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93rd Annual Meeting of the International Association of Applied Mathematics and Mechanics, GAMM 2023

作者： Horváth, Ádám Béda, Péter Department of Railway Vehicles and Vehicle System Analysis Faculty of Transportation Engineering and Vehicle Engineering Budapest University of Technology and Economics Budapest Hungary

Safety and efficiency are key aspects of research and development in the automotive industry, especially in the field of safety-critical subsystems, such as brake systems. The effect of time delay arise in brake systems, this adverse effect can cause performance degradations or make the brake system unstable. In this study, the bifurcation analysis of a wheel slip control feedback loop is presented. The control system consists of a wheel and a tyre, delayed actuator dynamics, and an LQR (linear quadratic regulator) that is designed to operate under relatively low wheel slip, during service braking. As a result, it is shown, that if time delay is neglected, the steady-state solution of the model is globally stable using the LQ optimal controller gains. However, considering nonzero time-delay may cause a subcritical Hopf-bifurcation, and an unstable limit-cycle exists around the steady-state solution in a large domain of time-delay parameters. Critical bifurcation maps and simulation results with more detailed system models are generated and shown in the study. © 2023 The Authors. Proceedings in Applied Mathematics and Mechanics published by Wiley-VCH GmbH.

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Online Optimization in Power systems With High Penetration of Renewable Generation:Advances and Prospects

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 839-858页

作者： Zhaojian Wang Wei Wei John Zhen Fu Pang Feng Liu Bo Yang Xinping Guan Shengwei Mei Key Laboratory of System Control and Information Processing Ministry of Education of ChinaDepartment of AutomationShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Power System and the Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Institute of High Performance Computing(IHPC) Agency for Science Technology and Research(A*STAR)Singapore 138632Singapore

Traditionally,offline optimization of power systems is acceptable due to the largely predictable loads and reliable *** increasing penetration of fluctuating renewable generation and internet-of-things devices allowing for fine-grained controllability of loads have led to the diminishing applicability of offline optimization in the power systems domain,and have redirected attention to online optimization ***,online optimization is a broad topic that can be applied in and motivated by different settings,operated on different time scales,and built on different theoretical *** paper reviews the various types of online optimization techniques used in the power systems domain and aims to make clear the distinction between the most common techniques *** particular,we introduce and compare four distinct techniques used covering the breadth of online optimization techniques used in the power systems domain,i.e.,optimization-guided dynamic control,feedback optimization for single-period problems,Lyapunov-based optimization,and online convex optimization techniques for multi-period ***,we recommend some potential future directions for online optimization in the power systems domain.

关键词： optimization Lyapunov optimization online convex optimization online optimization optimization-guided control

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Speech Method for Caregiving Robots Considering Uncertainty 16th

Speech Method for Caregiving Robots Considering Uncertainty

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16th International Conference on Social Robotics, ICSR + AI 2024

作者： Shindo, Arisa Kawasaki, Yosuke Takahashi, Masaki School of Science for Open and Environmental Systems Graduate School of Science and Technology Keio University Kanagawa Japan Department of System Design Engineering Faculty of Science and Technology Keio University Kanagawa Japan

ISBN: (纸本)9789819635214

Recent studies have explored the integration of large language models (LLMs) into caregiving robots. The use of LLMs facilitates the generation of human-like natural dialogues and diverse, varied expressions. However, in case of a lack of direct and specific instructions from a user, gaining an accurate understanding of the user's intent is challenging, which may result in miscommunication. Thus, this study proposed a method to achieve robust communication even in the absence of direct instructions by considering the uncertainty in destination prediction probabilities. The proposed system leveraged GPT-4 to generate various Japanese speech content candidates and employed neighborhood components analysis to facilitate dimensionality reduction. Consequently, notable features of the rich linguistic embeddings were preserved while transforming them into manageable data. The system selected appropriate utterances based on the destination prediction probabilities. Furthermore, this study investigated changes in the speech content according to the variations in these probabilities, and the incorporation of uncertainty in communication was validated. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Dimensionality reduction

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Single Block Encoder-Decoder Transformer Model for Multi-Step Traffic Flow Forecasting 6

Single Block Encoder-Decoder Transformer Model for Multi-Ste...

