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Linear mathematical model for the unique solution of 3D ptychographic iterative engine

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Chinese Optics Letters 2024年第5期22卷 1-7页

作者：吴丽青齐乃杰昌成成陶华何小亮刘诚朱健强 key laboratory of High Power Laser and Physics Shanghai Institute of Optics and Fine MechanicsChinese Academy of SciencesShanghai 201800China National laboratory on High Power Laser and Physics China Academy of Engineering PhysicsChinese Academy of SciencesShanghai 201800China University of Chinese Academy of Sciences Beijing 100049China

Diffraction intensities of the 3D ptychographic iterative engine(3PIE)were written as a set of linear equations of the selfcorrelations of Fourier components of all sample slices,and an effective computing method was developed to solve these linear equations for the transmission functions of all sample slices *** both theoretical analysis and numerical simulations,this study revealed the underlying physics and mathematics of 3PIE and demonstrated for the first time,to our knowledge,that 3PIE can generate mathematically unique reconstruction even with noisy data.

关键词： 3D imaging 3D ptychographic iterative engine linear equation group unique solution

High-precision parallel computing model of solute transport based on GPU acceleration

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Journal of Hydrodynamics 2024年第1期36卷 202-212页

作者： Shang-hong Zhang Rong-qi Zhang Wen-da Li Xi-yan Yang Yang Zhou School of Water Resources and Hydropower Engineering North China Electric Power UniversityBeijing102206China Hubei key laboratory of Intelligent Yangtze and Hydroelectric Science China Yangtze Power Co.Ltd.Yichang443133China

The scenario simulation analysis of water environmental emergencies is very important for risk prevention and control,and emergency *** quickly and accurately simulate the transport and diffusion process of high-intensity pollutants during sudden environmental water pollution events,in this study,a high-precision pollution transport and diffusion model for unstructured grids based on Compute Unified Device Architecture(CUDA)is *** finite volume method of a total variation diminishing limiter with the Kong proposed r-factor is used to reduce numerical diffusion and oscillation errors in the simulation of pollutants under sharp concentration conditions,and graphics processing unit acceleration technology is used to improve computational *** advection diffusion process of the model is verified numerically using two benchmark cases,and the efficiency of the model is evaluated using an engineering *** results demonstrate that the model perform well in the simulation of material transport in the presence of sharp ***,it has high computational *** acceleration ratio is 46 times the single-thread acceleration effect of the original *** efficiency of the accelerated model meet the requirements of an engineering application,and the rapid early warning and assessment of water pollution accidents is achieved.

关键词： Pollution transport and diffusion model parallel computing Compute Unified Device Architecture(CUDA) pollution event

UAV-assisted cooperative offloading energy efficiency system for mobile edge computing

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Digital Communications and Networks 2024年第1期10卷 16-24页

作者： Xue-Yong Yu Wen-Jin Niu Ye Zhu Hong-Bo Zhu Jiangsu key laboratory of Wireless Communications Nanjing University of Posts and Telecommunications Nanjing210003China Engineering Research Centerof Health Service System Based on Ubiquitous Wireless Networks Ministry of EducationNanjng Universityof Posts and Telecommunications Nanjing210003China

Reliable communication and intensive computing power cannot be provided effectively by temporary hot spots in disaster areas and complex terrain ground *** this has greatly developed the application and integration of UAV and Mobile Edge computing(MEC)to the Internet of Things(loT).However,problems such as multi-user and huge data flow in large areas,which contradict the reality that a single UAV is constrained by limited computing power,still *** to allowing UAV collaboration to accomplish complex tasks,cooperative task offloading between multiple UAVs must meet the interdependence of tasks and realize parallel processing,which reduces the computing power consumption and endurance pressure of *** the computing requirements of the user terminal,delay constraint of a computing task,energy constraint,and safe distance of UAV,we constructed a UAV-Assisted cooperative offloading energy efficiency system for mobile edge computing to minimize user terminal energy ***,the resulting optimization problem is originally nonconvex and thus,difficult to solve *** tackle this problem,we developed an energy efficiency optimization algorithm using Block Coordinate Descent(BCD)that decomposes the problem into three convex ***,we jointly optimized the number of local computing tasks,number of computing offloaded tasks,trajectories of UAV,and offloading matching relationship between multi-UAVs and multiuser *** results show that the proposed approach is suitable for different channel conditions and significantly saves the user terminal energy consumption compared with other benchmark schemes.

