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2019 Photonics and Electromagnetics Research Symposium - Fall, PIERS - Fall 2019

作者： Hu, Wei Li, Jian Huang, Yongjun Wen, Guangjun Zhang, Haobin Zheng, Wenxian Yang, Yongjun Gu, Weiwei Inserra, Daniele Xu, Zhengwu Li, Gui Zhang, Dongliang University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Science and Technology on Electronic Information Control Laboratory Chengdu610036 China Tsinghua Shenzhen International Graduate School Shenzhen518055 China University of Electronic Science and Technology of China Yibin Intelligent Information System Institute Yibin644005 China

ISBN: (纸本)9781728153049

A novel broadband absorber is designed in this paper, which consists of two layers of magnetic materials and metal reflector. In order to achieve broadband performance, the upper layer and the lower layer magnetic material are designed into periodically cylindrically holes with performance multi-resonance frequency. The simulations showed that an absorption more than 90% for normal incident is obtained in the frequency range from 1.62GHz to 18GHz. The absorber has polarization insensitivity when the incident electromagnetic wave is obliquely with TE/TM polarization, and the absorbing is stable within 0-60 degrees incident. The absorber has potential application in radar system and RCS reduced. © 2019 IEEE.

关键词： Ultra-wideband (UWB)

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A Scattered Wave Deceptive Jamming Method Based on Genetic Algorithm against Three Channel SAR GMTI

A Scattered Wave Deceptive Jamming Method Based on Genetic A...

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IEEE International Conference on Radar

作者： Xin Chang Yanbin Li Yan Zhao Yufeng Du Donghui Liu Jun Wan Electronics Technology Group Corporation (CETC54) Hebei Key Laboratory of Electromagnetic Spectrum Cognition and Control The 54th Research Institute of China Shijiazhuang China Electronics Technology Group The 54th Research Institute of China Corporation (CETC54) Shijiazhuang China School of Economics and Management Shijiazhuang Tiedao University Shijiazhuang China Chongqing Key Laboratory of Space Information Network and Intelligent School of Microelectronics and Communication Engineering Chongqing University Information Fusion Chongqing University Chongqing China

ISBN: (纸本)9781665468893

To reduce difficulty of obtaining jamming parameters, combining scattered wave deception jamming method structure with genetic algorithm, a scattered wave deceptive jamming method based on genetic algorithm is proposed against three Channel SAR GMTI. Four-dimensional jamming parameter searching problem is separated as a one-dimensional optimization problem and a two-dimensional optimization problem, which will reduce computational burden and jamming parameter acquirement time and raise fidelity of deceptive jamming. In addition, the problem, that tolerance of Doppler rate mismatch is difficult to describe, is solved by transforming an objective function of the two-dimensional optimization problem. By utilizing jamming quality parameters, simulation experiments are provided to verify the effectiveness of SGA method against the three-channel SAR GMTI.

关键词： Azimuth Computational modeling Radar antennas Search problems Linear programming Doppler effect Jamming

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Local spin-state manipulation of iron single-atom sites induced by sulfur modification to boost Fenton-like reaction

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Chinese Chemical Letters 2025年

作者： Lina Zou Dengke Wang Shiqin Lai Xunheng Jiang Siqi Chen Lanqing Deng Dong Fan Hengshuai Li Zhigang Zhou Denglong Chen Xiangyang Yao Jianping Zou National-Local Joint Engineering Research Center of Heavy Metals Pollutants Control and Resource Utilization Nanchang Hangkong University Nanchang 330063 China College of Environmental and Resource Sciences Zhejiang University Hangzhou 310058 China School of Physics Science and Information Technology & Shandong Key Laboratory of Optical Communication Science and Technology Liaocheng University Liaocheng 252000 China Quangang Research Institute of Petrochemical Technology Fujian Normal University Fuzhou 350007 China Fujian Longking New Land Tech Co. Ltd. Fuzhou 350015 China

