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Immobilizing ultrafine bimetallic PtAg alloy onto uniform MnO_(2) microsphere as a highly active catalyst for CO oxidation

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Chinese Chemical Letters 2021年第6期32卷 2057-2060页

作者： Shengpeng Mo Peng Peng Yinchang Pei Taiming Shen Qinglin Xie Mingli Fu Yunfa Chen Daiqi Ye College of Environment Science and Engineering Guilin University of TechnologyGuilin 541004China School of Environment and Energy South China University of TechnologyGuangzhou 510006China Guangxi Key Laboratory of Theory and Technology for Environmental Pollution Control Guilin University of TechnologyGuilin 541004China State Key Laboratory of Multi-Phase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China

Herein,a facile glycol reduction route is successful employed to synthesize bimetallic Pt Ag alloys with homogeneous distribution of sizes and *** studies reveal that the ultrafine Pt Ag alloys with well-defined sizes from around 3.3 nm to 5.8 nm are immobilized onto MnO_(2)microsphere,which remarkably enhances the catalytic performances for CO ***,quasi in-situ X-ray photoelectron spectroscopy(XPS)result reveals that both Mn and Pt ions on the surface of catalysts would realize alternating reduction-oxidation by CO and O_(2)molecules,and the oxygen vacancy sites could be replenished and excited by gas-phase O_(2).

关键词： Bimetallic alloys PtAg NPs MnO_(2) Quasi in-situ XPS CO oxidation

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The Shadow of Fraud: The Emerging Danger of AI-powered Social engineering and its Possible Cure

arXiv

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arXiv 2024年

作者： Yu, Jingru Yu, Yi Wang, Xuhong Lin, Yilun Yang, Manzhi Qiao, Yu Wang, Fei-Yue Shanghai Artificial Intelligence Laboratory Shanghai200240 China The Macau Institute of Systems Engineering Macau University of Science and Technology China Eversec Technology Company Ltd. Beijing100080 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

Social engineering (SE) attacks remain a significant threat to both individuals and organizations. The advancement of Artificial Intelligence (AI), including diffusion models and large language models (LLMs), has potentially intensified these threats by enabling more personalized and convincing attacks. This survey paper categorizes SE attack mechanisms, analyzes their evolution, and explores methods for measuring these threats. It highlights the challenges in raising awareness about the risks of AI-enhanced SE attacks and offers insights into developing proactive and adaptable defense strategies. Additionally, we introduce a categorization of the evolving nature of AI-powered social engineering attacks into"3E phases": Enlarging, wherein the magnitude of attacks expands through the leverage of digital media;Enriching, introducing novel attack vectors and techniques;and Emerging, signifying the advent of novel threats and methods. Moreover, we emphasize the necessity for a robust framework to assess the risk of AI-powered SE attacks. By identifying and addressing gaps in existing research, we aim to guide future studies and encourage the development of more effective defenses against the growing threat of AI-powered social engineering. Copyright © 2024, The Authors. All rights reserved.

关键词： Artificial intelligence

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Formulation of Optimization Problems with Radiation Field Phases as Design Variables for Pattern Synthesis of Linear Antenna Arrays

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China Communications 2022年第12期19卷 86-100页

作者： Fei Zhao Jun He Sanyou Zeng Changhe Li Qinghui Xu Zhigao Zeng School of Mechanical Engineering and Electronic Information China University of GeosciencesWuhan 430074China Science and Technology on Blind Signal Processing Laboratory Southwest Electronics and Telecommunication Technology Research InstituteChengdu 610041China School of Automation China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074China College of Computer Hunan University of TechnologyZhuzhou CityHunan Province412007China

Pattern synthesise of antenna arrays is usually complicated optimization problems,while evolutionary algorithms(EAs)are promising in solving these *** paper does not propose a new EA,but does construct a new form of optimization *** new optimization formulation has two differences from the common *** is the objective function is the field error between the desired and the designed,not the usual amplitude error between the desired and the *** difference is beneficial to decrease complexity in some *** second difference is that the design variables are changed as phases of desired radiation field within shaped-region,instead of excitation *** difference leads to the reduction of the number of design variables.A series of synthesis experiments including equally and unequally spaced linear arrays with different pattern shape requirements are applied,and the effectiveness and advantages of the proposed new optimization problems are *** results show that the proposing a new optimization formulation with less complexity is as significant as proposing a new algorithm.

