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Distribution-free data density estimation in large-scale networks

计算机科学前沿 2018年第6期12卷 1220-1240页

作者： Minqi ZHOU Rong ZHANG Weining QIAN Aoying ZHOU Data Science and Engineering Institute East China Normal University Shanghai 200062 China State Key Lab of Software Engineering Wuhan University Wuhan 430072 China Data Science and Engineering Institute East China Normal University Shanghai 200062 China

Estimating the global data distribution in largescale networks is an important issue and yet to be well *** can benefit many applications,especially in the cloud computing era,such as load balancing analysis,query processing,and data *** by the inversion method for random variate (number) generation,in this paper,we present a novel model called distribution-free data density estimation for large ring-based networks to achieve high estimation accuracy with low estimation cost regardless of the distribution models of the underlying *** model generates random samples for any arbitrary distribution by sampling the global cumulative distribution function and is free from sampling *** with this estimation method,we can estimate data densities over both one-dimensional and multidimensional tuple sets,where each dimension could be either continuous or discrete as its *** large-scale networks,the key idea for distribution-free estimation is to sample a small subset of peers for estimating the global data distribution over the data *** on computing and sampling the global cumulative distribution function based on which the global data distribution is estimated are introduced with a detailed theoretical *** extensive performance study confirms the effectiveness and efficiency of our methods in large ring-based networks.

关键词： distribution-free data density estimation random sampling

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Internal search of the evolution matrix in QUasi-Affine TRansformation Evolution (QUATRE) algorithm

Internal search of the evolution matrix in QUasi-Affine TRan...

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作者： Chu, Shu-Chuan Chen, Yuxin Meng, Fanjia Yang, Chen Pan, Jeng-Shyang Meng, Zhenyu College of Computer Science and Engineering Shandong University of Science and Technology Qingdao China Institute of Artificial Intelligence Fujian University of Technology Fuzhou China Guanzhuang Central Primary School of Zhangqiu District Jinan China Fujian Provincial Key Lab of Big Data Mining and Applications Fujian University of Technology Fuzhou China

Optimization demands exist everywhere in the real world especially in science studies and engineering practices, and it is important that the method to deal with intricacy optimization problems should itself be relative simple. Particle Swarm Optimization (PSO) and Differential Evolution (DE) both are simple evolutionary algorithms (EAs) which are proposed for single-objective optimization and both of them have been proved to be efficient methods for optimizing applications, however, there are still some weakness existing within them. A innovative evolutionary method named QUasi-Affine TRansformation Evolutionary (QUATRE) algorithm which is derived from, also tackles some weaknesses of PSO and DE algorithm, and obtains better performance on commonly used test suites. The key characteristic of QUATRE is that an automatically generated matrix named evolution matrix M is implemented in evolutionary process, which is taken as an alternative of employing the crossover rate CR. Here in this paper, we present a novel QUATRE variant, named IS-QUATRE, which can explore the search area in a better way comparison with the previous method, and relatively good optimization ability can be obtained by our proposed IS-QUATRE algorithm under CEC2013 test suit. And the conducted experimental results validate that our proposed IS-QUATRE is competitive with some other famous PSO and DE variants. © 2020 - IOS Press and the authors. All rights reserved.

关键词： Particle swarm optimization (PSO)

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MIPI 2022 Challenge on Under-Display Camera Image Restoration: Methods and Results 17th

MIPI 2022 Challenge on Under-Display Camera Image Restorati...

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17th European Conference on Computer Vision, ECCV 2022

