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2023 Advanced Fiber Laser Conference, AFL 2023

作者： Shen, Shiteng Dong, Fanlong Yan, Peiguang Wang, Jingzhang Lue, Qitao Guo, Chunyu Ruan, Shuangchen Shenzhen Key Laboratory of Laser Engineering Guangdong Provincial Key Laboratory of Micro/Nano Optomechatronics Engineering Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province State Key Laboratory of Radio Frequency Heterogeneous Integration College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518060 China Key Lab. of Adv. Optical Precision Manufacturing Technology of Guangdong Higher Education Institutes Shenzhen Technology University Shenzhen518118 China Han s Laser Technology Industry Group Co. Ltd Shenzhen518057 China

ISBN: (纸本)9781510677661

In this paper, a high power Tm3+-doped fiber laser (TDFL) based on a monolithic master oscillator power amplifier (MOPA) system with the center wavelength is 1940 nm is demonstrated. The maximum laser power was measured to be 200 W with a slope efficiency of 56.2% at the 793 nm pump power of 368.6 W. Power stability of the laser output over 60 min is measured to be ∼0.12%, which indicate a relatively stable laser operation of the TDFL. The output power is limited by the availab.e pump power for the lack of amplified spontaneous emission, parasitic oscillation or self-pulsing effects even at the maximum output power level, showing further power scaling should be possible with increase the pump power. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Fiber lasers

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Bifocal metalens incorporating spatial-variant subwavelength gratings 4

Bifocal metalens incorporating spatial-variant subwavelength...

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2024 4th International Conference on Optics and Communication Technology, ICOCT 2024

作者： Qian, Sen Zhou, Chenglin Xu, Yishen Ye, Yan School of Optoelectronics Science and Engineering Collaborative Innovation Center of Suzhou Nano Science and Technology Soochow University Suzhou215006 China School of Optical and Electronic Information Suzhou City University Suzhou215104 China Key Lab. of Advanced Optical Manufacturing Technologies of Jiangsu Province Key Lab. of Modern Optical Technologies of Education Ministry of China Soochow University Suzhou215006 China

ISBN: (纸本)9781510685734

Based on the Pancharatnam-Berry phase principle, metalens permits precise phase manipulation through spatial-variant micro/nano-structures. In this study, a bifocal metalens incorporating spatial-variant subwavelength silicon(Si) gratings is introduced for an incident wavelength of 1550 nm with orthogonally circular polarization. The metalens is segmented into two interleaved sub-apertures for right-handed circularly polarized(RCP) and left-handed circularly polarized(LCP) lights, respectively. For incident RCP light, the proposed bifocal metalens attains a focal length of 100 µm, which can be adjusted to 200 µm through polarization state switching to LCP. Furthermore, with inverse designed diaphragms and holographic optical element, a Fourier transform optical interference lithography system is utilized to generate multiple interference light beams simultaneously and fabricate targeted spatial-variant micro/nano-gratings in the photoresist film, which is promising for the production of the Pancharatnam-Berry phase metalens based on spatial-variant nanogratings. © 2024 SPIE.

关键词： Photoresists

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Evolutionary Algorithms with Heuristic Gradient-based Repair for Constrained Optimization

Evolutionary Algorithms with Heuristic Gradient-based Repair...

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2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Du, Jiacheng Bu, Chenyang Liu, Yuxin Liu, Fei Luo, Wenjian Hefei University of Technology Ministry of Education Key Laboratory of Knowledge Engineering with Big Data School of Computer Science and Information Engineering Anhui Hefei230027 China Harbin Institute of Technology School of Computer Science and Technology Guangdong Shenzhen518000 China