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6th IEEE Symposium on Computers and Informatics, ISCI 2024

作者： Omar, Mas Yakub, Fitri Talip, Mohamad Sofian Abu Maslan, Mohd Nazmin Sinha, Vijay Kumar Muljono, Muljono Universiti Teknologi Malaysia Wee Laboratory Malaysia-Japan International Institute of Technology Kuala Lumpur Malaysia Universiti Teknologi Malaysia Malaysia-Japan International Institute of Technology Department of Electronic System Engineering Kuala Lumpur Malaysia University of Malaya Faculty of Engineering Department of Electrical Engineering Kuala Lumpur Malaysia Universiti Teknikal Malaysia Faculty of Industrial and Manufacturing Technology and Engineering Melaka Malaysia Chitkara University School of Engineering & Technology Department of Computer Science & Engineering Himachal Pradesh India Universitas Dian Nuswantoro Faculty of Computer Science Semarang Indonesia

ISBN: (纸本)9798350353853

Accurate traffic flow forecasting is crucial for managing and planning urban transportation systems. Despite the widespread use of sequence modelling models like Long Short-Term Memory (LSTM) for this purpose, the potential of Transformer models remains underexplored. This is particularly true for the simplest form of a single block encoder-decoder Transformer model, which can be finely tuned through optimised hyperparameters. This paper examines the performance of a singular horizon-step forecasting method for multi-step traffic flow forecasting using a proposed Single Block Encoder-Decoder Transformer model optimised with a Grid Search algorithm. Results demonstrate that this model can enhance forecasting accuracy compared to the state-of-the-art LSTM model typically used for multi-step forecasting. The model effectively captures long-range temporal dependencies within a single road traffic flow dataset. It was tested on hourly traffic flow data to forecast the next 24 hours for the I5-North freeway in California, sourced from the Caltrans Performance Measurement system. The optimal configuration included an embedding dimension of 32, a feed-forward dimension of 128, and 8 attention heads. Results show a significant improvement, with a 4.7% reduction in Root Mean Squared Error compared to an LSTM model with two hidden layers of 100 neurons each, showcasing the potential of Single Block Encoder-Decoder Transformer models for real-world traffic prediction applications. © 2024 IEEE.

关键词： Mean square error

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Effective and Imperceptible Adversarial Textual Attack Via Multi-objectivization

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ACM Transactions on Evolutionary Learning and Optimization 2024年第3期4卷 1-23页

作者： Liu, Shengcai Lu, Ning Hong, Wenjing Qian, Chao Tang, Ke Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen College of Engineering South Tower 1088 Xueyuan Avenue Guangdong Shenzhen518055 China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong999077 Hong Kong National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen 10F Zhizhen Building Canghai Campus 3688 Nanhai Avenue Guangdong Shenzhen China National Key Laboratory for Novel Software Technology School of Artificial Intelligence Nanjing University Nanjing International College Area Xianlin Campus 163 Xianlin Avenue Jiangsu Nanjing China

The field of adversarial textual attack has significantly grown over the past few years, where the commonly considered objective is to craft adversarial examples (AEs) that can successfully fool the target model. However, the imperceptibility of attacks, which is also essential for practical attackers, is often left out by previous studies. In consequence, the crafted AEs tend to have obvious structural and semantic differences from the original human-written text, making them easily perceptible. In this work, we advocate leveraging multi-objectivization to address such an issue. Specifically, we reformulate the problem of crafting AEs as a multi-objective optimization problem, where the attack imperceptibility is considered as an auxiliary objective. Then, we propose a simple yet effective evolutionary algorithm, dubbed HydraText, to solve this problem. HydraText can be effectively applied to both score-based and decision-based attack settings. Exhaustive experiments involving 44,237 instances demonstrate that HydraText consistently achieves competitive attack success rates and better attack imperceptibility than the recently proposed attack approaches. A human evaluation study also shows that the AEs crafted by HydraText are more indistinguishable from human-written text. Finally, these AEs exhibit good transferability and can bring notable robustness improvement to the target model by adversarial training. © 2024 Copyright held by the owner/author(s).

