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Recent Advances in Triboelectric Nanogenerators: From Technological Progress to Commercial Applications

ACS Nano 2023年第12期17卷 11087-11219页

作者： Choi, Dongwhi Lee, Younghoon Lin, Zong-Hong Cho, Sumin Kim, Miso Ao, Chi Kit Soh, Siowling Sohn, Changwan Jeong, Chang Kyu Lee, Jeongwan Lee, Minbaek Lee, Seungah Ryu, Jungho Parashar, Parag Cho, Yujang Ahn, Jaewan Kim, Il-Doo Jiang, Feng Lee, Pooi See Khandelwal, Gaurav Kim, Sang-Jae Kim, Hyun Soo Song, Hyun-Cheol Kim, Minje Nah, Junghyo Kim, Wook Menge, Habtamu Gebeyehu Park, Yong Tae Xu, Wei Hao, Jianhua Park, Hyosik Lee, Ju-Hyuck Lee, Dong-Min Kim, Sang-Woo Park, Ji Young Zhang, Haixia Zi, Yunlong Guo, Ru Cheng, Jia Yang, Ze Xie, Yannan Lee, Sangmin Chung, Jihoon Oh, Il-Kwon Kim, Ji-Seok Cheng, Tinghai Gao, Qi Cheng, Gang Gu, Guangqin Shim, Minseob Jung, Jeehoon Yun, Changwoo Zhang, Chi Liu, Guoxu Chen, Yufeng Kim, Suhan Chen, Xiangyu Hu, Jun Pu, Xiong Guo, Zi Hao Wang, Xudong Chen, Jun Xiao, Xiao Xie, Xing Jarin, Mourin Zhang, Hulin Lai, Ying-Chih He, Tianyiyi Kim, Hakjeong Park, Inkyu Ahn, Junseong Huynh, Nghia Dinh Yang, Ya Wang, Zhong Lin Baik, Jeong Min Choi, Dukhyun Kyung Hee University Gyeonggi Yongin17104 Korea Republic of Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States Department of Mechanical Engineering Soft Robotics Research Center Seoul National University Seoul08826 Korea Republic of Department of Mechanical Engineering Gachon University Seongnam13120 Korea Republic of Department of Biomedical Engineering National Taiwan University Taipei10617 Taiwan Frontier Research Center on Fundamental and Applied Sciences of Matters National Tsing Hua University Hsinchu30013 Taiwan School of Advanced Materials Science & Engineering Sungkyunkwan University Suwon16419 Korea Republic of Sungkyunkwan University 2066 Seobu-ro Gyeonggi Suwon16419 Korea Republic of Department of Chemical and Biomolecular Engineering National University of Singapore 4 Engineering Drive 4 117585 Singapore Division of Advanced Materials Engineering Jeonbuk National University 567 Baekje-daero Jeonbuk Jeonju54896 Korea Republic of Jeonbuk National University 567 Baekje-daero Jeonbuk Jeonju54896 Korea Republic of Department of Physics Inha University 100 Inha-ro Incheon22212 Korea Republic of School of Materials Science & Engineering Yeungnam University Gyeongbuk Gyeongsan38541 Korea Republic of 291 Daehak-ro Daejeon34141 Korea Republic of School of Materials Science and Engineering Nanyang Technological University 50 Nanyang Avenue 639798 Singapore Institute of Flexible Electronics Technology of Tsinghua Zhejiang Jiaxing314000 China Nanomaterials and System Lab Major of Mechatronics Engineering Faculty of Applied Energy System Jeju National University Jeju632-43 Korea Republic of School of Engineering University of Glasgow GlasgowG128QQ United Kingdom Seoul02792 Korea Republic of Department of Physics Inha University Incheon22212 Korea Republic of Suwon16419 Korea Republic of Department of

