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IEEE International Symposium on Information (IT) in Medicine and Education, ITME

作者： Zhihao Liang Huijuan Lu Cunqian You Wenjie Zhu Li Xie Yudong Yao Key Laboratory of Electromagnetic Wave Information Technology and Metrology College of Information Engineering China Jiliang University Hangzhou Zhejiang Province China College of Information Engineering China Jiliang University Drore Information and Technology Co. LTD Hangzhou Zhejiang Province China College of Information Engineering China Jiliang University Modern Educational Technology Center Hangzhou City Zhejiang Province China College of Biomedical Engineering and Instrumentation Science Zhejiang University Institute of Advanced Digital Technologies and Instrumentation Hangzhou Zhejiang Province China Department of Electrical and Computer Engineering Stevens Institute of Technology Hoboken New Jersey USA

The COVID-19 epidemic started in 2019 and it is still important to develop intelligent and efficient diagnostic methods for the detection of COVID-19. In the task of COVID-19 X-ray image recognition, conventional deep neural networks encounter challenges in effectively discerning distinctive features within pneumonia images, resulting in limited generalization capability when confronted with novel samples. To address this issue, we introduce a novel model in this paper, denoted as PDCapsNet. The model effectively exploits Pyconv's multi-scale fusion technique and leverages the capsule network's capacity to encapsulate diverse attributes of specific entities within COVID-19 X-ray images, resulting in enhancements in both accuracy and generalization. Experimental results show that the proposed model outperforms other previous related works.

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Periodic tracking for piezo-actuated displacement stage based on disturbance rejection proportional integral derivative and repetitive control

Advanced Control for Applications: Engineering and Industria...

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advanced control for Applications: engineering and Industrial Systems 2021年第2期3卷

作者： Zhuoyun, Nie Zhaoyang, Li Bing, Zhang Gao, Zhiqiang School of Information Science and Engineering Huaqiao University Xiamen China Shanghai Institute of Technical Physics Chinese Academy of Sciences Shanghai China Department of Mechanical and Electrical Engineering Nanyang Vocational College of Agriculture Nanyang China Center for Advanced Control Technologies Cleveland State University ClevelandOH United States

Piezo-actuated displacement stage is often used to perform periodic scanning tasks, but the conventional control schemes may not satisfactorily track periodic reference signals. Our solution is a disturbance rejection proportional-integral-derivative (DR-PID)-based repetitive control (RC) scheme in which the hysteresis nonlinearity with the same period of reference input can be well suppressed by RC law. Stability criterions for the closed-loop system are developed based on small-gain theorem. A simple and effective design algorithm is obtained based on the stability conditions, such that DR-PID and RC can be designed separately. Finally, the validation and superiority of the proposed method are demonstrated by simulation studies. © 2021 John Wiley & Sons, Ltd.

关键词： Disturbance rejection

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Multimodal Information-Based Broad and Deep Learning Model for Emotion Understanding

Multimodal Information-Based Broad and Deep Learning Model f...

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第40届中国控制会议

作者： Min Li Luefeng Chen Min Wu Witold Pedrycz Kaoru Hirota School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Department of Electrical and Computer Engineering University of Alberta Tokyo Institute of Technology

Multimodal information-based broad and deep learning model（MIBDL） for emotion understanding is proposed, in which facial expression and body gesture are used to achieve emotional states recognition for emotion understanding. It aims to understand coexistence multimodal information in human-robot interaction by using different processing methods of deep network and broad network, which obtains the features of depth and width dimensions. Moreover, random mapping in the initial broad learning network could cause information loss and its shallow layer network is difficult to cope with complex tasks. To address this problem, we use principal component analysis to generate the nodes of the broad learning, and the stacked broad learning network is adapted to make it easier for the existing broad learning networks to cope with complex tasks by creating deep variations of the existing network. To verify the effectiveness of the proposal, experiments completed on benchmark database of spontaneous emotion expressions are developed, and experimental results show that the proposal outperforms the state-of-theart methods. According to the simulation experiments on the FABO database, by using the proposed method, the multimodal recognition rate is 17,54%, 1.24%, and 0.23% higher than those of the temporal normalized motion and appearance features（TN）,the multi-channel CNN（MCCNN）, and the hierarchical classification fusion strategy（HCFS）, respectively.

