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An Algorithm for Detecting Ice Cloud at Different Altitudes by Combining Dual CrIS Full Spectrum Resolution CO2 Channels

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Journal of Tropical Meteorology 2020年第3期26卷 300-310页

作者： WANG Li-wen ZHENG You-fei TIAN Miao XU Jing-xin Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration Nanjing University of Information Science&TechnologyNanjing 210044 China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science&TechnologyNanjing 210044China Information Engineering Department School of Information and Communication EngineeringUniversity of Electronic Science and Technology of ChinaChengdu 611731 China State Environmental Protection Key Laboratory of Atmospheric Physical Modeling and Pollution Control State Power Environmental Protection Research InstituteNanjing 210031 China

Using infrared sensors to detect ice clouds in different atmospheric layers is still a *** different scattering and absorption properties of longwave and shortwave infrared channels can be utilized to fulfill this *** this study,the release of Suomi-NPP Cross-track Infrared Sounder(Cr IS)full spectrum resolution is used to select and pair channels from longwave(~15μm)and shortwave(~4.3μm)CO2 absorption bands under stricter conditions,so as to better detect ice ***,the differences of the weighting function peaks and cloud insensitive level altitudes of the paired channels are both within 50 h Pa so that the variances due to atmospheric conditions can be *** training data of clear sky are determined by Visible Infrared Imaging Radiometer Suite(VIIRS)cloud mask product and used to find the linear relationship between the paired longwave and shortwave CO2 absorption *** the linear relationship,the so-called cloud emission and scattering index(CESI)is derived to detect ice *** clearly captures the center and the ice cloud features of the Super Typhoon Hato located above 415 h ***,the CESI distributions agree with cloud top pressure from the VIIRS in both daytime and nighttime in different atmospheric layers.

关键词： Cross-track Infrared Sounder Full Spectral Resolution(CrIS FSR) ice cloud detection dual CO2 absorption bands

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Robust Interference Cancellation Beamforming Based on Signal Covariance Matrix Reconstruction

Robust Interference Cancellation Beamforming Based on Signal...

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IEEE International Conference on Signal and Image Processing (ICSIP)

作者： Yang Yang Yi Yang Ling Zhang Sultana Rejina Jie Zhuang State Grid Xin Jiang Company Limited Electric Power Research Institute University of Electronic Science and Technology of China (UESTC) Chengdu China School of Information and Communication Engineering University of Electronic Science and Technology of China (UESTC) Chengdu China Precision Measurement Radar System Technology Key Laboratory of Sichuan Province Chengdu China

ISBN: (纸本)9781665446006

As an important branch of array signal processing, robust adaptive beamforming (RAB) has been widely used in many fields. In the conventional robust adaptive beamformers, a common problem is that the estimated manifold vector of the signal of interest (SOI) may converge to the interference subspace. By using the data dependent constraints, such problem can be mitigated. In this paper, first we reconstruct the covariance matrices for the desired signal. Then a novel RAB is proposed in which the data dependent constraints are formed on the basis of the reconstructed signal covariance matrices. Moreover, the optimal solution to the proposed RAB can be found by the Lagrange multiplier methodology and the semi-definite generalized eigen- decomposition. Simulation results demonstrate the effectiveness of our proposed RAB.

关键词： Manifolds Degradation Interference cancellation Array signal processing Simulation Conferences Parallel processing

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Time-Domain-Multiplexed measurement-Based Quantum Operations with 25-MHz Clock Frequency

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Physical Review Applied 2021年第3期16卷 034005-034005页

作者： Warit Asavanant Baramee Charoensombutamon Shota Yokoyama Takeru Ebihara Tomohiro Nakamura Rafael N. Alexander Mamoru Endo Jun-ichi Yoshikawa Nicolas C. Menicucci Hidehiro Yonezawa Akira Furusawa Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-8656 Japan Centre for Quantum Computation and Communication Technology School of Engineering and Information Technology University of New South Wales Canberra Australian Capital Territory 2600 Australia Center for Quantum Information and Control Department of Physics and Astronomy University of New Mexico Albuquerque New Mexico 87131 USA Centre for Quantum Computation and Communication Technology School of Science RMIT University Melbourne Victoria 3001 Australia Optical Quantum Computing Research Team RIKEN Center for Quantum Computing 2-1 Hirosawa Wako Saitama 351-0198 Japan