作者： Feng, Ruicheng Li, Chongyi Zhou, Shangchen Sun, Wenxiu Zhu, Qingpeng Jiang, Jun Yang, Qingyu Loy, Chen Change Gu, Jinwei Zhu, Yurui Wang, Xi Fu, Xueyang Hu, Xiaowei Hu, Jinfan Liu, Xina Chen, Xiangyu Dong, Chao Zhang, Dafeng Huang, Feiyu Liu, Shizhuo Wang, Xiaobing Jin, Zhezhu Jiang, Xuhao Shao, Guangqi Wang, Xiaotao Lei, Lei Zhang, Zhao Zhao, Suiyi Zheng, Huan Gao, Yangcheng Wei, Yanyan Ren, Jiahuan Huang, Tao Fang, Zhenxuan Huang, Mengluan Xu, Junwei Zhang, Yong Yang, Yuechi Shu, Qidi Yang, Zhiwen Li, Shaocong Yao, Mingde Xu, Ruikang Guan, Yuanshen Huang, Jie Xiong, Zhiwei Zhu, Hangyan Liu, Ming Liu, Shaohui Zuo, Wangmeng Jia, Zhuang Song, Binbin Song, Ziqi Mao, Guiting Hou, Ben Liu, Zhimou Ke, Yi Ouyang, Dengpei Han, Dekui Zhang, Jinghao Zhu, Qi Zheng, Naishan Zhao, Feng Jin, Wu Conde, Marcos Nathan, Sabari Timofte, Radu Xu, Tianyi Xu, Jun Hrishikesh, P.S. Puthussery, Densen Jiji, C.V. Jiang, Biao Ding, Yuhan Li, WanZhang Feng, Xiaoyue Chen, Sijing Zhong, Tianheng Lu, Jiyang Chen, Hongming Fan, Zhentao Chen, Xiang Nanyang Technological University Singapore Singapore SenseBrain San Jose United States Shanghai AI Laboratory Shanghai China SenseTime Research and Tetras.AI Beijing China University of Science and Technology of China Hefei China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Samsung Research China Beijing China Xiaomi Beijing China Hefei University of Technology Hefei China School of Artificial Intelligence Xidian University Xi’an China School of Remote Sensing and Information Engineering Wuhan University Wuhan China State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan China Harbin Institute of Technology Harbin China University of Macau China Changsha Research Institute of Mining and Metallurgy Changsha China Tianjin University Tianjin China Computer Vision Lab University of Wurzburg Würzburg Germany Couger Inc. Tokyo Japan School of Statistics and Data Science Nankai University Tianjin China Founding Minds Software Thiruvananthapuram India Department of Electronics and Communication SRM University AP Amaravati India Fudan University Shanghai China Shenyang Aerospace University Shenyang China Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9783031250712

Developing and integrating advanced image sensors with novel algorithms in camera systems is prevalent with the increasing demand for computational photography and imaging on mobile platforms. However, the lack of high-quality data for research and the rare opportunity for in-depth exchange of views from industry and academia constrain the development of mobile intelligent photography and imaging (MIPI). To bridge the gap, we introduce the first MIPI challenge including five tracks focusing on novel image sensors and imaging algorithms. In this paper, we summarize and review the Under-Display Camera (UDC) Image Restoration track on MIPI 2022. In total, 167 participants were successfully registered, and 19 teams submitted results in the final testing phase. The developed solutions in this challenge achieved state-of-the-art performance on Under-Display Camera Image Restoration. A detailed description of all models developed in this challenge is provided in this paper. More details of this challenge and the link to the dataset can be found at https://***/mipi-challenge/MIPI2022. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Image reconstruction

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An Adaptive Image Contrast Enhancement Algorithm Based on Retinex

An Adaptive Image Contrast Enhancement Algorithm Based on Re...

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Chinese Automation Congress (CAC)

作者： Guifang Shao Fengqiang Gao Tiejun Li Rong Zhu Ting Pan Yuwen Chen Xiamen Key Lab. of Big Data Intelligent Analysis and Decision Xiamen University Xiamen China School of Information Engineering Jimei University Xiamen China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

Image contrast enhancement is an essential operation for various image processing applications, especially for segmentation and feature extraction. However, different contrast enhancement methods contain various performance on the same images. To automatically choose the suitable algorithm for image contrast enhancement, in this paper, we put forward a different Retinex based method according to image feature fusion. First, five features, including gray value, contrast, definition, edge and entropy, are defined to characterize various image. Then, five fusion rules are designed to distinguish images with low contrast, foggy, monotonous color, rich in detail or color. Finally, the single scale Retinex (SSR), the multi-scale Retinex (MSR) and MSR in HSV color space (MSR_HSV) are introduced to improve image contrast. Experiments on various images drawn from different data sets prove the effectiveness of our proposed method.

