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8th International Conference on Computer science and Application engineering, CSAE 2024

作者： Hongxing, Hao Ronghuan, Yu Jing, Guo Huaquan, Hu Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Huairou Beijing China

ISBN: (纸本)9798400718090

The Autonomous and controllable of the spacecraft component is of great importance for the development of our space industry. The key step of the spacecraft component is the production. Many researchers focus on the estimation of the autonomous and controllable of the spacecraft component production. This paper model the evaluation method including the construction of the evaluation index system and the estimation method. The proposed estimation method is based on the fuzzy model to synthesize the qualitative, quantitative indicators and the according weights. Compared to mapping the qualitative value to a fixed number, the proposed method avoids the effect of the subjectivity. The experimental results show that the proposed method tend to think highly of the quantitative values when the qualitative values are not very too much so as to avoid the effect of the subjectivity for the qualitative indicators in the evaluation. © 2024 Copyright held by the owner/author(s).

关键词： Aerospace industry

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Image reconstruction based on Graph structure for MRI-guided diffuse optical tomography 17

Image reconstruction based on Graph structure for MRI-guided...

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17th International Conference on Photonics and Imaging in Biology and Medicine, PIBM 2024

作者： Zou, Peiwen Wei, Chengpu Hu, Ting Li, Zhe Sun, Zhonghua Jia, Kebin Feng, Jinchao Beijing Key Laboratory of Computational Intelligence and Intelligent System School of Information Science and Technology Beijing University of Technology Beijing100124 China Beijing Laboratory of Advanced Information Networks Beijing100124 China

ISBN: (数字)9781510688070

ISBN: (纸本)9781510688063

Diffuse optical tomography (DOT) is a non-invasive, label-free imaging technique widely used in applications such as breast cancer diagnosis and brain imaging. It allows for the quantitative measurement of tissue functional parameters, including the concentrations of oxyhemoglobin, deoxyhemoglobin, and water. However, the quality of reconstructed images is poor due to light scattering. To address this challenge, one effective strategy is to incorporate anatomical information from high-resolution imaging to guide DOT reconstruction. In this study, a new approach (GRI) is developed to leverage MRI images based on graph structure for DOT reconstruction. And its feasibility and effectiveness were evaluated with numerical simulations. The results indicate that GRI significantly improves the structural similarity index (SSIM) of reconstructed total hemoglobin (HbT) images, outperforming conventional Tikhonov regularization and direct regularization imaging (DRI) method by more than 63% and 82%, respectively. These findings are further supported by experiments using real patient data, which demonstrate GRI's potential in breast cancer diagnosis. © 2025 SPIE.

关键词： Optical tomography

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Two efficient beamforming methods for hybrid IRS-aided AF relay wireless networks

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science China(information sciences) 2025年第4期68卷 363-379页

作者： Xuehui WANG Qingbo LI Wen ZHU Feng SHU Mengxing HUANG Fuhui ZHOU Riqing CHEN Cunhua PAN Yongpeng WU Jiangzhou WANG School of Mathematics and Statistics Hainan Normal University Key Laboratory of Data Science and Smart Education Ministry of Education Hainan Normal University School of Information and Communication Engineering Hainan University Collaborative Innovation Center of Information Technology Hainan University School of Electronic and Optical Engineering Nanjing University of Science and Technology College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Digital Fujian Institute of Big Data for Agriculture Fujian Agriculture and Forestry University National Mobile Communications Research Laboratory Southeast University Shanghai Key Laboratory of Navigation and Location Based Services Shanghai Jiao Tong University School of Engineering University of Kent

Owing to its ability to mitigate the double-fading effect by amplifying the reflected signal, the active intelligent reflecting surface(IRS) has garnered significant attention. In this paper, an amplify-and-forward(AF) relay network assisted by a hybrid IRS consisting of both passive and active units is developed. A signal-to-noise ratio(SNR) maximization problem is formulated, where the AF relay beamforming matrix and the hybrid IRS reflecting coefficient matrices for two-time slots need to be optimized. To address the SNR maximization problem, this paper proposes both a high-performance(HP) method and a low-complexity(LC) method. The HP method is based on the semidefinite relaxation and fractional programming(SDR-FP)algorithm, with rank-1 solutions obtained through Gaussian randomization. For the LC method, the amplification coefficient of each active IRS element is assumed to be equal. The SNR maximization problem is then addressed using the whitening filter,generalized power iteration, and generalized Rayleigh-Ritz(WF-GPI-GRR) approach. Simulation results show that compared with the benchmarks, such as the passive IRS-aided AF relay network, the proposed HP-SDR-FP and WF-GPI-GRR methods achieve significant rate improvements. In particular, the HP-SDR-FP and WF-GPI-GRR methods yield more than a 135.0%rate gain when the transmit power Ps of the source is 10 dBm. Furthermore, the proposed HP-SDR-FP method outperforms the WF-GPI-GRR method in terms of rate performance.

