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13th IEEE Data Driven Control and Learning systems Conference, DDCLS 2024

作者： He, Zhichen Liang, Dingguo Yang, Ying College of Engineering Peking University State Key Lab for Turbulence and Complex Systems Department of Mechanics and Engineering Science Beijing100871 China

ISBN: (纸本)9798350361674

In this brief, an accelerated data-driven cooperative distributed predictive control approach with the cloud-edge-end collaboration implemented is proposed for the finishing rolling system(FRS) of the hot strip mill process. Specifically, in the end device, the operating data of the rolling mill stands and looper systems are collected and uploaded to the cloud server, which contributes to satisfying the interconnected information communication requirements for optimization problem-solving. Then, the control optimization problem is quickly solved in the cloud server, where the cooperative distributed solving method is applied, and an accelerated iteration strategy is adopted. Moreover, a regularized optimization technique is used to suppress the interference of disturbance and noise. Thus, the edge device can set the input of the bottom-level control to realize the control of the finishing rolling system with the optimal control sequences sent from the cloud server. Finally, simulations on a real finishing rolling system are conducted to illustrate the effectiveness of the proposed method. © 2024 IEEE.

关键词： Predictive control systems

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Non-Invasive Self-Adaptive Information States'Acquisition inside Dynamic Scattering Spaces

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Research 2025年第1期2024卷 346-355页

作者： Ruifeng Li Jinyan Ma Da Li Yunlong Wu Chao Qian Ling Zhang Hongsheng Chen Tsampikos Kottos Er-Ping Li Zhejiang University-University of Illinois at Urbana-Champaign Institute Zhejiang UniversityHaining 314400China College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou 310027China Wave Transport in Complex Systems Lab Department of PhysicsWesleyan UniversityMiddletownCT 06459USA.

Pushing the information states'acquisition efficiency has been a long-held goal to reach the measurement precision limit inside scattering *** studies have indicated that maximal information states can be attained through engineered modes;however,partial intrusion is generally *** non-invasive designs have been substantially explored across diverse physical scenarios,the non-invasive acquisition of information states inside dynamic scattering spaces remains challenging due to the intractable non-unique mapping problem,particularly in the context of multi-target ***,we establish the feasibility of non-invasive information states'acquisition experimentally for the first time by introducing a tandem-generated adversarial network framework inside dynamic scattering *** illustrate the framework's efficacy,we demonstrate that efficient information states'acquisition for multi-target scenarios can achieve the Fisher information limit solely through the utilization of the external scattering matrix of the *** work provides insightful perspectives for precise measurements inside dynamic complex systems.

关键词： engineered modeshoweverpartial Fisher information limit non invasive acquisition adversarial network dynamic scattering spaces information states

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Dendritic flow networks: the link between patterns and design with purpose in biosystems

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Research on Biomedical engineering 2025年第1期41卷 1-15页

作者： Miguel, Antonio F. Lorente, Sylvie School of Science and Technology University of Evora 7002-554 Apartado 94 Evora Portugal Complex Flow Systems Lab Institute of Earth Sciences Pole of Evora Rua Romao Ramalho 59 Evora7000-671 Portugal Mechanical Engineering Department Villanova University 800 Lancaster Ave VillanovaPA19085 United States

Purpose: This study presents a comprehensive methodology, based on physics laws, for predicting the architecture of symmetric and asymmetric dendritic flow networks. These flow networks, found in vascular systems and respiratory trees, exhibit prefractal patterns that can be described by using recursive processes based on the concept of self-similarity, and the definition of a dimension that represents the degree of the system occupancy in space. Prefractal dendritic networks are thought that ensure the best possible access to flow transport. Methods: According to the second law of thermodynamics, the path with the lowest impedance uses the least amount of energy to perform its task. The methodology employed in this study is the minimizing of flow impedance within constraints. The constraints are defined as the path's volume and lateral area. Results and conclusion: The homothety ratios for sizes of the network that ensure maximum flow access are presented. We also examine the relationship between the fractality of dendritic flow networks and the design obtained from physical laws in this study. Based on the homothetic relations obtained here, the prefractal dimension is defined in terms of physics quantities, giving it meaning beyond the degree of space occupation and potentially shedding light on predicting issues in specific systems when the measured fractality differs from the predicted. Our study can be also very valuable in designing flow networks, which are crucial in the bioengineering sciences. © The Author(s), under exclusive licence to The Brazilian Society of Biomedical engineering 2025.

关键词： Fractal dimension

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EMHDRL: Adversarial Attacks on Graph Neural Networks via Hierarchical Reinforcement Learning 42

EMHDRL: Adversarial Attacks on Graph Neural Networks via Hie...

