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459 articles for “Detection Algorithm”
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Identifying COVID-19 in chest X-ray and CT scan images through the application of machine learning algorithms.
Abstract: Since the beginning of the current COVID-19 pandemic, more than five million people have been infected and the numbers are still on the rise. Early symptom detection and proper hygienic standards are thus of utmost importance, especially in venues where people are in random or opportunistic contact with each other. To this end, automated systems with medical-grade body temperature measurement, hygienic compliance evaluation and individualized, person-to-person tracking, are essential, not …
Published in Research and Reviews : A Journal of Immunology · Vol. 13, Issue 2, 2023 · pp. 13–21 Read article
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Multisensor Data Fusion based Intelligent Temperature Measurement Technique
Abstract: Design and validation of a temperature measurement technique using fusion of temperature sensor like resistance temperature detector (RTD), and thermistor is proposed in this work. The objective of proposed work is to design a technique using fuzzy logic algorithms to fuse two different sensors having dissimilar characteristics. A fuzzy logic system is trained to produce an output for a temperature measurement system which is (a) more linear input-output characteristics as …
Published in Journal of Control & Instrumentation · Vol. 5, Issue 2, 2014 · pp. 1–13 Read article
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Detection of Phishing Website URLs and Email/SMS Using Random Forest and Multinomial Naive Bayes
Abstract: Currently, phishing attacks via SMS/email and URL have become significant threat to cybersecurity, posing risks to both individuals and organizations alike. Phishing attacks typically involve the creation of fraudulent websites or the dissemination of deceptive emails and SMS messages to trick users into disclosing sensitive information such as passwords, credit card numbers or personal details. To respond to these attacks, we develop a robust system for the detection of phishing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 22–30 Read article
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Early Disease Detection Using Artificial Intelligence
Abstract: Growth in artificial intelligence and machine learning now make it possible for the healthcare sector to be totally transformed by a new chapter, particularly in the era of medical image analysis. This study focuses on harnessing these advancements to develop a sophisticated model for early disease detection across diverse medical domains, majorly in skin disease. By integrating diverse datasets and leveraging advanced algorithms, our methodology aims to identify subtle disease …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 11–19 Read article
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Physically Challenged People Health Monitoring System Using Blynk Server
Abstract: Because of the fast pace of modern life, keeping an eye on persons who are physically challenged is a challenging task. Examining the medical histories of persons who are physically challenged who live in their homes is a challenging endeavor. In this paper, a proposal was made to maintain a continuous health monitoring system for intelligent people who are physically challenged. The system would use sensors to monitor the health …
Published in Trends in Opto-electro & Optical Communication · Vol. 12, Issue 3, 2022 · pp. 11–18 Read article
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Random Forrest Based Man-in-the-Middle Attack Detection in Advanced Metering Infrastructure
Abstract: Advanced metering infrastructure (AMI) plays a central role in the operation of modern smart grid (SG) systems by enabling continuous, two-way communication between utility providers and consumers. Through this communication, AMI supports real-time monitoring, dynamic pricing, and efficient energy management. However, the same connectivity that makes AMI effective also increases its exposure to cyber threats. One of the most critical threats is the man-in-the-middle (MITM) attack, in which an attacker …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 · pp. 1–8 Read article
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An Efficient Fault Detection and Localization System for Three-Phase Transmission Line using Arduino and Artificial Neural Networks
Abstract: This paper presents an efficient fault detection and localization system for a three-phase transmission line using Arduino and artificial neural networks. Theproposed system is designed to detect and localize faults in real-time, reducing the downtime and improving the reliability of the power system. The system consists of three main components: the fault detection unit, the fault classification unit, and the fault localization unit. The fault detection unit uses Arduino microcontroller …
Published in Recent Trends in Electronics Communication Systems · Vol. 9, Issue 3, 2022 · pp. 35–42 Read article
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Innovative Eyewear for the Visually Impaired
Abstract: Object detection systems are essential tools for identifying and locating objects within images or videos. When integrated into spectacles or wearable devices, these systems provide users with real-time information about objects present in their surroundings. This functionality serves diverse purposes, such as assisting visually impaired individuals in navigating their environment or offering augmented reality data to workers during tasks. Region-based Convolutional Neural Networks (RCNN) represent a prominent machine learning model …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 1, 2024 · pp. 27–34 Read article
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Vision Sense Rover
Abstract: This paper presents the design and implementation of an autonomous obstacle-avoiding robotic system utilizing an Arduino Uno microcontroller, an ultrasonic distance measurement module, a servo-based scanning mechanism, an L298N motor driver module, and an ESP32-CAM for real-time visual monitoring. The proposed system is developed to operate without human intervention, using sensor- driven decision making for navigation. The ultrasonic sensor continuously measures the distance to adjacent obstacles, while the servo motor …
Published in Journal of Microcontroller Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 38–43 Read article
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Wavelet Based Protection Scheme on Renewable Energy Integrated Multi Terminal Transmission System
Abstract: The power plants behavior is crucial under faulted conditions and their interaction with protection systems. The major microgrid protection problem is related to huge difference between the fault current in utilitygrid mode and microgrid mode. As conventional protection system doesn’t offer solution for all micro grid protection challenge, but it needs advanced protection strategy. Protection system must be response to both the utilitygrid and microgrid faults. Rapid response is necessary …
Published in Journal of Instrumentation Technology & Innovations · Vol. 8, Issue 3, 2018 · pp. 27–34 Read article