关键词： pattern synthesis evolutionary algorithms linear antenna arrays

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SAD-TIME: a Spatiotemporal-fused network for depression detection with Automated multi-scale Depth-wise and TIME-interval-related common feature extractor

arXiv

引用

arXiv 2024年

作者： Wang, Han-Guang Hou, Hui-Rang Jin, Li-Cheng Xu, Chen-Yang Zhang, Zhong-Yi Meng, Qing-Hao Zhang, Yong-Hui Tianjin Key Laboratory of Process Measurement and Control Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University Tianjin300072 China Department of Psychiatry Tianjin Anding Hospital Mental Health Center Tianjin Medical University China

Background and Objective: Depression is a severe mental disorder, and accurate diagnosis is pivotal to the cure and rehabilitation of people with depression. However, the current questionnaire-based diagnostic methods could bring subjective biases and may be denied by subjects. In search of a more objective means of diagnosis, researchers have begun to experiment with deep learning-based methods for identifying depressive disorders in recent years. Methods: In this study, a novel Spatiotemporal-fused network with Automated multi-scale Depth-wise and TIME-interval-related common feature extractor (SAD-TIME) is proposed. SAD-TIME incorporates an automated nodes’ common features extractor (CFE), a spatial sector (SpS), a modified temporal sector (TeS), and a domain adversarial learner (DAL). The CFE includes a multiscale depth-wise 1D-convolutional neural network and a time-interval embedding generator, where the unique information of each channel is preserved. The SpS fuses the functional connectivity with the distance-based connectivity containing spatial position of EEG electrodes. A multi-head-attention graph convolutional network is also applied in the SpS to fuse the features from different EEG channels. The TeS is based on long short-term memory and graph transformer networks, where the temporal information of different time-windows is fused. Moreover, the DAL is used after the SpS to obtain the domain-invariant feature. Results: Experimental results under tenfold cross-validation show that the proposed SAD-TIME method achieves 92.00% and 94.00% depression classification accuracies on two datasets, respectively, in cross-subject mode. Conclusion: SAD-TIME is a robust depression detection model, where the automatedly-generated features, the SpS and the TeS assist the classification performance with the fusion of the innate spatiotemporal information in the EEG signals. Copyright © 2024, The Authors. All rights reserved.

关键词： Convolutional neural networks

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LogisticsVISTA: 3D Terminal Delivery Services With UAVs, UGVs and USVs Based on Foundation Models and Scenarios engineering

LogisticsVISTA: 3D Terminal Delivery Services With UAVs, UGV...

引用

2024 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2024

作者： Tian, Yonglin Lin, Fei Zhang, Xinyuan Ge, Jingwei Wang, Yutong Dai, Xingyuan Lv, Yisheng Wang, Fei-Yue University of Chinese Academy of Sciences Beijing100049 China Tsinghua University Department of Automation Beijing100084 China Institute of Automation Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems State Key Laboratory for Management and Control of Complex Systems Beijing100190 China Macau University of Science and Technology Faculty of Innovation Engineering Department of Engineering Science 999078 China

Intelligent logistics with autonomous vehicles is promising to improve the efficiency of rapidly expanding delivery systems. However, complex environments, diverse packages, and irregular human interaction have imposed challenges to the application of unmanned delivery vehicles. Combining various forms of vehicles and developing knowledge-driven delivery services have been the key to further facilitating the upgrading of logistics systems. In this paper, we propose an integrated framework named LogisticsVISTA (Logistics on Vehicles with Intelligent systems for Transport Automation) comprised of UAVs (Unmanned Aerial Vehicles), UGVs (Unmanned Ground Vehicles), and USVs (Unmanned Surface Vehicles) to provide timely and flexible 3D delivery services. In LogisticsVISTA, we design Large language models (LLMs) and large multimodal models (LMMs) for task planning, active perception, autonomous decision, and human-machine interaction. Besides, virtual-real integrated parallel scenarios are constructed to provide the playing ground for embodied agents efficiently and flexibly. © 2024 IEEE.

