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SSRN 2024年

作者： Wang, Jian Wu, Zuoxu Sun, Xiaoyu Tang, Zunqian Wang, Chong Yu, Fangyuan Zhao, Zirui Mao, Jun Zhang, Qian Cao, Feng School of Science Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System Harbin Institute of Technology Shenzhen518055 China School of Materials Science and Engineering Institute of Materials Genome & Big Data Harbin Institute of Technology Shenzhen518055 China State Key Laboratory of Advanced Welding and Joining China Fuzhou University China

With the rapid development of detection technology, there is an urgent need for multi-band compatible camouflage technology, particularly in the visible-infrared band. However, the conflicting requirements between camouflage across different bands and surface thermal management pose significant challenges in achieving synchronized control for multiple bands in diverse application environments and targets. Herein, we propose a spectrally selective emitter leveraging phase-change modulation of Ge2Sb2Te5, capable of achieving effective camouflage in both the visible band and two atmospheric windows over a wide temperature range. The designed emitters exhibit colorful appearances, compatible with various background environments, thereby ensuring the visible camouflage. Meanwhile, the emitters demonstrate low emissivity values of 0.1 in the MWIR band and 0.08 in the LWIR band, effectively reducing the infrared emission through atmospheric *** radiative temperatures of the optimized emitters in the MWIR and LWIR bands are reduced by 105 °C and 140 °C relative to the target surface (200 °C), respectively, providing excellent radiative suppression compared to similar studies. Remarkably, the designed emitter still demonstrates robust flexibility, making it suitable for a variety of targets with complex curved surfaces. This work paves the way for designing the flexible visible-infrared compatible camouflage coatings with integrated thermal management functionality. © 2024, The Authors. All rights reserved.

关键词： Germanium alloys

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Sampling-Based Methods for Multi-Block Optimization Problems over Transport Polytopes

arXiv

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arXiv 2023年

作者： Hu, Yukuan Li, Mengyu Liu, Xin Meng, Cheng State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China Institute of Statistics and Big Data Renmin University of China Beijing China Center for Applied Statistics Institute of Statistics and Big Data Renmin University of China Beijing China

This paper focuses on multi-block optimization problems over transport polytopes, which underlie various applications including strongly correlated quantum physics and machine learning. Conventional block coordinate descent-type methods for the general multi-block problems store and operate on the matrix variables directly, resulting in formidable expenditure for large-scale settings. On the other hand, optimal transport problems, as a special case, have attracted extensive attention and numerical techniques that waive the use of the full matrices have recently emerged. However, it remains nontrivial to apply these techniques to the multi-block, possibly nonconvex problems with theoretical guarantees. In this work, we leverage the benefits of both sides and develop novel sampling-based block coordinate descent-type methods, which are equipped with either entropy regularization or Kullback-Leibler divergence. Each iteration of these methods solves subproblems restricted on the sampled degrees of freedom. Consequently, they involve only sparse matrices, which amounts to considerable complexity reductions. We explicitly characterize the sampling-induced errors and establish convergence and asymptotic properties for the methods equipped with the entropy regularization. Numerical experiments on typical strongly correlated electron systems corroborate their superior scalability over the methods utilizing full matrices. The advantage also enables the first visualization of approximate optimal transport maps between electron positions in three-dimensional *** Codes 52-08, 65C05, 65F50, 81V05, 90C30 © 2023, CC BY.

关键词： Entropy

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Long term results in children underwent nuss procedure preschool with pectus excavatum: Real-world study with propensity matching

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Heliyon 2024年第20期10卷 e39477页

作者： Wang, Quan Kong, Xiangpan Ren, Chunian Pan, Zhengxia Wu, Chun Li, Hongbo Li, Yonggang Wang, Gang Dai, Jiangtao Department of Cardiothoracic Surgery Children's Hospital of Chongqing Medical University Ministry of Education Key Laboratory of Child Development and Disorders International Science and Technology Cooperation Base of Child Development and Critical Disorders National Clinical Research Center for Child Health and Disorders Chongqing Key Laboratory of Pediatrics Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering Chongqing Higher Institution Engineering Research Center of Children's Medical Big Data Intelligent Application Chongqing China Department of Urology Children's Hospital of Chongqing Medical University China

