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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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Robust optimization for quantum reinforcement learning control using partial observations

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Physical Review A 2022年第6期105卷 062443-062443页

作者： Chen Jiang Yu Pan Zheng-Guang Wu Qing Gao Daoyi Dong State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou 310027 China The School of Automation Science and Electrical Engineering and Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing 100191 China The School of Engineering and Information Technology University of New South Wales Canberra Australian Capital Territory 2600 Australia

The current quantum reinforcement learning control models often assume that the quantum states are known a priori for control optimization. However, full observation of the quantum state is experimentally infeasible due to the exponential scaling of the number of required quantum measurements on the number of qubits. In this paper, we investigate a robust reinforcement learning method using partial observations to overcome this difficulty. This control scheme is compatible with near-term quantum devices, where the noise is prevalent and predetermining the dynamics of the quantum state is practically impossible. We show that this simplified control scheme can achieve similar or even better performance when compared to the conventional methods relying on full observation. We demonstrate the effectiveness of this scheme on examples of quantum state control and the quantum approximate optimization algorithm (QAOA). It has been shown that high-fidelity state control can be achieved even if the noise amplitude is at the same level as the control amplitude. Besides, an acceptable level of optimization accuracy can be achieved for a QAOA with a noisy control Hamiltonian. This robust control optimization model can be trained to compensate for the uncertainties in practical quantum computing.

关键词： Machine learning Quantum control Quantum engineering

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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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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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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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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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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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Utilization of machine learning and neural networks to optimize the enclosure angle, magnetic field, and radiation parameter for mixed convection of hybrid nanofluid flow next to assess environmental impact

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engineering Analysis with Boundary Elements 2023年 146卷 252-262页

作者： Tao Hai Hayder A. Dhahad Masood Ashraf Ali Vishal Goyal Sattam Fahad Almojil Abdulaziz Ibrahim Almohana Abdulrhman Fahmi Alali Khaled Twfiq Almoalimi Farah Qasim Ahmed Alyousuf School of Computer and Information Qiannan Normal University for Nationalities Duyun Guizhou 558000 China Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Duyun Guizhou 558000 China Institute for Big Data Analytics and Artificial Intelligence (IBDAAI) Universiti Teknologi MARA Shah Alam Selangor 40450 Malaysia Mechanical Engineering Department University of Technology Baghdad Iraq Department of Industrial Engineering College of Engineering Prince Sattam bin Abdulaziz University Alkharj 16273 Saudi Arabia Department of Electronics and Communication Engineering GLA University Mathura India Department of Civil Engineering College of Engineering King Saud University P.O. Box 800 Riyadh 11421 Saudi Arabia Department of Information Technology College of Engineering and Computer Science Lebanese French University Kurdistan Region Iraq

This paper examines the mixed convective heat transfer (HTR) of nanofluid (NFD) flow in a rectangular enclosure with the upper moving wall numerically. The lower wall has a high temperature and a number of semi-circular obstacles with the same temperature are installed on it. The upper moving wall has a low temperature and the other two walls are insulated. The enclosure can change from horizontal to vertical. Radiation HTR is considered in the enclosure and there is a magnetic field (MGF) that can change the angle from horizontal to vertical affecting the NFD. This study is carried out for different angles of the enclosure and MGF from horizontal to vertical for radiation parameters (RDP) of 0 to 3 and a constant MGF with Hartmann number of 20 and Richardson number of 10. The aim is to estimate the Nusselt number (Nu), entropy generation (ETG), and Bejan number (Be). The SIMPLE algorithm is utilized using FORTRAN software, and optimization is done using artificial intelligence to find the maximum and minimum output values. The results demonstrate that the maximum value of Nu and Bes corresponds to the MGF angle and enclosure angle of 90°. The minimum value of the Nu and the maximum amount of ETG corresponds to the horizontal MGF and horizontal enclosure when the RDP is 1.5. An increment in the RDP enhances the amount of Nu. The maximum amount of ETG, i.e. 12.87, corresponds to the enclosure with an angle of 45° for the horizontal MGF and the absence of RDP. corresponds to the enclosure with an angle of 45° for the horizontal MGF and the absence of RDP. It was also found that most environmental impacts, and hence values for different environmental factors, arise from the production of nanoparticles; thus, it is a significant contributor to environmental impacts.

关键词： Machine learning Entropy generation Numerical calculations Convection Nanofluid

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Semiconductive and Ferromagnetic Lanthanide MXenes Derived from Carbon Intercalated Two-dimensional Halides

arXiv

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arXiv 2024年

作者： Fang, Qian Wang, Liming Chang, Kai Yang, Hongxin Yan, Pu Cao, Kecheng Li, Mian Chai, Zhifang Huang, Qing Zhejiang Key Laboratory of Data-Driven High-Safety Energy Materials and Applications Ningbo Key Laboratory of Special Energy Materials and Chemistry Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China University of Chinese Academy of Sciences Beijing100049 China Qianwan Institute of CNiTECH Ningbo315336 China Center for Quantum Matter School of Physics Zhejiang University Hangzhou31008 China School of Physical Science and Technology Shanghai Key Laboratory of High-resolution Electron Microscopy ShanghaiTech University Shanghai201210 China

Two-dimensional (2D) magnetic semiconductors are a key focus in developing next-generation information storage technologies1,2. MXenes, as emerging 2D early transition metal carbides and nitrides, offer versatile compositions and tunable chemical structures3. Incorporating lanthanide metals, with their unique role of 4f-electrons in engineering physical properties4, into MXenes holds potential for advancing technological applications. However, the scarcity of lanthanide-containing ternary MAX phase precursors and the propensity of lanthanides to oxidize pose significant challenges to obtain lanthanide MXenes (Ln2CT2) via the ‘top-down’ etching method5. Here, we propose a general ‘bottom-up’ methodology for lanthanide MXenes, that derive from carbon intercalated van der Waals building blocks of 2D halides. Compared to conventional MXenes conductors, the synthesized Ln2CT2 exhibit tunable band gaps spanning 0.32 eV to 1.22 eV that cover typical semiconductors such as Si (1.12 eV) and Ge (0.67 eV). Additionally, the presence of unpaired f-electrons endows Ln2CT2 with intrinsic ferromagnetism, with Curie temperatures ranging between 36 K and 60 K. Theoretical calculations reveal that, in contrast to traditional MXenes, the number of delectrons states around the Fermi level are largely diminishes in bare Ln2C MXenes, and the halogen terminals can further exhaust these electrons to open band gaps. Meanwhile, the Ln-4f electrons in Ln2CT2 are highly localized and stay away from the Fermi level, contributing to the spin splitting for the observed ferromagnetic behavior. Lanthanide MXenes hold immense promise for revolutionizing future applications in spintronic devices. © 2024, CC BY.

关键词： Nitrides

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