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731 articles for “extraction methods”
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Automated Plant Disease Detection and Treatment Advisor Using Artificial Intelligence
Abstract: Automated plant disease detection and treatment advisors using artificial intelligence represent a significant advancement in modern agriculture. The identification of plant leaf diseases is essential to maintaining food security and agricultural output. Machine learning models, particularly deep learning algorithms like convolutional neural networks (CNNs), are trained on labeled datasets containing images of healthy and diseased plants. These models learn to classify images into different disease categories with high accuracy. Convolutional …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 1–7 Read article
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Improved Vision Based Algorithm for Deep Web Data Extraction
Abstract: Several systems and languages have been proposed for solving web-data management problems, but none of existing system addresses all the problems from a unified perspective. Most of the existing link analysis algorithms treat a web page as a single node in the web graph. However, in most cases, a web page contains multiple semantics and hence the web page might not be considered as the atomic node. New web content, …
Published in Journal of Web Engineering & Technology · Vol. 2, Issue 2, 2015 · pp. 28–37 Read article
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Organic Phase Speciation of 36% Tri-Iso Amyl Phosphate/N-Dodecane Solvent during Nitric Acid Extraction
Abstract: Several solutions of 36% TiAP/n-dodecane solvent were equilibrated with different concentrations of aqueous nitric acid solutions at 298.15 K at a phase ratio of unity. The resultant equilibrated aqueous and organic solutions were analyzed for acidity. A three-solvate model with molecular HNO3 based mechanism was assumed for nitric acid extraction by TiAP. This model was analogous to the 3-solvate model for nitric acid extraction by TBP, recently reported by authors. …
Published in Journal of Nuclear Engineering & Technology · Vol. 5, Issue 2, 2015 · pp. 28–34 Read article
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In Vivo Hypoglycemic Activity of Aqueous Leaf and Root Extracts of Macaranga Barteri Müll. Arg. (Euphorbiaceae) In Swiss Albino Mice
Abstract: Background: Macaranga barteri Müll. Arg. is a perennial plant in the family Euphorbiaceae and is used in African traditional medicine for the management of several ailments, including diabetes. Although the leaves and stem bark have been studied for various pharmacological activities, little is known about the therapeutic value of the roots. Objective: This study evaluated the in vivo hypoglycemic activity of aqueous leaf and root extracts of M. barteri in …
Published in Research and Reviews : Journal of Veterinary Science and Technology · Vol. 15, Issue 2, 2026 · pp. 60–78 Read article
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Lossless and Reversible Data Hiding in Encrypted Images with Public Key Cryptography
Abstract: In this paper, system uses the cryptography and steganography concept, which proposes a lossless, reversible, and combined data hiding methods for images encrypted by public key cryptosystems with probabilistic and homomorphic properties. In the lossless method, pixels of encrypted images are replaced with new values to embed additional data into LSB-planes of ciphertext pixels by multiple layer wet paper coding. Thus, original data can be directly extracted from encrypted image, …
Published in Current Trends in Information Technology · Vol. 6, Issue 2, 2016 · pp. 27–33 Read article
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A Review on Artificial Intelligence Techniques for Analyzing Deforestation and Illegal Logging Using Satellite Imagery
Abstract: Deforestation and illegal logging remain critical environmental threats, driving biodiversity loss, climate change, and socio-economic disruption. Conventional monitoring techniques frequently do not yield real-time, large-scale insights. Recent developments in Artificial Intelligence (AI), especially in deep learning and computer vision, have revolutionized the ability to analyze high-resolution satellite images for detecting deforestation and monitoring illegal logging. This review synthesizes recent developments in AI-driven approaches, highlighting convolutional neural networks (CNNs), anomaly detection …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
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Mechanical Properties of Composites Made from Waste PET and Coconut Husk Fibres Using an Innovative Method
