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10 articles for “Super critical extraction”
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A Novel Approach for Extraction of Polyphenols
Abstract: Polyphenols are class of compounds which are found in fruits, vegetables, walnuts, olives, tea leaves and many more. Polyphenols are antioxidant phyto-chemicals that prevent or neutralize the damaging effects of free radicals. They are secondary metabolites of plants and are generally involved in defence against ultra-violet radiation or aggression against pathogens. Polyphenols are various alcoholic compounds containing two or more benzene rings that each has at least one hydroxyl group …
Published in Emerging Trends in Chemical Engineering · Vol. 1, Issue 1, 2014 · pp. 31–36 Read article
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A Review of Machine Learning Applications in Web Data Mining
Abstract: The rapid development of Internet technology has resulted in a rapidly changing and intricate digital environment that requires new methods for organizing and evaluating online data. This study examines the use of machine learning (ML) in web data mining, focusing on its ability to extract relevant insights from huge amounts of online data. Web data mining, which is divided into three categories: content mining, structure mining, and use mining, uses …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 39–47 Read article
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Acoustic Sensing for City Flow: Quasi-Supervised Recognition of Sirens and Traffic for Urban Mobility Intelligence
Abstract: This paper frames environmental audio as a mobility telemetry source, extending a benchmark urban-sound corpus with transportation-critical classes—ambulance, firetruck, police, and traffic—and training spectrogram-based models under a quasi-supervised regime to support real-time city operations; leveraging 10-fold protocols, class-weighted objectives, and audiospecific augmentations (time stretch, pitch shift, SpecAugment, PatchAugment), the system benchmarks multiple CNN backbones combined with self-supervised learning paradigms enable the extraction of rich, discriminative acoustic representations, achieving strong multi-class …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 42–50 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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Early Detection of Alzheimer’s Disease Using Machine Learning Techniques
Abstract: Alzheimer's Disease (AD) is a progressive neurodegenerative condition impacting a large global population. Detecting AD early is critical for timely intervention and effective management. Conventional diagnostic approaches involve cognitive assessments and neuroimaging, which are often lengthy, costly, and prone to human error. In this paper, we propose a novel approach for early detection of AD using machine learning techniques applied to multimodal data, including neuroimaging, cognitive assessments, and biomarkers. Our …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 32–43 Read article
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Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
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Network Intrusion Detection System Using Decision Tree
Abstract: This paper presents a novel approach to network intrusion detection systems (NIDS) using advanced decision tree algorithms to address critical limitations in existing IDS solutions. Traditional IDSs often struggle with high false positive and negative rates, lack of scalability, and poor interpretability. Our proposed IDS leverages decision trees to enhance detection accuracy, interpretability, and scalability, thereby improving network security. Decision trees are chosen for their adaptive learning capabilities, transparent decision-making …
Published in Journal Of Network security · Vol. 12, Issue 2, 2024 · pp. 22–33 Read article
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A Comprehensive Tool for Authenticating Instagram Profiles Using Instaloader
Abstract: With the rapid growth of Instagram as a dominant social media platform, there is an increasing need for tools that allow users to extract, analyze, and monitor profile data efficiently. Instagram has become one of the leading platforms for personal branding, influencer marketing, business promotion, and public communication. As businesses and individuals seek to better understand their presence and influence on this platform, the need for reliable data extraction tools …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 93–98 Read article
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Eco-Friendly Elixirs: A Critical Review of Biosurfactants for Sustainable Wastewater Solutions
Abstract: Biosurfactants are the amphiphilic substances which are acquired from the remains of the living microorganisms and have attracted a lot of scientific interests because of their applicability in various fields. This review aims at reviewing current research and development on biosurfactants with special emphasis on their application in wastewater and oil. Biosurfactants being less hazardous to the environment are produced by microorganisms and works as a substitute for chemically produced …
Published in Emerging Trends in Chemical Engineering · Vol. 11, Issue 2, 2024 · pp. 14–33 Read article
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Self-Healing Polymeric Composites Reinforced with Green Synthesized Nanoparticles
Abstract: The development of sustainable self-healing polymeric materials is critical for enhancing durability and service life in advanced engineering applications. In this study, zinc oxide (ZnO), magnesium oxide (MgO), and ferric oxide (Fe₂O₃) nanoparticles were green-synthesized using Allium cepa extract and incorporated into epoxy-based polymeric composites to improve mechanical, thermal, and self-healing properties. This bio-based synthesis is eco-friendly and safe alternative to harsh chemical techniques, utilizing natural antioxidants to stabilize the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 305–314 Read article