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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Zhao, Xuena Liu, Zhijie Li, Guang He, Wei Key Laboratory of Perception and Control of Intelligent Bionic Unmanned Systems Ministry of Education China School of Intelligence Science and Technology China Beijing100083 China School of Engineering and Materials Science Queen Mary University of London London United Kingdom

ISBN: (纸本)9798350337020

Bionic flapping-wing aircraft is a strongly coupled and underactuated system, and its dynamic modeling and intelligent control are still a major challenge. In this paper, we develop an 3-dimensional dynamic model for the flapping-wing aircraft designed by our team. The aerodynamic performance of the wing is analysed by the blade element method and a theoretical calculation model is obtained. Based on wind tunnel experiment, an aerodynamic model is identified for the V-Tail, the attitude control ruddervators. Further, we build a virtual simulation environment based on gym, which is verified by the outdoor flight data. This work provides the basis for intelligent control of flapping wing aircraft. © 2023 IEEE.

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Federated intelligence for Intelligent Vehicles

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年第5期9卷 1-5页

作者： Zhang, Weishan Zhang, Baoyu Jia, Xiaofeng Qi, Hongwei Qin, Rui Li, Juanjuan Tian, Yonglin Liang, Xiaolong Wang, Fei-Yue School of China University of Petroleum Qingdao China Department of Data Management Big Data Centre Beijing Beijing China Technology Company Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China Faculty of Innovation Engineering Macau University of Science and Technology Macao China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

This letter is a brief summary of a series of IEEE TIV's decentralized and hybrid workshops (DHWs) on Federated intelligence for Intelligent Vehicles. The discussed results are: 1) Different scales of large models (LMs) can be federated and deployed on IVs, and three types of federated collaboration between large and small models can be adopted for IVs. 2) Federated fine-tuning of LMs is beneficial for IVs data security. 3) The sustainability of IVs can be improved through optimizing existing models and continuous learning using federated intelligence. 4) LM-enhanced knowledge can make IVs smarter. IEEE

关键词： Intelligent vehicle highway systems

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Spatial adaptivity with boundary refinement for smoothed particle hydrodynamics fluid simulation

Spatial adaptivity with boundary refinement for smoothed par...

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作者： Xu, Yanrui Song, Chongming Wang, Xiaokun Ban, Xiaojuan Wang, Jiamin Zhang, Yalan Chang, Jian School of Intelligence Science and Technology University of Science and Technology Beijing Beijing China Beijing Key Laboratory of Knowledge Engineering for Materials Science University of Science and Technology Beijing Beijing China National Centre for Computer Animation Bournemouth University Poole United Kingdom Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing Beijing China Key Laboratory of Perception and Control of Intelligent Bionic Unmanned Systems Ministry of Education University of Science and Technology Beijing Beijing China

Fluid simulation is well-known for being visually stunning while computationally expensive. Spatial adaptivity can effectively ease the computational cost by discretizing the simulation space with varying resolutions. Adaptive methods nowadays mainly focus on the mechanism of refining the fluid surfaces to obtain more vivid splashes and wave effects. But such techniques hinder further performance gain under the condition where most of the vast fluid surface is tranquil. Moreover, energetic flow beneath the surface cannot be adequately captured with the interior of the fluid still being simulated under coarse discretization. This article proposes a novel boundary-distance based adaptive method for smoothed particle hydrodynamics fluid simulation. The signed-distance field constructed with respect to the coupling boundary is introduced to determine particle resolution in different spatial positions. The resolution is maximal within a specific distance to the boundary and decreases smoothly as the distance increases until a threshold is reached. The sizes of the particles are then adjusted towards the resolution via splitting and merging. Additionally, a wake flow preservation mechanism is introduced to keep the particle resolution at a high level for a period of time after a particle flows through the boundary object to prevent the loss of flow details. Experiments show that our method can refine fluid–solid coupling details more efficiently and effectively capture dynamic effects beneath the surface. © 2023 The Authors. Computer Animation and Virtual Worlds published by John Wiley & Sons Ltd.

