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Facile assembly of flexible,stretchable and attachable symmetric microsupercapacitors with wide working voltage windows and favorable durability

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Microsystems & Nanoengineering 2024年第4期10卷 297-304页

作者： Xiangguang Han Xiaoyu Wu Libo Zhao Min Li Chen Jia Zhikang Li Jiaqi Xie Guoxi Luo Ping Yang Rabah Boukherroub Yurdanur Türker Mert UmutÖzkaynak Koray Bahadır Dönmez State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement TechnologiesXi’an Jiaotong University(Yantai)Research Institute for Intelligent Sensing Technology and SystemXi’an Jiaotong UniversityXi’an 710049China School of Instrument Science and Technology Xi’an Jiaotong UniversityXi’an 710049China Shandong Laboratory of Advanced Materials and Green Manufacturing at Yantai Yantai 264000China School of Mechanical Engineering Xi’an Jiaotong UniversityXi’anShaanxi 710049China Chongqing Key Laboratory of Micro-Nano Systems and Intelligent Sensing Chongqing Academician WorkstationChongqing 2011 Collaborative Innovation Center of Micro/Nano Sensing and Intelligent Ecological Internet of ThingsChongqing Technology and Business UniversityNan’an DistrictChongqing 400067China Univ.Lille CNRSUniv.Polytechnique Hauts-de-FranceUMR 8520-IEMNF-59000 LilleFrance Sabanci University Nanotechnology Research and Application Center(SUNUM) IstanbulTurkey Department of Materials Science and Engineering Istanbul Technical UniversityIstanbulTurkey

With the increasing development of intelligent robots and wearable electronics,the demand for high-performance flexible energy storage devices is drastically *** this study,flexible symmetric microsupercapacitors(MSCs)that could operate in a wide working voltage window were developed by combining laser-direct-writing graphene(LG)electrodes with a phosphoric acid-nonionic surfactant liquid crystal(PA-NI LC)gel *** increase the flexibility and enhance the conformal ability of the MSC devices to anisotropic surfaces,after the interdigitated LG formed on the polyimide(PI)film surface,the devices were further transferred onto a flexible,stretchable and transparent polydimethylsiloxane(PDMS)substrate;this substrate displayed favorable flexibility and mechanical characteristics in the bending ***,the electrochemical performances of the symmetric MSCs with various electrode widths(300,400,500 and 600μm)were *** findings revealed that symmetric MSC devices could operate in a large voltage range(0–1.5 V);additionally,the device with a 300μm electrode width(MSC-300)exhibited the largest areal capacitance of 2.3 mF cm^(−2)at 0.07 mA cm^(−2)and an areal(volumetric)energy density of 0.72μWh cm−2(0.36 mWh cm^(−3))at 55.07μWcm−2(27.54mWcm−3),along with favorable mechanical and cycling *** charging for~20 s,two MSC-300 devices connected in series could supply energy to a calculator to operate for~130 s,showing its practical application potential as an energy storage ***,the device displayed favorable reversibility,stability and *** 12 months of aging in air at room temperature,its electrochemical performance was not altered,and after charging-discharging measurements for 5000 cycles at 0.07 mA cm^(−2),~93.6%of the areal capacitance was still retained;these results demonstrated its practical long-term application potential as an energy storage device.

关键词： cycling durability electrode

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Dynamic Evaluation Strategies for Multiple Aircrafts Formation Using Collision and Matching Probabilities

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IEEE/CAA Journal of Automatica Sinica 2021年第4期8卷 890-904页

作者： Hongbo Zhao Yongming Wen Sentang Wu Jia Deng Deng are with the Beihang University Beijing 100191China Science and Technology on Information Systems Engineering Laboratory Beijing Institute of Control&Electronics TechnologyBeijing 100038China

