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arXiv 2024年

作者： Fu, Xingcheng Gao, Yisen Wei, Yuecen Sun, Qingyun Peng, Hao Li, Jianxin Li, Xianxian Key Lab of Education Blockchain and Intelligent Technology Ministry of Education Guangxi Normal University Guilin China Institute of Artificial Intelligence Beihang University Beijing China School of Software Beihang University Beijing China Beijing Advanced Innovation Center for Big Data and Brain Computing School of Computer Science and Engineering Beihang University Beijing China

Diffusion models have made significant contributions to computer vision, sparking a growing interest in the community recently regarding the application of them to graph generation. Existing discrete graph diffusion models exhibit heightened computational complexity and diminished training efficiency. A preferable and natural way is to directly diffuse the graph within the latent space. However, due to the non-Euclidean structure of graphs is not isotropic in the latent space, the existing latent diffusion models effectively make it difficult to capture and preserve the topological information of graphs. To address the above challenges, we propose a novel geometrically latent diffusion framework HypDiff. Specifically, we first establish a geometrically latent space with interpretability measures based on hyperbolic geometry, to define anisotropic latent diffusion processes for graphs. Then, we propose a geometrically latent diffusion process that is constrained by both radial and angular geometric properties, thereby ensuring the preservation of the original topological properties in the generative graphs. Extensive experimental results demonstrate the superior effectiveness of HypDiff for graph generation with various topologies. Copyright © 2024, The Authors. All rights reserved.

关键词： Topology

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Social science Is Necessary for Operationalizing Socially Responsible Foundation Models

arXiv

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arXiv 2024年

作者： Davies, Adam Nguyen, Elisa Simeone, Michael Johnston, Erik Gubri, Martin Siebel School of Computing and Data Science The Grainger College of Engineering University of Illinois Urbana-Champaign United States Tübingen AI Center University of Tübingen Germany School of Complex Adaptive Systems Arizona State University United States School for the Future of Innovation in Society Arizona State University United States Parameter Lab Germany

With the rise of foundation models, there is growing concern about their potential social impacts. Social science has a long history of studying the social impacts of transformative technologies in terms of pre-existing systems of power and how these systems are disrupted or reinforced by new technologies. In this position paper, we build on prior work studying the social impacts of earlier technologies to propose a conceptual framework studying foundation models as sociotechnical systems, incorporating social science expertise to better understand how these models affect systems of power, anticipate the impacts of deploying these models in various applications, and study the effectiveness of technical interventions intended to mitigate social harms. We advocate for an interdisciplinary and collaborative research paradigm between AI and social science across all stages of foundation model research and development to promote socially responsible research practices and use cases, and outline several strategies to facilitate such research. Copyright © 2024, The Authors. All rights reserved.

关键词： Music

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data-mechanism-driven Product Performance Optimization with Multiple Parameters Under Uncertainties in Manufacturing Automation Systems

Data-mechanism-driven Product Performance Optimization with ...

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IEEE International Conference on Automation science and engineering (CASE)

作者： Kaiyue Cui Zhaoxi Hong Xiuju Song Mengchu Zhou Zhiwu Li Yixiong Feng Jianrong Tan State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou China Ningbo Innovation Center Zhejiang University Ningbo China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA Institute of Systems Engineering Macau University of Science and Technology Macau China State Key Laboratory of Public Big Data Guizhou University Guiyang China

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

High-end equipment with robust and excellent performance is of great significance to manufacturing automation systems. Product parameters are the foundation of performance. Usually, there is a lack of clear physical models to reveal the relationship between parameters and performance. Simulation is an important way to understand the design results of product performance parameters. However, simulations are often particularly time and resource-consuming. To address these issues, this work proposes a data-mechanism-driven product performance optimization method, which introduces Taguchi' method, nonparametric correlation testing, and multiple attribute decision making (MADM), to efficiently obtain the optimal parameter scheme. A novel MADM method is designed, which is combined with the Multi-Objective Optimization on the basis of a Ratio Analysis plus the full MULTIplicative form (MULTIMOORA) and the Variable Neighborhood Search. It has been proven that it performs better than the MULTIMOORA based on the well-known Simulated Annealing and Tabu search. Finally, taking the cutting unit of EBZ200i as a case study, we have successfully obtained the optimal parameter scheme that comprehensively performs better in terms of wear performance, robustness, and environmental economic performance.

