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6th Annual International Conference on Computer science and Applications, CSA 2020

作者： Luo, Zhangkai Pei, Zhongmin Li, Yinan Wang, Xinmin Zou, Bo Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing101400 China

Main lobe interferences usually cause the distortion and peak offset of main lobe and the heighten of side lobe level in adaptive beamformers. The block matrix algorithm utilized the direction vector which was determined by both the antenna arrays and the direction of interference to eliminate the main lobe interference. But this algorithms is sensitive to the error occurred in the interference arrive angle and would consume the array of degrees of freedom. In this paper a new algorithm is proposed which projects the receive signal into a space which is orthogonal to the signal subspace to achieve the goal. The space can get by three steps. Frist we obtain eigenvalues by the decomposition of the covariance matrix of the snapshots to evaluate the noise power. Then we get a new matrix by removing the noise from the covariance matrix of the snapshots. At last we get the target space by conducting the singular value decomposition to the new matrix. Performance is mainly assessed in terms of the beamforming gain and the signal to interference and noise (SINR) ratio. The computer simulation shows the effective of this method. © 2020 Institute of Physics Publishing. All rights reserved.

关键词： Covariance matrix

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Collaborative Filtering Recommendation Algorithm of Weaponry Based on Knowledge Graph

Collaborative Filtering Recommendation Algorithm of Weaponry...

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Information technology,Big Data and Artificial Intelligence (ICIBA), International Conference on IEEE International Conference on

作者： Xiao Li Desheng Liu Qing Chang Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing

ISBN: (纸本)9781665428781

Nowadays, modern warfare has changed from weapon-centric operations to network-centric system operations, which has led to the phenomenon of sea-level quantification of weaponry. It is an important research topic for combat commanders to select suitable weaponry from a large number of available resources when facing combat tasks. Recommendation technology is a solution to this problem, which can effectively solve the problem of information overload, so that combat commanders do not produce the phenomenon of “information loss”, in the shortest possible time to make the right decision. Therefore, this paper proposes a collaborative filtering recommendation algorithm for weaponry based on the knowledge graph and the idea of collaborative filtering. In this algorithm, the knowledge graph provides a clear data model with various association relationships, and the collaborative filtering algorithm can realize it without relying on professional experience, which can realize the recommendation process more actively, faster and more intelligently.

关键词： Weapons Collaborative filtering systems operation Conferences Filtering algorithms Big Data Information filters

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Implicit high-order gas-kinetic schemes for compressible flows on three-dimensional unstructured meshes II: unsteady flows

arXiv

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arXiv 2024年

作者： Yang, Yaqing Pan, Liang Xu, Kun Laboratory of Mathematics and Complex Systems School of Mathematical Sciences Beijing Normal University Beijing China Department of Mathematics Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Shenzhen Research Institute Hong Kong University of Science and Technology Shenzhen China

For the simulations of unsteady flow, the global time step becomes really small with a large variation of local cell size. In this paper, an implicit high-order gas-kinetic scheme (HGKS) is developed to remove the restrictions on the time step for unsteady simulations. In order to improve the efficiency and keep the high-order accuracy, a two-stage third-order implicit time-accurate discretization is proposed. In each stage, an artificial steady solution is obtained for the implicit system with the pseudo-time iteration. In the iteration, the classical implicit methods are adopted to solve the nonlinear system, including the lower-upper symmetric Gauss-Seidel (LUSGS) and generalized minimum residual (GMRES) methods. To achieve the spatial accuracy, the HGKSs with both non-compact and compact reconstructions are constructed. For the non-compact scheme, the weighted essentially non-oscillatory (WENO) reconstruction is used. For the compact one, the Hermite WENO (HWENO) reconstruction is adopted due to the updates of both cell-averaged flow variables and their derivatives. The expected third-order temporal accuracy is achieved with the two-stage temporal discretization. For the smooth flow, only a single artificial iteration is needed. For uniform meshes, the efficiency of the current implicit method improves significantly in comparison with the explicit one. For the flow with discontinuities, compared with the well-known Crank-Nicholson method, the spurious oscillations in the current schemes are well suppressed. The increase of the artificial iteration steps introduces extra reconstructions associating with a reduction of the computational efficiency. Overall, the current implicit method leads to an improvement in efficiency over the explicit one in the cases with a large variation of mesh size. Meanwhile, for the cases with strong discontinuities on a uniform mesh, the efficiency of the current method is comparable with that of the explicit scheme. Copyright © 2024,

