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International Conference on Management of Large-Scale System Development (MLSD)

作者： Viktor Medennikov Larisa Bogatyreva Information and Computing Systems Department Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences Moscow Russia Laboratory of modular data processing and control systems V.A. Trapeznikov Institute of Control Sciences of the Russian Academy of Sciences Moscow Russia

ISBN: (数字)9798350375718

ISBN: (纸本)9798350375725

The paper deals with complementary changes in scientific research and real economy (exemplified by the farming industry) taking place when using the holistic approach to the industry”s digital transformation resulting in the appearance of precise agrarian technologies that require a comprehensive., system-based combination of research and production resources that are able to ensure increased productivity in the industry. We demonstrate that among these new technologies, the artificial intelligence methods have a special significance. They have to, however, go through integration transformations to become standards for the proposed common digital farming management platform.

关键词： Productivity Digital transformation Large-scale systems Artificial intelligence Standards Farming

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MULTI-AGENT COOPERATION VIA UNSUPERVISED LEARNING OF JOINT INTENTIONS

arXiv

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arXiv 2023年

作者： Liu, Shanqi Liu, Weiwei Chen, Wenzhou Tian, Guanzhong Liu, Yong Control Science and Engineering Zhejiang University Zhejiang China Computer Science Hangzhou Dianzi University Zhejiang China Ningbo Research Institute Zhejiang University Zhejiang China

The field of cooperative multi-agent reinforcement learning (MARL) has seen widespread use in addressing complex coordination tasks. While value decomposition methods in MARL have been popular, they have limitations in solving tasks with non-monotonic returns, restricting their general application. Our work highlights the significance of joint intentions in cooperation, which can overcome non-monotonic problems and increase the interpretability of the learning process. To this end, we present a novel MARL method that leverages learnable joint intentions. Our method employs a hierarchical framework consisting of a joint intention policy and a behavior policy to formulate the optimal cooperative policy. The joint intentions are autonomously learned in a latent space through unsupervised learning and enable the method adaptable to different agent configurations. Our results demonstrate significant performance improvements in both the StarCraft micromanagement benchmark and challenging MAgent domains, showcasing the effectiveness of our method in learning meaningful joint intentions. Copyright © 2023, The Authors. All rights reserved.

关键词： Unsupervised learning

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The influence of coordinated behavior on toxicity

arXiv

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arXiv 2023年

作者： Loru, Edoardo Cinelli, Matteo Tesconi, Maurizio Quattrociocchi, Walter Department of Computer Control and Management Engineering Sapienza University of Rome Italy Department of Computer Science Sapienza University of Rome Italy Institute of Informatics and Telematics National Research Council

In the intricate landscape of social media, genuine content dissemination may be altered by a number of threats. Coordinated Behavior (CB), defined as orchestrated efforts by entities to deceive or mislead users about their identity and intentions, emerges as a tactic to exploit or manipulate online discourse. This study delves into the relationship between CB and toxic conversation on X (formerly known as Twitter). Using a dataset of 11 million tweets from 1 million users preceding the 2019 UK general election, we show that users displaying CB typically disseminate less harmful content, irrespective of political affiliation. However, distinct toxicity patterns emerge among different coordinated cohorts. Compared to their non-CB counterparts, CB participants show marginally higher toxicity levels only when considering their original posts. We further show the effects of CB-driven toxic content on non-CB users, gauging its impact based on political leanings. Our findings suggest that CB only has a limited impact on the toxicity of digital discourse. Please cite published version: https://***/10.1016/***.2024.100289 © 2023, CC BY.