关键词： Convolution neural network broad learning emotion understanding facial expression body gesture

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NTIRE 2023 Challenge on Efficient Super-Resolution: Methods and Results

NTIRE 2023 Challenge on Efficient Super-Resolution: Methods ...

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2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Li, Yawei Zhang, Yulun Timofte, Radu Van Gool, Luc Yu, Lei Li, Youwei Li, Xinpeng Jiang, Ting Wu, Qi Han, Mingyan Lin, Wenjie Jiang, Chengzhi Luo, Jinting Fan, Haoqiang Liu, Shuaicheng Wang, Yucong Cai, Minjie Li, Mingxi Zhang, Yuhang Fan, Xian-Jun Sheng, Yankai Mao, Yanyu Zhang, Nihao Wang, Qian Zheng, Mingjun Sun, Long Pan, Jinshan Dong, Jiangxin Tang, Jinhui Yang, Zhongbao Wang, Yan Pan, Erlin Cai, Qixuan Dai, Xinan Zhussip, Magauiya Kalyazin, Nikolay Vyal, Dmitry Zou, Xueyi Yan, Youliang Chung, Heaseo Zhang, Jin Yu, Gaocheng Zhang, Feng Wang, Hongbin Liao, Bohao Du, Zhibo Wu, Yu-Liang Shi, Gege Peng, Long Wang, Yang Cao, Yang Zha, Zhengjun Huang, Zhi-Kai Chen, Yi-Chung Chiang, Yuan-Chun Yang, Hao-Hsiang Chen, Wei-Ting Chang, Hua-En Chen, I-Hsiang Hsieh, Chia-Hsuan Kuo, Sy-Yen Liu, Xin Pan, Jiahao Yu, Hongyuan Yu, Weichen Ge, Lin Dong, Jiahua Zou, Yajun Wu, Zhuoyuan Han, Binnan Zhang, Xiaolin Zhang, Heng Yin, Xuanwu Zuo, Kunlong Deng, Weijian Yuan, Hongjie Lu, Zengtong Ouyang, Mingyu Ma, Wenzhuo Liu, Nian Zheng, Hanyou Zhang, Yuantong Zhang, Junxi Chen, Zhenzhong Gendy, Garas Sabor, Nabil Hou, Jingchao He, Guanghui Zhu, Yurui Wang, Xi Fu, Xueyang Zha, Zheng-Jun Yin, Daheng Liu, Mengyang Chen, Baijun Li, Ao Luo, Lei Jin, Kangjun Zhu, Ce Zhang, Xiaoming Xie, Chengxing Li, Linze Meng, Haiteng Zhang, Tianlin Li, Tianrui Zhao, Xiaole Zhang, Zhao Li, Baiang Zheng, Huan Zhao, Suiyi Gao, Yangcheng Ren, Jiahuan Hu, Kang Shi, Jingpeng Wu, Zhijian Huang, Dingjiang Zhu, Jinchen Li, Hui Xv, Qianru Liu, Tianle Weng, Shizhuang Wu, Gang Jiang, Junpeng Liu, Xianming Jiang, Junjun Zhang, Mingjian Hu, Jing Wu, Chengxu Fan, Qinrui Feng, Chengming Luo, Ziwei Hu, Shu Lyu, Siwei Wu, Xi Wang, Xin Computer Vision Lab ETH Zurich Switzerland Computer Vision Lab University of Würzburg Germany Megvii Technology China MicroBT China College of Computer Science and Electronic Engineering Hunan University China Attrsense Xian University of Posts and Telecommunications Xi'an China National Engineering Laboratory for Cyber Event Warning and Control Technologies China Nanjing University of Science and Technology China Nankai University China University of Electronic Science and Technology of China China Tianjin University China Noah's Ark Lab Huawei Technologies McMaster University Canada Espresomedia Korea Republic of AntGroup China University of Science and Technology of China China Department of Electrical Engineering National Taiwan University Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan Graduate Institute of Electronics Engineering National Taiwan University Taiwan ServiceNow United States China Mobile Research Institute China Chongqing University of Technology China Multimedia Department Xiaomi Inc. China Institute of Automation Chinese Academy of Sciences China Shenyang Institute of Automation Chinese Academy of Sciences China School of Information and Communication Engineering Communication University of China China Smart Classroom Division Ruijie Networks Co. Ltd. China School of Remote Sensing and Information Engineering Wuhan University China Micro-Nano Electronics Department Shanghai Jiao Tong University Shanghai200240 China Electrical Engineering Department Faculty of Engineering Assiut University Assiut71516 Egypt Southeast University China University of Electronic Science and Technology of China Chengdu China Chongqing University of Posts and Telecommunications Chongqing China Information Technology Co. Ltd Hangzhou China Southwest Jiaotong University China National Space Science Center Chinese Academy of Science China Hefei University of Technology Hefei China Anhui University China Fried Ric

