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arXiv 2024年

作者： Mohammad-Djafari, Ali Chu, Ning Wang, Li Cai, Caifang Yu, Liang Bures sur Yvette91440 France Zhejiang Shangfeng special blower company Shaoxing312352 China Central South University Changsha China Khalifa University Abu Dhabi United Arab Emirates School of Civil Aviation Northwestern Polytechnical Univ. Xian710072 China State Key Laboratory of Airliner Integration Technology and Flight Simulation Shanghai200126 China

Neural Networks (NN) has been used in many areas with great success. When a NN’s structure (Model) is given, during the training steps, the parameters of the model are determined using an appropriate criterion and an optimization algorithm (Training). Then, the trained model can be used for the prediction or inference step (Testing). As there are also many hyperparameters, related to the optimization criteria and optimization algorithms, a validation step is necessary before its final use. One of the great difficulties is the choice of the NN’s structure. Even if there are many"on the shelf" networks, selecting or proposing a new appropriate network for a given data, signal or image processing, is still an open problem. In this work, we consider this problem using model based signal and image processing and inverse problems methods. We classify the methods in five classes, based on: i) Explicit analytical solutions, ii) Transform domain decomposition, iii) Operator Decomposition, iv) Optimization algorithms unfolding, and v) Physics Informed NN methods (PINN). Few examples in each category are explained. © 2024, CC BY.

关键词： Neural network models

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Effect of Dislocation Characteristics on Diamond Radiation Detector Performance by Affecting Dark Current

SSRN

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SSRN 2024年

作者： Mu, Lianxi Yuan, Xiaolu Feng, Zhelin Liu, Linyue Liu, Jinlong Chen, Liangxian Wei, Junjun Ouyang, Xiaoping Li, Chengming Institute for Advanced Materials and Technology University of Science and Technology Beijing Beijing100083 China School of Mechanical Engineering University of Science and Technology Beijing Beijing100083 China School of Energy and Power Engineering Xi'an Jiaotong University Xi’an710049 China State Key Laboratory of Intense Pulsed Radiation Simulation and Effect Northwest Institute of Nuclear Technology Xi’an710024 China School of Materials Science and Engineering Xiangtan University Xiangtan411105 China

The application of diamond radiation detectors in high-energy physics requires effective control of impurity content in the material. Microwave plasma chemical vapor deposition (MPCVD) technology has made significant progress in the synthesis of high-purity single crystal diamonds. However, when the impurity content is controlled to the ppb level, there are still significant differences in the performance of diamond radiation detectors. In this study, we prepared high-purity single-crystal CVD diamonds using self-made MPCVD equipment. Electron paramagnetic resonance (EPR) testing showed that the content of substituted nitrogen (Ns) impurities in diamonds were 0.77 and 1.04 ppb, respectively. The dislocation densities measured by X-ray rocking curves were 3.3 × 106 cm-2 and 4.7 × 106 cm-2, respectively. After metallization, the charge collection efficiency (CCE) of diamond radiation detectors were 12.61% and 98.27%, respectively. There are significant differences in CCE between diamond detectors. By studying the influence of dislocations and stress distribution in diamonds on dark current, it is believed that after controlling the content of Ns impurities in diamond, the effect of dislocations along the [110] direction on detector performance is greater than that in the [100] direction for diamonds with similar dislocation densities. This may be due to the easy decomposition of dislocations in the [110] direction, leading to unstable diamond growth process and resulting the non-homogeneous epitaxy. © 2024, The Authors. All rights reserved.

关键词： Dark currents

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Physical model for acoustic resonance in annular cavity structure

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Chinese Journal of Aeronautics 2020年第12期33卷 3228-3237页

作者： Fengtong ZHAO Mingsui YANG Xiaodong JING Deyou WANG Yundong SHA Yujin LIU School of Energy and Power Engineering Beihang UniversityBeijing 100083China Liaoning Province Key Laboratory of Advanced Measurement and Test Technology of Aviation Propulsion Systems Shenyang Aerospace UniversityShenyang 110136China Shenyang Engine Research Institute of AECC Shenyang 110015China

A physical model for acoustic resonance in the annular cavity structure is developed to represent the typical characteristic when acoustic resonance ***,the measurement of sound pressure in the casing and rotor blades vibration is operated in a multistage high pressure *** sharp peak frequency and discrete multi-tone occur in the frequency spectrum of sound pressure in the compressor,and the vibration of the first stage of rotor blades synchronously presents the high *** frequencies associated with rotor blades vibration can be calculated with rotating sound source *** is also confirmed that acoustic resonance occurs in the multistage *** acoustic similarity principle,an annular cavity model is established to simulate the typical characteristics of acoustic resonance in the compressor based on Large Eddy simulation(LES)and Lighthill acoustic *** coupling relationship between cavity acoustic mode and disc vibration mode shape is expounded when acoustic resonance occurs in the *** acoustic resonance will be locked in the certain flow rate *** these characteristics match well with those occur in the multistage high pressure compressor.