A strategy based on local spin-state manipulation was achieved through S-modification on single-Fe-atom catalysts (Fe 1 -NSC). Spectral analyses and theoretical calculations elucidated that a medium-spin reconfiguration of Fe species in Fe 1 -NSC endowed an increased orbital overlap between Fe-3d and O-2p, reinforcing the peroxymonosulfate (PMS) dissociation kinetics. Consequently, Fe 1 -NSC delivered excellent performance in PMS conversion and pollutant degradation. The specific activity of PMS activation over Fe 1 -NSC reached 36.1 × 10 -3 L min -1 m -2 , 4.2-folds that of Fe 1 -NC (8.61 × 10 -3 L min -1 m -2 ) and superior to the state-of-the-art catalysts reported to date. Importantly, the atomic spin-state modulation via S-modification can extend to other metals (Mn, Co and Cu) for improved PMS activation with > 3 times higher than those without S-modification. This work provides a universal scheme for electronic configuration regulation and highlights the significance of local environment modulation in designing high-performance catalysts for PMS activation.

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Target tracking based on KCF combining with spatio-temporal context learning

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International Journal of Performability engineering 2018年第2期14卷 386-395页

作者： Wang, Aili Yang, Zhennan Chen, Yushi Iwahori, Yuji Higher Education Key Lab for Measure and Control Technology and Instrumentations of Heilongjiang Harbin University of Science and Technology Harbin150080 China School of Electronics and Information Engineering Harbin Institute of Technology Harbin150001 China Dept of Computer Science Chubu University Aichi Japan

Most target tracking is based on a lot of samples training to build the model of the target, which is then carried on the tracking processing. This will need to choose a lot of tracked target samples for learning and training. However, there are all kinds of deformation of the training samples, including variety of light and scale, and so on, causing the long computation time, high computational complexity, and less robustness. The traditional kernel correlation filtering (KCF) tracking is through online learning of the first frame in the target vide. It then uses cyclic matrix to strengthen samples robustness, reducing the complexity of the calculation and time. But, the traditional KCF nuclear is unsatisfactory used for complex scenarios and quick treatment. In this paper, under the framework of the KCF, the target context information is introduced to make the tracking have better robustness and a better effect to deal with complex scenarios. © 2018 Totem Publisher, Inc. All rights reserved.

关键词： Target tracking

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control method for EV charging and discharging in V2G/V2H scenario based on the synchronvter technology and H∞ repetitive control

Control method for EV charging and discharging in V2G/V2H sc...

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作者： Liu, Dongqi Zeng, Xiangjun Liu, Guorong Hunan Province Key Laboratory of Smart Grids Operation and Control Changsha University of Science and Technology Changsha China College of Electrical and Information Engineering Hunan University Changsha China School of Computer and Communication Hunan Institute of Engineering Xiangtan China

Electric vehicles (EVs) will play a vital role in the future's transportation systems since this technology is promising for environment, energy security, and improved fuel economy. EVs have huge potential of serving as the energy storage for the power grid as well as inhabitants in vehicle-to-grid (V2G) or vehicle-to-house (V2H) scenario. In this study, a control method is proposed for EV charging and discharging by using the synchronverter technology and H∞ repetitive controller, where synchronverter technology is used to generate the reference voltage to decide the power angle and amplitude of the AC side voltage of the charging/discharging port, so that the power flow between EV and the grid is controlled. In order to ensure the power quality of EVs provided for the grid and the load while EVs are with local loads, a H∞ repetitive controller is designed to control the voltage between EVs and the grid to follow the reference voltage. Simulation results have shown that the proposed controller is not only able to realise bi-directional real power and reactive power control, but also keep the output voltage of EVs in V2G or V2H scenario stable and clear while they are with different kinds of local loads. © 2019 Institution of engineering and *** right reserved.

