Search Results - "IEEE Access"

Bearing faults are a critical concern in electrical machines, particularly permanent magnet synchronous motors (PMSMs), commonly used in electric vehicles. Early and accurate classification of bearing fault severity is essential for predictive maintenance, as it enhances cost-effectiveness, ensures...

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This paper investigates the joint spectrum and energy efficiency in multimanned aerial vehicle (Multi-UAV) communication network in environments beyond the fifth generation and sixth generation (B5G / 6G), with a focus on the challenges posed by redundant data. We propose a linear optimization model...

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Uncertainty analysis of classification or regression models is a key feature of probabilistic approaches to supervised learning, allowing the assessment of how trustworthy predictions are. Just as boosting algorithms aim at obtaining accurate ensembles of simple classifiers, using a process guided b...

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This paper introduces novel nonparametric supervised learning techniques for classifying massive datasets, addressing key limitations of existing methods in Big and Streaming Data framework. We propose an offline kernel-based classifier enhanced by Batch Principal Component Analysis (PCA) for dimens...

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Routing plays a pivotal role in the design of printed circuit boards (PCBs). Existing automated routers typically tackle the routing problem by dividing it into two separate phases: escape routing and area routing. However, this approach often leads to suboptimal solutions or even the absence of sol...

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The scattered light is common in biomedical images. However, its removal is a challenging task. The challenge comes from two aspects. First, the scattered-light-free ground truth biomedical images are difficult to obtain or even unavailable. This is fundamentally different from the case in natural i...

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Brain-inspired computing is a key technology to break through the von Neumann bottleneck, and memristors have become potential candidate devices for achieving brain-inspired computing. The precise tuning of the conductance of a memristor device in the memristor array determines the accuracy of its p...

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This paper presents the design and development of a metamaterial-enhanced pentagonal patch antenna integrated with a monopulse comparator operating at 2.4 GHz for S-band radar tracking and UAV applications. The metamaterial structure is specifically designed to reduce cross-polarization and enhance...

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In modern power systems, insulators, as key components of transmission lines, are crucial for defect detection for the safe operation of power grids. Aiming at the problems of low efficiency of traditional manual detection, the vulnerability of traditional image processing methods to environmental i...

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Telecare medical information systems (TMIS) integrate telecommunication and information technology with Internet of Things (IoT) devices, such as wearable sensors, to enable the remote delivery of healthcare services by seamlessly collecting and transmitting health data to the system. However, the i...

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Face detection in complex environments remains challenging due to trade-offs between accuracy and computational efficiency, particularly for edge devices with limited resources. GhostNet-MTCNN is proposed. In this approach, the computationally intensive standard convolution layers in the Multi-task...

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This study focuses on the anomaly detection problem in Network Security Situational Awareness (NSSA). We systematically review traditional approaches and recent advancements based on Machine Learning (ML) and Deep Learning (DL), and assess the application status of various anomaly detection models w...

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With the rapid development of artificial intelligence (AI) technologies, AI-generated content (AIGC) on social media platforms has significantly increased. This study collected text data related to AIGC from mainstream social media platforms and employed the Latent Dirichlet Allocation (LDA) topic m...

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Software logs generated by sophisticated network emulators in the telecommunications industry, such as VIAVI TM500, are extremely complex, often comprising tens of thousands of text lines with minimal resemblance to natural language. Only specialised expert engineers can decipher such logs and troub...

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Historically, electrocardiogram (ECG) datasets have been created based on physicians’ interpretation of the ECG, which may introduce human biases and errors. Nightingale Open Science provides an open-source ECG dataset linking to an imaging marker, regional wall motion abnormality (RWMA),...

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Semi-Supervised Partial Label Learning (SSPLL) is an important branch of weakly supervised learning, where the data consists of both partial label examples and unlabeled ones. In SSPLL, the existence of unlabeled examples presents a great challenge to train a model with good generalization ability....

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Malware remains a persistent and evolving cybersecurity threat, necessitating advanced detection techniques to counter increasingly sophisticated attacks. This survey provides a comprehensive review of deep learning-based approaches for malware detection, synthesizing 109 publications published betw...

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Deep learning-based medical image processing methods can enhance diagnostic accuracy while significantly accelerating clinical decision workflows. However, in order to learn better visual representations, such approaches usually need substantial amount of expert-annotated data, which are highly cost...

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This study proposes a novel dual input power amplifier (PA) with a frequency-periodic load modulated output matching network supported by a broadband biasing network. The output matching network consists of two transmission lines which enable the dual-input PA to operate in Doherty or outphasing mod...

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In response to the application scenarios of modernized Traditional Chinese Medicine (TCM) diagnostic and treatment equipment moving towards the user end, an effort has been made to enhance the user-friendliness of TCM diagnostic and treatment devices. This involves introducing the concept of edge co...

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