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IEEE Transactions on Artificial Intelligence 2025年第5期6卷 1080-1099页

作者： Mai, Weijian Zhang, Jian Fang, Pengfei Zhang, Zhijun South China University of Technology School of Automation Science and Engineering Guangzhou510640 China Southeast University School of Computer Science and Engineering Nanjing210096 China South China University of Technology Key Library of Autonomous Systems and Network Control Ministry of Education The School of Automation Science and Engineering Guangzhou510640 China Institute for Super Robotics Huangpu Guangzhou510555 China Nanchang University Jiangxi Thousand Talents Plan Nanchang330031 China Jishou University College of Computer Science and Engineering Jishou416000 China Guangdong Artificial Intelligence and Digital Economy Laboratory Pazhou Lab Guangzhou510335 China Shaanxi University of Technology Shaanxi Provincial Key Laboratory of Industrial Automation School of Mechanical Engineering Hanzhong723001 China Changsha Normal University School of Information Science and Engineering Changsha410100 China Guangdong University of Petrochemical Technology School of Automation Science and Engineering Institute of Artificial Intelligence and Automation Maoming525000 China

In the era of artificial intelligence generated content (AIGC), conditional multimodal synthesis technologies (e.g., text-to-image) are dynamically reshaping the natural content. Brain signals, serving as potential reflections of how the brain interprets external information, exhibit a distinctive one-to-many correspondence with various external modalities. This correspondence makes brain signals emerge as a promising guiding condition for multimodal synthesis (e.g., image, text, and audio), which is crucial for developing practical brain–computer interface systems and unraveling complex mechanisms underlying human perception. This survey comprehensively examines the emerging field of brain-conditional multimodal synthesis, termed AIGC-brain, to delineate the current landscape and future directions. To begin, related neuroimaging datasets and generative models are introduced as the foundation of AIGC-brain decoding and analysis. Next, we present a comprehensive taxonomy according to AIGC-brain methodologies, followed by task-specific representative work and implementation details to facilitate in-depth comparison and analysis. Quality assessments are then introduced for both qualitative and quantitative evaluation. Finally, this survey explores insights gained, outlining current challenges and prospects of AIGC-brain. As a pioneering survey, this article paves the way for future advances in AIGC-brain research. © 2020 IEEE.

关键词： Taxonomies

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Synthesis of Variable Gain Robust State Observer for a Class of Uncertain Nonlinear Systems 6

Synthesis of Variable Gain Robust State Observer for a Class...

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6th International Conference on Electrical, control and Instrumentation engineering, ICECIE 2024

作者： Hirasawa, Kazuhiro Asada, Daiki Nagai, Shunya Oya, Hidetoshi Graduate School of Integrative Science and Engineering Tokyo City University Tokyo Japan Niihama College Department of Electronics and Control Engineering Ehime Japan Tokyo City University The Department of Computer Science Tokyo Japan

ISBN: (纸本)9798350380040

This paper proposes a new variable gain robust state observer for a class of uncertain nonlinear systems. The variable gain robust state observer proposed in this paper consists of fixed observer gain matrices and nonlinear modification functions which are determined by appropriate updating rules. It is shown that sufficient conditions for the existence of the proposed variable gain robust state observer can be reduced to solvability of Linear Matrix Inequalities (LMIs). Finally, we give a simple numerical example. © 2024 IEEE.

关键词： State estimation

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Drosophila Larvae-Inspired Soft Crawling Robot with Multimodal Locomotion and Versatile Applications

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Research 2025年第1期7卷 35-46页

作者： Qin Fang Jingyu Zhang Yinhui He Nenggan Zheng Yue Wang Rong Xiong Zhefeng Gong Haojian Lu State Key Laboratory of Industrial Control and Technology Zhejiang UniversityHangzhou 310027China Institute of Cyber-Systems and Control Zhejiang UniversityHangzhou 310027China Medical School of Zhejiang University Hangzhou 310027China College of Computer Science and Technology Zhejiang UniversityHangzhou 310027China Stomatology Hospital School of StomatologyZhejiang University School of MedicineZhejiang Provincial Clinical Research Center for Oral DiseasesKey Laboratory of Oral Biomedical Research of Zhejiang ProvinceCancer Center of Zhejiang UniversityEngineering Research Center of Oral Biomaterials and Devices of Zhejiang ProvinceHangzhou 310000China

