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arXiv 2025年

作者： Guo, Fei Wang, Zilong Gong, Guang State Key Laboratory of Mathematical Engineering and Advanced Computing Information Engineering University Zhengzhou450001 China State Key Laboratory of Integrated Service Networks Xidian University Xi’an710071 China Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

In 2017, Zhang et al. proposed a question (not open problem) and two open problems in [IEEE TIT 63 (8): 5336–5349, 2017] about constructing bent functions by using Rothaus’ construction. In this note, we prove that the sufficient conditions of Rothaus’ construction are also necessary, which answers their question. Besides, we demonstrate that the second open problem, which considers the iterative method of constructing bent functions by using Rothaus’ construction, has only a trivial solution. It indicates that all bent functions obtained by using Rothaus’ construction iteratively can be generated from the direct sum of an initial bent function and a quadratic bent function. This directly means that Zhang et al.’s construction idea makes no contribution to the construction of bent functions. To compensate the weakness of their work, we propose an iterative construction of bent functions by using a secondary construction in [DCC 88: 2007–2035, 2020]. © 2025, CC BY-NC-ND.

关键词： Hadamard transforms

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ThicknesVAE: Learning a Latera Prior for Clothed Human Body Reconsuction

ThicknesVAE: Learning a Latera Prior for Clothed Human Body ...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Wu, Xiaotao Fan, Zhaoxin He, Huiguang Shen, Dinggang School of Biomedical Engineering State Key Laboratory of Advanced Medical Materials and Devices ShanghaiTech University Shanghai201210 China NeuBCI Group State Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology Institute of Automation Chinese Academy of Sciences Beijing China Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Institute of Artificial Intelligence Beihang University Beijing100191 China Beijing Academy of Blockchain and Edge Computing China Shanghai United Imaging Intelligence Co. Ltd. Shanghai200232 China Shanghai Clnical Research and Trial Center Shanghai201210 China

ISBN: (纸本)9798350368741

Sandwich-like structures have shown remarkable efficacy in clothed human reconstruction. However, these approaches often generate unrealistic side geometries due to inadequate handling of lateral regions. This paper addresses this limitation by incorporating the side geometry of clothed humans as a prior. We propose ThicknessVAE, a novel two-stage method that makes two key contributions: (1) We learn a prototype from point clouds for the lateral regions of clothed humans to extract common and detailed geometric features. (2) We utilize this prototype as a prior to transform geometric features into a thickness map associated with clothed human images, enabling refined normal integration for sandwich-like reconstruction methods. By seamlessly integrating our model into the sandwich-like reconstruction pipeline, we achieve highly realistic side views. Both qualitative and quantitative experiments demonstrate that our approach is comparable to state-of-the-art methods in terms of side-view realism. © 2025 IEEE.

关键词： 3D Human Reconsruction Normal Integraton Prior Learning

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Detection of Malicious PDF Files Using a Two-Stage Machine Learning Algorithm

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Chinese Journal of Electronics 2020年第6期29卷 1165-1177页

作者： HE Kang ZHU Yuefei HE Yubo LIU Long LU Bin LIN Wei State Key Laboratory of Mathematical Engineering and Advanced Computing

Portable document format(PDF) files are increasingly used to launch cyberattacks due to their popularity and increasing number of *** solutions have been developed to detect malicious files,but their accuracy decreases rapidly in face of new evasion *** explore how to improve the robustness of classifiers for detecting adversarial attacks in PDF *** replacement and the n-gram are implemented to extract robust features using proposed guiding *** the two-stage machine learning model,the objects are divided based on their types,and the anomaly detection model is first trained for each type *** former detection results are organized into tree-like information structure and treated as inputs to convolutional neural *** results show that the accuracy of our classifier is nearly 100% and the robustness against evasive samples is *** object features also enable the identification of different vulnerabilities exploited in malicious PDF files.

关键词： convolutional neural nets document handling feature extraction learning (artificial intelligence) pattern classification security of data trees (mathematics) robust feature extraction convolutional neural network tree-like information structure adversarial attack detection two-stage machine learning algorithm evasion techniques malicious files portable document format malicious PDF files classifier robustness anomaly detection model two-stage machine learning model Malicious PDF classification Robustness Guiding principles Two-stage classifier Convolutional neural network

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Non-binary entanglement-assisted quantum stabilizer codes

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Science China(Information Sciences) 2017年第4期60卷 210-223页

作者： Lan LUO Zhi MA Zhengchao WEI Riguang LENG State Key Laboratory of Mathematical Engineering and Advanced Computing

In this paper, we present the pm-ary entanglement-assisted(EA) stabilizer formalism, where p is a prime and m is a positive integer. Given an arbitrary non-abelian "stabilizer", the problem of code construction and encoding is settled perfectly in the case of m = 1. The optimal number of required maximally entangled pairs is discussed and an algorithm to determine the encoding and decoding circuits is proposed. We also generalize several bounds on p-ary EA stabilizer codes, such as the BCH bound, the G-V bound and the linear programming bound. However, the issue becomes tricky when it comes to m > 1, in which case, the former construction method applies only when the non-commuting "stabilizer" satisfies a sophisticated limitation.

