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Orbit-Orbit Interaction in Spatiotemporal Optical Vortex

engineering 2025年第2期45卷 44-51页

作者： Jian Chen Jie Zhao Xi Shen Dewei Mo Cheng-Wei Qiu Qiwen Zhan School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China Shanghai Key Laboratory of Modern Optical System University of Shanghai for Science and TechnologyShanghai 200093China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore

While spin-orbit interaction has been extensively studied,few investigations have reported on the interaction between orbital angular momenta(OAMs).In this work,we study a new type of orbit-orbit coupling between the longitudinal OAM and the transverse OAM carried by a three-dimensional(3D)spatiotemporal optical vortex(STOV)in the process of tight *** 3D STOV possesses orthogonal OAMs in the x-y,t-x,and y-t planes,and is preconditioned to overcome the spatiotemporal astigmatism effect.x,y,and t are the axes in the spatiotemporal *** corresponding focused wavepacket is calculated by employing the Debye diffraction theory,showing that a phase singularity ring is generated by the interactions among the transverse and longitudinal vortices in the highly confined *** Fourier-transform decomposition of the Debye integral is employed to analyze the mechanism of the orbit-orbit *** is the first revelation of coupling between the longitudinal OAM and the transverse OAM,paving the way for potential applications in optical trapping,laser machining,nonlinear light-matter interactions,and more.

关键词： Spatiotemporal optical vortex Orbital angular momentum Momentum interaction Highly confined wavepacket Diffraction

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Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 126-137页

作者： Dongfang Li Jie Huang Rob Law Xin Xu Limin Zhu Edmond Q.Wu IEEE the School of Electrical Engineering and Automation Fuzhou University the Key Laboratory of System Control and Information Processing Ministry of Education the School of Electrical Engineering and Automation Fuzhou University 5G+Industrial Internet Institute Fuzhou University the University of Macau the College of Mechatronics and Automation National University of Defense Technology the School of Mechanical Engineering Shanghai Jiao Tong University the Department of Computer Science and Engineering Shanghai Jiao Tong University

This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.

关键词： Adaptive integral surge line-of-sight approximation robotic fish speed observer

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A Fully LTPS-TFT-Based Bi-Directional Biomedical Interface Circuit for Large-Area Healthcare Applications

IEEE Journal on Flexible Electronics

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IEEE Journal on Flexible Electronics 2025年第12期3卷 526-532页

作者： Zhang, Hanbo Lou, Yuqing Zhang, Zhihang Li, Yongfu Rokhan, Fakhrul Wang, Guoxing Zhao, Jian Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai200240 China Universiti Putra Malaysia Faculty of Engineering Department of Computer and Communication System Engineering Selangor Serdang43400 Malaysia

This paper proposed a fully LTPS-TFT-based bi-directional biomedical pixel interface with integrated a high linearity stimulator and a high-performance bio-potential sensing front-end circuit to amplify and digitize biological signals for high robustness data transmission. All circuits are designed and manufactured under a 3-μm LTPS process. We demonstrated the experiment in saline using the stimulator circuit to simulate stimulation inside the organism, achieving stimulation with different average currents under different duty cycles. The proposed front-end circuit has a gain of 40 dB. The referred input voltage noise of the entire signal chain is 86.2 μV/√Hz, and the ENOB is 9.13 bits at an input of 0.5 mVPP. Simultaneously conducting statistical testing on 20 chips has achieved a 1.05 dB SNDR standard deviation. Finally, we use a function signal generator to simulate the input signals of ECoG, ECG, and EOG, then use front-end circuits to read and reconstruct them to demonstrate that the proposed pixel interface can correctly read common biomedical signals for healthcare applications. © 2022 IEEE.

