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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Zhong, Yu Zhao, Jiajia Northwestern Polytechnical University School of Electronics and Information Xi'an China Control and Intelligent Agent Cooperation Laboratory Science and Technology on Complex System Bejing China

ISBN: (纸本)9781728137926

The multiple criteria decision making (MCDM) is universal and applicable for plenty of unmanned systems which are widely concerned in civil and military fields due to their adaptability and safety. The contributing factors of decision making in unmanned systems are complicated due to the inhomogeneity and nondeterminacy of environment and the relative importance of criteria. Consequently, these critical factors fail to be considered felicitously in many traditional methods. In this paper, a neutrosophic MCDM approach is proposed to mitigate this matter. The neutrosophic set generated from collected information of multiple sources would be fused by the aggregation operator to obtain the decision matrix, then the weights of criteria would be obtained via the proposed method based on the decision matrix, and the decision results could be determined by the aggregation operator and defuzzification method of aggregated neutrosophic set. The application of neutrosophic set can handle numerous uncertain matters in unmanned systems. Finally, an example was provided to illustrate the reasonableness and stability of the proposed approach. © 2019 IEEE.

关键词： Decision making

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Design of a compact ultra-wideband MIMO antenna

Design of a compact ultra-wideband MIMO antenna

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IET International Radar Conference 2018, IRC 2018

作者： Youcheng, Wang Yanjiao, Yang Qingxi, Chi Hucheng, Pei Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China

A compact ultra-wideband (UWB) multiple-input multiple-output (MIMO) antenna is presented. The MIMO antenna consists of four monopoles which are printed on FR4 substrate, whose impedance bandwidth is from 2 to 12 GHz, and the isolation of two adjacent antennas is less than−20 dB in mostly frequency band. The current distribution of the antenna is discussed by simulation, and the radiation characteristics of the antenna are improved by increasing the parasitic radiation patch and digging holes in the radiation patch. Four monopoles are placed with polarisation orthogonality, and the adjacent units are separated by slot to cut off the coupling current on the floor, thus effectively improving the isolation of the antenna. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Electric impedance

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Failure Mode and Effects Analysis of UAV Power system Based on Generalized Dempster-Shafer Structures

Failure Mode and Effects Analysis of UAV Power System Based ...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Zhang, Zhuo Hao, Mingrui Northwestern Polytechnical University School of Electronics and Information Xian China Intelligent Agent Cooperation Laboratory Science and Technology on Complex System Control Beijing China

ISBN: (纸本)9781728137926

The unmanned aerial vehicle(UAV) power system consists of components that provide flight power for the UAV, which mainly includes three parts: motor, electronic speed controller(ESC), and battery. Since the UAV always operates in the open air, which requires high stability of the power system, the failure mode and effects analysis(FMEA) is particularly significant and it has been widely used to examine potential failures in systems or components. However, the traditional FMEA method has many unreasonable points. In order to better deal with the uncertainty and improve the stability of the UAV power system, we propose a FMEA method which is based on the generalized Dempster-Shafer structures, the failure modes are comprehensively analyzed and the risks are ranked by combining the characteristic information of risk factors with the generalized evidence theory. The new method can not only deal with the uncertainty of risk assessment, but also further improve the reliability of effects analysis. In addition, the FMEA experiment of the UAV power system is carried out in this paper. The experimental results show that the method is effective for practical applications. © 2019 IEEE.

关键词： Fuzzy set theory

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PATCH: Empowering Large Language Model with Programmer-Intent Guidance and Collaborative-Behavior Simulation for Automatic Bug Fixing

arXiv

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arXiv 2025年

作者： Zhang, Yuwei Jin, Zhi Xing, Ying Li, Ge Liu, Fang Zhu, Jiaxin Dou, Wensheng Wei, Jun Affiliated with Nanjing Institute of Software Technology University of Chinese Academy of Sciences Nanjing China Key Laboratory of System Software Chinese Academy of Sciences Institute of Software Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China Key Laboratory of High Confidence Software Technologies Peking University Ministry of Education School of Computer Science Peking University Beijing China School of Computer Science Wuhan University Wuhan China School of Intelligent Engineering and Automation Beijing University of Posts and Telecommunications Beijing China State Key Laboratory of Complex & Critical Software Environment School of Computer Science and Engineering Beihang University Beijing China