关键词： Drones

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Sensing With Random Communication Signals

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IEEE Network 2025年

作者： Lu, Shihang Liu, Fan Xiong, Yifeng Du, Zhen Cui, Yuanhao Li, Shuangyang Yuan, Weijie Yang, Jie Jin, Shi Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing100876 China Nanjing University of Information Science and Technology School of Electronic and Information Engineering Nanjing210044 China Technical University of Berlin Faculty of Electrical Engineering and Computer Science Berlin10587 Germany Shenzhen518055 China Frontiers Science Center for Mobile Information Communication and Security China Southeast University MOE Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing211189 China

Communication-centric Integrated Sensing and Communication (ISAC) has been recognized as a promising methodology to implement wireless sensing functionality over existing network architectures, due to its cost-effectiveness and backward compatibility to legacy cellular systems. However, the inherent randomness of the communication signal may incur huge fluctuations in sensing capabilities, leading to unfavorable detection and estimation performance. To address this issue, we elaborate on random ISAC signal processing methods in this article, aiming at improving the sensing performance without unduly deteriorating the communication functionality. Specifically, we commence by discussing the fundamentals of sensing with random communication signals, including the performance metrics and optimal ranging waveforms. Building on these concepts, we then present a general framework for random ISAC signal transmission, followed by an in-depth exploration of time-domain pulse shaping, frequency-domain constellation shaping, and spatial-domain precoding methods. We provide a comprehensive overview of each of these topics, including models, results, and design guidelines. Finally, we conclude this article by identifying several promising research directions for random ISAC signal transmission. © 2025 IEEE.

关键词： Mobile telecommunication systems

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Development of a 3-RRS Micromanipulator Based on Origami-Inspired Spherical Joint

Development of a 3-RRS Micromanipulator Based on Origami-Ins...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Haoqi Han Xiaoming Liu Yan Chen Hao Pang Xiaoqing Tang Dan Liu Qiang Huang Tatsuo Arai Beijing Advanced Innovation Center for Intelligent Robots and Systems and School of Mechatronical Engineering Key Laboratory of Biomimetic Robots and Systems Ministry of Education State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Department of Micro-Nano Electronics Shanghai Jiao Tong University China Center for Neuroscience and Biomedical Engineering The University of Electro-Communications Tokyo Japan

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In recent years, micromanipulation technology has achieved extensive applications in industry and life science. Improving the precision and bandwidth of the micromanipulator and simultaneously reducing size, weight, and cost pose significant challenges to the existing micromanipulator design and fabrication methods. Here, we propose a 3-RRS micromanipulator with an origami-inspired spherical joint based on the PC-MEMS process, aiming for miniaturization and cost-effectiveness. The spherical joint allows rotations of 140° around the x-axis approximately, 140° around the y-axis approximately, and 20° around the z-axis approximately. The micromanipulator has weights of 0.8 g, dimensions of 16 mm × 16 mm × 22 mm, and workspace of 0.7 mm 3 . The end platform of the micromanipulator can be equipped with various effectors to accomplish different kinds of tasks. Experimental results validated its high precision and bandwidth, exhibiting its potential to perform intricate micromanipulation tasks.

关键词： Industries Fabrication Costs Micromanipulators Design methodology Bandwidth Life sciences

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DriveRP: RAG and Prompt engineering Embodied Parallel Driving in Cyber-Physical-Social Spaces

DriveRP: RAG and Prompt Engineering Embodied Parallel Drivin...