关键词： Image segmentation

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Functionalised B-Cu@F-Ag@Au trimetallic nanomaterials with long term stability for rapid and highly sensitive in situ SERS detection of furfural in transformer oil

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High Voltage 2023年第2期8卷 293-304页

作者： Yu Lei Changding Wang Weiping Kong Mingliang Wang Xinyuan Zhang Abdolmaleki Nima Caisheng Wang Weigen Chen Fu Wan School of Electrical Engineering Chongqing UniversityChongqingChina State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing UniversityChongqingChina Electrical and Computer Engineering Wayne State UniversityWayneNebraskaUSA

The surface-enhanced Raman scattering(SERS)substrates enable a highly sensitive detection of furfural in the transformer ***,detection substrates with long-term stability are still extremely *** this work,we anchored the thiol-containing coupling agents 2,5-dimercapto-1,3,4-thiadiazole(DMTD)and 1,4-benzenedithiol(BDT)on the surface of bubble copper(B-Cu)and flower-like silver nanoparticles(FAg),*** three-dimensional SERS detection substrates with long-term stability by using a combination of chemical reduction and self-assembly methods were *** substrate has a minimum detection limit of 10^(−9) M for rhodamine B in oil with an enhancement factor of up to 2.23×10^(7).Importantly,the three-crystal BCu@F-Ag_(1)@Au_(5) substrate was used for the detection of furfural in the transformer oil with a detection limit of 2 mg/L and a relative standard deviation value of 2.46%.After 60 days of a simulated operation,the detection signal of furfural in the transformer oil samples at 75℃ and still reached the initial value of 77.53%,indicating that the substrate has a good long-term *** triple frame structured SERS detection platform shows great potential in tracking furfural in the aging transformer oil mixing systems.

关键词： stability. stability SERS

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Large circuit models: opportunities and challenges

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Science China(Information Sciences) 2024年第10期67卷 25-66页

作者： Lei CHEN Yiqi CHEN Zhufei CHU Wenji FANG Tsung-Yi HO Ru HUANG Yu HUANG Sadaf KHAN Min LI Xingquan LI Yu LI Yun LIANG Jinwei LIU Yi LIU Yibo LIN Guojie LUO Hongyang PAN Zhengyuan SHI Guangyu SUN Dimitrios TSARAS Runsheng WANG Ziyi WANG Xinming WEI Zhiyao XIE Qiang XU Chenhao XUE Junchi YAN Jun YANG Bei YU Mingxuan YUAN Evangeline F.Y.YOUNG Xuan ZENG Haoyi ZHANG Zuodong ZHANG Yuxiang ZHAO Hui-Ling ZHEN Ziyang ZHENG Binwu ZHU Keren ZHU Sunan ZOU Huawei Noah’s Ark Lab School of Integrated Circuits Peking University Faculty of Electrical Engineering and Computer Science Ningbo University Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Department of Computer Science and Engineering The Chinese University of Hong Kong School of Integrated Circuits Southeast University Huawei HiSilicon Peng Cheng Laboratory School of Computer Science Peking University School of Microelectronics State Key Laboratory of Integrated Chips and System Fudan University School of Artificial Intelligence Shanghai Jiao Tong University

Within the electronic design automation(EDA) domain, artificial intelligence(AI)-driven solutions have emerged as formidable tools, yet they typically augment rather than redefine existing methodologies. These solutions often repurpose deep learning models from other domains, such as vision, text, and graph analytics, applying them to circuit design without tailoring to the unique complexities of electronic circuits. Such an “AI4EDA” approach falls short of achieving a holistic design synthesis and understanding,overlooking the intricate interplay of electrical, logical, and physical facets of circuit data. This study argues for a paradigm shift from AI4EDA towards AI-rooted EDA from the ground up, integrating AI at the core of the design process. Pivotal to this vision is the development of a multimodal circuit representation learning technique, poised to provide a comprehensive understanding by harmonizing and extracting insights from varied data sources, such as functional specifications, register-transfer level(RTL) designs, circuit netlists,and physical layouts. We champion the creation of large circuit models(LCMs) that are inherently multimodal, crafted to decode and express the rich semantics and structures of circuit data, thus fostering more resilient, efficient, and inventive design methodologies. Embracing this AI-rooted philosophy, we foresee a trajectory that transcends the current innovation plateau in EDA, igniting a profound “shift-left” in electronic design methodology. The envisioned advancements herald not just an evolution of existing EDA tools but a revolution, giving rise to novel instruments of design-tools that promise to radically enhance design productivity and inaugurate a new epoch where the optimization of circuit performance, power, and area(PPA) is achieved not incrementally, but through leaps that redefine the benchmarks of electronic systems' capabilities.