Configuration evaluation is a key technology to be considered in the design of multiple aircrafts formation(MAF)configurations with high dynamic properties in engineering *** paper deduces the relationship between relative velocity,dynamic safety distance and dynamic adjacent distance of formation members,then divides the formation states into collision-state and ***,probability models are constructed based on the binary normal distribution of relative distance and relative ***,configuration evaluation strategies are studied by quantitatively analyzing the denseness and the basic capabilities according to the MAF collision-state probability and the MAF matching-state probability,*** scale of MAF is grouped into 5 levels,and previous lattice-type structures are extended into four degrees by taking the relative velocities into account to instruct the configuration design under complex task ***,hardware-in-loop(HIL)simulation and outfield flight test results are presented to verify the feasibility of these evaluation strategies.

关键词： Collision-state probability dynamic configuration evaluation matching-state probability multiple aircrafts formation

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Perfect Vortex Beam Based Metasurface in Microwave Band 6

Perfect Vortex Beam Based Metasurface in Microwave Band

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6th IEEE International Conference on Electronic information and Communication technology, ICEICT 2023

作者： Wang, Xuehan Deng, Li Chen, Weiping Xiao, Long Chen, Lijie Yao, Gengjiang Chen, Jiawei Feng, Botao School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China China Ship Development and Design Center Science and Technology on Electromagnetic Compatibility Laboratory Wuhan China College of Electronics and Information Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9798350399059

A perfect vortex beam is a beam with a constant radius regardless of its topological charge, and it may find significant applications in wireless communications systems, radar systems, and imaging systems. This paper introduces a novel perfect vortex beam operating in the microwave band, offering independent modulation of electromagnetic waves in X-polarization. This approach offers advantages such as miniaturization and reduced weight compared to conventional methods. © 2023 IEEE.

关键词： Vortex flow

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Low-light image enhancement based on Transformer and CNN architecture

Low-light image enhancement based on Transformer and CNN arc...

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第35届中国控制与决策会议

作者： Keyuan Chen Bin Chen Shiqian Wu Institute of Robotics and Intelligent System School of Information Science and Engineering Wuhan University of Science and Technology

Affected by low photon counts and noise,images captured in low-light environments commonly have low signalto-noise ratios,details losing,low contrast and other ***-light image enhancement which restores clear images from low-light images with unsatisfactory quality is *** this paper,we propose a strong baseline model based on transformer and CNN architecture for low light image enhancement(TrCLLE).In TrCLLE,the advantages of transformer in effectively modeling long-distance dependence and convolutional neural network in modeling local features through inductive bias are *** consists of three parts:shallow feature extraction module,deep feature extraction module and high-quality image reconstruction *** last,the factors affecting performance are analyzed in detail and the experimental results demonstrate that the proposed method achieves enhanced images with higher quality compared to other popular approaches.

关键词： transformer self-attention mechanism convolutional neural network low-light image enhancement

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Identifiability Analysis of Load Model Parameters by Estimating Confidential Intervals

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CSEE Journal of Power and Energy systems 2023年第5期9卷 1666-1675页

作者： Xinran Zhang Chao Lu Ying Wang Qiantu Ruan Hongbo Ye Weihong Wang the School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China. the State Key Laboratory of Control and Simulation of Power System and Generation Equipment Tsinghua UniversityBeijing 100084China School of Technology Beijing Forestry UniversityBeijing 100083China the State Grid Shanghai Electric Power Company Shanghai 200122China

The identification of load model parameters from practical measurement data has become an essential method to build load models for power system simulation,analysis and *** practical situations,the accuracy of the load model parameters identification results is impacted by data quality and measurement accuracy,which leads to the problem of *** this paper,an identifiability analysis methodology of load model parameters,by estimating the confidential intervals(CIs)of the parameters,is *** load model structure and the combined optimization and regression method to identify the parameters are first ***,the definition and analysis method of identifiability are *** CIs of the parameters are estimated through the profile likelihood method,based on which a practical identifiability index(PII)is defined to quantitatively evaluate ***,the effectiveness of the proposed analysis approach is validated by the case study results in a practical provincial power *** results show that the impact of various disturbance magnitudes,measurement errors and data length can all be reflected by the proposed ***,the proposed PII can provide guidance in data length selection in practical load model identification situations.

