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446 articles for “FEA analysis”
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User Review-Driven Recommendation Model for E-Scooter Selection
Abstract: In the era of rising environmental awareness and the growing emphasis on sustainable mobility practices, electric scooters (e-scooters) have gained significant popularity as an efficient and eco-friendly alternative to conventional modes of transport. Their ability to reduce carbon emissions, minimize traffic congestion, and offer cost-effective commuting solutions has made them highly attractive, particularly in urban environments. However, with the rapid expansion of the e-scooter market, consumers are faced with an …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 6–16 Read article
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ASSESSING OF FOREST STRUCTURE USING EARTH OBSERVATION DATA: ACASE STUDY IN MUNESSA FOREST, OROMIA REGION, ETHIOPIA
Abstract: Forest structure is essential for estimating forest-related carbon emissions, analyzing forest degradation, and quantifying the effectiveness of forest restoration initiatives. However, forest structure quantification is only limited to the specific area of interest without considering the whole forest coverage. Remote sensing data can easily deliver a large area to assess forest structure. Therefore, this study aims to assess forest structure of Munessa Natural Forest by integrating satellite based light detection …
Published in International Journal of Land 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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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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A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression
Abstract: Early diagnosis of genetic diseases is crucial for effective treatment, especially in the case of Leukemia, a type of blood cancer characterized by abnormal proliferation of white blood cells. This paper presents a systematic review of recent computational techniques for the detection and classification of Leukemia using gene expression data obtained from DNA microarray analysis. The study explores diverse methodologies including machine learning (ML), deep learning (DL), and bio-inspired algorithms …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 2, 2025 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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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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Analysis of Security in Cloud Computing
Abstract: These days, cloud computing is expanding quickly in the IT sector, offering a fresh approach to managing various information systems. The rapid pace of technological advancement highlights the importance of embracing and leveraging its advantages. Organizations transitioning to cloud-based information archiving demonstrate several key characteristics. These include enhanced IT infrastructure, the ability to manage remote access from any location in the world with a stable Internet connection, and the cost …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 1, 2024 · pp. 35–40 Read article
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Fusion of deep learning autoencoders with random forest for wetland classification using Sentinel-2A data: A case study on Sirpur wetland
Abstract: Present study analyses the performance of deep leaning algorithm-autoencoder to reduce data dimension as compared to conventional models. Classification accuracies of Sirpur wetland using Sentinel 2A dataset with different inputs have also been studied. These inputs sets comprise the reconstructed data through compression of original 13 bands into 4 bands using decoder algorithm, first four Principal Components, all spectral bands, and spectral indices. Random Forest classifier (RF) is used to …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 · pp. 25–35 Read article
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Contextualising health-disaster risk reduction pillars for under-resourced rural secondary schools in Limpopo Province, South Africa
Abstract: School communities in under-resourced rural settings face a disproportionate burden of health-related disasters, including outbreaks, water and sanitation failures, food insecurity and compound events that disrupt learning and wellbeing. Yet school based disaster risk reduction (DRR) evidence in Southern Africa is uneven with limited empirically guidance tailored to the organisational and infrastructural realities of disadvantaged schools. Drawing on the Comprehensive School Safety Framework and the World Health Organization's Health Emergency …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 124–135 Read article
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Predicting and Prohibiting the Risk of Heart Failure Using Machine Learning
Abstract: It is challenging to estimate the likelihood of complex chronic disease while treating conditions like heart failure. The application of machine learning, an area of artificial intelligence, in cardiovascular care is growing quickly. In essence, it defines how computers classify and understand data, or choose a task with or without human intervention. The theoretical underpinnings of machine learning are models that accept input data (such as images or text) and …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 1, 2023 · pp. 15–20 Read article
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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Geothermal Energy in Nigeria: Assessing Its Potential and Environmental Impacts for Sustainable Development
