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84 articles for “error detection”
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Advancing EEG Technology for Affordable and Effective Epilepsy Detection
Abstract: For a proper diagnosis and prompt treatment, epilepsy, a neurological condition marked by recurring seizures, needs to be continuously monitored. Manual interpretation is frequently used in traditional approaches for identifying epileptic seizures from electroencephalogram (EEG) signals, which can be laborious and error-prone. In this research, a novel method for automatically detecting epilepsy from EEG data using deep learning algorithms is presented. According to centers for disease control and prevention (CDC) …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 11–18 Read article
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A Survey on Ensemble Technique for Enhanced Cyberattack Detection
Abstract: It is now more difficult than ever to safeguard enterprises against cyberattacks due to their fast growth and growing sophistication. Stronger cyberattack detection systems are becoming more and more necessary as hostile strategies continue to evolve in order to safeguard information, preserve corporate trust, and protect sensitive data. An overview of contemporary detection techniques is given in this study, with a focus on integrating machine learning (ML) to increase efficacy. …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 50–54 Read article
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Early Detection of Alzheimer’s Disease Using Machine Learning Techniques
Abstract: Alzheimer's Disease (AD) is a progressive neurodegenerative condition impacting a large global population. Detecting AD early is critical for timely intervention and effective management. Conventional diagnostic approaches involve cognitive assessments and neuroimaging, which are often lengthy, costly, and prone to human error. In this paper, we propose a novel approach for early detection of AD using machine learning techniques applied to multimodal data, including neuroimaging, cognitive assessments, and biomarkers. Our …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 32–43 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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Advancements in AI-Driven Diagnostics for Dental Health: A Comprehensive Review
Abstract: Dental diseases, also known as oral diseases or dental conditions, encompass a range of health problems affecting the teeth, gums, mouth, and associated structures. These conditions can lead to pain, discomfort, and severe complications if left untreated. Early detection and accurate diagnosis are crucial for effective treatment and prevention of further complications. This comprehensive literature review aims to identify common dental problems such as Tooth Decay (Cavities), Gingivitis, Periodontitis, and …
Published in Current Trends in Signal Processing · Vol. 14, Issue 2, 2024 · pp. 1–7 Read article
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Detectiverse: Advancing Supply Chain Efficiency with AI-Enhanced Screw Counting
Abstract: Accurate screw counting is essential in the manufacturing sector to ensure efficient inventory management and maintain quality control standards. The current manual counting method is prone to errors and lacks the ability to identify the source of missing screws. To address this challenge, we propose implementing an automated screw counting system at Indo Metal Tech in Ambattur, Chennai. This system would utilize advanced image processing and machine learning algorithms to …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 21–26 Read article
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Non-contact Real Time Digital Distance Measurement System for Vehicle Applications
Abstract: An Arduino-powered Digital Distance Measurement System with LCD Display a compact and precise solution presents a practical and portable digital distance measurement system utilizing the versatility of Arduino microcontrollers and the accuracy of ultrasonic sensors. This system can be utilised for airplane docking system which measures the distance exactly. Leveraging Arduino’s programming capabilities and readily available libraries, the system transmits ultrasonic pulses and analyses the reflected echoes to calculate real-time …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 670–678 Read article
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An Automated Smart Contract Repair Framework for Reentrancy, Integer Overflow, and Denial- of-Service Vulnerabilities
Abstract: This paper introduces a novel static analysis framework designed to bridge a long-standing gap in Ethereum smart contract security: the disconnect between vulnerability detection and automated remediation. Although widely adopted tools such as Slither and Oyente are highly effective at identifying security weaknesses, they stop short of providing actionable fixes. As a result, developers manually patch vulnerabilities, a process that is not only time-consuming but also susceptible to human error …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 31–41 Read article
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Artificial Intelligence in Pharmacovigilance: Improving Drug Safety
Abstract: Artificial intelligence (AI) is revolutionizing pharmacovigilance (PV) by enhancing the detection, assessment, and prevention of adverse drug reactions (ADRs). This review examines how AI technologies – such as machine learning (ML), natural language processing (NLP), and big data analytics – tackle existing challenges in pharmacovigilance (PV), including issues like underreporting, large data volumes, and inefficiencies in data processing. AI improves drug safety by automating data collection, enabling real-time adverse event …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 1–16 Read article
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DFT Compatible Low Power EDAC Based on Clock Gating
Abstract: The in-situ EDAC architecture is normally hired in timing-error tolerant circuits in a try and decrease the conservative timing protect band due to procedure, voltage, and temperature (PVT) fluctuations. But with the addition of the latch-based totally data channel, extra detection, and propagation common sense, it makes the implementation of the layout for- testability (DFT) tough. We present a new low area test overhead DFT EDAC architecture with extreme reduction …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 1, 2025 · pp. 41–53 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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A Review of Automated Pomegranate Disease Detection and Classification Using Machine Learning