Serious climate changes and energy-related environmental problems are currently critical issues in the world. In order to reduce carbon emissions and save our environment, renewable energy harvesting technologies will serve as a key solution in the near future. Among them, triboelectric nanogenerators (TENGs), which is one of the most promising mechanical energy harvesters by means of contact electrification phenomenon, are explosively developing due to abundant wasting mechanical energy sources and a number of superior advantages in a wide availability and selection of materials, relatively simple device configurations, and low-cost processing. Significant experimental and theoretical efforts have been achieved toward understanding fundamental behaviors and a wide range of demonstrations since its report in 2012. As a result, considerable technological advancement has been exhibited and it advances the timeline of achievement in the proposed roadmap. Now, the technology has reached the stage of prototype development with verification of performance beyond the lab scale environment toward its commercialization. In this review, distinguished authors in the world worked together to summarize the state of the art in theory, materials, devices, systems, circuits, and applications in TENG fields. The great research achievements of researchers in this field around the world over the past decade are expected to play a major role in coming to fruition of unexpectedly accelerated technological advances over the next decade. © 2023 The Authors. Published by American Chemical Society

关键词： Nanogenerators

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5G entering into a new era [Guest Editorial]

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China Communications 2017年第12期14卷 iv-vi页

作者： Feifei Gao Changle Li Jun Fang Kaizhi Huang Zhi Quan Chengwen Xing Jianhua Zhang Zhongshan Zhang Liqiang Zhao Yulong Zou Department of Automation Tsinghua University Beijing China State Key Laboratory of Integrated Services Networks Xidian University University of Eletronic Science and Technology of China National Digital Switching System Engineering & Technological Research Center Zhengzhou China College of Information Engineering Shenzhen University School of Information and Electronics Beijing Institute of Technology Beijing University of Posts and Telecommunication School of Computer and Communication Engineering in the University of Science and Technology Beijing State Key Lab. of Integrated Service Networks Xidian University Nanjing University of Posts and Telecommunications (NUPT) Nanjing China

The ever increasing wireless data services, such as imaging, video, audio, multimedia, etc., have demands for the very high speed wireless communications and network, which are unfortunately a bottleneck when combining with the wireline core network. Users' are now expecting high quality of experience with low-cost devices, ubiquitous connectivity, energy efficiency, high reliability, or even ultra-low latency if a vehicle terminal is applied.

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一种可用于网络环境的模糊推理机制

一种可用于网络环境的模糊推理机制

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第19届全国计算机新科技与计算机教育学术大会

作者： ZHANG Hao 张浩 HUANG Daguang 黄大广 ZHANG Lin 张琳 School of Computer Science & Engineering Southeast UniversityNanjing 210096 东南大学计算机科学与工程学院南京210096 College of Computer China University of Mining and TechnologyXuzhou 221008 中国矿业大学计算机学院徐州221008 College of Computer Nanjing University of Posts & TelecommunicationsNanjing 210003 南京邮电大学计算机学院南京210003

网络环境的多变性以及模糊性使得安全问题已经成为研究的热点。借助模糊逻辑技术建立了基于主客观结合的模糊推理系统，深入讨论了模糊语言变量的信任等级划分，并对模糊推理系统的运行结果作出了详细的分析。

关键词：网络安全模糊推理系统语言变量信任等级

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面向开放网络的改进的风险传播算法研究

面向开放网络的改进的风险传播算法研究

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第19届全国计算机新科技与计算机教育学术大会

作者： LI Ya 李娅 ZHANG Lin 张琳 HUANG Daguang 黄大广 School of Information Science Nanjing Audit UniversityNanjing 221008 南京审计学院信息科学学院南京210029 College of Computer Nanjing University of Posts & TelecommunicationsNanjing 210003 南京邮电大学计算机学院南京210003 College of Computer China University of Mining and TechnologyXuzhou 221008 中国矿业大学计算机学院徐州221008

网络风险传播正成为安全领域研究的热点。本文对现有的风险传播算法进行了深刻的剖析，指出其在算法设计的正确性和低效性方面存在不足，通过引入风险传播路径长度限值给出了相应的改进算法，并设计了预处理过程，使算法更符合实际传播... 详细信息

网络风险传播正成为安全领域研究的热点。本文对现有的风险传播算法进行了深刻的剖析，指出其在算法设计的正确性和低效性方面存在不足，通过引入风险传播路径长度限值给出了相应的改进算法，并设计了预处理过程，使算法更符合实际传播现象。