Continuous-variable optical quantum computation has seen much progress in recent years. In particular, cluster states—the universal resource for measurement-based quantum computation—have been realized in a scalable fashion using the time-domain multiplexing method. To utilize the cluster states in actual quantum computation, the measurement bases need to be programmed according to the desired computation. In addition, as the information is encoded in time in the time-domain multiplexing method, the measurement bases must be dynamically changed in time to fully utilize the large-scale cluster states. Here we report demonstrations of quantum operations using time-domain-multiplexed cluster states with a clock frequency of 25 MHz. This is achieved by our combining the cluster-state-generation setup with the setup to change the measurement basis in the time domain. We also formulate a method to evaluate and verify continuous-variable operations where the quantum entanglements in the cluster states are utilized. Therefore, we demonstrate the implementation of quantum operations on scalable continuous-variable cluster-state architectures. The results in this work are compatible with the developing nonlinear feedforward and non-Gaussian state generation technology, which brings the realization of the large-scale fault-tolerant universal optical quantum computer closer to reality.

关键词： Entanglement detection measurement-based quantum computing Optical quantum information processing Quantum computation Quantum gates Quantum information processing with continuous variables Quantum teleportation Homodyne & heterodyne detection

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Discrete-Phase Waveform Design to Quadratic Optimization via an ADPM Framework with Convergence Guarantee

Discrete-Phase Waveform Design to Quadratic Optimization via...

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Sensor Array and Multichannel Signal Processing Workshop

作者： Xianxiang Yu Guolong Cui Zhenghong Zhang Lin Zhou Jing Yang Lingjiang Kong School of Information and Communication Engineering University of Electronic Science and Technology of China Science and Technology on Electronic Information Control Laboratory Chengdu China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

This paper considers a quadratic optimization problem in radar discrete-phase waveform design under similarity and constant modulus constraints. A computationally efficient iterative algorithm based on the Alternating Direction Penalty Method (ADPM) framework is proposed. In each iteration, it converts the considered problem into two subproblems with closed-form solutions via an introduced auxiliary variable, while locally increasing the penalty factor involved in the ADPM framework. The proposed algorithm is ensured to converge for any initialization under some mild conditions and avoids the non-convergence problem of the Alternating Direction Method of Multipliers (ADMM) when handling the NP-hard problems. Finally, numerical simulations demonstrate that the proposed algorithm can outperform their counterparts by providing better objective values.

关键词： Phased arrays NP-hard problem Signal processing algorithms Radar Numerical simulation Convex functions Iterative methods

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Energy-saving Strategy for Edge Computing by Collaborative Processing Tasks on Base Stations

Energy-saving Strategy for Edge Computing by Collaborative P...

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International Conference on Mobile Ad-hoc and Sensor Networks, MSN

作者： Zhongjun Ma Zhenchun Wei Wenjie Zhang Zengwei Lyu Junyi Xu Benhong Zhang School of Computer Science and Information Engineering Hefei University of Technology Hefei China Engineering Research Center of Safety Critical Industrial Measurement and Control Technology Ministry of Education China

ISBN: (数字)9781728199160

ISBN: (纸本)9781728192369

Mobile Edge Computing (MEC) can significantly save the energy consumption of small-cell base stations(SBSs) by using Dynamic Voltage Scaling (DVS) technology. In this paper, we study how to reduce energy consumption of SBSs by using DVS technology. We propose a scheme to divide base station groups in wireless MEC network, and SBSs in the same base station group collaboratively process tasks. For cooperating tasks in a base station group, we propose a task-offloading strategy, which can effectively reduce the energy consumption of the base station groups. We use Task-offloading Decision Algorithm (TDA) to decide the number of task fragments allocated to each SBSs in the base station group. For processing task fragments in the task queue of SBSs, we propose a computing resource allocation scheme, and we can get the processing time of every task fragments in the task queue by Task Fragments Processing Algorithm (TFPA). Experimental results show that the task-offloading strategy and computing source allocation scheme can reduce the energy consumption by 30%-40% in a cellular network composed of 100 base stations.