关键词： Acoustic resonance Annular cavity structure Large eddy simulation Lighthill acoustic analogy Multistage compressor

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Development of Realistic Numerical Brain Model Based on MRIs for Microwave Brain Stroke Detection 15

Development of Realistic Numerical Brain Model Based on MRIs...

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15th IEEE International Conference on Electronic Measurement and Instruments, ICEMI 2021

作者： Han, Ping Liu, Ziyu Li, Qinwei Yu, Ming Zhao, Rongnan Civil Aviation University of China Tianjin Key Laboratory for Advanced Signal Processing Tianjin China Institute of Medical Support Technology Institute of Systems Engineering Academy of Military Sciences Tianjin China Yingkou Jucheng Development Ltd. of teaching Yingkou China

ISBN: (纸本)9781665444910

In this paper, a two-dimensional truth-oriented brain model is proposed for imaging simulation of wearable stroke detection devices. Stroke detection based on ultra-wideband microwave imaging is a new detection method, which is portable, fast and safe. Wearable detection equipment is an important development direction of ultra-wideband microwave imaging for stroke. By analyzing the electromagnetic characteristics of the brain tissue at different frequencies, the electromagnetic parameters of the brain tissue were determined, and the real human brain MRI images were used for analysis and modeling. Compared to previous simple brain model, this model can more truly reflect the internal structure of human brain, and provide a more accurate experimental platform for various imaging simulation algorithms. Finally, the delay confocal algorithm was used to reconstruct the brain image. In the imaging results, the bleeding spots with a diameter of 6 mm in the brain is clearly identified. © 2021 IEEE.

关键词： Ultra-wideband (UWB)

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

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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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Semi-supervised Open-set Recognition of Radar Active Jamming

Semi-supervised Open-set Recognition of Radar Active Jamming

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IEEE International Conference on Radar

作者： Hao Li Xueli Fang Lei Zhang Hui Kang Wei Zhang School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China Key Laboratory of complex aviation simulation system Beijing China

ISBN: (纸本)9781665468893

With the emergence of various kinds of complex radar jamming, radar jamming intelligent recognition technology has increasingly become the key to electronic counter-counter measures. To achieve radar jamming open-set recognition with a small number of tagged samples, Generative adversarial network-based pseudolabeled convolutional neural network (GAN-PL-CNN) model is proposed in this paper. Firstly, radar jamming is modelled, and the radar jamming datasets with known and unknown types are established after time-frequency transformation and image processing. Then, the adaptive pseudolabeling method is used to achieve semi-supervised recognition of radar jamming by combining the learning capability of convolutional neural networks and the characteristics of pseudolabeling to increase labeled samples intelligently. Finally, generative adversarial networks are introduced to enhance the recognition ability of the model and the discrimination ability of the unknown type through the game between the generator and the discriminator in the iterative process. Experimental results show that the GAN-PL-CNN model achieves 89.7%-95.1% for known types and 30.7%-86.8% for unknown types at 3%-6% labeling rate. As the number of labeled samples increases, the recognition effect becomes better and has a greater ability to exclude unknown type.

关键词： Adaptation models Time-frequency analysis Radar measurements Neural networks Radar Radar imaging Convolutional neural networks

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Fractional Domain Information Enhanced Hyperspherical Prototype Learning Method for Hyperspectral Image Open-Set Classification

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IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Feng, Shou Wang, Shengnan Xu, Congan Zhao, Chunhui Li, Wei Tao, Ran Harbin Engineering University College of Information and Communication Engineering Harbin 150001 China Harbin Engineering University Key Laboratory of Advanced Marine Communication and Information Technology Ministry of Industry and Information Technology Harbin 150001 China Naval Aviation University research Institute of Information Fusion Yantai 264001 China Beijing Institute of Technology School of Information and Electronics Beijing 100081 China

In recent years, research in the field of hyperspectral image classification (HSIC) has increasingly focused on the open-set problem. Open-set classification (OSC) demands not only accurately classifying the known categories but also identifying the unknown samples that are not labeled or included within the training data during the testing stage. Existing open-set methods often suffer from misclassification between the known and unknown categories due to their inadequate utilization of metric space. Moreover, relying on a single-threshold strategy performs poorly in identifying unknown categories in complex open environments. In this article, a fractional-domain information-enhanced hyperspherical prototype learning (FrHSPL) method is proposed for hyperspectral image (HSI) OSC. FrHSPL develops a hyperspherical prototype learning (HSPL) strategy that ensures the features of known categories are uniformly distributed on the hypersphere. Therefore, HSPL can effectively enhance the interclass separability and optimize the exploitation of metric space. Subsequently, to enhance the discrimination capability of spectral features, a frequency-spatial-spectral information aggregation (FSSIA) module is devised to deeply integrate fractional domain information with spatial and spectral information. Finally, an open-set recognition (OSR) module is designed to identify unknown categories by using the prototypes of each known category along with the corresponding prototype radii. Extensive experiments on four common HSI datasets indicate that the proposed FrHSPL exhibits superior performance in comparison with both closed-set and open-set methods. © 1980-2012 IEEE.

