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4th IEEE International Conference on Electronic Information and Communication technology, ICEICT 2021

作者： Zhang, Yongli Chen, Wan Lv, Bo Gao, Lei Zhang, Mingyue China Academy of Civil Aviation Science and Technology Beijing China Space Environment Simulation and Research Infrastructure Harbin Institute of Technology Harbin China Key Laboratory of In-Fiber Integrated Optics of Ministry of Education College of Physics and Optoelectronic Engineering Harbin Engineering University Harbin China Harbin Medical University Harbin China Heilongjiang Xinshan Technology Co. Ltd Harbin China Key Laboratory of In-Fiber Integrated Optics of Ministry of Education College of Physics and Optoelectronic Engineering Harbin Engineering University Harbin China

ISBN: (纸本)9781665432030

Superdirective antenna can realize high channel capacity of multiple-input multiple-output system (MIMO). The optimization of superdirective scattering by a novel weighting optimizing goal and Dirac-Delta function model is proposed. Both main-lobe and side-lobe characteristics of the lobe are optimized. Compared with the traditional optimization method, which only takes the main-lobe characteristic into consideration, the directivity has improved by 50% (from 6.0 to 9.0). Meanwhile, the radius of the scattering object is only 0.1λ0, which indicates this antenna is a super-directive antenna. ©2021 IEEE

关键词： Dielectric devices

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Proton and Helium Heating by Cascading Turbulence in a Low-beta Plasma

arXiv

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arXiv 2022年

作者： Shi, Zhaodong Muñoz, P.A. Büchner, J. Liu, Siming Key Laboratory of Dark Matter and Space Astronomy Purple Mountain Observatory Chinese Academy of Sciences Jiangsu Nanjing210008 China School of Astronomy and Space Science University of Science and Technology of China Anhui Hefei230026 China Max-Planck-Institute for Solar System Research Göttingen37077 Germany Center for Astronomy and Astrophysics Berlin Institute of Technology Berlin10623 Germany School of Physical Science and Technology Southwest Jiaotong University Sichuan Chengdu611756 China

How ions are energized and heated is a fundamental problem in the study of energy dissipation in magnetized plasmas. In particular, the heating of heavy ions (including 4He2+3He2+ and others) has been a constant concern for understanding the microphysics of impulsive solar flares. In this article, via two-dimensional hybrid-kinetic Particle-in-Cell simulations, we study the heating of Helium ions (4He2+) by turbulence driven by cascading waves launched at large scales from the left-handed polarized Helium ion cyclotron wave branch of a multi-ion plasma composed of electrons, protons, and Helium ions. We find significant parallel (to the background magnetic field) heating for both Helium ions and protons due to the formation of beams and plateaus in their velocity distribution functions along the background magnetic field. The heating of Helium ions in the direction perpendicular to the magnetic field starts with a lower rate than that in the parallel direction, but overtakes the parallel heating after a few hundreds of the proton gyro-periods due to cyclotron resonances with mainly obliquely propagating waves induced by the cascade of injected Helium ion cyclotron waves at large scales. There is however little evidence for proton heating in the perpendicular direction due to the absence of left-handed polarized cyclotron waves near the proton cyclotron frequency. Our results are useful for understanding the preferential heating of 3He and other heavy ions in the 3He-rich solar energetic particle events, in which Helium ions play a crucial role as a species of background ions regulating the kinetic plasma behavior. Copyright © 2022, The Authors. All rights reserved.

关键词： Heavy ions

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Multiple Algorithms Against Multiple Hardware Architectures: Data-Driven Exploration on Deep Convolution Neural Network 16th

Multiple Algorithms Against Multiple Hardware Architectures:...

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16th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2019

作者： Xu, Chongyang Luan, Zhongzhi Gao, Lan Wang, Rui Zhang, Han Zhang, Lianyi Liu, Yi Qian, Depei Beihang University Beijing China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing China

ISBN: (纸本)9783030307080

With the rapid development of deep learning (DL), various convolution neural network (CNN) models have been developed. Moreover, to execute different DL workloads efficiently, many accelerators have been proposed. To guide the design of both CNN models and hardware architectures for a high-performance inference system, we choose five types of CNN models and test them on six processors and measure three metrics. With our experiments, we get two observations and conduct two insights for the design of CNN algorithms and hardware architectures. © 2019, IFIP International Federation for Information Processing.

