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588 articles for “Extractive”
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Utilizing Machine Learning to Evaluate the Connection between Poisson's Ratio and the Petrophysical Properties of Reservoir Rocks
Abstract: The Poisson's ratio is a crucial cornerstone, illuminating our understanding of geomechanical behaviour in wells during the dynamic drilling process and the inspiring recovery journey. This research rigorously employs machine learning methods to analyse the significant impact of geophysical parameters on the Poisson ratio in hydrocarbon reservoirs found in oil fields. The analysis utilized data from multiple oil and gas fields, highlighting the crucial relationships between the Poisson ratio, the …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 33–43 Read article
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Formulation, Evaluation and Development of Multipurpose Cream Containing kokum Butter
Abstract: The creation of the multipurpose polyherbal crack-healing cream, which shields the skin from cracks and can also serve as a multifunctional cream to shield the skin from other skin issues. The polyherbal cosmetic formulation can be used to give skin a protective barrier and is safe to use. Over the course of the study, this multipurpose polyherbal cream demonstrated good homogeneity, pH, consistency, spreadability, and lack of phase separation. This …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 12, Issue 1, 2025 · pp. 78–89 Read article
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Automated Suspicious Activity Detection in Video Surveillance Using Deep Learning: A Review
Abstract: In the current era of advanced security systems, video surveillance plays an essential role in ensuring safety by detecting suspicious activities. With the increase in real-time data, manual monitoring has become impractical, paving the way for automated surveillance systems utilizing machine learning (ML) and artificial intelligence (AI) technologies. This paper explores the integration of ML and AI models, specifically convolutional neural networks (CNNs) and long short-term memory (LSTM) networks, for …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 20–27 Read article
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Polyherbal Cookies For Diabetic Patients: Formulation and Evaluation
Abstract: In order to control their hunger and obtain some energy, most people eat cookies for breakfast, snacks, and at leisure. Refined flour, sugar, and butter are the major ingredients of the various types of cookies that are sold in stores. Because they raise blood sugar levels, obese and diabetic individuals typically avoid them. As a result, we have created Polyherbal cookies in this latest study utilizing oats, wheat flour, and …
Published in Research & Reviews : Journal of Herbal Science · Vol. 14, Issue 2, 2025 · pp. 22–40 Read article
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Facial Emotion Detection and Its Applications
Abstract: Facial emotion detection (FED) is an interdisciplinary field that integrates artificial intelligence, computer vision, and machine learning to recognize and interpret human emotions based on facial expressions. The development of FED systems has been propelled by advancements in deep learning, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which enhance recognition accuracy. Feature extraction techniques, including geometric and appearance-based methods, play a crucial role in classifying emotional states. …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 8–12 Read article
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A Review on Phytochemical and Pharmacological Properties of Anacyclus Pyrethrum (Akarkara)
Abstract: The wild species Anacyclus pyrethrum, or A. pyrethrum, is a member of the Asteraceae family. It is commonly known as Akarkara. It originated in Spain, Morocco, and Algeria, and has since spread to Sri Lanka, India, Ukraine, Germany, Myanmar, France, and Poland. It is the benefits of bioactive compounds of plant found the chemical makeup, analgesic, anti-inflammatory, and wound-healing effects of hydroalcoholic extracts of A. pyrethrum’s roots, seeds, leaves, and …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 12, Issue 1, 2025 · pp. 102–110 Read article
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Garcinia cambogia Use of Weight Loss and Hepatotoxicity: A Review
Abstract: A complex disorder of hunger control and energy metabolism driven by certain biological variables is obesity. This study aims to evaluate the applications of Garcinia cambogia products for appetite suppression and fat burning. This little fruit, which looks a lot like a pumpkin, is marketed and used most frequently these days as a weight-loss supplement. Research has demonstrated that the fruit rind's main organic acid component, (−)-hydroxycitric acid (HCA), and …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 12, Issue 2, 2025 · pp. 08–14 Read article
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Herbal Shampoo: A Comprehensive Overview
Abstract: Shampoo is a cosmetic product designed mainly to use surfactants to clean away grease, dirt, and skin flakes from hair safely when used as intended. Today, shampoo not only cleanses the hair and scalp, but also helps stimulate hair growth and reduce hair loss. To achieve these goals, the shampoo industry incorporates a range of chemical additives that may present risks to consumers. It also acts as a conditioning agent, …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 12, Issue 2, 2025 · pp. 15–21 Read article
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A summary continuation analysis evaluating the prevalence and predictors of diabetic retinopathy in newly diagnosed type 2 diabetic patients.
