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372 articles for “Extraction process”
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Crop Disease Prediction Using Image Processing
Abstract: For any country in the world, its livelihood depends on agriculture. However, crop diseases affect the production and food supply of any country because we are unable to detect crop diseases. This paper presents a machine learning CNN (convolutional neural network) model, which uses images of crops to detect diseases. This model detects the diseases in the early stage and provides us with a solution to the crop diseases. It …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 9–16 Read article
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Machine Learning Approaches Towards Resume Classification
Abstract: Finding the right person for an open position can be an unnerving task, especially when there are many applicants, and if the recruiter or the Human Resources department must sort and further categorize all those resumes then it will be a labor-intensive, time-consuming, and tiresome task. Additionally, human assessment of resumes may be biased and prone to mistakes. Manually screening the proper candidate's resume from the pool is not practicable; …
Published in International Journal of Electronics Automation · Vol. 1, Issue 2, 2023 · pp. 1–7 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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Evaluation of Speech Recognition System for Security Purposes using Comparative Correlation Method
Abstract: Humans rely heavily on language for communication and most often, speech (oral) is one of the commonest means of communication. The speech recognition system is a smart system which grants access to users by recognizing the speech of the authorized user. Speech recognition is smart and precise in terms of authentication and validation. The problem with most security systems is imbalance pitch estimation, random noise and increment in theft due …
Published in Current Trends in Signal Processing · Vol. 12, Issue 3, 2022 · pp. 1–9 Read article
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Application of Compressive Sensing for Sampling and Reconstruction of MRI Images
Abstract: In recent years, a new theory of compressive sensing has evolved which asserts that super resolved signals and images can be recovered with far fewer samples than that demanded by the Nyquist sampling theorem. It is required that the signal being sensed has a low information-rate meaning that it is sparse in original or some transform domain. Former approaches capture the complete signal and process it to extract the information. …
Published in Current Trends in Signal Processing · Vol. 6, Issue 2, 2016 · pp. 42–48 Read article
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Exploring Technologies for Extractive Text Summarization: A Review of Transformer and Reinforcement Learning Models
Abstract: In recent years, the size of information on the Internet has increased exponentially. Therefore, a solution is needed to transform large amounts of raw data into useful information the human brain can understand. Automatic Text Summarization (ATS) is a part of Natural Language Processing (NLP) that aims to take long texts and shorten them, keeping the most important information in a clear and easy-to-understand way. This research report explores methods …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 1–6 Read article
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Machine Learning Based Early Cataract Detection: A Predictive Modeling Approach
Abstract: Cataracts, characterized by dense cloudy areas in the eye’s lens, afflict more than 50% of elderly individuals, leading to impaired vision and potential blindness. Detecting cataracts at an early stage is crucial to facilitate simpler treatments, as neglecting the condition may necessitate complex eye surgery. To address this issue, we are creating a predictive system that identifies cataract disease by analyzing user-provided eye features. To achieve this, we leverage OpenCV, …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 2, 2023 · pp. 1–8 Read article
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Enhancing Mechanical and Durability Performance of Composite Material Using Egg Shell Powder and Copper Slag.
Abstract: This research aims to investigate the use of copper slag (CS) and Egg Shell Powder (ESP) as partial substitutes in polymer composite to enhance mechanical properties and durability. Considering that the construction sector is recognized for consuming a significant amount of resources in comparison to other industries, its further expansion poses a direct danger to resource availability. This could disrupt ecosystems, lower biodiversity, and have an effect on riverine and …
Published in Journal of Polymer & Composites · Vol. 12, Issue 6, 2024 · pp. 1–7 Read article
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Deep Learning based Solution for Leaf disease Detection in Crops and Fertilizer Recommendation
Abstract: The field of agriculture faces significant threats, including diseases that attack plant leaves. To address this issue, our system assists farmers in promptly detecting plant diseases using advanced technology. The user, typically a farmer, only needs to capture an image of the affected leaf and input it into our system. Our system then analyzes the uploaded image to accurately identify the specific disease afflicting the leaf. This analytical process is …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 31–40 Read article
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Data-Driven Life Prediction of Fiber-Reinforced Polymer Composites Using IoT Sensing and Machine Learning Algorithms
Abstract: The accurate prediction of fatigue life in fiber-reinforced polymer (FRP) composites remains a major challenge due to their nonlinear, multi-mechanism degradation behavior under variable loading conditions. This study presents a data-driven framework, H-LiProNet, which combines real-time IoT sensing with hybrid machine learning to estimate remaining useful life (RUL) in FRP composites. The proposed system integrates embedded Fiber Bragg Grating (FBG) and acoustic emission (AE) sensors to capture strain and damage …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 116–130 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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Design of an ArUco Marker-Guided Smart Trolley with Integrated Billing Estimation
