainable recycling technologies. In this paper, banana exocarp as agriculture-based waste, in terms of substrate was utilised as major raw material. The extracted cellulose from the substrate with homogeneous acetylation process, transformed into cellulose acetate …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 51–62 Read article
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Minerals: A Comprehensive Review of Classification, Properties, Formation, and Their Role in Modern Technology and Sustainability
Abstract: Minerals are naturally occurring, inorganic, solid elements with a definite chemical composition and a characteristic crystal structure. They are the building blocks of rocks. Minerals are the key to the development and progress of human civilization. They are used for the development of infrastructure, electronic gadgets, agriculture, and medicine. This research paper aims to present an exhaustive overview on the field of mineralogy, which includes the definition, classification, physical and …
Published in International Journal of Crystalline Materials · Vol. 3, Issue 1, 2026 · pp. 25–33 Read article
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Balancing Growth and Sustainability: Developing a Socio-ecological Urban Design Framework for Edge Cities
Abstract: In the rapidly urbanizing world, edge cities, urban areas situated on the outskirts of larger metropolitan regions have emerged as dynamic centres of economic activity. However, their development often prioritizes growth over sustainability, leading to ecological degradation and social inequities. This dissertation presents a socio-ecological urban design framework aimed at balancing growth with sustainability in edge cities. By integrating principles from ecology, sociology, and urban planning, this framework addresses the …
Published in International Journal of Urban Design and Development · Vol. 4, Issue 2, 2026 · pp. 1–24 Read article
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Multi-Scale Analysis of Polymer Based Energy Storage Systems for High Performance Battery Applications
Abstract: The energy storage systems based on polymers are becoming promising materials for the next generation of high performance batteries because of their excellent mechanical flexibility, improved safety, and favorable electrochemical properties. Even with computational tools in Python, polymer-based energy storage systems remain plagued by poor ionic conductivity, complicated electrochemical reactions and potential thermal runaway. Therefore, a multi-scale model is proposed to improve battery performance, thermal stability, reliability, and large-scale deployment …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1035–1048 Read article
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Seasonal Dynamics of Coastal Landscapes: A Critical Review Using Remote Sensing and GIS
Abstract: Coastal landscapes are among the most dynamic environments on Earth, undergoing continuous transformation due to both natural processes and anthropogenic activities. In India, particularly along the southern coastal regions of Andhra Pradesh, Tamil Nadu, and Kerala, shoreline morphology and sediment transport patterns are significantly influenced by seasonal monsoons, cyclones, storm surges, waves, tides, and changing river discharges. These factors contribute to varying rates of coastal erosion, accretion, inundation, and land- …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 2, 2026 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. 16, Issue 2, 2026 · pp. 15–27 Read article
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Nanotechnology-Based Cosmeceuticals for Anti-Aging and Skin Regeneration
Abstract: Nanotechnology has transformed the cosmetic industry of the cosmeceuticals by allowing the production of sophisticated delivery systems that improve the stability, penetration, bioavailability, and therapeutic efficacy of active ingredients in cosmetics. The present review identifies the value of nanotechnology-based cosmeceuticals in anti-aging and skin regeneration, with special focus on the recent developments in nanocarrier technologies and their use in dermatology. Many nanocarriers have exhibited great potentials in enhancing delivery of …
Published in Recent Trends in Cosmetics · Vol. 3, Issue 2, 2026 · pp. 33–45 Read article
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Bias Detection and Accuracy Enhancement in Voice-based Banking Authentication Using Deep Learning
Abstract: Biometric systems have become an integral part of how many people access banking services today, and voice verification systems can be a secure and easy-to-use source of banking authentication that does not require any physical contact with the bank or any other person. From the security perspective, these systems would normally provide an effective means of identifying an individual but frequently exhibit bias with respect to demographics such as the …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article
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AI-Based Outfit Rating and Suggestion System
Abstract: The increasing demand for personalised fashion advice in the digital era has highlighted the need for intelligent, automated styling solutions. The AI-Based Outfit Rating and Suggestion System is a web- based platform that assists users in evaluating and improving their clothing choices through intelligent image analysis. Unlike conventional fashion applications that merely identify garment categories or suggest purchases, this system performs a holistic assessment of complete outfits by analysing colour …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 2, 2026 Read article
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Generative Design of Bioactive Orthopedic Composites for Fracture Repair Using an Integrated Conditional GAN–Transformer Framework: A Multi-Objective Approach
Abstract: Orthopedic composite implants for fracture repair must simultaneously satisfy conflicting mechanical and biological demands: high fracture toughness, sufficient compressive stiffness, and bioactive surface chemistry enabling osteoblast adhesion and mineralization. Existing design approaches rely on trial-and-error experimentation, yielding sub-optimal trade-offs between these objectives. This paper presents an integrated conditional Generative Adversarial Network–Transformer (cGAN-T) framework for fully computational, multi-objective generative design of hydroxyapatite (HA)-reinforced polymer composite microstructures targeting Orthopedic fracture repair. A …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 21–35 Read article
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A Conceptual Framework for AI-Integrated Metabolomics in Predictive Health Systems for Resource-Constrained Environments
Abstract: The increasing prevalence of non-communicable diseases (NCDs) continues to place a significant strain on healthcare systems, particularly in low- and middle-income regions where access to early diagnostic infrastructure is limited. Conventional healthcare approaches remain largely reactive, often detecting diseases at advanced stages when treatment effectiveness is reduced. This challenge underscores the need for predictive, cost-effective, and data-driven healthcare solutions. This study presents a conceptual framework that integrates metabolomics with artificial …
Published in Emerging Trends in Metabolites · Vol. 3, Issue 2, 2026 Read article