关键词： Hydrodynamics

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A generative deep learning framework for airfoil flow field prediction with sparse data

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Chinese Journal of Aeronautics 2022年第1期35卷 470-484页

作者： Haizhou WU Xuejun LIU Wei AN Hongqiang LYU MIIT Key Laboratory of Pattern Analysis and Machine Intelligence College of Computer Science and TechnologyNanjing University of Aeronautics and AstronauticsNanjing 211106China Key Laboratory of Aerodynamic Noise Control Mianyang 621000China State Key Laboratory of Aerodynamics Mianyang 621000China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing 210023China College of Aerospace Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China

Deep learning has been probed for the airfoil performance prediction in recent *** with the expensive CFD simulations and wind tunnel experiments,deep learning models can be leveraged to somewhat mitigate such expenses with proper ***,effective training of the data-driven models in deep learning severely hinges on the data in diversity and *** this paper,we present a novel data augmented Generative Adversarial Network(GAN),daGAN,for rapid and accurate flow filed prediction,allowing the adaption to the task with sparse *** presented approach consists of two modules,pre-training module and fine-tuning *** pre-training module utilizes a conditional GAN(cGAN)to preliminarily estimate the distribution of the training *** the fine-tuning module,we propose a novel adversarial architecture with two generators one of which fulfils a promising data augmentation operation,so that the complement data is adequately incorporated to boost the generalization of the *** use numerical simulation data to verify the generalization of daGAN on airfoils and flow conditions with sparse training *** results show that daGAN is a promising tool for rapid and accurate evaluation of detailed flow field without the requirement for big training data.

关键词： CFD Flow field Generative adversarial networks(GANs) Sparse data Supercritical airfoil

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All-optical logic gates based on hierarchical photonic crystal modulated photoluminescence of perovskite nanocrystals

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science China(Technological sciences) 2023年第9期66卷 2735-2742页

作者： WANG Yun ZHA YanFang YANG YunYi LIU CiHui DI YunSong CAO GuiYuan WEI ShiBiao CHEN ZhiHui GAN ZhiXing Center for Future Optoelectronic Functional Materials School of Computer and Electronic InformationSchool of Artificial IntelligenceNanjing Normal UniversityNanjing 210023China Centre for Translational Atomaterials School of ScienceSwinburne University of TechnologyHawthorn VIC 3122Australia Nanophotonics Research Center Shenzhen Key Laboratory of Micro-Scale Optical Information TechnologyShenzhen UniversityShenzhen 518060China Key Laboratory of Advanced Transducers and Intelligent Control Systems Ministry of Education and Shanxi ProvinceCollege of Electronic Information and Optical EngineeringTaiyuan University of TechnologyTaiyuan 030024China

Halide perovskites exhibit high performance in all sorts of optoelectronic and photonic areas, suggesting their huge potential in integrated photonic devices. However, until now, all optical logic gates based on perovskites are still rarely explored, hindering the development of all-optical networks and computing. Herein, a new concept of all-optical logic gates is proposed based on the modulation of photoluminescence(PL) from perovskite nanocrystals(PNCs). A hierarchical photonic crystal(Hie PhC) is developed by self-assembling polystyrene(PS) and SiO2nanoparticles, which exhibit a higher PL enhancement than that of a monolayer PhC. Moreover, the light-controlled PL is realized by taking advantage of the high thermal response of the PL from PNCs/Hie PhC on polyethylene(PE) substrate, assisted by a graphene layer for light-heat conversion. Consequently, optical diode and triode are achieved based on the modulated PL, which exhibit contrast ratios(CR) of 24.7 and 74.0 dB, ***-optical logic gates, including “AND”, “OR” and “NOT”, are realized based on the optical diode and triode.

关键词： perovskite nanocrystals photonic crystals all-optical logic gates modulation of photoluminescence

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Fast reconstruction and optical-sectioning three-dimensional structured illumination microscopy

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The Innovation 2025年第3期6卷 50-58,49页

作者： Ruijie Cao Yaning Li Wenyi Wang Yunzhe Fu Xiaoyu Bu Dilizhatai Saimi Jing Sun Xichuan Ge Shan Jiang Yuru Pei Baoxiang Gao Zhixing Chen Meiqi Li Peng Xi Department of Biomedical Engineering College of Future TechnologyPeking UniversityBeijing 100871China National Biomedical Imaging Center College of Future TechnologyPeking UniversityBeijing 100871China China Academy of Space Technology Beijing Institute of Space Mechanics and ElectricityBeijing 100094China Airy Technologies Co. Ltd.Beijing 100081China Key Laboratory of Analytical Science and Technology of Hebei Province College of Chemistry and Materials ScienceHebei UniversityBaoding 071002China College of Future Technology Institute of Molecular MedicineNational Biomedical Imaging CenterBeijing Key Laboratory of Cardiometabolic Molecular MedicinePeking UniversityBeijing 100871China Institute of Biomedical Engineering Beijing Institute of Collaborative InnovationBeijingChina Key Laboratory of Machine Perception(MOE) Department of Machine IntelligencePeking UniversityBeijing 100871China Peking-Tsinghua Center for Life Science Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijing 100871China School of Life Sciences Peking UniversityBeijing 100871China

