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Wireless Interference Classification with Low Complexity Multi-Branch Networks

China Communications 2023年第4期20卷 382-394页

作者： Song Ma Yufan Cheng Ying Mou Pengyu Wang Qihang Peng Jun Wang National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of ChinaChengdu 611731China School of Information and Communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

In non-cooperative communication systems,wireless interference classification(WIC)is one of the most essential ***,deep learning(DL)based WIC methods have been ***,conventional DL-based WIC methods have high computational complexity and unsatisfactory accuracy,especially when the interference-tonoise ratio(INR)is *** this end,we propose three effective ***,we introduce multibranch convolutional neural networks(CNNs)for interference *** multi-branch CNN is constructed by repeating a layer that aggregates several transformations with the same topology,and it notably improves the recognition ability for *** design avoids the carefully crafted selection of each ***,multi-branch CNNs are computationally expensive and *** this end,we further propose Low complexity multibranch networks(LCMN),which are mathematically equivalent to multi-branch CNNs but maintain low computing costs and efficient ***,we present novel loss function,which encourages networks to have consistent prediction probabilities for samples with high visual similarities,resulting in increasing recognition accuracy of *** results demonstrate the proposed methods consistently boost the classification performance of WIC without substantially increasing computational overhead compared to traditional DL-based methods.

关键词： electromagnetic interference wireless interference identification deep learning multi-branch architectures

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Interfacial engineering for efficient and stable two-terminal perovskite-based tandem solar cells

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Rare Metals 2024年第11期43卷 5573-5624页

作者： Ying Li Di-Sheng Yao Fei Long Guo-Zhen Zhang Feng Yu Guangxi Key Laboratory of Optical and Electronic Material and Devices School of Materials Science and EngineeringGuilin University of TechnologyGuilin 541004China Guangxi Key Laboratory of Optical and Electronic Material and Devices School of Materials Science and EngineeringCollaborative Innovation Center for Exploration of Nonferrous Metal Deposits and Efficient Utilization of ResourcesGuilin University of TechnologyGuilin 541004China School of Chemistry and Materials Science Nanjing University of Information Science and TechnologyNanjing 210044China

Two-terminal(2T)tandem solar cells(TSCs)are optically and electrically connected by two subcells with complementary bandgaps,which are designed to overcome the Shockley-Queisser(S-Q)limit of singlejunction solar ***-inorganic hybrid perovskites are ideal light-absorbing materials for 2T TSCs due to their tunable bandgaps,low-temperature solution-based processing,and excellent light absorption ***,2T perovskite-based TSCs(PTSCs)have aroused widespread interest among the photovoltaic *** present,the key to obtaining efficient and stable 2T PTSCs is establishing efficient interfaces and layers with good photoelectric properties and high compatibility of *** particular,interfacial engineering based on effective recombination layers(RCLs)and buffers has a prominent effect on achieving enhanced power conversion efficiency(PCE)of 2T PTSCs with improved operational *** this article,the current frontier issues of 2T PTSCs including different device structures and properties are reviewed in detail to analyze their merits,demerits and solutions to overcome ***,the component engineering,interface engineering and theoretical PCE analysis for designing 2T PTSCs proposed by material simulations are ***,the scalability of interfacial passivation from single-junction perovskite solar cells to 2T PTSCs is evaluated,and the function mechanisms of RCLs and buffers are also summarized and analyzed ***,the challenges faced by 2T PTSCs are pointed out,and their developme nt directions are *** article aims to provide viable guidance for realizing practical manufacturing technologies for the commercialization of 2T PTSCs.