关键词： Image color analysis Feature extraction Image edge detection Image quality Gray-scale Filtering algorithms Color

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Determination of the cross section from 10 to 200 keV at the Back-n facility at CSNS

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The European Physical Journal A 2023年第10期59卷 1-11页

作者： Wang, Jincheng Ren, Jie Jiang, Wei Ruan, Xichao Sun, Qi Hu, Jifeng Jiang, Bing Bao, Jie Zhang, Qiwei Luan, Guangyuan Huang, Hanxiong Nie, Yangbo Ge, Zhigang An, Qi Bai, Haofan Bai, Jiangbo Cao, Ping Chen, Qiping Chen, Yonghao Chen, Zhen Cui, Zengqi Fan, Anchuan Fan, Ruirui Feng, Changqing Feng, Fanzhen Gao, Keqing Gu, Minhao Han, Changcai Han, Zijie He, Guozhu He, Yongcheng Hong, Yang Hu, Yiwei Jia, Weihua Jiang, Haoyu Jiang, Zhijie Jin, Zhengyao Kang, Ling Li, Bo Li, Chao Li, Gong Li, Jiawen Li, Qiang Li, Yang Liu, Jie Liu, Rong Liu, Shubin Ning, Changjun Qi, Binbin Ren, Zhizhou Song, Zhaohui Sun, Kang Tan, Zhixin Tang, Jingyu Tang, Shengda Wang, Lijiao Wang, Pengcheng Wang, Zhaohui Wen, Zhongwei Wu, Xiaoguang Wu, Xuan Xie, Likun Yang, Yiwei Yi, Han Yu, Yongji Zhang, Guohui Zhang, Linhao Zhang, Mohan Zhang, Xianpeng Zhang, Yuliang Zhang, Yue Zhang, Zhiyong Zhao, Maoyuan Zhou, Luping Zhu, Kejun Zhang, Jie Key Laboratory of Nuclear Data China Institute of Atomic Energy Beijing China Institute of High Energy Physics Chinese Academy of Sciences (CAS) Beijing China Spallation Neutron Source Science Center Dongguan China Shanghai Institute of Applied Physics Chinese Academy of Sciences Shanghai China State Key Laboratory of Particle Detection and Electronics University of Science and Technology of China Hefei China Department of Modern Physics University of Science and Technology of China Hefei China State Key Laboratory of Nuclear Physics and Technology School of Physics Peking University Beijing China Institute of Nuclear Physics and Chemistry China Academy of Engineering Physics Mianyang China School of Nuclear Science and Technology University of Science and Technology of China Hefei China USTC Archaeometry Lab University of Science and Technology of China Hefei China State Key Laboratory of Particle Detection and Electronics Institute of High Energy Physics Chinese Academy of Sciences Beijing China Northwest Institute of Nuclear Technology Xi’an China University of Chinese Academy of Sciences Beijing China

The neutron capture cross section of $$^{232}Th$$ has been measured with the time-of-flight technique in the energy range from 10 to 200 keV at the back-streaming white neutron beam-line (Back-n) of China Spallation Neutron Source (CSNS). The pulse height weighting technique (PHWT) was applied with four C $$_{6}$$ D $$_{6}$$ liquid scintillators to measure the prompt gamma-ray energy release following neutron capture. The measurement data, corrected with the PHWT, have been normalized to the saturated resonances at 21.8 eV. The background was determined by a lead sample measurement and detailed Monte Carlo simulations. The $$^{232}Th(n,\gamma )$$ average cross sections have been determined relative to the $$^{197}Au(n,\gamma )$$ reaction cross sections. The results are consistent with the evaluation values of CENDL-3.2 and JENDL-5. The total uncertainties, including the PHWT, normalization, background subtraction, corrections, and relative measurement, are in the range of 4.5–4.8%.

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Three branch net lane detection on complex road conditions

Three branch net lane detection on complex road conditions

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2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019

作者： Chen, Qiaosong Wang, Zhixiang Long, Baijun Sui, Xiaoxu Zhang, Meng Deng, Xin Wang, Jin Chongqing University of Posts and Telecommunications Key Laboratory of Data Engineering and Visual Computing Chongqing400065 China Streamax AI Lab Streamax Chongqing400039 China

ISBN: (纸本)9781728145693

Lane detection task is the most necessary part in modern intelligent driving technology. However, there still have many challenge need to be conquered. In this paper, we proposed a three-branch neural network, in this framework, there are several new techniques are used. Including multi-branch, lightweight module, feature recalibration and decoder module, named Three Branch Net. Furthermore, A new dataset have been used, which includes much more complex situation and more close to the real world. Compared with other newest method, experiment results shows the proposed approach is the most effective method in complex road conditions task. © 2019 IEEE.