关键词：计算机网络安全信息系统风险传播改进算法

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Multi-objective Task Scheduling Algorithm Based on Harmony Search for Grid Microservice Optimization

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Journal of Physics: Conference Series 2021年第1期1746卷

作者： Yuqing Xie Yuan Wang Ying Jiang Zirong Peng Yongli Wang Information & Telecommunication Branch State Grid Zhejiang Electric Power Corporation Hangzhou 310000 China State Grid Electric Power Research Institute Co. Ltd. Nanjing 211100 China China Realtime Database Co. Ltd. Nanjing 211100 China School of Computer Science and Technology Nanjing University of Science and Technology Nanjing 210094 China

In order to solve the multi-objective task scheduling optimization problem of data platform microservice combination, this paper proposes an improved harmony search algorithm MODRHS, which fuses the multi-objective optimization NSGA-II algorithm, and improve its elite selection strategy by a circular elimination method, and strengthens the uniformity of the non-dominated solutions at first layer and improves the algorithm's Pareto optimization ability. At the same time, it describes the mathematical expression of the Dockers model and service optimization goals of the data platform microservice scheduling. The improved harmony search algorithm is applied to practical problems. The performance test of MODRHS is carried out through standard test functions and real data sets. Compared with other classic multi-objective optimization algorithms, the convergence and diversity of the MODRHS algorithm have been effectively improved.

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Guest editorial: Wireless security challenges and counter measures for dynamic spectrum sharing

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China Communications 2021年第12期18卷 iii-vi页

作者： Yingchang Liang Yue Gao Liang Xiao Yulong Zou Guoru Ding University of Electronic Science and Technology of China China School of Computer Science and Electronic Engineering Institute for Communication Systems University of Surrey U.K. Department of Information and Communication Engineering Xiamen University Xiamen China Nanjing University of Posts and Telecommunications (NUPT) Nanjing China College of Communications Engineering PLA Army Engineering University

To meet the rapid growth of mobile communications services, the continuously upgraded wireless networks significantly increase the demand for radio spectrum resources. However, the spectrum supply is limited, thus triggering the spectrum demand-supply gap. Consequently, dynamic spectrum sharing emerges as a promising paradigm of enhancing spectrum usage, which has been widely recognized and adopted in commercial wireless standards, such as the 4G LTE, 5G NR, and so on. As part of 3GPP Release 15, operators allocate portions of the 4G LTE spectrum that they are already using to 5G NR — this means that 4G LTE and 5G NR users can coexist in the same frequency band/channel at the same time. A software upgrade makes it possible to use existing RAN to deliver 5G services to unleash the potential of artificial intelligence in mobile networks.

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Unleashing the Strengths of Unlabeled Data in Pan-cancer Abdominal Organ Quantification: The FLARE22 Challenge