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42nd Chinese Control Conference, CCC 2023

作者： Sun, Guowei Ding, Jie Li, Xiang School of Information Science and Engineering Fudan University Adaptive Networks and Control Lab Department of Electronic Engineering Shanghai200433 China Institute of Complex Networks and Intelligent Systems Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai201210 China

ISBN: (纸本)9789887581543

Graph neural networks (GNNs), with its powerful ability to explore the topological structure of graph data, have achieved great success in various downstream tasks. However, recent studies have shown that due to the lack of robustness, GNNs are easily fooled by perturbations. For node classification tasks, the current attack methods mainly focus on manipulating edges, modifying features and adding fake nodes. Although these attacks are effective, the changes to the original graph data are easy to be detected. Therefore, to misclassify the target nodes, we propose an Edge Manipulation method via Hierarchical Deep Reinforcement Learning (EMHDRL) by taking accounting to the imperceptibility of perturbation on graph data. Through modeling the topology perturbation as Finite Horizon Markov Decision Process, EMHDRL adopts a hierarchical Q-function network to manipulate edges of graph, while trying to ensure that the degree of the attacked node and the total number of edges of the whole graph remain unchanged. Our experimental results show that the proposed method can effectively reduce the performance of GNNs in classifying the target nodes and has strong transferability. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Reinforcement learning

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A Unified Information Diffusion Prediction Model Based on Multi-task Learning 9th

A Unified Information Diffusion Prediction Model Based on M...

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19th International Conference on Advanced Data Mining and Applications, ADMA 2023

作者： Shang, Yingdan Zhou, Bin Zeng, Xiang Chen, Kai College of Computer Science and Technology National University of Defense Technology Changsha China Key Lab of Software Engineering for Complex Systems School of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9783031466731

The prediction of online information diffusion trends on social networks is crucial for understanding people’s interests and concerns, and has many real-world applications in fields such as business, politics and social security. Existing research on information diffusion prediction has predominantly focused on either macro level prediction of the future popularity of online information or micro level user activation prediction. However, information diffusion prediction on micro or macro level only may lead to one-sided prediction results, and there is a lack of research on implementing micro and macro level diffusion prediction tasks at the same time. Since micro and macro level diffusion prediction tasks are related to each other, we propose a unified information diffusion model which can jointly predicting the micro level user activation probability and macro level information popularity based on multi-task learning framework. We utilize graph neural network to learn user representation from both the information cascades and social network structure. Comparing with micro and macro level baseline methods separately, the prediction results of our proposed model outperform all baseline methods and proves the effectiveness of the proposed method. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Forecasting

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Phase transfer-based high-efficiency recycling of precious metal electrocatalysts

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Green Chemical engineering 2024年第1期5卷 68-74页

作者： Qing Zeng Shaonan Tian Yu Zhang Hui Liu Dong Chen Xinlong Tian Chaoquan Hu Jun Yang State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing100190China State Key Laboratory of Marine Resource Utilization in South China Sea Hainan Provincial Key Lab of Fine ChemistrySchool of Chemical Engineering and TechnologyHainan UniversityHaikou570228China Nanjing IPE Institute of Green Manufacturing Industry Nanjing211100China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing100049China

Recycling precious metals with high-efficiency is undoubtedly beneficial to optimize resource utilization for environmental remediation and sustainable ***,we report an efficient route to recycle the palladium(Pd)and platinum(Pt)electrocatalysts using a phase transfer *** strategy involves acidic dissolution of deactivated precious metal(Pd/Pt)electrocatalysts from their loading substrates,mixing with an ethanolic solution of dodecylamine(DDA),subsequent extraction of metal ions into a non-polar organic phase,and final reduction by sodium borohydride to reproduce high-performance electrocatalysts towards typical electrochemical reactions,e.g.,oxygen reduction reaction(ORR)and ethanol oxidation reaction(EOR).In specific,the transfer efficiencies are up to 98%and the final recovery rate is over 85%for Pd and Pt electrocatalysts in each *** approach symbolizes a facile and efficient way to recover precious metals,which might be applied to recycling a wide range of metals in various realms after appropriate modifications.

关键词： Precious metal Phase transfer Extraction Recovery Electrocatalyst

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Soft Measures for Extracting Causal Collective Intelligence 1

Soft Measures for Extracting Causal Collective Intelligence

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1st Workshop on NLP for science, NLP4science 2024

作者： Berijanian, Maryam Dork, Spencer Singh, Kuldeep Millikan, Michael Riley Riggs, Ashlin Swaminathan, Aadarsh Gibbs, Sarah L. Friedman, Scott E. Brugnone, Nathan Department of Computational Mathematics Science & Engineering Michigan State University United States Department of Computer Science Michigan State University United States Complex & Social Systems Lab Two Six Technologies United States University of South Alabama United States SIFT United States

ISBN: (纸本)9798891761858

Understanding and modeling collective intelligence is essential for addressing complex social systems. Directed graphs called fuzzy cognitive maps (FCMs) offer a powerful tool for encoding causal mental models, but extracting high-integrity FCMs from text is challenging. This study presents an approach using large language models (LLMs) to automate FCM extraction. We introduce novel graph-based similarity measures and evaluate them by correlating their outputs with human judgments through the Elo rating system. Results show positive correlations with human evaluations, but even the best-performing measure exhibits limitations in capturing FCM nuances. Fine-tuning LLMs improves performance, but existing measures still fall short. This study highlights the need for soft similarity measures tailored to FCM extraction, advancing collective intelligence modeling with NLP. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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The Two Fundamental Shapes of Sleep Heart Rate Dynamics and Their Connection to Mental Health in College Students

