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SSRN 2024年

作者： Li, Hongliang Wang, Zichen Zhao, Hairui Zhang, Meng Li, Xiang Xu, Haixiao College of Computer Science and Technology Jilin University Qianjin street 2699 Jilin Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering The Ministry of Education Qianjin street 2699 Jilin Changchun130012 China High Performance Computing Center Qianjin street 2699 Jilin Changchun130012 China

Training Deep Learning (DL) models are becoming more time-consuming, thus interruptions to the training processes are inevitable. Existing fault-tolerant work adopted checkpoint/recovery mechanism from traditional HPC platforms that makes periodical persistent copies of model states to save execution progress. These checkpoints have fixed time intervals that they are evenly placed across the training. We can obtain an optimal checkpointing interval for an HPC job with the precondition that the progress of a job is proportional to its execution time. Unfortunately, it is not the case in DL model training where a DL training job yields diminishing returns across its lifetime. It makes the early progress of a DL training job more valuable than the later ones. Even placement of checkpoints would either increase the risks in the early stages or waste resources overprotecting the latter stages. Meanwhile, the issue can get amplified for exploratory training jobs, where early terminations are common. Moreover, in data parallelism, the state-of-art quality-driven scheduling strategies allocate more resources for the early stages of a job than the later ones to accelerate the training progress which further amplifies the issue. This paper introduces a novel checkpointing interval problem for exploratory DL training jobs based on model convergence progress. We present COCI, an approach to compute optimal checkpointing configuration for a DL training job, minimizing the fault-tolerant overhead, including checkpointing cost and recovery cost. We implement COCI based on state-of-art iteration-level checkpointing mechanism, as a pluggable module compatible with PyTorch. COCI requires no extra user input. We conduct comprehensive evaluations with real DL application setups. The experimental results show that COCI reduces up to 40.18% fault-tolerant overhead compared to existing state-of-the-art DL fault-tolerant methods in serial scenario, 57.26% in data parallel scenario and 63.8

关键词： Iterative methods

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Characterizing Human Collective Behaviors During COVID-19 — Hong Kong SAR, China, 2020

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China CDC weekly 2023年第4期5卷 71-75,I0001-I0003页

作者： Zhanwei Du Xiao Zhang Lin Wang Sidan Yao Yuan Bai Qi Tan Xiaoke Xu Sen Pei Jingyi Xiao Tim K.Tsang Qiuyan Liao Eric H.YLau Peng Wu Chao Gao Benjamin J.Cowling WHO Collaborating Centre for Infectious Disease Epidemiology and Control School of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina Laboratory of Data Discovery for Health Hong Kong Science and Technology ParkNew TerritoriesHong Kong Special Administrative RegionChina Department of Genetics University of CambridgeCambridgeCB23EHUK Institute of High Performance Computing(IHPC) Agency for ScienceTechnology and Research(A*STAR)Singapore College of Information and Communication Engineering Dalian Minzu UniversityDalian CityLiaoning ProvinceChina Department of Environmental Health Sciences Mailman School of Public HealthColumbia UniversityNew York CityNYUSA School of Artificial Intelligence Opticsand Electronics(iOpen)Northwestern Polytechnical UniversityXi’an CityShaanxi ProvinceChina

Summary What is already known about this topic?People are likely to engage in collective behaviors online during extreme events,such as the coronavirus disease 2019(COVID-19)crisis,to express awareness,take action,and... 详细信息

关键词： collective likely extreme

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MedRG: Medical Report Grounding with Multi-modal Large Language Model

arXiv

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arXiv 2024年

作者： Zou, Ke Bai, Yang Chen, Zhihao Zhou, Yang Chen, Yidi Ren, Kai Wang, Meng Yuan, Xuedong Shen, Xiaojing Fu, Huazhu National Key Laboratory of Fundamental Science on Synthetic Vision Sichuan University Sichuan China College of Computer Science Sichuan University Sichuan China Institute of High Performance Computing A*STAR Singapore College of Intelligence and Computing Tianjin University Tianjin China Department of Radiology West China Hospital Sichuan University China Beth Israel Deaconess Medical Center Harvard Medical School Boston United States College of Mathematics Sichuan University Sichuan China