关键词： Computational efficiency

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Cost-Effective Mapping of Hyperlocal Air Pollution Using Large-Scale Mobile Monitoring and Land-Use Machine Learning

ACS ES&T Air

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ACS ES&T Air 2025年第2期2卷 151-161页

作者： Tie Zheng Yifan Wen Sheng Xiang Pan Yang Xuan Zheng Yan You Shaojun Zhang Ye Wu School of Environment State Key Joint Laboratory of Environment Simulation and Pollution Control Tsinghua University Beijing 100084 China State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Beijing Normal University Beijing 100875 China State Key Laboratory of Pollution Control and Resource Reuse Tongji University Shanghai 200092 China；College of Environmental Science and Engineering Tongji University Shanghai 200092 China College of Chemistry and Environmental Engineering Shenzhen University Shenzhen 518060 China Macao Environmental Research Institute Macau University of Science and Technology Macau 999078 China；National Observation and Research Station of Coastal Ecological Environments in Macao Macao Environmental Research Institute Macau University of Science and Technology Macao 999078 China School of Environment State Key Joint Laboratory of Environment Simulation and Pollution Control Tsinghua University Beijing 100084 China；State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084 China；Beijing Laboratory of Environmental Frontier Technologies Beijing 100084 China

The advent of large-scale mobile monitoring using fast-response instruments has enabled hyperlocal mapping (≤100 m) of traffic-related air pollution (TRAP), with important implications for air quality management. However, most related studies have been confined within small areas due to the high cost and labor intensity. This study pioneers a cost-effective TRAP mapping method by incorporating large-scale mobile monitoring and land-use machine learning (LUML). Here, over 4.6 million 1 Hz high-frequency measurements (∼1300 h) were collected on a part of major roadways in the Chinese megacity of Shenzhen. Unmeasured locations were estimated by LUML models to reduce measurement costs and labor intensity. Various ML algorithms and varying spatial aggregation segment lengths were incorporated to optimize the model performance. Hyperlocal maps of NO, NO2, and PM2.5were predicted across the entire road network covering over 1700 km2. Based on our results, LU-RF (random forest) for mapping NO and NO2and LU-GBM (Gradient Boosting Machine) for mapping PM2.5, demonstrated superior performance. Deep learning models, in contrast, did not yield comparable results. Finer partitioning of road segments (≤100 m) improved NO prediction performance, but worsened that for NO2and PM2.5. By deployment of optimal ML algorithms and segment lengths, the TRAP mapping accuracy increased by 20–80% compared to conventional land-use regression models. This study provides a promising and cost-effective approach to hyperlocal air pollution mapping and management in cities worldwide.

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Flow structures, nonlinear inertial waves and energy transfer in rotating spheres

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Theoretical & Applied Mechanics Letters 2021年第6期11卷 380-390页

作者： Tianyi Li Minping Wan Shiyi Chen Guangdong Provincial Key Laboratory of Turbulence Research and Applications Department of Mechanics and Aerospace EngineeringSouthern University of Science and TechnologyShenzhen 518055China State Key Laboratory for Turbulence and Complex Systems College of EngineeringPeking UniversityBeijing 100871China Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou) Guangzhou 511458China