Background: It is controversial when surgery should be performed for pectus excavatum (PE). The study retrospectively compared the long-term prognosis in PE children undergoing the Nuss procedure at the age of 4–6 versus those performing surgery at the age of 12–14. Methods: 178 patients were included in the retrospective real-world research. Clinical Characteristics were collected at baseline. The endpoint of the study was set as the last follow-up at the age of 18 in outpatient services. Satisfaction and complication rate were set as the primary outcome and were collected at the endpoint. Hospital stay post-surgery and analgesia dosage were regard as the secondary outcome. To reduce potential bias between two different age groups, propensity score matching (PSM) analysis was analysized. Results: The oral analgesic dosage of children in the 4–6 years old age group is significantly lower than that of the 12–14 years old group (0.70/kg, 0.30–1.50/kg versus 1.50/kg, 0.90–2.30/kg, P < 0.001), and children in the younger age group are discharged earlier. There was no difference in overall satisfaction (89.1 %, versus 88.20 %, P = 0.99) and recurrence rate (7.2 %, versus 6.8 %, P = 0.99) between the two groups of when they reach the age of 18. Conclusions: Performing Nuss procedure at the age of 4–6 does not affect the overall long-term satisfaction of the child or increase the long-term recurrence rate. Surgical intervention in children with pectus excavatum preschool can provide a better postoperative experience in hospital compared with intervention in adolescent. © 2024 The Authors

关键词： Long-term results Nuss procedure Pectus excavatum Preschool

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Research on Indoor Localization Algorithm for Emergency Rescue Personnel Based on INS/UWB

Research on Indoor Localization Algorithm for Emergency Resc...

引用

Electrical, Electronic Information and Communication engineering (EEICE), International Conference on

作者： Mingyue Zhang Cheng Peng Guan Li Xiangli Bu Yang Wang North China Institute of Science and Technology School of Information and Control Engineering Key Laboratory of Brain-Computer Interface Technology Application of the Ministry of Emergency Management Langfang City China School of Information and Control Engineering North China Institute of Science and Technology Langfang City China Big Data Center Ministry of Emergency Management Beijing China School of Emergency Equipment North China Institute of Science and Technology Langfang City China

ISBN: (数字)9798331532598

ISBN: (纸本)9798331532604

To address the problem of low rescuer positioning accuracy in complex indoor rescue scenarios, a tightly combined positioning algorithm based on an adaptive weighting inertial navigation system/ultra-wideband (INS/UWB) is proposed. The algorithm innovatively integrates deep learning and error-resistant estimation theory and reduces the positioning error through multi-dimensional optimization. A zero velocity detection algorithm is developed based on a hybrid model of convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM), and an attention mechanism, which can accurately detect the zero velocity interval (ZVI) of a person's gait. The Zero Velocity Interval (ZVI) of a person's gait can be accurately recognized with a recognition accuracy of 98.2%, which is 15.7% higher than that of the traditional method. For the indoor UWB non-line-of-sight (NLOS) error, the IGG III error-resistant model is introduced to dynamically adjust the weights of the UWB range values and adaptively adjust the configuration of the system state covariance matrix and the measurement matrix. The experimental results show that under the indoor mixed occlusion conditions, the positioning accuracy is improved by 16.3% compared with the standard EKF algorithm, and the positioning error is controlled within 0.89m, indicating that the adaptive weighting INS/UWB tight combination positioning algorithm proposed in this paper is able to effectively use the IMU and UWB information to achieve a high-precision positioning function in indoor rescue scenarios and meet the positioning requirements in emergency rescue scenarios.

关键词： Location awareness Weight measurement Adaptation models Accuracy Adaptive systems Feature extraction Real-time systems Personnel Covariance matrices Standards

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ML-DSVM+: A meta-learning based deep SVM+ for computer-aided diagnosis

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Pattern Recognition 2023年 134卷

作者： Han, Xiangmin Wang, Jun Ying, Shihui Shi, Jun Shen, Dinggang Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication School of Communication and Information Engineering Shanghai University China Shanghai Institute for Advanced Communication and Data Science Shanghai University China Department of Mathematics School of Science Shanghai University Shanghai China School of Biomedical Engineering ShanghaiTech University Shanghai China Shanghai United Imaging Intelligence Co. Ltd. Shanghai China