关键词： Neural network models

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Cosmic Ray Variation Lags behind Sunspot Number due to the Late Opening of Solar Magnetic Field

arXiv

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arXiv 2022年

作者： Wang, Yuming Guo, Jingnan Li, Gang Roussos, Elias Zhao, Junwei CAS Key Laboratory of Geospace Environment School of Earth and Space Sciences University of Science and Technology of China Hefei230026 China CAS Center for Excellence in Comparative Planetology University of Science and Technology of China Hefei230026 China Mengcheng National Geophysical Observatory University of Science and Technology of China Mengcheng 233500 China Department of Space Science CSPAR The University of Alabama in Huntsville Alabama United States Max Planck Institute for Solar System Research Goettingen Germany W. W. Hansen Experimental Physics Laboratory Stanford University Stanford United States

Galactic cosmic rays (GCRs), the highly energetic particles that may raise critical health issues of astronauts in space, are modulated by solar activity with their intensity lagging behind the sunspot number (SSN) variation by about one year. Previously, this lag has been attributed to result of outward convecting solar wind and inward propagating GCRs. However, the lag’s amplitude and its solar-cycle dependence are still not fully understood (e.g., Ross & Chaplin 2019). By investigating the solar surface magnetic field, we find that the source of heliospheric magnetic field, i.e., the open magnetic flux on the Sun, already lags behind SSN before it convects into heliosphere along with the solar wind, and the delay during odd cycles is longer than that during sequential even cycles. Thus, we propose that the GCR lag is primarily due to the greatly late opening of the solar magnetic field with respect to SSN, though solar wind convection and particle transport in the heliosphere also matters. We further investigate the origin of the open flux from different latitudes of the Sun and found that the total open flux is significantly contributed by that from low latitudes where coronal mass ejections frequently occur and also show an odd-even cyclic pattern. Our findings challenge existing theories, and may serve as the physical basis of long-term forecasts radiation dose estimates for manned deep-space exploration missions. © 2022, CC BY.

关键词： Solar energy

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Range migration-based Doppler ambiguous integer estimation for moving targets with azimuth spectrum aliasing 6

Range migration-based Doppler ambiguous integer estimation f...

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6th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2019

作者： Zhang, Ying Xiong, Wei Dong, Xichao Hu, Cheng Liu, Chengxiang Sun, Yang Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China School of Information and Electronics Beijing Institute of Technology Beijing China

ISBN: (纸本)9781728129129

In some case, the azimuth spectrum bandwidth is larger than the pulse repetition frequency (PRF), leading to a whole azimuth spectrum has been folded into multiple subsegments and aliased. Therefore, the traditional Doppler ambiguous integer estimation method cannot be used directly. In this paper, the influence of Doppler ambiguous integer on residual range migrations' slope is analyzed. Based on the slope, the Doppler ambiguous integer estimation method for moving targets with azimuth spectrum aliasing is given. From the simulation results, the Doppler ambiguous integer can be estimated accurately by proposed method. © 2019 IEEE.

关键词： Synthetic aperture radar

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High-Resolution Particle Density Measurement for Argon Plasma Plume by Image Reconstruction and Collisional-Radiative Model

SSRN

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SSRN 2022年

作者： Han, Xing Wang, Yimeng Chen, Zhiyuan Wang, Yibai Wu, Jianjun Tang, Haibin Cao, Jinbin School of Space and Environment Beihang University Beijing100083 China School of Astronautics Beihang University Beijing100083 China Key Laboratory of Spacecraft Design Optimization and Dynamic Simulation Technologies of the Ministry of Education Beihang University Beijing100083 China Aircraft and Propulsion Laboratory Ningbo Institute of Technology Beihang University Ningbo315100 China College of Aerospace Science and Engineering National University of Defense Technology Changsha410073 China Laboratory of Space Environment monitoring and Information Processing Ministry of Industry and Information Technology Beijing100083 China

A measurement method of the high-resolution atom and ion density distributions based on the image reconstruction and collisional-radiative model is presented and could apply to the parameter measurement of the axisymmetric argon plasma plume. The projection integral signals of two-band ion spectral lines and one-band atom spectral line are acquired, and the spatial distribution of the light intensity signals are obtained by the image reconstruction technique. The collisional-radiative model includes the major atomic levels and singly ionized argon levels, taking into account electron-impact excitation and ionization, electron-impact deexcitation, three-body recombination processes to obtain the theoretical signal intensity in the wavelength bands as a function of electron temperature, electron density, and atom density. The plasma parameters are determined by the theoretical signal intensity and spatial light intensity with the three filters, and the common coefficient is calibrated by the known parameters of some positions. The method was applied to the plume region of an applied-field magnetoplasmadynamic thruster to verify the feasibility of this method in comparison with the electrostatic probe, and the plasma parameters with a spatial resolution of 0.81 mm/pixel were obtained finally. © 2022, The Authors. All rights reserved.

