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Discovery of Four Pulsars in a Pilot Survey at Intermediate Galactic Latitudes with FAST

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arXiv 2023年

作者： Zhi, Q.J. Bai, J.T. Dai, S. Xu, X. Dang, S.J. Shang, L.H. Zhao, R.S. Li, D. Zhu, W.W. Wang, N. Yuan, J.P. Wang, P. Zhang, L. Feng, Y. Wang, J.B. Wang, S.Q. Wu, Q.D. Dong, A.J. Yang, H. Tian, J. Zhong, W.Q. Luo, X.H. Filipović, Miroslav D. Qiao, G.J. School of Physics and Electronic Science Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing Guizhou Normal University Guiyang550001 China Xinjiang Astronomical Observatory Chinese Academy of Sciences Xinjiang Urumqi830011 China School of Science Western Sydney University Locked Bag 1797 Penrith South DCNSW2751 Australia School of Mathematical Sciences Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing Guizhou Normal University Guiyang550001 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China University of Chinese Academy of Sciences Beijing100049 China Research Center for Intelligent Computing Platforms Zhejiang Laboratory Hangzhou311100 China Key Laboratory of Radio Astronomy Chinese Academy of Sciences Xinjiang Urumqi830011 China Xinjiang Key Laboratory of Radio Astrophysics 150 Science1-Street Xinjiang Urumqi830011 China Zhejiang Lab Zhejiang Hangzhou311121 China Institute of Optoelectronic Technology Lishui University Lishui323000 China School of Astronomy and Space Science University of Chinese Academy of Sciences Beijing100049 China School of Physics Peking University Beijing100871 China

We present the discovery and timing results of four pulsars discovered in a pilot survey at intermediate Galactic latitudes with the Five-hundred Aperture Spherical Telescope (FAST). Among these pulsars, two belong to the category of millisecond pulsars (MSPs) with spin periods of less than 20 ms. The other two fall under the classification of "mildly recycled" pulsars, with massive white dwarfs as companions. Remarkably, this small survey, covering an area of 4.7 deg2, led to the discovery of four recycled pulsars. Such success underscores the immense potential of future surveys at intermediate Galactic latitudes. In order to assess the potential yield of MSPs, we conducted population simulations and found that both FAST and Parkes new phased array feed surveys, focusing on intermediate Galactic latitudes, have the capacity to uncover several hundred new MSPs. Copyright © 2023, The Authors. All rights reserved.

关键词： Pulsars

Generalized association and deep understanding method for big video data processing

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Generalized association and deep understanding method for bi...

2019 IEEE International Conferences on Ubiquitous computing and Communications and Data Science and Computational Intelligence and Smart computing, Networking and Services, IUCC/DSCI/SmartCNS 2019

作者： Xu, Lin Wu, Wei Lv, Wanghan Wang, Dong Science and Technology in Information System Engineering Lab Nanjing Research Institute of Electronic Engineering Nanjing China School of Information Science and Engineering University of Jinan China Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan China

ISBN: (纸本)9781728152097

In Big Data Era, it is becoming more and more important to timely and efficient processing of massive videos, and mining of the value information contained in them. This paper studies chaotic compressed sensing theory and uses Long-term and short-term memory networks (LSTM) algorithm to generate a summary of the content of video behavior track. It has already to apply the proposed method in target recognition and tracking, and the recognition rate achieves more than 86%. © 2019 IEEE.

关键词： Big data

DessiLBI: Exploring Structural Sparsity of Deep Networks via Differential Inclusion Paths

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arXiv 2020年

作者： Fu, Yanwei Liu, Chen Li, Donghao Sun, Xinwei Zeng, Jinshan Yao, Yuan School of Data Science MOE Frontiers Center for Brain Science Shanghai Key Lab of Intelligent Information Processing Fudan University Hong Kong University of Science and Technology Hong Kong Microsoft Research-Asia Jiangxi Normal University