We investigate flow structures,nonlinear inertial waves and energy transfer in a rotating fluid sphere,using a Galerkin spectral method based on helical-wave decomposition(HWD).Numerical simulations of flows in a sphere are performed with different system rotation rates,where a large-scale forcing is *** the case without system rotation,the intense vortex structures are *** a weak rotation is introduced,small-scale structures are reduced and vortex tubes tend to align with the rotation *** the rotation rate increases,a large-scale anticyclonic vortex structure is formed near the rotation *** structure is shown to be led by certain geostrophic *** the rotation rate further increases,a cyclone and an anticyclone emerge from the top and bottom of the boundary,respectively,where two quasi-geostrophic equatorially symmetric inertial waves dominate the *** on HWD,effects of spherical confinement on rotating turbulence are systematically *** is found that the forward cascade becomes weaker as the rotation *** the rotation rate becomes larger than some critical value,dual energy cascades emerge,with an inverse cascade at large scales and a forward cascade at small ***,the flow behavior near the boundary is studied,where the average boundary layer thickness gets smaller when system rotation *** flow behavior in the boundary layer is closely related to the interior flow structures,which create significant mass flux between the boundary layer and the interior fluid through Ekman pumping.

关键词： Rotating turbulence Spherical confinement Helical-wave deomposition Inertial wave

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Applying Predictive Machine Learning Algorithms to Petroleum Refining Processes as Part of Intelligent Automation 23

Applying Predictive Machine Learning Algorithms to Petroleum...

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23rd IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2022

作者： Nekrasov, Ivan S. Tynchenko, Vadim S. Bukhtoyarov, Vladimir B. Kachaeva, Vera A. Bashmur, Kirill A. Sinitskaya, Aleksandra E. Siberian Federal Univercity Laboratory of Biofuel Composition Krasnoyarsk Russia Siberian Federal Univercity Dept. of Technological Machines and Equipment of Oil and Gas Complex Krasnoyarsk Russia Institute of Computer Science and Telecommunications Reshetnev Siberian State University of Science and Technology Information-Control Systems Department Krasnoyarsk Russia

ISBN: (纸本)9781665498043

Intelligent automation is a term that can be applied to the more complex field of workflow automation, consisting of robotic workplace automation, robotic process automation, machine learning, and artificial intelligence. Depending on the type of business, companies often use one or more types of automation to improve efficiency or effectiveness. As you move from process-driven automation to more flexible data-driven automation, additional costs arise in the form of training datasets, technical development, infrastructure, and expertise. But the potential benefits in terms of new ideas and financial development can increase significantly. The development of mechanized oil production in recent years has been accompanied by significant achievements in the field of digitalization. Machine learning, as an important element of digitalization, can successfully solve many production problems. The paper describes the application of some machine learning algorithms for solving the problem of classifying and predicting failures of hydrocracking process equipment that occur during oil refining and diesel fuel production. The application of random forest, principal component analysis and hyperparameter tuning methods is considered. The effectiveness of their application is compared. © 2022 IEEE.

关键词： Decision trees

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Effects of infinite-range interaction on the localization properties of one-dimensional disordered harmonic chains

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Physical Review B 2023年第2期108卷 024202-024202页

作者： Wanwan Shi Peiqing Tong School of Physics and Technology Nanjing Normal University Nanjing 210023 People's Republic of China Jiangsu Key Laboratory for Numerical Simulation of Large Scale Complex Systems Nanjing Normal University Nanjing 210023 People's Republic of China and Nanjing Normal University Taizhou College Taizhou 225300 People's Republic of China

We study the effects of infinite-range (IR) interaction on the localization properties of one-dimensional disordered harmonic chains. Two kinds of disordered models are considered: one is with disordered masses, but constant spring coefficient (mass model), and the other is with disordered spring coefficient, but constant mass (spring model). It is found that the IR interaction induces a gap between the ω=0 and the excited frequency band for both types of disordered models, and their gaps are both proportional to the IR interaction coefficient γ for larger γ. In addition, the width of the excited frequency band of the mass model is also proportional to γ for larger γ, while that of the spring model is independent of γ. By employing the normalized participation ratio, we find that the low-frequency modes of the mass model except for the lowest frequency change from extended to localized states, while the localized properties of the spring model modes remain unchanged. We also discuss the effects of IR interaction on the dynamic behaviors of the two kinds of disordered models.