Abstract: The abstract outlines a research study focused on developing an automated system for detecting and classifying diseases that affect pomegranate fruits. Pomegranates, like many other crops, are vulnerable to several types of diseases that appear as visible colored spots on the fruit’s surface. These visible symptoms, such as lesions or discoloration, can significantly impact the fruit’s quality, market value, and yield. Therefore, timely and accurate identification of such diseases is …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 01–13 Read article
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Optimized Receivers for Underwater Visible Light Communication
Abstract: For uses like ocean exploration, environmental monitoring, and underwater data transfer, wireless communication under water is crucial. Conventional acoustic and radio frequency communication methods suffer from low bandwidth, high latency, and severe signal attenuation in underwater environments. With its high data rate and low propagation delay, Visible Light Communication (VLC) provides a promising alternative. In this work, an underwater VLC system is implemented using Light Emitting Diodes (LEDs) with intensity …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 1, 2026 · pp. 22–33 Read article
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Intelligent Brain Tumor Diagnosis with AI-Based Classification* * Harnessing Deep and Machine Learning for Tumor Identification
Abstract: Brain tumors have become a leading cause of cancer- related deaths, posing significant health risks to many patients. This urgent medical challenge calls for rapid, automated, and reliable techniques to detect brain tumors accurately. Timely and precise tumor identification is crucial for devising effective medical plans that have the potential to save lives and improve patient outcomes. By leveraging advanced image processing methods, healthcare professionals can enhance their diagnostic capabilities …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 1, 2026 Read article
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Noise-Resilient QPSK Modem for Reliable Communication for Green Communication
Abstract: The channel noise is the severely degraded the performance of communication system and that also limits the maximum data transmission rate. Hence, it is required to design a demodulator in a receiver which overcomes the effect of noise in the received signal, reconstructs un-corrupted information signal and improves data rate. In QPSK, noise effect the phase of the modulated signal and that causes error in the information signal. This study …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 1, 2025 · pp. 36–46 Read article
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Automated Shopping Trolley with Billing System
Abstract: The Smart Trolley Billing System is a modern solution created to simplify and speed up shopping by automating the billing process, reducing manual effort and saving time for customers. It enhances the overall shopping experience by streamlining checkout and improving efficiency in retail environments through smart technology integration. This system utilizes RFID technology, Arduino microcontrollers, an LCD display, and a push-button mechanism to manage the trolley’s movement. These components work …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 11–17 Read article
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An Investigative Study on Secure Coding Practices with Shell Scripting
Abstract: This investigative research delves into secure coding practices within shell scripting, aiming to reduce prevalent security vulnerabilities and improve the overall security stance of shell scripts. It emphasizes three key areas: static analysis, dynamic analysis, and manual code review. Through static analysis, the code structure, usage of unsafe functions, and potential vulnerabilities are examined without executing the script. Dynamic analysis entails running the script in controlled settings to detect runtime …
Published in Journal of Advances in Shell Programming · Vol. 11, Issue 1, 2024 · pp. 16–23 Read article
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SmartTrack : Advanced Attendence System using LR RFID
Abstract: This project presents the design and implementation of a long-range RFID attendance system aimed at transforming how educational institutions track attendance by making the process faster, more accurate, and completely contactless. Tradi- tional methods, whether manual roll calls or short-range RFID scanners, often interrupt class routines and leave room for errors or proxy attendance. To address these issues, the proposed system integrates long-range RFID readers, beam sensors, and ESP32 microcontrollers …
Published in Journal of Semiconductor Devices and Circuits · Vol. 13, Issue 1, 2026 Read article
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Bias Detection and Accuracy Enhancement in Voice-based Banking Authentication Using Deep Learning
Abstract: Biometric systems have become an integral part of how many people access banking services today, and voice verification systems can be a secure and easy-to-use source of banking authentication that does not require any physical contact with the bank or any other person. From the security perspective, these systems would normally provide an effective means of identifying an individual but frequently exhibit bias with respect to demographics such as the …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article
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A Comparative Study of Transfer Learning-Based Deep Learning Models for Breast Cancer Detection
Abstract: Breast cancer is a major concern in the world today, and early and accurate diagnosis is most crucial in the case of breast cancer, as it is among the disorders where the total cost of loss of life is high. Traditional screening processes are subjective and vulnerable to inter-observer reliability issues and diagnostic errors, being primarily based on manual interpretation of medical images. To address these limitations, Deep Learning (DL) …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–34 Read article