关键词： Fuel economy

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Modulation Recognition of Composite Signal Based on ResNet and Frequency Domain Graph

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Journal of Physics: Conference Series 2021年第1期2025卷

作者： Lijun Wang Yu Han Hongfang Ge Yongkuan Zhao Lei Shen Science and Technology on Communication Information Security Control Laboratory Jiaxing China The 36th Research Institute of China Electronics Technology Group Corporation Jiaxing China School of Communication Engineering Hangzhou Dianzi University Hangzhou China

Aiming at the problem of composite signal recognition in measurement and control system, a modulation recognition method of composite signal is proposed based on clipped internal modulation signal frequency image and residual network. Residual network has the advantages of fast convergence and high recognition accuracy, which is used to realize the recognition of different modulation modes and different bandwidth signals. The experimental results show that, compared with the traditional decision tree algorithm and the constellation based CNN recognition algorithm, the recognition performance of the proposed method is improved by more than 3dB for the variable bandwidth composite modulation signal set (BPSK-FM and QPSK-FM with internal modulation bandwidth of 128kHz, BPSK-FM and QPSK-FM with internal modulation bandwidth of 2kHz and 2FSK-FM with internal modulation bandwidth of 32kHz and 2kHz).

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Comparison of Different Machine Learning Methods to Forecast Air Quality Index 6th

Comparison of Different Machine Learning Methods to Forecast...

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6th International Conference on Frontier Computing, FC 2018

作者： Liu, Bo Shi, Chao Li, Jianqiang Li, Yong Lang, Jianlei Gu, Rentao Beijing Advanced Innovation Center for Future Internet Technology Beijing University of Technology Beijing100124 China Faculty of Information Technology School of Software Engineering Beijing University of Technology Beijing100124 China Key Laboratory of Beijing on Regional Air Pollution Control Beijing University of Technology Beijing100124 China College of Environmental and Energy Engineering Beijing University of Technology Beijing100124 China Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9789811336478

In recent years, more and more people have been plagued by respiratory diseases. The air quality, which is characterized by inhalable particles and fine particles, has attracted increasing attention. Accurately monitor and forecast the quality of air could not only help the government conduct interventions to alleviate the air pollution earlier, but also alert relevant people who suffer from respiratory diseases. In order to develop effective Air Quality Index (AQI) prediction models, this paper compared the performance of different Machine Learning (ML) methods and feature selection methods. First the air quality data in Beijing from 2016 to 2017 were collected. Then Multi-Linear Regression (MLR), Random forest Regression (RFR), BP Neural Network (BPNN) and Support Vector Regression (SVR) algorithm were trained on 10-fold cross validation. Correlation coefficient (R), mean absolute error (MAE) and root mean square error (RMSE) were used as evaluation metrics. The experimental results showed that the performance of SVR and BPNN were similarly well. MLR had the worst performance, which was possibly caused by a small feature dimension, and RFR had higher accuracy and better generalization capability than the other models, probably because the algorithm of regression tree in random forest included the interaction of variables. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Decision trees

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[email protected] nanorods：Synthesis and their wide controllable range for the local surface plasmon

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Optical Materials 2022年 134卷

作者： Wenlong Yang Xingchen Meng Xinmei Liu Liuyang Zhang Chenwei Wang Xiaoyang Yu Ying Yang School of Measurement and Communication Engineering Harbin University of Science and Technology Harbin 150080 PR China Key Laboratory of Laser Spectroscopy Technology and Application of Heilongjiang Province Harbin 150080 PR China State Key Laboratory of Mechanics and Control of Mechanical Structures Nanjing University of Aeronautics and Astronautics Nanjing 210016 PR China School of Material Science and Chemical Engineering Harbin University of Science and Technology Harbin 150080 PR China

