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169 articles for “extraction efficiency”
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Intelligent Design Approaches in Microwave Engineering Using Machine Learning Techniques
Abstract: In microwave engineering, machine learning (ML) has become a potent technology allowing quicker design cycles, improved modelling accuracy, and automatic optimisation of complicated systems. Recent developments in the use of ML methods to microwave components and systems, including antennas, filters, and high-frequency circuits, are summarised in this study. In the framework of electromagnetic simulation, surrogate modelling, and parameter extraction, supervised and unsupervised learning algorithms are addressed. Moreover, the study looked …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 31–38 Read article
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Bioscouring And Anionization of Waste Cotton Fabric for Efficient Removal of Malachite Green Dye
Abstract: Adsorption is an efficient method for dye removal but the high cost of adsorbents limits its use, emphasizing the need for sustainable, low-cost alternatives. This study explores the usage of modified cotton fabric for the treatment of malachite green (cationic dye) from wastewater. Cellulase extracted from Raphanus sativus and Daucus carota were evaluated for bioscouring potential which was confirmed by scanning electron microscopy. Further, cotton fabric was chemically modified using …
Published in Journal of Water Pollution & Purification Research · Vol. 13, Issue 1, 2026 · pp. 53–68 Read article
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Evaluating the Influence of Temperature on the Efficacy of Capparis Decidua Extract as a Corrosion Inhibitor for Aluminium in Acidic Media
Abstract: The study investigates the anti-corrosive properties of the ethanolic extract of Capparis decidua fruit on aluminum corrosion in a 2N HCl acid solution, using a weight loss technique at temperatures ranging from 303 to 343 K. At a concentration of 0.45%, the inhibition efficiency (η%) is notably high, reaching 63.15% at 303 K. The inhibitor's adsorption behavior on the aluminum surface is consistent with the Langmuir adsorption isotherm, suggesting that …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 15, Issue 3, 2024 · pp. 58–65 Read article
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Emerging Trends in Data Structures for Modern Machine Learning Applications
Abstract: In the realm of machine learning, data structures play a pivotal role in facilitating efficient data manipulation, storage, and retrieval, thereby significantly impacting the performance and scalability of machine learning algorithms. In recent years, the field of machine learning has witnessed the emergence of novel data structures tailored to address scalability and efficiency challenges inherent in handling large-scale and high-dimensional data. This study provides a look at the data preprocessing, …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 1, 2024 · pp. 1–7 Read article
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Multi-Parameter Biomedical Sensor-Based Mental State Classification Using EEG And Deep Learning Techniques
Abstract: With mental health concerns becoming increasingly widespread, there is a strong need for systems that can monitor conditions like stress, anxiety, and fatigue in a continuous and non- invasive manner. This research proposes a novel multi-parameter biomedical sensing framework for mental state classification by integrating electroencephalography (EEG) signals with physiological parameters, including body temperature acquired using LM35 sensors, heart rate from pulse sensors, and blood oxygen saturation (SpO₂) measurements. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 Read article
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pH-Triggered In-Situ Nasal Gel Systems for Migraine Therapy: A Review
Abstract: Intranasal drug delivery has gained considerable attention as a non-invasive route for delivering drugs to both systemic circulation and the central nervous system, particularly for the treatment of migraine. Traditional nasal formulations such as sprays and drops often show poor therapeutic performance due to rapid mucociliary clearance and limited retention within the nasal cavity. To overcome these challenges, in-situ gel systems have been designed, which transform from a liquid to …
Published in Trends in Drug Delivery · Vol. 13, Issue 2, 2026 Read article
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A Novel Approach to Fingerprint Authentication Using Histogram Oriented Gradients for Feature Extraction and Machine Learning Convolution Neural Network for Classification
Abstract: With applied biometrics, it is possible to identify a person by examining a feature vector of attributes derived from their physical and behaviour characteristics. In biometrics, fingerprints have become one of the most famous and well known techniques of identification and authentication. In light of technological advancements and safety, fingerprint recognition has been successfully used in a variety of Civil, Defence, and Commercial applications for more than a decade. The …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 1–12 Read article
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Application of Convolutional Neural Networks in Design of Efficient Pipe Flow System
Abstract: Convolutional Neural Networks exhibit remarkable capabilities in flow pattern recognition, pressure drop prediction, leak detection, and system optimization through their ability to process complex spatial and temporal data patterns. The study examines CNN architectures specifically adapted for fluid dynamics applications, including data preprocessing techniques, feature extraction methods, and performance optimization strategies. Key applications include real-time flow monitoring, predictive maintenance, design parameter optimization, and anomaly detection in pipe networks. Comparative analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 1–9 Read article
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ML Model Comparison for Sentiment Analysis Across Diverse Datasets
Abstract: Analyzing sentiment is crucial for understanding public opinion on various issues in marketing, politics, and social sciences. This study compares the performance of seven different machine learning algorithms for sentiment classification, focusing on their effectiveness, accuracy, and complexity. The research is conducted on a pre-processed dataset with balanced text samples, utilizing feature extraction methods such as Term Frequency-Inverse Document Frequency (TF-IDF). The performance assessment criteria consist of accuracy, precision, recall, …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 26–33 Read article
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Log Identification and Monitoring System Using Generative AI