关键词： AI-rooted EDA large circuit models (LCMs) multimodal circuit representation learning circuit optimization

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CRAFT: Criticality-Aware Fault-Tolerance Enhancement Techniques for Emerging Memories-Based Deep Neural Networks

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IEEE Transactions on computer-Aided Design of Integrated Circuits and systems 2023年第10期42卷 3289-3300页

作者： Nguyen, Thai-Hoang Imran, Muhammad Choi, Jaehyuk Yang, Joon-Sung Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of Department of Electrical Engineering School of Electrical Engineering and Computer Science National University of Sciences and Technology Islamabad44000 Pakistan Department of Semiconductor Systems Engineering Sungkyunkwan University Suwon16419 Korea Republic of School of Electrical and Electronic Engineering Department of System Semiconductor Engineering Yonsei University Seoul03722 Korea Republic of

Deep neural networks (DNNs) have emerged as the most effective programming paradigm for computer vision and natural language processing applications. With the rapid development of DNNs, efficient hardware architectures for deploying DNN-based applications on edge devices have been extensively studied. Emerging nonvolatile memories (NVMs), with their better scalability, nonvolatility, and good read performance, are found to be promising candidates for deploying DNNs. However, despite the promise, emerging NVMs often suffer from reliability issues, such as stuck-at faults, which decrease the chip yield/memory lifetime and severely impact the accuracy of DNNs. A stuck-at cell can be read but not reprogrammed, thus, stuck-at faults in NVMs may or may not result in errors depending on the data to be stored. By reducing the number of errors caused by stuck-at faults, the reliability of a DNN-based system can be enhanced. This article proposes CRAFT, i.e., criticality-aware fault-tolerance enhancement techniques to enhance the reliability of NVM-based DNNs in the presence of stuck-at faults. A data block remapping technique is used to reduce the impact of stuck-at faults on DNNs accuracy. Additionally, by performing bit-level criticality analysis on various DNNs, the critical-bit positions in network parameters that can significantly impact the accuracy are identified. Based on this analysis, we propose an encoding method which effectively swaps the critical bit positions with that of noncritical bits when more errors (due to stuck-at faults) are present in the critical bits. Experiments of CRAFT architecture with various DNN models indicate that the robustness of a DNN against stuck-at faults can be enhanced by up to 105 times on the CIFAR-10 dataset and up to 29 times on ImageNet dataset with only a minimal amount of storage overhead, i.e., 1.17%. Being orthogonal, CRAFT can be integrated with existing fault-tolerance schemes to further enhance the robustness of DNNs aga

关键词： Fault tolerance

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Enhancement Methods for Chiral Optical Signals by Tailoring Optical Fields and Nanostructures

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engineering 2025年第2期45卷 25-43页

作者： Hanqing Cai Liangliang Gu Haifeng Hu Qiwen Zhan School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China Zhangjiang Laboratory Shanghai 201204China Shanghai Key Laboratory of Modern Optical System University of Shanghai for Science and TechnologyShanghai 200093China

The unique property of chirality is widely used in various *** the past few decades,a great deal of research has been conducted on the interactions between light and matter,resulting in significant technical advancements in the precise manipulation of light field *** this review,which focuses on current chiral optics research,we introduce the fundamental theory of chirality and highlight the latest achievements in enhancing chiral signals through artificial nano-manufacturing technology,with a particular focus on mechanisms such as light scattering and Mie resonance used to amplify chiral *** providing an overview of enhanced chiral signals,this review aims to provide researchers with an indepth understanding of chiral phenomena and its versatile applications in various domains.

关键词： Mie scattering Optical chirality Circular dichroism Orbital angular momentum Bound states in the continuum Nonlinear optics

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Salp Swarm Algorithm Based Optimal Network Reconfiguration with Distributed Generation for Power Loss Minimization and Voltage Profile Improvement

Salp Swarm Algorithm Based Optimal Network Reconfiguration w...