引用

Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Jun Huang Hao Ma Tengchao Zhang Fei Lin Siji Ma Xiao Wang Fei-Yue Wang Faculty of Innovation Engineering Macau University of Science and Technology Macau China School of Artificial Intelligence Anhui University Hefei China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350349252

ISBN: (纸本)9798350349269

In recent years, numerous technological advancements in Artificial Generative Intelligences (AGIs) have demonstrated significant potential to transform the intelligence acquisition mechanisms in connected autonomous vehicles (CAVs). Integrating technologies like ChatGPT into CAVs can enhance human-machine interactions. However, the emergence of such new traffic entities may introduce unforeseen hallucinations and complex risks that surpass our current understanding. To address these challenges, Retrieval-Augmented Generation (RAG) and prompt engineering technologies are being explored to enhance the reliability and safety of autonomous driving systems. RAG retrieves relevant contextual information, such as driving experiences and real-time road network status, from external databases to ensure that foundation models have access to accurate and timely data for informed decision-making. Prompt engineering optimizes the performance of large language models in autonomous driving systems by designing and refining prompts that guide the models’ responses, thereby improving their relevance and accuracy in various driving scenarios. Together, these technologies enhance the robustness and trustworthiness of autonomous driving systems. This paper proposes DriveRP, a framework that integrates RAG and prompt engineering within the Descriptive-Predictive-Prescriptive Intelligence framework of Parallel Driving theory. DriveRP aims to enhance the safety and interpretability of autonomous vehicle trajectory planning, decision-making, and motion control, ultimately achieving the "6S" goals. Grounded in Digital Twins and Metaverse-embodied parallel driving theory, DriveRP provides the infrastructure and foundational intelligence for parallel driving with Multi-modal Large Lange Models(MLLMs). Additionally, the paper discusses future trends and potential research directions, focusing on the "6S" goals of parallel driving: Smart, Safe, Secure, Sensitive, Sustainable, and Serviceable.

关键词： Accuracy Trajectory planning Decision making Transportation Transforms Safety Digital twins Prompt engineering Motion control Autonomous vehicles

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Parallel control for Optimal Tracking via Adaptive Dynamic Programming

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IEEE/CAA Journal of Automatica Sinica 2020年第6期7卷 1662-1674页

作者： Jingwei Lu Qinglai Wei Fei-Yue Wang School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 The State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078 Qingdao Academy of Intelligent Industries Qingdao 266109China

This paper studies the problem of optimal parallel tracking control for continuous-time general nonlinear *** existing optimal state feedback control,the control input of the optimal parallel control is introduced into the feedback ***,due to the introduction of control input into the feedback system,the optimal state feedback control methods can not be applied *** address this problem,an augmented system and an augmented performance index function are proposed ***,the general nonlinear system is transformed into an affine nonlinear *** difference between the optimal parallel control and the optimal state feedback control is analyzed *** is proven that the optimal parallel control with the augmented performance index function can be seen as the suboptimal state feedback control with the traditional performance index ***,an adaptive dynamic programming(ADP)technique is utilized to implement the optimal parallel tracking control using a critic neural network(NN)to approximate the value function *** stability analysis of the closed-loop system is performed using the Lyapunov theory,and the tracking error and NN weights errors are uniformly ultimately bounded(UUB).Also,the optimal parallel controller guarantees the continuity of the control input under the circumstance that there are finite jump discontinuities in the reference ***,the effectiveness of the developed optimal parallel control method is verified in two cases.

关键词： Adaptive dynamic programming(ADP) nonlinear optimal control parallel controller parallel control theory parallel system tracking control neural network(NN)

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Anomaly Detection Based on Principle of Justifiable Granularity and Probability Density Estimation

Anomaly Detection Based on Principle of Justifiable Granular...

引用

2023 China Automation Congress, CAC 2023

作者： Du, Sheng Ma, Xian Li, Xiang Wu, Min Cao, Weihua Pedrycz, Witold School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University Faculty of Engineering and Natural Sciences Department of Computer Engineering Istanbul Sariyer Turkey

ISBN: (纸本)9798350303759

Anomaly detection is essential to ensure the safety of industrial processes. This paper presents an anomaly detection approach based on the probability density estimation and principle of justifiable granularity. First, time series data are transformed into a two-dimensional information granule by the principle of justifiable granularity. Then, the test statistic is constructed, and the probability density and cumulative distribution functions of the test statistic are calculated. Next, the confidence level determines the test threshold. Finally, the time series data of a key parameter in the sintering process is used as a case study. The experimental result demonstrates that the proposed approach can detect abnormal time series data effectively, providing an accurate and effective solution for detecting time series anomalies in industrial processes. © 2023 IEEE.

关键词： Time series

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