关键词： Fractional Fourier domain hyperspectral image (HSI) hyperspherical prototype learning (HSPL) open-set classification (OSC)

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Reconstructing the Nanoscale Porous Structures in Coal-Based Membranes by Ultrafast High-Temperature Sintering for Solar-Driven Water Treatment

SSRN

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SSRN 2023年

作者： Liu, Chih-Chin Chen, Rong Wei, Yanzhuo Huang, Yang Zhang, Zhijun Zhao, Yixin Fu, Tairan Hu, Chuxiong Huang, Xia Zang, Xining Department of Mechanical Engineering Tsinghua University Beijing100084 China Key Laboratory for Advanced Materials Processing Technology Ministry of Education Tsinghua University Beijing100084 China State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Tsinghua University Beijing100084 China Department of Thermal Engineering Tsinghua University Beijing100084 China School of Chemical and Environmental Engineering China University of Mining and Technology Beijing100083 China Key Laboratory for Thermal Science and Power Engineering Ministry of Education China Beijing Key Laboratory for Precise Mining of Inter grown Energy and Resources China

Lignite, a low-grade coal, accounts for over 40% of the global coal reserves. The use of lignite has been limited compared to other grades due to its low calorific value, high impurities content, and elevated volatile matter. Exploring a scalable and environment-friendly approach to upgrade lignite will offer new opportunities. In this work, Ultrafast High-Temperature Carbonization (UHC) has been developed to carbonize lignite and modify its nanoscale structure to construct a conductive porous membrane. The whole process takes only 30 s with an ultrafast heating rate exceeding 2400°C/min and a maximum temperature over 1500°C. Upon heating the pore structures in the coal membrane evolves into micro- and mesopores with a specific surface area of over 300 m2/g. The carbonized coal-based membrane provides superior performance as a solar evaporator for water treatment, due to its interconnected porous structures, hydrophilicity, and over 85% absorption of full-band visible light. Under 1 sun solar irradiation, the membrane shows over 98.2% removal rate of salts, heavy metal ions, and volatile organic compounds (VOCs). © 2023, The Authors. All rights reserved.

关键词： Metal ions

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Hamiltonian Dynamics and Targeted Energy Transfer of a Grounded Bistable Nonlinear Energy Sink

SSRN

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SSRN 2022年

作者： Li, Shuangbao Zhou, Xinxing Chen, Jianen Research Institute of Science and Technology Civil Aviation University of China Tianjin300300 China College of Science Civil Aviation University of China Tianjin300300 China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China

A two-degree-of-freedom nonlinear mechanical system describing a damped linear oscillator weakly coupled to a lightweight grounded bistable nonlinear energy sink is proposed to investigate the targeted energy transfer (TET) under asymmetric local nonlinear potentials. The Bogdanov-Takens bifurcations of equilibria are discussed to reflect the bistable and asymmetric characteristics of the system. Through projections of isoenergetic manifolds, the topological features of the Hamiltonian dynamics under $1:1$ internal resonance have been investigated, which induces conditions for energy localization and exchange. In the general case, the topological features of the Hamiltonian dynamics related to the nonlinear normal modes (NNMs) are classified by the Poincare map, the relations between the NNMs and the Hamiltonian dynamics have been interpreted through the frequency energy plots. The results show that introducing the asymmetric characteristics may enhance the TET and realize the complete TET. © 2022, The Authors. All rights reserved.

关键词： Degrees of freedom (mechanics)

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Disorder- and Topology-Enhanced Fully Spin-Polarized Currents in Nodal Chain Spin-Gapless Semimetals

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Physical Review Letters 2022年第9期129卷 097201-097201页

作者： Xiaodong Zhou Run-Wu Zhang Xiuxian Yang Xiao-Ping Li Wanxiang Feng Yuriy Mokrousov Yugui Yao Centre for Quantum Physics Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement (MOE) School of Physics Beijing Institute of Technology Beijing 100081 China Beijing Key Lab of Nanophotonics and Ultrafine Optoelectronic Systems School of Physics Beijing Institute of Technology Beijing 100081 China Peter Grünberg Institut and Institute for Advanced Simulation Forschungszentrum Jülich and JARA 52425 Jülich Germany Institute of Physics Johannes Gutenberg University Mainz 55099 Mainz Germany

Recently discovered high-quality nodal chain spin-gapless semimetals MF3 (M=Pd, Mn) feature an ultraclean nodal chain in the spin up channel residing right at the Fermi level and displaying a large spin gap leading to a 100% spin polarization of transport properties. Here, we investigate both intrinsic and extrinsic contributions to anomalous and spin transport in this class of materials. The dominant intrinsic origin is found to originate entirely from the gapped nodal chains without the entanglement of any other trivial bands. The side-jump mechanism is predicted to be negligibly small, but intrinsic skew scattering enhances the intrinsic Hall and Nernst signals significantly, leading to large values of respective conductivities. Our findings open a new material platform for exploring strong anomalous and spin transport properties in magnetic topological semimetals.

关键词： Transport phenomena Topological materials

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