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CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Qin, Jun Yang, Qipeng Han, Changhao Zhou, Yan Zhang, Yunhao Wu, Yichen Sun, Yu Lu, Junde Liu, Siming Li, Yueqin Sun, Jian Min, Miao Hu, Weiwei He, Zhixue Wang, Lei Yu, Shaohua Shu, Haowen Wang, Xingjun Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument Beijing Information Science and Technology University Beijing100192 China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing100871 China Department of Electrical and Computer Engineering University of California Santa BarbaraCA93106 United States Peking University Yangtze Delta Institute of Optoelectronics Nantong226010 China Peng Cheng Laboratory Shenzhen518055 China State Key Laboratory of Information Photonics and Optical Communications BUPT Beijing100876 China

We explore implementing a multilevel deep neural network to enhance the performance of a 4-channel photonic-electrical hybrid-packaged silicon transceiver. Stable transmission and reception of 150 Gbps/λ PAM4 signals... 详细信息

关键词： Optical interconnects

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Analysis and Study on Grid-Connected Photovoltaic Solar Power Plant using Artificial Intelligence

Analysis and Study on Grid-Connected Photovoltaic Solar Powe...

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2024 Asia Pacific Conference on Innovation in technology, APCIT 2024

作者： Sood, Devendra Kumar, Sumit Agarwal, Pawan Singh, Akhilesh Chakravorty, Abhishek Goyal, Shweta Tula's Institute Deptt. of CSE Dehradun India JB Instiitute of Technology Dept of Mechanical Engineering Uttarakhand Dehradun India Graphic Era Hill University Deptt. of Professional Communication Uttarakhand Bhimtal India Uttarakhand Technical University Deptt. of Electrical Engg. NPSEI Pithoragarh Campus India Tula's Institute Deptt. of Instrumentation & Control Dehradun India Graphic Era Deemed to Be University Deptt. of Electrical Engg. Dehradun India

ISBN: (纸本)9798350361537

The photovoltaic (PV) industry is adopting artificial intelligence (AI) more frequently as a result of advancements in data collecting, tools, and processing power. It has been demonstrated that the current methods employed in many solar photovoltaic sector activities related to design, estimation, management, and monitoring yield positive outcomes;however, complex equipment is needed for the analysis and estimation of the operation and management of the solar photovoltaic power plant. Promoting solar photovoltaic energy is necessary to address climate change-related issues and increase the usage of renewable energy sources. This project's objectives are to assess the efficiency of artificial intelligence (AI) in resolving energy-related issues and investigate the effects of grid-connected photovoltaic (PV) systems. Research has been done on the effects of artificial intelligence (AI) on specific PV grid functions. The purpose of this project is to assess the state of artificial intelligence technology at the moment and look at how artificial intelligence may be used in the future. © 2024 IEEE.

关键词： Information management

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Application of Integrated Sensing and communication in Structural Health Monitoring

Application of Integrated Sensing and Communication in Struc...

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International Conference on Wireless and Optical communications ( WOCC)

作者： Jie Yang Chao-Kai Wen Shi Jin Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China Institute of Communications Engineering National Sun Yat-sen University Kaohsiung Taiwan National Mobile Communications Research Laboratory Southeast University Nanjing China

ISBN: (数字)9798331539658

ISBN: (纸本)9798331539665

Integrated sensing and communication (ISAC) is a primary goal in future cellular systems. Numerous researchers have explored how cellular systems can incorporate sensing capabilities in various use cases, such as intruder detection, monitoring, tracking, and collision avoidance. However, the potential of ISAC in structural health monitoring (SHM), which involves detecting slow and subtle changes in structures, remains unexplored. This study introduces a pioneering problem model and a solution framework for SHM using ISAC technology, employing reconfigurable intelligent surfaces (RIS) as reference points for monitoring building structures. Our method is inspired by the dynamic phase configuration of RIS to generate varying radio signals, which differ from background interference and thus facilitate the acquisition of precise radio measurements from the reference points. We conduct a theoretical analysis of these radio measurements through the lens of Fisher information. Our findings confirm that increasing observation time, adding more receivers, and optimizing RIS phases significantly enhance the position error bound (PEB) and orientation error bound (OEB) of the reference points, meeting the stringent accuracy requirements of SHM. Furthermore, we develop a Bayesian inference model to recognize structural states based on the calculated PEB and OEB, enabling the validation of detection probabilities of cellular systems in identifying damaged structural conditions. Our comprehensive theoretical and numerical analysis reveals the capability of ISAC to effectively detect millimeter-level deformations.