Soft crawling robots have been widely studied and applied because of their excellent environmental adaptability and flexible ***,most existing soft crawling robots typically exhibit a single-motion mode and lack diverse *** by Drosophila larvae,this paper proposes a compact soft crawling robot(weight,13 g;length,165 mm;diameter,35 mm)with multimodal locomotion(forward,turning,rolling,and twisting).Each robot module uses 4 sets of high-power-density shape memory alloy actuators,endowing it with 4 degrees of motion *** analyze the mechanical characteristics of the robot modules through experiments and simulation *** plug-and-play modules can be quickly assembled to meet different motion and task *** soft crawling robot can be remotely operated with an external controller,showcasing multimodal motion on various material *** a narrow maze,the robot demonstrates agile movement and effective maneuvering around *** addition,leveraging the inherent bistable characteristics of the robot modules,we used the robot modules as anchoring units and installed a microcamera on the robot's head for pipeline *** robot completed the inspection in horizontal,vertical,curved,and branched pipelines,adjusted the camera view,and twisted a valve in the pipeline for the first *** research highlights the robot's superior locomotion and application capabilities,providing an innovative strategy for the development of lightweight,compact,and multifunctional soft crawling robots.

关键词： multimodal locomotion versatile applications Drosophila larvae soft crawling robot weight soft crawling robots shape memory alloy actuators

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Event-Triggered-Based Robust control of Heterogeneous Connected Vehicles Platoon with Communication Delay and Random Packet Loss 8

Event-Triggered-Based Robust Control of Heterogeneous Connec...

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8th CAA International Conference on Vehicular control and Intelligence, CVCI 2024

作者： Liu, Chen Ru, Shuangkun Qi, Lin Fang, Jiayi Zhang, Ting Yanshan University Hebei Key Laboratory of Industrial Computer Control Engineering Hebei Province Qinhuangdao066004 China School of Mechanical Engineering Beijing Institute of Technology Beijing100081 China School of Vehicle and Mobility Tsinghua University Beijing100081 China

ISBN: (纸本)9798331504892

With the development of vehicle autonomous driving technology and wireless network communication technology, the mix platoon of connected autonomous vehicles (CAVs) and connected human-driven vehicles (CHVs) is becoming inevitable. The abnormal V2V communication and uncertain vehicle dynamics may affect the CAV control performance. Considering time-varying communication delays and random packet loss, an event-trigger-based robust control strategy is proposed based on the stability theory of stochastic time-delay systems. The Bernoulli packet loss model is constructed to solve the random packet loss problem. The robust controller with the event-triggered mechanism designed using the Lyapunov functional stability theory of stochastic systems ensures the stability of the mix platoon with vehicle heterogeneity and the stability of CAV. The simulation comparison has verified that the proposed control strategy can better suppress the fluctuation of the preceding vehicle and more quickly reach the desired value when both time delay and packet loss are present. © 2024 IEEE.

关键词： Stochastic systems

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African Bison Optimization Algorithm:A New Bio-Inspired Optimizer with engineering Applications

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computers, Materials & Continua 2024年第10期81卷 603-623页

作者： Jian Zhao Kang Wang Jiacun Wang Xiwang Guo Liang Qi School of Science University of Science and Technology LiaoningAnshan114051China Team of Artificial Intelligence Theory and Application University of Science and Technology LiaoningAnshan114051China Department of Computer Science and Software Engineering Monmouth UniversityWest Long BranchNJ 07764USA Information and Control Engineering College Liaoning Petrochemical UniversityFushun113000China Department of Computer Science and Technology Shandong University of Science and TechnologyQingdao266590China

This paper introduces the African Bison Optimization(ABO)algorithm,which is based on biological *** is inspired by the survival behaviors of the African bison,including foraging,bathing,jousting,mating,and *** foraging behavior prompts the bison to seek a richer food source for *** bison find a food source,they stick around for a while by bathing *** jousting behavior makes bison stand out in the population,then the winner gets the chance to produce offspring in the mating *** eliminating behavior causes the old or injured bison to be weeded out from the herd,thus maintaining the excellent *** above behaviors are translated into ABO by mathematical *** assess the reliability and performance of ABO,it is evaluated on a diverse set of 23 benchmark functions and applied to solve five practical engineering problems with *** findings from the simulation demonstrate that ABO exhibits superior and more competitive performance by effectively managing the trade-off between exploration and exploitation when compared with the other nine popular metaheuristics algorithms.

