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Proceedings of the 2020 International Conference on cyberspace Innovation of Advanced Technologies

作者： Xueying Zhang Jun Li Daojuan Zhang Jianlei Gao Hao Jiang Department of Security Technology China Industrial Control Systems Cyber Emergency Response Team Beijing P. R. China State Grid Key Laboratory of Information & Network Security Global Energy Interconnection Research Institute co. Ltd. Beijing P. R. China

ISBN: (纸本)9781450387828

With the rapid development of network technology, billions of industrial control systems (ICSs) and the Internet of Things (IoTs) have been equipped with network communication functions. This brings many network security issues while realizing data intercommunication and sharing. In particular, the massive amount of data and the heterogeneous nature of the data have brought huge challenges to the design of an effective intrusion detection system (IDS). In order to clarify the impact of distinct features on anomaly detection, this paper conducts a series of experiments based on the maximum correlation minimum redundancy (MRMR) feature selection algorithm and the support vector machine (SVM) classification method. By comparing the experimental results of UNSW-NB15 data set and MSU data set, traditional data set and industrial data set, it can be seen that different features have different effects on anomaly detection. To be precise, there are both coupling and independence between different features. In particular, industrial data sets based on the Modbus protocol (MSU) have higher redundancy and independence. In other words, we can select more effective data features as attributes of anomaly detection in designing industrial IDS, which can improve the detection accuracy while reducing the detection time.

关键词： coupling and independence

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LDM: Large tensorial SDF model for textured mesh generation

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Graphical Models 2025年 140卷

作者： Rengan Xie Kai Huang Xiaoliang Luo Yizheng Chen Lvchun Wang Qi Wang Qi Ye Wei Chen Wenting Zheng Yuchi Huo State Key Lab of CAD&CG Zhejiang University Hangzhou China Institute of Computing Technology Chinese Academy of Sciences Beijing China Mobile (Jiangxi) Virtual Reality Technology Co. Ltd Nanchang China Zhejiang lab Hangzhou China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

Previous efforts have managed to generate production-ready 3D assets from text or images. However, these methods primarily employ NeRF or 3D Gaussian representations, which are not adept at producing smooth, high-quality geometries required by modern rendering pipelines. In this paper, we propose LDM, a L arge tensorial S D F M odel, which introduces a novel feed-forward framework capable of generating high-fidelity, illumination-decoupled textured mesh from a single image or text prompts. We firstly utilize a multi-view diffusion model to generate sparse multi-view inputs from single images or text prompts, and then a transformer-based model is trained to predict a tensorial SDF field from these sparse multi-view image inputs. Finally, we employ a gradient-based mesh optimization layer to refine this model, enabling it to produce an SDF field from which high-quality textured meshes can be extracted. Extensive experiments demonstrate that our method can generate diverse, high-quality 3D mesh assets with corresponding decomposed RGB textures within seconds. The project code is available at https://***/rgxie/LDM .

关键词： 3D generation model Diffusion Intrinsic decomposition Relighting

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Electrochemical Model based state of Charge Estimation for Lithium Batteries with Backstepping Techniques

Electrochemical Model based State of Charge Estimation for L...

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第三十八届中国控制会议

作者： Guangwei Chen Zhitao Liu Hongye Su Quanling Zhang State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University

In this paper, state of charge(SOC) estimation based on the lithium-ion battery electrochemical model is considered. The battery electrochemical model, which is given by partial differential equations(PDE), can describe the variation process of lithium-ion concentration during charging and discharging very well. And with the charging and discharging cycle number increasing, the electrochemical model parameters will change, such as the diffusion coefficient in the battery. In order to estimate the SOC well, passive identifier method is applied to identify the diffusion coefficient in the electrochemical model. Then a PDE observer based on backstepping technique is proposed to estimate the SOC in the battery, and Crank-Nicolson-Method is used to solve PDE. The simulation results indicate that proposed estimation method based on backstepping for SOC estimation in lithium-ion battery has good performance.