关键词： Tweets

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Convergent Approaches to AI Explainability for HEP Muonic Particles Pattern Recognition

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Computing and Software for Big science 2023年第1期7卷 1-18页

作者： Maglianella, Leandro Nicoletti, Lorenzo Giagu, Stefano Napoli, Christian Scardapane, Simone Department of Computer Control and Management Engineering Antonio Ruberti Sapienza University of Rome Rome Italy Department of Physics Sapienza University of Rome Rome Italy Institute for Systems Analysis and Computer Science Italian National Research Council Rome Italy Department of Computational Intelligence Electronics and Telecommunications Czestochowa University of Technology Czestochowa Poland Department of Information Engineering Electronics and Telecommunications Sapienza University of Rome Rome Italy

Neural networks are commonly defined as ‘black-box’ models, meaning that the mechanism describing how they give predictions and perform decisions is not immediately clear or even understandable by humans. Therefore, Explainable Artificial Intelligence (xAI) aims at overcoming such limitation by providing explanations to Machine Learning (ML) algorithms and, consequently, making their outcomes reliable for users. However, different xAI methods may provide different explanations, both from a quantitative and a qualitative point of view, and the heterogeneity of approaches makes it difficult for a domain expert to select and interpret their result. In this work, we consider this issue in the context of a high-energy physics (HEP) use-case concerning muonic motion. In particular, we explored an array of xAI methods based on different approaches, and we tested their capabilities in our use-case. As a result, we obtained an array of potentially easy-to-understand and human-readable explanations of models’ predictions, and for each of them we describe strengths and drawbacks in this particular scenario, providing an interesting atlas on the convergent application of multiple xAI algorithms in a realistic context. © 2023, The Author(s).

关键词： Explainable Artificial Intelligence High-energy physics Intrinsically interpretable Decision Trees Saliency maps methods Tracing gradient descent

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Magnetoelastic coupling driven magnon gap in a honeycomb antiferromagnet

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Physical Review B 2024年第10期110卷 104419页

作者： Jeongheon Choe Andrey Baydin Gaihua Ye Bowen Ma Cynthia Nnokwe Martin Rodriguez-Vega David Lujan Swati Chaudhary Fuyang Tay Jiaming He Hiroyuki Nojiri Jianshi Zhou Gregory A. Fiete Junichiro Kono Rui He Xiaoqin Li Department of Physics Center of Complex Quantum Systems Center for Dynamics and Control of Materials Department of Electrical and Computer Engineering Smalley–Curl Institute Department of Physics Applied Physics Graduate Program Smalley–Curl Institute Department of Mechanical Engineering Institute for Materials Research Department of Physics and Astronomy Department of Materials Science and NanoEngineering

Cobalt titanate, CoTiO3, is a honeycomb antiferromagnet recently confirmed experimentally to host Dirac magnons, topological spin-orbit excitons, and chiral phonons. Here, we investigate a magnon gap at the zone center which calls for a refined spin Hamiltonian. We propose a microscopic model for the magnon gap and attribute it to a lattice-distortion (phonon)-induced higher-order spin interaction. Strong magnetoelastic coupling in CoTiO3 is also evident in Raman spectra, in which the magnetic order exerts a stronger influence on phonons corresponding to in-plane ionic motions than those with out-of-plane motions. We further examine the evolution of the zone-center magnons in a high magnetic field up to 18.5 T via THz absorption spectroscopy measurements. Based on this field dependence, we propose a spin Hamiltonian that not only agrees with magnon dispersion measured by inelastic neutron scattering but also includes fewer exchange constants and a realistic anisotropy term. Our work highlights the broad implications of magnetoelastic coupling in the study of topologically protected bosonic excitations.

关键词： Magnetism Magnons Topological materials Raman spectroscopy Terahertz spectroscopy

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Estimating the Probability of Falling Share Price Below the Minimum Level

Estimating the Probability of Falling Share Price Below the ...

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International Conference on control, Decision and Information Technologies (CoDIT)

作者： Sergei L. Semakov Faculty of Control and Applied Mathematics Moscow Institute of Physics and Technology Department of Mathematics Moscow Automobile and Road Construction Institute Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences the Russian Federation

A technology is proposed for estimating the probability that a share price will fall below the minimum level. The exact expression is obtained for the required probability under the assumption that the behavior of the share price is described by the well-known model of Samuelson, according to which the relative change in price is the sum of the non-random trend and the Wiener process. The obtained result is qualitatively analyzed for various relations of the problem parameters.