Over-parameterization is ubiquitous nowadays in training neural networks to benefit both optimization in seeking global optima and generalization in reducing prediction error. However, compressive networks are desired in many real world applications and direct training of small networks may be trapped in local optima. In this paper, instead of pruning or distilling over-parameterized models to compressive ones, we propose a new approach based on differential inclusions of inverse scale spaces. Specifically, it generates a family of models from simple to complex ones that couples a pair of parameters to simultaneously train over-parameterized deep models and structural sparsity on weights of fully connected and convolutional layers. Such a differential inclusion scheme has a simple discretization, proposed as Deep structurally splitting Linearized Bregman Iteration (DessiLBI), whose global convergence analysis in deep learning is established that from any initializations, algorithmic iterations converge to a critical point of empirical risks. Experimental evidence shows that DessiLBI achieve comparable and even better performance than the competitive optimizers in exploring the structural sparsity of several widely used backbones on the benchmark datasets. Remarkably, with early stopping, DessiLBI unveils "winning tickets" in early epochs: the effective sparse structure with comparable test accuracy to fully trained overparameterized models. Copyright © 2020, The Authors. All rights reserved.

关键词： Differential equations

False news detection on social media

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arXiv 2019年

作者： Cao, Juan Sheng, Qiang Qi, Peng Zhong, Lei Wang, Yanyan Zhang, Xueyao Key Laboratory of Intelligent Information Processing Center for Advanced Computing Research Institute of Computing Technology CAS Beijing China University of Chinese Academy of Sciences Beijing China

Social media has become an important information platform where people consume and share news. However, it has also enabled the wide dissemination of false news, i.e., news posts published on social media that are verifiably false, causing significant negative effects on society. To help prevent further propagation of false news on social media, we set up this competition to motivate the development of automated real-time false news detection approaches. Specifically, this competition includes three subtasks: false-news text detection, false-news image detection, and falsenews multi-modal detection, which aims to motivate participants to further explore the efficiency of multiple modalities in detecting false news and effective fusion approaches of multi-modal contents. To better support this competition, we also construct and release a multi-modal data repository about False News on Weibo Social platform(MCG-FNeWS) to help evaluate the performance of different approaches from participants. Copyright © 2019, The Authors. All rights reserved.

关键词： Social networking (online)

Analysis of impact of environmental wind on motion characteristics of hovercraft 29th

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Analysis of impact of environmental wind on motion character...

29th International Ocean and Polar Engineering Conference, ISOPE 2019

作者： Yan, Chuanxu Gao, Song Huo, Yiqun Marine Design & Research Institute of China Shanghai China Shanghai Zhongchuan Nerc-sdt Co. LTD Fudan University China Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University China

ISBN: (纸本)9781880653852

During the voyage of hovercraft, the bottom air cushion lifts the hull completely out of the water, which allows hovercraft to sail above air-water interface. Therefore, hovercraft has the advantages of high speed, obstacle crossing capability, small underwater physical field, etc. However, it also has some disadvantages, such as great interference effect on environmental wind and poor resisting wind ability, etc. The lateral drift and other motion characteristics are usually occur. In addition, the air propeller thrust and air rudder effect of hovercraft are closely related to wind speed and wind direction, which directly affect the speed and maneuverability of hovercraft. It is necessary to study the effect of wind on hovercraft under various navigational status, so as to provide theoretical guidance of maneuvering for operators. In this paper, one type of hovercraft is selected as the object of study. Based on the theoretical model of four-degree-of-freedom maneuvering motion and the test results of the full-scale hovercraft, through analyzing characteristics of the motion parameter change during high speed sailing and mechanic rotation in downwind, headwind and crosswind, the influence of environmental wind on motion characteristics of this type of hovercraft is derived. The results show that the environmental wind has a great influence on the motion of hovercraft during high speed sailing. It not only directly reflects the influence on the speed, but also greatly changes the turning diameter of hovercraft. With the influence of the headwind and crosswind, it may be difficult to turn and significant lateral drift might occur for the hovercraft, which should be paid close attention to by operators. © 2019 by the International Society of Offshore and Polar Engineers (ISOPE).

