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20th Chinese Materials Conference, CMC 2019

作者： Liu, Yangsi Xi, Xiaoli Nie, Zuoren Zhao, Linyan Fan, Youshu College of Materials Science and Engineering Key Laboratory of Advanced Functional Materials Education Ministry of China Beijing University of Technology Beijing100124 China National Engineering Laboratory for Industrial Big-data Application Technology Beijing University of Technology Beijing100124 China

ISBN: (纸本)9783035715668

Tungsten trioxide (WO3) nanostructures were synthesized by a hydrothermal method, and the influence of essential hydrothermal conditions, temperature and time, on their crystal structure, morphology and visible-light driven photocatalysis was studied. The hydrothermal temperature was varied from 120 °C to 200 °C, and the hydrothermal time changed from 12 h to 32 h. The crystal structure, morphology and photocatalytic performance of WO3 nanostructures were characterized by XRD, SEM and UV-Vis. The crystal structure of WO3 nanostructure was triclinic phase and their morphology was mainly one dimensional nanorods. Methylene blue was used as the target to evaluate their photocatalytic performance under visible light (λ>420 nm). The photocatalytic results suggest the suitable hydrothermal conditions to synthesize WO3 nanostructures for the wastewater treatment application. © 2020 Trans Tech Publications Ltd, Switzerland.

关键词： Crystal structure

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Improved Polar Complex Exponential Transform for Robust Local Image Description

SSRN

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SSRN 2022年

作者： Yang, Zhanlong Yang, Linzhi Chen, Geng Yap, Pew-Thian School of Marine Science and Technology Northwestern Polytechnical University Xi’an China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi’an China University of North Carolina Chapel HillNC United States

Image description via robust local descriptors plays a vital role in a large number of image representation and matching applications. In this paper, we propose a novel distinctive local image descriptor that is based on the phase and amplitude information of Polar Complex Exponential Transform (PCET). The proposed descriptor, called IPCET (Improved PCET), is robust to the common photometric transformations (e.g., illumination, noise, JPEG compression, and blur) and geometric transformations (e.g., scaling, rotation, translation, and significant affine distortion). We perform extensive experiments to compare our IPCET descriptor with five most cutting-edge region descriptors (i.e., SIFT, Zernike Moment, GLOH, PCA-SIFT, and SURF). Experimental results demonstrate that our IPCET descriptor outperforms cutting-edge moment-based descriptors. © 2022, The Authors. All rights reserved.

关键词： Image enhancement

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Green synthesis of tungsten ditelluride and the magnetoresistance property 20th

Green synthesis of tungsten ditelluride and the magnetoresis...

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20th Chinese Materials Conference, CMC 2019

作者： Cao, Mingxing Ma, Liwen Xi, Xiaoli Wang, Zhihong National Engineering Laboratory for Industrial Big-data Application Technology Beijing University of Technology Beijing100124 China College of Materials Science and Engineering Key Laboratory of Advanced Functional Materials Education Ministry of China Beijing University of Technology Beijing100124 China

ISBN: (纸本)9783035715668

As a new type of unsaturated linear magnetoresistive materials, tungsten ditelluride series material has potential applications in the fields of strong magnetic detection, information recording and magnetic storage devices. The current development concepts of "green materials", "green chemical technology" and "environmentally friendly technology" require us to pursue the non-toxic, low-emission and non-emission in material synthesis technology. At the same time, the prepared products show excellent performance and high versatility and efficiency. According to our previous work, the study attempts to use a low-volatile amine solvent as a pretreatment raw material to synthesize a tungsten germanium-based linear magnetoresistive material by hydrothermal/solvothermal method and self-fluxing method. The obtained materials were subjected to XRD, Raman, SEM and Magnetoresistance. Experimental results show that when the mass ratio of W and Te is 1:4, the prepared material is pure phase and the sample is the layered structure. The Magnetoresistance Property points out that the maximum value is about 190 %, which appears in the condition of 10 K and 7 T. Those test projects include phase, structure and morphology characteristics, and provide technical parameters and methods for the development of green synthesis and potential applications of tungsten ditelluride series linear magnetoresistive materials. © 2020 Trans Tech Publications Ltd, Switzerland.

关键词： Virtual storage

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Improved Sparse Activity Detection Based on Optimized Measurement Matrix in mMTC

Improved Sparse Activity Detection Based on Optimized Measur...

