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Study of the shear-rate dependence of granular friction based on community detection

science China(Physics,Mechanics & Astronomy) 2019年第4期62卷 38-44页

作者： YongWen Zhang GaoKe Hu XiaoSong Chen Wei Chen WenQi Liu Data Science Research Center Faculty of Science Kunming University of Science and Technology CAS Key Laboratory of Theoretical Physics Institute of Theoretical Physics Chinese Academy of Sciences School of Physical Sciences University of Chinese Academy of Sciences State Key Laboratory of Multiphase Complex System Institute of Process Engineering Chinese Academy of Sciences

In this study, computer simulations are performed on three-dimensional granular systems under shear conditions. The system comprises granular particles that are confined between two rigid plates. The top plate is subjected to a normal force and driven by a shearing velocity. A positive shear-rate dependence of granular friction, known as velocity-strengthening, exists between the granular and shearing plate. To understand the origin of the dependence of frictional sliding, we treat the granular system as a complex network, where granular particles are nodes and normal contact forces are weighted edges used to obtain insight into the interiors of granular matter. Community structures within granular property networks are detected under different shearing velocities in the steady state. Community parameters, such as the size of the largest cluster and average size of clusters, show significant monotonous trends in shearing velocity associated with the shear-rate dependence of granular friction. Then, we apply an instantaneous change in shearing velocity. A dramatic increase in friction is observed with a change in shearing velocity in the non-steady state. The community structures in the non-steady state are different from those in the steady state. Results indicate that the largest cluster is a key factor affecting the friction between the granular and shearing plate.

关键词： granular shear-rate friction community detection

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The X-ray high-energy cutoff in Compact Symmetric Object Mrk 348

arXiv

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arXiv 2024年

作者： Liao, Mai Wang, Junxian Kang, Jialai Li, Xiaofeng Zhou, Minhua National Astronomical Observatories Chinese Academy of Sciences 20A Datun Road Chaoyang District Beijing100101 China Chinese Academy of Sciences South America Center for Astronomy National Astronomical Observatories CAS Beijing100101 China Instituto de Estudios Astrofísicos Facultad de Ingeniería y Ciencias Universidad Diego Portales Av. Ejército 441 Santiago Chile CAS Key Laboratory for Research in Galaxies and Cosmology Department of Astronomy University of Science and Technology of China Anhui Hefei230026 China School of Astronomy and Space Science University of Science and Technology of China Hefei230026 China Department of Astronomy Guangzhou University Guangzhou510006 China Great Bay Center National Astronomical Data Center Guangdong Guangzhou510006 China Astronomy Science and Technology Research Laboratory Department of Education of Guangdong Province Guangzhou510006 China School of Physical Science and Intelligent Education Shangrao Normal University 401 Zhimin Road Shangrao334001 China

Compact radio AGN are thought to be young radio active galactic nuclei (AGN) at the early stage of AGN evolution, thus are ideal laboratory to study the high-energy emission throughout the evolution of radio AGN. In this work, we report for the first time the detection of the high-energy cutoff (Ecut), a direct indicator of thermal coronal radiation, of X-ray emission in Mrk 348 (z = 0.015), a young radio galaxy classified as compact symmetric object. With a 100 ks NuSTAR exposure, we find that the high-energy cutoff (Ecut ) is firmly detected (218−62+124 keV). Fitting with various Comptonization models indicates the presence of a hot corona with temperature kTe = 35 – 40 keV. These strongly support the corona origin for its hard X-ray emission. The comparison in the Ecut – spectra index Γ plot of Mrk 348 with normal large-scale radio galaxies (mostly FR II) yields no difference between them. This suggests the corona properties in radio sources may not evolve over time (i.e., from the infant stage to mature stage), which is to-be-confirmed with future sample studies of young radio AGN. Copyright © 2024, The Authors. All rights reserved.