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Digital Biomarkers 2024年第1期8卷 120-131页

作者： Fudolig, Mikaela Irene Bloomfield, Laura S.P. Price, Matthew Bird, Yoshi M. Hidalgo, Johanna E. Kim, Julia N. Llorin, Jordan Lovato, Juniper McGinnis, Ellen W. McGinnis, Ryan S. Ricketts, Taylor Stanton, Kathryn Dodds, Peter Sheridan Danforth, Christopher M. Vermont Complex Systems Center MassMutual Center of Excellence for Complex Systems and Data Science University of Vermont BurlingtonVT United States Department of Mathematics and Statistics University of Vermont BurlingtonVT United States Computational Story Lab MassMutual Center of Excellence for Complex Systems and Data Science University of Vermont BurlingtonVT United States Gund Institute for Environment University of Vermont BurlingtonVT United States Department of Psychological Science University of Vermont BurlingtonVT United States Project Lemurs University of Vermont BurlingtonVT United States Department of Electrical and Biomedical Engineering University of Vermont BurlingtonVT United States Department of Computer Science University of Vermont BurlingtonVT United States Wake Forest University School of Medicine Winston-SalemNC United States Rubenstein School of Environment and Natural Resources University of Vermont BurlingtonVT United States Santa Fe Institute Santa FeNM United States

Introduction: Wearable devices are rapidly improving our ability to observe health-related processes for extended durations in an unintrusive manner. In this study, we use wearable devices to understand how the shape of the heart rate curve during sleep relates to mental health. Methods: As part of the Lived Experiences Measured Using Rings Study (LEMURS), we collected heart rate measurements using the Oura ring (Gen3) for over 25,000 sleep periods and self-reported mental health indicators from roughly 600 first-year university students in the USA during the fall semester of 2022. Using clustering techniques, we find that the sleeping heart rate curves can be broadly separated into two categories that are mainly differentiated by how far along the sleep period the lowest heart rate is reached. Results: Sleep periods characterized by reaching the lowest heart rate later during sleep are also associated with shorter deep and REM sleep and longer light sleep, but not a difference in total sleep duration. Aggregating sleep periods at the individual level, we find that consistently reaching the lowest heart rate later during sleep is a significant predictor of (1) self-reported impairment due to anxiety or depression, (2) a prior mental health diagnosis, and (3) firsthand experience in traumatic events. This association is more pronounced among females. Conclusion: Our results show that the shape of the sleeping heart rate curve, which is only weakly correlated with descriptive statistics such as the average or the minimum heart rate, is a viable but mostly overlooked metric that can help quantify the relationship between sleep and mental health. © 2024 The Author(s). Published by S. Karger AG, Basel.

关键词： Wearable technology

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Public Goods Game on Hypergraph with Gentle Win-Stay,Lose-Shift Strategy 41

Public Goods Game on Hypergraph with Gentle Win-Stay,Lose-Sh...

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第41届中国控制会议

作者： Junchi Li Cong Li Xiang Li Adaptive Networks and Control Lab Department of Electronic EngineeringSchool of Information Science and TechnologyFudan University the Institute of Complex Networks and Intelligent Systems Shanghai Research Institute for Intelligent Autonomous SystemsTongji University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper introduces a kind of strategy called gentle win-stay,lose-shift(GWSLS) which is used in the revolutionary of public goods game(PGG) on *** work focuses on how this strategy influence the process of evolution of *** take the approach of numerical simulation to study whether cooperation would eventually survive in PGG on different kinds of *** also compare the results in different conditions and find out that cooperation will eventually survive if the number of hyperlinks is not that many.A non-uniform hypergraph is beneficial to the survival of cooperation.

关键词： PGG hypergraph cooperation GWSLS

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Influence of Reporting Rate on Epidemic Control Based on SIXAR Model 41

Influence of Reporting Rate on Epidemic Control Based on SIX...

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第41届中国控制会议

作者： Lingyu Wu Qiandong Sun Cong Li Xiang Li Adaptive Networks and Control Lab Department of Electronic EngineeringSchool of Information Science and TechnologyFudan University The Institute of Complex Networks and Intelligent Systems Shanghai Research Institute for Intelligent Autonomous SystemsTongji University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

How to balance the control efficiency of the epidemic and the economy is extremely *** paper proposes a Susceptible-Infected-Isolated-Asymptomatic-Recovered(SIXAR,X represents isolated people) model,considering the asymptomatic and the *** conduct an in-depth research on the reporting rate in the epidemic,and find the critical reporting rate to prevent the spread of the *** result proves that maintaining the reporting rate near a critical value can both ensure epidemic prevention and control and reduce economic *** will provide a new idea for the government to formulate rational measures.

关键词： Epidemic models SIR model complex Network COVID-19

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