Bug fixing holds significant importance in software development and maintenance. Recent research has made substantial strides in exploring the potential of large language models (LLMs) for automatically resolving software bugs. However, a noticeable gap in existing approaches lies in the oversight of collaborative facets intrinsic to bug resolution, treating the process as a single-stage endeavor. Moreover, most approaches solely take the buggy code snippet as input for LLMs during the patch generation stage. To mitigate the aforementioned limitations, we introduce a novel stage-wise framework named PATCH. Specifically, we first augment the buggy code snippet with corresponding dependence context and intent information to better guide LLMs in generating the correct candidate patches. Additionally, by taking inspiration from bug management practices, we decompose the bug-fixing task into four distinct stages: bug reporting, bug diagnosis, patch generation, and patch verification. These stages are performed interactively by LLMs, aiming to simulate the collaborative behavior of programmers during the resolution of software bugs. By harnessing these collective contributions, PATCH effectively enhances the bug-fixing capability of LLMs. We implement PATCH by employing the powerful dialogue-based LLM ChatGPT. Our evaluation on the widely used bug-fixing benchmark BFP demonstrates that PATCH has achieved better performance than state-of-the-art LLMs. Copyright © 2025, The Authors. All rights reserved.

关键词： Computer software maintenance

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Wavelet Transform-Based High-Definition Map Construction From a Panoramic Camera

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Journal of Shanghai Jiaotong university(science) 2021年第5期26卷 569-576页

作者： ZHUANG Hanyang ZHOU Xuejun WANG Chunxiang QIAN Yuhan University of Michigan-Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong UniversityShanghai 200240China Guangxi Key Laboratory of Automobile Components and Vehicle Technology Guangxi University of Science and TechnologyLiuzhou 545006GuangxiChina Noblelift Intelligent Equipment Co. Ltd.Huzhou 313100ZhejiangChina Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai 200240China School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghai 200240China

High-definition(HD)maps are key components that provide rich topologic and semantic information for decision-making in vehicle autonomous driving systems.A complete ground orthophoto is usually used as the base image to construct the HD *** ground orthophoto is obtained through inverse perspective transformation and image *** the image mosaicing,multiple consecutive orthophotos are stitched together using pose information and image *** this study,wavelet transform is introduced to the image mosaicing process to alleviate the information loss caused by image *** the orthophoto wavelet transform,high-frequency and low-frequency components are fused using different strategies to form a complete base image with clearer local *** results show that the accuracy of the orthophotos generated using this method is improved.

关键词： high-definition(HD)map wavelet transform image registration panorama

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Learning Network-Invariant and Label-Discriminative Representations for Cross-Network Node Classification

Learning Network-Invariant and Label-Discriminative Represen...

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2021 China Automation Congress, CAC 2021

作者： Yang, Linyao Xu, Yancai Hou, Jiachen Dai, Yuxin Lv, Chen The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Institute of Systems Engineering Macau University of Science and Technology China School of Electrical Engineering and Automation Wuhan University Wuhan China China Electric Power Research Institute Beijing China

ISBN: (纸本)9781665426473

Networks are ubiquitous data structures in the real world. The accurate and efficient analysis of networks is critical to realizing many intelligent network-based services. However, most existing network analysis methods are developed for single networks and require a lot of labeled data, which is costly and time-consuming to acquire. Transfer learning has been widely accepted as an effective paradigm for tackling this problem by reusing the model trained on a supervised task. However, transfer learning on the non-euclidean network data has been investigated by no more than a few studies. To realize accurate node classification based on the knowledge learned from the labeled source network, this paper proposes to learn network-invariant and label-discriminative representations based on graph embedding and linear discriminant analysis. Specifically, we embed the source and target networks into adjacent vector spaces based on the graph attention network by minimizing the Sinkhorn distributional distances between their embeddings. To obtain label-discriminative features for learning better classification models, we then utilize a transferable linear discriminative analysis method to project the embeddings into label-discriminative subspaces. In the end, a support vector machine model trained on the labeled source network is utilized to classify the target nodes. Experiments on two pairs of networks illustrate that our method achieves the best performance and evaluates the effectiveness of the proposed modules. © 2021 IEEE