关键词： Active Galactic Nuclei

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On the Relation between Quality-Diversity Evaluation and Distribution-Fitting Goal in Text Generation

arXiv

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arXiv 2020年

作者： Li, Jianing Lan, Yanyan Guo, Jiafeng Cheng, Xueqi CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

The goal of text generation models is to fit the underlying real probability distribution of text. For performance evaluation, quality and diversity metrics are usually applied. However, it is still not clear to what extend can the quality-diversity evaluation reflect the distribution-fitting goal. In this paper, we try to reveal such relation in a theoretical approach. We prove that under certain conditions, a linear combination of quality and diversity constitutes a divergence metric between the generated distribution and the real distribution. We also show that the commonly used BLEU/Self-BLEU metric pair fails to match any divergence metric, thus propose CR/NRR as a substitute for quality/diversity metric pair. Copyright © 2020, The Authors. All rights reserved.

关键词： Probability distributions

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Artificial intelligence-assisted niacin skin flush screening in early psychosis identification and prediction

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General Psychiatry 2022年第2期35卷 76-78页

作者： Tao Chen Haichun Liu Renfang Tian Ranpiao Gan Wenzuo Xu Tianhong Zhang Jijun Wang Department of Economics University of WaterlooWaterlooOntarioCanada Depatment of Statistics and Actuarial Science(Cross Appointed) University of Waterloo WaterlooOntarioCanada Big Data Research Lab Universty of WaterlooWaterlooOntarioCanada Shanghai Niacin Tech Co. LtdShanghal China Labor and Worklife Program Harvard UniversityCambridgeMassachusettsUSA Department of Automation Shanghai Jao Tong UniversityShanghaiChina Ningbo Artificial Intelligent Institute Shanghai Jiao Tong UniversityNingboChina School of Management Economicsand MathematicsKing's University CollegeLondon0ntarioCanada Shanghai Intelligent Psychological Evaluaton and Intervention Engineering Technology Research Center Shanghai Key Laboratory of Psychotic DisordersShanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghaiChina Bio-X Institutes Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders(Ministry of Education)ShanghaiChina CAS Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of SciencesShanghaiChina Institute of Psychology and Behavioral Science Shanghai Jiao Tong UniversiyShanghaiChina

Schizophrenia is a devastating mental disorder affecting 20 million people *** diagnosis is crucial for disease management and improvement in prognosis,and diagnostic biomarkerscan serveasobjective indicators for the early screening of the *** on the observation of diminished flush responses to niacin in patients with schizophrenia Horrobin proposed anoninvasive niacin skin flush screening for schizophrenia.

关键词： diagnosis prognosis prediction

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ICT at TREC 2019: Fair Ranking Track 28

ICT at TREC 2019: Fair Ranking Track

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28th Text REtrieval Conference, TREC 2019

作者： Wang, Meng Zhang, Haopeng Liang, Fuhuai Feng, Bin Zhao, Di CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

In this paper, we will introduce our work in the 2019 TREC fair ranking task. In temporal academic search, more and more people choose to pay attention to the fairness constraints of ranking. The purpose of this task is to provide fairness exposure to different groups of authors, where the definition of group is diverse, such as based on demographics, height, topics, etc. For this reason, the model we design should consider the fairness of the ranking results while ensuring the relevance of the ranking results. We will show how to use our model to achieve the relevance of query results, then adjust the overall ranking results according to the fairness of documents, and finally achieve the relevance and fairness of document ordering. This paper will introduce the framework and methods of the fair ranking system, as well as the experimental results. © 2019 28th Text REtrieval Conference, TREC 2019 - Proceedings. All Rights Reserved.

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Plagiarism detection of multi-threaded programs using frequent behavioral pattern mining 32

Plagiarism detection of multi-threaded programs using freque...

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32nd International Conference on Software Engineering and Knowledge Engineering, SEKE 2020

作者： Wang, Qing Tian, Zhenzhou Gao, Cong Chen, Lingwei School of Computer Science and Technology Xi'an University of Posts and Telecommunications Xi'an China Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi'an China College of Information Sciences and Technology Pennsylvania State University PA United States

ISBN: (纸本)1891706500

Software dynamic birthmark techniques construct birthmarks using the captured execution traces from running the programs, which serve as one of the most promising methods for obfuscation-resilient software plagiarism detection. However, due to the perturbation caused by non-deterministic thread scheduling in multi-threaded programs, such dynamic approaches optimized for sequential programs may suffer from the randomness in multi-threaded program plagiarism detection. In this paper, we propose a new dynamic thread-aware birthmark FPBirth to facilitate multi-threaded program plagiarism detection. We first explore dynamic monitoring to capture multiple execution traces with respect to system calls for each multi-threaded program under a specified input, and then leverage Apriori algorithm to mine frequent patterns to formulate our dynamic birthmark, which can not only depict the program's behavioral semantics, but also resist the changes and perturbations over execution traces caused by the thread scheduling in multithreaded programs. Using FPBirth, we design a multi-threaded program plagiarism detection system. The experimental results based on a public software plagiarism sample set demonstrate that the developed system integrating our proposed birthmark FPBirth cope better with multi-threaded plagiarism detection than alternative approaches. © 2020 Knowledge Systems Institute Graduate School. All rights reserved.

