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Estimating the value of a statistical life in China: A contingent valuation study in six representative cities

Chinese Journal of Population,Resources and Environment 2023年第4期21卷 269-278页

作者： Chaoji Cao Xinke Song Wenjia Cai Yichao Li Jianhui Cong Xueying Yu Mengzhao Gao Can Wang Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing100084China Center for Healthy Cities Institute for China Sustainable UrbanizationTsinghua UniversityBeijing100084China Tsinghua Urban Institute Tsinghua UniversityBeijing100084China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing100084China Center for Statistical Science Tsinghua UniversityBeijing100084China Department of Industrial Engineering Tsinghua UniversityBeijing100084China School of Economics and Management Shanxi UniversityTaiyuan030000China School of Economics and Management Beihang UniversityBeijing100191China Beijing Advanced Innovation Center for Big Data-based Precision Medicine Beihang UniversityBeijing100191China Key Laboratory of Big Data-Based Precision Medicine(Beihang University) Ministry of Industry and Information TechnologyBeijing100191China

The value of a statistical life(VSL)is a crucial tool for monetizing health *** explore the VSL in China,this study examines people’s willingness to pay(WTP)to reduce death risk from air pollution in six representative cities in China based on face-to-face contingent valuation interviews(n=3936)from March 7,2019 to September 30,*** results reveal that the WTP varied from CNY 455 to 763 in 2019(USD 66-111),corresponding to a VSL range of CNY 3.79-6.36 million(USD 549395-921940).The VSL in China in 2019 is estimated to be CNY 4.76 million(USD 689659).The statistics indicate that monthly expenditure levels,environmental concerns,risk attitudes,and assumed market acceptance,which have seldom been dis‐cussed in previous studies,significantly impact WTP and *** findings will serve as a reference for ana‐lyzing mortality risk reduction benefits in future research and for policymaking.

关键词： Air pollution Contingent valuation method Willingness to pay Value of a statistical life China

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TomoSAR-ALISTA: Efficient TomoSAR imaging via deep unfolded network

TomoSAR-ALISTA: Efficient TomoSAR imaging via deep unfolded ...

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International Conference on Radar systems (RADAR 2022)

作者： M. Wang Z. Zhang Y. Wang S. Gao X. Qiu Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing 100190 People's Republic of China Key Laboratory of Intelligent Aerospace Big Data Application Technology Suzhou 215123 People's Republic of China Electrical and Computer Engineering Department George Mason University Fairfax VA 22030 USA

ISBN: (数字)9781839537776

Synthetic aperture radar (SAR) tomography (TomoSAR) has attracted remarkable interest for its ability in achieving threedimensional reconstruction along the elevation direction from multiple observations. In recent years, compressed sensing (CS) technique has been introduced into TomoSAR considering for its super-resolution ability with limited samples. Whereas, the CS-based methods suffer from several drawbacks, including weak noise resistance, high computational complexity and complex parameter fine-tuning. Among the different CS algorithms, iterative soft-thresholding algorithm (ISTA) is widely used as a robust reconstruction approach, however, the parameters in the ISTA are manually chosen, which usually requires a time-consuming fine-tuning process to achieve the best performance. Aiming at efficient TomoSAR imaging, a novel sparse unfolding network named analytic learned ISTA (ALISTA) is proposed towards the TomoSAR imaging problem in this paper, and the key parameters of ISTA are learned from training data via deep learning to avoid complex parameter fine-tuning and significantly relieves the training burden. In addition, experiments verify that it is feasible to use traditional CS algorithms as training labels, which provides a tangible supervised training method to achieve better 3D reconstruction performance even in the absence of labeled data in real applications.

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A MAC Protocol Identification Approach Based on Convolutional Neural Network

A MAC Protocol Identification Approach Based on Convolutiona...

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International Conference on Wireless Communications and Signal processing (WCSP)

作者： Xutong Zhang Weiguo Shen Jianliang Xu Zitong Liu Guoru Ding Colledge of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing China Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Science and Technology on Communication Information Security Control Laboratory No.36 Research Institute of CETC Jiaxing China College of Communication Engineering Army Engineering University Nanjing China

ISBN: (数字)9781728172361

ISBN: (纸本)9781728172378

The medium access control (MAC) protocol identification is of great application value in cognitive radio. In order to realize the MAC protocol identification with high accuracy and avoid manual feature extraction, we convert the sampled data into the form of spectrogram. Then, a graphical scheme which combines the convolutional neural network (CNN) and the spectrogram is proposed. The simulation includes CNN method and support vector machine (SVM) method. It is suggested that the CNN method has better identification performance.

关键词： Media Access Protocol Spectrogram Protocols Support vector machines Time division multiple access Feature extraction Cognitive radio

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Modal Analysis of Optical Waveguide using a Novel Symplectic Compact FDTD Schemes

Modal Analysis of Optical Waveguide using a Novel Symplectic...