关键词： Two-terminal tandem solar cells Organic-inorganic perovskites Passivation interfaces Recombination layers and buffers Efficiency and stability

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ER‐Mapping: An extrinsic robust coloured mapping system using residual evaluation and selection

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IET Cyber-systems and Robotics 2024年第2期6卷 97-108页

作者： Changjian Jiang Zeyu Wan Ruilan Gao Yu Zhang State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhouChina Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province HangzhouChina

The colour-enhanced point cloud map is increasingly being employed in fields such as robotics,3D reconstruction and virtual *** authors propose ER-Mapping(Extrinsic Robust coloured Mapping system using residual evaluation and selection).ER-Mapping consists of two components:the simultaneous localisation and mapping(SLAM)subsystem and the colouring *** SLAM subsystem reconstructs the geometric structure,where it employs a dynamic threshold-based residual selection in LiDAR-inertial odometry to improve mapping *** the other hand,the col-ouring subsystem focuses on recovering texture information from input images and innovatively utilises 3D–2D feature selection and optimisation methods,eliminating the need for strict hardware time synchronisation and highly accurate extrinsic *** were conducted in both indoor and outdoor *** results demonstrate that our system can enhance accuracy,reduce computational costs and achieve extrinsic robustness.

关键词： robot vision sensor fusion simultaneous localisation and mapping(robots)

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Typhoon Wind Speed Retrieval from HY-2C Microwave Radiometer Based on LightGBM

Typhoon Wind Speed Retrieval from HY-2C Microwave Radiometer...

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2024 Photonics and Electromagnetics Research Symposium, PIERS 2024

作者： Dai, Xuchen Zhang, Biao Zhang, Yifan Zhang, Lanjie Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing100101 China Ministry of Education Beijing Information Science and Technology University Key Laboratory of Modern Measurement and Control Technology Beijing100101 China

ISBN: (纸本)9798350375909

In this paper, the sea surface wind speed (SSWS) retrieval accuracy for HaiYang-2C (HY-2C) passive microwave radiometer under the severe weather such as typhoon is evaluated. Based on the observation data of HY-2C, this study explores the influence of brightness temperature (TB) observed by microwave radiometer on sea surface wind speed retrieval under typhoon conditions. In the case of typhoon precipitation, the attenuation of the atmosphere to the high frequency channel is stronger, which makes the sea surface information observed by the microwave radiometer very weak. Therefore, we mainly select the TB of horizontal polarization and vertical polarization observation of 6.9GHz and 10.7GHz channels to carry out the study of typhoon wind speed retrieval. This paper constructs a matching data set based on the TB observed by HY-2C passive microwave radiometer, HY-2C L2B wind product and H*wind reanalysis wind field data in October and November 2020. The maximum differences of spatial and temporal were set as 25km and 30minutes, respectively. Then, the typhoon wind speed retrieval model based on LightGBM is established. We use the data of October 2020 to train the model and the data of November 2020 to test model performance. Comparing with the H*wind reanalysis wind field data, the bias and root-mean-square error of retrieved wind speed are 0.15m/s and 1.26m/s, respectively. In addition, the correlation coefficient is 0.90, indicating that the retrieved wind speed has a good consistency with H*wind data. © 2024 IEEE.

关键词： Hurricanes

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Fine-Grained Cross-Modal Fusion Based Refinement for Text-to-Image Synthesis

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Chinese Journal of Electronics 2023年第6期32卷 1329-1340页

作者： SUN Haoran WANG Yang LIU Haipeng QIAN Biao Department of Computer Science and Information Engineering Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data Ministry of EducationHefei University of Technology

Text-to-image synthesis refers to generating visual-realistic and semantically consistent images from given textual descriptions. Previous approaches generate an initial low-resolution image and then refine it to be high-resolution. Despite the remarkable progress, these methods are limited in fully utilizing the given texts and could generate text-mismatched images, especially when the text description is complex. We propose a novel finegrained text-image fusion based generative adversarial networks(FF-GAN), which consists of two modules: Finegrained text-image fusion block(FF-Block) and global semantic refinement(GSR). The proposed FF-Block integrates an attention block and several convolution layers to effectively fuse the fine-grained word-context features into the corresponding visual features, in which the text information is fully used to refine the initial image with more details. And the GSR is proposed to improve the global semantic consistency between linguistic and visual features during the refinement process. Extensive experiments on CUB-200 and COCO datasets demonstrate the superiority of FF-GAN over other state-of-the-art approaches in generating images with semantic consistency to the given texts.