关键词： Semantics

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Towards fine-grained compiler identification with neural modeling 32

Towards fine-grained compiler identification with neural mod...

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32nd International Conference on Software Engineering and Knowledge Engineering, SEKE 2020

作者： Xie, Borun Tian, Zhenzhou Gao, Cong Chen, Lingwei School of Computer Science and Technology Xi'an University of Posts and Telecommunications Xi'an China Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi'an China College of Information Sciences and Technology Pennsylvania State University PA United States

ISBN: (纸本)1891706500

Different compilers and optimization levels can be used to compile the source code. Revealed in reverse from the produced binaries, these compiler details facilitate essential binary analysis tasks, such as malware forensics and binary code similarity analysis. Most existing approaches adopt a signature matching based or machine learning based strategy to identify the compiler details, showing limits in either the detection accuracy or granularity. In this work, we propose NeuralCI (Neural modeling-based Compiler Identification) to perform the identification of compiler family and optimization level on individual functions. The basic idea is to formulate sophisticated neural networks to process abstracted instruction sequences generated using a lightweight function abstraction strategy. To evaluate the performance of NeuralCI, a large dataset consisting of 413,119 unique functions collected from real-world projects is constructed. The experiments show that NeuralCI achieves over 99% and 90% accuracy in identifying the compiler family and optimization level respectively, which outperforms most state-of-the-art function level compiler identification methods. Also, we explore for the first time the possibility of conducting compiler identification on binary code snippets rather than complete functions, where NeuralCI still achieves 96% accuracy, indicating its ability of capturing subtle yet significant features. © 2020 Knowledge Systems Institute Graduate School. All rights reserved.

关键词： Binary codes

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The Gravitational-wave physics Ⅱ: Progress

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science China(Physics,Mechanics & Astronomy) 2021年第12期64卷 18-67页

作者： Ligong Bian Rong-Gen Cai Shuo Cao Zhoujian Cao He Gao Zong-Kuan Guo Kejia Lee Di Li Jing Liu Youjun Lu Shi Pi Jian-Min Wang Shao-Jiang Wang Yan Wang Tao Yang Xing-Yu Yang Shenghua Yu Xin Zhang CAS Key Laboratory of Theoretical Physics Institute of Theoretical PhysicsChinese Academy of SciencesBeijing 100190China Department of Astronomy Beijing Normal UniversityBeijing 100875China National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China Kavli Institute for Astronomy and Astrophysics Peking UniversityBeijing 100080China School of Physical Sciences University of Chinese Academy of SciencesBeijing 100049China School of Astronomy and Space Sciences University of Chinese Academy of SciencesBeijing 100049China Key Laboratory for Particle Astrophysics Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China School of Fundamental Physics and Mathematical Sciences Hangzhou Institute for Advanced Study(HIAS)University of Chinese Academy of SciencesHangzhou 310024China MOE Key Laboratory of Fundamental Physical Quantities Measurements Hubei Key Laboratory of Gravitation and Quantum PhysicsNational Precise Gravity Measurement Facility(PGMF)Department of Astronomy and School of PhysicsHuazhong University of Science and TechnologyWuhan 430074China Asia Pacific Center for Theoretical Physics Pohang 37673Korea Department of Physics College of SciencesNortheastern UniversityShenyang 110819China Key Laboratory of Data Analytics and Optimization for Smart Industry(Northeastern University) Ministry of EducationShenyang 110819China Department of Physics Chongqing UniversityChongqing 401331China