Abstract: The growing adoption of automation in retail environments has increased the need for intelligent systems that improve user convenience and reduce manual effort. This paper presents the design and development of a human-following smart shopping trolley with an integrated automatic billing system based on computer vision. The proposed system employs ArUco marker–based human tracking to achieve reliable and real-time following behaviour. A Raspberry Pi serves as the central processing unit, …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 1, 2026 · pp. 55–65 Read article
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AI-Based Outfit Rating and Suggestion System
Abstract: The increasing demand for personalised fashion advice in the digital era has highlighted the need for intelligent, automated styling solutions. The AI-Based Outfit Rating and Suggestion System is a web- based platform that assists users in evaluating and improving their clothing choices through intelligent image analysis. Unlike conventional fashion applications that merely identify garment categories or suggest purchases, this system performs a holistic assessment of complete outfits by analysing colour …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 2, 2026 Read article
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Explainable GeoAI-Based Multi-Temporal Remote Sensing Framework for Early Detection of Climate-Induced Land Cover Transformation
Abstract: Climate change has emerged as one of the primary drivers of rapid land cover transformation, affecting ecosystems, agricultural productivity, biodiversity, and regional sustainability. Traditional remote sensing approaches often face challenges in detecting subtle and early-stage land cover changes due to limitations in temporal analysis and model interpretability. This study proposes an Explainable GeoAI-based multi-temporal remote sensing framework for the early detection of climate-induced land cover transformation using multi-source satellite imagery …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 2, 2026 Read article
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Recovery of Iron Values from Iron Ore Slimes using Reagents
Abstract: Mining wastes include waste generated during the extraction, beneficiation or processing of minerals like iron ore fines, slimes and tailings. Approximately 10–20% of the raw material is discarded as slimes in to slime ponds/tailing dams. Recovery of iron values from slimes result in economic benefit by utilization of waste as a resource and minimizes the threat to the environment. The iron ore slime is generally considered as waste due to …
Published in Journal of Materials & Metallurgical Engineering · Vol. 6, Issue 3, 2016 · pp. 32–43 Read article
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Automatic Traffic Monitoring and E-Challan Generation Using Matlab
Abstract: This paper deals with the efficient traffic management and automatic challan generation. In this era of modernization, with increasing number of vehicles it is quite impossible for Traffic Officers to maintain Traffic Rules in large Hi-Tech cities. So our aim is to minimise the work load of traffic personnel by automating a system that will itself detect a vehicle if it breaches the traffic laws. Using Matlab further process of …
Published in Journal of Control & Instrumentation · Vol. 10, Issue 1, 2019 · pp. 9–11 Read article
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Comparison of Tuning Methods of PID Controllers of Two Conical Tank System of Interacting Type
Abstract: The rapid increasing complexity of modern control systems has accentuated the idea of applying new modern approaches in order to solve design problems for various control engineering applications. This paper deals with the tuning of PID controllers for complex nonlinear process of two interacting Conical Tank Systems. Conical tanks play vital role in leaching extractions in pharmaceutical and chemical industries, as well as in food processing industry. It is a …
Published in Journal of Control & Instrumentation · Vol. 5, Issue 3, 2014 · pp. 8–14 Read article
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Design and Development of Screw Detection System : A case study
Abstract: This study explores the design of a vision-based screw detection and orientation system for industrial automation, inspection, and robot disassembly. By integrating machine learning algorithms like region-based convolutional neural networks (R-CNN) with traditional image processing and impedance sensing, the system performs real-time screw presence detection, head type identification, and alignment. Three key technologies—deep learning classification, edge-based geometric analysis, and impedance verification—are integrated into a single modular system. The findings indicate …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 30–36 Read article
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The Impact of Extraction Conditions on the Trend of the Type of Red Onion and the Characteristics of Oil Harvest for the Use of Constraints
Abstract: The therapeutic potential of plant-derived medicinal products, including essential oils, has not yet been fully exploited. Many medicinal plants have been studied to provide the biologically active compounds on which most modern drugs are based. However, much more remains to be learned about their precise pharmacology. This is particularly important for essential oils which have such a concentrated but complex composition. This is the reason for the interest they generate …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 16, Issue 2, 2025 · pp. 70–76 Read article
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Development of Herbal Mosquitoes repellent candle
Abstract: Citronella oil and essential oil are commonly used for their insect-repellent properties. They’re important for creating natural insect repellents, candles, and sprays, offering a safer alternative to chemical-based products. Citronella oil is particularly effective against mosquitoes, making it invaluable for outdoor activities and protecting against insect-borne diseases like malaria and Zika virus. Its pleasant scent also adds to its appeal as a natural air freshener. In a mosquito repellent study, …
Published in Recent Trends in Cosmetics · Vol. 1, Issue 2, 2024 · pp. 8–12 Read article