关键词： Degrees of freedom (mechanics)

Large language models for diabetes training:a prospective study

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Science Bulletin 2025年第6期70卷 934-942页

作者： Haoxuan Li Zehua Jiang Zhouyu Guan Yuqian Bao Yuexing Liu Tingting Hu Jiajia Li Ruhan Liu Liang Wu Di Cheng Hongwei Ji Yong Wang Ya-Xing Wang Carol Y.Cheung Yingfeng Zheng Jihong Wang Zhen Li Weibing Wu Cynthia Ciwei Lim Yong Mong Bee Hong Chang Tan Elif I.Ekinci David C.Klonoff Justin B.Echouffo-Tcheugui Nestoras Mathioudakis Leonor Corsino Rafael Simó Charumathi Sabanayagam Gavin Siew Wei Tan Ching-Yu Cheng Tien Yin Wong Huating Li Chun Cai Lijuan Mao Lee-Ling Lim Yih-Chung Tham Bin Sheng Weiping Jia Shanghai University of Sport Shanghai 200438China School of Clinical Medicine Beijing Tsinghua Changgung HospitalTsinghua MedicineTsinghua UniversityBeijing 100084China Beijing Visual Science and Translational Eye Research Institute(BERI) Tsinghua MedicineTsinghua UniversityBeijing 100084China Shanghai Belt and Road International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases Department of Computer Science and EngineeringSchool of ElectronicInformationand Electrical EngineeringShanghai Jiao Tong UniversityDepartment of Endocrinology and MetabolismShanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai Diabetes InstituteShanghai Clinical Center for DiabetesShanghai 200240China MoE Key Lab of Artificial Intelligence Artificial Intelligence InstituteShanghai Jiao Tong UniversityShanghai 200240China Department of Cardiology the Affiliated Hospital of Qingdao UniversityQingdao 266011China CEMS NCMISHCMSMADISAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematics University of Chinese Academy of SciencesChinese Academy of SciencesBeijing 100049China Key Laboratory of Systems Health Science of Zhejiang Province School of Life ScienceHangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China Beijing Institute of Ophthalmology Beijing Tongren HospitalCapital Medical UniversityBeijing Ophthalmology and Visual Sciences Key LaboratoryBeijing 100730China k.Department of Ophthalmology and Visual Sciences The Chinese University of Hong KongHong Kong 999077China State Key Laboratory of Ophthalmology Zhongshan Ophthalmic CenterSun Yat-sen UniversityGuangdong Provincial Key Laboratory of Ophthalmology and Visual ScienceGuangdong Provincial Clinical Research Center for Ocular DiseasesGuangzhou 510060China Department of Renal Medicine Singapore General HospitalSingHealth-Duke Academic Medical CentreSingapore169

Diabetes poses a considerable global health challenge,with varying levels of diabetes knowledge among healthcare professionals,highlighting the importance of diabetes *** Language Models(LLMs)provide new insights into diabetes training,but their performance in diabetes-related queries remains uncertain,especially outside the English language like *** first evaluated the performance of ten LLMs:ChatGPT-3.5,ChatGPT-4.0,Google Bard,LlaMA-7B,LlaMA2-7B,Baidu ERNIE Bot,Ali Tongyi Qianwen,MedGPT,HuatuoGPT,and Chinese LlaMA2-7B on diabetes-related queries,based on the Chinese National Certificate Examination for Primary Diabetes Care in China(NCE-CPDC)and the English Specialty Certificate Examination in Endocrinology and Diabetes of Membership of the Royal College of Physicians of the United ***,we assessed the training of primary care physicians(PCPs)without and with the assistance of ChatGPT-4.0 in the NCE-CPDC examination to ascertain the reliability of LLMs as medical *** found that ChatGPT-4.0 outperformed other LLMs in the English examination,achieving a passing accuracy of 62.50%,which was significantly higher than that of Google Bard,LlaMA-7B,and *** the NCE-CPFC examination,ChatGPT-4.0,Ali Tongyi Qianwen,Baidu ERNIE Bot,Google Bard,MedGPT,and ChatGPT-3.5 successfully passed,whereas LlaMA2-7B,HuatuoGPT,Chinese LLaMA2-7B,and LlaMA-7B ***-4.0(84.82%)surpassed all PCPs and assisted most PCPs in the NCE-CPDC examination(improving by 1%–6.13%).In summary,LLMs demonstrated outstanding competence for diabetes-related questions in both the Chinese and English language,and hold great potential to assist future diabetes training for physicians globally.