It has been a half-decade since the first direct detection of gravitational waves, which signifies the coming of the era of the gravitational-wave astronomy and gravitational-wave cosmology. The increasing number of the detected gravitational-wave events has revealed the promising capability of constraining various aspects of cosmology, astronomy, and gravity. Due to the limited space in this review article, we will briefly summarize the recent progress over the past five years, but with a special focus on some of our own work for the key Project "Physics associated with the gravitational waves" supported by the National Natural science Foundation of China. In particular,(1) we have presented the mechanism of the gravitational-wave production during some physical processes of the early Universe, such as inflation, preheating and phase transition, and the cosmological implications of gravitational-wave measurements;(2) we have put constraints on the neutron star maximum mass according to GW170817 observations;(3) we have developed a numerical relativity algorithm based on the finite element method and a waveform model for the binary black hole coalescence along an eccentric orbit.

关键词： gravitational wave gravitational-wave cosmology gravitational-wave astronomy numerical relativity

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An Efficient Image Captioning Method Based on Generative Adversarial networks 21

An Efficient Image Captioning Method Based on Generative Adv...

引用

Proceedings of the 2021 4th International Conference on Artificial Intelligence and Pattern Recognition

作者： Lin Zhenxian Feng Feirong Yang Xiaobao Ding Chen School of Science Xi'an University of Posts and Telecommunications China School of Telecommunication and Information Engineering Xi'an University of Posts and Telecommunications China School of Computer Science and Technology Northwestern Polytechnical UniversityChina. China and School of Computer Science and TechnologyXi'an University of Posts and Telecommunications China School of Computer Science and Technology Xi'an University of Posts and TelecommunicationsChina China and Shaanxi Key Laboratory of Network Data Analysis and Intelligent ProcessingXi'an University of Posts and Telecommunications China

ISBN: (纸本)9781450384087

Image captioning is usually based on the mainstream encoder-decoder framework, the accuracy of the encoders and the generation capability of the decoders directly affect the quality of image captions. But no matter how the encoders and the decoders are combined, the generated captions will only imitate the ground-truth captions, and its diversity is suppressed. To generate more accurate and diverse captions while exploring the impact of different encoder-decoder frameworks for the quality of the generated captions, we conducted an exploration of an efficient image captioning method based on GAN. Specifically, we use ResNet152, EfficientNet-B0, and EfficientNet-B2 as the encoders to extract image features, GRU or Transformer as the decoders to generate captions, respectively. Based on MS COCO2014 dataset, a large number of experiment results show that the EfficientNet-B2+GRU framework has best performance, training time is reduced, BLUE-4 score increases by 0.6, parameters reduce by 0.66 million, which can be used as an efficient encoder-decoder framework for generating diverse captions.

关键词： Decoder Encoder Generative Adversarial networks Image captioning

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A Hybrid Prediction Method Based on MODWT-EMD for Time Series in Wireless Sensor networks

A Hybrid Prediction Method Based on MODWT-EMD for Time Serie...

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International Conference on Intelligent System and Knowledge Engineering, ISKE

作者： Zhongmin Wang Jingwen Jia Cong Gao Yanping Chen Hong Xia Xi’an Key Laboratory of Big Data and Intelligent Computing Xi’an University of Posts and Telecommunications Xi’an China School of Computer Science & Technology Xi’an University of Posts and Telecommunications Xi’an China Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi’an University of Posts and Telecommunications Xi’an China

ISBN: (纸本)9781665405546

Time series is the main form of sensor data. Time series prediction is conducive to reduce the energy consumption of sensor nodes and increase the service life. As time cost and computation cost of the existing hybrid prediction methods for time series are not good, this paper proposes a hybrid prediction method based on MODWT-EMD for time series. Firstly, the original time series is decomposed into multiple frequency components by Maximal Overlapping Discrete Wavelet Transform (MODWT). Secondly, the multiple frequency components are decomposed successively by Empirical Mode Decomposition (EMD) to obtain IMF components and residuals. IMFs and residuals contain the feature information of time series. Then, the importance of the extracted feature information is scored and sorted by random forest. We select feature information with a higher score. Finally, the selected feature information is input into Bi-GRU for training. We predicted the original time series by the trained Bi-GRU and obtained the prediction results. The experimental results show that the method proposed in this paper can predict the time series effectively.

关键词： Training Wireless communication Wireless sensor networks Time-frequency analysis Costs Time series analysis Predictive models

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