Three-dimensional structured illumination microscopy(3DSIM)is a popular method for observing subcellular/cellular structures or animal/plant tissues with gentle phototoxicity and 3D ***,its time-consuming reconstruction process poses challenges for high-throughput imaging and real-time ***,traditional 3DSIM typically requires more than six z layers for successful reconstruction and is susceptible to defocused *** poses a great gap between single-layer 2DSIM and 6-layer 3DSIM,and limits the observation of thicker *** address these limitations,we developed FO-3DSIM,a novel method that integrates spatial-domain reconstruction with optical-sectioning ***-3DSIM enhances reconstruction speed by up to 855.7 times with superior performance with limited z layers and under high defocused *** retains the high-fidelity,low-photon reconstruction capabilities of our previously proposed *** fast reconstruction and optical sectioning,we achieved large field-of-view(FOV)3D super-resolution imaging of mouse kidney actin,covering a region of 0.453 mm×0.453 mm×2.75μm within 23 min of acquisition and 13 min of *** real-time performance was demonstrated in live actin imaging with *** approach reduces photodamage through limited z layer reconstruction,allowing the observation of ER tubes with just three *** anticipate that FO-3DSIM will pave the way for near real-time,large FOV 6D imaging,encompassing xyz super-resolution,multi-color,long-term,and polarization imaging with less photodamage,removed defocused backgrounds,and reduced reconstruction time.

关键词： gentle phototoxicity phototoxicity high throughput imaging fast reconstruction real time observation optical sectioning three dimensional structured illumination microscopy reconstruction process

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DevEval: A Manually-Annotated Code Generation Benchmark Aligned with Real-World Code Repositories 62

DevEval: A Manually-Annotated Code Generation Benchmark Alig...

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Findings of the 62nd Annual Meeting of the Association for Computational Linguistics, ACL 2024

作者： Li, Jia Li, Ge Zhao, Yunfei Li, Yongmin Liu, Huanyu Zhu, Hao Wang, Lecheng Liu, Kaibo Fang, Zheng Wang, Lanshen Ding, Jiazheng Zhang, Xuanming Zhu, Yuqi Dong, Yihong Jin, Zhi Li, Binhua Huang, Fei Li, Yongbin Gu, Bin Yang, Mengfei School of Computer Science Peking University China Key Laboratory of High Confidence Software Technologies Peking University Ministry of Education China Alibaba Group China Beijing Institute of Control Engineering China China Academy of Space Technology China

ISBN: (纸本)9798891760998

How to evaluate the coding abilities of Large Language Models (LLMs) remains an open question. We find that existing benchmarks are poorly aligned with real-world code repositories and are insufficient to evaluate the coding abilities of LLMs. To address the knowledge gap, we propose a new benchmark named DevEval, which has three advances. 1 DevEval aligns with real-world repositories in multiple dimensions, e.g., code and dependency distributions. 2 DevEval is annotated by 13 developers and contains comprehensive annotations (e.g., requirements, original repositories, reference code, and reference dependencies). 3 DevEval comprises 1,825 testing samples from 115 repositories, covering 10 popular domains (e.g., Internet, Database). Based on DevEval, we propose repository-level code generation and evaluate 8 popular LLMs on DevEval (e.g., gpt-4, gpt-3.5, StarCoder 2, DeepSeek Coder, CodeLLaMa). Our experiments reveal these LLMs' coding abilities in real-world code repositories. For example, the highest Pass@1 of gpt-4 only is 53.04% in our experiments. We also analyze LLMs' failed cases and summarize their shortcomings. We hope DevEval can facilitate the development of LLMs in real code repositories. DevEval, prompts, and LLMs' predictions have been released. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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Attention Mechanism and Detection Box Information Based Real-time Multi-Object Vehicle Detection

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Journal of Computing and Information technology 2022年第4期30卷 239-256页

作者： Wu, Hao Wu, Wei Sun, Xiaoyan Zhong, Jin Cao, Fengyun School of Computer Science and Technology Hefei Normal University Hefei China School of Information and Control Engineering China University of Mining and Technology Xuzhou China Universities Joint Key Laboratory of Photoelectric Detection Science and Technology in Anhui Province Hefei China Key Laboratory of Philosophy and Social Science of Anhui Province on Adolescent Mental Health and Crisis Intelligence Intervention Hefei China School of Economics and Trade Anhui Business and Technology College Hefei China