关键词： Diabetes Diabetestraining Largelanguagemodels Primarydiabetescare Prospectivestudy

Multi-granulation variable precision rough set based on limited tolerance relation

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2021年第3期83卷 63-74页

作者： Wan, Renxia Yao, Yonghong Kumar, Hussain School of Mathematics and Information Science North Minzu University Ningxia750021 China HongYang Institute for Big Data in Health Fuzhou Fujian350028 China School of Mathematical Sciences Tiangong University Tianjin300387 China The Key Laboratory of Intelligent Information and Data Processing of NingXia Province North Minzu University and Health Big Data Research Institute of North Minzu University Yinchuan750021 China Machine vision and pattern recognition lab University of Regina ReginaSKS4S0A2 Canada

In this paper, the combination of the variable precision rough set and the limited tolerance relation under multi-granularity is explored. As an extension of rough set model, Multi-granularity variable precision limited tolerance rough set model is con-structed. Properties of upper and lower approximation operator and detailed structure of object class through threshold are discussed. Theoretical proofs are given to show the rationality and superiority of the proposed model. © 2021, Politechnica University of Bucharest. All rights reserved.

关键词： Granulation

Neural quality estimation with multiple hypotheses for grammatical error correction

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arXiv 2021年

作者： Liu, Zhenghao Yi, Xiaoyuan Sun, Maosong Yang, Liner Chua, Tat-Seng Department of Computer Science and Technology Tsinghua University Beijing China Institute for Artificial Intelligence Tsinghua University Beijing China Beijing National Research Center for Information Science and Technology State Key Lab on Intelligent Technology and Systems Tsinghua University Beijing China Beijing Academy of Artificial Intelligence Beijing Language and Culture University Beijing China School of Computing National University of Singapore Singapore

Grammatical Error Correction (GEC) aims to correct writing errors and help language learners improve their writing skills. However, existing GEC models tend to produce spurious corrections or fail to detect lots of errors. The quality estimation model is necessary to ensure learners get accurate GEC results and avoid misleading from poorly corrected sentences. Well-trained GEC models can generate several high-quality hypotheses through decoding, such as beam search, which provide valuable GEC evidence and can be used to evaluate GEC quality. However, existing models neglect the possible GEC evidence from different hypotheses. This paper presents the Neural Verification Network (VERNet) for GEC quality estimation with multiple hypotheses. VERNet establishes interactions among hypotheses with a reasoning graph and conducts two kinds of attention mechanisms to propagate GEC evidence to verify the quality of generated hypotheses. Our experiments on four GEC datasets show that VERNet achieves state-of-the-art grammatical error detection performance, achieves the best quality estimation results, and significantly improves GEC performance by reranking hypotheses. All data and source codes are available at https://***/thunlp/VERNet. Copyright © 2021, The Authors. All rights reserved.

关键词： Error correction

Open-world Weakly-Supervised Object Localization

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Pattern Recognition 2026年 169卷

作者： Jinheng Xie Zhaochuan Luo Rouyi Li Yawen Huang Haozhe Liu Yuexiang Li Yefeng Zheng Yang Zhang Linlin Shen Mike Zheng Shou Computer Vision Institute School of Artificial Intelligence Shenzhen University Shenzhen 518060 China Guangdong Provincial Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen 518060 China The Jarvis Research Center Tencent YouTu Lab Shenzhen 518057 China National University of Singapore Singapore 639798 Singapore Shenzhen Power Supply Bureau Co. Ltd. ShenZhen 518000 China

While remarkable success has been achieved in weakly supervised object localization (WSOL), current frameworks are not capable of locating objects of novel categories in open-world settings. To address this issue, we are the first to introduce a new weakly supervised object localization task called Open-world Weakly Supervised Object Localization ( OWSOL ). During training, all labeled data comes from known categories and, both known and novel categories exist in the unlabeled data. To handle such data, we propose a novel paradigm of contrastive representation co-learning using both labeled and unlabeled data to perform Generalized Class Activation Mapping ( GCAM ) for object localization, without the requirement of bounding box annotation. As no class label is available for the unlabeled data, we conduct clustering over the full training set and design a novel multiple semantic centroids-driven contrastive loss for representation learning. We re-organize two widely used datasets, i.e., ImageNet-1K and iNatLoc500, and propose OpenImages150 to serve as evaluation benchmarks for OWSOL. Extensive experiments demonstrate that the proposed method can surpass all baselines by a large margin. We believe that this work can shift the close-set localization towards the open-world setting and serve as a foundation for subsequent works. The code and dataset are available at https://***/ryylcc/OWSOL .

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