Due to optical fiber limitations for quantum communication, global-scale quantum networks are possible only by integrating non-terrestrial components in the overall network architecture. Quantum networks are expected ...
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This study investigates the cognitive and emotional processes involved in augmented reality (AR)-based learning. The study looks at learning outcomes, emotional responses, meditation, and attention using a comprehensi...
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To satisfy the low delay, low jitter, and high success rate requirements for in-vehicle networks, IEEE 802.1 Task Group proposed Time-Sensitive Networking (TSN), which has aroused increasing attention in managing time...
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IDS is becoming increasingly important as networks become more vulnerable to a variety of attacks. However, traditional ML and DL-based IDS have limited accuracy and false positive rates due to the lack of open advers...
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ISBN:
(数字)9798331507022
ISBN:
(纸本)9798331507039
IDS is becoming increasingly important as networks become more vulnerable to a variety of attacks. However, traditional ML and DL-based IDS have limited accuracy and false positive rates due to the lack of open adversarial network datasets and vendors' concerns regarding potential data leakage during the training process. To address these challenges, VAE and GAN-based network packet generation models have emerged, but they still face issues with low data fidelity. In this context, TabDDPM is a suitable option for generating network packets, as it surpasses VAE and GAN in accurately capturing data distribution characteristics and effectively learning the inherent structure of network packet formats. Despite its potential, research applying TabDDPM to network packet generation has not yet been explored. In this paper, we propose and evaluate DP-NetDDPM, a novel framework that enables adversarial network traffic generation while preserving both fidelity and privacy guarantees. Specifically, we examine the use of diffusion to generate adversarial network packet datasets and compare its performance with baseline models. Our framework focuses on three key criteria: data fidelity, adaptability for machine learning applications, and data privacy. The results show that DP-NetDDPM surpasses traditional models in both fidelity and adaptability, achieving a notable 72% improvement in fidelity and a 45% enhancement in adaptability over baselines.
This paper introduces a real-time head-pose detection and eye-gaze estimation system for Automatic Driver Assistance Technology (ADAT) aimed at enhancing driver safety by accurately collecting and transmitting data on...
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Wearable and implantable devices mark a major advancement in biomedical engineering, enabling continuous bio-signal monitoring and treatment based on precise feedback. However, traditional rigid bioelectronic devices ...
Wearable and implantable devices mark a major advancement in biomedical engineering, enabling continuous bio-signal monitoring and treatment based on precise feedback. However, traditional rigid bioelectronic devices face challenges in seamlessly interfacing with soft organs, often leading to tissue damage and inflammation. To address these issues, soft bioelectronics that better conform to the body while maintaining performance accuracy have been developed. Despite these advancements, the dynamic nature of body movements and the complex chemical environment in the body can compromise the stability of devices over time. Therefore, recent innovations have focused on ultrathin and stretchable designs that enhance conformal contact through van der Waals forces, as well as the incorporation of adhesive hydrogels, to improve adhesion, even in the presence of biofluids. This review provides a comprehensive overview of the advancements in wearable and implantable bioelectronics aimed at achieving conformal tissue adhesion and long-term stability, covering structural modifications to bilayer designs. Finally, the integration of bioelectronics with closed-loop therapies to significantly enhance treatment efficacy is explored. • Materials strategies and device fabrication/integration processes optimally tailored to various organs are addressed. • Mechanical and electrical characterizations of wearable and implantable adhesive bioelectronics are described, while emphasizing challenges and opportunities in long-term stable tissue interfacing. • Various demonstrations of closed-loop bio-integrated systems using soft stretchable adhesive materials, and their futuristic perspectives are introduced.
This paper proposes the multiple-input multiple-output(MIMO)detection scheme by using the deep neural network(DNN)based ensemble machine learning for higher error performance in wireless communication *** the MIMO det...
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This paper proposes the multiple-input multiple-output(MIMO)detection scheme by using the deep neural network(DNN)based ensemble machine learning for higher error performance in wireless communication *** the MIMO detection based on the ensemble machine learning,all learning models for the DNN are generated in offline and the detection is performed in online by using already learned *** the offline learning,the received signals and channel coefficients are set to input data,and the labels which correspond to transmit symbols are set to output *** the online learning,the perfectly learned models are used for signal detection where the models have fixed bias and *** performance improvement,the proposed scheme uses the majority vote and the maximum probability as the methods of the model combinations for obtaining diversity gains at the MIMO *** simulation results show that the proposed scheme has improved symbol error rate(SER)performance without additional receive antennas.
Low Earth Orbit (LEO) constellations and Unmanned Aerial Vehicle (UAV) networks enable wide coverage for the sixth generation (6G) mobile communication. However, it is a challenge to achieve high scheduling success ra...
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A number of requirements for 5G mobile communication are satisfied by adopting multiple input multiple output(MIMO)*** inter user interference(IUI)which is an inevitable problem in MIMO systems becomes controllable wh...
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A number of requirements for 5G mobile communication are satisfied by adopting multiple input multiple output(MIMO)*** inter user interference(IUI)which is an inevitable problem in MIMO systems becomes controllable when the precoding scheme is *** this paper,the horizontal Gauss-Seidel(HGS)method is proposed as precoding scheme in massive MIMO *** massive MIMO systems,the exact inversion of channel matrix is impractical due to the severe computational ***,the conventionalGauss-Seidel(GS)method is used to approximate the inversion of channel *** GS has good performance by using previous calculation results as ***,the required time for obtaining the precoding symbols is too long due to the sequential process of ***,the HGS with parallel calculation is proposed in this paper to reduce the required *** rows of channel matrix are eliminated for parallel calculation *** addition,HGSuses the ordered channelmatrix to prevent performance degradation which is occurred by parallel *** HGS with proper number of parallelly computed symbols has better performance and reduced required time compared to the traditional GS.
As the installation of small cells increases,the use of relay also *** relay operates as a base station as well as just an *** the roles and types of relays become more diverse,appropriate relay selection technology i...
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As the installation of small cells increases,the use of relay also *** relay operates as a base station as well as just an *** the roles and types of relays become more diverse,appropriate relay selection technology is an effective way to improve communication *** researches for relay selection have been studied to secure the reliability of relay *** this paper,the relay selection scheme is proposed for a cooperative system using decode-and-forward(DF)relaying scheme in the mobile communication *** maintain the transmission rate,the proposed scheme classifies a candidate group considering the outage probability of multiple *** the applicable candidate group,the proposed scheme selects the relay considering the amount of data allocated to each ***,the proposed scheme defines the unit transmission time through each user’s data and relay ***,the proposed scheme selects a relay that minimizes the total transmission time through the relay transmission time that calculates the unit transmission time for all *** this adaptive relay selection scheme,an optimal relay can be assigned for each *** the same transmission rate and the amount of data,the proposed scheme improves the performance of transmission time and *** results show that the proposed scheme reduces the total transmission time for the same amount of data and signal to noise ratio(SNR).
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