关键词： double-fading intelligent reflecting surface active elements passive elements hybrid IRS AF relay

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BEDiff: denoising diffusion probabilistic models for building extraction

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Optoelectronics Letters 2025年第5期21卷 298-305页

作者： LEI Yanjing WANG Yuan CHAN Sixian HU Jie ZHOU Xiaolong ZHANG Hongkai College of Computer Science and Technology Zhejiang University of Technology Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering College of Computer and Information China Three Gorges University Key Laboratory of Intelligent Informatics for Safety & Emergency of Zhejiang Province Wenzhou University College of Electrical and Information Engineering Quzhou University School of Electronic and Information Engineering Anhui Jianzhu University

Accurately identifying building distribution from remote sensing images with complex background information is challenging. The emergence of diffusion models has prompted the innovative idea of employing the reverse denoising process to distill building distribution from these complex backgrounds. Building on this concept, we propose a novel framework, building extraction diffusion model(BEDiff), which meticulously refines the extraction of building footprints from remote sensing images in a stepwise fashion. Our approach begins with the design of booster guidance, a mechanism that extracts structural and semantic features from remote sensing images to serve as priors, thereby providing targeted guidance for the diffusion process. Additionally, we introduce a cross-feature fusion module(CFM) that bridges the semantic gap between different types of features, facilitating the integration of the attributes extracted by booster guidance into the diffusion process more effectively. Our proposed BEDiff marks the first application of diffusion models to the task of building extraction. Empirical evidence from extensive experiments on the Beijing building dataset demonstrates the superior performance of BEDiff, affirming its effectiveness and potential for enhancing the accuracy of building extraction in complex urban landscapes.

关键词： A

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Plasmonic nanolaser with tunable emitting wavelength near 1 µm

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Optics Letters 2025年第10期50卷 3305-3308页

作者： Wang, Yuhua Lu, Shudi Ma, Jingteng Lin, Runkang Wang, Peiling Xu, Yipeng Yue, Shizhong Wang, Zhijie Qu, Shengchun Huang, Le Liu, Kong Dong, Huafeng Guangdong Provincial Key Laboratory of Sensing Physics and System Integration Applications School of Physics and Optoelectronic Engineering Guangdong University of Technology Guangzhou510006 China Laboratory of Solid-State Optoelectronics Information Technology Beijing Key Laboratory of Low Dimensional Semiconductor Materials and Devices Institute of Semiconductors Chinese Academy of Sciences Beijing100083 China College of Physical Science and Technology Hebei Normal University of Science & Technology Qinhuangdao066004 China

Surface plasmon polaritons (SPPs) can produce a confined electromagnetic field near the metal–dielectric interface, allowing energy to be compressed into a scale smaller than the optical diffraction limit. The characteristic enables the fabrication of sub-wavelength-sized, ultra-low-threshold, ultrafast, specific polarization, room-temperature lasing nanolasers, which is especially meaningful for the lasers emitting long wavelength light. In this work, we developed a Cs0.1MA0.9SnI3 perovskite plasmonic laser based on a metal–insulator–semiconductor (MIS) structure, demonstrating a low threshold of 281 µJ cm−2, a tunable emitting wavelength from 973 to 1023 nm, strong mode confinement at the cutoff height of 90 nm, and a rapid response lifetime of 29.43 ps. Our study represents the first, to the best of our knowledge, theoretical design and experimental production of perovskite plasmonic nanolaser with a tunable emitting wavelength near 1 µm, filling a significant research gap and paving the way for the application of perovskite nanolasers in optoelectronic integration and information technology. © 2025 Optica Publishing Group. All rights are reserved.