arXiv

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arXiv 2023年

作者： Ma, Jun Zhang, Yao Gu, Song Ge, Cheng Ma, Shihao Young, Adamo Zhu, Cheng Meng, Kangkang Yang, Xin Huang, Ziyan Zhang, Fan Liu, Wentao Pan, YuanKe Huang, Shoujin Wang, Jiacheng Sun, Mingze Xu, Weixin Jia, Dengqiang Choi, Jae Won Alves, Natália de Wilde, Bram Koehler, Gregor Wu, Yajun Wiesenfarth, Manuel Zhu, Qiongjie Dong, Guoqiang He, Jian Wang, Bo He, Junjun Yang, Hua Yang, Huihua Huang, Bingding Lyu, Mengye Ma, Yongkang Guo, Heng Zhang, Rongguo Maier-Hein, Klaus The Department of Laboratory Medicine and Pathobiology University of Toronto Peter Munk Cardiac Centre University Health Network Vector Institute Toronto Canada Shanghai AI Laboratory Shanghai200232 China The Department of Image Reconstruction Nanjing Anke Medical Technology Co. Ltd. Nanjing211113 China Ocean University of China Qingdao266100 China The Department of Computer Science University of Toronto Peter Munk Cardiac Centre University Health Network Vector Institute Toronto Canada Tinavi Medical Technologies Co. Ltd. Beijing100192 China University of Science and Technology Beijing Beijing100083 China The School of Biomedical Engineering Health Science Center Shenzhen University Shenzhen518055 China The Department of Radiological Algorithm Fosun Aitrox Information Technology Co. Ltd. Shanghai200033 China The School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China Shenzhen Technology University Shenzhen518000 China Xiamen University Xiamen361005 China Alibaba Beijing100084 China Infervision Medical Technology Co. Ltd. Beijing100025 China Hong Kong Centre for Cerebro-cardiovascular Health Engineering 000000 Hong Kong The Department of Radiology Armed Forces Yangju Hospital Yangju11429 Korea Republic of The Department of Radiology Radboudumc Nijmegen6525XZ Netherlands The Department of Medical Image Computing German Cancer Research Center Heidelberg69120 Germany ShenZhen Yorktal DMIT LLC Shenzhen518100 China Heidelberg69120 Germany The Department of Nuclear Medicine Nanjing Drum Tower Hospital Nanjing210008 China The College of Big Data and Internet Shenzhen Technology University Shenzhen518188 China The College of Health Science and Environmental Engineering Shenzhen Technology University Shenzhen China The Manteia Technologies Co. Ltd Xiamen China The Alibaba DAMO Academy Beijing China The Peter Munk Cardiac Centre University Health Network Department of Laboratory M

Quantitative organ assessment is an essential step in automated abdominal disease diagnosis and treatment planning. Artificial intelligence (AI) has shown great potential to automatize this process. However, most existing AI algorithms rely on many expert annotations and lack a comprehensive evaluation of accuracy and efficiency in real-world multinational settings. To overcome these limitations, we organized the FLARE 2022 Challenge, the largest abdominal organ analysis challenge to date, to benchmark fast, low-resource, accurate, annotation-efficient, and generalized AI algorithms. We constructed an intercontinental and multinational dataset from more than 50 medical groups, including Computed Tomography (CT) scans with different races, diseases, phases, and manufacturers. We independently validated that a set of AI algorithms achieved a median Dice Similarity Coefficient (DSC) of 90.0% by using 50 labeled scans and 2000 unlabeled scans, which can significantly reduce annotation requirements. The best-performing algorithms successfully generalized to holdout external validation sets, achieving a median DSC of 89.5%, 90.9%, and 88.3% on North American, European, and Asian cohorts, respectively. They also enabled automatic extraction of key organ biology features, which was labor-intensive with traditional manual measurements. This opens the potential to use unlabeled data to boost performance and alleviate annotation shortages for modern AI models. © 2023, CC BY-NC-ND.

关键词： Diseases

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Enabling Cost-effective Wireless Data Collection by Piggybacking on Delivery Drones in Agriculture

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ACM Transactions on Sensor Networks 1000年

作者： Chaocan Xiang Wenhui Cheng Xiao Zheng Tao Wu Xiaochen Fan Yingjie Wang Yanlin Zhou Fu Xiao College of Computer Science Chongqing University China 1) Anhui University of Technology China 2) Institute of Artificial Intelligence Hefei Comprehensive National Science Center China National University of Defense Technology China 1) Institute for Electronics and Information Technology in Tianjin Tsinghua University China 2) Department of Electronic Engineering Tsinghua University China 3) Consulting Center for Strategic Assessment Academy of Military Science China School of Computer and Control Engineering Yantai University China School of Computer Nanjing University of Posts and Telecommunications China

