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9th International Conference on Intelligent Computing and Signal processing, ICSP 2024

作者： Tian, Pingfang Liu, Deting Department of Computer Science and Technology Wuhan University of Science and Technology Wuhan430065 China Institute of Scientific and Technical Information of China The Key Laboratory of the Rich Media Knowledge Organisation and Service of Digital Publishing Content Beijing100038 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Big Data Science and Engineering Research Institute Wuhan University of Science and Technology Wuhan430065 China

ISBN: (纸本)9798350376548

Topic shift detection aims to identify whether there is a change in the current topic of conversation or if a change is needed. The study found previous work did not evaluate the performance of large language models like ChatGPT on the task of topic shift. Therefore, this paper's main task and innovation lie in analyzing ChatGPT's performance on topic shift detection. To provide a more comprehensive evaluation, we conducted topic shift detection tasks on ChatGPT from three aspects: single utterances, adjacent utterances, and contextual levels. Additionally, to gauge the performance of large language models, we conducted experiments on multiple small-scale models and compared the results of the two models. Experimental results on the publicly available English TIAGE dataset showed that small-scale models exhibited lower recall in all three aspects, while ChatGPT performed better in the recall. This suggests that compared to small-scale models, large models are more capable of accurately detecting topic shifts. However, large models also exhibited lower precision, indicating that while ChatGPT can recognize content differences in utterances, its judgment on whether these different contents belong to the same topic is poor. © 2024 IEEE.

关键词： adjacent utterances level ChatGPT contextual level single utterances level topic shift detection

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Learning-Based Defense Against Prediction-Based Displacement Attacks on Formation control

Learning-Based Defense Against Prediction-Based Displacement...

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Chinese Automation Congress (CAC)

作者： Bingtong Chen Yushan Li Shukun Wu Chongrong Fang Jianping He Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China Student Innovation Center Shanghai Jiao Tong University China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Formation control is a widely performed task in multi-agent systems. However, agents under formation control are susceptible to attacks, and how to defend against the attack is important for system security. This paper aims to design a new method to protect the system from prediction-based displacement attack, which predicts the movement of agents, diverts them from their original tracks and drives them to a preset trap. The defense is challenging due to the robustness of the attacker's prediction mechanism. Also, undermining the attack can be costly and harm the system's performance. To address this issue, we first build obstacle-avoidance and formation control models of the holonomic and non-holonomic agents and specify the prediction-based attacks to limit the cases where the defense strategy can be effective. Then, we propose a learning-based defense strategy, which learns the prediction mechanism of the attackers. It modifies the control input based on self-adaptive fuzzy methods to reduce prediction accuracy and guarantee that the agents can reach the goal. Simulation results demonstrate that our method is better than the previous noise-based one at reducing the accuracy of the attacker's prediction.

关键词： Accuracy Tracking system performance Simulation Predictive models Formation control Robustness Trajectory Security Multi-agent systems

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Time and Angle Constraint Guidance Law Applicable to Maneuvering Target

Time and Angle Constraint Guidance Law Applicable to Maneuve...

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Chen, Ye Guo, Zhengyu Cai, Yunze Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China China Air-to-Air Missile Research Institute Luoyang471000 China Department of Automation Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9789811581540

In the modern battlefield, traditional guidance law like PNG can’t meet the needs of specific tasks. In this paper, we take terminal angle and flight time into consideration. Firstly, we use optimal control to satisfy impact angle requirement. Then, flight time error is designed to control impact time. Consider large errors caused by using the traditional estimator of time-to-go to attack maneuvering target, an improved time-to-go estimator is designed. Numerical simulations show excellent results of the devised law. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Angle constraint Optimal control Target maneuvering Time constraint Time-to-go estimation

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Optimization of Extreme Learning Machine Based on Improved Beetle Antennae Search for Slot Die Coating Prediction

Optimization of Extreme Learning Machine Based on Improved B...