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International Conference on Numerical Electromagnetic Modeling and Optimization for RF, Microwave, and Terahertz Applications (NEMO)

作者： Xiaojing Kuang Kong Meng Qi Qi Xin Zeng Zhixiang Huang Mingshen Chen The Anhui Province key laboratory of simulation & design for electronic information system Hefei Normal University Hefei China Digital circuit design east china institute of photo-electronic Suzhou China Key laboratory of intelligent & computing & signal processing Anhui University Hefei China School of Electronic Engineering Huainan Normal University Huainan China

ISBN: (数字)9781728169668

ISBN: (纸本)9781728169675

For modal analysis of longitudinally invariant optical devices, the compact-finite-difference time-domain is an efficient algorithm for alleviating the large amount of storage space and computing time under the 3D complex structure simulation. However, this algorithm needs to scale down the time step to mitigate the numerical dispersion errors while simulating optical waveguide working at high frequency. Here, a novel high-order symplectic compact FDTD scheme is proposed, which is attributed to the theory combination of the fast-spatial scheme and stable temporal scheme. The research results not only verify the effectiveness by numerical experiment on a planar dielectric waveguide with complex cross section, but also provide efficient theoretical guidance for the design and optimization of optical devices at the nanometer scale.

关键词： Electromagnetic waveguides Optical waveguide theory Adaptive optics Numerical models Time-domain analysis Optical waveguides Finite difference methods

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Research of Drawing Data Asset Graph Based on Force-Oriented Algorithm

Research of Drawing Data Asset Graph Based on Force-Oriented...

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International Conference on Wavelet Active Media Technology and information processing (ICWAMTIP)

作者： Huang Sihan Qin Zhi Zhang Shibin Chang Yan Yan Lili School of Cybersecurity (Xin Gu Industrial College) Chengdu University of Information Technology Chengdu China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu China SUGON Industrial Control and Security Center Chengdu China

ISBN: (数字)9798331519254

ISBN: (纸本)9798331519261

With the rapid development of the new energy vehicle industry, the data volume in the industry is growing explosively. How to effectively visualize and analyze these data has become a focus of attention in the industry. As an intuitive way of data organization and presentation, asset graphs can display complex data relationships in a graphical form, which helps to quickly understand the information behind the data. This paper proposes a method for drawing data asset graphs based on the force-oriented algorithm, specifically tailored to the data characteristics of the new energy vehicle industry. The method improves the existing force-oriented algorithms through feature-enhanced node importance assessment, customized force model construction, multi-level community division and clustering, and node layout optimization. Experimental verification has shown that this method can effectively visualize new energy vehicle data, with certain advantages in layout quality and layout efficiency.

关键词： Industries Runtime Layout Force Clustering algorithms Data visualization Organizations Media Optimization Research and development

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Adaptive Spectral Broadening Filter-Based Phased Array Focused Ultrasound Imaging for High-Echo Target Detection

SSRN

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SSRN 2024年

作者： Lou, Cuijuan Zhou, Quan Li, Ranyang Liu, Wufeng Li, Yan Yuchi, Ming Ding, Mingyue Key Laboratory of Grain Information Processing and Control Henan University of Technology Henan Key Laboratory of Grain Photoelectric Detection and Control China School of Artificial Intelligence and Big Data Henan University of Technology Zhengzhou450001 China Department of Automation School of Automation Wuhan University of Technology Wuhan430070 China Department of Biomedical Engineering School of Life Science and Technology Key Laboratory of Molecular Biophysics of the Ministry of Education Medical Ultrasound Laboratory Huazhong University of Science and Technology Wuhan430074 China

Noise suppression and resolution improvement are important issues in high-echo target ultrasound imaging detection. To address this problem, this paper proposes a phased array focused ultrasound imaging method based on an adaptive spectral broadening filter. The proposed method first standardizes the received signals after fixed-point transmission by subtracting the mean of the received aperture signals and dividing by the standard deviation of the received aperture signals. Then, spectralbroadening was achieved through covariance and temporal autocorrelation coefficient calculations. Finally, the variance factor proposed for the first time is calculated as a weight from standardized received data after fixed-point transmission focusing to obtain the final scanline data. To evaluate the performance of the proposed method in high-echo target ultrasound imaging detection, experimental phantom images and two views of the interventricular septum including the parasternal long-axisviews and the apical four-chamber views, are reconstructed. In three scenarios, some finer structures of the targets in the images by the proposed method can be more easily identified compared to delay and sum (DAS), square-neighborhood robust signal mean-to-standard-deviation factor (SN-RSMSF), and coherence factor beamforming (CF). For the experimental phantom data, the image resolution measured by -20dB mainlobe width of the proposed method can reach 14.2 percents of DAS, 18.3 percents of SN-RSMSF and 18.3 percents of CF. The proposed method also outperforms the other three methods in terms of noise suppression. The proposed method can be used to detect diseases that involve high-echo targets such as stones, heart valves, and calcifications. © 2024, The Authors. All rights reserved.