Abstract: Context: Diabetic retinopathy (DR), the leading cause of acquired blindness in adults, affects approximately 93 million people globally. It is a serious complication of type 2 diabetes, resulting from prolonged damage to the blood vessels in the retina. Although largely preventable and treatable, DR continues to be the main cause of vision loss among working-age adults and significantly impacts quality of life. While most studies on DR in Nepal have …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 21–30 Read article
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Integrated Dam Automation: Real-Time Monitoring and Controlling Using IoT
Abstract: Dam automation is a critical area in water resource management, especially given the rising demand for sustainable and safe water control systems. An integrated approach to dam automation involves implementing advanced sensors and monitoring systems to improve structural safety, water quality, and resource management. This paper presents a comprehensive automation model that combines crack detection, convolutional neural networks (CNNs), water level monitoring, turbidity sensing, and rainfall data to ensure real-time …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 31–38 Read article
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Enhanced Biodiesel Production Via Encapsulation of Yeast Cells in Biocompatible Polymers
Abstract: Yeast-based biodiesel production offers a sustainable alternative to conventional fossil fuels. However, factors like harsh environmental conditions and shear stress during processing can limit yeast cell viability and overall biodiesel yield. This study explores the potential of encapsulation technology using biocompatible polymers to improve yeast performance in biodiesel production. Encapsulation can create a protective barrier for yeast cells, shielding them from harsh environments and shear stress during processing. This protection …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 57–62 Read article
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Comparative Study of AI-Driven Fashion Trend Prediction System Using AI and ML: A Review
Abstract: To overcome the challenges in fashion trend forecasting, researchers have introduced several advanced and data-driven approaches. One such method uses a long short-term memory (LSTM) model combined with an encoder-decoder architecture to extract meaningful fashion content and recognize styles from product images. This model achieves higher accuracy in predicting upcoming fashion trends by incorporating varying price intervals and has shown impressive results when evaluated on the Amazon fashion dataset. Another …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 2, 2025 · pp. 35–41 Read article
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Advances in Multiclass Oral Cancer Detection Using Spectroscopic and AI Techniques
Abstract: Oral cancer, primarily OSCC, is still a major health issue worldwide, especially in low-HDI countries. Early diagnosis is essential since survival rates for early detection are much higher than for late-stage detection. However, traditional methods like visual inspection and biopsy are time-consuming, invasive, and rely on the clinician's skill, which is a limitation in accessibility and efficiency. Oral cancer detection has just been revolutionized by recent advances in spectroscopic techniques, …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 3, 2025 · pp. 39–48 Read article
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The Silent Mineral: Structural Complexity and Industrial Utility of Natural Kaolin
Abstract: Kaolin, a naturally occurring aluminosilicate clay predominantly comprising the mineral kaolinite (Al₂Si₂O₅(OH)₄), exhibits a 1:1 layered silicate structure that imparts distinctive physicochemical properties suitable for extensive industrial utilization. Deposits of kaolin are broadly classified into primary (residual) and secondary (sedimentary) categories, each defined by their geological origin and mineralogical features. The industrial processing of kaolin encompasses stages such as raw material extraction, beneficiation, and purification, aiming to optimize parameters including …
Published in International Journal of Crystalline Materials · Vol. 2, Issue 1, 2025 · pp. 52–61 Read article
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Big Data in Chemistry: Problems and Answers
Abstract: The rapid growth of experimental and computational chemistry data, researchers now have access to vast datasets, presenting both significant opportunities and challenges. This paper explores the primary challenges associated with managing, processing, and utilizing big data in chemistry, including data heterogeneity, integration across various scales and systems, lack of standardized formats, and the need for advanced tools for data analysis. Additionally, the paper discusses the ethical concerns of data ownership, …
Published in International Journal of Cheminformatics · Vol. 2, Issue 1, 2024 · pp. 9–14 Read article
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A Multi-Criteria Analysis Based on Various Factors for Evaluation of Organic-Mineral Fertilizer Components
Abstract: This study explores the potential of organic-mineral fertilizers as sustainable alternatives to synthetic options, evaluating ten such fertilizers, including coffee grounds, poultry eggshells, bone meal, Fish Emulsion, compost, cow manure, wood ash, biochar, seaweed extract, and green manure. A multi-criteria analysis assessed factors like effectiveness, cost, environmental impact, availability, and waste potential. Coffee grounds and poultry eggshells performed best due to their high nutrient content and positive soil effects, with …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 32–44 Read article
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U-Net Based Approach for Automated Brain Tumor Classification
Abstract: Brain tumor detection and identification play vital roles in diagnostic procedures in the field of medicine, with the conventional analysis of MRI images requiring a lot of time and also subject to variability. The proposed study involves the use of a CNN-U-Net based approach for brain tumor detection and identification automatically. The study uses a database of 3,064 contrast-enhanced T1-weighted MRI images from 233 patients with the tumors of meningioma, …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 Read article
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Machine Learning-Based Disease Prediction: A Comparative Analysis for Diabetes, Brain Tumor, and Parkinson's Disease
Abstract: This paper presents a web-based disease prediction system that integrates machine learning and deep learning techniques to assist in the early detection of Parkinson’s Disease, Diabetes, and Brain Tumors. By utilizing clinical data and MRI images, the platform provides rapid and interpretable predictions to support proactive health management. Logistic Regression models are applied to classify structured datasets for predicting Parkinson’s disease and Diabetes, making use of their effectiveness in binary …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 44–54 Read article
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First Insights into Whole Genome Sequencing of the Mycobacterium tuberculosis Complex: Molecular Diversity and Drug Susceptibility Patterns in Senegal
Abstract: Background: We conducted a bibliographic analysis of the Mycobacterium tuberculosis complex (MTBC) in sub-Saharan Africa, which included the analysis of 8,139 genomic sequences from 34 of the 49 sub-Saharan African countries. Notably, only one complete sequence from Senegal was identified, which had been generated in the United States. Our primary objective was to utilize whole genome sequencing (WGS) to detect resistance in anti-tuberculous strains of the MTBC in Senegal. This …
Published in Recent Trends in Infectious Diseases · Vol. 2, Issue 1, 2025 Read article
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Role of Generative AI in Redefining Data Analytics
Abstract: The rapid evolution of data-driven technologies has introduced both significant challenges and promising opportunities within the field of data analytics. Among the most impactful advancements is Generative Artificial Intelligence (Generative AI), a groundbreaking subset of AI that is reshaping how data is interpreted, generated, and utilized. Unlike traditional analytical tools that rely solely on existing data patterns, generative AI possesses the capability to create synthetic data, simulate complex scenarios, and …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 01–07 Read article