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Retraction Note: Minimal key set of binary key-derivation tree in cloud storage

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Soft computing 2024年第2期28卷 1007-1007页

作者： Ren, Zhengwei Li, Xiaojuan Wang, Lina Xu, Shiwei Tong, Yan Tang, Jinshan School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan China School of Cyber Science and Engineering Wuhan University Wuhan China Huazhong Agricultural University Wuhan China Department of Health Administration and Policy College of Health and Human Services George Mason University Fairfax USA

Undoped Strained Ge Quantum Well with Ultrahigh Mobility Grown by Reduce Pressure Chemical Vapor Deposition

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arXiv 2022年

作者： Kong, Zhenzhen Li, Zonghu Cao, Gang Su, Jiale Zhang, Yiwen Liu, Jinbiao Liu, Jingxiong Ren, Yuhui Wei, Laiming Guo, Guoping Wu, Yuanyuan Radamson, Henry H. Li, Junfeng Wu, Zhenhua Li, Haiou Yang, Jiecheng Zhao, Chao Wang, Guilei Integrated Circuit Advanced Process R&D Center Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China School of Integrated Circuits University of Chinese Academy of Sciences Beijing100049 China CAS Key Laboratory of Quantum Information University of Science and Technology of China Hefei230026 China Hefei National Laboratory Hefei230088 China School of Advanced Manufacturing Engineering Hefei University Hefei230601 China Origin Quantum Computing Company Limited Hefei230026 China Research and Development Center of Optoelectronic Hybrid IC Guangdong Greater Bay Area Institute of Integrated Circuit and System Guangzhou510535 China Beijing Superstring Academy of Memory Technology 100176 China

We fabricate an undoped Ge quantum well under a 30 nm relaxed Ge0.8Si0.2 shallow barrier. The bottom barrier contains Ge0.8Si0.2 (650 ℃) followed by Ge0.9Si0.1 (800 ℃) such that variation of Ge content forms a sharp interface that can suppress the threading dislocation density (TDD) penetrating into the undoped Ge quantum well. The Ge0.8Si0.2 barrier introduces enough in-plane parallel strain (Ε strain -0.41%) in the Ge quantum well. The heterostructure field-effect transistors with a shallow buried channel obtain an ultrahigh two-dimensional hole gas (2DHG) mobility over 2×106 cm2/Vs and a very low percolation of 5.625 × 1010cm−2. A tunable fractional quantum Hall effect at high densities and high magnetic fields has also been observed. This approach defines strained germanium as providing the material basis for tuning the spin-orbit coupling strength for fast and coherent quantum *** Codes 81-05, 81V70 © 2022, CC BY-NC-ND.

关键词： Germanium

Spin-induced orbital frustration in a hexagonal optical lattice

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arXiv 2021年

作者： Li, Yongqiang Yuan, Jianmin Zhou, Xiaoji Li, Xiaopeng Department of Physics National University of Defense Technology Changsha410073 China Department of Physics Graduate School of China Academy of Engineering Physics Beijing100193 China State Key Laboratory of Advanced Optical Communication System and Network Department of Electronics Peking University Beijing100871 China State Key Laboratory of Surface Physics Institute of Nanoelectronics and Quantum Computing Department of Physics Fudan University Shanghai200438 China Shanghai Qi Zhi Institute AI Tower Xuhui District Shanghai200232 China

Complex lattices provide a versatile ground for fascinating quantum many-body physics. Here, we propose an exotic mechanics for generating orbital frustration in hexagonal lattices. We study two-component (pseudospin-1/2) Bose gases in p-orbital bands of two-dimensional hexagonal lattices, and find that the system exhibits previously untouched orbital frustration as a result of the interplay of spin and orbital degrees of freedom, in contrast to normal Ising-type orbital ordering of spinless porbital band bosons in two-dimensional hexagonal lattices. Based on the classification by symmetry analysis, we find the interplay of orbital frustration and strong interaction leads to exotic Mott and superfluid phases with spin-orbital intertwined orders, in spite of the complete absence of spin-orbital interaction in the Hamiltonian. Our study implies many-body correlations in a multi-orbital setting could induce rich spin-orbital intertwined physics in complex lattice structures. Copyright © 2021, The Authors. All rights reserved.

关键词： Bosons

Temperature prediction of generator carbon brush based on LSTM neural network

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Temperature prediction of generator carbon brush based on LS...

Chinese Automation Congress (CAC)

作者： Qing Zhang Tingyang Jiao Yinxing Ma Youmin Zhang Xiaohui Wu Pengyue Wu Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an China The Faculty of Computing Science The University of Alberta Edmonton Alberta Canada Concordia University Montreal Canada Huaneng Weihai Power Generation Co. Ltd Wei’hai China Xi’an Thermal Power Research Institute Co. Ltd Xi’an China

ISBN: (纸本)9781665426480

In order to improve the prediction accuracy of the carbon brush temperature trend of the generator, analyzing the operating state of the generator more accurately, and reduce other accidents like the unplanned outage caused by carbon brush failure of the generator in the power plant. A multi-step temperature prediction model based on the LSTM (Long Short-Term Memory) neural network is proposed. The data comes from real operating carbon brush temperature of Weihai Power Plant in ten days. Then the temperature prediction model is established to achieve an accurate prediction of the carbon brush temperature in the future day. The prediction error is stable within 0.4 °C. By comparing the predicted results of the BP model and Elman model, the error between the predicted results of each model and the actual temperature data is analyzed. By comparing the indicators and analyzing the actual curves, the results show that LSTM neural network has higher accuracy in predicting the temperature of generator carbon brush. This method is of reference significance for the accurate analysis of the operation state of the generator and the load analysis of the excitation system.