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Efficient Photothermal Catalytic Oxidation Enabled by Three-Dimensional Nanochannel Substrates

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Environmental science and Technology 2024年第11期58卷 5153-5161页

作者： Li, Yifei Zhang, Qianpeng Chong, Yanan Huang, Wei-Hsiang Chen, Chi-Liang Jin, Xiaojing Chen, Guangxu Fan, Zhiyong Qiu, Yongcai Ye, Daiqi School of Environment and Energy State Key Laboratory of Luminescent Materials and Devices Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control South China University of Technology Guangdong Guangzhou510000 China State Key Laboratory of Photovoltaic Science and Technology Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and Perception Institute of Optoelectronics Fudan University Shanghai200433 China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon999077 Hong Kong State Key Laboratory of Advanced Displays and Optoelectronics Technologies The Hong Kong University of Science and Technology Clear Water Bay Kowloon999077 Hong Kong National Synchrotron Radiation Research Center 101 Hsin-Ann Road Hsinchu Science Park Hsinchu30076 Taiwan Taipei10607 Taiwan College of Light Chemical Industry and Materials Engineering Shunde Polytechnic Foshan528333 China

Photothermal catalysis exhibits promising prospects to overcome the shortcomings of high-energy consumption of traditional thermal catalysis and the low efficiency of photocatalysis. However, there is still a challenge to develop catalysts with outstanding light absorption capability and photothermal conversion efficiency for the degradation of atmospheric pollutants. Herein, we introduced the Co3O4 layer and Pt nanoclusters into the three-dimensional (3D) porous membrane through the atomic layer deposition (ALD) technique, leading to a Pt/Co3O4/AAO monolithic catalyst. The 3D ordered nanochannel structure can significantly enhance the solar absorption capacity through the light-trapping effect. Therefore, the embedded Pt/Co3O4 catalyst can be rapidly heated and the O2 adsorbed on the Pt clusters can be activated to generate sufficient O2- species, exhibiting outstanding activity for the diverse VOCs (toluene, acetone, and formaldehyde) degradation. Optical characterization and simulation calculation confirmed that Pt/Co3O4/AAO exhibited state-of-the-art light absorption and a notable localized surface plasmon resonance (LSPR) effect. In situ diffuse reflectance infrared Fourier transform spectrometry (in situ DRIFTS) studies demonstrated that light irradiation can accelerate the conversion of intermediates during toluene and acetone oxidation, thereby inhibiting byproduct accumulation. Our finding extends the application of AAO’s optical properties in photothermal catalytic degradation of air pollutants. © 2024 American Chemical Society.

关键词： Catalysis

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Dual-Mode Disturbance Observer-based Predictive control with Harmonic Current Suppression for Dual Three-Phase Permanent Magnet Synchronous Motor Drives

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IEEE Journal of Emerging and Selected Topics in Power Electronics 2025年

作者： Liu, Huanli Lin, Weiyang Liu, Zhitai Yu, Xinghu Buccella, Concettina Cecati, Carlo Harbin Institute of Technology Research Institute of Intelligent Control and Systems Harbin150001 China Ningbo Institute of Intelligent Equipment Technology Company Ltd Ningbo315200 China University of L'Aquila DigiPower srl Department of Information Engineering Computer Science and Mathematics L'Aquila67100 Italy

Dual three-phase permanent magnet synchronous motor drives have gained considerable interest in those applications requiring high levels of reliability. However, they often suffer from high-order harmonic currents and mismatch of motor parameters, resulting in degraded performance and reduced efficiency. Therefore, this paper proposes a dual-mode disturbance observer based model predictive current controller. Not only direct current disturbances caused by motor parameters, but also alternating current disturbances caused by high-order harmonic currents are explicitly modeled and estimated to achieve improved model accuracy. In addition, the observer parameter design is given in detail. Furthermore, a generalized predictive current controller with the integration of the proposed observer is developed to provide satisfactory harmonic current suppression capability and parameter robustness simultaneously. Proof of the stability with the proposed controller is given and several experiments and comparisons demonstrate the effectiveness of the proposed method. © 2013 IEEE.