关键词： Visualization Fuses Convolution Semantics Linguistics Benchmark testing Generative adversarial networks

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Remote entangling gate between a quantum dot spin and a transmon qubit mediated by microwave photons

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Chinese Physics B 2024年第2期33卷 52-59页

作者：朱行宇朱乐天涂涛李传锋 Key Laboratory of Quantum Information Chinese Academy of SciencesUniversity of Science and Technology of ChinaHefei 230026China School of Mechanical and Electronic Engineering Suzhou UniversitySuzhou 234000China Hefei National Laboratory University of Science and Technology of ChinaChinese Academy of SciencesHefei 230088China

Spin qubits and superconducting qubits are promising candidates for realizing solid-state quantum information *** a hybrid architecture that combines the advantages of different qubits on the same chip is a highly desirable but challenging *** we propose a hybrid architecture that utilizes a high-impedance SQUID array resonator as a quantum bus,thereby coherently coupling different solid-state *** employ a resonant exchange spin qubit hosted in a triple quantum dot and a superconducting transmon *** this hybrid system is highly tunable,it can operate in a dispersive regime,where the interaction between the different qubits is mediated by virtual *** utilizing such interactions,entangling gate operations between different qubits can be realized in a short time of 30 ns with a fidelity of up to 96.5%under realistic parameter *** utilizing this interaction,remote entangled state between different qubits can be prepared and is robust to perturbations of various *** results pave the way for exploring efficient fault-tolerant quantum computation on hybrid quantum architecture platforms.

关键词： hybrid quantum architectures circuit quantum electrodynamics entangling gate

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High-Speed PAM8 Silicon Photonics IM/DD System with Artificial Neural Network Equalization 13

High-Speed PAM8 Silicon Photonics IM/DD System with Artifici...

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Optoelectronic Devices and Integration XIII 2024

作者： Lu, Junde Sun, Yu Qin, Jun Tan, Junxiong Wang, Qian Li, Yueqin Sun, Jian Li, Zhensong Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing100192 China Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument Beijing Information Science and Technology University Beijing100192 China

ISBN: (纸本)9781510682009

The intensity modulation direct detection (IM/DD) system based on silicon photonic devices stands out as a leading contender for the next generation of short-reach optical communication due to its cost-effectiveness, low power consumption, and compact physical footprint. Nonetheless, its direct representation of digital information through amplitude variations renders them acutely susceptible to transmission impairments. To improve the signal quality at the receiver, digital signal processing (DSP) based equalization plays a pivotal role due to its programmability, flexibility and stability. Among different kinds of equalization methods, neural network (NN)-based equalization algorithms have attracted considerable attention, surpassing traditional algorithms such as feed-forward equalization (FFE), decision feedback equalization (DFE) and Volterra series-based nonlinear equalization (VNLE) et al. This increased attention is attributed to their robust capability for modeling both linear and nonlinear systems. In this paper, by employing a novel NN-based equalization with eight saturation regions activation function, we successfully transmit a 60 GBaud 8-ary pulse amplitude modulation (PAM8) signal with the bit error rate (BER) below high-definition forward error correction (HD-FEC) threshold of 3.8×10-3 and a 70 GBaud PAM8 signal with BER below soft-decision forward error correction (SD-FEC) threshold 2×10-2 using a 4-layer network architecture. Compared to the traditional activation function such as sigmoid and tanh, 1∼3 orders of magnitude of BER can be decreased. The results show that the proposed innovative NNbased equalization has the potential to significantly enhance the performance of the next generation silicon photonics based short-range optical communication systems. © 2024 SPIE. All rights reserved.