关键词： Base stations Energy consumption Collaboration Resource management Task analysis Voltage control Edge computing

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Mainlobe Jamming Suppression Via Independent Component Analysis for Polarimetric SIMO Radar

Mainlobe Jamming Suppression Via Independent Component Analy...

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Sensor Array and Multichannel Signal Processing Workshop

作者： Mengmeng Ge Guolong Cui Zhenghong Zhang Lin Zhou Xianxiang Yu Feng Yang Lingjiang Kong School of Information and Communication Engineering University of Electronic Science and Technology of China Science and Technology on Electronic Information Control Laboratory Chengdu China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

The presence of mainlobe jamming will significantly reduce the radar detection capabilities. Conventional independent component analysis (ICA)-based methods will suffer from the ineffectiveness when the angle of the target is same as that of the jammer. In this paper, exploring polarization characteristics, we propose an approach based on ICA for polarimetric SIMO (P-SIMO) radar to resist mainlobe jamming. Specifically, the signal model of P-SIMO radar accounting for the target and jamming signals is derived. Then, the approach based on ICA is utilized to separate the target component and jamming component while achieving the mainlobe jamming suppression. Finally, the effectiveness and capacities of proposed method are demonstrated by simulations, and the results show that the proposed method outperforms conventional ICA-based method.

关键词： Radar detection Radar Independent component analysis Resists Numerical simulation Radar polarimetry Radar signal processing

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Tumor Detection, Segmentation and Classification Challenge on Automated 3D Breast Ultrasound: The TDSC-ABUS Challenge

arXiv

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arXiv 2025年

作者： Luo, Gongning Xu, Mingwang Chen, Hongyu Liang, Xinjie Tao, Xing Ni, Dong Jeong, Hyunsu Kim, Chulhong Stock, Raphael Baumgartner, Michael Kirchhoff, Yannick Rokuss, Maximilian Maier-Hein, Klaus Yang, Zhikai Fan, Tianyu Boutry, Nicolas Tereshchenko, Dmitry Moine, Arthur Charmetant, Maximilien Sauer, Jan Du, Hao Bai, Xiang-Hui Raikar, Vipul Pai Montoya-Del-Angel, Ricardo Martí, Robert Luna, Miguel Lee, Dongmin Qayyum, Abdul Mazher, Moona Guo, Qihui Wang, Changyan Awasthi, Navchetan Zhao, Qiaochu Wang, Wei Wang, Kuanquan Wang, Qiucheng Dong, Suyu School of Computer Science and Technology Harbin Institute of Technology Harbin150001 China Department of Mathematics Faculty of Science National University of Singapore Singapore National-Regional Key Technology Engineering Laboratory for Medical Ultrasound School of Biomedical Engineering Shenzhen University Medical School Shenzhen University Shenzhen China Laboratory Shenzhen University Shenzhen China School of Biomedical Engineering and Informatics Nanjing Medical University Nanjing China Pohang Korea Republic of Heidelberg Division of Medical Image Computing Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Germany Heidelberg Germany HIDSS4Health - Helmholtz Information and Data Science School for Health Karlsruhe Heidelberg Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Germany Department of Biomedical Engineering and Health KTH Royal Institute of Technology Stockholm Sweden France FathomX Singapore Saw Swee Hock School of Public Health National University of Singapore Singapore Philips Research University of Girona Spain Department of Robotics and Mechatronics Engineering DGIST Korea Republic of Department of Interdisciplinary Studies of Artificial Intelligence DGIST Korea Republic of National Heart and Lung Institute Faculty of Medicine Imperial College London London United Kingdom Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom Lab School of Communication and Information Engineering Shanghai University Shanghai China Faculty of Science Mathematics and Computer Science Informatics Institute University of Amsterdam Amsterdam1090 GH Netherlands Department of Biomedical Engineering and Physics Amsterdam UMC Amsterdam1081 HV Netherlands Xi’an Jiaotong-Liverpool University China Department of Ultrasound Harbin Medical University Cancer Hospital No. 150 Haping Road Nangang