Abstract: The main purpose of this study was to develop a composite material based on two waste products, namely, polyethylene terephthalate (PET) bottles and coconut husk fibres using a simple innovative method to improve its mechanical properties. The fibres, after extraction, were treated with 5 wt% NaOH. They were then coated with a thin layer of polyester resin. The composite specimens were then manufactured in an industrial furnace. The shredded PET …
Published in Journal of Polymer & Composites · Vol. 11, Issue 3, 2023 · pp. 56–71 Read article
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Validation of geomorphological parameters of Bori Basin of Akkalkot Taluka, Solapur District by using GIS & Topographic Data
Abstract: The present research discusses the geomorphologic parameters of Bori basin that are determined byusing Geographic Information Systems (GIS) and Topographical Conventional System. The digitalelevation model (DEM) of the basin is downloaded from Aster-GDEM and this digital map is used inthe GIS software program to determine the geomorphologic parameters of the Bori basin. Thegeomorphological parameters are the area of basin, perimeter, river length, slope, etc. The extractedparameters are compared with the …
Published in Journal of Water Resource Engineering and Management · Vol. 8, Issue 1, 2021 · pp. 27–33 Read article
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Inhibition of Ehrlich Ascites Carcinoma by Crotalaria verrucosa L. Leaf in Swiss Albino Mice
Abstract: Objective: The objective of the present study was to evaluate the antitumor activity of Crotalaria verrucosa L. leaf against Ehrlich ascites carcinoma (EAC) in Swiss albino mice. Methods: The in vivo antitumour activity of the ethanol extract of leaf of C. verrucosa L. (ELCV) was evaluated at 50, 100 and 200 mg/kg bw against EAC, using mean survival time. After administration of the extract of C. verrucosa, viable EAC cell …
Published in Research and Reviews : A Journal of Ayurvedic Science, Yoga and Naturopathy · Vol. 5, Issue 2, 2018 · pp. 5–10 Read article
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Traffic Density Estimation Using Image Frames in Python
Abstract: Traffic congestion is a critical challenge in modern urban environments, leading to significant delays, environmental pollution, and increased accident rates. With the rapid growth of vehicle populations in metropolitan areas worldwide, the need for intelligent and automated traffic monitoring systems has become increasingly urgent. Traditional monitoring approaches, such as inductive loop detectors and manual surveillance, are limited in scalability, deployment cost, and adaptability to dynamic traffic scenarios. This paper presents …
Published in Trends in Transport Engineering and Applications · Vol. 13, Issue 2, 2026 · pp. 38–45 Read article
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Multiclass Content-based Visual Information Retrieval using Multi Layer Perceptron and Convolution Neural Network: A Comparative Study
Abstract: Content-based visual information extraction is an area, which utilizes the computer vision methods for searching and indexing the images in image library more competently than manual annotations. Due to the exponentially increase in image database volume, there is a demand of efficient retrieval system. Deep learning-based machine vision systems have the ability to handle large amount of data efficiently than ordinary machine vision systems. This paper proposed a content-based image …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 1, 2020 · pp. 1–9 Read article
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Multi-Layer Perceptron Neural Network Based Person Identification Using Appearance Based Facial Feature
Abstract: This paper deals with secure person identification system using Back-Propagation learning neural network algorithm where appearance based facial feature and Principal Component Analysis based dimensionality reduction technique have been used. To extract the appearance based facial features, Viola-Jones method has used as a face detector, Stam’s method of Active Shape Model has applied for detecting the facial edges and image pre-processing method has used for eliminating the background noises. For …
Published in Current Trends in Signal Processing · Vol. 4, Issue 1, 2014 · pp. 26–34 Read article
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Using the TCGA Database, Establishing and Validating an RNA-binding Protein-based on Prognostic Model for Liver Cancer
Abstract: Background: The third most common cause of cancer-related death is liver cancer, one of the most prevalent hematological malignancies in the world. The term RNA-binding protein (RBP) refers to a group of proteins that bind to RNA to control metabolic processes. The development of RNA-binding proteins is related to the mortality of liver cancer victims. Methods: RBP gene expression data from liver cancer were extracted using the TCGA database. The …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 9, Issue 2, 2022 · pp. 7–22 Read article