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2023 International Conference on Sustainable Technology and engineering, i-COSTE 2023

作者： Alende, Azmerawu Argawu School of Electrical and Computer Engineering Hawassa University Department of Power System and Energy Engineering Hawassa Ethiopia

ISBN: (纸本)9798350329711

In a distribution system, power loss and voltage deviation are the main concern for the customers and utility. The distribution system has a lower voltage level and higher amount of flowing current than the transmission system, so that, the percentage real power loss in the distribution system is higher. This study addresses power loss and voltage deviation concerns in distribution systems. It optimizes the Yirgalem-Ethiopia radial distribution network using the Salp Swarm Algorithm (SSA) and solar Distributed Generation (DG). SSA outperforms other algorithms in reducing real and reactive power losses and improving the voltage profile. The approach minimizes network costs and maintains voltage within acceptable limits. It proves cost-effective, demonstrating significant power loss reduction and improved voltage profiles. The resource feasibility of solar and wind power in Yirgalem city was analyzed and the outcomes showed that solar power generation is more desirable. For this reason, the solar-type Distributed Generation (DG) is used. The proposed SSA algorithm was compared with Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA) in three various scenarios (only optimal network reconfiguration, only optimal DG size and site, and simultaneous optimal network reconfiguration and DG allocation) for the Aposto feeder. As stated, the SSA method performs better in terms of reducing both real and reactive power losses and improvement of voltage profile. The model has been formulated to minimize the total cost of the network by determining the optima of the substation locations and power, the load transfers between the demand centers, the feeder routes and the load flow in the network subject to a set of constraints. From the point of view of economic evaluations, the proposed approach is cost-effective. Generally, the simulation results show that the proposed technique is effective to maintain all buses voltage magnitude within the IEEE acceptable lim

关键词： Distributed power generation

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Control and Stability of Large-scale Power system with Highly Distributed Renewable Energy Generation:Viewpoints from Six Aspects

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CSEE Journal of Power and Energy systems 2023年第1期9卷 8-14页

作者： Qing-Hua Wu Anjan Bose Chanan Singh Joe H.Chow Gang Mu Yuanzhang Sun Zhaoxi Liu Zhigang Li Yang Liu School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China School of Electrical Engineering&Computer Science Washington State UniversityPullmanWA 99164USA Department of Electrical and Computer Engineering Texas A&M UniversityCollege StationTX 77843USA Department of Electrical Computer and Systems EngineeringRensselaer Polytechnic Institute(RPI)TroyNYUSA Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin 132012China School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China

Power systems are moving toward a low-carbon or carbon-neutral future where high penetration of renewables is *** conventional fossil-fueled synchronous generators in the transmission network being replaced by renewable energy generation which is highly distributed across the entire grid,new challenges are emerging to the control and stability of large-scale power *** analysis and control methods are needed for power systems to cope with the ongoing *** the CSEE JPES forum,six leading experts were invited to deliver keynote speeches,and the participating researchers and professionals had extensive exchanges and discussions on the control and stability of power ***,potential changes and challenges of power systems with high penetration of renewable energy generation were introduced and explained,and advanced control methods were proposed and analyzed for the transient stability enhancement of power grids.

关键词： Distributed energy resources high converter penetration power system control renewable energy generation stability control transient stability

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Incorporating Lasso Regression to Physics-Informed Neural Network for Inverse PDE Problem

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computer Modeling in engineering & Sciences 2024年第10期141卷 385-399页

作者： Meng Ma Liu Fu Xu Guo Zhi Zhai National Key Lab of Aerospace Power System and Plasma Technology Xi’an Jiaotong UniversityXi’an710049China School of Mechanical Engineering Xi’an Jiaotong UniversityXi’an710049China Department of Electrical and Computer Engineering University of Massachusetts LowellLowellMA 01854USA

Partial Differential Equation(PDE)is among the most fundamental tools employed to model dynamic *** PDE modeling methods are typically derived from established knowledge and known phenomena,which are time-consuming and ***,discovering governing PDEs from collected actual data via Physics Informed Neural Networks(PINNs)provides a more efficient way to analyze fresh dynamic systems and establish *** study proposes Sequentially Threshold Least Squares-Lasso(STLasso),a module constructed by incorporating Lasso regression into the Sequentially Threshold Least Squares(STLS)algorithm,which can complete sparse regression of PDE coefficients with the constraints of l0 *** further introduces PINN-STLasso,a physics informed neural network combined with Lasso sparse regression,able to find underlying PDEs from data with reduced data requirements and better *** addition,this research conducts experiments on canonical inverse PDE problems and compares the results to several recent *** results demonstrated that the proposed PINN-STLasso outperforms other methods,achieving lower error rates even with less data.

关键词： Physics-informed neural network inverse partial differential equation Lasso regression scientific machine learning

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