With the advancement of wireless network technology,vast amounts of traffic have been generated,and malicious traffic attacks that threaten the network environment are becoming increasingly sophisticated.While signatu...With the advancement of wireless network technology,vast amounts of traffic have been generated,and malicious traffic attacks that threaten the network environment are becoming increasingly sophisticated.While signature-based detection methods,static analysis,and dynamic analysis techniques have been previously explored for malicious traffic detection,they have limitations in identifying diversified malware traffic patterns.Recent research has been focused on the application of machine learning to detect these patterns.However,applying machine learning to lightweight devices like IoT devices is challenging because of the high computational demands and complexity involved in the learning process.In this study,we examined methods for effectively utilizing machine learning-based malicious traffic detection approaches for lightweight devices.We introduced the suboptimal feature selection model(SFSM),a feature selection technique designed to reduce complexity while maintaining the effectiveness of malicious traffic detection.Detection performance was evaluated on various malicious traffic,benign,exploits,and generic,using the UNSW-NB15 dataset and SFSM sub-optimized hyperparameters for feature selection and narrowed the search scope to encompass all features.SFSM improved learning performance while minimizing complexity by considering feature selection and exhaustive search as two steps,a problem not considered in conventional models.Our experimental results showed that the detection accuracy was improved by approximately 20%compared to the random model,and the reduction in accuracy compared to the greedy model,which performs an exhaustive search on all features,was kept within 6%.Additionally,latency and complexity were reduced by approximately 96%and 99.78%,respectively,compared to the greedy model.This study demonstrates that malicious traffic can be effectively detected even in lightweight device environments.SFSM verified the possibility of detecting various attack traffic on lightweight devices.展开更多
To meet the increasing demand of wireless broadband applications in future 5G cellular networks, Device-to-Device(D2D) communications serve as a candidate paradigm to improve spectrum efficiency. Considering the chall...To meet the increasing demand of wireless broadband applications in future 5G cellular networks, Device-to-Device(D2D) communications serve as a candidate paradigm to improve spectrum efficiency. Considering the challenges after D2 D transmission is introduced for future cellular networks, this paper deals with mode selection and resource allocation issues related with D2 D communications. First, we propose a mode selection scheme which aims at guaranteeing the transmission of cellular users and also considering the potential interference. We analyze the condition under which D2 D underlay mode should be used. Second, we answer the question of "how to effectively reuse cellular resource once underlaying mode is adopted". We further present a resource allocation scheme that focuses on minimizing overall interference as well as a power control method to improve the performance of D2 D systems. Simulation results demonstrate that system parameters greatly affect the switching condition of mode selection and probability of choosing underlay mode. Furthermore, for D2 D underlaying scenario, the proposed resource allocation algorithm guarantees the transmission of cellular users with consideration of transmission requirements of D2 D users. Hence, the proposed scheme can achieve better user experience.展开更多
Narrow bandwidth is a crucial factor in a high performance wavelength selective device(WSD). There are many different expressions to estimate bandwidths of many different WSDs. In this paper, we derive an important ...Narrow bandwidth is a crucial factor in a high performance wavelength selective device(WSD). There are many different expressions to estimate bandwidths of many different WSDs. In this paper, we derive an important rule that the differential time delay between two coupling modes is the most important factor deciding the wavelength channel bandwidth for several different WSDs. This rule reveals that larger differential time delay between two coupling modes results in higher discrimination level of the operating wavelength. Based on the rule, a novel design of wavelength selective coupler that has a bandwidth narrower than normal couplers is presented.展开更多
1 Introduction? Mechanical circulatory support (MCS) has increasingly become an important management opportunity for patients with stage D heart failure (HF) with remarkable impact on patient survival and quality of l...1 Introduction? Mechanical circulatory support (MCS) has increasingly become an important management opportunity for patients with stage D heart failure (HF) with remarkable impact on patient survival and quality of life. Early clinical trials have demonstrated improved outcomes of durable left ventricular assist device (LVAD) support compared with optimal medical management.[1] As technology advanced, continuous flow LVADs outperformed pulsatile flow devices in clinical trials and the field migrated to HeartMate (Abbott Laboratories, Abbott Park, IL) and HeartWare (Medtronic, Minneapolis, MN) devices due to their clinical superiority. Among the continuous flow devices.展开更多
Recently,the increasing interest in wearable technology for personal healthcare and smart virtual/augmented reality applications has led to the development of facile fabrication methods.Lasers have long been used to d...Recently,the increasing interest in wearable technology for personal healthcare and smart virtual/augmented reality applications has led to the development of facile fabrication methods.Lasers have long been used to develop original solutions to such challenging technological problems due to their remote,sterile,rapid,and site-selective processing of materials.In this review,recent developments in relevant laser processes are summarized under two separate categories.First,transformative approaches,such as for laser-induced graphene,are introduced.In addition to design optimization and the alteration of a native substrate,the latest advances under a transformative approach now enable more complex material compositions and multilayer device configurations through the simultaneous transformation of heterogeneous precursors,or the sequential addition of functional layers coupled with other electronic elements.In addition,the more conventional laser techniques,such as ablation,sintering,and synthesis,can still be used to enhance the functionality of an entire system through the expansion of applicable materials and the adoption of new mechanisms.Later,various wearable device components developed through the corresponding laser processes are discussed,with an emphasis on chemical/physical sensors and energy devices.In addition,special attention is given to applications that use multiple laser sources or processes,which lay the foundation for the all-laser fabrication of wearable devices.展开更多
基金supported by the Korea Institute for Advancement of Technology(KIAT)Grant funded by the Korean Government(MOTIE)(P0008703,The Competency Development Program for Industry Specialists)MSIT under the ICAN(ICT Challenge and Advanced Network of HRD)Program(No.IITP-2022-RS-2022-00156310)supervised by the Institute of Information&Communication Technology Planning and Evaluation(IITP).
