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1850 articles for “extractant”
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Animal Species Prediction Using Deep Learning
Abstract: In the face of escalating biodiversity loss, effective monitoring of animal species is critical for conservation efforts. This study presents a deep learning approach for species detection and a multimodal feature identification technique for animals vulnerable to poaching. The suggested prediction system recognizes objects automatically by the application of deep learning techniques to detect objects and then recognize them by using computer vision techniques, and it is triggered when an …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 14–22 Read article
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COMPARATIVE SEISMIC RESPONSE OF IRREGULAR HIGH-RISE RCC 25 STOREY BUILDINGS WITH AND WITHOUT SHEAR WALLS CONSIDERING P–DELTA EFFECT
Abstract: The seismic performance of high-rise reinforced concrete (RCC) buildings is significantly affected by plan irregularity, lateral stiffness distribution, and second-order (P–Delta) effects. Irregular structural configurations may generate torsional response and increased deformation demand under seismic excitation while geometric nonlinearity further amplifies displacement and internal forces in tall structures . This study presents a comparative seismic assessment of a G+24 storey RCC building having overall plan dimensions of 30,000 mm × …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 2, 2026 Read article
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Comparative Study of Structural, Optical, Morphological, and Magnetic Properties of BifeO3 Nanoparticles Synthesized Via Green and Chemical Methods
Abstract: BiFeO3 nanoparticles were synthesized via a green route using Strychnos nux-vomica leaf extract and a conventional chemical sol–gel method to study the effect of synthesis routes on their properties. XRD analysis confirmed phase-pure rhombohedral BiFeO3 for both samples. FTIR analysis was carried out to confirm the formation of the perovskite structure and to detect surface functional groups. FESEM analysis indicated a significant effect of phytochemicals in controlling particle growth and …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 16, Issue 1, 2026 · pp. 1–8 Read article
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A Study on “Clean" in Beauty: A Machine LearningApproach to Ingredient Transparency and ConsumerTrust
Abstract: The burgeoning "clean beauty" market, while driven by consumer demand for safer and more sustainable products, is plagued by ambiguous definitions and the pervasive challenge of "greenwashing". This ambiguity hinders informed consumer choices and complicates brand authenticity. This study addresses these complexities by developing a novel machine learning (ML) framework designed to objectively analyze cosmetic ingredient lists, classify products based on their "cleanliness" profile, and identify key ingredient attributes that …
Published in Recent Trends in Cosmetics · Vol. 3, Issue 1, 2026 · pp. 1–12 Read article
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“REVIEW ARTICLE ON TRIDAX PROCURMBENS HERBAL ANTIBACTERIAL CREAM”
Abstract: Abstract Tridax procumbens (L.), also referred to as coat buttons or tridax daisy, is a common plant in the Asteraceae family that is well-known for its exceptional pharmacological and therapeutic properties. This plant has long been utilized as an anticoagulant, antifungal, insect repellent, wound healer, and hepatoprotective agent in Indian Ayurveda. With a focus on its medicinal and formulation features, the current study offers a thorough summary of its botanical …
Published in Recent Trends in Cosmetics · Vol. 3, Issue 1, 2026 · pp. 21–29 Read article
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Optimized Machine Learning Framework for Battery State Prediction in Smart Charging Systems
Abstract: Good estimation of battery states, including State-of-Charge (SoC), State-of-Health (SoH), and Remaining Useful Life (RUL), are important in managing energy wisely and controlling the adaptive charging. This work introduces a streamlined machine learning model based on the ability to use multi-dimensional sensor measurements in terms of voltage, current, temperature, and cycle number to forecast battery conditions with high accuracy. Decent preprocessing, such as noise elimination, feature scaling, and calculated features, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 55–66 Read article
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Integrative Perspectives on Lipoma: Traditional Therapeutics from Siddha, Ayurveda, and Unani with Biomedical Correlates
Abstract: Background: Lipoma is the most common benign soft tissue tumor, with an incidence of approximately 2 per 1,000 individuals annually. Modern biomedicine attributes its pathogenesis to genetic abnormalities like HMGA2 rearrangements and dysregulated adipogenesis via PPARγ pathways. Effective pharmacological therapies are lacking. Traditional Indian systems – Siddha, Ayurveda, and Unani – offer unique perspectives and non‑surgical approaches yet remain underexplored in integrative research. Objective: To critically evaluate the descriptions, pathophysiological …