关键词： Surface plasmon resonance

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Differential-geometry-based multi-dimensional joint position-velocity estimation using Crab pulsar profile distortion

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Chinese Journal of Aeronautics 2025年第1期38卷 551-567页

作者： Jin LIU Huanzi ZHANG Xiaolin NING Xin MA School of Electronic Information Wuhan University of Science and TechnologyWuhan 430081China School of Instrumentation and Optoelectronic Engineering Beihang UniversityBeijing 100191China Hefei National Laboratory Hefei 230088China

The traditional orbit determination method based on pulsar profile distortion can determine the six elements of the ***,the estimation accuracies of these methods are limited and the computational load of a six-dimensional search is *** solve this problem,the differential-geometry-based Multi-dimensional Joint Position-Velocity Estimation(MJPVE)using Crab pulsar profile distortion is proposed in this ***,through theoretical analysis,it is found that the pulsar profile distortion caused by the initial state error in some joint positionvelocity directions is very *** other words,the accuracies of estimation in these directions are very ***,the search dimension can be reduced,which in turn greatly reduces the computational ***,we construct the chi-squared function of the pulsar profile with respect to the estimation error in joint position-velocity direction and use differential geometry to find the joint position-velocity directions corresponding to different degrees of ***,we utilize the grid search based on directory folding in these joint position-velocity directions corresponding to large degrees of distortion to obtain the joint position-velocity *** experimental results show that compared with the grouping bi-chi-squared inversion method,MJPVE has high precision and extensive navigation information.

关键词： Joint Position-Velocity Estimation Pulsars Profile Distortion Orbit Determination Differential Geometry

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Low dielectric loss in vanadium-based zircon ceramics via high-entropy strategy

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Journal of Advanced Ceramics 2025年第1期14卷 151-161页

作者： Yuheng Zhang Huaicheng Xiang Xiaoyu Wu Yang Zhou Ying Tang Liang Fang College of Physics and Electronic Information Engineering Guilin University of TechnologyGuilin 541004China Guangxi Universities Key Laboratory of Non-Ferrous Metal Oxide Electronic Functional Materials and Devices Guangxi Key Laboratory of Optical and Electronic Materials and DevicesCollege of Materials Science and EngineeringGuilin University of TechnologyGuilin 541004China

Zircon ceramics have potential applications in next-generation wireless communication because of their low permittivity and adjustable temperature coefficient at microwave ***,the vast challenge of realizing ultralow dielectric loss still ***,we propose a high-entropy strategy to enhance the bonding of the A-site dodecahedron in zircon and design(Nd_(0.2)Eu_(0.2)Y_(0.2)Ho_(0.2)Yb_(0.2))VO_(4) ceramics with a high quality factor(high Q×f,that is,low dielectric loss).The(Nd_(0.2)Eu_(0.2)Y_(0.2)Ho_(0.2)Yb_(0.2))VO_(4) high-entropy ceramics,which belong to the tetragonal zircon structure with the I4_(1)/amd space group,exhibit a low relative permittivity(ε_(r)=11.55),a negative temperature coefficient of resonant frequency(τ_(f)=−37.3 ppm/℃),and a high Q×f of 76,400 GHz(at 12.31 GHz).The high Q×f value can be attributed to the high chemical bond strength and structural ***,the relationship between the crystal structure and the microwave dielectric properties of(Nd_(0.2)Eu_(0.2)Y_(0.2)Ho_(0.2)Yb_(0.2))VO_(4) high-entropy ceramics was analyzed through high resolution transmission electron microscopy(HRTEM),Raman spectroscopy,far-infrared reflection spectroscopy,and chemical bond *** work provides an effective avenue for designing microwave dielectric materials with low loss to meet the demands of passive components.

关键词： high-entropy ceramics vanadium-based zircon microwave dielectric properties low dielectric loss chemical bond characteristics

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Integrating clinical knowledge and imaging for medical report generation

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Pattern Recognition Letters 2025年 195卷 59-65页

作者： Zhao, Meng Liu, Juncai Shen, Hongyu Yan, Bin Pei, Mingtao Wang, Yi College of Electrical Engineering and Automation Shandong University of Science and Technology China Beijing Laboratory of Intelligent Information Technology Beijing Institute of Technology China