关键词： Confidential interval Load modeling parameter estimation practical identifiability

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Cancer classification with data augmentation based on generative adversarial networks

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Frontiers of Computer science 2022年第2期16卷 69-79页

作者： Kaimin WEI Tianqi LI Feiran HUANG Jinpeng CHEN Zefan HE College of Information Science and Technology Jinan UniversityGuangzhou 510632China Guangdong Key Laboratory of Data Security and Privacy Protection Guangzhou 510632China School of Software Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China

Accurate diagnosis is a significant step in cancer *** learning can support doctors in prognosis decision-making,and its performance is always weakened by the high dimension and small quantity of genetic ***,deep learning can effectively process the high dimensional data with ***,the problem of inadequate data remains unsolved and has lowered the performance of deep *** end it,we propose a generative adversarial model that uses non target cancer data to help target generator *** use the reconstruction loss to further stabilize model training and improve the quality of generated *** also present a cancer classification model to optimize classification *** results prove that mean absolute error of cancer gene made by our model is 19.3%lower than DC-GAN,and the classification accuracy rate of our produced data is higher than the data created by *** for the classification model,the classification accuracy of our model reaches 92.6%,which is 7.6%higher than the model without any generated data.

关键词： data mining cancer data analysis deep learning generative adversarial networks

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Narrow-bandgap materials for optoelectronics applications

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Frontiers of physics 2022年第1期17卷 89-121页

作者： Xiao-Hui Li Yi-Xuan Guo Yujie Ren Jia-Jun Peng Ji-Shu Liu Cong Wang Han Zhang School of Physics&Information Technology Shaanxi Normal UniversityXi’an710119China Shenzhen Key Laboratory of Two-Dimensional Materials and Devices/Shenzhen Engineering Laboratory of Phosphorene and Optoelectronics Collaborative Innovation Center for Optoelectronic Science and TechnologyKey Laboratory of Optoelectronic Devices and Systems of Ministry of Education and GuangdongShenzhen518060China

Narrow-bandgap materials possess the intriguing optical-electric properties and unique structures,which can be widely applied in the field of photonics,energy optoelectronic sensing and biomedicine,***,the researches on nonlinear optical properties of narrow-bandgap materials have attracted extensive attention *** this paper,we review the progress of narrow-bandgap materials from many aspects,such as background,nonlinear optical properties,energy band structure,methods of preparation,and *** materials have obvious nonlinear optical characteristics and the interaction with the short pulse laser excitation shows the extremely strong nonlinear absorption characteristics,which leads to the optical limiting or saturable absorption related to Pauli blocking and excited state ***,some of these novel narrow-bandgap materials have been utilized for the generation of ultrashort pulse that covers the range from the visible to mid-infrared wavelength ***,the study on these materials paves a new way for the advancement of optoelctronics devices.

关键词： narrow-bandgap materials saturable absorber ultrafast lasers modulator photodetectors

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Toward Comprehensive Semantic Prompt for Region Contrastive Learning Underwater Image Enhancement