关键词： Wireless communication Wireless sensor networks Deformation Numerical analysis Buildings Receivers Reconfigurable intelligent surfaces Integrated sensing and communication Numerical models Monitoring

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Preface: Security and safety in artificial intelligence

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Security and Safety 2024年第4期3卷 4-5页

作者： Hao Zhang Yu-Gang Jiang Claudio Melchiorri Gerhard Rigoll Department of Control Science and Engineering Tongji UniversityShanghai 200092China Shanghai Institute of Intelligent Science and Technology Shanghai 201210China School of Computer Science Fudan UniversityShanghai 200433China Department of Electrical Electronic and Information EngineeringUniversity of BolognaBologna 40136Italy Institute for Human-Machine Communication Technical University of MunichMunich 80539Germany

This special topic centers on cutting-edge advancements in the security and safety of artificial intelligence(AI),with a focus on critical applications across domains such as autonomous systems,federated learning,and network *** rapid evolution of AI algorithms,enabled by advances in hardware and software,has led to transformative applications but also revealed significant vulnerabilities and security risks.

关键词： artificial hardware autonomous

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Design of an Assistive technology Wearable Vest for persons with Hearing Disability

Design of an Assistive Technology Wearable Vest for persons ...

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RSI/ISM International Conference on Robotics and Mechatronics (ICROM)

作者： Tariq Anwaar Arun Srinivasan V K Nandha Kizor V Navneeth Rajiv Mechanical Engineering National Institute of Technology Tiruchirappalli Tamil Nadu India Instrumentation and Control Engineering National Institute of Technology Tiruchirappalli Tamil Nadu India Electronics and Communication Engineering National Institute of Technology Tiruchirappalli Tamil Nadu India Metallurgical Engineering National Institute of Technology Tiruchirappalli Tamil Nadu India

ISBN: (纸本)9781665454537

People with hearing disability face several limitations in life when it comes to being independent and looking after their own selves. Although there has been significant research in hearing aids, they turn out to be costly and have several drawbacks. Research on wearable devices for people with hearing disability has manifested into the availability of several wearable devices for indoor purposes. However, there is a lack of such devices for outdoor settings. This paper seeks to propose an assistive technology device for people with hearing disability to be used in crowded outdoor environments, warning them of potential sources of danger not in line of their vision.

关键词： Mechatronics Wearable computers Auditory system Assistive technologies Hearing aids Robots Faces

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Deep Neural Network Enhanced Chip-on-board Hybrid-Packaged Photonic-Electrical Silicon Transceiver for High-speed Optical Interconnects

Deep Neural Network Enhanced Chip-on-board Hybrid-Packaged P...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

ISBN: (纸本)9781957171395

关键词： Optical interconnects

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Polarized Modulation for RIS-Aided Vehicular communication Networks

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IEEE Internet of Things Journal 2025年第12期12卷 18616-18627页

作者： Shang, Pingping Xie, Longhui Li, Jun Feng, Li Hai, Han Xu, Binbin Li, Jie Yu, Ling Hubei University of Technology School of Electrical and Electronic Engineering Wuhan430068 China Hubei University of Technology Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Wuhan430068 China Guangzhou University Research Center of Intelligent Communication Engineering School of Electronics and Communication Engineering Guangzhou510006 China Key Laboratory of On-Chip Communication and Sensor Chip of Guangdong Higher Education Institutes Guangzhou510006 China Donghua University School of Information Science and Technology Shanghai201620 China Maritime Communication Research Institute Wuhan430068 China Guangdong Provincial Hospital of Chinese Medicine Guangzhou510120 China State Key Laboratory of Traditional Chinese Medicine Syndrome Guangzhou510120 China

The reconfigurable intelligent surface (RIS) stands as an emergent technique poised to revolutionize future vehicular communication. In order to facilitate the application of RIS in vehicular communication, this paper proposes two effective RIS-aided schemes tailored for polarization modulation (PM) aiming to achieve remarkable spectral efficiency. Specifically, Scheme I proposes a novel index modulation (IM) aided PM-RIS framework that innovatively encodes information across three distinct dimensions, the indices of dual-polarized antennas (DP-AEs), PM symbols and the reflecting surface indices of the RIS. Scheme II employs a deep neural network method to analyze the channel state information (CSI) for transmit antenna selection, that enhances the reliability and interference immunity in dynamic conditions while reducing computational complexity. Furthermore, a stepwise estimation (SE) method is introduced at the detection stage, which significantly reduces the complexity associated with information decoding. The simulation results highlight the superiority of the proposed system. Compared with traditional PM systems, it demonstrates enhanced performance in terms of spectral efficiency, channel stability, and bit error rate (BER). © 2014 IEEE.

