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A Succinct Power Management Circuit for Wireless Sensor Network Nodes 6th

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A Succinct Power Management Circuit for Wireless Sensor Netw...

6th International Conference on Artificial Intelligence and Security,ICAIS 2020

作者： Li, Gang Zheng, Wenxian Li, Zhenbing Huang, Zhong Yang, Yongjun Wen, Guangjun Centre for RFIC and System School of Information and Communication Engineering University of Electronic Science and Technology of China ChengduSichuan China Tsinghua Shenzhen International Graduate School Shenzhen518055 China Shenzhen Intellifusion Technologies Co. Ltd. Shenzheng518000 China

ISBN: (纸本)9789811580857

In wireless sensor networks, radio frequency identification (RFID) is one of the key technologies for data transmitted by the sensor node. In the RFID system, tags convert RF energy to DC through antennas and rectifying circuits, and supply power to other circuits. The sensor and signal conditioning circuit require high energy, so it is difficult to make the sensor node work normally by using the traditional energy harvest and power management circuits. Moreover, since the power management circuit is charged and discharged at the same time, when the converted RF energy is close to the energy consumed by circuit, the sensor and signal conditioning circuit may not work normally. In order to improve the performance of the power management circuit of the sensor node, a succinct power management circuit based on double capacitance is proposed in this paper. Compared with the classical commercial BQ25570 devices, the proposed power management circuit is easier to realize and integrate into the sensor node chip, thus reducing the power consumption of the sensor node. In the paper, the different charging time constants of two capacitor circuits are used to provide power for the subsequent circuits after enough energy is collected. This mode of operation enables the sensor nodes to work stably. The proposed circuit is succinct and easy to implement, and the energy transfer efficiency is about 87% after the capacitor is charged. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Capacitance

Smart photonic wristband for pulse wave monitoring

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Opto-Electronic Science 2024年第12期3卷 12-27页

作者： Renfei Kuang Zhuo Wang Lin Ma Heng Wang Qingming Chen Arnaldo Leal Junior Santosh Kumar Xiaoli Li Carlos Marques Rui Min Center for Cognition and Neuroergonomics State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityZhuhai 519087China College of Science Shenyang Aerospace UniversityShenyang 110136China School of Microelectronics Science and Technology Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and SystemsSun Yat-Sen UniversityZhuhai 519082China Graduate Program in Electrical Engineering Federal University of Espírito SantoFernando Ferrari AvenueVitoria 29075-910Brazil Department of Electronics and Communication Engineering Koneru Lakshmaiah Education FoundationVaddeswaramAndhra Pradesh 522302India CICECO-Aveiro Institute of Materials Physics DepartmentUniversity of AveiroAveiro 3810-193Portugal

Real-time acquisition of human pulse signals in daily life is clinically important for cardiovascular disease monitoring and ***,we propose a smart photonic wristband for pulse signal monitoring based on speckle pattern analysis with a polymer optical fiber(POF)integrated into a sports *** different speckle pattern processing algorithms and POFs with different core diameters were *** results indicated that the smart photonic wristband had a high signal-to-noise ratio and low latency,with the measurement error controlled at approximately 3.7%.This optimized pulse signal could be used for further medical diagnosis and was capable of objectively monitoring subtle pulse signal changes,such as the pulse waveform at different positions of Cunkou and pulse waveforms before and after *** the assistance of artificial intelligence(AI),functions such as gesture recognition have been realized through the established prediction model by processing pulse signals,in which the recognition accuracy reaches 95%.Our AI-assisted smart photonic wristband has potential applications for clinical treatment of cardiovascular diseases and home monitoring,paving the way for medical Internet of Things-enabled smart systems.

关键词： smart healthcare specklegram pulse monitoring gesture recognition artificial intelligence wearable sensor

Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization

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arXiv 2023年

作者： Du, Hongyang Zhang, Ruichen Liu, Yinqiu Wang, Jiacheng Lin, Yijing Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Cui, Shuguang Ai, Bo Zhou, Haibo Kim, Dong In The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Computer Science and Engineering Nanyang Technological University Singapore The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications China The School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore Shenzhen China The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China School of Electronic Science and Engineering Nanjing University Jiangsu Nanjing210093 China The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy across various applications. The ability to model complex data distributions and generate high-quality samples has made GDMs particularly effective in tasks such as image generation and reinforcement learning. Furthermore, their iterative nature, which involves a series of noise addition and denoising steps, is a powerful and unique approach to learning and generating data. This paper serves as a comprehensive tutorial on applying GDMs in network optimization tasks. We delve into the strengths of GDMs, emphasizing their wide applicability across various domains, such as vision, text, and audio generation. We detail how GDMs can be effectively harnessed to solve complex optimization problems inherent in networks. The paper first provides a basic background of GDMs and their applications in network optimization. This is followed by a series of case studies, showcasing the integration of GDMs with Deep Reinforcement Learning (DRL), incentive mechanism design, Semantic communications (SemCom), Internet of Vehicles (IoV) networks, etc. These case studies underscore the practicality and efficacy of GDMs in real-world scenarios, offering insights into network design. We conclude with a discussion on potential future directions for GDM research and applications, providing major insights into how they can continue to shape the future of network optimization. © 2023, CC BY.

