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2023 3rd International Conference on Measurement Control and Instrumentation, MCAI 2023

作者： Liu, Zhihui Guo, Tengda Cheng, Yongjun Wang, Bi Shen, Kai Hu, Kai Zhou, Jiankang Zhang, Chuanbing Wang, Zixi Ding, Wanyu State Key Laboratory of Tribology in Advanced Equipment Tsinghua University Beijing100084 China College of Materials Science and Engineering Dalian Jiaotong University Dalian116028 China Laboratory of Low Frequency Electromagnetic Communication Technology Wmcrt Cssc China State Key Laboratory of High-end Compressor and System Technology Hefei Anhui230031 China

In this paper, by using magnetron sputtering to prepare NiCr/NiSi thin film thermocouples, the static calibration method is used for NiCr/NiSi thermocouples with rapid temperature calibration experiments. Different temperature calibration curves are obtained. The Seebeck coefficient of NiCr/NiSi thin film thermocouples connected to NiCr/NiSi wires is significantly higher (41.39 μV/°C) than that of NiCr/NiSi wires (0 μV/°C). The Seebeck coefficient (41.39 μV/°C) of the NiCr/NiSi thin-film thermocouple connected to copper wire is significantly higher than that of the thermocouple connected to copper wire (0 μV/°C). The problem of the Seebeck coefficient of the K-type thermocouple is analyzed by experimental data, which provides the relevant parameter basis for the use of the K-type thermocouple. The method has the advantages of simple equipment, convenient operation, accurate and reliable data, and provides a basis for the sensor to measure the temperature measurement. © Published under licence by IOP Publishing Ltd.

关键词： Temperature measurement

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Distributed Hovering Formation Method based on Multi-objective Trajectory Optimization for UAVs

Distributed Hovering Formation Method based on Multi-objecti...

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第43届中国控制会议

作者： Jiajun Xu Chaofang Hu Didi Wang Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

A novel distributed formation algorithm based on multi-objective trajectory optimization is proposed for unmanned aerial vehicle(UAV) hovering formation. The formation problem is transformed into maintenance of the hovering distance and standoff distance. And the desired cruise speed and steering rate are incorporated to ensure flight stability. All expected values of objectives are fuzzified as fuzzy parameters and the relaxation variables are introduced as optimization parameters to address language preference differences among objectives. Thus a multi-objective optimization(MOO) model under parameter ambiguity and language preference is constructed. On the basis, the UAV distributed formation trajectory optimization method is developed by combining the MOO model with the receding horizon optimization. Finally, the performance of the proposed algorithm is demonstrated in the simulation.

关键词： Unmanned aerial vehicles Hovering formation Trajectory optimization Multi-objective optimization Fuzzy parameter Linguistic preference

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A Machine Learning-Based Observational Constraint Correction Method for Seasonal Precipitation Prediction

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Advances in Atmospheric sciences 2025年第1期42卷 36-52页

作者： Bofei ZHANG Haipeng YU Zeyong HU Ping YUE Zunye TANG Hongyu LUO Guantian WANG Shanling CHENG Key Laboratory of Cryospheric Science and Frozen Soil Engineering Nagqu Plateau Climate and Environment Observation and Research Station of Tibet Autonomous RegionNorthwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhou 730000China University of the Chinese Academy of Sciences Beijing 100049China Key Open Laboratory of Arid Climate Change and Disaster Reduction of CMA Key Laboratory of Arid Climate Change and Reducing Disaster of Gansu ProvinceInstitute of Arid MeteorologyChina Meteorological AdministrationLanzhou 730000China School of Computer Science and Technology Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China