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IEEE Conference on Vehicular technology (VTC)

作者： Jianyu Wang Liu Yang Chaoyuan Bai Heng Liu Communication and Sensor Network for Modern Transportation International Cooperation Center(CSNMT) Southwest Jiaotong University Chengdu P.R.China Key Lab of Information Coding & Transmission Institude of Mobile Communication Southwest Jiaotong University Chengdu P.R.China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu P.R.China

ISBN: (数字)9798331517786

ISBN: (纸本)9798331517793

Device activity detection and channel estimation are central problems in massive Machine Type Communication (mMTC) scenarios. Given the sparse distribution of active devices, compressive sensing (CS) emerges as a viable solution at the gNB to mitigate interference stemming from non-orthogonal preamble sets. This paper proposes an algorithm for optimizing measurement matrix, thereby elevating the performance of signal recovery in CS. Within the proposed algorithm, a optimization model that integrates eigenvalue averaging and equiangular tight frame (ETF) theory is formulated, and an iterative algorithm is devised to approximate the optimal solution utilizing singular value decomposition (SVD). Further, a weight-based strategie is discussed with respect to the feasibility of the proposed algorithm, accompanied by the introduction of iteration termination condition. Experimental results corroborate the algorithm’s swift convergence, underpinning the efficient production of high-performance matrices that refine the accuracy of joint device activity detection and channel estimation.

关键词： Vehicular and wireless technologies Optimization models Channel estimation Approximation algorithms Eigenvalues and eigenfunctions Sparse matrices Matrix decomposition Optimization Convergence Singular value decomposition

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Microstructure, Mechanism and Performance of Tungsten Coating Electrodeposited in Na2wo4–Wo3–Napo3–Y2o3 Molten Salt

SSRN

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SSRN 2022年

作者： Xi, Xiaoli Qin, Wenxuan Zhang, Liwen Nie, Zuoren Collaborative Innovation Center of Capital Resource-Recycling Material Technology Beijing University of Technology Beijing100124 China Key Laboratory of Advanced Functional Materials Ministry of Education Faculty of Materials and Manufacturing Beijing University of Technology Beijing100124 China National Engineering Laboratory for Industrial Big-data Application Technology Beijing University of Technology Beijing100124 China

In this paper, smooth tungsten coatings with fine grains were prepared by constant direct current electrodeposition in different molten salt. The X–ray diffraction, scanning electron microscopy and laser scanning confocal microscope were used to characterize the microstructure and micromorphology of tungsten coatings. The micromorphology and surface roughness of tungsten coatings are significantly influenced by the cathodic overpotential. The cathodic overpotential can be modified by the addition of NaPO3 and Y2O3 to influence the coating surface quality. When 3.0 mol% Y2O3 was added to the Na2WO4–WO3–NaPO3 molten salt, the coating has the finest average grains size of 9.86 µm. What’s more, with the Y2O3 concentration increasing, the Ra of the coatings decreases. It is noteworthy that the synergistic addition of NaPO3 and Y2O3 results in superior surface quality. The microhardness and thermal shock resistance of the coatings are improved due to grain refinement. The electroreduction mechanism was explored by electrochemical testing and thermodynamic calculations. The results indicated that the electroreduction of tungsten ions is W(VI)→W(IV)→W, and differences in redox potential and overpotential of tungsten ions in different molten salt were observed by electrochemical tests. © 2022, The Authors. All rights reserved.

关键词： Electrodeposition

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An Orbital Angular Momentum Mode Estimation Method with an Unknown Beam Axis

An Orbital Angular Momentum Mode Estimation Method with an U...

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IEEE SENSORS

作者： Gaofeng Shu Bingxu Chen Ning Li School of Computer and Information Engineering Henan University Henan Engineering Research Center of Intelligent Technology and Application Henan University Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng China

Orbital angular momentum (OAM) beam is very difficult to receive due to the divergence of the beam. The position of the beam axis must be known by the existing receiving methods, including the single point method and the phase gradient method. This article proposes an OAM mode estimation method with an unknown beam axis. This method first estimates the position of the beam axis according to the phase characteristics and then uses the phase gradient method to estimate the OAM mode. The simulation results verify the effectiveness of the method.

关键词： Gradient methods Simulation Estimation Orbits Sensors

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Decomposed Neural Architecture Search for image denoising

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Applied Soft Computing 2022年 124卷

作者： Li, Di Bai, Yunpeng Bai, Zongwen Li, Ying Shang, Changjing Shen, Qiang School of Computer Science National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Shaanxi Provincial Key Laboratory of Speech & Image Information Processing Northwestern Polytechnical University Xi'an710129 China Department of Computer Science Faculty of Business and Physical Sciences Aberystwyth University AberystwythSY233DB United Kingdom Shaanxi Key Laboratory of Intelligent Processing for Big Energy Data School of Physics and Electronic Information Yan'an University Yan'an716000 China

In practical applications of deep learning, as the demand for the modeling capability increases, the network size may need to be massively enlarged in response. This may form a significant challenge in practice, especially when facing the dilemma of limited computational resources, making model compression indispensable. It can be time-consuming and interminable to obtain an appropriate network architecture through manual compression. In this paper, we propose an automated method for searching decomposed network architectures, named DNAS (standing for Decomposed Neural Architecture Search). It integrates both tasks of neural architecture search and tensor decomposition based model compression within a unified framework. The method is able to efficiently find a compact network with high performance for image denoising, with respect to memory and runtime. Particularly, using one single V100 GPU, it only takes about 1.5 h to obtain a denoising network on the BSD500 dataset. Experimental results demonstrate that compared with models developed using existing methods, DNAS consumes significantly less inference time and employs much fewer trainable parameters, outperforming existing approaches on both synthetic and real-world denoising datasets. © 2022 Elsevier B.V.