关键词： Argon

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Wind Power Forecasting Considering Data Privacy Protection: A Federated Deep Reinforcement Learning Approach

arXiv

引用

arXiv 2022年

作者： Li, Yang Wang, Ruinong Li, Yuanzheng Zhang, Meng Long, Chao The Key Laboratory of Modern Power System Simulation Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China The State Grid Jilin Electric Power Co. Ltd Jilin Power Supply Company Chuanying District Jilin132001 China The School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The School of National Key Laboratory of Science and Technology Vessel Integrated Power System Naval University of Engineering Wuhan430033 China The School of Water Energy and Environment Cranfield University United Kingdom

In a modern power system with an increasing proportion of renewable energy, wind power prediction is crucial to the arrangement of power grid dispatching plans due to the volatility of wind power. However, traditional centralized forecasting methods raise concerns regarding data privacy-preserving and data islands problem. To handle the data privacy and openness, we propose a forecasting scheme that combines federated learning and deep reinforcement learning (DRL) for ultra-short-term wind power forecasting, called federated deep reinforcement learning (FedDRL). Firstly, this paper uses the deep deterministic policy gradient (DDPG) algorithm as the basic forecasting model to improve prediction accuracy. Secondly, we integrate the DDPG forecasting model into the framework of federated learning. The designed FedDRL can obtain an accurate prediction model in a decentralized way by sharing model parameters instead of sharing private data which can avoid sensitive privacy issues. The simulation results show that the proposed FedDRL outperforms the traditional prediction methods in terms of forecasting accuracy. More importantly, while ensuring the forecasting performance, FedDRL can effectively protect the data privacy and relieve the communication pressure compared with the traditional centralized forecasting method. In addition, a simulation with different federated learning parameters is conducted to confirm the robustness of the proposed scheme. Copyright © 2022, The Authors. All rights reserved.

关键词： Electric load dispatching

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Vertical Transport of Ultrafine Particles and Turbulence Evolution Impact on New Particle Formation at the Surface & Canton Tower

SSRN

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SSRN 2023年

作者： Wu, Hao Li, Zhanqing Hai, Shangfei Gao, Yang Jiang, Jingkun Zhao, Bin Cribb, Maureen Zhang, Dongmei Pu, Dongyang Liu, Mengqi Wang, Chunling Lan, Jing Wang, Yuying Key Laboratory of China Meteorological Administration Atmospheric Sounding School of Electrical Engineering Chengdu University of Information Technology Chengdu610225 China Department of Atmospheric and Oceanic Science University of Maryland College ParkMD20742 United States College of Oceanic and Atmospheric Sciences Ocean University of China Qingdao266100 China Frontiers Science Center for Deep Ocean Multispheres and Earth System Key Laboratory of Marine Environmental Science and Ecology Ministry of Education Ocean University of China Qingdao266100 China School of Environment State Key Joint Laboratory of Environment Simulation and Pollution Control Tsinghua University Beijing100084 China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing100084 China College of Global Change and Earth System Science Beijing Normal University Beijing100875 China Guangzhou Climate and Agrometeorology Center Guangzhou511430 China Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration Nanjing University of Information Science & Technology Nanjing210044 China

New particle formation (NPF) is a key process occurring in the planetary boundary layer (PBL). Newly formed particles are an important source of aerosols and cloud condensation nuclei (CCN) that influence clouds and climate, while the distribution of these new particles at different altitudes has rarely been studied. In-situ measurements of ultrafine particles (UFP) observed at the ground and at the top of the Canton Tower (454 m) located in downtown Guangzhou in southern China were analyzed using the measurements of multiple meteorological and physicochemical quantities, as both observed during a field campaign and simulated with the WRF-chem model. We found that turbulence and NPF characters vary considerably with heights, with UFP concentration diminishing by half from the surface to the tower top. This indicates the UFP transports upward from the ground in the lower boundary layer. A consistent relationship is established between the occurrences of NPF and the evolution of turbulence. The correlation between the exchange ratio at the tower top has correlated well with nucleation growth, suggesting that turbulence can play an important role in the episodes of NPF growth, whose growth rate is closely related to the turbulence exchange ratio, effectively dictating the ultrafine particle concentration before and during the lockdown period. A new mechanism is thus hypothesized: NPF happens eailer near the surface and grows faster at the upper PBL, attributed to condensable vapors being transported by turbulent vertical mixing in the boundary layer. Model simulations using the WRF-Chem model reveal that the exchange ratio changed the NPF parameters, supporting the proposed mechanism that the evolution of the PBL variation has a significant impact on NPF, which should not be omitted in the NPF research, since this physical factor could be a dominant one in the NPF mechanism. © 2023, The Authors. All rights reserved.