Transfer learning (TL) can improve the performance of a single-modal medical imaging-based computer-aided diagnosis (CAD) by transferring knowledge from related imaging modalities. Support vector machine plus (SVM+) is a supervised TL classifier specially designed for TL between the paired data in the source and target domains with shared labels. In this work, a novel deep neural network (DNN) based SVM+ (DSVM+) algorithm is proposed for single-modal imaging-based CAD. DSVM+ integrates the bi-channel DNNs and SVM+ classifier into a unified framework to improve the performance of both feature representation and classification. In particular, a new coupled hinge loss function is developed to conduct bidirectional TL between the source and target domains, which further promotes knowledge transfer together with the feature representation under the guidance of shared labels. To alleviate the overfitting caused by the increased parameters in DNNs for limited training samples, the meta-learning based DSVM+ (ML-DSVM+) is further developed, which designs randomly selecting samples from the training data instead of other CAD tasks for meta-tasks. This sampling strategy also can avoid the issue of class imbalance. ML-DSVM+ is evaluated on three medical imaging datasets. It achieves the best results of 88.26±1.40%, 90.45±5.00%, and 87.63±5.56% on accuracy, sensitivity and specificity, respectively, on the Bimodal Breast Ultrasound Image dataset, 90.00±1.05%, 72.55±3.87%, and 96.40±2.26% of the corresponding indices on the Alzheimer's Disease Neuroimaging Initiative dataset, and 85.76±3.12% of classification accuracy, 88.73±7.22% of sensitivity, and 82.60±1.56% of specificity for the Autism Brain Imaging data Exchange dataset. © 2022

关键词： Support vector machines

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UAV-Aided Covert Federated Learning Networks

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IEEE Network 2025年

作者： Wang, Chao Guo, Shaoyong Xiong, Zehui Xing, Chengwen Zhao, Nan Niyato, Dusit Karagiannidis, George Dalian University of Technology School of Information and Communication Engineering Dalian116024 China Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China Singapore University of Technology and Design Information Systems Technology and Design Pillar 487372 Singapore Beijing Institute of Technology School of Information and Electronics Beijing100081 China Nanyang Technological University College of Computing and Data Science 639798 Singapore Aristotle University of Thessaloniki Department of Electrical and Computer Engineering Greece

With the increasing emphasis on data privacy, federated learning (FL) networks show great potential through distributed training without directly sharing the raw data. However, the coverage of FL terrestrial servers is usually limited. Therefore, we propose leveraging the unmanned aerial vehicle (UAV) as a mobile flying server to further improve the wireless coverage and training efficiency of FL. Nevertheless, frequent exchanges of model parameters in UAV-assisted FL can result in serious security risks. In order to achieve this, we propose a covert FL scheme assisted by the UAV, which can protect the transmission key features of local models from being detected by wardens. Furthermore, we discuss the FL network and covert communications, as well as the exceptional features of UAV-assisted covert FL. Finally, we present two case studies, one of which focuses on minimising the network latency, while the other concentrates on reducing the energy consumption of covert FL. The simulation results demonstrate the efficacy of the proposed schemes in addressing future challenges. © 1986-2012 IEEE.

关键词： data privacy

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Microscopic study of 7Li-nucleus potential

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Chinese Physics C 2020年第5期44卷 106-113页

作者： Wen-Di Chen Hai-Rui Guo Wei-Li Sun Tao Ye Yang-Jun Ying Yin-Lu Han Qing-Biao Shen Graduate School of China Academy of Engineering Physics Beijing 100088China Institute of Applied Physics and Computational Mathematics Beijing 100094China Key Laboratory of Nuclear Data China Institute of Atomic EnergyBeijing 102413China

A microscopic approach is employed to study the optical potential for the 7Li-nucleus interaction system without any free *** is obtained by folding the microscopic optical potentials of the constituent nucleons of 7Li over their density *** employ an isospin-dependent nucleon microscopic optical potential,which is based on the Skyrme nucleon-nucleon effective interaction and derived using the Green's function method,as the nucleon optical *** harmonic oscillator shell model is used to describe the internal wave function of 7Li and obtain the nucleon density *** 7Li microscopic optical potential is used to predict the reaction cross-sections and elastic scattering angular distributions for the target range from 27Al to 208Pb and energy range below 450 ***,the results can reproduce the measured data reasonably *** addition,the microscopic optical potential is comparable to a global phenomenological optical potential by fitting the presently existing measured data.

关键词： 7 Li microscopic optical potential 7 Li elastic scattering folding model

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A spectrum-enhanced attention model for semantic segmentation of remote sensing images

A spectrum-enhanced attention model for semantic segmentatio...