关键词： Embeddings

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PUGAN: Physical Model-Guided Underwater Image Enhancement Using GAN with Dual-Discriminators

arXiv

引用

arXiv 2023年

作者： Cong, Runmin Yang, Wenyu Zhang, Wei Li, Chongyi Guo, Chun-Le Huang, Qingming Kwong, Sam Institute of Information Science Beijing Jiaotong University Beijing100044 China School of Control Science and Engineering Shandong University Jinan250061 China Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan250061 China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China College of Computer Science Nankai University Tianjin300350 China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing101408 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Peng Cheng Laboratory Shenzhen518055 China Department of Computer Science City University of Hong Kong Hong Kong City University of Hong Kong Shenzhen Research Institute Shenzhen51800 China

Due to the light absorption and scattering induced by the water medium, underwater images usually suffer from some degradation problems, such as low contrast, color distortion, and blurring details, which aggravate the difficulty of downstream underwater understanding tasks. Therefore, how to obtain clear and visually pleasant images has become a common concern of people, and the task of underwater image enhancement (UIE) has also emerged as the times require. Among existing UIE methods, Generative Adversarial Networks (GANs) based methods perform well in visual aesthetics, while the physical model-based methods have better scene adaptability. Inheriting the advantages of the above two types of models, we propose a physical model-guided GAN model for UIE in this paper, referred to as PUGAN. The entire network is under the GAN architecture. On the one hand, we design a Parameters Estimation subnetwork (Par-subnet) to learn the parameters for physical model inversion, and use the generated color enhancement image as auxiliary information for the Two-Stream Interaction Enhancement subnetwork (TSIE-subnet). Meanwhile, we design a Degradation Quantization (DQ) module in TSIE-subnet to quantize scene degradation, thereby achieving reinforcing enhancement of key regions. On the other hand, we design the Dual-Discriminators for the style-content adversarial constraint, promoting the authenticity and visual aesthetics of the results. Extensive experiments on three benchmark datasets demonstrate that our PUGAN outperforms state-of-the-art methods in both qualitative and quantitative metrics. The code and results can be found from the link of https://***/proj_***. © 2023, CC BY-NC-SA.

关键词： Discriminators

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Spin–Orbit Torque Induced Magnetization Switching of Heusler Alloy Co2fesi for Neuromorphic Computing

SSRN

引用

SSRN 2022年

作者： Zhao, Jiale Zhang, Shuai Li, Wendi Dong, Kaifeng Wang, Ke Guo, Zhe School of Optical and Electronic Information Huazhong University of Science and Technology Wuhan430074 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China School of Mechanical and Electronic Engineering East China University of Technology Nanchang330013 China

Spintronic devices have the advantages of high endurance and energy efficiency for nonvolatile memory and emerging neuromorphic computing applications, especially with the spin-orbit torque (SOT) driven magnetization switching manner. The Co-based Heusler alloy is potentially an ideal material for constructing spintronic devices due to its high spin polarization, high saturation magnetization, high Curie temperature and low damping. Here, we investigate the current induced magnetization switching of Heusler alloy Co 2 FeSi with good perpendicular magnetic anisotropy through SOT. Inspired by the gradual switching process, we further study the memristive behaviors of the device, which can be used as artificial synapse for neuromorphic computing. Both the pulse amplitudes and pulse numbers are exploited to modulate the resistance states. Based on the extracted synaptic characteristics, an artificial neural network is simulated, causing a high accuracy of 91.52%. Our work paves a way for the application of Heusler alloy in magnetic random-access memory and neuromorphic computing. © 2022, The Authors. All rights reserved.