关键词： Uncertainty Correlation Computer aided software engineering Decision making Simulated annealing Robustness Environmental economics Optimization Manufacturing automation Testing

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FincGAN: A Gan Framework of Imbalanced Node Classification on Heterogeneous Graph Neural Network

FincGAN: A Gan Framework of Imbalanced Node Classification o...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Hung Chun Hsu Ting-Le Lin Bo-Jun Wu Ming-Yi Hong Che Lin Chih-Yu Wang Graduate Program of Data Science National Taiwan University and Academia Sinica Taiwan Department of Accounting and Statistics National ChengChi University Taiwan Department of Risk Management and Insurance National ChengChi University Taiwan Department of Electrical Engineering National Taiwan University Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan Research Center for Information Technology Innovation Academia Sinica Taiwan

Graph Neural Networks (GNNs) frequently face class imbalance issues, especially in heterogeneous graphs. Existing GNNs often assume balanced class sizes, which isn’t true in many cases. Applying them directly to imbalanced data can lead to sub-optimal performance. Traditional oversampling methods, while effective, risk overfitting and face difficulties in reintegrating synthetic samples into the original graph. In this study, we introduce Framework of Imbalanced Node Classification on heterogeneous graph neural network with GAN (FincGAN), a new framework that utilizes oversampling techniques to address class imbalance in heterogeneous graphs. Instead of duplicating existing samples, FincGAN employs a Generative Adversarial Network (GAN) to create synthetic samples and uses deep learning-based edge generators to connect them back to the original graph. Our evaluations on spam user detection in the Amazon and Yelp Review datasets show that FincGAN outperforms baseline models in all essential metrics, including F-score and AUC-PRC score, showing its effectiveness in addressing class imbalance.

关键词：

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Measurement-device-independent quantum key distribution protocol with phase post-selection

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Photonics Research 2022年第7期10卷 1703-1711页

作者： CONG JIANG XIAO-LONG HU ZONG-WEN YU XIANG-BIN WANG Jinan Institute of Quantum Technology Jinan 250101China State Key Laboratory of Low Dimensional Quantum Physics Department of PhysicsTsinghua UniversityBeijing 100084China School of Physics State Key Laboratory of Optoelectronic Materials and TechnologiesSun Yat-sen UniversityGuangzhou 510275China Data Communication Science and Technology Research Institute Beijing 100191China Shanghai Branch CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum PhysicsUniversity of Science and Technology of ChinaShanghai 201315China Shenzhen Institute for Quantum Science and Engineering and Physics DepartmentSouthern University of Science and TechnologyShenzhen 518055China Frontier Science Center for Quantum Information BeijingChina

Measurement-device-independent quantum key distribution(MDI-QKD)protocol can remove all the loopholes of the detection devices and,thus,has attracted much *** on the technique of single-photon interference,we propose a modified MDI-QKD protocol with phase *** prove the security of the announcement of the private phases in the X basis and show how to apply the phase post-selection method to the double-scanning four-intensity MDI-QKD *** numerical results show that the phase postselection method can significantly improve the key rates at all *** the double-scanning method,two parameters need to be scanned in the calculation of the final key rate,and the global parameter optimization is pretty *** propose an accelerated method that can greatly reduce the running time of the global parameter optimization *** makes the method practically useful in an unstable channel.