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Gradient-based repair aims to repair infeasible solutions to feasible ones using the gradient information of the constraints. As an effective constraint handling method, gradientbased repair has received extensive attention and has been applied in various evolutionary algorithms (EAs). Nevertheless, due to the complexity of constraints in practical problems, a single infeasible solution often needs to be repaired multiple times until it becomes a feasible solution or reaches the maximum number of repairs. As far as we know, existing related research on gradient-based repair mainly applies this method directly to EAs, while there is little work in the evolutionary computing community on how to improve gradient-based repair. Currently, the multiple repairs for a single individual are independent. That is, the current repair does not consider the previous repair experience. However, only using gradient information to repair infeasible individuals may result in oscillations in the search process. Therefore, in this paper, we propose a heuristic gradient-based repair method (HGR) which exploits the previous repair information of an individual to alleviate this issue. Experimental results on several benchmarks demonstrate the effectiveness of the proposed method. The source code is availab.e at https://***/DMiC-lab.HFUT/HGR-SMC2022. © 2022 IEEE.

关键词： Constrained optimization

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Spin-Momentum Locking based on Single Layer Bianisotropic Metasurface

Spin-Momentum Locking based on Single Layer Bianisotropic Me...

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2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023

作者： Sun, Yiqian Jiang, Zhaoqi Zhou, Hao Cong, Rong Li, Wenjia Zhu, Zheng Guan, Chunying Shi, Jinhui College of Physics and Optoelectronic Engineering Key Lab. of Photonic Mat. and Devices Phys. for Oceanic Applic. Min. of Indust. and Info. Technol. of China Harbin Engineering University Harbin150001 China College of Physics and Optoelectronic Engineering Key Laboratory of In-Fiber Integrated Optics of Ministry of Education Harbin Engineering University Harbin150001 China

ISBN: (纸本)9798350358971

In recent years, photon spin has been widely used in quantum information coding and spin filtering. Metasurface can control the spin and polarization of electromagnetic wave, which has a wide range of applications in polarizer, switch, optical communication, photoelectric detection, quantum information processing. In this work, the spin momentum locking of bianisotropic metasurfaces is thoroughly investigated and discussed, focusing on the transverse spins in bianisotropic metasurfaces and their polarization modulation of electromagnetic waves. The polarization responses of the designed structure are investigated by theoretical derivation and simulation. The proposed metasurface provides an idea of designing a polarization device for various applications. © 2023 IEEE.

关键词： bianisotropy metasurface spin momentum locking transverse spin

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Machine Learning Method Evaluates Upper-Limb Motor Function by fNIRS in Stroke Patients 4

Machine Learning Method Evaluates Upper-Limb Motor Function ...

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4th IEEE International Conference on Pattern Recognition and Machine Learning, PRML 2023

作者： Xu, Weiwei Tao, Yi Zhu, Jialin Yuan, Ziwen Guo, Jing Wang, Gang Xi'An Jiaotong University Key Lab. of Biomed. Info. Engineering of Ministry of Education School of Life Science and Technology Xi'an China First Affiliated Hospital of xi'An Jiaotong University Department of Rehabilitation Xi'an China

ISBN: (纸本)9798350324303

The upper limb motor impairment after stroke seriously affects patients' quality of life, and the evaluation of upper limb motor function depends on professionals, which is subjective, complicated, and time-consuming. Neurophysiological information evaluation Fugl-Meyer assessment of the upper limb (FMA-UL) is expected to solve this problem. Our study aims to estimate FMA-UL using the functional connectivity measures and network properties of task state functional near-infrared spectroscopy (fNIRS). FNIRS was recorded when the subjects performed the hand-grasping task, representing the oxyhemoglobin concentration changes. Functional connectivity was gauged via Pearson correlation coefficients, selectively retained within a 10% to 50% threshold. We calculated two macroscale and two mesoscale network properties based on graph theory. Then the support vector regression (SVR) was applied to estimate the FMA-UL. Cross-validation with leave-one-out, resulted in an R^{\mathbf{2}} of 0.49, with a root mean square error of 4.96, 5 of the 15 subjects had absolute errors less than 0.75, when the sparsity of functional connectivity is 40%. Functional connectivity and network properties by fNIRS is a promising method to predict motor impairment. Our study demonstrated that functional connectivity and network properties are correlated with motor impairment and brain reorganization in stroke patients. The method proposed reflects prospects for finding neural biomarkers to predict FMA-UL and is feasible for using fNIRS to predict the motor function of stroke. © 2023 IEEE.

