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1987 articles for “Lap Splice Detection” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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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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DVT in Athletes: A Physiotherapist’s Approach to Prevention, Early Detection, and Rehabilitation
Abstract: Deep vein thrombosis (DVT) is a serious medical condition where blood clots develop in the deep veins, most often in the lower limbs. While it is traditionally associated with immobility, athletes are also at risk due to factors like prolonged travel, injuries, dehydration, and genetic predispositions. This paper explores the role of physiotherapists in preventing, detecting, and rehabilitating DVT in athletes. Preventive strategies include promoting hydration, active recovery, circulatory exercises, …
Published in Research and Reviews : Journal of Surgery · Vol. 14, Issue 1, 2025 · pp. 11–16 Read article
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Milk Allergy: Significance, Detection and Management
Abstract: Milk allergy is a significant public health issue, particularly among infants and young children, with prevalence rates between 2 and 6% in early childhood, declining to 0.1–0.5% in adulthood. It is an immune-mediated adverse reaction to milk proteins, primarily involving immunoglobulin E (IgE)-mediated responses. Symptoms range from gastrointestinal distress and respiratory complications to severe anaphylaxis. The etiology of milk allergy involves genetic predisposition, environmental factors, an immature immune system, and …
Published in Research and Reviews : Journal of Dairy Science and Technology · Vol. 14, Issue 1, 2025 · pp. 15–19 Read article
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Revolutionizing oncology - role of artificial intelligence in early cancer detection and diagnostic advances-A comprehensive review
Abstract: Oncology has experienced a remarkable transformation with the adoption of artificial intelligence (AI), which has greatly enhanced cancer detection and diagnosis. As one of the leading causes of death worldwide, cancer highlights the importance of early detection in improving patient outcomes and survival rates. AI’s ability to analyze vast and complex datasets has enabled groundbreaking innovations in imaging, pathology, biomarker discovery, and predictive analytics. This review highlights key AI-driven advancements …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 1, 2025 · pp. 18–22 Read article
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Finite Element Analysis of Multiwall Carbon Nanotubes Enabled Single Lap Joint
Abstract: This study uses finite element analysis (FEA) to examine the strength of adhesively bonded single lap joints with and without Multiwall Carbon Nanotubes (MWCNT) added to the adhesive. Shear strength analysis is performed by applying a tensile load that generates shear stress at the overlap between the two substrates bonded with adhesive. Aluminum (Al-Al) substrates were used, and single-lap joints were prepared following ASTM standards. Specimens with identical overlap and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 195–203 Read article
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Street Light Automation and Fault Detection
Abstract: This paper addresses the concept, design, and implementation of an automated streetlighting system that uses Arduino technology for improving energy saving and detecting faults across the lamp. The system consists of several sensors: Light Dependent Resistors (LDR) as well as Infrared (IR) sensors, which are employed in the management to control the lighting of the streets and posts with surroundings and other conditions. Here, we use IR sensors for measuring …
Published in International Journal of Electronics Automation · Vol. 3, Issue 1, 2025 · pp. 12–20 Read article
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Fault Detection in Solar PV Systems Integrated with the Power Grid: Evaluating Logistic Regression through Confusion Matrix Analysis
Abstract: This paper proposes a method for failure detection in grid-integrated solar photovoltaic (PV) systems using logistic regression and real-time sensor data. The approach effectively classifies and identifies seven distinct fault types. The developed model demonstrates a high fault identification accuracy, ranging from 93% to 96.5% across various fault types and operational conditions. By leveraging logistic regression, the system utilizes key independent variables that significantly influence the classification process. Additionally, the …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 2, 2025 · pp. 45–52 Read article
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Leak Location Detection in Underground Pipeline Using Transient Pollutant Propagation Concentration Signature Analysis with Theory of Hypernumbers
Abstract: The paper introduces a new analytical method of detecting leakage locations in underground pipe systems. For the first time, the phenomenon of pollutant backflush through leaks in liquid transport systems is used for algorithmic leak location identification. The paper compares the proposed concept with known monitoring methods. The theoretical analysis of the method's capability to increase leak localization distance and detect the location of tiny holes in pipelines is provided. …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 13–22 Read article
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Smart Agriculture in India: Advancements in Image Processing for Automated Plant Disease Detection and Crop Analysis
Abstract: The adoption of image processing technologies in agriculture is emerging as a revolutionary method for tackling persistent challenges in the farming industry. These techniques are increasingly used for different tasks such as detecting plant diseases, assessing crop health, and predicting yields, especially in the framework of smart agriculture systems. This study paints a detailed picture of the latest progress in image processing techniques applied to automated disease detection and detailed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 13–19 Read article
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Real Time Alcohol Detection with Accident Prevention System Using Arduino
