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84 articles for “error detection”
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Versatile CNC Machine for Tabletop Use Enhanced with Machine Learning Integration
Abstract: In the realm of tabletop multipurpose CNC machines, the integration of machine learning represents a groundbreaking advancement potentially revolutionary in the field of desktop manufacturing. This research explores the seamless incorporation of machine learning algorithms into tabletop CNC machines to enhance their capabilities, performance, and user experience. Through case studies and examples, we demonstrate the profound impact of machine learning integration in key areas of CNC machining, such as accurate …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 353–361 Read article
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Leveraging Generative AI for Test Case Creation in Complex Systems
Abstract: Modern software systems exhibit increasing complexity, demanding sophisticated testing methodologies to ensure reliability and functionality. Traditional manual testing approaches often struggle to keep pace with this complexity, leading to inadequate test coverage and increased risk of unforeseen issues. This study explores the potential of Generative AI (GAI) in revolutionizing test case creation for complex systems. We delve into the practical application of GAI techniques, such as Variational Autoencoders (VAEs) and …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 16–22 Read article
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Quasar: Quantum-Accelerated Sustainable Anomaly Recognition in Climate Systems
Abstract: Accurate detection of climate anomalies is vital for disaster alleviation and policy making in a sustainable manner, but customary detection methods face the challenges of computational inefficiency and physical inconsistency. In this study, we propose a novel approach called Quantum-Optimized Fuzzy Physics-Informed Neural Networks (QFuzzy-PINNs), which integrates quantum computing, fuzzy logic, and physics-informed deep learning. As a first step, we employ quantum annealing for conventional optimization to adjust multiple Gaussian …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 18–27 Read article
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Improving Dataset Integrity Through Automated Data Cleaning Techniques
Abstract: High-quality data is a fundamental requirement in data science for producing trustworthy analytical insights and effective machine learning models. Problems, including incomplete records, inconsistent entries, duplicate observations, and anomalous values, can severely reduce the accuracy and robustness of predictive systems. As modern datasets continue to expand in both volume and structural complexity, relying on manual data cleaning methods become time-consuming and error-prone, highlighting the growing importance of automated data preprocessing …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 40–45 Read article
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Path Lab-AI: An Autonomous Framework for Error-Free Histopathology Slide Interpretation
Abstract: Path Lab-AI represents a fully autonomous platform for the analysis of histopathology slides with circumscribed structures, designed to obtain highly accurate results using diagnostic methods and avoiding the usual limitations of standard microscopy-based pathology. Leveraging recent deep learning and whole slide image (WSI) analysis innovations, our system takes advantage of automated WSI ingestion along with pre-processing steps to account for staining variability, remove artifacts, and localize tissue from background. Such …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 19–30 Read article
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Efficient Fault Detection in Power Transmission: A Review of Three-Phase Line Fault Detection with Hybrid Energy using MATLAB
Abstract: In urban regions, the density of power demand has significantly increased recently. Large-scale subterranean power cable installations are beginning to take the place of overhead transmission lines everywhere in the world because of environmental concerns in highly populated areas. The present project's primary objective is to use MATLAB to create a simulation model that includes 3ph symmetrical and unsymmetrical defects. Some have proven to be effective in detecting errors while …
Published in International Journal of Electrical Power and Machine Systems · Vol. 1, Issue 1, 2023 · pp. 42–47 Read article
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An Analysis of Multimodal Fusion in Deepfake Detection for Video Samples
Abstract: In today’s rapidly evolving digital landscape, deepfake technology stands as both a marvel and a threat to privacy and security. Deepfakes, hyper-realistic synthetic media created using artificial intelligence (AI), can deceive and manipulate on an unprecedented scale, from political propaganda to compromising videos of public figures. This research navigates deepfake detection, focusing on two advanced methodologies: the vision transformers (ViT) image classifier and the Meso4 method. The ViT model utilizes …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 19–27 Read article
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Facial Recognition System Utilizing Real-time Deep Learning Techniques
Abstract: This research introduces an openly accessible deep learning-based framework designed for facial recognition. The system encompasses five key stages: face segmentation, detection of facial features, face alignment, embedding, and classification. Deep learning methods are employed for the extraction of fiducial points and embedding within the system. For the classification task, a Support Vector Machine (SVM) is utilized due to its efficiency in both training and inference phases. Notably, the system …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 14–20 Read article
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Reconfigurable AES Based AEAD For Multi-Mode Operation with Lightweight Compatibility
Abstract: The proposal is for a lightweight, multi-mode, reconfigurable authenticated encryption system with associated data (AEADs) based on AES. It is challenging to effectively integrate different AEADs in hardware because each one has its own mode of operation and/or subfunctions, even though some major AEADs share several basic components (such as the XOR-Encryption-XOR (XEX) scheme, block chaining, and advanced encryption standard (AES). This paper proposes hardware that effectively combines the basic …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 1, 2025 · pp. 54–68 Read article
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A Comprehensive Review of CAN Bus And IEEE 802.11b Networks: Evolution, Performance, and Wireless Extensions
Abstract: The Controller Area Network (CAN) bus has been a cornerstone in vehicular communication, facilitating robust and efficient data exchange among electronic control units (ECUs). This paper provides a comprehensive review of the classical CAN bus, CAN FD, and their key attributes, including message prioritization, arbitration mechanisms, and error detection. Additionally, the paper explores the IEEE 802.11b wireless standard, emphasizing its potential for extending CAN-based networks into wireless domains. The study …