关键词： Graph theory

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Plus ça change, plus c'est la même chose – The Australian Records Management Case 18th

Plus ça change, plus c'est la même chose – The Australian...

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18th International Conference on Information for a Better World: Normality, Virtuality, Physicality, Inclusivity, iConference 2023

作者： Xie, Sherry L. Gao, Yubao Ma, Linqing School of Information Resource Management Renmin University of China Beijing100872 China Center for Digital Records Management Research Renmin University of China Beijing100872 China Key Laboratory of Data Engineering and Data Knowledge of the Ministry of Education of China Beijing100872 China Center for Archival Undertakings Renmin University of China Beijing100872 China

ISBN: (纸本)9783031280344

Intrigued by the information management replacing records management phenomenon, this study aimed at shedding light on it. Relying on preserved websites, the study examined relevant contents from 2007 to early 2022. It discovered the battle between records and information, and later on information asset. This battle incurred dazzling changes in managerial considerations, yet the challenges to management – either towards records, information, information and records, or information asset – remained the same. So were the unsatisfactory outcomes. A case seemed perfect to tell the plus ça change, plus c'est la même chose story. It is our hope that future studies can gather mighty strengthen and thus settle down the records-information battle once for all. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Information management

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data-Driven Stabilization for a Class of Unknown Switched Linear Systems with Asynchronism 43

Data-Driven Stabilization for a Class of Unknown Switched Li...

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43rd Chinese Control Conference, CCC 2024

作者： Qi, Wan-Ling Liu, Kun-Zhi Cheng, Xiao-Lin Wang, Rui Dalian University of Technology School of Control Science and Engineering Dalian116024 China Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China Dalian University of Technology School of Aeronautics and Astronautics Dalian116024 China

ISBN: (纸本)9789887581581

This brief investigates the data-driven stabilization for a class of unknown switched linear systems in both continuous and discrete time. We assume that the switching signal is known but the system matrices of each subsystem are unknown and belong to some sets described by finite noisy input-state data. data-driven parameterization of each unknown subsystem is built on the instantaneous bound of the external disturbance rather than the energy bound. The closed-loop stability is guaranteed by adopting a controller-mode-dependent Lyapunov function and the resulting stability conditions are data-based rather than model-based. The switching signals are arbitrary as long as they satisfy the average dwell time (ADT) condition that derived from noisy data. Two numerical examples are presented to illustrate how to enhance the feasibility of the proposed methods. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Stabilization

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arXiv

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arXiv 2025年

作者： Li, Yangning Kang, Hui Li, Jiahui Sun, Geng Sun, Zemin Wang, Jiacheng Zhao, Changyuan Niyato, Dusit College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China College of Computing and Data Science Nanyang Technological University 639798 Singapore College of Computing and Data Science Nanyang Technological University Singapore

An expansion of Internet of Things (IoTs) has led to significant challenges in wireless data harvesting, dissemination, and energy management due to the massive volumes of data generated by IoT devices. These challenges are exacerbated by data redundancy arising from spatial and temporal correlations. To address these issues, this paper proposes a novel data-driven collab.rative beamforming (CB)-based communication framework for IoT networks. Specifically, the framework integrates CB with an overlap-based multi-hop routing protocol (OMRP) to enhance data transmission efficiency while mitigating energy consumption and addressing hot spot issues in remotely deployed IoT networks. Based on the data aggregation to a specific node by OMRP, we formulate a node selection problem for the CB stage, with the objective of optimizing uplink transmission energy consumption. Given the complexity of the problem, we introduce a softmax-based proximal policy optimization with long-short-term memory (SoftPPO-LSTM) algorithm to intelligently select CB nodes for improving transmission efficiency. Simulation results show that the proposed OMRP improves network lifetime by 17% compared to benchmark routing protocols, while the SoftPPO-LSTM method for CB node selection achieves an 8.3% increase in throughput over benchmark algorithms. The results also reveal that the combined OMRP with the SoftPPO- Copyright © 2025, The Authors. All rights reserved.

