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Versatile core-shell magnetic fluorescent mesoporous microspheres for multilevel latent fingerprints magneto-optic information recognition

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InfoMat 2022年第5期4卷 152-163页

作者： Bingjie Yu Shude Liu Wenhe Xie Panpan Pan Peng Zhou Yidong Zou Qin Yue Yonghui Deng Department of Chemistry Department of Gastroenterology and HepatologyZhongshan HospitalState Key Laboratory of Molecular Engineering of PolymersShanghai Key Laboratory of Molecular Catalysis and Innovative MaterialsFudan UniversityShanghaiChina State Key Laboratory of ASIC and System School of MicroelectronicsFudan UniversityShanghaiChina Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of ChinaChengduChina

Latent fingerprints are extremely vital for personal identification and criminalinvestigation,and potential information recognition techniques have been widelyused in the fields of information and communication *** physicalpowder dusting methods have been frequently employed to develop latent fingerprintsand most of them are carried out by using single component powders ofmicron-sized fluorescent particles,magnetic powders,or metal particles,there isstill an enormous challenge in producing high-resolution image of latent fingerprintsat different backgrounds or ***,a novel and effectivenanoimpregnation method is developed to synthesize bifunctional magnetic fluorescentmesoporous microspheres for latent fingerprints visualization by growthof mesoporous silica(mesoSiO_(2))on magical Fe_(3)O_(4) core and then deposition offluorescent YVO4:Eu^(3+)nanoparticles in the *** obtainedFe_(3)O_(4)@mesoSiO_(2)@YVO4:Eu^(3+)microspheres possess spatially isolated magneticcore and fluorescent shell which were insulated by mesoporous silica *** their small particle size of submicrometer scale,high magnetization and lowmagnetic remanence as well as the combined magnetic and fluorescent properties,the microspheres show superior performance in visual latent fingerprint recognitionwith high contrast,high anti-interference,and sensitivity as well as goodretention on multifarious substrates regardless of surface permeability,roughness,refraction,colorfulness,and background fluorescence interference,and it makesthem ideal candidates for practical application in fingerprint visualization andeven magneto-optic information storage.

关键词： core-shell structure fluorescent materials latent fingerprint magnetic microspheres magneto-optic information recognition

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On the PMD Impact of Dual-Polarization Direct Detection with Jones-Space Optical Field Recovery

On the PMD Impact of Dual-Polarization Direct Detection with...

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2023 Asia communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings, ACP/POEM 2023

作者： Wu, Qi Zhu, Yixiao Jiang, Hexun Xu, Zhaopeng Ji, Honglin Yang, Yu Qiao, Gang Wang, Shangcheng Liu, Lulu Liang, Junpeng Wei, Jinlong Li, Jiali He, Zhixue Zhuge, Qunbi Hu, Weisheng Shanghai Jiao Tong University State Key Laboratory of Advanced Optical Communication System and Networks Department of Electronic Engineering China Peng Cheng Laboratory Shenzhen China

ISBN: (纸本)9798350312614

We theoretically extend the concept of proposed Jones-space optical field recovery to the all-order polarization mode dispersion model for short-reach direct detection optical fiber communications. We numerically verify the impact of polarization mode dispersion can be mitigated using linear equalization as coherent detection systems with a 56-GBd dual-polarization QPSK, 16-QAM, and 64-QAM simulation. © 2023 IEEE.

关键词： Direct detection Jones-space optical field recovery polarization mode dispersion

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405-GBd OOK and 201-GBd PAM-4 IM/DD Optics at Record Faster-Than-Nyquist Ratios of 226.6% and 62.1% Enabled by Advanced Noise Whitening

405-GBd OOK and 201-GBd PAM-4 IM/DD Optics at Record Faster-...

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2023 Asia communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings, ACP/POEM 2023

作者： Wu, Qi Xu, Zhaopeng Zhu, Yixiao Ji, Honglin Yang, Yu Liang, Junpeng Qiao, Gang Wang, Shangcheng Liu, Lulu Wei, Jinlong Zhuge, Qunbi Hu, Weisheng Peng Cheng Laboratory Shenzhen China Shanghai Jiao Tong University State Key Laboratory of Advanced Optical Communication System and Networks Department of Electronic Engineering China

ISBN: (纸本)9798350312614

We experimentally demonstrate 405-GBd OOK and 201-GBd PAM-4 signaling in an intensity modulation and direct detection system with a 62-GHz brick-wall bandwidth. Record faster-than-Nyquist ratios of 226.6% and 62.1% are successfully achieved for OOK and PAM-4 modulations, enabled by the proposed gradient-decent noise whitening technique. © 2023 IEEE.