关键词： distribution phase quantum

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Game-Theoretic Analysis on CBDC Adoption 1st

Game-Theoretic Analysis on CBDC Adoption

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1st BenchCouncil International Federated Intelligent Computing and Block Chain Conferences, FICC 2020

作者： Mou, Chenqi Tsai, Wei-Tek Jiang, Xiaofang Yang, Dong LMIB – School of Mathematics and Systems Science Beihang University Beijing100191 China SKLSDE – School of Computer Science and Engineering Beihang University Beijing100191 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe United States

ISBN: (纸本)9789811611599

As an important blockchain application, CBDC (Central Bank Digital Currency) has received significant worldwide attention as it can restructure financial market, affect national currency policies, and introduce new regulation policies and mechanisms. It is widely predicted that CBDC will introduce numerous digital currency competitions in various aspects of the global financial market, and winners will lead the next wave of digital currency market. This paper applies the game theory to study the competitions between different countries, in particular to analyze whether they should adopt the CBDC program. We propose two game-theoretic models for CBDC adoption, both analyzing whether to adopt the CBDC program via the Nash equilibrium. Both game-theoretic models draw the same conclusion that each country should adopt the CBDC program regardless of the choices of other counties. In other words, current currency leaders should adopt CBDC because it may lose the premier status, and other countries should adopt CBDC otherwise they risk of getting even further behind in the digital economy. According to our game-theoretic models, the current market leader who has 90% of market shares may lose about 19.2% shares if it is not the first mover. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Game theory

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Research on Layout Optimization in Complex Environments Based on Genetic Algorithm 14th

Research on Layout Optimization in Complex Environments Base...

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14th International Conference on Computer engineering and Networks, CENet 2024

作者： Cai, Daomeng Yang, Lin Wang, Chao Wang, Can Tong, Yue Sun, Hao Wu, Hao Lyu, Ting Beihang University No. 37 Xueyuan Road Haidian District Beijing China Systems Engineering Research Institute China State Shipbuilding Corporation No. 1 Fengxian East Road Haidian District Beijing China School of Physics University of Electronic Science and Technology of China Chengdu 610054 China Department of Medical Engineering Medical Supplies Center of Chinese PLA General Hospital 28 Fuxing Road Beijing 100853 China Medical Innovation Research Division Chinese PLA General Hospital 28 Fuxing Road Beijing 100853 China Medical Big Data Research Center Chinese PLA General Hospital 28 Fuxing Road Beijing 100853 China

ISBN: (纸本)9789819642281

In fields such as manufacturing, logistics, and communication networks, equipment layout optimization is a significant and prevalent issue. This paper investigates an equipment layout optimization method in complex environments based on a genetic algorithm (CE-GA). Initially, we formulate the layout optimization problem mathematically, defining the optimization objectives and constraints. Subsequently, we propose and improve the GA, incorporating initial population generation, fitness function design, selection, crossover, mutation operations, and elite retention strategy. Experiments validate the superiority of this method in terms of convergence speed and solution quality, comparing it with simulated annealing (SA) and particle swarm optimization (PSO) algorithms. The experimental results demonstrate that the improved GA performs excellently in handling layout optimization problems in complex environments. Finally, this paper summarizes the research findings, highlights contributions and limitations, and suggests future research directions. This study has significant practical implications for improving system efficiency and reducing operational costs, providing a valuable reference for future layout optimization research. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Complex Environment Convergence Speed Fitness Function Genetic Algorithm Layout Optimization

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Machine learning-based prediction model for sports injury risk in biomechanics: A case study of joint injuries in basketball at a university in Xi’an

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MCB Molecular and Cellular Biomechanics 2024年第4期21卷

作者： Min, Liang Li, Nan Bi, Peng Gao, Bo School of Computer Science Xi’an Jiaotong University City College Xi’an710018 China The Youth Innovation Team of Shaanxi Universities "Multi-modal Data Mining and Fusion" Xi’an710018 China Engineering Research Center of IoT Intelligent Sensing Interactive Platform Universities of Shaanxi Province Xi’an710018 China School of Electrical and Information Engineering Xi’an Jiaotong University City College Xi’an710018 China DHC Software Co. Ltd. Xi’an710000 China