ISBN: (纸本)9798350302493

This paper reviews the NTIRE 2023 challenge on efficient single-image super-resolution with a focus on the proposed solutions and results. The aim of this challenge is to devise a network that reduces one or several aspects such as runtime, parameters, FLOPs, activations, memory footprint, and depth of RFDN while at least maintaining the PSNR of 29.00dB on DIV2K validation datasets. The challenge had 272 registered participants, and 35 teams made valid submissions. They gauge the state-of-the-art for efficient single-image super-resolution. © 2023 IEEE.

关键词： Optical resolving power

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Investigation of Conditions for Non-degeneracy and Normality in control Problems with Equality and Inequality State Constraints

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IFAC-PapersOnLine 2020年第2期53卷 6869-6874页

作者： Aram Arutyunov Dmitry Karamzin Fernando L. Pereira Institute of Control Sciences of the Russian Academy of Science Moscow Russia Federal Research Center “Computer Science and Control” of the Russian Academy of Science Moscow Russia Research Center for Systems and Technologies (SYSTEC) Electrical and Computer Engineering Department Faculty of Engineering University of Porto 4200-465 Portugal

This work aims to investigate conditions for normality and non-degeneracy of the maximum principle for general state-constrained optimal control problems in which the state constraints are given by equalities and inequalities. Non-degeneracy is proved under a regularity condition formulated in terms of the limiting normal cone to the feasible control set. The same regularity condition implies normality of the maximum principle if one of the end-points is free.

关键词： Optimal control maximum principle state constraints

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Hydrogen iodide (HI) neutral beam etching characteristics of InGaN and GaN for micro-LED fabrication

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Nanotechnology 2023年第36期34卷 365302-365302页

作者： Ohori, Daisuke Ishihara, Takahiro Wang, Xuelun Endo, Kazuhiko Hsieh, Tsou-Hwa Li, Yiming Natori, Nobuhiro Matsui, Kazuma Samukawa, Seiji Institute of Fluid Science Tohoku University 2-1-1 Katahira Aoba-ku Sendai980-8577 Japan Furo-cho Chikusa-ku Nagoya464-8601 Japan Institute of Materials and Systems for Sustainability Nagoya University Furo-cho Chikusa-ku Nagoya464-8601 Japan Institute of Communications Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electronics and Electrical Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Center for mmWave Smart Radar System and Technologies National Chiao Tung University Hsinchu300 Taiwan Advanced Institute for Materials Research Tohoku University 2-1-1 Katahira Aoba-ku Sendai980-8577 Japan Resonac Corporation 5-1 Ohgimachi Kawasaki-ku Kanagawa Kawasaki210-0867 Japan