关键词： Multiobjective optimization

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Comparative study on the hydrogen storage performance of as-milled MgRENi rapid quenched alloy catalyzed by metal sulfides

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Journal of Magnesium and Alloys 2024年第5期12卷 2010-2023页

作者： Xiaoping Dong Zhaoqing Zhang Liying Yang Shenghai Xin Dandan Su Zhiyuan Li Department of Mechanical Design and Manufacture and Automation Hebei UniversityBaoding 071000PR China Baoding New Energy Vehicle Power Engineering Technology Research Center Hebei UniversityBaoding 071002PR China Hebei Technology Innovation Center for Lightweight of New Energy Vehicle Power System(Preparation) Hebei UniversityBaoding 071002PR China

The composites of Mg_(20)Pr_(1)Sm_(3)Y_(1)Ni_(10)as-quenched alloy and 3 wt.%M(M=CoS,CoS_(2),MoS_(2))catalyst were prepared by high-speed vibration ball *** effects of metal sulfides on the hydrogenation and dehydrogenation dynamics of alloys were *** results show that the as-milled composites contain a large number of amorphous embedded by a small amount of nanocrystals,and there are many point *** ball milling,the crystal grain size in the composites containing CoS is relatively larger,followed by CoS_(2)and MoS_(2)*** hydrogenation,the amorphous phase is crystallized to form Mg_(2)NiH_(4),YH_(3),Pr_(8)H_(18.96),Sm_(3)H_7,Mg,Co or Mo phases,however,Mg_(2)Ni,YH_(2),PrH_(2)and Ni_(3)Y phases appeared after *** maximum hydrogenation capacity of the composites containing CoS,CoS_(2)and MoS_(2)are 3.939,4.265 and 4.507 wt.%,*** hydrogenation saturation ratio of composite containing MoS_(2)is higher than that of the composites containing CoS and CoS_(2).The dehydrogenation activation energy of the composites containing CoS,CoS_(2)and MoS_(2)is 107.76,68.43 and 63.28 ***^(-1).H_(2).On the improvement of hydrogen storage performance of Mg_(20)Pr_(1)Sm_(3)Y_(1)Ni_(10)alloy,the catalytic effect of MoS_(2)sulfide is better than that of CoS_(2)sulfide,and which is better than CoS sulfide.

关键词： Mg_(20)Pr_(1)Sm_(3)Y_(1)Ni_(10)as-quenched alloy CoS CoS_(2)and MoS_(2)sulfide Milling Activation energy Hydrogen storage dynamics

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Pango FPGA Implementation of a Real-Time Display system for Multi-Channel Video Processing

Pango FPGA Implementation of a Real-Time Display System for ...

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2024 IEEE International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2024

作者： Huang, Cao Du, Lifu Peng, Yu Xiang, Gang Yu, Yang Chen, Jingyi School of Electronics Information Engineering Habin Institute of Technology Harbin China Beijing Aerospace Automatic Control Institute Beijing China Beijing Aerospace Automatic Control Institute Department of System Engineering Beijing China

ISBN: (纸本)9798350388855

A Pango FPGA-based solution for merging and processing multiple independent video streams and reconstructing a real-time display system is presented. The system handles each video stream individually, then produces a combined video output in HDMI format. To ensure high efficiency and low latency, a parallel processing scheme and a hardware-oriented architecture are employed. The Pango PG50K FPGA board acts as the central hardware for managing inputs, reconstructing video, and producing outputs. Rapid-access DDR3-SDRAM ensures efficient data caching and signal integrity. This system is ideal for applications requiring rapid response, such as traffic monitoring and industrial automation, and supports quick algorithm iteration and optimization, enhancing performance and adaptability. © 2024 IEEE.