Published in Research & Reviews : A Journal of Unani, Siddha and Homeopathy · Vol. 13, Issue 1, 2026 · pp. 19–33 Read article
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Effect of Polyherbal Formulation on Blood Biochemical Parameters in Post-Weaned Ghoongroo Piglets with Diarrhea in West Bengal
Abstract: Weaning condition is one of the critical and challenging phases of piglet where they get separated from mother and exposed to different environment. Sudden and abrupt changes in the total environment lead to the increase of physical stress that leads to various diseases, such as diarrhea, to the piglets. Use of phytogenic feed additives other than antibiotics is safe not only to the livestock, but also to the consumers and …
Published in Research and Reviews : Journal of Veterinary Science and Technology · Vol. 15, Issue 1, 2026 · pp. 42–47 Read article
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Design and Analysis of Smart Solar EV Charging System
Abstract: The rising demand for electric vehicles (EVs) has generated an urgent requirement for sustainable and advanced charging systems. This study delineates the design and analysis of an intelligent solar EV charging system intended to reduce dependence on the grid and optimize the utilization of renewable energy. The system incorporates a solar photovoltaic (PV) array, battery energy storage, and an IoT-enabled smart controller to optimize power delivery. A Maximum Power Point …
Published in Journal of Power Electronics and Power Systems · Vol. 16, Issue 1, 2026 · pp. 06–15 Read article
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Modeling and Simulation of a Grid-Connected Solar-Wind Hybrid Renewable Energy System with Controlled Inverter
Abstract: Solar and wind energy offer eco-friendly and renewable options to conventional energy sources, holding great promise for the future. This research delves into the modeling and simulation of a grid-connected solar-wind hybrid renewable energy system employing a controlled inverter. The study examines the individual photovoltaic (PV) and wind energy conversion systems and investigates their seamless integration to create a powerful hybrid generation system. To maximize energy use, the application of …
Published in Journal of Thermal Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 22–32 Read article
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AI Powered Fault Detection in DC Motor using STM32
Abstract: This work presents the design and implementation of an embedded artificial intelligence system for real-time fault detection in a direct current (DC) motor using the STM32 Nucleo- F411RE microcontroller. The objective of the study is to develop a low-cost and efficient predictive maintenance solution capable of identifying abnormal motor behavior at an early stage. Vibration and temperature signals are acquired using an MPU6050 sensor and processed directly on the microcontroller …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 39–49 Read article
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A SEIR-Informed Stacked Fusion of Prophet, XGBoost, and LSTM for Ward-Level Epidemic Forecasting in Amravati Municipal Corporation
Abstract: Municipal epidemic preparedness depends on accurate short-horizon forecasts at fine spatial granularity. Ward-level incidence series are typically nonstationary due to changing contact patterns, interventions, reporting delays, and heterogeneous demographic and environmental factors. This paper presents a mathematically formulated hybrid forecasting architecture designed for Amravati Municipal Corporation (AMC). The method decomposes observed incidence into (i) a mechanistic SEIR baseline that enforces epidemiological structure and (ii) a data-driven residual learned using Prophet …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 17–23 Read article
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AI Voice Detection Tool
Abstract: In today’s digital era, distinguishing between AI-generated and human voices is more important than ever. This project introduces an AI-based voice detection system designed to accurately identify synthetic voices, ensuring security and authenticity across various applications like cybersecurity, media verification, and fraud prevention.Our system works by analyzing incoming audio samples and comparing them against a diverse database of both AI-generated and real human voices. Using advanced machine learning and signal …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 1, 2026 · pp. 1–8 Read article
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Mathematical Modelling of Semiconductor Device Physics: An Analytical Approach