We investigated the etching characteristics of hydrogen iodide (HI) neutral beam etching (NBE) of GaN and InGaN and compared with Cl2 NBE. We showed the advantages of HI NBE versus Cl2 NBE, namely: higher InGaN etch rate, better surface smoothness, and significantly reduced etching residues. Moreover, HI NBE was suppressed of yellow luminescence compared with Cl2 plasma. InCl x is a product of Cl2 NBE. It does not evaporate and remains on the surface as a residue, resulting in a low InGaN etching rate. We found that HI NBE has a higher reactivity with In resulting in InGaN etch rates up to 6.3 nm min−1, and low activation energy for InGaN of approximately 0.015 eV, and a thinner reaction layer than Cl2 NBE due to high volatility of In-I compounds. HI NBE resulted in smoother etching surface with a root mean square average (rms) of 2.9 nm of HI NBE than Cl2 NBE (rms: 4.3 nm) with controlled etching residue. Moreover, the defect generation was suppressed in HI NBE compared to Cl2 plasma, as indicated by lower yellow luminescence intensity increase after etching. Therefore, HI NBE is potentially useful for high throughput fabrication of μLEDs. © 2023 The Author(s). Published by IOP Publishing Ltd.

关键词： Etching

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Characterization of State-Preparation Uncertainty in Quantum Key Distribution

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Physical Review Applied 2023年第1期19卷 014048-014048页

作者： Anqi Huang Akihiro Mizutani Hoi-Kwong Lo Vadim Makarov Kiyoshi Tamaki Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha 410073 People’s Republic of China Graduate School of Engineering Science Osaka University Toyonaka Osaka 560-8531 Japan Department of Electrical & Computer Engineering and Department of Physics Centre for Quantum Information and Quantum Control (CQIQC) University of Toronto Toronto Ontario M5S 3G4 Canada Department of Physics University of Hong Kong Pokfulam Hong Kong Quantum Bridge Technologies Inc. 100 College Street Toronto Ontario M5G 1L5 Canada Russian Quantum Center Skolkovo Moscow 121205 Russia Shanghai Branch National Laboratory for Physical Sciences at Microscale and CAS Center for Excellence in Quantum Information University of Science and Technology of China Shanghai 201315 People’s Republic of China NTI Center for Quantum Communications National University of Science and Technology MISiS Moscow 119049 Russia Faculty of Engineering University of Toyama Gofuku 3190 Toyama 930-8555 Japan

To achieve secure quantum key distribution, all imperfections in the source unit must be incorporated in a security proof and measured in the lab. Here we perform a proof-of-principle demonstration of the experimental techniques for characterizing the source phase and intensity fluctuation in commercial quantum key distribution systems. When we apply the measured phase-fluctuation intervals to the security proof that takes into account fluctuations in the state preparation, it predicts a key distribution distance of over 100km of fiber. The measured intensity fluctuation intervals are, however, so large that the proof predicts zero key, indicating a source improvement may be needed. Our characterization methods pave the way for a future certification standard.

关键词： Fluctuations & noise Optical quantum information processing Quantum cryptography Quantum engineering Quantum state engineering

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Dipole-matter interactions governed by the asymmetry of Maxwell equations

arXiv

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arXiv 2023年

作者： Zhong, Yuhan Wang, Chan Bian, Chenxu Chen, Xuhuinan Chen, Jialin Zhu, Xingjian Hu, Hao Low, Tony Chen, Hongsheng Zhang, Baile Lin, Xiao Interdisciplinary Center for Quantum Information State Key Laboratory of Extreme Photonics and Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China International Joint Innovation Center Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang The Electromagnetics Academy at Zhejiang University Zhejiang University Haining314400 China Jinhua Institute of Zhejiang University Zhejiang University Jinhua321099 China Department of Electrical and Computer Engineering Technion-Israel Institute of Technology Haifa32000 Israel School of Physics Zhejiang University Hangzhou310027 China School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States Department of Physics University of Minnesota MinneapolisMN55455 United States Shaoxing Institute of Zhejiang University Zhejiang University Shaoxing312000 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore637371 Singapore Centre for Disruptive Photonic Technologies Nanyang Technological University Singapore637371 Singapore

Directionally molding the near-field and far-field radiation lies at the heart of nanophotonics and is crucial for applications such as on-chip information processing and chiral quantum networks. The most fundamental model for radiating structures is a dipolar source located inside a homogeneous matter. However, the influence of matter on the directionality of dipolar radiation is oftentimes overlooked, especially for the near-field radiation. We show that the dipole-matter interaction is intrinsically asymmetric and does not fulfill the duality principle, originating from the inherent asymmetry of Maxwell’s equations, i.e., electric charge and current are ubiquitous but their magnetic counterparts are non-existent to elusive. Moreover, we find that the asymmetric dipole-matter interaction could offer an enticing route to reshape the directionality of not only the near-field radiation but also the far-field radiation. As an example, both the near-field and far-field radiation directionality of Huygens dipole (located close to a dielectric-metal interface) would be reversed, if the dipolar position is changed from the dielectric region to the metal region. © 2023, CC BY.