关键词： Reinforcement learning

A Vehicle Forensics framework with Post-Quantum Cryptography and Blockchain

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A Vehicle Forensics framework with Post-Quantum Cryptography...

IEEE International Symposium on Intelligent Signal Processing and communication Systems (ISPACS)

作者： Chien-Lung Hsu Yi-Cheih Hsu Yu-Jen Shih Cheng-Wei Wu Fu-Hau Hsu Graduate Institute of Management Chang Gung University Taiwan Taoyuan R.O.C Department of Information Management Chang Gung University Taiwan Taoyuan R.O.C Healthy Aging Research Center Chang Gung University Taiwan Taoyuan R.O.C Department of Visual Communication Design Ming-Chi University of Technology Taiwan Taoyuan R.O.C Chang-Gung Memorial Hospital Taiwan Taoyuan R.O.C Department of Master of Science Degree Program in Innovation for Smart Medicine Chang Gung University Taiwan Taoyuan R.O.C Computer Science& Information Engineering National Central University Taiwan Taoyuan R.O.C Information Management Chang Gung University Taiwan Taoyuan R.O.C

ISBN: (数字)9798350389210

ISBN: (纸本)9798350389227

With the recent rapid development of the Internet of Vehicles and autonomous driving technology, the demand for digital vehicle identification has also increased. Coupled with the gradual maturity of quantum technology, the Internet of Vehicles, which mainly uses wireless communication technology for data transmission, will face the threat of quantum computing and privacy issues. This research proposes the Vehicle Forensics Cloud System (VFCS), a framework combining post-quantum cryptography and blockchain technology to address these issues and provide a comprehensive solution for vehicle digital forensics.

关键词： Wireless communication Quantum computing Digital forensics Insurance Signal processing Blockchains Safety Autonomous vehicles Interoperability Internet of Vehicles

Generative AI-enabled Vehicular Networks: Fundamentals, Framework, and Case Study

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arXiv 2023年

作者： Zhang, Ruichen Xiong, Ke Du, Hongyang Niyato, Dusit Kang, Jiawen Shen, Xuemin Poor, H. Vincent The Engineering Research Center of Network Management Technology High Speed Railway of Ministry of Education School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China The Collaborative Innovation Center of Railway Traffic Safety Beijing Jiaotong University Beijing100044 China The National Engineering Research Center of Advanced Network Technologies Beijing Jiaotong University Beijing100044 China The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Department of Electrical and Computer Engineering University of Waterloo Canada The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

Recognizing the tremendous improvements that the integration of generative AI can bring to intelligent transportation systems, this article explores the integration of generative AI technologies in vehicular networks, focusing on their potential applications and challenges. Generative AI, with its capabilities of generating realistic data and facilitating advanced decision-making processes, enhances various applications when combined with vehicular networks, such as navigation optimization, traffic prediction, data generation, and evaluation. Despite these promising applications, the integration of generative AI with vehicular networks faces several challenges, such as real-time data processing and decision-making, adapting to dynamic and unpredictable environments, as well as privacy and security concerns. To address these challenges, we propose a multi-modality semantic-aware framework to enhance the service quality of generative AI. By leveraging multi-modal and semantic communication technologies, the framework enables the use of text and image data for creating multi-modal content, providing more reliable guidance to receiving vehicles and ultimately improving system usability and efficiency. To further improve the reliability and efficiency of information transmission and reconstruction within the framework, taking generative AI-enabled vehicle-to-vehicle (V2V) as a case study, a deep reinforcement learning (DRL)-based approach is proposed for resource allocation. Finally, we discuss potential research directions and anticipated advancements in the field of generative AI-enabled vehicular networks. Copyright © 2023, The Authors. All rights reserved.

关键词： Reinforcement learning

University Students’ Attitudes toward Adoption of Mobile Health Application for Serving Older People

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Sensors and Materials 2023年第7期35卷 2581-2601页

作者： Chao, Pei-Ju Cheng, Yu-Huei Liu, Yi-Hui Hsu, Tsu-Hsuan Travel & Tourism Program International College Ming Chuan University 5 De Ming Rd. Gui Shan District Taoyuan333 Taiwan Department of Information and Communication Engineering Chaoyang University of Technology 168 Jifeng E. Rd. Wufeng District Taichung413 Taiwan Department of Senior Citizen Service Management National Taichung University of Science and Technology No. 129 Sec. 3 Sanmin Rd. North District Taichung404 Taiwan Graduate Institute of Rehabilitation Counseling National Changhua University of Education 1 Jin-De Rd. Changhua City500 Taiwan