关键词： Signal modulation

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Concept, Principle, and Modeling of Driving Risk Entropy Based on Human-Vehicle-Road Coupling Model for Autonomous Vehicle

SSRN

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SSRN 2024年

作者： Gao, Hongbo Yang, Hanqing Zhu, Juping Su, Huiping Wang, Ning Xie, Liping Li, Keqiang Department of Automation University of Science and Technology of China Hefei230026 China Institute of Advanced Technology University of Science and Technology of China Hefei230088 China School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore Chongqing College of Mobile Communication Chongqing400044 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing100084 China

Driving risk entropy, based on entropy law, is an innovative concept proposed for intelligent driving systems. The concept deals with the driving risks caused by the human-vehicle-road system from the driving information obtained;however, driving risks are difficult to assess due to many influencing factors and great uncertainty. The risk entropy model of vehicles is visualized by introducing the concept of basic isotropic risk elliptic line (BIREL). Further incorporating the concept of information entropy, risk entropy models for vehicle interaction and vulnerable participants are established, and the risk entropy model for roads is developed using raster coordinates. Ultimately, a three-dimensional driving risk entropy model is constructed based on the human-vehicle-road coupling model, with appropriate weights assigned to each parameter through the DDPG algorithm. Experimental results demonstrate the effectiveness of the driving risk entropy model. © 2024, The Authors. All rights reserved.

关键词： Autonomous vehicles

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Deep Learning-Based LOS and NLOS Parameters Estimation, Tracking, and Identification

Deep Learning-Based LOS and NLOS Parameters Estimation, Trac...

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IEEE International Conference on communications in China Workshops (ICCC)

作者： Kai Chen Jun Wang Jie Yang Le Liang Chao-Kai Wen Shi Jin National Mobile Communications Research Laboratory Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing China Institute of Communications Engineering National Sun Yat-sen University Kaohsiung Taiwan

ISBN: (数字)9798350377675

ISBN: (纸本)9798350377682

Millimeter-wave (mmWave) communication systems have large bandwidths and, combined with large-scale antenna arrays and beamforming technology, facilitate higher resolution of angle and delay measurements. This, in turn, provides opportunities for integrated sensing and communication (ISAC). Accurate and reliable estimation of mmWave channel state information is crucial for ISAC. In this paper, we propose a deep learning-based method for estimating channel multipath parameters, tracking, and identifying line-of-sight (LOS) and non-line-of-sight (NLOS) paths. Specifically, we leverage a network named “you only look once (YOLO)”, a highly efficient object detection network in computer vision, to detect the angles of arrival (AOAs) and angles of departure (AODs) of multipaths from received radio frequency signals. Moreover, we use a tracking-by-detection algorithm, ByteTrack, to track the variation of each path's AOA and AOD under a mobile scenario. Thanks to these vision-based channel estimation approaches, we reveal that LOS and NLOS paths exhibit different trajectory properties, allowing us to precisely identify LOS and NLOS paths, a challenge originally in the context of ISAC. We validate the proposed estimation, tracking, and identification methods on real measurement data and demonstrate that the proposed estimation method shows better performance compared to existing methods.

关键词： Antenna measurements Computer vision Simultaneous localization and mapping Millimeter wave measurements Estimation Channel estimation Transforms Integrated sensing and communication Millimeter wave communication Antenna arrays

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Adaptive detectors with enhanced selectivity properties in the compound Gaussain clutter with generalized inverse Gaussian texture

Adaptive detectors with enhanced selectivity properties in t...

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IET International Radar Conference (IRC 2023)

作者： Zeyu Wang Zhirui Wang Xiaona Sun State Key Laboratory of Networking and Switching Technology School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing People's Republic of China Beijing Institute of Radio Measurement Beijing People's Republic of China

ISBN: (数字)9781837240982

In this paper, the problem of adaptive detection of signals in the compound Gaussian clutter when the signal mismatch occurs is discussed. The texture follows the generalized inverse Gaussian distribution which includes inverse Gaussian, inverse gamma and gamma as three special examples. To increase the mismatch rejection performance, the binary hypothesis test is modified and a fictitious signal is introduced under the null hypothesis. Two adaptive mismatch selective detectors are derived according to the maximum a posteriori test and generalized likelihood ratio test. The performance evaluation shows that the two proposed adaptive detectors have stronger mismatch rejection performance than the conventional detector.

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