Basketball players are prone to joint injuries due to the sport’s high intensity and physical demands. Early prediction of injury risk is crucial for implementing effective prevention strategies. Incorporating biomechanics, this study focuses on basketball players at a university in Xi’an, China, aiming to develop a machine learning-based model to predict joint injury risk using easily collectable data such as training load, fatigue levels, and previous injury history. Considering regional differences, we observed that local and northern Chinese students are generally taller, while students from southern China are typically shorter. This anthropometric variation was included in our sampling and analysis. Utilizing data from 100 basketball players, the Random Forest algorithm achieved the best predictive performance with an accuracy of 85%. Key risk factors identified include high training load, elevated subjective fatigue scores, and a history of previous joint injuries. Additionally, biomechanical data were integrated to elucidate the underlying mechanisms of joint injuries, and the cellular responses to injury were explored. The results demonstrate that even with limited data types, machine learning methods can effectively predict joint injury risk among basketball players, providing a valuable tool for injury prevention. © 2024 by author(s).

关键词： Prediction models

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Effect of Nitrate-Reducing-Bacteria on Stress Corrosion Cracking Behavior of Simulated Heat-Affected Zone Microstructures of X80 Steel in a Near-Neutral Ph Solution

SSRN

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SSRN 2022年

作者： Liu, Bo Du, Cuiwei Liu, Zhiyong Li, Xiaogang Institute for Advanced Materials and Technology University of Science and Technology Beijing Beijing100083 China National Materials Corrosion Protection Scientific Data Center Beijing100083 China Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing Beijing100083 China

Stress corrosion cracking (SCC) behavior of X80 steel different heat-affected zone (HAZ) microstructures caused by nitrate reducing bacteria (NRB) in a near-neutral pH solution were studied. The results show that NRB has a significant effect on the corrosion rate and SCC sensitivity of coarse-grained HAZ (CGHAZ), compared with the intercritical HAZ and fine-grained HAZ. The mechanism suggests that CGHAZ has a higher surface work function, which is conducive to bacterial adhesion, and the microgalvanic corrosion between high and low stress contributes to more bacteria adhere to the adjacent transition region to obtain extracellular electrons. © 2022, The Authors. All rights reserved.

关键词： Stress corrosion cracking

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Model maturity towards modeling and simulation:Concepts,index system framework and evaluation method

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International Journal of Modeling, Simulation, and Scientific Computing 2020年第3期11卷 1-21页

作者： Lin Zhang Ying Liu Yuanjun Laili Weicun Zhang School of Automation Science and Electrical Engineering Beihang University(BUAA) Engineering Research Center of Complex Product Advanced Manufacturing Systems Ministry of EducationBeijing Advanced Innovation Center for Big Data-Based Precision Medicine Beijing 100191P.R.China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 P.R.China

Simulation has become an essential way and sometimes the only way to study complex systems(e.g.,system of systems,SoS).Simulation is the model-based *** to build a high-quality model is the first consideration in *** and credibility are the two mostly used metrics to evaluate the quality of a ***,the definitions and evaluation methods of fidelity and credibility vary from one research to another and it’s hard to evaluate the metrics *** importantly,the evolution process of a model in use cannot be directly reflected by the two ***,this paper introduces the model maturity to track the status of a model during its life cycle,especially in the use and management phases,which will be an important supplement to the quality evaluation system of *** concept of model maturity is given and a framework of index system for model maturity evaluation is ***,a hierarchical evaluation method based on qualitative and quantitative analysis(HEQQ)for model maturity is ***,a case study is used to validate the feasibility and effectiveness of the proposed method.

关键词： Modeling and simulation(M&S) model maturity index system evaluation method

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