关键词： faster-than-Nyquist IM-DD noise whitening OOK PAM-4

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Integrated optical frequency transfer and optical physical layer key distribution with enhanced link reciprocity detection

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science China(Information sciences) 2024年第7期67卷 335-336页

作者： Kunfeng XIE Liang HU Jianping CHEN Guiling WU State Key Laboratory of Advanced Optical Communication System and Networks Department of Electronic EngineeringShanghai Jiao Tong University

Optical fiber transmission has been widely used in communications and metrology, wherein optical frequency transfer (OFT) and optical physical layer secure key distribution (OKD) have become research hotspots [1, 2]. Moreover,OFT can perform a comparison between state-of-the-art optical atomic clocks and implement coherent optical phase transfer over long distances to support geodesy [1, 3].

关键词： distribution integrated physical detection layer link with enhanced frequency optical

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Efficient Model-Based OPC via Graph Neural Network

Efficient Model-Based OPC via Graph Neural Network

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2023 International Symposium of Electronics Design Automation, ISEDA 2023

作者： Sun, Shuyuan Chen, Xuelian Yang, Fan Yu, Bei Li, Shang Zeng, Xuan School of Microelectronics Fudan University State Key Lab of ASIC and System China Cogenda Inc China The Chinese University of Hong Kong Department of Computer Science and Engineering Hong Kong

ISBN: (纸本)9798350304510

As feature size continues to shrink and light source wavelengths remain unchanged, the optical diffraction effects seriously degrade chip yield. Optical proximity correction (OPC) has become an essential step for chip manufacturability. However, OPC cannot achieve satisfactory mask correction results in an affordable number of iterations on some layouts, delaying the chip design cycle. In this paper, we propose to use the Graph Neural Network (GNN) to predict the initial mask correction and speed up model-based OPC. We design a graph model to represent the chip layout, with segments represented as graph nodes and the diffraction effects between them represented as graph edges. The GNN is used to obtain the embedding of the segment, and we predict the shift value based on its output. The proposed GNN-based predictor enhances the original OPC to find a good correction solution for full-chip-size masks in fewer iterations. compared with the original OPC method, experimental results on 55nm and 32nm full chip designs show that the proposed GNN-based OPC method reduces the number of iterations up to 75% and the acquired mask of comparable quality. © 2023 IEEE.

关键词： Diffraction

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Automated object recognition in high-resolution optical remote sensing imagery

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National science Review 2023年第6期10卷 38-41页

作者： Yazhou Yao Tao Chen Hanbo Bi Xinhao Cai Gensheng Pei Guoye Yang Zhiyuan Yan Xian Sun Xing Xu Hai Zhang School of Computer Science and Engineering Nanjing University of Science and Technology Aerospace Information Research Institute Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Key Laboratory of Network Information System Technology (NIST) Aerospace Information Research Institute Chinese Academy of Sciences Department of Computer Science and Technology Tsinghua University School of Computer Science and Engineering University of Electronic Science and Technology of China Pazhou Laboratory (Huangpu) School of Mathematics Northwest University

INTRODUCTION With the rapid development of remote sensing technology,high-quality remote sensing images have become widely *** automated object detection and recognition of these images,which aims to automatically locate objects of interest in remote sensing images and distinguish their specific categories,is an important fundamental task in the *** provides an effective means for geospatial object monitoring in many social applications,such as intelligent transportation,urban planning,environmental monitoring and homeland security.

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Simulation and Optimization of In-Situ Integration Ultraviolet HEMT-LED Enabled by P-GaN Selective Epitaxy Growth

Simulation and Optimization of In-Situ Integration Ultraviol...

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SID International Symposium Digest of Technical Papers, 2023

作者： Zhang, Jingyang Huang, Wei Liu, Zhaojun Department of Electronic and Electrical Engineering Southern University of Science and Technology Guangdong Shenzhen518055 China A State Key Laboratory of ASIC and System Shanghai Institute of Intelligent Electronics and Systems School of Microelectronics Fudan University Shanghai200433 China

Based on previous work, the ultraviolet HEMT-LED we fabricated by selective epitaxy growth, this paper further performed simulation to explore the most appropriate p-GaN selection size. P-GaN grown by Selective Epitaxy Growth (SEG) can not only be employed as a junction termination to reduce the electric field crowding of the gate of HEMT, but also form an active region by contacting with 2-dimentional electron gas (2DEG). The simulation results provide an effective reference for the design of p-GaN grown by SEG, and further pave the way for the realization of the idea of integration through the selection of growth methods. © 2023, John Wiley and Sons Inc. All rights reserved.