关键词： Network architecture

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Dynamic image restoration and fusion based on dynamic degradation

arXiv

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arXiv 2021年

作者： Fang, Aiqing Zhao, Xinbo Yang, Jiaqi Zhang, Yanning National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science Northwestern Polytechnical University Xi'an710072 China

The deep-learning-based image restoration and fusion methods have achieved remarkable results. However, the existing restoration and fusion methods paid limited research attention to the robustness problem caused by dynamic degradation. In this paper, we propose a novel dynamic image restoration and fusion neural network, termed as DDRF-Net, which is capable of solving two problems, i.e., static restoration and fusion, dynamic degradation. In order to solve the static fusion problem of existing methods, dynamic convolution is introduced to learn dynamic restoration and fusion weights. In addition, a dynamic degradation kernel is proposed to improve the robustness of image restoration and fusion. Our network framework can effectively combine image degradation with image fusion tasks, provides more detailed information for image fusion tasks through image restoration loss, and optimizes image restoration tasks through image fusion loss. Therefore, the stumbling blocks of deep learning in image fusion, e.g., static fusion weight and specifically designed network architecture, are greatly mitigated. Extensive experiments show that our method neatly outperforms the state-of-the-art methods. © 2021, CC0.

关键词： Image fusion

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Understanding the Long-Distance Travel Mobility of Passengers Based on big Railway data: Travel Network and Motif Perspectives

SSRN

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SSRN 2022年

作者： Xu, Jin Song, Haonan Lu, Zhaoyang Department of Information System & Operation Management School of Economics and Management Southwest Jiaotong University Sichuan Chengdu China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Sichuan Chengdu China Service Science and Innovation Key Laboratory of Sichuan Province Sichuan Chengdu China

With the booming construction of new railway lines and stations in China, the number of railway passengers is increasing. The large railway population shows certain mobility characteristics that we are interested in clarifying. Based on the theory of complex networks, this paper proposes a novel method to identify travel patterns from big railway data, which associates travel motifs with travel networks. This paper derives some meaningful results from the data analysis of more than three million railway travel records of a city in China. These results illustrate that higher motif complexity leads to a narrower travel radius for motif-based subnets. The higher the stability of the travel sequence is, the shorter the average length of the sequence. Four types of travel patterns are identified and classified by analyzing the motif of travel activities, i.e., labor, tourism, surrounding and commuting. The methodology and findings presented in this paper contribute to a better understanding of the long-distance travel mobility of railway passengers. The method designed in this paper can also be used to analyze traffic data from airlines, buses, subways, etc. © 2022, The Authors. All rights reserved.

关键词： Complex networks

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Green and Efficient Method for Recycling Valuable Metals from Scrapped Lithium Cobalt Oxide Cathode Materials 2

Green and Efficient Method for Recycling Valuable Metals fro...

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2nd International Conference on Environmental Prevention and Pollution Control Technologies, EPPCT 2020

作者： Guo, Miaomiao Xi, Xiaoli Zhang, Dongdong Yang, Hang Bi, Fan Hu, Yi Nie, Zuoren Xu, Kaihua National Engineering Laboratory for Industrial Big-data Application Technology Beijing University of Technology Beijing100124 China Chinese National WEEE Recycling Engineering Research Center Jingmen GEM New Material Co. Ltd Jingmen448124 China

In this study, green and efficient method for recycling valuable metals from scrapped lithium cobalt oxide cathode materials to form lithium carbonate and cobalt powder was proposed. To this end, aluminum and iron impurities were efficiently removed from scrapped lithium cobalt oxide cathode materials through alkali dissolution and magnetic separation with removal rates of 99.9% and 98.3%, respectively. After removal of impurities, lithium cobalt oxides were reduced by hydrogen at high temperature of 650 °C for 3 h to yield Li2O, Co, and very small amounts of CoO and LiOH. Next, the mixture was subjected to water leaching and sodium carbonate precipitation to obtain lithium carbonate with purity of 99.5%. The water-leaching Co and small amounts of cobalt oxides were again reduced by hydrogen to form cobalt powder with purity of 99.4%. In sum, the proposed method looks promising in terms of efficiency, easy for implementation, environmentally-friendliness, and potential industrialization. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Cobalt compounds

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