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

作者： Xin Li Feng Xu Feifei Tao Yao Tong Xin Lyu Jianyi Zhong André Kaup College of Computer Science and Software Engineering Hohai University Nanjing China Key Laboratory of Water Big Data Technology of Ministry of Water Resources Hohai University Nanjing China School of Computer Engineering Jiangsu Ocean University Lianyungang China School of Artificial Intelligence and Information Technology Nanjing University of Chinese Medicine Nanjing China Chair of Multimedia Communications and Signal Processing Friedrich-Alexander University Erlangen-Nuremberg Erlangen Germany

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Semantic segmentation of remote sensing images (RSIs) is essential for applications such as environmental monitoring, urban planning, and disaster management. Convolutional Neural Networks (CNNs) and their variants struggle to capture comprehensive spectral context for learning discriminative representations. In this paper, we propose a Spectrum-Enhanced Network (SPENet) that leverages the Frequency Transformer Block (FTB) to capture rich spectral context. FTB integrates Spectrum-Enhanced Attention (SEA) with Multi-Head Frequency Self-Attention (MH-FSA), incorporating more informative contextual cues. Specifically, SEA aggregates spectral statistics through covariance matrix normalization before applying channel-wise attention. By projecting feature maps onto the frequency domain, MH-FSA provides the network with a broader context, extending beyond the low-frequency focus of standard self-attention mechanisms. Extensive experiments on the ISPRS Potsdam and LoveDA datasets show that SPENet significantly outperforms state-of-the-art methods. Besides, the proposed SEA module notably rises average F1-score/overall accuracy/mean insert over union wiht more than 2.5/2.6%/2.3%, as demonstrated by ablation study.

关键词： Semantic segmentation Frequency-domain analysis Urban planning Semantics Speech enhancement Signal processing Transformers Sensors Remote sensing Standards

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Voice Conversion Augmentation for Speaker Recognition on Defective datasets

arXiv

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arXiv 2024年

作者： Tao, Ruijie Shi, Zhan Jiang, Yidi Liu, Tianchi Li, Haizhou Department of Electrical and Computer Engineering National University of Singapore Singapore119077 Singapore School of Data Science The Chinese University of Hong Kong Shenzhen518172 China Singapore Institute of Technology Institute for Infocomm Research A∗STAR Singapore138632 Singapore Guangdong Provincial Key Laboratory of Big Data Computing The Chinese University of Hong Kong Shenzhen518172 China Shenzhen Research Institute of Big data Shenzhen518172 China University of Bremen Bremen28359 Germany

Modern speaker recognition system relies on abundant and balanced datasets for classification training. However, diverse defective datasets, such as partially-labelled, small-scale, and imbalanced datasets, are common in real-world applications. Previous works usually studied specific solutions for each scenario from the algorithm perspective. However, the root cause of these problems lies in dataset imperfections. To address these challenges with a unified solution, we propose the Voice Conversion Augmentation (VCA) strategy to obtain pseudo speech from the training set. Furthermore, to guarantee generation quality, we designed the VCA-NN (nearest neighbours) strategy to select source speech from utterances that are close to the target speech in the representation space. Our experimental results on three created datasets demonstrated that VCA-NN effectively mitigates these dataset problems, which provides a new direction for handling the speaker recognition problems from the data aspect. © 2024, CC BY.

关键词： Classification (of information)

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Channel Estimation for Optical Intelligent Reflecting Surface-Assisted VLC System: A Joint Space-Time Sampling Approach

arXiv

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arXiv 2024年

作者： Sun, Shiyuan Yang, Fang Mei, Weidong Song, Jian Han, Zhu Zhang, Rui The Department of Electronic Engineering Tsinghua University Beijing100084 China The National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China Chengdu611731 China The Shenzhen International Graduate School Tsinghua University Shenzhen518055 China The Department of Electrical and Computer Engineering The University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Guangdong Shenzhen518172 China The Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore

Optical intelligent reflecting surface (OIRS) has attracted increasing attention due to its capability of overcoming signal blockages in visible light communication (VLC), an emerging technology for the next-generation advanced transceivers. However, current works on OIRS predominantly assume known channel state information (CSI), which are essential to practical OIRS configuration. To bridge such a gap, this paper proposes a new and customized channel estimation protocol for OIRSs under the alignment-based channel model. Specifically, we first unveil OIRS spatial and temporal coherence characteristics and derive the coherence distance and the coherence time in closed-form. Next, to achieve fast beam alignment over different coherence time, we propose to dynamically tune the rotational angles of the OIRS reflecting elements following a geometric optics-based non-uniform codebook. Given the above beam alignment, we propose an efficient joint space-time sampling-based algorithm to estimate the OIRS channel. In particular, we divide the OIRS into multiple subarrays based on the coherence distance and sequentially estimate their associated CSI, followed by a spacetime interpolation to retrieve full CSI for other non-aligned transceiver antennas. Numerical results validate our theoretical analyses and demonstrate the efficacy of our proposed OIRS channel estimation scheme as compared to other benchmark schemes. Copyright © 2024, The Authors. All rights reserved.

关键词： Channel estimation

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