关键词： Gallium nitride

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Investigation and Comparison of 5G Channel Models: From Qua DRi Ga, NYUSIM,and MG5G Perspectives

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Chinese Journal of Electronics 2022年第1期31卷 1-17页

作者： PANG Lihua ZHANG Jin ZHANG Yang HUANG Xinyi CHEN Yijian LI Jiandong School of Communication and Information Engineering Xi'an University of Science and Technology State Key Laboratory of Integrated Service Networks Xidian University National Mobile Communications Research Laboratory Southeast University Algorithm Department ZTE Corporation

This paper investigates and compares three channel models for the fifth generation(5 G) wireless communications: the quasi deterministic radio channel generator(Qua DRi Ga), the NYUSIM channel simulator model developed by New York University, and the more general 5 G(MG5 G) channel model. First, the characteristics of the modeling processes of the three models are introduced from the perspective of model ***, the small-scale parameter modeling strategies of the three models are compared from space/time/frequency domains as well as polarization aspect. In particular, the drifting of small-scale parameters is introduced in ***, through the simulation results of angular power spectrum, Doppler power spectrum density, temporal autocorrelation function, power delay profile, frequency correlation function, channel capacity, and eigenvalue distribution, the three models are comprehensively investigated. According to the simulation results, we clearly analyze the impact of the modeling strategy on the three channel models and give certain evaluations and suggestion which lay a solid foundation for link and system-level simulations for 5 G transmission algorithms.

关键词： model framework MG5G Perspectives quasideterministic radio channel generator channel capacity QuaDRiGa fifth generation wireless communications general 5G channel model 5G transmission algorithms wireless channels NYUSIM channel simulator model frequency correlation function 5G mobile communication power delay profile eigenvalue distribution eigenvalues and eigenfunctions channel models temporal autocorrelation function small-scale parameter angular power spectrum Doppler power spectrum density

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An Acoustic Dataset Construction Method of Chinese Traditional Musical Instrument Guqin

An Acoustic Dataset Construction Method of Chinese Tradition...

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2024 International Conference on Culture-Oriented science and Technology, CoST 2024

作者： Liu, Jingyu Yang, Chen Li, Zijin Jiang, Wei State Key Laboratory of Media Convergence and Communication Communication University of China 100024 China Ministry of Culture and Tourism Communication University of China Key Laboratory of Acoustic Visual Technology and Intelligent Control System 100024 China Communication University of China School of Information and Communication Engineering 100024 China Central Conservatory of Music Ai Music and Music Information Technology Department 100032 China

ISBN: (纸本)9798350380347

With the acceleration of modernization and the rapid development of popular music, the splendid culture of Guqin, a type of Chinese traditional musical instrument which has lasted for nearly 1,000 years, is facing a serious inheritance crisis. Therefore, how to make full use of modern technical means to digitally store and manage the valuable traditional music cultural resources is the current *** response to the aforementioned challenges, this study focuses on the Guqin, an emblematic Chinese traditional musical instrument. By employing advanced audio feature extraction techniques, this research systematically analyzes the diverse playing techniques of Guqin, thereby establishing a comprehensive acoustic dataset. This endeavor not only facilitates the digital preservation and management of the Guqin's musical heritage but also pioneers a standardized framework for the creation of acoustic datasets. This framework serves as a benchmark for the development of similar datasets, thereby promoting the conservation and standardization of resources associated with Chinese traditional musical instruments. This will provide a scientific basis for the inheritance, standardized management and construction of more acoustic datasets of ethnic musical instruments in the future. © 2024 IEEE.

关键词： Musical instruments

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Edge-Driven Industrial Computing Power Networks: Digital Twin-Empowered Service Provisioning by Hybrid Soft Actor-Critic

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IEEE Transactions on Vehicular Technology 2025年第5期74卷 8095-8109页

作者： Zhang, Long Song, Deng-Ao Zhang, Hongliang Tian, Ni Zhuang, Zirui Niyato, Dusit Han, Zhu Hebei University of Engineering School of Information and Electrical Engineering Handan056038 China Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Beijing100871 China Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China Nanyang Technological University College of Computing and Data Science 639798 Singapore University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

With the proliferation of data-intensive industrial applications, the collaboration of computing powers among standalone edge servers is vital to provision such services for smart devices. In this paper, we propose an edge-driven industrial computing power network (CPN) by orchestrating the computing and network resources of edge servers through the centralized resource scheduling and decentralized task computing. However, efficient task offloading and collaborative processing is challenging, which requires higher degrees of network automation and intelligence. Therefore, we incorporate digital twins (DTs) into the edge-driven CPN architecture, where the DTs are created as the digital replicas to assist both the computation offloading and collaborative processing. A joint optimization problem of the computing power assignment, service association, task partition, and transmit power control is formulated for maximizing the system average weighted utility. Due to the temporal-spatial variability of tasks and the resulted dynamic environment, we transform the original problem as a Markov decision process aiming at maximizing the long-term average weighted utility. To efficiently handle the high-dimensional discrete-continuous action space, a hybrid soft actor-critic based deep reinforcement learning algorithm is developed for optimizing the joint design. Simulation results validate the superiority of our proposed algorithm over the benchmarks, showing the significant gains obtained by integrating DTs into the edge-driven CPN. © 1967-2012 IEEE.

关键词： Markov processes

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