Abstract: This study explores the possibility of using geothermal energy to address Nigeria's electricity generation issues sustainably. Significant potential for high-output power generation from geothermal resources is revealed by analyzing the geological features of the nation. Environmental issues including pollutant emissions and ecosystem damage are explored with the benefits of geothermal energy, such as its small land footprint and dependability. The purpose of the article is to identify possible geothermal energy …
Published in International Journal of Energy and Thermal Applications · Vol. 2, Issue 2, 2024 · pp. 01–07 Read article
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Import Substitute for Production of Ultrapure Water by Membrane Integrated Process for Medical and Biotechnological Applications
Abstract: The present invention discloses an inexpensive import substitute compact design of low-cost membrane process for the production of ultrapure water for dialysis and medical applications in different fields like pathological laboratories, biochemical analysis, sterilization and sanitation, dental and optical lens cleansers. The ultrapure water of demineralization (DM) process is related to the cascaded high- flux and high-selective membrane system for hyper permeation which is operated under the pressure of 3-7 …
Published in Research and Reviews : A Journal of Biotechnology Read article
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The Rise of Fractional Calculus: Novel Applications in Engineering and Biological Systems
Abstract: Fractional calculus (FC) is an advanced mathematical framework that generalizes the classical concepts of differentiation and integration to non-integer, or fractional, orders. This extension of traditional calculus allows for the modeling of complex dynamic systems that exhibit behavior not easily captured by integer-order differential equations. Over the last few decades, fractional calculus has seen a rapid rise in popularity, particularly in applied mathematics, engineering, and biological sciences, due to its …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 7–11 Read article
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A Fuzzy Integrated Web-based Quality Function Deployment Application:A Conceptual Analysis
Abstract: The 'voice of customers' drives the Quality Function Deployment (QFD) process, which is a customer-focusedproduct development method. Making decisions is a critical component of the QFD process. Although QFD aids decision-making, its subjectivity results in ambiguity and uncertainty, resulting in less accurate and consistent findings. Fuzzy ideas must be incorporated to deal with the ambiguity and uncertainty inherent in the QFD process. This will result in better decision-making. Businesses can …
Published in Journal of Web Engineering & Technology Read article
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Image Preprocessing and Analysis on Eye Fundus Images Segmentation by Using Density Clustering Methods
Abstract: In order to do an automated evaluation of various retinal illnesses such as Diabetic retinopathy, Glaucoma, and Macular Edema, fundus images must be pre-processed first. For many reasons, it's difficult to accurately detect the optic disc. Many blood vessels cross the optic disc, making it difficult to discern the disc's boundaries in fundus images. Lesion regions in diabetic retinopathy look very much like an optic disc's colour and texture, so …
Published in Recent Trends in Sensor Research & Technology Read article
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Exploring Lactic Acid Bacteria in Nasiriyah’s Locally Manufactured Cheese
Abstract: This investigation aimed to identify and diagnose lactic acid bacteria in locally produced cheese. Forty-eight isolates were obtained by categorizing them according to their phenotypic and microscopic features. After conducting biochemical tests, we acquired ten bacterial isolates from the Lactobacillus species. The VITEK 2 instrument was utilized to distinguish the samples to the species level with a threshold for the Lactobacillus genus. In the city of Nasiriyah, visiting the various …
Published in International Journal of Pathogens · Vol. 1, Issue 2, 2024 · pp. 15–23 Read article
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Rotational Speed Influence on Weld Temperature in Friction Stir Lap Joint of Aluminium Alloy 6061 Using Numerical Simulation
Abstract: The weld quality assessment in friction stir welding depends on the choice of suitable weld parameters. Rotational speed is one such parameter. The study utilizes a computational fluid dynamics model to examine the influence of various rotational on the workpiece and weld interface temperature. The workpiece selected for this study is an Aluminium Alloy 6061, while the tool employed is a truncated conical pin tool featuring a conical shoulder in …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 235–245 Read article
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Automated Guided Robotic Armed Vehicle (AGRAV)
Abstract: An automated guided vehicle (AGV) with a robotic arm mounted on top is the subject of this paper's prototype. "How to improve material handling in industries while reducing repetitive work and human involvement in pick and place applications" was the issue statement that was kept in mind. The fundamental issue in industries and warehouses where people work to choose and move goods is that their workdays are constrained by human …
Published in Journal of Control & Instrumentation · Vol. 15, Issue 3, 2024 · pp. 9–18 Read article