Medical Report Grounding is pivotal in identifying the most relevant regions in medical images based on a given phrase query, a critical aspect in medical image analysis and radiological diagnosis. However, prevailing visual grounding approaches necessitate the manual extraction of key phrases from medical reports, imposing substantial burdens on both system efficiency and physicians. In this paper, we introduce a novel framework—Medical Report Grounding (MedRG)—an end-to-end solution for utilizing a multi-modal Large Language Model to predict key phrase by incorporating a unique token, , into the vocabulary to serve as an embedding for unlocking detection capabilities. Subsequently, the vision encoder-decoder jointly decodes the hidden embedding and the input medical image, generating the corresponding grounding box. The experimental results validate the effectiveness of MedRG, surpassing the performance of the existing state-of-the-art medical phrase grounding methods. This study represents a pioneering exploration of the medical report grounding task, marking the first-ever endeavor in this domain. © 2024, CC BY.

关键词： Diagnosis

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Distributed Online Generalized Nash Equilibrium Tracking for Prosumer Energy Trading Games

Distributed Online Generalized Nash Equilibrium Tracking for...

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American Control Conference (ACC)

作者： Yongkai Xie Zhaojian Wang John Z.F. Pang Bo Yang Xinping Guan Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China Agency for Science Technology and Research (A*STAR) Institute of High Performance Computing (IHPC) Singapore Republic of Singapore

With the proliferation of distributed generations, traditional passive consumers in distribution networks are evolving into "prosumers", which can both produce and consume energy. Energy trading with the main grid or between prosumers is inevitable if the energy surplus and shortage exist. To this end, this paper investigates the peer-to-peer (P2P) energy trading market, which is formulated as a generalized Nash game. We first prove the existence and uniqueness of the generalized Nash equilibrium (GNE). Then, an distributed online algorithm is proposed to track the GNE in the time-varying environment. Its regret is proved to be bounded by a sublinear function of learning time, which indicates that the online algorithm has an acceptable accuracy in practice. Finally, numerical results with six microgrids validate the performance of the algorithm.

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MediFind - A Medicine Detection Framework for Vietnamese Medical Prescription

MediFind - A Medicine Detection Framework for Vietnamese Med...

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Advanced computing and Analytics (ACOMPA), International Conference on

作者： Khanh Le Bao Toai Tran Hoang Cong Thu Nguyen Hoang Anh Minh Vo Duc Thanh Hoang Le Hai Nam Thoai High Performance Computing Laboratory Advanced Institute of Interdisciplinary Science and Technology Faculty of Computer Science and Engineering Ho Chi Minh City University of Technology (HCMUT) Ho Chi Minh City Vietnam Vietnam National University Ho Chi Minh City Ho Chi Minh City Vietnam

The pharmaceutical industry in Vietnam faces a significant challenge due to the time-consuming and inaccurate manual operational protocols. This results in incorrect pharmaceutical administration and antibiotic resistance, seriously affecting patient health. However, the implementation of Optical Character Recognition (OCR) can help automate the extraction of medication information from prescriptions, leading to stream-lined drug administration and reduced errors. In this study, drug misuse patterns are analyzed, a novel method for extracting medication names from Vietnamese prescriptions is introduced, and an app named “MediFind” is created to enhance accessibility. This innovative solution enhances pharmaceutical practices and streamlines drug administration.

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Deviation Backfilling: A Robust Backfilling Scheme for Improving the Efficiency of Job Scheduling on high performance computing Systems

Deviation Backfilling: A Robust Backfilling Scheme for Impro...

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Advanced computing and Analytics (ACOMPA), International Conference on

作者： Thanh Hoang Le Hai Khang Nguyen Duy Thin Nguyen Manh Danh Mai Hoang Nam Thoai High Performance Computing Laboratory Faculty of Computer Science and Engineering Advanced Institute of Interdisciplinary Science and Technology Ho Chi Minh City University of Technology (HCMUT) Ho Chi Minh City Vietnam Vietnam National University Ho Chi Minh City Ho Chi Minh City Vietnam