关键词： Neural networks

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Generating infrared image from visible image using Generative Adversarial Networks

Generating infrared image from visible image using Generativ...

引用

2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： An, Lei Zhao, Jiajia Di, Huijun Beijing Institute of Technology School of Computer Science and Technology Beijing China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Coorperation Laboratory Beijing China

ISBN: (纸本)9781728137926

Infrared images have properties that are unaffected by illumination compared to visible images, object can be clearly recognized at day or night. Therefore, it is a better choice to use infrared images when training deep learning algorithms in unmanned systems. However, how to obtain a large number of infrared images makes it possible to train deep learning algorithm, which is the focus of our attention. In contrast to difficulties in direct shooting, computer simulations can generate large infrared images from visible images. But models that are trained on simulated data usually do not translate well to real scenarios. To bridge the domain gap between simulated and real infrared images, we exploit recent advances in paired image-to-image translation. We extend Pixel2Pixel to generate infrared image from visible image and propose a novel way of multilayer semantic information fusion, which significantly improves the quality of generated images. Finally, the image generated by our proposed PixelPro network is almost consistent with the real image distribution, achieved the purpose of expanding the dataset. © 2019 IEEE.

关键词： Generative adversarial networks

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Role of Black Carbon in Modulating Aerosol Direct Effects Driven by Air Pollution controls During 2013-2017 in China

SSRN

引用

SSRN 2022年

作者： Zhang, Fenfen Xing, Jia Ding, Dian Wang, Jiandong Zheng, Haotian Zhao, Bin Qi, Ling Wang, Shuxiao State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Tsinghua University Beijing100084 China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing100084 China Institute for Atmospheric and Earth System Research Faculty of Science University of Helsinki Helsinki00014 Finland School of Atmospheric Physics Nanjing University of Information Science and Technology Nanjing210044 China School of Energy and Environmental Engineering University of Science and Technology Beijing Beijing100083 China

Aerosol direct effects (ADEs) can modulate shortwave radiation as well as atmospheric dynamics and air quality. As the key absorbing component of aerosol, the black carbon (BC) largely determines the aerosol optical properties. Therefore, it is expected that BC emission controls might gain co-benefits from the simultaneous reduction of ADEs. To demonstrate such synergy, we quantified the ADEs changes and role of BC controls in China during 2013-2017 using a regional two-way coupled meteorology chemistry transport model. Results suggest that the control action effectively reduced wintertime PM2.5 concentration (-26.0 μg m-3) and associated ADEs. The influence of ADEs on surface shortwave radiation, 2-meter temperature, and planetary boundary layer height was weakened from -16.7 W m-2, -0.20°C, and -15.4 m in 2013 to -11.3 W m-2, -0.06°C, and -10.7 m in 2017, respectively. The enhancement of SO2, NO2, and PM2.5 concentrations due to ADEs was reduced from +3.1%, +5.2%, and +5.4% in 2013, to +2.6%, +4.5%, and +3.3% in 2017, respectively, demonstrating the extra benefit of air pollution controls by reducing ADEs. The BC emission reduced by 12.5% simultaneously along with the effective controls during 2013-2017. Such BC controls contributes 15.6-60.2% of such changes in the ADEs influence on meteorological variables, and 32.6-41.1% on air pollutants. More specially, the effectiveness of collaborative reduction of BC further reduced surface shortwave radiation in China by 3.6 W m-2 in January and 1.0 W m-2 in July, leading to a more weakened ADEs that bring extra benefits in reducing PM2.5 concentrations by 1.8 μg m-3 in January and 0.3 μg m-3 in July. Apparently, BC played a dominant role in modulating the ADEs and associated influences on meteorology and air quality, suggesting a wise control strategy by targeting absorbing component of PM2.5 reduction to address both air pollution and climate change in the future. © 2022, The Authors. All rights reserved.

关键词： Air quality

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