Drones have drawn considerable attention as the agents in wireless data collection for agricultural applications, by virtue of their three-dimensional mobility and dominant line-of-sight communication channels. Existing works mainly exploit dedicated drones via deployment and maintenance, which is insufficient regarding resource and cost-efficiency. In contrast, leveraging existing delivery drones for the data collection on their way of delivery, called delivery drones’ piggybacking, is a promising solution. For achieving such cost-efficiency, drone scheduling inevitably stands in front, but the delivery missions involved have escalated it to a wholly different and unexplored problem. As an attempt, we first survey 514 delivery workers and conduct field experiments; noticeably, the collection cost, which mostly comes from the energy consumption of drones’ piggybacking, is determined by the decisions on package-route scheduling and data collection time distribution. Based on such findings, we build a new model that jointly optimizes these two decisions to maximize data collection amount, subject to the collection budget and delivery constraints. Further model analysis finds it a Mixed Integer Non-Linear Programming problem, which is NP-hard. The major challenge stems from interdependence entangling the two decisions. For this point, we propose Delta, a \(\frac{1}{9+\delta }\)-approximation delivery drone scheduling algorithm. The key idea is to devise an approximate collection time distribution scheme leveraging energy slicing, which transforms the complex problem with two interdependent variables into a submodular function maximization problem only with one variable. The theoretical proofs and extensive evaluations verify the effectiveness and the near-optimal performance of Delta.

关键词： Wireless Data Collection Drone’s Piggybacking Energy Consumption

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Retraction Note: Identification and prioritization of DevOps success factors using fuzzy-AHP approach

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Soft Computing 2024年第1期28卷 405-405页

作者： Akbar, Muhammad Azeem Mahmood, Sajjad Shafiq, Muhammad Alsanad, Ahmed Alsanad, Abeer Abdul-Aziz Gumaei, Abdu College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing People’s Republic of China Information and Computer Science Department King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China Research Chair of Artificial Intelligence (RCAI) Department of Information Systems College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia Information Systems Department College of Computer and Information Sciences Imam Muhammad Ibn-Saud Islamic University Riyadh Saudi Arabia

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Emergent ferromagnetism with superconductivity in Fe(Te,Se) van der Waals Josephson junctions

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Nature Communications 2023年第1期14卷 1-9页

作者： Qiu, Gang Yang, Hung-Yu Hu, Lunhui Zhang, Huairuo Chen, Chih-Yen Lyu, Yanfeng Eckberg, Christopher Deng, Peng Krylyuk, Sergiy Davydov, Albert V. Zhang, Ruixing Wang, Kang L. Department of Electrical and Computer Engineering University of California Los Angeles 90095 CA United States Department of Physics & Astronomy The University of Tennessee Knoxville Knoxville 37996 TN United States Materials Science and Engineering Division National Institute of Standards and Technology (NIST) Gaithersburg 20899 MD United States Theiss Research Inc La Jolla 92037 CA United States Department of Electrophysics National Yang Ming Chiao Tung University (NYCU) Hsinchu 30010 Taiwan School of Science Nanjing University of Posts and Telecommunications Nanjing 210023 China Fibertek Inc Herndon 20171 VA United States DEVCOM Army Research Laboratory Adelphi 20783 MD United States DEVCOM Army Research Laboratory Playa Vista Los Angeles 90094 CA United States Beijing Academy of Quantum Information Sciences Beijing 100193 China

Ferromagnetism and superconductivity are two key ingredients for topological superconductors, which can serve as building blocks of fault-tolerant quantum computers. Adversely, ferromagnetism and superconductivity are typically also two hostile orderings competing to align spins in different configurations, and thus making the material design and experimental implementation extremely challenging. A single material platform with concurrent ferromagnetism and superconductivity is actively pursued. In this paper, we fabricate van der Waals Josephson junctions made with iron-based superconductor Fe(Te,Se), and report the global device-level transport signatures of interfacial ferromagnetism emerging with superconducting states for the first time. Magnetic hysteresis in the junction resistance is observed only below the superconducting critical temperature, suggesting an inherent correlation between ferromagnetic and superconducting order parameters. The 0-π phase mixing in the Fraunhofer patterns pinpoints the ferromagnetism on the junction interface. More importantly, a stochastic field-free superconducting diode effect was observed in Josephson junction devices, with a significant diode efficiency up to 10%, which unambiguously confirms the spontaneous time-reversal symmetry breaking. Our work demonstrates a new way to search for topological superconductivity in iron-based superconductors for future high T_c fault-tolerant qubit implementations from a device perspective. © 2023, Springer Nature Limited.

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