Breast cancer is one of the most common causes of death among women worldwide. Early detection helps in reducing the number of deaths. Automated 3D Breast Ultrasound (ABUS) is a newer approach for breast screening, which has many advantages over handheld mammography such as safety, speed, and higher detection rate of breast cancer. Tumor detection, segmentation, and classification are key components in the analysis of medical images, especially challenging in the context of 3D ABUS due to the significant variability in tumor size and shape, unclear tumor boundaries, and a low signal-to-noise ratio. The lack of publicly accessible, well-labeled ABUS datasets further hinders the advancement of systems for breast tumor analysis. Addressing this gap, we have organized the inaugural Tumor Detection, Segmentation, and Classification Challenge on Automated 3D Breast Ultrasound 2023 (TDSC-ABUS2023). This initiative aims to spearhead research in this field and create a definitive benchmark for tasks associated with 3D ABUS image analysis. In this paper, we summarize the top-performing algorithms from the challenge and provide critical analysis for ABUS image examination. We offer the TDSC-ABUS challenge as an open-access platform at https://***/ to benchmark and inspire future developments in1algorithmic research. © 2025, CC BY.

关键词： Image segmentation

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The role of input imaging combination and ADC threshold on segmentation of acute ischemic stroke lesion using U-Net

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European Radiology 2023年第9期33卷 6157-6167页

作者： Li, Ya-Hui Lin, Shao-Chieh Chung, Hsiao-Wen Chang, Chia-Ching Peng, Hsu-Hsia Huang, Teng-Yi Shen, Wu-Chung Tsai, Chon-Haw Lo, Yu-Chien Lee, Tung-Yang Juan, Cheng-Hsuan Juan, Cheng-En Chang, Hing-Chiu Liu, Yi-Jui Juan, Chun-Jung Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital No. 199 Sec. 1 Xinglong Rd. Zhubei City Hsinchu County 302 Hsinchu Taiwan Ph.D. Program in Electrical and Communication Engineering Feng Chia University Taichung Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Department of Management Science National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biomedical Engineering and Environmental Sciences National Tsing Hua University Hsinchu Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Radiology School of Medicine College of Medicine China Medical University Taichung Taiwan Department of Medical Imaging Medical University Hospital Taichung Taiwan Department of Neurology China Medical University Hospital Taichung Taiwan Cheng Ching Hospital Taichung Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Department of Automatic Control Engineering Feng Chia University No. 100 Wenhwa Rd. Seatwen Taichung 40724 Taiwan Department of Biomedical Engineering The Chinese University of Hong Kong ERB1112 11/F William M.W. Mong Engineering Building N.T Shatin Hong Kong Multi-Scale Medical Robotics Center The Chinese University of Hong Kong N.T Shatin Hong Kong Department of Biomedical Engineering National Defense Medical Center Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

Background: To evaluate the effect of the weighting of input imaging combo and ADC threshold on the performance of the U-Net and to find an optimized input imaging combo and ADC threshold in segmenting acute ischemic stroke (AIS) lesion. Methods: This study retrospectively enrolled a total of 212 patients having AIS. Four combos, including ADC-ADC-ADC (AAA), DWI-ADC-ADC (DAA), DWI-DWI-ADC (DDA), and DWI-DWI-DWI (DDD), were used as input images, respectively. Three ADC thresholds including 0.6, 0.8 and 1.8 × 10^–3 mm²/s were applied. Dice similarity coefficient (DSC) was used to evaluate the segmentation performance of U-Nets. Nonparametric Kruskal–Wallis test with Tukey–Kramer post-hoc tests were used for comparison. A p <.05 was considered statistically significant. Results: The DSC significantly varied among different combos of images and different ADC thresholds. Hybrid U-Nets outperformed uniform U-Nets at ADC thresholds of 0.6 × 10^–3 mm²/s and 0.8 × 10^–3 mm²/s (p <.001). The U-Net with imaging combo of DDD had segmentation performance similar to hybrid U-Nets at an ADC threshold of 1.8 × 10^–3 mm²/s (p =.062 to 1). The U-Net using the imaging combo of DAA at the ADC threshold of 0.6 × 10^–3 mm²/s achieved the highest DSC in the segmentation of AIS lesion. Conclusions: The segmentation performance of U-Net for AIS varies among the input imaging combos and ADC thresholds. The U-Net is optimized by choosing the imaging combo of DAA at an ADC threshold of 0.6 × 10^–3 mm²/s in segmentating AIS lesion with highest DSC. Key Points: • Segmentation performance of U-Net for AIS differs among input imaging combos. • Segmentation performance of U-Net for AIS differs among ADC thresholds. • U-Net is optimized using DAA with ADC = 0.6 × 10^–3mm²/s. © 2023, The Author(s), under exclusive licence to European Society of Radiology.