Published in Journal Of Network security · Vol. 13, Issue 2, 2025 · pp. 26–39 Read article
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Study of Algebraic Structures in Discrete Mathematics and Its Applications
Abstract: Algebraic structures such as groups, rings, fields, semi groups, and lattices form the foundational framework of discrete mathematics. These structures are defined by specific sets and operations that follow algebraic laws, enabling a systematic approach to problem-solving in various domains. This paper explores the theoretical principles of these algebraic systems and highlights their vital role in computer science, cryptography, automata theory, coding theory, and software engineering. By examining their properties …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 1, 2025 · pp. 35–40 Read article
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Nitro IDE: Exploring Integrated Development Environments: Current Trends and Innovations
Abstract: Integrated Development Environments (IDEs) have become essential in modern software development, offering a centralized platform that brings together source code management, debugging tools, version control, and compilation features. This study offers an in-depth analysis of various IDE platforms, with a particular focus on Eclipse as a widely used open-source integration environment. It also explores specialized IDEs tailored for embedded systems and enterprise-level Java (J2EE) application development. Additionally, the study examines …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 35–40 Read article
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Recent Trends and Techniques in the Advanced Microcontroller Bus Architecture (AMBA) Protocol: A Comprehensive Review
Abstract: ARM has created the Advanced Microcontroller Bus Architecture (AMBA) that is used as the main method for communication on chips in today’s embedded systems. Since AMBA is built to scale and combine with other components, it allows data transfer to high-performance and low-power components easily. The paper discusses how AMBA protocols have evolved and presents new trends of producing higher data rates, conserving energy, and lowering latency. This study offers …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 3, 2025 · pp. 9–15 Read article
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Alzheimer’s Disease Classification Based on Transfer Learning of New-CNN Model
Abstract: The long-term, irreversible brain disorder “Alzheimer’s disease (AD)” currently has no known cure. Nonetheless, current medications may impede their advancement. Globally, those over 65 are the primary population affected by Alzheimer’s disease. Accurate detection of this condition requires early diagnosis. Because there are so many people who come with an ailment, manual diagnosis by health specialists is laborious and prone to error. Early detection of AD is a difficult undertaking …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 · pp. 16–23 Read article
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Advanced Deep Learning Techniques for Sickle Cell Anaemia Detection
Abstract: Sickle Cell Anemia (SCA) is a prevalent genetic blood disorder characterized by the presence of abnormal hemoglobin, resulting in the distinctive sickle shape of red blood cells. Timely and accurate identification of Sickle Cell Anemia (SCA) is essential for effective management and treatment. This study presents a new method that utilizes Convolutional Neural Networks (CNNs), a deep learning model particularly effective for image analysis. The process involves using microscopic images …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 3, 2024 · pp. 9–15 Read article
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Skin Disease prediction and classification from dermoscopy images using Neural Network
Abstract: Skin diseases are among the most common health-related problems affecting people of all age groups, and their occurrence often varies with seasonal and environmental conditions. Delayed or incorrect diagnosis of skin disorders can lead to severe complications, making early and accurate detection extremely important for effective treatment and prevention. In recent years, rapid advancements in deep learning and neural network technologies have significantly contributed to the development of automated medical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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Design of a Verilog HDL-Based Advanced Intelligent Automatic Railway Gate Control System
Abstract: Human mistake, sluggish reaction times, and manual gate operation are common causes of railway level crossing accidents. This project suggests an Intelligent Automatic Railway Gate Controller made with Verilog HDL and simulated in Xilinx Vivado to lessen these mishaps. With the goal of improving safety at unmanned railway crossings, the system is intended to offer a dependable and entirely automated solution. Without human interaction, the railway gate is automatically controlled …
Published in International Journal of Electronics Automation · Vol. 4, Issue 1, 2026 Read article
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Enhancing LAN Security Using Machine Learning
Abstract: The modern Local Area Network (LAN) is a critical component of any organization's infrastructure, facilitating communication, resource sharing, and access to the wider internet. However, this connectivity also brings inherent security risks. Traditional security measures, relying on signature-based detection and rule-based systems, are increasingly struggling to keep pace with the evolving sophistication of cyberattacks. This is where Machine Learning (ML) offers a powerful alternative, enabling proactive threat detection and enhanced …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 07–16 Read article
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An Adaptive Approach for Real-Time Embedded System Design, Analysis and Optimization
Abstract: Real-time embedded systems are critical components in various domains, such as automotive, aerospace, healthcare, and industrial automation. The design, analysis, and optimization of these systems are vital to ensure their reliable and efficient operation. In this paper, we propose an adaptive approach for real-time embedded systems that aims to address the challenges faced during the development process while maintaining high-quality results. Our approach leverages adaptive techniques to dynamically adjust the …
Published in International Journal of Solid State Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 8–14 Read article
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Animal/Object Recognition and Monitoring
Abstract: This study focuses on teaching a computer to identify leopards in images through a process called Object Detection and Image Recognition. We created a special set of pictures (dataset) containing thousands of leopard images. Using a small camera module called ESP32 CAM, we trained the computer to recognize leopards by comparing the images it captures with the ones in the dataset. The results were obtained using a Convolutional Neural Network …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 1, 2024 · pp. 1–6 Read article