关键词： Silicon photonics

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MCFF-Net: Multi-Scale Contextual Feature Fusion Network for Polyp Segmentation

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Journal of Shanghai Jiaotong University (science) 2025年 1-13页

作者： Ma, Lei Yan, Jiangkai Shao, Dangguo Li, Jingtao Wang, Jiawei Yan, Yukun Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Yunnan Provincial Key Laboratory of Artificial Intelligence Kunming650500 China

In clinical practice, technologies for automatically segmenting polyps might greatly improve the speed and accuracy of medical diagnosis, significantly reducing the chances of patients developing colorectal cancer. Nevertheless, the segmentation of polyps presents a considerable challenge due to their low contrast, presence of occlusion, and intricate background disturbances. In this paper, we propose an innovative approach for segmenting polyps, called multi-scale contextual feature fusion network for polyp segmentation (MCFF-Net). Specifically, MCFF-Net includes three modules: feature enhancement module (FEM), global-local feature fusion module (GLFF), and cross-scale feature fusion module (CFFM). Among them, FEM is used to improve the features at each scale. Building on this, the CFFM enables comprehensive interaction among the information across various scales, enhancing the diversity of the feature scales extracted. Moreover, the GLFF fuses global-local features to generate a rough object localization map. This map further modulates the fusion features from the CFFM, facilitating more precise segmentation. On five publicly available datasets, our approach not only segments various polyp types but also surpasses existing methods in terms of accuracy and generalizability. © Shanghai Jiao Tong University 2024.

关键词： Diseases

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Sequence structure controllable polymerization-induced self-assembly

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science China Chemistry 2024年第1期67卷 390-397页

作者： Zi-Xuan Chang Ren-Man Zhu Chun-Yan Hong Wen-Jian Zhang Department of Polymer Science and Engineering University of Science and Technology of ChinaHefei 230026China Institute of Physical Science and Information Technology Anhui UniversityHefei 230601China Key Laboratory of Environment-Friendly Polymeric Materials of Anhui Province Anhui UniversityHefei 230601China

Polymerization-induced self-assembly(PISA)combines synthesis and self-assembly of artificial polymers in one-pot,which brings us one step closer to emulating ***,the reported PISA formulations primarily focus on developing nano-objects with new chemical compositions and rarely on structural regulation of polymers with specific ***,sequence structure controllable polymerization-induced self-assembly(SCPISA)is reported by using 7-(2-methacryloyloxyethoxy)-4-methylcoumarin(CMA)as a *** the copolymerization of 2-hydroxyethyl methacrylate(HEMA)and CMA,controlled incorporation of CMA units into the polymer chains can be realized by programmable light/heat ***-based P(HEMA-co-CMA)copolymers with the same composition but different sequence structures generate a range of ***,the morphologies of the resultant nano-objects can also be controlled by regulating the feed molar ratio of CMA and HEMA,which is similar to the conventional PISA,but the synthesis procedure is obviously simplified in *** versatility of the methodology is further demonstrated by the fabrication of different functional nano-objects with sequence structure-dependent morphologies in SCPISA systems with different functional monomers.

关键词： polymerization-induced self-assembly sequence-controlled polymers PET-RAFT polymerization

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Transfer learning enables the rapid design of single crystal superalloys with superior creep resistances at ultrahigh temperature

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npj Computational Materials 2024年第1期10卷 1718-1732页

作者： Fan Yang Wenyue Zhao Yi Ru Siyuan Lin Jiapeng Huang Boxuan Du Yanling Pei Shusuo Li Shengkai Gong Huibin Xu School of Materials Science and Engineering Beihang UniversityBeijing 100191China Key Laboratory of Aerospace Materials and Performance(Ministry of Education) Key Laboratory of High-temperature Structural Materials&Coating Technology(Ministry of Industry and Information Technology)BeijingChina Tianmushan Laboratory Yuhang District311115 HangzhouZhejiang ProvinceChina

Accelerating the design of Ni-based single crystal(SX)superalloys with superior creep resistance at ultrahigh temperatures is a desirable goal but extremely challenging *** the present work,a deep transfer learning neural network with physical constraints for creep rupture life prediction at ultrahigh temperatures is *** learning enables deep learning model breaks through the generalization performance barrier in the extrapolation space of ultrahigh temperature creep properties in the case of a very small dataset,which is the key to achieving the above design goal.

关键词： creep resistance ultrahigh

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