Abstract: In contemporary software ecosystems, application and infrastructure logs play a vital role in ensuring system reliability, performance optimization, fault diagnosis, and security compliance. As applications become increasingly distributed and cloud native, the volume, velocity, and variety of generated log data have grown dramatically. This rapid expansion makes traditional manual log inspection inefficient, error-prone, and largely impractical. To address these challenges, this paper proposes an artificial intelligence (AI) driven log monitoring …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 08–16 Read article
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Sustainable Innovations in Home Decor: Exploring Eco-friendly Paint Materials and Recycled Interior Applications
Abstract: This paper delves into sustainable practices in home decorating, particularly focusing on eco-friendly paint products and innovative interior design solutions. It underscores the significance of zero-VOC and low-VOC coatings for indoor air quality and environmental safety, advocating for their use. Natural colors derived from plant extracts, clay, and minerals are highlighted for their biodegradability and availability in earthy tones, emphasizing their contribution to environmental sustainability. Milk-based paints are explored for …
Published in International Journal of Sustainability · Vol. 1, Issue 1, 2024 · pp. 10–20 Read article
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Revolutionizing Document Analysis Using AI Based Text Extraction Methods
Abstract: The AI Document Analyzer is an innovative application created to revolutionize how we engage with and comprehend textual data. By integrating a range of advanced technologies, including Next.js, Drizzle ORM, OpenAI, Stripe, TypeScript, and Tailwind, this tool offers a comprehensive solution for document comprehension. Central to its functionality is a chat-based interface powered by the ChatGPT API, allowing users to engage in natural language conversations with their uploaded documents. This …
Published in Current Trends in Information Technology · Vol. 14, Issue 2, 2024 · pp. 40–46 Read article
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Blind Image Quality Assessment using NSS Approach in the DCT Domain
Abstract: We have develop an efficient model for improving image quality using IQA and NSS based on blind image Quality Assessment. This algorithm does computation for the parameters which user expect at output. The certain extracted features approach depends on a simple Bayesian inference model to dipict image quality scores. The project features are based on statistic scenes of discrete cosine transform for images. The resultant parameters of the model are …
Published in Recent Trends in Electronics Communication Systems 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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Neuromorphic Self-Learning Polymer–MXene Photovoltaic Composites with Embedded Memristive Energy Routing for Adaptive Solar Energy Harvesting
Abstract: This dynamic and fast-growing intelligent renewable energy system requires photovoltaic materials that can autonomously adapt to fast-changing environmental conditions. In this study, a novel system is proposed for adaptive harvesting of solar energy based on Neuromorphic Self-Learning Polymer–MXene Photovoltaic Composites (NSPMPCs) with embedded memristive energy routing networks. To boost the charge generation and charge transport in the polymer–MXene heterostructure, the flexibility and processability of conductive polymers are integrated with the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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A Comprehensive Review on the Miniaturized Analytical Techniques for Sustainable Pharmaceutical Testing
Abstract: Miniaturized analytical techniques are revolutionizing pharmaceutical testing by offering sustainable and efficient alternatives to traditional methods. These techniques are designed to reduce sample and reagent consumption, minimize waste generation, and accelerate analysis, aligning perfectly with the principles of green analytical chemistry. This comprehensive review aims to thoroughly explore the landscape of miniaturized analytical techniques, specifically highlighting their profound impact on fostering sustainable practices within the pharmaceutical sector. The review systematically …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 17, Issue 1, 2026 · pp. 18–39 Read article
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Removal of Lead (II) ions from Water by using green nanoTrimanganese Tetroxide
Abstract: Inorganic pollutants like heavy metal ions and organic pollutants like pesticides and dyes are the main causes of water pollution. These contaminants cause serious issues for the environment and public health when they are present. To get rid of these contaminants from water bodies, several methods are employed.Due to its ease of use, great efficiency, abundance of adsorbents, and low sludge creation, adsorption is the most advantageous method for purifying …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 691–700 Read article
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Formulation and Evaluation of Topical Anti-Acne Gel from Coriander and Garlic Extract
Abstract: Objective: To develop and evaluate a topical anti-acne gel formulated using aqueous extracts of coriander (Coriandrum sativum) and garlic (Allium sativum). The study aims to assess the antibacterial efficacy of the gel against acne-causing bacteria, specifically Propionibacterium acnes. Methods: 1.Extraction: Coriander Extract: Aqueous extraction was performed by soaking coriander seeds in distilled water, followed by filtration. Garlic Extract: Non-chemical extraction involved mixing crushed garlic with honey in a 1:1 ratio …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 11, Issue 3, 2024 · pp. 10–15 Read article
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Green Synthesis of Cobalt Oxide Nanoparticles Using Delonix regia Leaf
Abstract: Green synthesis of nanoparticles offers a sustainable and eco-friendly alternative to conventional methods. This study explores the biosynthesis of cobalt oxide nanoparticles (Co3O4 NPs) using Delonix regia leaf extract as a reducing and stabilizing agent. The synthesized Co3O4 NPs were characterized by UV-visible spectroscopy, Fourier transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM), confirming their uniform spherical morphology with an average size of …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 16, Issue 1, 2025 · pp. 30–38 Read article
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Innovative CNN Strategies for Superior Handwritten Digit Recognition
Abstract: Handwritten digit recognition is a fundamental problem in the field of computer vision and machine learning with numerous applications, such as postal code recognition, bank check processing, and digitizing historical documents. Convolutional Neural Networks have demonstrated remarkable success in various image recognition tasks, making them a popular choice for digit recognition. In this study, we present an enhanced approach to handwritten digit recognition using CNNs. Handwritten digit recognition plays a …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 1, 2024 · pp. 27–34 Read article