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256 articles for “extraction method”
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Crop Yield Prediction Using Machine Learning Algorithm Based on Climate Variables
Abstract: India's economy is based primarily on agriculture, as over 50% of the country's population depends on it for their livelihood. The long-term viability of agriculture is seriously threatened by variations in the weather, climate, and other environmental factors. Because machine learning provides tools for decision assistance in agricultural yield prediction, including guidance on which crops to plant and when to plant them during the growing season, it is essential to …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 49–52 Read article
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The Role of Precision Agriculture in Enhancing Horticultural Crop Yields
Abstract: This article explores the quantification of lithium and mapping of mineral composition in crushed lithium ore utilizing two distinct calibration techniques with Laser-Induced Breakdown Spectroscopy (LIBS). Thirty samples from a pegmatite lithium deposit were analyzed, with representative mineral samples extracted, mixed with resin, and polished into disks. These disks underwent examination via an analyzer and an integrated mineral analyzer, facilitating mineral identification. The first calibration technique used empirical mineral chemistry …
Published in International Journal of Trends in Horticulture · Vol. 1, Issue 1, 2024 · pp. 18–23 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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Study of Evaluating the Feasibility of Banana Stem Fibers and Sugarcane Husk as a Sustainable Additive in Pervious Concrete for Urban Pavements
Abstract: This study explores the integration of eco-friendly materials: banana stem fibers and sugarcane husk, into pervious concrete to enhance its mechanical properties while maintaining high permeability. The research addresses environmental concerns related to agricultural waste disposal and the resource-intensive nature of traditional construction materials. Banana stem fibers, known for their tensile strength and durability, and sugarcane husk, rich in lignin and cellulose, were selected as reinforcements. The fibers were extracted, …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 33–39 Read article
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Depression Detection Using Machine Learning: A Comprehensive Review
Abstract: Depression remains one of the most prevalent mental health conditions globally, yet it frequently goes undiagnosed due to the reliance on subjective evaluation methods. With the growing availability of digital behavioral data and significant progress in machine learning (ML), new possibilities have emerged for the automated detection of depression. This review offers a detailed examination of recent advancements in ML-driven approaches to identifying depressive symptoms. It covers a range of …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 27–32 Read article
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A Review on Banana Fiber Reinforced Polymer Composites through Advanced Surface Treatments and Manufacturing Techniques
Abstract: In today's rapidly evolving world, heightened environmental concerns and stringent government regulations have spurred scientists and researchers to seek biodegradable and renewable alternatives to synthetic materials. Natural fibers, derived from resources like banana, jute, bagasse, and sisal, offer distinct advantages such as low density, comparable strength, non-toxicity, cost-effectiveness, and minimal waste disposal issues over synthetic counterparts. Extensive research has explored the potential applications of these natural fibers, with banana fibers …
Published in Trends in Mechanical Engineering & Technology · Vol. 14, Issue 3, 2024 Read article
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Exploring Wheat Derivatives in Cosmetic Formulations: An in-Depth Analysis of Efficacy And Applications
Abstract: Natural and environmentally friendly, herbal cosmetics made from organic plant-based ingredients are becoming more and more popular in the skincare sector. These products meet the growing demand from consumers for safer, more environmentally friendly personal care products by substituting plant extracts for synthetic ingredients. Herbal cosmetics target a range of skin issues, including dryness, aging, and acne, by utilizing the medicinal qualities of plants including chamomile, green tea, and aloe …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 12, Issue 1, 2025 · pp. 22–34 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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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. 17, Issue 2, 2026 Read article
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Sustainable Cotton Crop Productivity through Precision Weed Detection: A Deep Learning-Based Approach with UAV Integration
Abstract: Weeds present a major challenge to crop productivity by competing with crops for vital resources, including water, sunlight, and nutrients, often resulting in significant yield reductions. On a global scale, weeds are responsible for approximately 13.2% of annual crop losses, a quantity sufficient to feed nearly one billion people. These invasive plants disrupt agricultural systems and adversely impact crop yields. Given their uneven distribution in fields, ground or aerial robots …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 19–26 Read article
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An Intelligent Neural Networks Approach for Monitoring of Soilless Urban Farms
Abstract: Urban agriculture is increasingly recognized as a sustainable approach to addressing food security challenges in rapidly growing and densely populated cities. Conventional soil-based farming often faces limitations such as space scarcity, excessive water consumption, and environmental degradation. To overcome these challenges, soilless farming techniques such as hydroponics and aeroponics have gained significant attention due to their efficient utilization of space, reduced water requirements, and potential for year-round crop production. However, …
Published in Journal of Water Resource Engineering and Management · Vol. 12, Issue 3, 2025 · pp. 31–37 Read article
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Assessing the Performance of DL Methods in Handwritten Digit Recognition