关键词： Deep reinforcement learning

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Dual-Modeling Decouple Distillation for Unsupervised Anomaly Detection 24

Dual-Modeling Decouple Distillation for Unsupervised Anomaly...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Liu, Xinyue Wang, Jianyuan Leng, Biao Zhang, Shuo School of Computer Science and Engineering Beihang University Beijing China Key Laboratory of Intelligent Bionic Unmanned Systems Ministry of Education School of Intelligence Science and Technology University of Science and Technology Beijing Beijing China Beijing Key Lab of Traffic Data Analysis and Mining School of Computer & Technology Beijing Jiaotong University Beijing China

ISBN: (纸本)9798400706868

knowledge distillation based on student-teacher network is one of the mainstream solution paradigms for the challenging unsupervised Anomaly Detection task, utilizing the difference in representation capabilities of the teacher and student networks to implement anomaly localization. However, over-generalization of the student network to the teacher network may lead to negligible differences in representation capabilities of anomaly, thus affecting the detection effectiveness. Existing methods address the possible over-generalization by using differentiated students and teachers from the structural perspective or explicitly expanding distilled information from the content perspective, which inevitably results in an increased likelihood of underfitting of the student network and poor anomaly detection capabilities in anomaly center or edge. In this paper, we propose Dual-Modeling Decouple Distillation (DMDD) for the unsupervised Anomaly Detection. In DMDD, a Decouple Student-Teacher Network is proposed to decouple the initial student features into normality and abnormality features. We further introduce Dual-Modeling Distillation based on normal-anomalous image pairs, fitting normality features of anomalous image and the teacher features of the corresponding normal image, widening the distance between abnormality features and the teacher features in anomalous regions. Synthesizing these two distillation ideas, we achieve anomaly detection which focuses on both edge and center of anomaly. Finally, a Multi-perception Segmentation Network is proposed to achieve focused anomaly map fusion based on multiple attention. Experimental results on MVTec AD show that DMDD surpasses SOTA localization performance of previous knowledge distillation-based methods, reaching 98.85% on pixel-level AUC and 96.13% on PRO. © 2024 ACM.

关键词： Students

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ESO-Based data Driven Set-Point Learning Control for Nonlinear batch Processes with PD-Type Feedback Control Structure Subject to Nonrepetitive Uncertainties* 13

ESO-Based Data Driven Set-Point Learning Control for Nonline...

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13th IEEE data Driven Control and Learning Systems Conference, DDCLS 2024

作者： Ahmad, Naseem Hao, Shoulin Liu, Tao Gong, Yihui Zhang, Jiyan Wang, Haixia Zhu, Yong Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China Institute of Advanced Control Technology Dalian University of Technology Dalian116024 China School of Biomedical Engineering Dalian University of Technology Dalian116024 China

ISBN: (纸本)9798350361674

In this paper, an extended state observer (ESO) based data-driven set-point learning control (DDSPLC) scheme is proposed for nonlinear batch processes configured with an inherent PD-type control loop, so as to actively suppress the adverse effect of nonrepetitive external disturbances and nonidentical initial resetting conditions, by only utilizing the availab.e process input/output data. The controlled process is firstly reformulated as an iterative dynamic linearization data model (IDLDM) with an extra generalized disturbance, where the unknown pseudo partial derivative and the generalized disturbance are, respectively, estimated by a projection-like algorithm and iterative ESO along the batch direction. By virtue of the estimated PPD and generalized disturbance, a set-point learning updating law with adaptive learning gain is then developed to optimize the tracking performance from batch-to-batch, by tuning the set-point command of the closed-loop PD-type control. Robust convergence analysis for the established closed-loop learning system is analyzed rigorously. The effectiveness and superiority of the proposed scheme are verified by an illustrative example. © 2024 IEEE.

关键词： State estimation

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