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Dimensionality Reduction using Eigenfaces and Fisherfaces for Face Recognition Applications using Kernel LMS Algorithm
Abstract: AbstractFace recognition is an intricate numerical technology in computer systems that can support recognition of human faces using methods such as principal component analysis (PCA), linear discriminant analysis (LDA), etc. by comparing the given facial uniqueness with the already available face database. PCA and LDA are classical feature extraction and data representation techniques used in face recognition algorithm involving unsupervised statistical methods. The 2-D facial image can be transformed into …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 2, 2015 · pp. 29–55 Read article
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Efficient Green Synthesis of TiO2 Nanoparticles Using Murraya koenigii Leaf Extract
Abstract: Green synthesis of nanoparticles by plant extract is at present under exploitation due to eco-friendly, non-toxic and inexpensive process. Titanium dioxide (TiO2) nanoparticles were synthesized by ultrasound assisted sol-gel precipitation method using titanium tetra-isopropoxide as a precursor and Murraya koenigii leaf extract as a reducing and stabilizing agent. The leaf extract was prepared under various solvent media such as ethanol and distilled water under controlled ultrasonication. Due to effective ultrasound, …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 6, Issue 1, 2016 · pp. 29–38 Read article
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Improvement of Yield of Bioactive Compounds and Antioxidant Activity of Moringa stenopetala Leaves by Optimizing Ultrasonic-assisted Extraction
Abstract: Ultrasonic-assisted extraction (UAE) parameters were optimized in this study using response surface methodology (RSM) to improve the total phenolic content (TPC), total flavonoid content (TFC), and antioxidant activity assessed using 1,1-diphenyl-2-picrylhydrazyl (DPPH) and 2,2’-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) assays of Moringa stenopetala leaves. According to the results, the optimal UAE parameters were extraction time (26 min), ethanol concentration (68%), and solvent-to-sample ratio (42 mL/g). Based on these optimal parameters, …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 7, Issue 3, 2018 · pp. 1–11 Read article
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Phytochemical, Acute Toxicity and Heavy Metals Evaluation of Khaya senegalensis (Desr.) A. Juss (Meliaceae) Stem Bark
Abstract: The present work was aimed to determine the phytochemical constituents, median lethal dose (LD50) and levels of heavy metals in Khaya senegalensis stem bark obtained from Kano State, Nigeria. The preliminary phytochemical screening revealed the presence of steroids, terpenoids, alkaloids, anthraquinones, saponins, phenolic compounds and carbohydrates, while the LD50 of the aqueous stem bark extract was above 5000 mg/kg body weight using OECD and Lorke’s method. The heavy metals analysis …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 7, Issue 1, 2020 · pp. 1–7 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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Online Content based Approach of Network Extraction for Finding Weight, Size and Features
Abstract: In an online community, moderating the content created by users is a great challenge. Nevertheless, this paper is very costly to man-made workers. To end this, an automatic machine can arouse great interest to identify breaches of user content. Some ways to solve this problem, but word filtering or regular expression matches are most often seen in practice. The key drawbacks are their insecurity and their context-insensitive existence deliberately concealed …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 7, Issue 1, 2020 · pp. 23–30 Read article
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Transformative Breakthroughs: Revolutionizing Potato Disease Detection Through Machine Learning
Abstract: Advancements in agricultural technology and the integration of artificial intelligence for diagnosing plant and leaf diseases are crucial for sustainable agricultural development. Conditions like early blight and late blight exert a notable influence on both the quality and quantity of potato harvests. Identifying these leaf diseases manually demands significant labor and a considerable level of expertise. Therefore, efficient, and automated methods for disease detection are essential to improve potato production. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 54–62 Read article