Ensuring both the accuracy of vehicle target detection and meeting real-time requirements is crucial in traffic videos. The YOLOv5s target detection frame-work, known for its accuracy and efficiency, has at-tracted attention in academic circles. However, there are still some features that can be optimized. First of all, the detection subnet of the YOLOv5s framework cannot smoothly convert complex feature maps into relatively sparse target prediction boxes. To solve this, we integrate a self-attention-based gating mechanism into the detection subnet, forming the YOLOv5s-SAG network. Secondly, the loss function of CIoU used by YOLOv5s pays insufficient attention to the overlap-ping area of the detection frame, which can be used as metric for measuring target detection effectiveness. We add the loss term of area ratio to CIoU to further improve the modeling ability. Finally, the current multi-class Non-Maximum Suppression algorithm can cause high overlap of multi-class detection frames. To improve it, we propose a multi-class CS-NMS algorithm based on category suppression. Experimental results show an approximately 8% improvement in the mAP50 index on the UA-DETRAC dataset compared with YOLOv5s. The proposed algorithm also achieves better detection results compared to mainstream target detection algorithms and meets the real-time requirements of traffic video analysis. © 2022, University of Zagreb Faculty of Electrical Engineering and Computing. All rights reserved.

关键词： Object detection

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Multi-Task Affinity Propagation Based Natural Image Matting

Multi-Task Affinity Propagation Based Natural Image Matting

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IEEE International Conference on Image Processing

作者： Renkai Zhang Nong Sang School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology China

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

Image matting, aiming to accurately extract foreground objects by estimating their opacity against the background, has made remarkable progress through deep-learning approaches. Nevertheless, the majority of these methods require a user-defined auxiliary input, such as a trimap, which limits their applications in real-world scenarios. There are many auxiliary input-free methods that have been proposed by now, and some of them adopt a multi-task learning framework that includes a shared encoder and two separate decoders. However, these methods lack interactions between the two decoders, or interactions are implemented through simple summation or concatenation. Unfortunately, the integration of different features may cause negative transfer and limit the model performance due to the invisible information transmission process. To address the issue, we introduce the Pattern-Affinitive Propagation Module (PAP) to explicitly model cross-task propagation and task-specific propagation. Furthermore, image matting not only requires high-resolution detail features, but also semantic features. However, current CNN-based methods have limited receptive fields, making it challenging to capture global semantic features. Therefore, we design a module that integrates Dilated Convolution and Spectral Transformer (DSM), which can effectively capture global features and enhance global-local feature fusion. Extensive experiments on AM-2k and P3M-10k datasets demonstrate the superiority of our method.

关键词： Fuses Computational modeling Semantics Urban areas Information processing Multitasking Feature extraction

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Anomaly-Resistant Decentralized State Estimation Under Minimum Error Entropy With Fiducial Points for Wide-Area Power Systems

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 74-87页

作者： Bogang Qu Zidong Wang Bo Shen Hongli Dong Hongjian Liu the College of Automation Engineering Shanghai University of Electric PowerShanghai 200090China IEEE the Department of Computer Science Brunel University LondonUxbridgeMiddiesex UB83PHUK the College of Information Science and Technology Donghua UniversityShanghai 200051 the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China the Artificial Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast PetroleumDaqing 163318 the Sanya Offshore Oil&Gas Research Institute Northeast Petroleum UniversitySanya 572024China the Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of EducationAnhui Polytechnic UniversityWuhu 2410000 the School of Mathematics and Physics Anhui Polytechnic UniversityWuhu 241000China

This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines. Two classes of measurements(i.e., local measurements and edge measurements) are obtained, respectively, from the individual area and the transmission lines. A decentralized state estimator, whose performance is resistant against measurement with anomalies, is designed based on the minimum error entropy with fiducial points(MEEF) criterion. Specifically, 1) An augmented model, which incorporates the local prediction and local measurement, is developed by resorting to the unscented transformation approach and the statistical linearization approach;2) Using the augmented model, an MEEF-based cost function is designed that reflects the local prediction errors of the state and the measurement;and 3) The local estimate is first obtained by minimizing the MEEF-based cost function through a fixed-point iteration and then updated by using the edge measuring information. Finally, simulation experiments with three scenarios are carried out on the IEEE 14-bus system to illustrate the validity of the proposed anomaly-resistant decentralized SE scheme.

关键词： Decentralized state estimation(SE) measurements with anomalies minimum error entropy unscented Kalman filter wide-area power systems

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