The Big Data era has led to the rapid development of modern sciences. Making effective use of extremely large amounts of collected data is putting extremely urgent demands on high performance computing (HPC) systems, especially the resource allocation process, which is commonly managed by the job scheduler. Despite the potential for improved scheduling outcomes offered by modern algorithms, these systems still continue to favor the FCFS and EASY backfilling approach due to its straightforward implementation and fair resource allocation. In this paper, we propose a novel and robust backfilling scheme called Deviation Backfilling to enhance the efficiency of job scheduling on HPC systems while maintaining user fairness. Combined with the job runtime prediction method using kNN, the Deviation Backfilling uses the deviation between user estimates and system prediction as the delay threshold for the first job at the backfilling queue. Our experimental results show that Deviation Backfilling outperforms existing scheduling strategies regarding performance metrics on real-world datasets. This performance improvement also signifies the capability to motivate users to offer more accurate estimates for assisting the HPC scheduling procedures.

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Soccer match broadcast video analysis method based on detection and tracking

Soccer match broadcast video analysis method based on detect...

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作者： Li, Hongyu Yang, Meng Yang, Chao Kang, Jianglang Suo, Xiang Meng, Weiliang Li, Zhen Mao, Lijuan Sheng, Bin Qi, Jun School of Information science and Technology Beijing Forestry University Beijing China Engineering Research Center for Forestry-Oriented Intelligent Information Processing National Forestry and Grassland Administration Beijing China School of Athletic Performance Shanghai University of Sport Shanghai China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Department of Computer Science and Engineering Shanghai Jiao Tong Univerity Shanghai China Department of Computing Xi'an JiaoTong-Liverpool University Suzhou China

We propose a comprehensive soccer match video analysis pipeline tailored for broadcast footage, which encompasses three pivotal stages: soccer field localization, player tracking, and soccer ball detection. Firstly, we introduce sports camera calibration to seamlessly map soccer field images from match videos onto a standardized two-dimensional soccer field template. This addresses the challenge of consistent analysis across video frames amid continuous camera angle changes. Secondly, given challenges such as occlusions, high-speed movements, and dynamic camera perspectives, obtaining accurate position data for players and the soccer ball is non-trivial. To mitigate this, we curate a large-scale, high-precision soccer ball detection dataset and devise a robust detection model, which achieved the (Formula presented.) of 80.9%. Additionally, we develop a high-speed, efficient, and lightweight tracking model to ensure precise player tracking. Through the integration of these modules, our pipeline focuses on real-time analysis of the current camera lens content during matches, facilitating rapid and accurate computation and analysis while offering intuitive visualizations. © 2024 John Wiley & Sons Ltd.

关键词： Visualization

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Enabling Efficient Real-Time Requirements Inconsistency Detection for Safety-Critical Systems

Enabling Efficient Real-Time Requirements Inconsistency Dete...

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IEEE International Requirements Engineering Conference Workshops (REW)

作者： Yike Huang Xiaohong Chen Zhi Jin Tingliang Zhou Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China Key Laboratory of High-Confidence Software Technologies Ministry of Education Peking University China Department of Computer Science and Technology Peking University Beijing China CASCO Signal Ltd. Shanghai China

ISBN: (数字)9798350395518

ISBN: (纸本)9798350395525

The importance of real-time requirements inconsistency detection is increasingly manifested in safety -critical system development. Most existing tools use state-based detection methods for real-time requirements verification, but they sometimes struggle to efficiently detect results when faced with complex system requirements. Moreover, adding device properties into the verification has increased the complexity of the state space. As a complementary, in this paper, we present a lightweight efficient method for real-time requirements existence inconsistency detection for safety-critical systems. We reduce the real-time existential inconsistencies detection problem into a constraint solving problem. The real-time requirements and involved device properties are encoded into SMT formulas, which can be detected quickly by using a constraint solver such as Z3. Through a case study and experimental evaluation, it is shown that our method can efficiently detect real-time existential inconsistencies in requirements. This provides a practical solution to detect certain types of errors in the early stage, avoiding possible future expensive costs.