关键词： Video streaming

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Behaviour-diverse automatic penetration testing:a coverage-based deep reinforcement learning approach

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Frontiers of Computer Science 2025年第3期19卷 15-24页

作者： Yizhou YANG Longde CHEN Sha LIU Lanning WANG Haohuan FU Xin LIU Zuoning CHEN Zhongguancun Laboratory Beijing 100081China Zhejiang Lab Hangzhou 311121China National Research Centre of Parallel Computer Engineering and Technology Wuxi 214000China Faculty of Geographical Science Beijing Normal UniversityBeijing 100875China Department of Earth System Science Tsinghua UniversityBeijing 100084China

Reinforcement Learning(RL)is gaining importance in automating penetration testing as it reduces human effort and increases ***,given the rapidly expanding scale of modern network infrastructure,the limited testing scale and monotonous strategies of existing RLbased automated penetration testing methods make them less effective in practical *** this paper,we present CLAP(Coverage-Based Reinforcement Learning to Automate Penetration Testing),an RL penetration testing agent that provides comprehensive network security assessments with diverse adversary testing behaviours on a massive *** employs a novel neural network,namely the coverage mechanism,to address the enormous and growing action spaces in large *** also utilizes a Chebyshev decomposition critic to identify various adversary strategies and strike a balance between *** results across various scenarios demonstrate that CLAP outperforms state-of-the-art methods,by further reducing attack operations by nearly 35%.CLAP also provides enhanced training efficiency and stability and can effectively perform pen-testing over large-scale networks with up to 500 ***,the proposed agent is also able to discover pareto-dominant strategies that are both diverse and effective in achieving multiple objectives.

关键词： network security penetration testing reinforcement learning artificial intelligence

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IBATree: A Novel Method for Interpretable Cancer Cell Diagnosis Using Information Bottleneck Attribution

IBATree: A Novel Method for Interpretable Cancer Cell Diagno...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Raza, Muhammad Umair Chen, Jie Nawaz, Adil Saeed, Faisal Leung, Victor C.M. Li, Jianqiang Wang, Zhaoxia Shenzhen University College of Computer Science and Software Engineering China Shenzhen University National Engineering Laboratory for Big Data System Computing Technology China Shenzhen Children's Hospital Department of Gastroenterology China

ISBN: (纸本)9798350386226

Deep Neural Networks (DNNs) have demonstrated remarkable performance in classification and regression tasks on RGB-based pathological inputs. The network's prediction mechanism must be interpretable to establish trust in the clinical routine. One principal approach to interpretation is feature attribution. Feature attribution methods identify the importance of input features for the output prediction. Building on the Information Bottleneck Attribution (IBA) method, we recognize the RGB's input regions with high mutual information with the network's output for each prediction. IBA identifies input regions that have sufficient predictive information. In this paper, we introduce "IBATree", a novel approach that combines IBA with decision trees to enhance both the interpretability and accuracy of DNNs in cancer cell classification. Our method leverages the information bottleneck framework to inject noise into feature maps and then isolates the most informative features for model predictions while maintaining high classification performance. We evaluated our proposed approach on three datasets - CNMC, ISBI2016, and BreaKHis - demonstrating competitive accuracy and producing clear interpretations. This makes IBATree particularly suitable for clinical applications, where understanding the rationale behind predictions is crucial. Our results show that IBATree provides reliable predictions and valuable insights into feature importance, paving the way for its application in various biomedical domains. © 2024 IEEE.

关键词： Diseases

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CONTROL AUGMENTATION system DESIGN FOR THE QUAD TILT-WING UAV VIA H∞ STRUCTURE WITH GWO 33

CONTROL AUGMENTATION SYSTEM DESIGN FOR THE QUAD TILT-WING UA...

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33rd Congress of the International Council of the Aeronautical Sciences, ICAS 2022

作者： Deveerasetty, Kranthi Kumar Oka, Koichi Harada, Akinori Department of Intelligent Mechanical Engineering School of System Engineering Kochi University of Technology 782-8502 Japan

ISBN: (纸本)9781713871163

In this paper, an approach based on H∞ is proposed, in which reasonable bounds is employed and Grey wolf optimization is used to design the Control Augmentation system (CAS) for a Quad Tilt-Wing Unmanned Aerial Vehicle (QTW-UAV). Grey Wolf Optimization (GWO) is used to find the global optimal proportional-integral gains via H∞ structure. The CAS controller gains has been computed for a QTW-UAV from H∞ criteria. Simulation results are presented to show the validation of the technique. © 2022 ICAS. All Rights Reserved.

关键词： Unmanned aerial vehicles (UAV)

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