In this quantitative study, we examined the awareness of mobile health (mHealth) applications among Taiwan’s university students, particularly the government-operated My Health Bank application. The My Health Bank application allows users to access their personal health information simply through their smartphone’s sensor-assisted facial recognition camera and fingerprint sensor. Whether these university students might help older adults to use this application if they perceive it to be helpful was also explored. Two instruments were used in this study, namely, the Perceptions toward My Health Bank (PMHB) and Geriatric Attitudes Scale (GAS). Two hundred twenty-five (225) university students from the Departments of Senior Citizen Service Management (n = 136) and Nursing (n = 89) at two universities participated in this study. The findings indicated low adoption of My Health Bank and related mHealth applications among students even though they had high adoption rates of smartphones. However, they perceived that the functions of this application are useful and should be promoted to older adults. Thus, building a basic foundation of mHealth and related technology courses is recommended to assist healthcare students in being well-prepared for working with older adults in the digital society. © MYU K.K.

关键词： mHealth

SADDEL: Joint speech separation and denoising model based on multitask learning

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arXiv 2020年

作者： Wu, Yuan-Kuei Tuan, Chao-I Lee, Hung-Yi Tsao, Yu Graduate Institute of Communication Engineering National Taiwan University Data Science Degree Program National Taiwan University Research Center for Information Technology Innovation Academia Sinica

Speech data collected in real-world scenarios often encounters two issues. First, multiple sources may exist simultaneously, and the number of sources may vary with time. Second, the existence of background noise in recording is inevitable. To handle the first issue, we refer to speech separation approaches, that separate speech from an unknown number of speakers. To address the second issue, we refer to speech denoising approaches, which remove noise components and retrieve pure speech signals. Numerous deep learning based methods for speech separation and denoising have been proposed that show promising results. However, few works attempt to address the issues simultaneously, despite speech separation and denoising tasks having similar nature. In this study, we propose a joint speech separation and denoising framework based on the multitask learning criterion to tackle the two issues simultaneously. The experimental results show that the proposed framework not only performs well on both speech separation and denoising tasks, but also outperforms related methods in most conditions. Copyright © 2020, The Authors. All rights reserved.

关键词： Source separation

Performance prediction recipes for optical links

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arXiv 2021年

作者： Agrell, Erik Secondini, Marco Alvarado, Alex Yoshida, Tsuyoshi The Department of Electrical Engineering Chalmers University of Technology Gothenburg41296 Sweden The Institute of Communication Information and Perception Technologies Scuola Superiore Sant'Anna Pisa Italy The National Laboratory of Photonic Networks CNIT Pisa Italy The Information and Communication Theory Lab Signal Processing Systems Group Department of Electrical Engineering Eindhoven University of Technology Eindhoven5600 MB Netherlands Information Technology R&D Center Mitsubishi Electric Corporation 5-1-1 Ofuna Kamakura247-8501 Japan Graduate School of Osaka University 2-1 Yamadaoka Suita565-0871 Japan

Although forward error-correction (FEC) coding is an essential part of modern fiber-optic communication systems, it is impractical to implement and evaluate FEC in transmission experiments and simulations. Therefore, it is desirable to accurately predict the end-to-end link performance including FEC from transmission data recorded without FEC. In this tutorial, we provide ready-to-implement "recipes" for such prediction techniques, which apply to arbitrary channels and require no knowledge of information or coding theory. The appropriate choice of recipe depends on properties of the FEC encoder and decoder. The covered metrics include bit error rate, symbol error rate, achievable information rate, and asymptotic information, in all cases computed using a mismatched receiver. Supplementary software implementations are available. © 2021, CC BY-SA.

关键词： Forward error correction

Unveiling Topological Charges and Their Manipulation in Electronic Circuits

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arXiv 2022年

作者： Sakotic, Zarko Stankovic, Predrag Bengin, Vesna Krasnok, Alex Alú, Andrea Jankovic, Nikolina BioSense Institute Research Institute for Information Technologies in Biosystems University of Novi Sad Dr Zorana Djindjica 1a Novi Sad21101 Serbia Department of Electrical and Computer Engineering Florida International University MiamiFL33174 United States Advanced Science Research Center City University of New York New YorkNY10031 United States Physics Program Graduate Center City University of New York New YorkNY10016 United States

Leveraging topological properties in the response of electromagnetic systems can greatly enhance their potential. Although the investigation of singularity-based electromagnetics and non-Hermitian electronics has considerably increased in recent years in the context of various scattering anomalies, their topological properties have not been fully assessed. In this work, we theoretically and experimentally demonstrate that non-Hermitian perturbations around bound states in the continuum can lead to singularities of the scattering matrix, which are topologically nontrivial and comply with charge conservation. The associated scattering matrix poles, zeros and pole-zero pairs delineate extreme scattering events, including lasing, coherent perfect absorption, and absorber-lasers. The presented framework enables a recipe for generation, annihilation and addition of these singularities in electric circuits, with potential for extreme scattering engineering across a broad range of the electromagnetic spectrum for sensing, wireless power transfer, lasing and thermal emission devices. Copyright © 2022, The Authors. All rights reserved.

关键词： Topology