关键词： Maxwell equations

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224-Gb/s 16QAM SV-DD Transmission Using Pilot-Assisted Polarization Recovery with Integrated Receiver

224-Gb/s 16QAM SV-DD Transmission Using Pilot-Assisted Polar...

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2021 Optical Fiber Communications Conference and Exhibition, OFC 2021

作者： Zhang, Sen Lu, Liwang Fan, Linsheng Chen, Bin Zhang, Tingting Zuo, Tianjian Liu, Lei Tang, Jin Zeng, Li Chen, Pengxin Huo, Jiahao Zhou, Xian Tao Lau, Alan Pak Lu, Chao Liu, Liu Guo, Changjian Network Technology Laboratory Huawei Technologies Co. Ltd. Shenzhen518129 China Guangdong Provincial Key Laboratory of Optical Information Materials and Technology South China Academy of Advanced Optoelectronics South China Normal University Guangzhou510006 China State Key Laboratory for Modern Optical Instrumentation College of Optical Science and Engineering Centre for Optical and Electromagnetic Research International Research Center for Advanced Photonics Zhejiang University Hangzhou310058 China BandP Laboratory Huawei Technologies Co. Ltd. Shenzhen518129 China School of Computer and Communication Engineering Beijing University of Science and Technology Beijing China Department of Electrical Engineering Hong Kong Polytechnic University Hong Kong Hong Kong Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong Hong Kong Hong Kong Polytechnic University Shenzhen Research Institute Shenzhen518057 China

We propose and experimentally demonstrate a low-complexity pilot-assisted analytical method for polarization demultiplexing in SV-DD systems, achieving a 224-Gb/s 16QAM transmission over 40-km SSMF and can tolerate up... 详细信息

ISBN: (纸本)9781943580866

关键词： Quadrature amplitude modulation

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Overview of Ancillary Services in the Nigerian Power Sector

Overview of Ancillary Services in the Nigerian Power Sector

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Multidisciplinary engineering and Applied Science (ICMEAS), International Conference on

作者： Bemdoo Saka Suleiman U. Hussein Biliaminu A. Ishola Yekini S. Mohammed Nanen D. Hembe Umar M. Mustapha Sadiq Thomas Dept. of Electrical/Electronics Eng. Nile University of Nigeria Abuja Nigeria Centre for Satellite Tech. Development Nat. Space Research and Dev. Agency Abuja Nigeria National Control Center Transmission Company of Nigeria Osogbo Abuja Dept. of Electrical/Electronics Eng. Federal Polytechnic Nasarawa Nasarawa Nigeria Department of Geography Nasarawa State University Nasarawa Nigeria Advanced UAV Laboratory Nat. Space Research and Dev. Agency Abuja Nigeria Dept. of Computer Engineering Nile University of Nigeria Abuja Nigeria

ISBN: (数字)9798350358834

ISBN: (纸本)9798350358841

An overview of the ancillary services in the Nigerian power sector is provided in this work. These services are essential in the power system because they are additional services required by the grid during critical times to enable the power grid to operate in a stable, safe, and reliable manner. The ancillary services provided as stipulated in the Grid Code are black start, frequency control, operating reserves, and voltage control. The System Operator procures the relevant ancillary service depending on the requirement of the grid at a particular time. The paper further presents some ways of improving the viability of ancillary services for the energy grid of Nigeria. These include making incentives more attractive for suppliers of ancillary services, utilizing more hydroelectric power plants for generation and load balancing, integrating distributed generation to provide support to the reactive power, and making necessary investments in the grid.

关键词： Codes Hydroelectric power generation Load management Power system reliability Reliability Voltage control Investment

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