关键词： Optimization metaheuristics African bison optimization engineering problems

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Futures Price Forecasting Based on LSTM Model Using Public Opinion Sentiment Analysis 42

Futures Price Forecasting Based on LSTM Model Using Public O...

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42nd Chinese control Conference, CCC 2023

作者： Shi, Panfeng Song, Shifan Lang, Qi Liu, Xiaodong School of Control Science and Engineering Dalian University of Technology Dalian116024 China School of Computer Science and Information Technology Northeast Normal University Changchun130117 China

ISBN: (纸本)9789887581543

As the economy continues to develop and the futures market grows, more and more attention is being paid to the subject of futures price forecasting. The factors influencing the futures market are complex, and the existing forecasting models tend to ignore the acquisition of information other than market information. Therefore, this paper proposes a futures price forecasting model based on sentiment analysis of online public opinions. Several futures products are selected for training and validation of the model, and the Chinese posts in the futures bar are used as input for public opinion, which is processed by the investor sentiment analysis fusion module to obtain sentiment values as a priori information for the task. Three groups of control experiments are set up to verify the validity of the proposed model and to compare the effect of sentiment feature fusion. Finally, the experimental results show that the proposed model incorporating public opinion gets better results in the selected futures product price prediction task. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Time series analysis

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State Estimator Design: Addressing General Delay Structures with Dissipative Constraints

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IEEE Transactions on Automatic control 2024年

作者： Feng, Qian Xiao, Feng Wang, Xiaoyu North China Electric Power University School of Control and Computer Engineering Beijing China

Dissipative estimator (observer) design for continuous time-delay systems poses a significant challenge when multiple pointwise and general distributed delays (DDs) are present. We propose an effective solution to this semi-open problem using the Krasovski functional (KF) framework in conjunction with a quadratic supply rate function, where both the plant and the estimator can accommodate a finite but unlimited number of pointwise and general distributed delays with square-integrable kernels. A key contribution is the introduction of a control concept called Kronecker-Seuret Decomposition (KSD) for matrix-valued functions, which allows for the factorizations or approximations of any DD integral kernel without introducing conservatism. Moreover, using KSD facilitates the construction of complete-type KFs with integral kernels that can contain any number of weakly differentiable and linearly independent functions. Our proposed solution is formulated as sequential convex SDP problems and is set out in two theorems along with an offline iterative algorithm, which eliminates the need for nonlinear numerical solvers. We show the effectiveness of our method using two challenging numerical experiments, including a system stabilized by a non-smooth controller. © 2024 IEEE.

关键词： Continuous time systems

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Deep Reinforcement Learning-based Computing Offloading and Resource Allocation Algorithm in Internet of Vehicles 11

Deep Reinforcement Learning-based Computing Offloading and R...

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2023 IEEE 11th International Conference on Information, Communication and Networks, ICICN 2023

作者： Yuan, Yiping Chen, Xin Jiao, Libo Wang, Yijie Beijing Information Science & Technology University School of Control Science and Engineering Beijing China Beijing Information Science & Technology University School of Computer Science Beijing China

ISBN: (纸本)9798350314014

With the rapid emergence of the Internet of Vehicles (IoV) and 6G networks, the exponential growth in data traffic has presented a formidable challenge to the limited computational capabilities of in-vehicle devices. To overcome this challenge, mobile edge computing (MEC) offers a viable solution by offloading computationally intensive tasks to the edge servers. In this study, we design a novel joint optimization approach that leverages deep reinforcement learning (DRL) to inform decisions on computational offloading, energy consumption, and resource allocation. Our proposed scheme considers the involvement of both the base station (BS) and road side units (RSUs) in providing computing resources to the user while simultaneously minimizing energy consumption and reducing latency of computational tasks. Our simulations unequivocally establish the efficacy of the Deep Reinforcement Learning-based computing offloading and resource allocation (DCORA) algorithm. The proposed DCORA algorithm outperforms alternative baseline schemes by approximately 15% in direct comparison. © 2023 IEEE.