Abstract: Handwritten digit recognition is a computer vision task that involves the automatic identification and classification of hand-written digits. The objective is to develop models capable of accurately recognizing and distinguishing digits handwritten by humans. With the development of machine learning and deep learning techniques, this field has advanced remarkably. The convolutional neural network (CNN) is the most often used technique for this purpose. By utilizing CNN, the model can learn …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 25–32 Read article
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Hybrid Techniques in Mango Leaf Disease Identification: Evaluating Neural Networks and Support Vector Machines
Abstract: Mango leaf diseases pose a significant threat to mango production, impacting both yield and fruit quality. Early and accurate detection of these diseases is crucial for effective management. This paper evaluates the use of hybrid techniques, specifically the integration of neural networks (NNs) and support vector machines (SVM), in the identification and classification of mango leaf diseases. NN excel in extracting complex features from images, while SVMs are robust classifiers, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 19–27 Read article
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Detection of Phishing Website Using URL
Abstract: Phishing attacks are one of the greatest threats to online security, where fraud websites deceive users into giving out sensitive information. Traditional methods of detection, such as blacklists and heuristic-based systems, often fail in identifying newly created or sophisticated phishing websites. This study proposes an intelligent phishing website detection system using Convolutional Neural Networks (CNNs) in analyzing URLs and associated features. Using labeled URLs, the system employs such attributes such …
Published in Journal Of Network security · Vol. 13, Issue 1, 2025 · pp. 10–15 Read article
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Energy Harvesting Circuits with Piezoelectric Material: Design, Integration, and Optimization
Abstract: Piezoelectric energy harvesters (PHE) have drawn significant interest as a method of harvesting environment energy to power because of its compatibility and high energy density. Integrating piezoelectric energy harvesters into wireless sensor networks, Internet of Things (IoT)) devices, and wearable electronics enhances their functionality and also increases sustainability. This integration can be lead to the development of self-powered devices that can operate continuously without the need for external power sources. …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1028–1039 Read article
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Advances in Analytical Techniques for Water Quality Assessment
Abstract: Assessing the quality of water is essential for preserving ecological balance and public health. This study evaluates new developments in analytical methods that are meant to improve the accuracy, effectiveness, and reach of water quality monitoring. While fundamental, conventional procedures like spectrophotometry and chromatography have drawbacks in terms of sensitivity and real-time capability. By allowing quick and precise pollutant and contaminant identification, emerging technologies such as sensor networks, remote sensing, …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 2, Issue 1, 2024 · pp. 1–7 Read article
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Fake Product Detection Using Convolutional Neural Networks
Abstract: The widespread circulation of counterfeit products in global markets presents a significant threat to both consumer trust and the integrity of established brands. With the advancement of artificial intelligence, particularly deep learning, there is growing potential to develop more sophisticated systems to combat this issue. This study introduces a novel counterfeit detection framework using the VGG16 Convolutional Neural Network (CNN) to distinguish between authentic and counterfeit products through image analysis. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 08–15 Read article
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Dimensionality Reduction Techniques and their Applications in Cancer Classification: A Comprehensive Review
Abstract: Dimensionality reduction techniques have become a vital tool in the investigation of high-dimensional data like gene expression profiles in cancer research. Here is a review, we deliver a comprehensive overview of dimensionality reduction techniques and their applications in cancer classification. Firstly, we introduce the concepts and approaches of dimensionality reduction, and after that, we explore several methods for decreasing dimensionality. These techniques include Linear Discriminant Analysis (LDA), Principal Component Analysis …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 1, Issue 2, 2023 · pp. 35–45 Read article
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Advancement in Image Classification: Media Player Control Using Hand Gestures
Abstract: We explore the development of picture categorization methods in this paper, with an emphasis on how they are used to manipulate media players with hand gestures. Our investigation focuses on the development of machine learning techniques, particularly on supporting vector machines (SVM) and convolutional neural networks (CNN). SVMs are used to identify and authenticate people from digital photos or video clips, but CNNs are great at face detection, which is …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 1–10 Read article
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Exploring The Therapeutical Potential Of Pongamia Pinnata For Herpes Simplex Virus Type 1 (HSV-1)
Abstract: Objective: Pongamia pinnata (L.), commonly known as Indian beech or pongam tree, is a tropical plant renowned for its medicinal properties in traditional medicine systems. Extracts derived from various parts of Pongamia pinnata have demonstrated antimicrobial, anti-inflammatory, and immunomodulatory activities. Such attributes make it a compelling candidate for exploring its therapeutic potential against HSV infections. Thymidine kinase is the target protein mostly used in the treatment of HSV1 infections. In …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 15, Issue 1, 2025 · pp. 1–9 Read article