关键词： Computation offloading Internet of things(IoT) Mobile edge computing(MEC) Block coordinate descent(BCD)

Scintillation Arc from FRB 20220912A

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Science China(Physics,Mechanics & Astronomy) 2024年第1期67卷 134-142页

作者： Zi-Wei Wu Robert AMain Wei-Wei Zhu Bing Zhang Peng Jiang Jia-Rui Niu Jin-Lin Han Di Li Ke-Jia Lee Dong-Zi Li Yuan-Pei Yang Fa-Yin Wang Rui Luo Pei Wang Chen-Hui Niu Heng Xu Bo-Jun Wang Wei-Yang Wang Yong-Kun Zhang Yi Feng De-Jiang Zhou Yong-Hua Xu Can-Min Deng Yu-Hao Zhu National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China Max-Planck-Institut für Radioastronomie Bonn 53121Germany Institute for Frontier in Astronomy and Astrophysics Beijing Normal UniversityBeijing 102206China Nevada Center for Astrophysics and Department of Physics and Astronomy University of NevadaLas VegasNV 89154USA CAS key laboratory of FAST National Astronomical ObservatoriesChinese Academy of SciencesBeijing 100101China School of Astronomy University of Chinese Academy of SciencesBeijing 100049China NAOC-UKZN Computational Astrophysics Centre University of KwaZulu-NatalDurban 4000South Africa Department of Astronomy Peking UniversityBeijing 100871China Kavli Institute for Astronomy and Astrophysics Peking UniversityBeijing 100871China Cahill Center for Astronomy and Astrophysics California Institute of TechnologyPasadena 91125USA South-Western Institute For Astronomy Research Yunnan UniversityKunming 650504China School of Astronomy and Space Science Nanjing UniversityNanjing 210093China key laboratory of Modern Astronomy and Astrophysics(Nanjing University) Ministry of EducationNanjing 210023China CSIRO Space and Astronomy Epping 1710Australia Department of Astronomy School of Physics and Materials ScienceGuangzhou UniversityGuangzhou 510006China Research Center for Intelligent computing Platforms Zhejiang LaboratoryHangzhou 311100China Yunnan Observatories Chinese Academy of SciencesKunming 650011China Guangxi key laboratory for Relativistic Astrophysics Department of PhysicsGuangxi UniversityNanning 530004China

We present the interstellar scintillation analysis of fast radio burst(FRB)20220912A during its extremely active episode in 2022using data from the Five-hundred-meter Aperture Spherical Radio Telescope(FAST).We detect a scintillation arc in the FRB’s secondary spectrum,which describes the power in terms of the scattered FRB signals’time delay and Doppler *** arc indicates that the scintillation is caused by a highly localized *** analysis favors a Milky Way origin of the ionized interstellar medium(IISM)for the localized scattering medium but cannot rule out a host galaxy *** present our method for detecting the scintillation arc,which can be applied generally to sources with irregularly spaced bursts or *** methods could help shed light on the complex interstellar environment surrounding the FRBs and in our Galaxy.

关键词： fast radio burst scintillation FRB 20220912A

Single-cell omics:experimental workflow,data analyses and applications

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Science China Life Sciences 2024年

作者： Fengying Sun Haoyan Li Dongqing Sun Shaliu Fu Lei Gu Xin Shao Qinqin Wang Xin Dong Bin Duan Feiyang Xing Jun Wu Minmin Xiao Fangqing Zhao Jing-Dong J.Han Qi Liu Xiaohui Fan Chen Li Chenfei Wang Tieliu Shi Center for Bioinformatics and Computational Biology Shanghai Key Laboratory of Regulatory Biology the Institute of Biomedical Sciences and School of Life Sciences East China Normal University Beijing Institutes of Life Science Chinese Academy of Sciences Peking-Tsinghua Center for Life Sciences Academy for Advanced Interdisciplinary Studies Center for Quantitative Biology (CQB) Peking University Zhejiang key laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases Women’s Hospital Zhejiang University School of Medicine key laboratory of Advanced Theory and Application in Statistics and data Science-MOE School of Statistics East China Normal University Shanghai 200062 China Department of Clinical laboratory the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City) Pharmaceutical Informatics Institute College of Pharmaceutical Sciences Zhejiang University key laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University) Ministry of Education Orthopaedic Department Tongji Hospital Bioinformatics Department School of Life Sciences and Technology Tongji University Frontier Science Center for Stem Cells School of Life Sciences and Technology Tongji University Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine Shanghai East Hospital Bioinformatics Department School of Life Sciences and Technology Tongji University Research Institute of Intelligent computing Zhejiang Lab Shanghai Research Institute for Intelligent Autonomous Systems Center for Single-cell Omics School of Public Health Shanghai Jiao Tong University School of Medicine National key laboratory of Chinese Medicine Modernization Innovation Center of Yangtze River Delta Zhejiang University

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome,proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field,offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

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Optimizing ASReview Simulations:A generic Multiprocessing Solution for“Light-data'and“Heavy-data'Users

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data Intelligence 2024年第2期6卷 320-343页

作者： Sergei Romanov Abel Soares Siqueira Jonathan de Bruin Jelle Teijema Laura Hofstee Rens van de Schoot Applied data Science Department of Information and Computing ScienceFaculty of ScienceUtrecht University Netherlands eScienceCenter AmsterdamNL Department of Research and data Management Services Information Technology ServicesUtrecht UniversityUtrechtthe Netherlands Department of Methodology and Statistics Faculty of Social and Behavioral SciencesUtrecht University

Active learning can be used for optimizing and speeding up the screening phase of systematic *** simulation studies mimicking the screening process can be used to test the performance of different machine-learning models or to study the impact of different training *** paper presents an architecture design withamultiprocessing computational strategyforrunningmanysuch simulation studiesinparallel,using the ASReview Makita workflow generator and Kubernetes software for deployment with cloud *** provide a technical explanation of the proposed cloud architecture and its *** addition to that,we conducted 1140 simulations investigating the computational time using various numbers of CPUs and RAM *** analysis demonstrates the degree to which simulations can be accelerated with multiprocessing computing *** parallel computation strategy and the architecture design that was developed in the present paper can contribute to future research with more optimal simulation time and,at the same time,ensure the safe completion of the needed processes.