关键词： Permanent magnets

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Study on the COVID-19 epidemic in China's Mainland between November 2022 and January 2023,with prediction of its tendency

引用

Journal of Biosafety and Biosecurity 2023年第1期5卷 39-44页

作者： Yao Bai Zhihang Peng Fengying Wei Zhen Jin Jinjie Wang Ximing Xu Xinyan Zhang Jun Xu Zixiong Ren Bulai Lu Zhaojun Wang Jianguo Xu Senzhong Huang Xi’an Center for Disease Control and Prevention Xi’an 710054ShaanxiChina Department of Biostatistics School of Public HealthNanjing Medical UniversityNanjing 211166JiangsuChina School of Mathematics and Statistics Fuzhou UniversityFuzhou 350116FujianChina Complex Systems Research Center Key Discipline of Computer Science and Technology of“Double-First-Class”Project of Shanxi ProvinceShanxi UniversityTaiyuan 030006ShanxiChina Nankai Institute of Economics Binhai Development InstituteNankai UniversityTianjin 300071China Children’s Hospital of Chongqing Medical University Chongqing 400010China Jinzhou Center for Disease Control and Prevention Jinzhou 121000LiaoningChina School of Statistics and Data Science Nankai UniversityTianjin 300071China Suzhou Center for Disease Control and Prevention Suzhou 215004JiangsuChina State Key Laboratory of Communicable Disease Prevention and Control National Institute for Communicable Disease Control and PreventionChinese Center for Disease Control and PreventionBeijing 102206China Institute of Public Health Nankai UniversityTianjin 300071China School of Statistics and Data Science ZhiYing Research Center for Health DataNankai UniversityTianjin 300071China

The prediction system EpiSIX was used to study the COVID-19 epidemic in China's Mainland between November 2022 and January 2023,based on reported data from December 9,2022,to January 30,2023,released by The Chinese Center for Disease control and Prevention on February 1,*** kinds of reported data were used for model fitting:the daily numbers of positive nucleic acid tests and deaths,and the daily number of hospital beds taken by COVID-19 *** was estimated that the overall infection rate was 87.54%and the overall case fatality rate was 0.078%–0.116%(median 0.100%).Assuming that a new COVID-19 epidemic outbreak would start in March or April of 2023,induced by a slightly more infectious mutant strain,we predicted a possible large rebound between September and October 2023,with a peak demand of between 800,000 and 900,000 inpatient *** no such new outbreak was induced by other variants,then the current COVID-19 epidemic course in China's Mainland would remain under control until the end of ***,it is suggested that the necessary medical resources be prepared to manage possible COVID-19 epidemic emergencies in the near future,especially for the period between September and October 2023.

关键词： COVID-19 Epidemic Infection rate Case fatality rate Prediction

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Low-disturbance Nonlinear control of TBM Cutterhead Speed in Coal Mine Tunneling

Low-disturbance Nonlinear Control of TBM Cutterhead Speed in...

引用

Annual Conference of Industrial Electronics Society

作者： Nannan Liu Tong Wang Jianmin Wang Yingda Fan School of Electronic and Information Engineering Ningbo University of Technology Ningbo China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin China Department of Computer Science University of Pittsburgh Pittsburgh USA

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

To minimize the disturbance of the Tunnel Boring Machine (TBM) cutterhead on the surrounding rock during the coal mine roadway excavation process and ensure that the cutterhead rotation speed achieves fast tracking performance with minimal overshoot, we propose a direct adaptive robust control method for the cutterhead rotation speed hydraulic system based on inversion design. This method considers the strong disturbances such as loads and motion affecting the cutterhead hydraulic drive system, as well as the uncertainties in the cutterhead model. We establish the nonlinear model of the cutterhead hydraulic drive system and employ virtual control to reduce the model order. Using Lyapunov functions, we ensure the stability of the entire system and derive the control law for the cutterhead rotation speed controller, along with parameter-adaptive laws acting as parameter estimators. We validate the effectiveness of the proposed control strategy through joint simulation using AMESim and Simulink. The results show that the designed cutterhead rotation speed controller achieves high tracking accuracy and good adaptability.

关键词： Robust control Adaptation models Uncertainty Tracking Software packages Hydraulic drives Tunneling Stability analysis Coal mining Load modeling

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