When it comes to smart healthcare business systems,network-based intrusion detection systems are crucial for protecting the system and its networks from malicious network *** protect IoMT devices and networks in healt...
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When it comes to smart healthcare business systems,network-based intrusion detection systems are crucial for protecting the system and its networks from malicious network *** protect IoMT devices and networks in healthcare and medical settings,our proposed model serves as a powerful tool for monitoring IoMT *** study presents a robust methodology for intrusion detection in Internet of Medical Things(IoMT)environments,integrating data augmentation,feature selection,and ensemble learning to effectively handle IoMT data *** rigorous preprocessing,including feature extraction,correlation removal,and Recursive Feature Elimi-nation(RFE),selected features are standardized and reshaped for deep learning *** using the BAT algorithm enhances dataset *** deep learning models,Transformer-based neural networks,self-attention Deep Convolutional Neural Networks(DCNNs),and Long Short-Term Memory(LSTM)networks,are trained to capture diverse data *** predictions form a meta-feature set for a subsequent meta-learner,which combines model *** classifiers validate meta-learner features for broad algorithm *** comprehensive method demonstrates high accuracy and robustness in IoMT intrusion *** were conducted using two datasets:the publicly available WUSTL-EHMS-2020 dataset,which contains two distinct categories,and the CICIoMT2024 dataset,encompassing sixteen *** results showcase the method’s exceptional performance,achieving optimal scores of 100%on the WUSTL-EHMS-2020 dataset and 99%on the CICIoMT2024.
Dear Editor, This letter is concerning friendly jamming unmanned aerial vehicles(UAVs) to assist in the safe communication of UAV base stations. Due to the openness of UAV wireless communication, it is vulnerable to a...
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Dear Editor, This letter is concerning friendly jamming unmanned aerial vehicles(UAVs) to assist in the safe communication of UAV base stations. Due to the openness of UAV wireless communication, it is vulnerable to attacks leading to information disclosure or blockage. To address this issue, friendly jamming UAVs can assist UAV base stations and improve the security of wireless communications.
Robust and high-precision vehicle positioning information is crucial for Internet of Things (IoT) applications like autonomous driving and intelligent transportation. While global navigation satellite system (GNSS)/in...
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Facial attractiveness prediction is an important research topic in the computervision community. It not only contributes to the development of interdisciplinary research in psychology and sociology, but also provides...
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The SDR-to-HDR translation technique can convert the abundant standard-dynamic-range (SDR) media resources to high-dynamic-range (HDR) ones, which can represent high-contrast scenes, providing more realistic visual ex...
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The SDR-to-HDR translation technique can convert the abundant standard-dynamic-range (SDR) media resources to high-dynamic-range (HDR) ones, which can represent high-contrast scenes, providing more realistic visual experiences. While recent vision Transformers have achieved promising performance in many low-level vision tasks, there are few works attempting to leverage Transformers for SDR-to-HDR translation. In this paper, we are among the first to investigate the performance of Transformers for SDR-to-HDR translation. We find that directly using the self-attention mechanism may involve artifacts in the results due to the inappropriate way to model long-range dependencies between the low-frequency and high-frequency components. Taking this into account, we advance the self-attention mechanism and present a dual frequency attention (DFA), which leverages the self-attention mechanism to separately encode the low-frequency structural information and high-frequency detail information. Based on the proposed DFA, we further design a multi-scale feature fusion network, named dual frequency Transformer (DFT), for efficient SDR-to-HDR translation. Extensive experiments on the HDRTV1K dataset demonstrate that our DFT can achieve better quantitative and qualitative performance than the recent state-of-the-art methods. The code of our DFT is made publicly available at https://***/CS-GangXu/DFT.
Abstract: The initial boundary value problem regarding vibrations of an annular membrane is considered. Nonsteady boundary conditions are specified, and there is no distributed load. This is a nonclassical formulation...
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Abstract: The initial model boundary value problem regarding vibrations of a viscoelastic beam with damping of Voigt type is considered. A classical formulation of a mixed problem for a fifth-order linear partial diff...
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Abstract: For a one-dimensional boundary problem associated with a linear parabolic equation in the presence of a nonlocal spatial condition, necessary and sufficient conditions for the existence of a solution are est...
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In this paper, the finite-time stabilization of the disturbed and uncertain rotary-inverted-pendulum system is studied based on the adaptive backstepping sliding mode control procedure. For this purpose, first of all,...
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A comprehensive benchmark is yet to be established in the Image Manipulation Detection & Localization (IMDL) field. The absence of such a benchmark leads to insufficient and misleading model evaluations, severely ...
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