关键词： Lithium-ion battery SOC estimation electrochemical model backstepping

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Self-intersection Attention Pooling Based Classification for Rock Recognition

Self-intersection Attention Pooling Based Classification for...

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International Conference on control, Automation, Robotics and Vision (ICARCV)

作者： Liang Chen Qian Zheng Zhitao Liu Weijie Mao Fulong Lin State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Fudan University Shanghai China General Institute of Design and Research China Railway Engineering Equipment Group Co. LTD Zhengzhou China

ISBN: (数字)9781728177090

ISBN: (纸本)9781728177106

Rock recognition is a critical step for intelligent control system in tunnel boring machine (TBM). We build the rock recognition dataset by the visual monitoring system in TBM. After that, we present an attention-fusion network (AFN) for rock recognition classification. Our model is trained with the recognition object (rock) image, and gets the rock attention map through the self-intersection operation. To complete the classification task, we propose the attention block in the attention-fusion classifier, which is effective to fuse and encode the feature and attention in an end-to-end manner. We confirm the effectiveness of the self-intersection operation and attention block by visualized experiment and contrast experiment. At the same time, experimental results of the rock recognition dataset indicate that AFN outperforms state-of-the-art methods, including LSTM (mask-guided), ABN (attention-based), ResNetSO (global-feature), both in accuracy and realtime on the rock recognition tasks.

关键词： Rocks Task analysis Feature extraction Visualization Monitoring Convolution Image recognition

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Improve the Conversion Rate and Selectivity of Aromatic Monomers in Lignin Photocatalytic Conversion Reaction Via Phase Junction Cadmium Sulphide Nanoparticles and External Hydrogen Supplier

SSRN

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SSRN 2023年

作者： Yue, Zongyang Shao, Shibo Yu, Jialin Lu, Guanchu Wei, Wenjing Huang, Yi Zhang, Kai Wang, Ke Fan, Xianfeng Institute for Materials and Processes School of Engineering The University of Edinburgh EdinburghEH9 3BF United Kingdom Petrochemical Research Institute PetroChina Company Limited Beijing102206 China Beijing Key Laboratory of Ionic Liquids Clean Process CAS Key Laboratory of Green Process and Engineering State Key Laboratory of Multiphase Complex Systems Innovation Academy for Green Manufacture Institute of Process Engineering Chinese Academy of Sciences Beijing100190 China Longzihu New Energy Laboratory Zhengzhou Institute of Emerging Industrial Technology Henan University Zhengzhou450000 China Beijing Key Laboratory of Emission Surveillance and Control for Thermal Power Generation North China Electric Power University Beijing102206 China

Photocatalysis has the potential for lignin valorisation to generate functionalised aromatic monomers, but its large-scale application has been limited by the slow conversion rate and the low selectivity to desirable products. In this work, record-high lignin model compound Cβ-O bonds cleavage rate and excellent selectivity to aromatic monomers has been achieved over the development of new hexagonal-cubic phase junction CdS nanoparticles, enhanced external hydrogen donor supply and hydrogen transfer, and improved separation efficiency of photo-excited electron-hole pairs. Water is employed as external hydrogen supplier, resulting in significant increase in the conversion rate of 2-Phenoxy-1-phenylethanol (PP-ol) as lignin model from 21.8% to 100% and the selectivity of aromatic monomers from ~45% to ~94% under 1h of visible light irradiation. 2-phenoxyacetophenone (PP-one) as by-product from PP-ol conversion can be further completely cleaved to aromatic monomers with assistance of TEA and reaction time is reduced from 2-12 hrs to10 min under visible-light irradiation. © 2023, The Authors. All rights reserved.