关键词： Complex networks

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A Crystal Plasticity Model with Irradiation Effect for the Mechanical Behavior of FCC Metals

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Acta Mechanica Solida Sinica 2019年第6期32卷 675-687页

作者： Jnnfeng Nie Yunpeng Liu Pandong Lin Qihao Xie Zhanli Liu Institute of Nuclear and New Energy Technology Collaborative Innovation Center of Advanced Nuclear Energy TechnologyKey Laboratory of Advanced Reactor Engineering and Safety of Minis try of EducationTsinghua UniversityBeijing 100084China Applied Mechanics Lab. School of Aerospace EngineeringTsinghua UniversityBeijing 100084China Data Science and Information Technology Research Center Tsinghua-Berkeley Shenzhen InstituteShenzhen 518055China

In this paper,a crystal plasticity model considering the irradiation effect based on the thermal activation theory is *** evolutions of screw dislocations,edge dislocations,and stacking fault tetrahedrals(SFTs)(induced by irradiation)are included into the *** interactions between dislocations and irradiation-induced SFTs are also *** constitutive model is numerically implemented on the ABAQUS platform through UMAT subroutine and applied to study the irradiation effect on the mechanical behavior of pure *** mechanical properties of single and polycrystalline copper are studied,and the simulation results show that the constitutive model can properly predict the mechanical behavior of irradiated pure *** for polycrystalline copper,the simulation results are in good agreement with the experimental data.

关键词： Crystal plasticity Irradiation effect Uniaxial tension Dislocation FCC crystal

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FedPHE: A Secure and Efficient Federated Learning via Packed Homomorphic Encryption

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IEEE Transactions on Dependable and Secure Computing 2025年

作者： Li, Yuqing Yan, Nan Chen, Jing Wang, Xiong Hong, Jianan He, Kun Wang, Wei Li, Bo Wuhan University Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Cyber Science and Engineering Wuhan430072 China Wuhan University RiZhao Information Technology Institute Rizhao276800 China Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab/Cluster and Grid Computing Lab School of Computer Science and Technology Wuhan430074 China Shanghai Jiao Tong University School of Cyber Science and Engineering Shanghai200240 China Hong Kong University of Science and Technology Department of Computer Science and Engineering Hong Kong

Cross-silo federated learning (FL) enables multiple institutions (clients) to collaboratively build a global model without sharing private data. To prevent privacy leakage during aggregation, homomorphic encryption (HE) is widely used to encrypt model updates, yet incurs high computation and communication overheads. To reduce these overheads, packed HE (PHE) has been proposed to encrypt multiple plaintexts into a single ciphertext. However, the original design of PHE assumes all clients share a single private key, making the system vulnerable to security threats of ciphertexts being intercepted and decrypted by honest-but-curious clients. Also, it does not consider the heterogeneity among different clients, resulting in undermined training efficiency with slow convergence and stragglers. To address these challenges, we propose FedPHE, a secure and efficient FL framework with PHE by jointly exploiting contribution-aware secure aggregation and straggler-resistant client selection. Using CKKS with sparsification and blinding, FedPHE achieves efficient secure aggregation that allows clients to only provide obscured encrypted updates while the server can perform aggregation by accounting for contributions of local updates. To mitigate the straggler effect, we devise a perturbed sketch-based selection to cherry-pick representative clients with heterogeneous models and computing capabilities in a communication-efficient and privacy-preserving manner. We show, through rigorous security analysis and extensive experiments, that FedPHE can efficiently safeguard clients' privacy, achieve 2.45-6.56× training speedup, cut the communication overhead by 1.32-24.85×, and reduce straggler effects by 1.89-2.78×. © 2004-2012 IEEE.