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Chinese control and Decision Conference, CCDC

作者： Haonan Yang Ding Liu Jun-Chao Ren Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China

In the actual production of slot die coating, the minimum coating thickness and the maximum substrate moving speed could only be judged by production experience, and there was no accurate prediction model due to the nonlinear characteristics of fluid motion. Therefore, building a reasonable and efficient prediction model for slot die coating is now an urgent and challenging task. In this paper, an optimized extreme learning machine (ELM) based on improved beetle antennae search (IBAS) algorithm is proposed for slot die coating prediction. The optimized ELM model can well learn the nonlinear characteristics of the system and make accurate predictions, thus solving the traditional inaccurate empirical judgment. As the prediction accuracy of ELM depends on the selection of weights and biases, the IBAS optimization algorithm is used to quickly search for the optimal value of weights and biases in the ELM network. IBAS algorithm improves the generation mechanism of antennae on the basis of the original algorithm, so that the algorithm can converge quickly. At the same time, the search strategy of the algorithm is improved to avoid falling into the local optimal solution. By predicting the production data of slit coating, the feasibility and effectiveness of IBAS-ELM model are proved.

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The Development and Industry Risks of New Energy Vehicles in China

The Development and Industry Risks of New Energy Vehicles in...

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2022 International Conference on Statistics, Data Science, and Computational Intelligence, CSDSCI 2022

作者： Tang, Xi-Ru Wang, Bin Institute of Urban System Engineering Beijing Academy of Science and Technology Beijing100035 China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100192 China

ISBN: (纸本)9781510661325

The development of the new energy automobile industry is an important direction to accelerate the construction of a powerful automobile country, and it is also an effective means to break the constraints of energy and environment, which is of great strategic significance to China. In this article, based on the perspective of the development of the overall new energy vehicle industry, we analyze the market size and development stage of China's new energy vehicle industry, and explore the characteristics of the industry's development. Further, this paper analyzes the industry risks of the future development of new energy vehicles under the background of the imminent withdrawal of government financial subsidies and the transition of the new energy vehicle industry from policy-driven to market-driven, and provides theoretical support for the healthy and sustainable development of Chinese new energy vehicle industry. © 2023 SPIE.

关键词： Automotive industry

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VAGeo: View-specific Attention for Cross-View Object Geo-Localization

VAGeo: View-specific Attention for Cross-View Object Geo-Loc...

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

作者： Zhongyang Li Xin Yuan Wei Liu Xin Xu School of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Cross-view object geo-localization (CVOGL) aims to locate an object of interest in a captured ground- or drone-view image within the satellite image. However, existing works treat ground-view and drone-view query images equivalently, overlooking their inherent viewpoint discrepancies and the spatial correlation between the query image and the satellite-view reference image. To this end, this paper proposes a novel View-specific Attention Geo-localization method (VAGeo) for accurate CVOGL. Specifically, VAGeo contains two key modules: view-specific positional encoding (VSPE) module and channel-spatial hybrid attention (CSHA) module. In object-level, according to the characteristics of different viewpoints of ground and drone query images, viewpoint-specific positional codings are designed to more accurately identify the click-point object of the query image in the VSPE module. In feature-level, a hybrid attention in the CSHA module is introduced by combining channel attention and spatial attention mechanisms simultaneously for learning discriminative features. Extensive experimental results demonstrate that the proposed VAGeo gains a significant performance improvement, i.e., improving acc@0.25/acc@0.5 on the CVOGL dataset from 45.43%/42.24% to 48.21%/45.22% for ground-view, and from 61.97%/57.66% to 66.19%/61.87% for drone-view.

关键词： Location awareness Accuracy Attention mechanisms Image coding Signal processing Encoding Satellite images Object recognition Speech processing Drones

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Online Identification of Boost Converter Components with Multiple Updating RLS Algorithm

Online Identification of Boost Converter Components with Mul...

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Chinese control Conference (CCC)

作者： Tong Zhou Zhicheng Zhang Zhiqiang Zuo Yijing Wang Peng Li Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin University Tianjin P. R. China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai P. R. China

In this paper, component parameters of the boost converter are identified online using a multiple updating recursive least squares (MURLS) algorithm. The component parameters, such as resistance, inductor inductance and capacitor capacitance, are obtained directly through the identification procedure rather than transfer function coefficients. The MURLS algorithm is applied to improve the rapidity of system identification compared to the traditional recursive least squares (RLS) algorithm, which is verified by a comparative simulation between MURLS and RLS and the simulation of a load-switching scenario.