关键词： Ultrasonic imaging

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86-Gb/s optical chaos communication over 100-km fiber transmission using semiconductor lasers

86-Gb/s optical chaos communication over 100-km fiber transm...

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49th European Conference on Optical Communications (ECOC 2023)

作者： X. Mao X. Fan L. Wang S. Fu Y. Wang A. Wang Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province Taiyuan 030024 People's Republic of China School of Information Engineering Guangdong University of Technology Guangzhou 510006 People's Republic of China

An optical-chaos secure communication of 86-Gb/s 16-ary QAM signal over 100-km fiber transmission is experimentally demonstrated under the 20%-overhead SD-FEC BER threshold of 2.0×10-2 by using wideband chaos syn...

ISBN: (数字)9781839539268

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Fast single image super-resolution using sparse Gaussian process regression

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Signal processing 2017年 134卷 52-62页

作者： Haijun Wang Xinbo Gao Kaibing Zhang Jie Li State Key Laboratory of Integrated Services Networks School of Electronic Engineering Xidian University Xi'an 710071 China School of Mathematics and Statistics Henan University of Science and Technology Luoyang 471023 China College of Electrics and Information Xi'an Polytechnic University Xi'an 710048 China Video and Image Processing System Laboratory School of Electronic Engineering Xidian University Xi'an 710071 China

Gaussian process (GP) regression is a popular statistical kernel method for learning the relationship hidden in data. However, the extensive calculation of kernel matrix hinders the further applications in many computer vision tasks such as super-resolution (SR). While active-sampling using active learning can extract a small informative subset from a large training set to overcome the bottleneck of GP regression based SR, there is still room for improving the SR quality as well as efficiency. In this paper, we target a nearly real-time GP-based SR, termed as SpGPR, by integrating the active-sampling and traditional sparse GP. The proposed framework is based on the statistics that the model projection vector is approximately sparse. To be more specific, we first train a full GP model based on an informative subset obtained by active sampling from the original training dataset. And then we propose to employ the sparse GP to further approximate the full GP model by seeking a sparse projection vector, which can significantly accelerate the prediction efficiency while getting higher reconstruction quality. The proposed method is fundamentally coarse-to-fine. Extensive experimental results indicate that the proposed method is superior to other state-of-art competitors and is promising for real-time SR application.

关键词： Super-resolution Gaussian process regression Active learning Sparse

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Single Sensor information Fusion for Local Fault Prediction of Large Rotating Machinery

Single Sensor Information Fusion for Local Fault Prediction ...

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International Conference on Electrical and control Engineering (ICECE)

作者： Sun Jianghong Zuo Yunbo Xu Xiaoli School of ElectroMechanical Engineering Beijing Information Science and Technology University Beijing China School of Mechanical & Vehicular Engineering Beijing Institute of Technology Beijing China Beijing Key Laboratory Measurement and Control of Mechanical and Electrical System Beijing China

Data process of large rotating machinery is in line with basic features of information fusion. A framework of fault diagnosis and prediction based on sensor information fusion is built. An improved extracting method of features is used to deal with the information fusion of single sensor, which raises the calculation efficiency and precision. The local fault prediction process is presented, and the fault deterioration trend is judged on the basis of dynamic weighted method. Actual example of Beijing Yanshan Petrochemical Co. shows the correction of conclusion.

关键词： Machinery Feature extraction Fault diagnosis Vibrations Accuracy Turbines Monitoring

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Synchronization of interconnected embedded systems via timer interrupts

Synchronization of interconnected embedded systems via timer...

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International Conference on control, Automation, Robotics and Vision (ICARCV)

作者： Fangyuan Li Jiahu Qin Shaoshuai Mou Yu Kang Department of Automation University of Science and Technology of China Hefei China School of Aeronautics and Astronautics Purdue University West Lafayette Indiana United States State Key Laboratory of Fire Science University of Science and Technology of China Hefei China Chinese Academy of Sciences Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Beijing China

ISBN: (纸本)9781509035502

Some applications of the interconnected embedded systems such as sensor networks rely on all nodes in the network to execute certain tasks simultaneously. To meet this demand for simultaneity, a multi-timer model based fully distributed task synchronization algorithm is proposed in this paper. In this multi-timer model, each node containing an embedded system is characterized by a timer. The microcontrollers (MCUs) within the interconnected embedded systems are switched to the assigned tasks by timer interrupts. Each timer decides when to trigger interrupts by only using the information from its neighbors. Task synchronization is realized by using the proposed synchronization algorithm. Some simulation examples are presented in the end to verify the effectiveness of the proposed synchronization algorithm.

关键词： Embedded systems Synchronization Clocks Nickel Switches Algorithm design and analysis Time-frequency analysis

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