关键词： Lignin

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Artificial intelligence-based methods for renewable power system operation

Nature Reviews Electrical Engineering

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Nature Reviews Electrical Engineering 2024年第3期1卷 163-179页

作者： Yuanzheng Li Fei Hu Juntao Duan Yong Zhao Zhigang Zeng Yizhou Ding Shangyang He Guanghui Wen Hua Geng Zhengguang Wu Hoay Beng Gooi Chenghui Zhang Shengwei Mei Key Laboratory of lmage Information Processing and Intelligent Control of Ministry of Education of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China National Key Laboratory of Multispectral Information Intelligent Processing Technology Huazhong University of Science and Technology Wuhan China China-EU Institute for Clean and Renewable Energy Huazhong University of Science and Technology Wuhan China Department of Systems Science School of Mathematics Southeast University Nanjing China Department of Automation Tsinghua University Beijing China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China School of Electrical and Electronics Engineering Nanyang Technological University Singapore Singapore School of Control Science and Engineering Shandong University Jinan China Department of Electrical Engineering Tsinghua University Beijing China

Carbon neutrality goals are driving the increased use of renewable energy (RE). Large-scale use of RE requires accurate energy generation forecasts; optimized power dispatch, which minimizes costs while satisfying operational constraints; effective system control to ensure a stable power supply; and electricity markets that support bidding and trading decisions associated with RE. However, the uncertainties in RE generation make renewable power systems challenging to operate. For example, the intermittent nature of wind power can make it difficult to balance the supply and demand of electricity in real time; therefore, traditional power sources could be needed to meet the demand, which can increase electricity prices. This Review outlines the potential of artificial intelligence-based methods for supporting renewable power system operation. We discuss the ability of machine learning, deep learning and reinforcement learning methods to facilitate power system forecasts, dispatch, control and markets to support the use of RE. We also emphasize the applicability of these techniques to different operational problems. Finally, we discuss potential trends in renewable power system development and approaches to address the associated operational challenges such as the increasingly distributed nature of RE installations, diversification of energy storage systems and growing market complexity.

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Polyhedral Feasible Set Computation of MPC-Based Optimal control Problems

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IEEE/CAA Journal of Automatica Sinica 2018年第4期5卷 765-770页

作者： Lantao Xie Lei Xie Hongye Su Jingdai Wang State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou 310027China College of Chemical and Biological Engineering Zhejiang UniversityHangzhou 310027China IEEE

Feasible sets play an important role in model predictive control(MPC) optimal control problems(OCPs). This paper proposes a multi-parametric programming-based algorithm to compute the feasible set for OCP derived from MPC-based algorithms involving both spectrahedron(represented by linear matrix inequalities) and polyhedral(represented by a set of inequalities) constraints. According to the geometrical meaning of the inner product of vectors, the maximum length of the projection vector from the feasible set to a unit spherical coordinates vector is computed and the optimal solution has been proved to be one of the vertices of the feasible set. After computing the vertices,the convex hull of these vertices is determined which equals the feasible set. The simulation results show that the proposed method is especially efficient for low dimensional feasible set computation and avoids the non-unicity problem of optimizers as well as the memory consumption problem that encountered by projection algorithms.

关键词： Feasible set computation linear matrix inequalities(LMIs) model predictive control(MPC) polyhedron

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MA-FSAR: Multimodal Adaptation of CLIP for few-shot action recognition

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Pattern Recognition 2026年 169卷

作者： Jiazheng Xing Jian Zhao Chao Xu Mengmeng Wang Guang Dai Yong Liu Jingdong Wang Xuelong Li State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University China Institute of AI (TeleAI) China School of Artificial Intelligence Optics and Electronics (iOPEN) Northwestern Polytechnical University (NWPU) China Zhejiang University of Technology China SGIT AI Lab State Grid Corporation of China China Baidu Inc. China