Seasonal precipitation has always been a key focus of climate *** a dynamic-statistical combined method,the existing observational constraint correction establishes a regression relationship between the numerical model outputs and historical observations,which can partly predict seasonal ***,solving a nonlinear problem through linear regression is significantly *** study implements a nonlinear optimization of an existing observational constrained correction model using a Light Gradient Boosting Machine(LightGBM)machine learning algorithm based on output from the Beijing National Climate Center Climate system Model(BCC-CSM)and station observations to improve the prediction of summer precipitation in *** model was trained using a rolling approach,and LightGBM outperformed Linear Regression(LR),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost).Using parameter tuning to optimize the machine learning model and predict future summer precipitation using eight different predictors in BCC-CSM,the mean Anomaly Correlation Coefficient(ACC)score in the 2019–22 summer precipitation predictions was 0.17,and the mean Prediction Score(PS)reached *** PS score was improved by 7.87%and 6.63%compared with the BCC-CSM and the linear observational constraint approach,*** observational constraint correction prediction strategy with LightGBM significantly and stably improved the prediction of summer precipitation in China compared to the previous linear observational constraint solution,providing a reference for flood control and drought relief during the flood season(summer)in China.

关键词： observational constraint LightGBM seasonal prediction summer precipitation machine learning

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SFLR: An Efficient LiDAR-based Lane Detection Network with Small Feature Map and Large Receptive Field

SFLR: An Efficient LiDAR-based Lane Detection Network with S...

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第43届中国控制会议

作者： Yanzhang Wang Yijing Wang Zheng Li Zhiqiang Zuo Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Lane detection plays a crucial role in autonomous driving. Compared to camera-based schemes, LiDAR-based lane detection methods show more robustness to changeable environments. However, LiDAR-based ones have high computational complexity, which makes them difficult to meet real-time requirements. Motivated by that, this paper proposes a LiDAR-based lane detection network with small feature map and large receptive field(SFLR). First, an efficient down-sampling module is developed to reduce the feature map size while minimizing information loss. After that, a novel feature extraction module processes the small-sized feature map to extract features, significantly enlarging the model's receptive field. Comparative and ablative experiments demonstrate that our approach reduces by 75% floating-point operations(FLOPs) compared to state-of-theart LiDAR-based methods with comparable F1-score. Additionally, the proposed network has 1.5× and 5.5× faster inference speed on CPU and GPU, respectively.

关键词： Autonomous driving lane detection feature fusion receptive field

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What are Pros and Cons? Stance Detection and Summarization on Feature Request 17

What are Pros and Cons? Stance Detection and Summarization o...

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17th ACM/IEEE International Symposium on Empirical Software engineering and Measurement, ESEM 2023

作者： Wang, Yawen Wang, Junjie Zhang, Hongyu Wang, Kairui Wang, Qing State Key Laboratory of Intelligent Game Beijing China Institute of Software Chinese Academy of Sciences Science and Technology on Integrated Information System Laboratory Beijing China University of Chinese Academy of Sciences Beijing China Chongqing University Chongqing China

ISBN: (纸本)9781665452236

BACKGROUND: In an online issue tracking system, e.g., GitHub Issue Tracker, feature requests and the associated comment stream provide valuable crowd-generated knowledge for requirements elicitation. To decide whether a feature request should be accepted or not, stakeholders need to identify the comments for/against the feature and understand the two-sided opinions, which is time- and effort-consuming considering the abundant information embedded in lengthy comment stream per feature request. AIMS: This paper proposes VoteBot for automatically detecting stance (for/against) and summarizing the related opinions on a feature request, which can facilitate the decision making (i.e., voting) of feature requests. To our best knowledge, such an approach is previously unexplored for crowd-based requirements elicitation. METHOD: VoteBot is a relation-aware approach, which incorporates three types of relations among the comments or among the comment sentences to better understand the discussions about feature requests. Specifically, it extracts the reply-to relation among the comments, and incorporates it into a BERT-based classifier for stance detection. It also designs a graph-based ranking algorithm, and incorporates semantic relevance and argumentative relations for stance summarization. RESULTS: The automatic evaluation on 250 feature requests with 6,598 comments from five GitHub projects, and the evaluation with practitioners on five new projects, show the promising results. CONCLUSIONS: VoteBot is effective in stance detection and stance summarization, and potentially useful for understanding feature requests and associated discussions in real-world practice. © 2023 IEEE.