Abstract: Semiconductor device physics forms the foundation of modern electronic and optoelectronic technologies. Mathematical modelling provides a rigorous framework for understanding, predicting, and optimizing the behavior of semiconductor devices by linking physical principles with device-level performance. This work presents an analytical approach to the mathematical modelling of semiconductor devices, emphasizing the derivation and interpretation of governing equations that describe charge transport and electrostatic behavior. The model is based on fundamental physical …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 36–42 Read article
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A Decade of Research on Polymer Manufacturing and Industry 4.0 Integration: A Comprehensive Bibliometric Review of Industry
Abstract: The advent of Industry 4.0 has brought a transformative revolution to the manufacturing sector by integrating advanced polymer technologies with intelligent, interconnected, and data-driven production systems. These developments have significantly reshaped industrial operations by improving efficiency, enhancing production flexibility, and enabling innovative manufacturing practices. Smart polymer processing, supported by automation, artificial intelligence, the Internet of Things (IoT), and real-time data analytics, allows manufacturers to optimize resource utilization, reduce waste, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1897–1905 Read article
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Harnessing Deep Learning to Explore Microbial Community Structure and Carbon Storage Capacity in Mangrove Ecosystems: A Framework for Computationally
Abstract: Mangrove ecosystems represent one of the most efficient natural carbon sinks on Earth, functioning as critical blue carbon habitats that sustain diverse microbial communities responsible for biogeochemical cycling and long-term carbon storage. Despite their global ecological significance, accurately quantifying and predicting carbon sequestration in mangrove systems remains challenging due to the complex interactions between microbial diversity, sediment chemistry, and environmental drivers. This study presents a comprehensive and sustainable artificial intelligence …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 41–49 Read article
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Aerodynamic Optimization of UAV Wings Using Machine Learning
Abstract: Unmanned Aerial Vehicles (UAVs) are increasingly deployed across defense, transportation, agriculture, and environmental monitoring, demanding improved aerodynamic efficiency to enhance endurance, stability, and payload capacity. Traditional aerodynamic optimization approaches, relying on computational fluid dynamics (CFD) simulations and wind tunnel experiments, are often time-consuming and computationally expensive. This study proposes a machine learning (ML)-driven framework for the aerodynamic optimization of UAV wing geometries, aiming to significantly reduce design cycles while improving …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 1–7 Read article
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SkinSight: Design and Implementation of an Intelligent Skin Type Detection System
Abstract: Identifying an individual’s skin type accurately is essential for creating personalized dermatological treatments and formulating skincare products that genuinely meet user needs. In this project, a real- time skin type classification system is developed using a combination of convolutional neural networks (CNNs) and modern computer vision techniques. The system processes live video streams, isolates the facial region through Haar cascade–based detection, and applies a series of preprocessing steps to enhance …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 35–45 Read article
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CNN-Based Diagnosis of Skin Cancer from Dermoscopic Images
Abstract: Skin cancer has become one of the diseases widely spread over the globe, with melanoma becoming a severe threat to one’s health. Detection of such diseases at the initial stage saves an individual from drastic damage. Using a Convolutional Neural Network (CNN) for detecting skin cancer through image classification as benign or malignant provides significant support to dermatological practice and reduces dependence solely on subjective visual examination. Dermatologists often face …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 1, 2026 · pp. 37–42 Read article
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SmartMed: An AI Powered Platform for Instant Medicine Access and Prescription Understanding
Abstract: Access to medicines during emergencies and the lack of prescription clarity remain significant challenges in modern healthcare systems. Most existing online pharmacy platforms primarily focus on home delivery services and do not provide real-time visibility of nearby pharmacy stock or intelligent prescription interpretation support. This limitation often delays treatment and creates confusion for patients. This paper presents a Smart Medicine Availability, Delivery, and AI Consultation System that integrates real-time pharmacy …
Published in Research and Reviews: A Journal of Medicine · Vol. 16, Issue 2, 2026 · pp. 1–15 Read article