关键词： Active learning Systematic review Simulation study Multiprocessing Cloud architecture

HAF: a hybrid annotation framework based on expert knowledge and learning technique

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Science China(Information Sciences) 2022年第1期65卷 276-278页

作者： Zhixing LI Yue YU Tao WANG Gang YIN Xinjun MAO Huaimin WANG key laboratory of parallel and Distributed computing National University of Defense Technology College of Computer National University of Defense Technology

Dear editor,The increasing awareness of the potential value hidden in data has resulted in many data mining studies being conducted. In the domain of software engineering, for example, developers' behavioral data and code review data have been leveraged in social coding sites to automatically recommend relevant projects [1] and candidate reviewers [2, 3].

关键词： PULL-BASED DEVELOPMENT RECOMMENDATION

Interest Points analysis for Internet Forum Based on Long-Short Windows Similarity

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Computers, Materials & Continua 2022年第8期72卷 3247-3267页

作者： Xinghai Ju Jicang Lu Xiangyang Luo Gang Zhou Shiyu Wang Shunhang Li Yang Yang State key laboratory of Mathematical Engineering and Advanced computing Zhengzhou450001China School of computing and Information Systems Singapore Management University188065Singapore College of Computer Science and big data Fuzhou UniversityFuzhou350116China

For Internet forum Points of Interest(PoI),existing analysis methods are usually lack of usability analysis under different conditions and ignore the long-term variation,which lead to blindness in method *** address this problem,this paper proposed a PoI variation prediction framework based on similarity analysis between long and short *** on the framework,this paper presented 5 PoI analysis algorithms which can be categorized into 2 types,i.e.,the traditional sequence analysis methods such as autoregressive integrated moving average model(ARIMA),support vector regressor(SVR),and the deep learning methods such as convolutional neural network(CNN),long-short term memory network(LSTM),Transformer(TRM).Specifically,this paper firstly divides observed data into long and short windows,and extracts key words as PoI of each ***,the PoI similarities between long and short windows are calculated for training and ***,series of experiments is conducted based on real Internet forum *** results show that,all the 5 algorithms could predict PoI variations well,which indicate effectiveness of the proposed *** the length of long window is small,traditional methods perform better,and SVR is the *** the contrary,the deep learning methods show superiority,and LSTM performs *** results could provide beneficial references for PoI variation analysis and prediction algorithms selection under different parameter configurations.

关键词： Point of interest(PoI)analysis long and short windows sequential analysis deep learning

Alignment efficient image-sentence retrieval considering transferable cross-modal representation learning

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Frontiers of Computer Science 2024年第1期18卷 77-91页

作者： Yang YANG Jinyi GUO Guangyu LI Lanyu LI Wenjie LI Jian YANG School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing 210094China Department of computing Hong Kong Polytechnic UniversityHong Kong 100872China State key Lab.for Novel Software Technology Nanjing UniversityNanjing 210094China 14th Research Institute of China Electronics Technology Group Corporation Nanjing 210094China guangyu.li2017@***

Traditional image-sentence cross-modal retrieval methods usually aim to learn consistent representations of heterogeneous modalities,thereby to search similar instances in one modality according to the query from another modality in *** basic assumption behind these methods is that parallel multi-modal data(i.e.,different modalities of the same example are aligned)can be obtained in *** other words,the image-sentence cross-modal retrieval task is a supervised task with the alignments as ***,in many real-world applications,it is difficult to realign a large amount of parallel data for new scenarios due to the substantial labor costs,leading the non-parallel multi-modal data and existing methods cannot be used *** the other hand,there actually exists auxiliary parallel multi-modal data with similar semantics,which can assist the non-parallel data to learn the consistent ***,in this paper,we aim at“Alignment Efficient Image-Sentence Retrieval”(AEIR),which recurs to the auxiliary parallel image-sentence data as the source domain data,and takes the non-parallel data as the target domain *** single-modal transfer learning,AEIR learns consistent image-sentence cross-modal representations of target domain by transferring the alignments of existing parallel ***,AEIR learns the image-sentence consistent representations in source domain with parallel data,while transferring the alignment knowledge across domains by jointly optimizing a novel designed cross-domain cross-modal metric learning based constraint with intra-modal domain adversarial ***,we can effectively learn the consistent representations for target domain considering both the structure and semantic ***,extensive experiments on different transfer scenarios validate that AEIR can achieve better retrieval results comparing with the baselines.

关键词： image-sentence retrieval transfer learning semantic transfer structure transfer