关键词： Decision making

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Single-molecule optoelectronic devices:physical mechanism and beyond

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Opto-Electronic Advances 2022年第5期5卷 1-21页

作者： Peihui Li Yijian Chen Boyu Wang Mengmeng Li Dong Xiang Chuancheng Jia Xuefeng Guo Center of Single-Molecule Sciences Institute of Modern OpticsTianjin Key Laboratory of Micro-scale Optical Information Science and TechnologyFrontiers Science Center for New Organic MatterCollege of Electronic Information and Optical EngineeringNankai UniversityTianjin 300350China Beijing National Laboratory for Molecular Sciences State Key Laboratory for Structural Chemistry of Unstable and Stable SpeciesCollege of Chemistry and Molecular EngineeringPeking UniversityBeijing 100871China

Single-molecule devices not only promise to provide an alternative strategy to break through the miniaturization and functionalization bottlenecks faced by traditional semiconductor devices,but also provide a reliable platform for exploration of the intrinsic properties of matters at the single-molecule *** the regulation of the electrical properties of single-molecule devices will be a key factor in enabling further advances in the development of molecular electronics,it is necessary to clarify the interactions between the charge transport occurring in the device and the external fields,particularly the optical *** review mainly introduces the optoelectronic effects that are involved in single-molecule devices,including photoisomerization switching,photoconductance,plasmon-induced excitation,photovoltaic effect,and *** also summarize the optoelectronic mechanisms of single-molecule devices,with particular emphasis on the photoisomerization,photoexcitation,and photo-assisted tunneling ***,we focus the discussion on the opportunities and challenges arising in the single-molecule optoelectronics field and propose further possible breakthroughs.

关键词： optoelectronic device single-molecule junction light-matter interaction switch electroluminescence plasmon

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Analysis of the Fluence of Multi-sources DEM in Remote Sensing Image Ortho-rectification

Analysis of the Fluence of Multi-sources DEM in Remote Sensi...

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2024 International Conference on Remote Sensing, Mapping, and Image Processing, RSMIP 2024

作者： Liu, Rui Zhu, Jingxing Jiao, Niangang Wang, Feng You, Hongjian Xiang, Yuming Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Chinese Academy of Sciences Beijing100190 China Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781510680012

Digital Elevation Models (DEMs) depict the configuration of the Earth surface, which is essential for remote sensing image ortho-rectification. Nowadays, the ALOS DEM, ASTER GDEM and SRTM DEM are the most commonly used models, produced based on different remote sensing datasets. Geolocation errors may be introduced with different producing methods and datasets. Therefore, multi-sources remote sensing images covering various terrain in China are experimented for the analysis of ortho-rectification accuracy using different DEMs. Based on the rational function model, the geolocation error of original imagery can be reduced greatly with the grounds control points, and different DEMs are used for the ortho-rectification of different imagery. The accuracy is experimented and verified using high-precision reference images. Experimental results show that ortho-rectificated images with the ALOS DEM can achieve better accuracy compared with the SRTM DEM and ASTER GDEM, which is significant for geometric processing of remote sensing images. © 2024 SPIE.

关键词： Remote sensing

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Enhanced Non-Contact Vital Sign Monitoring via Depth Camera-Assisted Millimeter-Wave Radar

Enhanced Non-Contact Vital Sign Monitoring via Depth Camera-...