关键词： Privacy by design

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Inconsistency-aware uncertainty estimation for semi-supervised medical image segmentation

arXiv

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arXiv 2021年

作者： Shi, Yinghuan Zhang, Jian Ling, Tong Lu, Jiwen Zheng, Yefeng Yu, Qian Qi, Lei Gao, Yang State Key Laboratory for Novel Software Technology Nanjing University China National Institute of Healthcare Data Science Nanjing University China Department of Automation Tsinghua University China Tencent Jarvis Lab China School of Data and Computer Science Shandong Women’s University China School of Computer Science and Engineering Southeast University Nanjing211189 China State Key Laboratory for Novel Software Technology Nanjing University Nanjing210046 China

In semi-supervised medical image segmentation, most previous works draw on the common assumption that higher entropy means higher uncertainty. In this paper, we investigate a novel method of estimating uncertainty. We observe that, when assigned different misclassification costs in a certain degree, if the segmentation result of a pixel becomes inconsistent, this pixel shows a relative uncertainty in its segmentation. Therefore, we present a new semi-supervised segmentation model, namely, conservative-radical network (CoraNet in short) based on our uncertainty estimation and separate self-training strategy. In particular, our CoraNet model consists of three major components: a conservative-radical module (CRM), a certain region segmentation network (C-SN), and an uncertain region segmentation network (UC-SN) that could be alternatively trained in an end-to-end manner. We have extensively evaluated our method on various segmentation tasks with publicly available benchmark datasets, including CT pancreas, MR endocardium, and MR multi-structures segmentation on the ACDC dataset. Compared with the current state of the art, our CoraNet has demonstrated superior performance. In addition, we have also analyzed its connection with and difference from conventional methods of uncertainty estimation in semi-supervised medical image segmentation. Copyright © 2021, The Authors. All rights reserved.

关键词： Pixels

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Highest overall conversion efficiency for portable thin-film zinc-ion batteries photorecharged by flexible perovskite solar cells

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Chemical engineering Journal 2025年 518卷

作者： Ming Chen Xin Guo Bita Farhadi Xiaojun Guo Yan Zhu Chao Zhou Xudong Li Kai Wang Dong Yang Xiao Jiang Haoxiang Zhang Shengzhong Liu School of Electric Power Civil Engineering and Architecture College of Physics and Electronics Engineering State Key Laboratory of Quantum Optics and Quantum Optics Devices Shanxi University Taiyuan 030006 China State Key Laboratory of Photoelectric Conversion and Utilization of Solar Energy Dalian Institute of Chemical Physics Chinese Academy of Sciences Dalian 116023 Liaoning China EIT Data Science and Communication College Zhejiang Yuexiu University Shaoxing China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing 100049 China CNNP Optoelectronics Technology 2828 Canghai Road Lingang Shanghai China Key Laboratory of Applied Surface and Colloid Chemistry Ministry of Education Shaanxi Key Laboratory for Advanced Energy Devices Shaanxi Engineering Lab for Advanced Energy Technology Institute for Advanced Energy Materials School of Materials Science and Engineering Shaanxi Normal China

The interconnection of flexible thin-film zinc-ion batteries (FTZIBs) and flexible perovskite solar cells presents an ideal system for portable photorechargeable power generation-storage system. However, the integration process of these two components still faces significant challenges. In this work, we develop a novel approach to enhance the integration compatibility between FTZIBs and flexible perovskite solar cells. Specifically, FTZIBs and flexible perovskite solar cells are fabricated on opposite sides of a polyimide (PI) substrate, aiming to improve the portability and compactness of the FTZIBs. By using Ag-Cu thin-film as the current collectors for the FTZIBs, not only suppress galvanic corrosion between the current collector and Zn but also ensure that the Ag-Cu-Zn thin-film electrode satisfies the Born-Huang stability criterion, significantly improved the electrochemical cycling stability and mechanical robustness of the thin-film electrodes. Additionally, a functional organohydrogel electrolyte with excellent mechanical strength, adhesion, and water retention is synthesized to suppress Zn dendrite formation and side reactions such as hydrogen evolution, enhancing the cycling stability and bendability of the FTZIBs. The resultant portable photorechargeable zinc-ion batteries (PZIBs) exhibit a high specific capacity of 250 mAh cm −3 and an overall conversion efficiency of 18.44 %, representing the best performance among similar systems.

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