Medical report generation is an important cross-modal task in the field of medicine, aiming to automatically generate professional and accurate reports for given medical images. Integrating clinical knowledge into the task of medical report generation can enhance the semantic accuracy of medical image feature descriptions and improves the interpretability and robustness of the model. In this paper, we propose to integrate clinical knowledge and image content to generate medical report. The clinical knowledge is presented by a clinical knowledge graph, where anatomical structures and observations are represented as nodes, and their relationships are represented as edges. We design a graph generation module to dynamically generate relevant knowledge graphs specific to each image, which can diversify the knowledge graph structures and expand the coverage of clinical knowledge to provide a more extensive range of clinical knowledge during report generation. Furthermore, we design a graph attention module to facilitate optimized feature representation within the clinical knowledge graph by incorporating message passing between nodes and edges. This fosters a more comprehensive understanding of the relationships and significance of clinical information. Experimental evaluations conducted on the IU X-Ray and MIMIC CXR datasets demonstrate the superiority of the proposed method in generating medical reports. The results highlight the potential of leveraging clinical knowledge for enhancing the precision and clinical relevance of the generated reports. © 2025 Elsevier B.V.

关键词： Clinical knowledge graph Graph attention Radiology reports generation

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Real-Time Event Recognition of Long-Distance Distributed Vibration Sensing With Knowledge Distillation and Hardware Acceleration

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IEEE Internet of Things Journal 2025年第11期12卷 17896-17905页

作者： Luo, Zhongyao Wu, Hao Ge, Zhao Tang, Ming Huazhong University of Science and Technology Wuhan National Laboratory for Optoelectronics Next Generation Internet Access National Engineering Laboratory Hubei Optics Valley Laboratory School of Optical and Electronic Information Wuhan430074 China

Fiber-optic sensing, especially distributed optical fiber vibration (DVS) sensing, is gaining importance in internet of things (IoT) applications, such as industrial safety monitoring and intrusion detection. Despite their wide application, existing post-processing methods that rely on deep learning models for event recognition in DVS systems face challenges with real-time processing of large sample data volumes, particularly in long-distance applications. To address this issue, we propose to use a four-layer convolutional neural network (CNN) as the student model with ResNet as the teacher model for knowledge distillation. Compared to the baseline CNN model, which achieves 83.41% accuracy on data from previously untrained environments, the distilled CNN improves accuracy significantly to 95.39%, demonstrating its superior generalizability and robustness. Additionally, we propose a novel hardware design based on field-programmable gate arrays (FPGA) to further accelerate model inference. This design replaces multiplication with binary shift operations and quantizes model weights, enabling high parallelism and low latency. Our implementation achieves an inference time of 0.083 ms for a spatial-temporal sample covering a 12.5 m fiber length and 0.256 s time frame. This performance enables real-time signal processing over approximately 38.55 km of fiber, about 2.14× the capability of an Nvidia GTX 4090 GPU. The proposed method greatly enhances the efficiency of vibration pattern recognition, promoting the use of DVS as a smart IoT system. The data and code are available at https://***/HUST-IOF/Efficient-DVS. © 2014 IEEE.

关键词： Multilayer neural networks

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DDT-Net:Deep Detail Tracking Network for Image Tampering Detection

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Computers, Materials & Continua 2025年第5期83卷 3451-3469页

作者： Jim Wong Zhaoxiang Zang Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges UniversityYichang443002China College of Computer and Information Technology ChinaThree Gorges UniversityYichang443002China Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650504China

In the field of image forensics,image tampering detection is a critical and challenging *** methods based on manually designed feature extraction typically focus on a specific type of tampering operation,which limits their effectiveness in complex scenarios involving multiple forms of *** deep learningbasedmethods offer the advantage of automatic feature learning,current approaches still require further improvements in terms of detection accuracy and computational *** address these challenges,this study applies the UNet 3+model to image tampering detection and proposes a hybrid framework,referred to as DDT-Net(Deep Detail Tracking Network),which integrates deep learning with traditional detection *** contrast to traditional additive methods,this approach innovatively applies amultiplicative fusion technique during downsampling,effectively combining the deep learning feature maps at each layer with those generated by the Bayar noise *** design enables noise residual features to guide the learning of semantic features more precisely and efficiently,thus facilitating comprehensive feature-level ***,by leveraging the complementary strengths of deep networks in capturing large-scale semantic manipulations and traditional algorithms’proficiency in detecting fine-grained local traces,the method significantly enhances the accuracy and robustness of tampered region *** with other approaches,the proposed method achieves an F1 score improvement exceeding 30% on the DEFACTO and DIS25k *** addition,it has been extensively validated on other datasets,including CASIA and *** results demonstrate that this method achieves outstanding performance across various types of image tampering detection tasks.

关键词： Image forensics image tampering detection image manipulation detection noise flow Bayar

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