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Automatic Baby Cry Detector with sleep music player (ABCD)
Abstract: In today’s world, our lives have become moredependent on technology. One problem which caught our eyesis when parents have to leave their wards (aged between 3months to 2 years) alone due to some essential tasks for a shortduration, the baby goes unmonitored. Normally, parents dothis by leaving their child asleep. In many cases, the childwakes up and starts to cry. In absence of loved ones, babiesneed immediate calmness relief. A …
Published in Journal of Mechatronics and Automation · Vol. 10, Issue 1, 2023 · pp. 21–29 Read article
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Disease Prediction Using Machine Learning (ML)
Abstract: A technique called Machine Learning Disease Prediction uses symptoms reported by users or patients to forecast disease. The user-provided symptoms are entered into the system, and it outputs the disease probability. In disease forecasting, various popular supervised machine learning methods are known to be utilized. These algorithm estimates the likelihood of a disease occurrence. Precise analysis of medical information will support timely disease detection and management of patients based on …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 12, Issue 2, 2024 · pp. 40–48 Read article
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OCL Fault Injection-Based Detection & Prevention of LDAP Query Injection Vulnerabilities
Abstract: Security for web application is a prime concern today. Lightweight Directory Access Protocol (LDAP) is used in web applications for enforcing authentication. It may suffer from LDAP injection vulnerabilities and that leads to some security breaches such as login bypass and privilege escalation. This is because of poor implementation of LDAP applications. Here we propose a technique, OCL fault injection-based detection and prevention of LDAP injection vulnerabilities. Here the design …
Published in Journal Of Network security · Vol. 6, Issue 3, 2018 · pp. 5–8 Read article
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Comparative Analysis of Data Augmentation Techniques in CNN-based Classification of Atelectasis
Abstract: This research delves into the critical issue of atelectasis, its causes, and potential complications if left untreated. Leveraging deep learning algorithms, particularly convolutional neural networks (CNN), the paper explores their application in medical image analysis, focusing on the detection of atelectasis using the “chestX-ray8” database. The study compares various data augmentation techniques for improved accuracy, showcasing the importance of augmentation in enhancing model generalization. Through meticulous experimentation and evaluation, the …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 3, 2024 · pp. 1–8 Read article
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Progression of Health and Wellness: Artificial Intelligence (AI) and Deep Learning (DL) for Precision Medicines
Abstract: Deep learning and artificial intelligence in the field of precision medicine is revolutionizing healthcare to make personalized therapeutic approaches desirable based on the unique characteristics of the patient. AI technologies improve diagnostic accuracy by analyzing medical data, spotting patterns and anomalies that human experts may miss. AI-driven models are instrumental in precision medicine, where they can predict patient response to therapies to tailor treatment plans, enhancing outcomes and reducing adverse …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 2, 2025 · pp. 1–5 Read article
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Predictive Analytics and Adaptive Learning: A Machine Learning Framework for Reducing Learning Gaps
Abstract: Most contemporary digital learning environments encounter persistent challenges when it comes to accurately identifying students who are at-risk of academic underperformance. These challenges often arise due to limited visibility in learners’ engagement levels and gaps in conceptual understanding, particularly during the early stages of a course. To address this issue, the present study proposes an early prediction framework that leverages comprehensive student-related data through the application of machine learning techniques. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 16–21 Read article
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Real-Time Browser-Based Early Warning System for Cyberbullying Detection in Online Platforms
Abstract: The rise in social networking through internet-based communication tools, Instagram, and YouTube, to name a few, significantly increases the risk of cyberbullying, thereby increasing psychological trauma on users, especially children, through adverse emotional states like anxiety, depression, etc. For a long time, researchers have been enhancing detection tools to counter cyberbullying, but their ability to detect only after the fact, along with limited support for English-based architecture, is a major …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 09–15 Read article
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A Comprehensive Review on Brain Tumour Classification through Deep Learning Utilizing Convolutional Neural Networks
Abstract: Abstract- Convolutional neural networks (CNNs) constitute a widely used deep learning approach that has frequently been applied to the problem of brain tumor diagnosis. Such techniques still face some critical challenges in moving towards clinic application. Brain tumours are classified using a biopsy, which is not normally done before conclusive brain surgery. The enhancement of this technology by machine learning could aid radiologists in tumour detection without the use of …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 12, Issue 3, 2023 · pp. 24–29 Read article
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Fuzzy C-Means Clustering for Effective Segmentation and Classification of Brain Tumors in MRI Scans
Abstract: The paper discusses the importance of detecting and classifying brain tumors via MRI for effective treatment. It proposes a framework utilizing the Fuzzy C-means clustering algorithm for segmentation, demonstrating improved performance through real dataset validation. The model is trained on a large, annotated MRI dataset to identify and classify different tumor types, enabling machine learning-based classification into benign and malignant tumors. The MATLAB-based solution automates brain tumor feature extraction, aiding …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 23–28 Read article
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Development of a Low-Cost Autonomous Robot for Obstacle Avoidance Using Ultrasonic Sensing
Abstract: In the evolving landscape of automation, autonomous mobile robots are becoming critical for performing tasks with minimal human intervention. This project presents the design and development of a cost-effective, small-scale obstacle-avoiding robot using an Arduino microcontroller and an ultrasonic sensor. The robot operates by scanning its surroundings, identifying nearby obstacles, and navigating by altering its path in real time. Through intelligent programming and sensor integration, the system achieves smooth, collision-free …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 1, 2026 · pp. 1–11 Read article