关键词： Lattice dynamics Localization Long-range interactions Phonons 1-dimensional systems Disordered systems

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Immobilizing ultrafine bimetallic PtAg alloy onto uniform MnO_(2) microsphere as a highly active catalyst for CO oxidation

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Chinese Chemical Letters 2021年第6期32卷 2057-2060页

作者： Shengpeng Mo Peng Peng Yinchang Pei Taiming Shen Qinglin Xie Mingli Fu Yunfa Chen Daiqi Ye College of Environment Science and Engineering Guilin University of TechnologyGuilin 541004China School of Environment and Energy South China University of TechnologyGuangzhou 510006China Guangxi Key Laboratory of Theory and Technology for Environmental Pollution Control Guilin University of TechnologyGuilin 541004China State Key Laboratory of Multi-Phase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China

Herein,a facile glycol reduction route is successful employed to synthesize bimetallic Pt Ag alloys with homogeneous distribution of sizes and *** studies reveal that the ultrafine Pt Ag alloys with well-defined sizes from around 3.3 nm to 5.8 nm are immobilized onto MnO_(2)microsphere,which remarkably enhances the catalytic performances for CO ***,quasi in-situ X-ray photoelectron spectroscopy(XPS)result reveals that both Mn and Pt ions on the surface of catalysts would realize alternating reduction-oxidation by CO and O_(2)molecules,and the oxygen vacancy sites could be replenished and excited by gas-phase O_(2).

关键词： Bimetallic alloys PtAg NPs MnO_(2) Quasi in-situ XPS CO oxidation

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Differentiable Neural Architecture Search for Domain Adaptation in Fault Diagnosis

SSRN

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SSRN 2023年

作者： Liu, Yumeng Li, Xudong Hu, Yang Institute of Software Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Jingdong Industry Beijing China Science and Technology on Complex Aviation System Simulation Laboratory 9236 mailbox Beijing China

In recent years, deep transfer learning has been widely applied in fault diagnosis. In particular, domain adaptation method to solve unsupervised transfer learning problem has become a research hotspot. However, these researches mainly focus on the construction of loss function, and the design of network structure still depends on manual work. A differentiable neural architecture search method is proposed to automatically search for network structures suitable for domain adaptation in fault diagnosis to solve this problem. The proposed method search for two components in the Inception search space: structures of Inception blocks and feature mask. Inception blocks are stacked to form a complete network, and the feature mask selects the features for domain adaptation. Besides, to improve the search efficiency, we search and adapt multiple target domains at the same time, expanding the application scenarios of domain adaptation. The proposed method is evaluated on two datasets, and experiments show that this method can generate networks with excellent performance. © 2023, The Authors. All rights reserved.

关键词： Failure analysis

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Flow structures and vertical transport in tilting salt fingers with a background shear

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Physical Review Fluids 2022年第5期7卷 053501-053501页

作者： Junyi Li Yantao Yang State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Peking University Beijing 100871 China Joint Laboratory of Marine Hydrodynamics and Ocean Engineering Pilot National Laboratory for Marine Science and Technology (Qingdao) Shandong 266237 China

In this work we study the fingering double diffusive convection, namely, the buoyancy-driven convection flow within a fluid layer experiencing an unstable salinity gradient and a stable thermal gradient. In particular, we investigate the influences from a background shear with uniform strength. Linear stability analysis indicates that the unstable modes shift from a circular shape to a sheetlike shape as the shear becomes stronger. Three-dimensional direct numerical simulations are conducted for five groups of cases, each of which has the same combination of thermal and salinity gradients (measured by corresponding Rayleigh numbers) and gradually increasing shear strength. The same properties of seawater are used for all simulations, i.e., the Prandtl number Pr=7 (the ratio of kinematic viscosity to thermal diffusivity) and the Schmidt number Sc=700 (the ratio of kinematic viscosity to salinity diffusivity). Numerical results reveal that a very weak shear organizes the salt fingers into a very regular pattern, which enhances the salinity flux. This enhancement effect, however, reduces as the Rayleigh number increases. For stronger shear the dominant structures shift from salt fingers to salt sheets, and the coherence length scale increases in the streamwise direction. Meanwhile, salinity and heat fluxes decrease. These findings suggest that even a weak shear can notably alter the morphology and transport properties of fingering double diffusive convection.

关键词： Convection Oceanography

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