关键词： Costs Conferences Real-time systems Safety Complexity theory Requirements engineering Complex systems

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Probing dynamics and ion structuring of imidazolium ionic liquid confined at charged graphene surfaces using graphene colloid probe AFM

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摩擦（英文版） 2025年第6期13卷 151-161页

作者： Muqiu Wu Zhongyang Dai Fan Zhang Faiz Ullah Shah Enrico Gnecco Yijun Shi Braham Prakash Rong An School of Materials Science and Engineering/Herbert Gleiter Institute of Nanoscience Nanjing University of Science and TechnologyNanjing 210094China State Key Laboratory of Solid Lubrication Lanzhou Institute of Chemical PhysicsChinese Academy of SciencesLanzhou 730000China Shandong Laboratory of Advanced Materials and Green Manufacturing at Yantai Yantai 264006China High Performance Computing Department National Supercomputing Center in ShenzhenShenzhen 518055China Department of Engineering and Design School of Engineering and InformationUniversity of SussexBrighton BN1 9RHUK Chemistry of Interfaces Luleå University of TechnologyLuleå 97187Sweden Marian Smoluchowski Institute of Physics Jagiellonian UniversityKrakow 30-348Poland Division of Machine Elements Luleå University of TechnologyLuleå 97187Sweden School of Materials Science and Engineering/Herbert Gleiter Institute of Nanoscience Nanjing University of Science and TechnologyNanjing 210094China Shandong Laboratory of Advanced Materials and Green Manufacturing at Yantai Yantai 264006China

Driven by the potential applications of ionic liquid(IL)flow for charging graphene-based surfaces in many emerging technologies,recent research efforts have focused on understanding ion dynamics and structuring at IL-graphene ***,graphene colloid probe(GrP)atomic force microscopy(AFM)was used to probe the dynamics and ion structuring of 1-butyl-3-methylimidazolium tetrafluoroborate at graphene surfaces under various bias *** particular,the AFM-measured nanofriction provides a good measure of the dynamic properties of the ILs at graphene *** with the IL at the unbiased graphene surface(0 V),the charged graphene surfaces with either negative(-1,-2 V)or positive(+1,+2 V)voltages favor a reduction in the friction coefficient by the IL.A higher magnitude of the bias voltage applied on the graphene surface with either sign(-2 or+2 V)results in a smaller friction coefficient than that at-1 and+1 *** combination with the AFM-probed contact stiffness,adhesion forces,and ion structuring force curves with an ion orientational distribution according to molecular dynamics(MD)simulations,we discovered that the unbiased graphene surface(0 V)possesses randomly structured IL ions and that the graphene colloid probe is more likely to become stuck,resulting in more energy dissipation to contribute to a larger friction *** of the graphene surface under either negative or positive voltages resulted in uniformly arranged ions,which produced a more ordered ion structure and,thus,a smoother sliding plane to reduce the friction *** impedance spectroscopy(EIS)for the IL with graphene as an electrode demonstrated a greater ionic conductivity in the IL paired with the biased graphene than in the unbiased one,implying faster ion movement at the charged graphene,which is beneficial for reducing the friction coefficient.

关键词： nanofriction graphene charge ionic liquid(IL) IL arrangement simulation

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Modeling Neural Networks Training Process with Markov Decision Process 2

Modeling Neural Networks Training Process with Markov Decisi...

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2nd International Conference on Artificial Intelligence and computer Engineering, ICAICE 2021

作者： Bai, Yantao Liu, Wanwei Mao, Xinjun Liang, Zhen National University of Defense Technology Key Laboratory of Software Engineering for Complex Systems Changsha China College of Computer Science National University of Defense Technology Changsha China Institute for Quantum Information National University of Defense Technology State Key Laboratory of High Performance Computing Changsha China

ISBN: (纸本)9781665421867

With the development of computer technology, statistics-based machine learning method has made great break-throughs, and also improved the development of artificial intelligence. Nevertheless, as a very influential model, neural networks are still treated as 'black boxes'. The results of neural networks are extremely sensitive to the training samples, which lead to great challenges to the controllability of the algorithm. With the wide application of machine learning, demand for interpretability and controllability of neural networks algorithms is increasing. As a result, various scholars have tried to explain and verify neural networks algorithms based on formal methods in recent years. In this paper, a method (called MNNTP) is presented to model the training process of neural networks by using a Markov decision process (MDP). Through MNNTP, the neural networks are abstracted into the form of MDP, which makes notable contributions for verifying some mathematical properties of the neural networks. © 2021 IEEE.

关键词： Markov processes

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