关键词： Turbulence

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Linking photosynthetic light use efficiency and optical vegetation active indicators: Implications for gross primary production estimation by remote sensing 24

Linking photosynthetic light use efficiency and optical vege...

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2020 24th ISPRS Congress on Technical Commission III

作者： Wang, S. Li, Z. Zhang, Y. Yang, D. Ni, C. Institute of Spacecraft System Engineering China Academy of Space Technology Beijing China International Institute for Earth System Sciences Nanjing University Nanjing China Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology School of Geographic and Oceanographic Science China Collaborative Innovation Center of Novel Software Technology and Industrialization China

Over the last 40 years, the light use efficiency (LUE) model has become a popular approach for gross primary productivity (GPP) estimation in the carbon and remote sensing communities. Despite the fact that the LUE model provides a simple but effective way to approximate GPP at ecosystem to global scales from remote sensing data, when implemented in real GPP modelling, however, the practical form of the model can vary. By reviewing different forms of LUE model and their performances at ecosystem to global scales, we conclude that the relationships between LUE and optical vegetation active indicators (OVAIs, including vegetation indices and sun-induced chlorophyll fluorescence-based products) across time and space are key for understanding and applying the LUE model. In this work, the relationships between LUE and OVAIs are investigated at flux-Tower scale, using both remotely sensed and simulated datasets. We find that i) LUE-OVAI relationships during the season are highly site-dependent, which is complexed by seasonal changes of leaf pigment concentration, canopy structure, radiation and Vcmax;ii) LUE tends to converge during peak growing season, which enables applying pure OVAI-based LUE models without specifically parameterizing LUE and iii) Chlorophyll-sensitive OVAIs, especially machine-learning-based SIF-like signal, exhibits a potential to represent spatial variability of LUE during the peak growing *** also show the power of time-series model simulations to improve the understanding of LUE-OVAI relationships at seasonal scale. © Authors 2020. All rights reserved.

关键词： Vegetation

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An Intrusive Gibbs Sampling Method for Implementating the Non-Synchronous Measurements of Microphone Arrays: An Alternative Way for the Expectation Maximization Algorithm of Non-Synchronous Measurements

SSRN

引用

SSRN 2024年

作者： Xu, Lingji Zeng, Fanchang Antoni, Jerome Yu, Liang Li, Zhenglin Wang, Ran Jiang, Weikang Southern Marine Science and Engineering Guangdong Laboratory Zhuhai519000 China Ministry of Education Zhuhai519082 China Laboratoire Vibrations Acoustique INSA-Lyon Batiment St. Exupery 25 bis av. Jean Capelle Villeurbanne69621 Cedex France School of Civil Aviation Northwestern Polytechnical University Xi’an710072 China State Key Laboratory of Airliner Integration Technology and Flight Simulation Shanghai200126 China College of Logistics Engineering Shanghai Maritime University Shanghai201306 China State Key Laboratory of Mechanical System Vibration Shanghai Jiao Tong University Shanghai200240 China

The non-synchronous measurements of microphone arrays are a powerful method for achieving large arrays and/or high microphone density by scanning the object of interest from a sequential movement of an arbitrary prototype array. It has attracted great interest recently since it is beyond the fundamental limitation of working frequency that is determined by the aperture and microphone density of an array. A crucial problem of non-synchronous measurements is to recover the missing phase relations information between consecutive positions compared with the synchronous measurements. The problem in the traditional solution is generally attributed to the matrix completion problem of a block diagonal spectral matrix. In the paper, this problem of non-synchronous measurements has been investigated as a problem of solving a system of equations in the Bayesian formalism. The Gibbs sampling method (a probabilistic approach) is proposed in this paper to reconstruct the source field that is encoded by unobservable latent variables. The proposed method can directly sample in the posterior probability density function (PDF) of all random variables. In the numerical simulations, convergence diagnosis of the Markov chain is illustrated through three approaches (i.e. trace plot, ergodic mean plot, and autocorrelation function plot). Acoustical source reconstruction error is also discussed with respect to the frequency range, signal-to-noise ratio (SNR), measurement distances, and shift distance of non-synchronous measurements. The proposed method is shown to return similar results with the Expectation Maximization algorithm of non-synchronous measurements. The effectiveness of the proposed method is also validated by experiments in a semi-anechoic chamber. © 2024, The Authors. All rights reserved.

关键词： Probability density function

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