关键词： Reinforcement learning

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Enhanced YOLOv8-Based Small Object Detection in Unmanned Aerial Vehicle (UAV) Perspective 14th

Enhanced YOLOv8-Based Small Object Detection in Unmanned Ae...

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14th International Conference on computer engineering and Networks, CENet 2024

作者： Li, Jiawen Yang, Chuxi Xu, Yi School of Computer Science and Technology Dalian University of Technology Dalian 116081 China School of Control Science and Engineering Dalian University of Technology Dalian 116081 China

ISBN: (纸本)9789819640157

Currently, unmanned aerial vehicles (UAVs) have been extensively utilized in ground target capture tasks, accompanied by the challenge of detecting and identifying small objects in UAV-captured images. Moreover, UAV-captured images exhibit varying scales of objects, posing additional difficulties for object detection tasks. To address these challenges, we propose an enhanced algorithm based on YOLOv8. In our algorithm, we incorporate Omni-dimensional Dynamic Convolution (ODConv) into the C2f module and apply this newly designed module to the backbone of YOLOv8. This integration enables us to leverage the advantages of ODConv, which features dynamic filters across multiple dimensions. This modified backbone reduces the model’s inference time while simultaneously enhancing prediction accuracy. Additionally, we introduce a novel Small Object Detection Structure (SODS) specifically designed for small object tasks. SODS focuses on small object regions at larger feature scales, resulting in the improvement of detection accuracy of small objects. Our proposed algorithm has been evaluated on the common unmanned aerial vehicles view datasets, and the experimental results reveal a significant improvement in both mAP and Recall values. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Omni-dimensional Dynamic Convolution Small Object Detection UAV Object Detection

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Recent advances in heterogeneous catalysis of solar-driven carbon dioxide conversion

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Journal of Environmental Sciences 2024年第6期140卷 165-182页

作者： Jun Xu Farzaneh Arabpour Roghabadi Ying Luo Vahid Ahmadi Qian Wang Zheng Wang Hong He State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China College of Chemistry and Chemical Engineering Henan Polytechnic UniversityJiaozuoHenan 454000China Department of Process Engineering Faculty of Chemical EngineeringTarbiat Modares UniversityTehranIran Optoelectronics and Nanophotonics Research Group Faculty of Electrical and Computer EngineeringTarbiat Modares UniversityTehranIran Graduate School of Engineering Nagoya UniversityFuro-choChikusa-kuNagoya 464-8603Japan

Solar-driven carbon dioxide(CO_(2))conversion including photocatalytic(PC),photoelectrochemical(PEC),photovoltaic plus electrochemical(PV/EC)systems,offers a renewable and scalable way to produce fuels and high-value chemicals for environment and energy *** review summarizes the basic fundament and the recent advances in the field of solar-driven CO_(2)*** the visible-light absorption is an important strategy to improve solar energy conversion *** separation and migration of photogenerated charges carriers to surface sites and the surface catalytic processes also determine the photocatalytic *** engineering including co-catalyst loading,defect engineering,morphology control,surface modification,surface phase junction,and Z-scheme photocatalytic system construction,have become fundamental strategies to obtain high-efficiency *** to photocatalysis,these strategies have been applied to improve the conversion efficiency and Faradaic efficiency of typical PEC *** PV/EC systems,the electrode surface structure and morphology,electrolyte effects,and mass transport conditions affect the activity and selectivity of electrochemical CO_(2)***,the challenges and prospects are addressed for the development of solar-driven CO_(2)conversion system with high energy conversion efficiency,high product selectivity and stability.

关键词： Solar-driven CO_(2)reduction Photocatalytic system Photoelectrochemical system Photovoltaic plus electrochemical system Surface/interface engineering

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