文摘With the advancement of wireless network technology,vast amounts of traffic have been generated,and malicious traffic attacks that threaten the network environment are becoming increasingly sophisticated.While signature-based detection methods,static analysis,and dynamic analysis techniques have been previously explored for malicious traffic detection,they have limitations in identifying diversified malware traffic patterns.Recent research has been focused on the application of machine learning to detect these patterns.However,applying machine learning to lightweight devices like IoT devices is challenging because of the high computational demands and complexity involved in the learning process.In this study,we examined methods for effectively utilizing machine learning-based malicious traffic detection approaches for lightweight devices.We introduced the suboptimal feature selection model(SFSM),a feature selection technique designed to reduce complexity while maintaining the effectiveness of malicious traffic detection.Detection performance was evaluated on various malicious traffic,benign,exploits,and generic,using the UNSW-NB15 dataset and SFSM sub-optimized hyperparameters for feature selection and narrowed the search scope to encompass all features.SFSM improved learning performance while minimizing complexity by considering feature selection and exhaustive search as two steps,a problem not considered in conventional models.Our experimental results showed that the detection accuracy was improved by approximately 20%compared to the random model,and the reduction in accuracy compared to the greedy model,which performs an exhaustive search on all features,was kept within 6%.Additionally,latency and complexity were reduced by approximately 96%and 99.78%,respectively,compared to the greedy model.This study demonstrates that malicious traffic can be effectively detected even in lightweight device environments.SFSM verified the possibility of detecting various attack traffic on lightweight devices.
基金supported by the National Natural Science Foundation of China(No.61501371)National 863 High Tech R&D Program of China(project number:2014AA01A703)+1 种基金National Science and Technology Major Project of the Ministry of Science and Technology of China(project number:2014ZX03001025-006)The international Exchange and Cooperation Projects of Shaanxi Province(project number:2016KW-046)
文摘To meet the increasing demand of wireless broadband applications in future 5G cellular networks, Device-to-Device(D2D) communications serve as a candidate paradigm to improve spectrum efficiency. Considering the challenges after D2 D transmission is introduced for future cellular networks, this paper deals with mode selection and resource allocation issues related with D2 D communications. First, we propose a mode selection scheme which aims at guaranteeing the transmission of cellular users and also considering the potential interference. We analyze the condition under which D2 D underlay mode should be used. Second, we answer the question of "how to effectively reuse cellular resource once underlaying mode is adopted". We further present a resource allocation scheme that focuses on minimizing overall interference as well as a power control method to improve the performance of D2 D systems. Simulation results demonstrate that system parameters greatly affect the switching condition of mode selection and probability of choosing underlay mode. Furthermore, for D2 D underlaying scenario, the proposed resource allocation algorithm guarantees the transmission of cellular users with consideration of transmission requirements of D2 D users. Hence, the proposed scheme can achieve better user experience.
文摘Narrow bandwidth is a crucial factor in a high performance wavelength selective device(WSD). There are many different expressions to estimate bandwidths of many different WSDs. In this paper, we derive an important rule that the differential time delay between two coupling modes is the most important factor deciding the wavelength channel bandwidth for several different WSDs. This rule reveals that larger differential time delay between two coupling modes results in higher discrimination level of the operating wavelength. Based on the rule, a novel design of wavelength selective coupler that has a bandwidth narrower than normal couplers is presented.
文摘1 Introduction? Mechanical circulatory support (MCS) has increasingly become an important management opportunity for patients with stage D heart failure (HF) with remarkable impact on patient survival and quality of life. Early clinical trials have demonstrated improved outcomes of durable left ventricular assist device (LVAD) support compared with optimal medical management.[1] As technology advanced, continuous flow LVADs outperformed pulsatile flow devices in clinical trials and the field migrated to HeartMate (Abbott Laboratories, Abbott Park, IL) and HeartWare (Medtronic, Minneapolis, MN) devices due to their clinical superiority. Among the continuous flow devices.
基金supported by the Basic Research Program through the National Research Foundation of Korea(NRF)(Nos.2022R1C1C1006593,2022R1A4A3031263,and RS-2023-00271166)the National Science Foundation(Nos.2054098 and 2213693)+1 种基金the National Natural Science Foundation of China(No.52105593)Zhejiang Provincial Natural Science Foundation of China(No.LDQ24E050001).EH acknowledges a fellowship from the Hyundai Motor Chung Mong-Koo Foundation.
文摘Recently,the increasing interest in wearable technology for personal healthcare and smart virtual/augmented reality applications has led to the development of facile fabrication methods.Lasers have long been used to develop original solutions to such challenging technological problems due to their remote,sterile,rapid,and site-selective processing of materials.In this review,recent developments in relevant laser processes are summarized under two separate categories.First,transformative approaches,such as for laser-induced graphene,are introduced.In addition to design optimization and the alteration of a native substrate,the latest advances under a transformative approach now enable more complex material compositions and multilayer device configurations through the simultaneous transformation of heterogeneous precursors,or the sequential addition of functional layers coupled with other electronic elements.In addition,the more conventional laser techniques,such as ablation,sintering,and synthesis,can still be used to enhance the functionality of an entire system through the expansion of applicable materials and the adoption of new mechanisms.Later,various wearable device components developed through the corresponding laser processes are discussed,with an emphasis on chemical/physical sensors and energy devices.In addition,special attention is given to applications that use multiple laser sources or processes,which lay the foundation for the all-laser fabrication of wearable devices.