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2024 International Conference on Artificial Intelligence of Things and systems, AIoTSys 2024

作者： Zhang, Hanwen Dou, Chenglong Liu, Yucheng Wu, Yuan Qian, Liping Shi, Zhiguo Lu, Rongxing University of Macau State Key Laboratory of Internet of Things for Smart City China Zhuhai UM Science and Technology Research Institute Zhuhai China College of Information Engineering Zhejiang University of Technology Hangzhou310023 China College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China University of New Brunswick Faculty of Computer Science FrederictonNBE3B 5A3 Canada

ISBN: (纸本)9798331507886

Non-contact vital sign monitoring with mmWave radar has been regarded as an effective method for identifying lung and heart diseases due to its strong penetration and non-invasive capabilities. Nevertheless, relying solely on millimeter-wave radar for vital sign monitoring is susceptible to interference from multipath reflections, which degrades the measurement accuracy. To address this issue and enhance measurement accuracy, we propose a system design that leverages the depth camera for precise target location and subsequently employs dynamic beamforming techniques to effectively monitor the specified region. The experimental results demonstrate that our proposed system achieves an average error of 2.44 beats per minute (BPM) for heart rate monitoring and 0.22 breaths per minute (BPM) for respiratory rate monitoring. Compared to systems without beamforming, our system reduces the mean error for heart rate monitoring by 4.21 BPM and for respiratory rate monitoring by 0.51 BPM. © 2024 IEEE.

关键词： Heart

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Human Action Recognition Based on Spatial Temporal Adaptive Residual Graph Convolutional Networks with Attention Mechanism

Human Action Recognition Based on Spatial Temporal Adaptive ...

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第43届中国控制会议

作者： Lu Song Yi He Huaqing Yuan Peng Du Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information EngineeringTianjin University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In human action recognition based on human skeleton data, Spatial-Temporal Graph Convolution Networks(ST-GCN)have recently achieved remarkable performances. However, the ST-GCN model based on fixed skeleton graphs only captures the local physical relationships among skeleton points. This may not be suitable for the diversity of action categories. To address this, we propose a spatial-temporal adaptive residual graph convolutional network with an attention mechanism. We enhance the flexibility of the graph structure by introducing the adaptive graph convolution, which can improve the model's generalization performance and apply it to more data samples. Besides, adding residual links into the graph convolutional network of the ST-GCN facilitates the fusion of information from both local and global features of human skeleton data, concurrently addressing the issue of network degradation. Additionally, we add the attention mechanism into ST-GCN to emphasize useful features selectively and suppress irrelevant ones. We evaluate the proposed approach on two large-scale datasets: NTU-RGB+D and Kinetics. The experimental results show that our approach surpasses some of the more prominent studies, showing higher accuracy and excellent recognition performance.

关键词： Action Recognition Graph Convolution Adaptive Graph Residual Network Attention Mechanism

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SAR Tomographic Inversion of Urban Areas via Morphology Regularization 15

SAR Tomographic Inversion of Urban Areas via Morphology Regu...

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15th European Conference on Synthetic Aperture Radar, EUSAR 2024

作者： Li, Jie Li, Zhiyuan Fan, Yizhe Zhang, Bingchen Wu, Yirong Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Chinese Academy of Sciences Beijing100190 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing101408 China

ISBN: (纸本)9783800762873

The current synthetic aperture radar (SAR) images with ultra high resolution provide the detailed structures of the urban areas, which are often utilized to retrieve 3D spatial information of the detailed structures based on tomographic synthetic aperture radar (TomoSAR). Compressive sensing (CS), as a favorable sparse reconstruction technique has been widely used in TomoSAR, however, the sparsity constraints by CS algorithms often lose detailed structures of the targets due to the pixel-wise processing. In this paper, we apply the morphology regularization as a prior term to form a novel approach based on the CS algorithm. The morphology regularization can shrink the concatenations caused by outliers in the iterative reconstruction, enhancing the detailed structural properties of reconstructed targets. And the alternating direction method of multipliers (ADMM) is applied, where the Bregman iteration is adopted for solving the sub-problem with the morphology regularization. Both simulation experiments and tests on real data show that the proposed method can suppress the outliers and preserve the detailed structures of tomographic reconstruction, leading to improved correctness and completeness. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Morphology

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