This work demonstrated the wide controllable range of the Local Surface Plasmon Resonance (LSPR) characteristic peak of the KTa x-1 Nb x O 3 @Ag ( [email protected] ). [email protected] nanocubes ( [email protected] NCs) and [email protected] nanorods ( [email protected] NRs) with different Ag loading rate have been prepared. Compared with [email protected] NCs, the LSPR characteristic peak of [email protected] NRs showed a wider controllable range and the enhanced factor could reach 5.48. This result could be derived from the higher aspect ratio of [email protected] NRs, resulting in an enhanced the coupling effect between KTN and Ag. This viewpoint could also be verified by the FDTD (Finite-Difference Time-Domain) calculation. With the increase of Ag loading rate, the coupling between KTN and Ag was weakened. And the characteristic peak of [email protected] show a blue shift, which shifts to the characteristic peak of Ag nanocrystal gradually. With the increase of Ag loading rate from 11 to 21 wt%, the LPSR characteristic peak of [email protected] NCs showed a blue shift from 569 to 547 nm, whereas peak for [email protected] NRs was shifted from 762 to 646 nm. This work combined the coupling effect of nanostructured KTN and Ag nanocrystals. And the anisotropy would be beneficial to broaden the LSPR controllable range of the characteristic extinction spectra of [email protected] Considering the low price of KTN, the [email protected] NRs should be a promising material applied in optical detection devices.

关键词： FDTD calculation LSPR Coupling effect Loading rate Blue shift

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Contrast enhancement of illumination layer image using optimized subsection-based histogram equalization

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International Journal of Performability engineering 2018年第11期14卷 2624-2632页

作者： Wang, Yongxin Diao, Ming Wu, Haibin School of Information and Communication Engineering Harbin Engineering University Harbin150080 China Higher Educational Key Laboratory for Measuring and Control Technology and Instrumentation of Heilongjiang Province Harbin University of Science and Technology Harbin150080 China

A key problem of underwater image sharpening is to improve image contrast while retaining image detail. The retinex model is used to obtain the illumination and detail layer images. The histogram of the illumination layer image is divided into under-exposure subsection and over-exposure subsection by using the maximum interclass variance method, and the histogram subsections are equalized separately. The above process of histogram dividing and equalization is repeated until the difference between adjacent thresholds for dividing histogram subsections reaches its optimal value. This enhances the contrast of the illumination layer image. As a result, our contrast enhancement method of illumination layer image using optimized histogram subsection based histogram equalization is formed. Furthermore, by multiplying the enhanced contrast of illumination layer image with the original detail layer image, the contrast of underwater image is enhanced and its original details are retained. Some evaluations, e.g. information entropy and mean structure similarity, are examined to show that the underwater image quality is improved appropriately. © 2018 Totem Publisher, Inc. All rights reserved.

关键词： Image enhancement

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3D facial geometry recovery from a depth view with attention guided generative adversarial network

arXiv

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arXiv 2020年

作者： Cai, Xiaoxu Yu, Hui Lou, Jianwen Zhang, Xuguang Li, Gongfa Dong, Junyu School of Creative Technologies University of Portsmouth PortsmouthPO1 2DJ United Kingdom School of Communication Engineering Hangzhou Dianzi University Hangzhou310018 China Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Wuhan430081 China College of Information Science and Engineering Ocean University of China Qingdao266100 China

We present to recover the complete 3D facial geometry from a single depth view by proposing an Attention Guided Generative Adversarial Networks (AGGAN). In contrast to existing work which normally requires two or more depth views to recover a full 3D facial geometry, the proposed AGGAN is able to generate a dense 3D voxel grid of the face from a single unconstrained depth view. Specifically, AGGAN encodes the 3D facial geometry within a voxel space and utilizes an attention-guided GAN to model the ill-posed 2.5D depth-3D mapping. Multiple loss functions, which enforce the 3D facial geometry consistency, together with a prior distribution of facial surface points in voxel space are incorporated to guide the training process. Both qualitative and quantitative comparisons show that AGGAN recovers a more complete and smoother 3D facial shape, with the capability to handle a much wider range of view angles and resist to noise in the depth view than conventional methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Generative adversarial networks

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