关键词： Analytical models Temperature distribution Brushes Neural networks Predictive models Market research Generators

CSformer: Bridging Convolution and Transformer for Compressive Sensing

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arXiv 2021年

作者： Ye, Dongjie Ni, Zhangkai Wang, Hanli Zhang, Jian Wang, Shiqi Kwong, Sam The Department of Computer Science City University of Hong Kong 999077 Hong Kong The Department of Computer Science & Technology Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai200092 China The School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Shenzhen518055 China The Peng Cheng Laboratory Shenzhen518052 China The City University of Hong Kong Shenzhen Research Institute Shenzhen518057 China

Convolution neural networks (CNNs) have succeeded in compressive image sensing. However, due to the inductive bias of locality and weight sharing, the convolution operations demonstrate the intrinsic limitations in modeling the long-range dependency. Transformer, designed initially as a sequence-to-sequence model, excels at capturing global contexts due to the self-attention-based architectures even though it may be equipped with limited localization abilities. This paper proposes CSformer, a hybrid framework that integrates the advantages of leveraging both detailed spatial information from CNN and the global context provided by transformer for enhanced representation learning. The proposed approach is an end-to-end compressive image sensing method, composed of adaptive sampling and recovery. In the sampling module, images are measured block-by-block by the learned sampling matrix. In the reconstruction stage, the measurement is projected into dual stems. One is the CNN stem for modeling the neighborhood relationships by convolution, and the other is the transformer stem for adopting global self-attention mechanism. The dual branches structure is concurrent, and the local features and global representations are fused under different resolutions to maximize the complementary of features. Furthermore, we explore a progressive strategy and window-based transformer block to reduce the parameter and computational complexity. The experimental results demonstrate the effectiveness of the dedicated transformer-based architecture for compressive sensing, which achieves superior performance compared to state-of-the-art methods on different datasets. Copyright © 2021, The Authors. All rights reserved.

关键词： Compressed sensing

An Online Market Mechanism for Edge Emergency Demand Response via Cloudlet Control

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An Online Market Mechanism for Edge Emergency Demand Respons...

IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Shutong Chen Lei Jiao Lin Wang Fangming Liu Key Laboratory of Services Computing Technology and System Ministry of Education School of Computer Science and Technology Huazhong University of Science and Technology China University of Oregon USA VU Amsterdam The Netherlands

The computing frontier is moving from centralized mega datacenters towards distributed cloudlets at the network edge. We argue that cloudlets are well-suited for participation in Emergency Demand Response (EDR) programs due to their enormous energy consumption and flexible workload distribution, while existing EDR mechanisms for clouds and colocation datacenters are not suitable for cloudlets. We propose a novel online market mechanism, EdgeEDR, to incentivize cloudlets to participate in EDR, featuring multiple cloudlet-specific designs. At a high level, we observe that cloudlet operators can dynamically switch on/off entire cloudlets to compensate for the energy reduction required by the power grid. We formulate a long-term social cost minimization problem and decompose it into a series of one-round procurement auctions. In each auction instance, we propose to let the cloudlet tenants bid with cost functions of their service quality degradation tolerance, and let the cloudlet operator choose the service quality, allocate the workload, and shut down the cloudlets. Via rigorous analysis, we exhibit that our bidding policy is individually rational and truthful; our workload distribution algorithm has near-optimal performance in each auction; and our overall online algorithm achieves a provable competitive ratio. We further confirm the performance of our mechanism through extensive trace-driven simulations.

关键词： Cloud computing Delays Switches Generators Degradation Procurement Load management

DeeperForensics challenge 2020 on real-world face forgery detection: Methods and results

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arXiv 2021年

作者： Jiang, Liming Guo, Zhengkui Wu, Wayne Liu, Zhaoyang Liu, Ziwei Loy, Chen Change Yang, Shuo Xiong, Yuanjun Xia, Wei Chen, Baoying Zhuang, Peiyu Li, Sili Chen, Shen Yao, Taiping Ding, Shouhong Li, Jilin Huang, Feiyue Cao, Liujuan Ji, Rongrong Lu, Changlei Tan, Ganchao S-Lab Nanyang Technological University Singapore Chinese University Hong Kong SenseTime Research Hong Kong Amazon Web Services. United States Shenzhen Key Laboratory of Media Information Content Security Shenzhen University China Media Analytics and Computing Lab Xiamen University China YouTu Lab Tencent Shanghai China University of Science and Technology China

This paper reports methods and results in the DeeperForensics Challenge 2020 on real-world face forgery detection. The challenge employs the DeeperForensics-1.0 dataset, one of the most extensive publicly available real-world face forgery detection datasets, with 60,000 videos constituted by a total of 17.6 million frames. The model evaluation is conducted online on a high-quality hidden test set with multiple sources and diverse distortions. A total of 115 participants registered for the competition, and 25 teams made valid submissions. We will summarize the winning solutions and present some discussions on potential research directions. Copyright © 2021, The Authors. All rights reserved.