Applying large-scale vision-language pre-trained models like CLIP to few-shot action recognition (FSAR) can significantly enhance both performance and efficiency. While several studies have recognized this advantage, most rely on full-parameter fine-tuning to adapt CLIP’s visual encoder to FSAR data, which not only incurs high computational costs but also overlooks the potential of the visual encoder to engage in temporal modeling and focus on targeted semantics directly. To tackle these issues, we introduce MA-FSAR, a framework that employs the Parameter-Efficient Fine-Tuning (PEFT) technique to enhance the CLIP visual encoder in terms of action-related temporal and semantic representations. Our solution involves a token-level Fine-grained Multimodal Adaptation mechanism: a Global Temporal Adaptation captures motion cues from video sequences, while a Local Multimodal Adaptation integrates text-guided semantics from the support set to emphasize action-critical features. Additionally, we propose a prototype-level text-guided construction module to further enrich the temporal and semantic characteristics of video prototypes. Extensive experiments demonstrate our superior performance in various tasks using minor trainable parameters.

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Privacy-Preserving Brain-Computer Interfaces: A Systematic Review

arXiv

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arXiv 2024年

作者： Xia, Kun Duch, Wlodzislaw Sun, Yu Xu, Kedi Fang, Weili Luo, Hanbin Zhang, Yi Sang, Dong Xu, Xiaodong Wang, Fei-Yue Wu, Dongrui The Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Zhejiang Lab Hangzhou311121 China The Department of Informatics School of Physics Astronomy and Informatics Neurocognitive Laboratory Center for Modern Interdisciplinary Technologies Nicolaus Copernicus University Torun Poland The Ministry of Education Key Laboratory for Biomedical Engineering Zhejiang University Hangzhou China The Zhejiang University School of Medicine National Clinical Research Center for Child Health Hangzhou China Department of Biomedical Engineering Zhejiang University Hangzhou China The School of Civil and Hydraulic Engineering Huazhong University of Science and Technology Wuhan430074 China The College of Public Administration Huazhong University of Science and Technology Wuhan430074 China The NetsUnion Clearing Corporation Beijing100045 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100049 China

A brain-computer interface (BCI) establishes a direct communication pathway between the human brain and a computer. It has been widely used in medical diagnosis, rehabilitation, education, entertainment, etc. Most research so far focuses on making BCIs more accurate and reliable, but much less attention has been paid to their privacy. Developing a commercial BCI system usually requires close collaborations among multiple organizations, e.g., hospitals, universities, and/or companies. Input data in BCIs, e.g., electroencephalogram (EEG), contain rich privacy information, and the developed machine learning model is usually proprietary. Data and model transmission among different parties may incur significant privacy threats, and hence privacy protection in BCIs must be considered. Unfortunately, there does not exist any contemporary and comprehensive review on privacy-preserving BCIs. This paper fills this gap, by describing potential privacy threats and protection strategies in BCIs. It also points out several challenges and future research directions in developing privacy-preserving BCIs. © 2024, CC BY.

关键词： Differential privacy

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A software and hardware design of intelligent measurement and control terminal of distribution network based on a communication adaptive approach 3

A software and hardware design of intelligent measurement an...

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3rd International Conference on Green Energy and Sustainable Development, GESD 2020

作者： Ding, Yujie Xiao, Xiaobing Tian, Hao Liu, Chang Ouyang, Guangze Zhang, Ruifeng Anshun Power Supply Bureau of Guizhou Power Grid Co. Ltd. Anshun China Electric Power Research Institute of Guizhou Power Grid Co. Ltd. Guiyang China State Key Lab of Control and Simulation of Power Systems and Generation Equipments Dept. of Electrical Engineering Tsinghua University Beijing China Binjiang College of Nanjing University of Information Science and Technology Wuxi China

With the development of science and technology, the hardware and software design of transformer intelligent measurement and control terminal is very important. Based on the hardware and software appization of internet of things, the design scheme of hardware and software structure is given. Supported by high-performance operating system, the terminal device can be upgraded flexibly through APP application software. The intelligent terminal pair can realize full data collection, full control and full fusion, and real-time exchange of key operation data with the power distribution master station. The intelligent terminal can support 5G communication and realize full compatibility of communication conditions downward. © Published under licence by IOP Publishing Ltd.

关键词： Application programs

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