关键词： Deep Learning Diffusion Magnetic Resonance Imaging Ischemic Stroke Neural Networks, Computer Retrospective Study

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The Study of Pt Isolated Single Atoms Assistant for the Hydrodeoxygenation of Phenol Under Mild Conditions

SSRN

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SSRN 2022年

作者： Li, Xu Ma, Longlong Yan, Long Liu, Ziyue Liao, Yuhe Department of Thermal Science and Energy Engineering University of Science and Technology of China Hefei230026 China Key Laboratory of Energy Thermal Conversion and Process Measurement and Control of Ministry of Education School of Energy and Environment Southeast University Jiangsu Nanjing210096 China CAS Key Laboratory of Renewable Energy Guangzhou Institute of Energy Conversion Chinese Academy of Sciences Guangzhou510640 China

Catalytic hydrodeoxygenation (HDO) of oxygenated compounds under mild conditions is essential for chemical refining, which is always relied on improving hydrogenation activity or/and acid strength of catalytic system. Here, with the synthesis of functional TiO 2 (B) nanosheet, we developed a novel Pt/TiO 2 (B) catalyst for HDO of phenol. Through the synergistic effect of dispersed Pt isolated single atoms and nanoclusters, phenol was efficiently converted into cyclohexane without extra acid under 50 o C and atmospheric hydrogen. The catalytic diversity of two Pt species for C=O/C=C bonds leads to the formation of ketene/enol intermediates, as detected in the in-situ FT-IR tests. Due to the low C-O bond energy of enol intermediates, the HDO of phenol could be carried out at mild conditions through the implementable C-O bond cleavage of enol intermediates. This study provides a new understanding of green HDO process and a novel approach for HDO catalysts developing. © 2022, The Authors. All rights reserved.

关键词： Phenols

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Enhancement of quantum heat engine by encircling a Liouvillian exceptional point

arXiv

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arXiv 2023年

作者： Bu, J.-T. Zhang, J.-Q. Ding, G.-Y. Li, J.-C. Zhang, J.-W. Wang, B. Ding, W.-Q. Yuan, W.-F. Chen, L. Özdemir, S.K. Zhou, F. Jing, H. Feng, M. State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics Wuhan Institute of Physics and Mathematics Innovation Academy of Precision Measurement Science and Technology Chinese Academy of Sciences Wuhan430071 China University of the Chinese Academy of Sciences Beijing100049 China Research Center for Quantum Precision Measurement Guangzhou Institute of Industry Technology Guangzhou511458 China Department of Engineering Science and Mechanics Materials Research Institute Pennsylvania State University University Park State CollegePA16802 United States Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China School of Physics Zhengzhou University Zhengzhou450001 China

Quantum heat engines are expected to outperform the classical counterparts due to quantum coherences involved. Here we experimentally execute a single-ion quantum heat engine and demonstrate, for the first time, the dynamics and the enhanced performance of the heat engine originating from the Liouvillian exceptional points (LEPs). In contrast to the topological effects solely concerned for the LEPs, here we focus on the thermodynamic effects, which can be understood by the Landau-Zener-Stückelberg process under decoherence. We witness a positive net work from the quantum heat engine if the heat engine cycle dynamically encircles an LEP. Further investigation reveals that, under the same circumstance of the heat engine cycles, the largest net work occurs when the system is operated close to the LEP. We argue that our observation of the enhanced performance of the quantum heat engine benefits from the eigen-energy landscape close to the LEP and the topological transition induced by the LEP. Therefore, our results open a new possibility to explore the advantages of the LEPs in quantum systems from both the thermodynamic and topological aspects. © 2023, CC BY.

关键词： Topology

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