Toward Comprehensive Semantic Prompt for Region Contrastive ...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Xiao Wang Yongsheng Fu Wei Wang Wei Liu School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Underwater image enhancement (UIE) focuses on mitigating image quality degradation due to light absorption and scattering. However, most existing methods enhance images via a global and uniform manner, neglecting the inherent semantic information in different regions, which may cause the network to easily deviate from the region’s original color. Moreover, these methods typically rely on clear images to guide network convergence, a process constrained by the limited availability of real-world datasets, making it extremely challenging to train enhancement models for various degradations. To address these challenges, this paper introduces a semantic guidance and region contrastive constraints network (SRCNet). Initially, we propose a semantic-aware RWKV (Receptance Weighted Key Value) block and a semantic prompt regularization module. These components leverage intra-target semantic correlations to preserve image details and colors within a global perceptual framework, while employing focal loss to emphasize the restoration of severely degraded regions. Subsequently, we introduce a region contrastive learning method that effectively utilizes negative samples to precisely capture features sensitive to degradation factors, thereby fostering robust feature distributions. Finally, experimental results demonstrate that our method outperforms existing state-of-the-art (SOTA) approaches.

关键词： Degradation Visualization Image color analysis Semantics Signal processing algorithms Contrastive learning Speech enhancement Signal processing Image restoration Image enhancement

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Poster: Towards Accurate and Fast Federated Learning in End-Edge-Cloud Orchestrated Networks 43

Poster: Towards Accurate and Fast Federated Learning in End-...

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43rd IEEE International Conference on Distributed Computing systems, ICDCS 2023

作者： Li, Mingze Sun, Peng Zhou, Huan Zhao, Liang Liu, Xuxun Leung, Victor C. M. College of Computer and Information Technology China Three Gorges University Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering Yichang China College of Computer Science and Electronic Engineering Hunan University Changsha China College of Electronic and Information Engineering South China University of Technology Guangzhou China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9798350339864

This work proposes a novel three-layer federated learning (FL) framework with parameter selection and pre-synchronization (PSPFL) to achieve fast and accurate model training. The basic idea of PSPFL is that clients select partial model parameters for transmission and then base stations aggregate them cooperatively (i.e., pre-synchronization) and send the aggregated results to the server for global model update periodically. However, there is an intrinsic trade-off between parameter transmission overhead and model training loss. To strike a desirable balance between them, we investigate the optimal parameter pre-synchronization round and local training round under PSPFL. Specifically, we propose a Deep Q-Network (DQN)-based method to obtain the local training round and parameter pre-synchronization round. Finally, extensive experiments are conducted to evaluate the performance of the proposed method on commonly used datasets. The results show that the proposed method can reduce the sum of FL completion time and training loss by an average of 8.17%-18.82% compared to benchmarks. © 2023 IEEE.

关键词： Synchronization

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A Cross Q-Learning Assisted Resource Allocation for User-Centric Optical Wireless Communication Networks

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green Communications and Networking 2025年

作者： Feng, Simeng Li, Nian Liu, Kai Li, Baolong Dong, Chao Wu, Qihui Nanjing University of Aeronautics and Astronautics Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Nanjing211106 China Nanjing University of Information Science and Technology Nanjing210044 China

The user-centric (UC) association in optical wireless communication (OWC) forms amorphous cells (A-Cells) by considering the dynamic distribution and load demand of user equipments (UEs). This philosophy offers advantages over the conventional network-centric (NC) association that purely relies on a pre-defined and fixed network configuration, in terms of alleviating undesired inter-cell interference (ICI) and achieving superior system performance. However, constructing the optimal A-Cells for a given OWC network, including determining the appropriate number of A-Cells associated to their contained UEs, is deeply integrated with the UEs’ distribution and transmission conditions. To address the intractable issue, in this paper, we conceive an adaptive UC-OWC network that relies on a feedback-guided iterative framework, which is capable of jointly optimizing A-Cells formation, modulation-mode assignment and power allocation strategies. For the sake of attaining the optimized throughput of this adaptive network, we initialize the UC association by the designed k-means based genetic algorithm (KGA), which can then be iteratively adjusted based on the throughput feedback obtained via our proposed multi-user cross Q-learning (MUCQ) resource allocation algorithm. Simulation results indicate that, compared to conventional counterparts, our adaptive UC-OWC network is able to significantly improve throughput performance and reduce outage probability. © 2025 IEEE. All rights reserved.

关键词： Optical communication

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