Abstract: The aim of our research work is to present a project designed to make human driving safer and to significantly reduce road accidents caused by drunk driving. This project integrates an MQ3 alcohol sensor with an Arduino-based system using the ATmega328 processor, which offers enhanced functionality compared to conventional microcontrollers. The MQ3 sensor is capable of detecting alcohol content in a person’s breath and has a sensitivity range of approximately …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 · pp. 19–26 Read article
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Multimodal Disease Detection Using Deep Learning
Abstract: Artificial Intelligence (AI) is playing an increasingly pivotal role in modern healthcare, particularly in improving the speed and accuracy of disease detection. With the evolution of Machine Learning (ML), Deep Learning (DL), and high-performance computing, AI-based solutions are now capable of processing extensive medical datasets, ranging from patient records to diagnostic images, with remarkable efficiency. These systems offer immense potential for early intervention, improved clinical decision-making, and alleviating pressure on …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 129–139 Read article
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Brain Tumor Detection by Aggregating Deep Learning and GAN Models for Faster MRI image Synthesis
Abstract: Brain tumors comprise a global health challenge that, in order to be treated and organized, need early and accurate diagnosis. Usually conducted through medical imaging, brain tumor detection techniques have problems of accuracy, efficiency, and confidentiality. Issues of limited datasets, strict privacy laws that provide restrictions on data sharing, and the necessity for specialized expertise on medical image analysis relegates modern methodologies to vulgar charades. For patient prognosis, treatment planning, …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 45–53 Read article
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A Comparative Study of Deep Learning Methods for Depression Detection in Social Media Data
Abstract: With the rise of social media platforms like Twitter, Reddit, and Facebook, individuals increasingly share personal information about their moods, behaviors, and mental states. This trend provides a unique opportunity to leverage large-scale textual data for understanding and monitoring mental health conditions, particularly depression, a prevalent and challenging mental health issue. Traditional depression assessments are often confined to clinical environments and lack the capacity for real-time monitoring. In contrast, social …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 55–65 Read article
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Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 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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Sensor and AI based Pre-Detection Systems Transfiguring Intoxication & Smoking
Abstract: The ubiquitous problems of drunkenness and uncontrolled smoking continue to pose substantial hazards to public health, safety, and productivity in a world that is becoming more linked and protective of its personal safety. The costs to society and the economy are substantial, and they range from automobile accidents caused by impaired driving to accidents that occur in the workplace, and from chronic health disorders that are connected to smoking to …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 3, 2025 · pp. 37–50 Read article
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ML-Driven Defect Detection in Additive Manufacturing of Polymer Composites Using Thermal Imaging
Abstract: Polymer-based flexible biosensors have emerged as a pivotal technology in continuous health monitoring, yet their deployment in real-world settings is often hindered by undetected micro-defects and signal distortion caused during fabrication or usage. Existing diagnostic frameworks typically rely on post-hoc processing or bulky instrumentation, failing to offer scalable, real-time detection during additive manufacturing workflows. This study introduces an end-to-end, thermographic imaging-integrated framework for in-situ defect identification during the additive manufacturing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 201–215 Read article
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Improving The Accuracy of Medical Diagonosis Detection Using Machine Learning
Abstract: While accurate and timely medical diagnosis is a fundamental aspect of effective health care delivery, traditional methods have not been able to overcome major hurdles such as inefficiencies in data analysis with Gi Human Error as well as limitations in scalability. The “Improved Accuracy of Medical Diagnosis Detection Using Machine Learning” project seamlessly integrates advanced machine learning (M L) technologies with efficient preprocessing and feature selection techniques to outperform all …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 1–8 Read article
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Breast Cancer Detection Using Machine Learning: A Comparative Analysis of Supervised Learning Algorithms
Abstract: Globally, breast cancer remains a predominant cause of mortality among women, highlighting the urgent need for timely and precise diagnostic approaches. This research explores the application of machine learning algorithms—including Logistic Regression, SVM, Naïve Bayes, KNN, and Random Forest—on the Wisconsin Breast Cancer Dataset for effective tumor classification. Key pre-processing steps such as missing value handling, feature scaling, and dimensionality reduction were employed to improve model performance. The study evaluated …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 46–52 Read article
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Enhancing IoT Network Security with Hybrid Deep Learning Classifiers for DDoS Attack Detection
Abstract: The security and operational dependability of Internet of Things (IoT) networks are seriously threatened by the growing susceptibility to Distributed Denial of Service (DDoS) assaults brought about by their rapid expansion. The intricacy and dynamic character of these advanced attacks can provide a challenge to conventional intrusion detection systems. This study presents a novel method for strengthening IoT network security by combining Convolutional Neural Networks (CNNs) and Long Short-Term Memory …
Published in Journal of Web Engineering & Technology · Vol. 13, Issue 1, 2026 · pp. 23–33 Read article