关键词： Face recognition

Model Parameter Analysis of Cracked Photovoltaic Module under Outdoor Conditions

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Model Parameter Analysis of Cracked Photovoltaic Module unde...

2020 47th IEEE Photovoltaic Specialists Conference (PVSC)

作者： Jingwei Zhang Yongjie Liu Kun Ding Li Feng Frank U. Hamelmann Xiang Chen College of Mechanical and Electrical Engineering Hohai University Changzhou China Solar Computing Lab University of Applied Science Bielefeld Minden Germany Changzhou Key Laboratory of Photovoltaic System Integration and Production Equipment Technology Changzhou China

ISBN: (数字)9781728161150

ISBN: (纸本)9781728161167

In the recent decade, the intelligent maintenance of the PV systems is a new trend in this area. In order to facilitate the further fault prognosis of the PV module, in this paper, the model parameters of the single diode model for a glass-cracked PV module with cracked cells, which cannot be visually inspected, are extracted based on the outdoor measured current-voltage (I-V) curves. The cracks of the solar cells are also observed from the electroluminescence images. The comparison results of the I-V curves from a referenced normal PV module and the glass-cracked PV module indicate that the photocurrent and the equivalent shunt resistance of the cracked solar cells in the fault PV module decreases significantly. The extracted parameters can quantitatively describe the failure degree of the cracked solar cells. The extracted parameter can also be used to further predict the degradation trend of the fault PV module and realize fault prognosis of PV modules.

关键词： Photovoltaic cells Resistance Temperature measurement Photovoltaic systems Photoconductivity Analytical models Market research

The effects of different travel modes and travel destinations on COVID-19 transmission in global cities

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Science Bulletin 2022年第6期67卷 588-592,M0003页

作者： Rui Zhu Luc Anselin Michael Batty Mei-Po Kwan Min Chen Wei Luo Tao Cheng Che Kang Lim Paolo Santi Cheng Cheng Qiushi Gu Man Sing Wong Kai Zhang Guonian Lü Carlo Ratti Department of Land Surveying and Geo-Informatics the Hong Kong Polytechnic UniversityHong KongChina Key Laboratory of Virtual Geographic Environment(Ministry of Education) Nanjing Normal UniversityNanjing 210023China Senseable City Laboratory Future Urban Mobility IRGSingapore-MIT Alliance for Research and TechnologySingapore 138602Singapore Center for Spatial Data Science Division of the Social SciencesUniversity of ChicagoChicago IL 60637USA School of Geography Science Nanjing Normal UniversityNanjing 210023China Centre for Advanced Spatial Analysis Faculty of the Built EnvironmentUniversity College LondonLondon WC1E 6BTUK Department of Geography and Resource Management the Chinese University of Hong KongHong KongChina Institute of Space and Earth Information Science the Chinese University of Hong KongHong KongChina Department of Human Geography and Spatial Planning Utrecht UniversityUtrecht 3584 CSNetherlands State Key Laboratory Cultivation Base of Geographical Environment Evolution Nanjing 210023China Department of Geography National University of SingaporeSingapore 117570Singapore SpaceTimeLab Department of CivilEnvironmental and Geomatic EngineeringUniversity College LondonLondon WC1E 6BTUK Department of Clinical Translational Research Singapore General HospitalSingapore 169856Singapore Division of Clinical Immunology and Transfusion Medicine Department of Laboratory MedicineKarolinska InstitutetStockholm 17177Sweden Senseable City Laboratory Department of Urban Studies and PlanningMassachusetts Institute of TechnologyCambridgeMA 02139USA Istituto di Informatica e Telematica del CNR Pisa 56124Italy Department of System Science Institute of High Performance Computing Agency for ScienceTechnology and ResearchSingapore 138632Singapore Department of Tourism Studies School of HumanitiesSoutheast UniversityNanjing 210096China

The international community has made significant efforts to flatten the COVID-19 curve,including predicting transmission[1,2],executing unprecedented global lockdowns and social distancing[3,4],promoting the wearing of facemasks and social distancing measures[5],and isolating confirmed cases and contacts[6].Because of the adverse consequences of these lockdown measures[7],many cities have reopened so they can rebuild their ***,as mobility has gradually returned towards normal,imported cases from unknown sources have disrupted the recovery situation,and cities are continually at high risk of new waves of infection[8,9]since airborne transmission is the dominant transmission route[10].

关键词：多变量时间序列疫情传播出行方式谷歌公司交通出行病毒传播出行行为大城市