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Progress in models for coupled human and natural systems

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Science China Earth Sciences 2024年第11期67卷 3631-3637页

作者： Tianxiang YUE Chenchen WU Wenjiao SHI Yongzhong TIAN Qing WANG Yimin LU Lili ZHANG State Key Laboratory of Resources and Environment Information System Institute of Geographical Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China College of Resources and Environment University of Chinese Academy of SciencesBeijing 101408China School of Geographical Sciences Southwest UniversityChongqing 400715China National Institute of Environmental Health Chinese Center for Disease Control and PreventionBeijing 100021China National Engineering Research Center of Geospatial Information Technology Fuzhou UniversityFuzhou 350108China The Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China

1. Introduction Malthus (1798) was one of the earliest researchers to propose a coupled human-natural system (CHANS) model, particularly in his analysis of the relationship between population growth and food supply. He argued that while population grows geometrically, food supply increases only arithmetically, suggesting that this imbalance could eventually lead to a food crisis due to diminishing per capita food availability (Malthus, 1798).

关键词： Malthus eventually population

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Predominant types of regional cold waves in North China and their historical changes

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Atmospheric and Oceanic Science Letters 2024年第4期17卷 46-51页

作者： Xinyi Cheng Yiyi Zhang Jiandong Li Xin Hao Center for Climate System Prediction Research/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster Ministry of EducationNanjing University of Information Science&TechnologyNanjingChina Nansen-Zhu International Research Centre Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment TechnologySchool of Environmental Science and EngineeringNanjing University of Information Science&TechnologyNanjingChina

寒潮事件对东亚地区的社会经济,生态系统和人体健康影响巨大.根据1980-2019年间10月至次年3月的每日寒潮记录和K-means聚类,本文识别出了中国两种不同类型的区域性寒潮(T1和T2). T1区域性寒潮主要影响东北地区,T2区域性寒潮则主要影响... 详细信息

寒潮事件对东亚地区的社会经济,生态系统和人体健康影响巨大.根据1980-2019年间10月至次年3月的每日寒潮记录和K-means聚类,本文识别出了中国两种不同类型的区域性寒潮(T1和T2). T1区域性寒潮主要影响东北地区,T2区域性寒潮则主要影响华北和东部地区.与T1区域性寒潮相比, T2区域性寒潮强度更强,持续时间更长,影响范围更广. 1980–2019年期间, T1区域性寒潮的频率显著增加,而T2区域性寒潮的频率则没有趋势变化. T1和T2区域性寒潮事件均与西伯利亚高压增强有关,然而与它们相关的对流层中层波列明显不同.在T1区域性寒潮事件发生期间,西伯利亚-蒙古上空出现负-正模态的500-hPa位势高度异常波列,削弱了东亚大槽,导致西伯利亚冷空气东移.T1区域寒潮频次增加趋势可能与全球变暖引起的500-hPa位势高度的线性趋势变化有关.与T2区域寒潮事件相关的波列则在乌拉尔山脉,蒙古和华北地区形成了脊-槽-脊环流异常,导致冷空气向东南方向入侵.本文得出结论,由于两类区域寒潮影响不同,西伯利亚高压增强和对流层中层波列模态在我国区域性寒潮事件的预报中应综合考虑.

关键词：寒潮 K-means聚类西伯利亚高压波列

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Nonlinear Deep Subspace Network for Micro-expression Recognition 3

Nonlinear Deep Subspace Network for Micro-expression Recogni...

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3rd Workshop on Facial Micro-Expression: Advanced Techniques for Multi-Modal Facial Expression Analysis, FME 2023

作者： Feng, Weijia Xu, Manlu Chen, Yuanxu Wang, Xiaofeng Guo, Jia Dai, Lei Wang, Nan Zuo, Xinyu Li, Xiaoxue College of Computer and Information Engineering Tianjin Normal University Tianjin China Ping An Technology Shenzhen China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin China

ISBN: (纸本)9798400702853

Deep learning (DL) models have been widely studied in the field of micro-expression recognition (MER). However, micro-expressions (MEs) suffer from small number of samples and difficulty in extracting subtle and transient features, resulting in limited improvement in the recognition performance. In addition, DL models are prone to overfitting problems and are difficult to extract discriminative features of facial actions from ME images or sequences. To address these issues, we propose a MER method that combines a nonlinear deep subspace network and optical flow features. Firstly, facial motion features are captured using optical flow computation, and then the optical flow features are input into a kernel principal component analysis network (KPCANet) to further learn deeper spatio-temporal features. Finally, a linear support vector machine (SVM) is used for ME classification. Experiments conducted on four public spontaneous ME datasets including SMIC, CASME, CASME II and SAMM validate the effectiveness of the proposed method. The experimental results demonstrate that the proposed method achieves even better recognition performance compared to existing state-of-the-art MER methods. © 2023 ACM.

关键词： Principal component analysis

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