关键词： entanglement non-commutativity non-binary stabilizer codes quantum error-correction quantum circuits bounds

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LaTLS: A Lattice-Based TLS Proxy Protocol

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Chinese Journal of Electronics 2022年第2期31卷 313-321页

作者： ZHANG Xinglong CHENG Qingfeng LI Yuting State Key Laboratory of Mathematical Engineering and Advanced Computing

The function of the Internet proxy is to check and convert the data exchanged between client and server. In fact, the two-party secure communication protocol with good security is turned into an unsafe multiparty protocol. At present, there are relatively few proxy protocols that can be applied in practice. This paper analyzes the classic agent protocol mcTLS and pointed out the security issues. We focus on the security of TLS 1.3 and proposed a lattice-based multi-party proxy protocol:La TLS. LaTLS can be proved secure in the eCK model, it can resist key-sharing attacks, counterfeiting attacks, replay attacks, and achieve forward security. Compared with traditional DH and ECDH schemes, LaTLS is more effcient. Its security is based on the shortest vector problem, therefor it has anti-quantum attack properties.

关键词： security issues Internet lattice-based multiparty proxy protocol relatively few proxy protocols data exchanged LaTLS key sharing attacks unsafe multiparty protocol Internet proxy shortest vector problem protocols antiquantum attack properties forward security two-party secure communication protocol classic agent protocol mcTLS classic agent protocol computer network security

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An Adaptive Proximal Inexact Gradient Framework and Its Application to Per-Antenna Constrained Joint Beamforming and Compression Design

arXiv

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arXiv 2025年

作者： Fan, Xilai Jiang, Bo Liu, Ya-Feng State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Ministry of Education Key Laboratory of NSLSCS School of Mathematical Sciences Nanjing Normal University Nanjing210023 China

In this paper, we propose an adaptive proximal inexact gradient (APIG) framework for solving a class of nonsmooth composite optimization problems involving function and gradient errors. Unlike existing inexact proximal gradient methods, the proposed framework introduces a new line search condition that jointly adapts to function and gradient errors, enabling adaptive stepsize selection while maintaining theoretical guarantees. Specifically, we prove that the proposed framework achieves an ϵ-stationary point within O(ϵ−2) iterations for nonconvex objectives and an ϵ-optimal solution within O(ϵ−1) iterations for convex cases, matching the best-known complexity in this context. We then custom-apply the APIG framework to an important signal processing problem: the joint beamforming and compression problem (JBCP) with per-antenna power constraints (PAPCs) in cooperative cellular networks. This customized application requires careful exploitation of the problem’s special structure such as the tightness of the semidefinite relaxation (SDR) and the differentiability of the dual. Numerical experiments demonstrate the superior performance of our custom-application over state-of-the-art benchmarks for the JBCP. © 2025, CC BY.

关键词： Beamforming

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Metaheuristic Optimization Methods and Techniques for Multiple Sclerosis Detection 4th

Metaheuristic Optimization Methods and Techniques for Multip...

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4th International Conference on IoT and Big Data Technologies for Health Care, IotCare 2023

作者： Wang, Jiaji Wu, Meng Chen, Shuwen Zhu, Huisheng School of Computing and Mathematical Sciences University of Leicester LeicesterLE1 7RH United Kingdom School of Physics and Information Engineering Jiangsu Second Normal University Jiangsu Nanjing210016 China State Key Laboratory of Millimeter Waves Southeast University Nanjing210096 China

ISBN: (纸本)9783031900839

This paper explores the application of metaheuristic optimization methods in the context of Multiple Sclerosis (MS) detection, addressing the challenges of early and accurate diagnosis. It introduces Genetic Algorithms, Simulated Annealing, and Particle Swarm Optimization as effective tools for feature selection and classification in MS detection. Additionally, the paper discusses emerging metaheuristic optimization methods and their potential contributions. Through critical evaluation, it emphasizes the need for method selection based on task-specific requirements. In conclusion, this research highlights the promise of metaheuristic optimization in revolutionizing MS detection, urging further development and validation on larger datasets. Future directions include hybrid algorithms and advanced machine learning integration for improved diagnostic precision. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering 2025.

关键词： Particle swarm optimization (PSO)

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Use Tabu Search Particle Swarm Optimization Algorithm to Detect COVID-19 4th

Use Tabu Search Particle Swarm Optimization Algorithm to Det...

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4th International Conference on IoT and Big Data Technologies for Health Care, IotCare 2023

作者： Chen, Shuwen Wang, Jiaji Zhu, Huisheng School of Physics and Information Engineering Jiangsu Second Normal University Jiangsu Nanjing210016 China State Key Laboratory of Millimeter Waves Southeast University Nanjing210096 China School of Computing and Mathematical Sciences University of Leicester LeicesterLE1 7RH United Kingdom

ISBN: (纸本)9783031900839

Efficient and accurate COVID-19 detection methods are paramount in the ongoing battle against the global pandemic. In this study, we present a novel approach that leverages the Tabu Search Particle Swarm Optimization (TS-PSO) algorithm for COVID-19 detection. Unlike conventional methods, our approach combines the strengths of both global and local search strategies, enhancing the accuracy of diagnosis. We conducted extensive experiments, benchmarking our TS-PSO-based approach against established methods. The results reveal that our TS-PSO method achieves competitive performance, with improvements in sensitivity, specificity, precision, accuracy, F1 score, MCC, and FMI. This innovative approach not only advances the field of COVID-19 detection but also demonstrates its potential as a valuable tool for healthcare professionals in the ongoing fight against the pandemic. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering 2025.

关键词： Tabu search

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RobNODDI: Robust NODDI Parameter Estimation with Adaptive Sampling Under Continuous Representation 15th

RobNODDI: Robust NODDI Parameter Estimation with Adaptive S...

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15th International Workshop on Computational Diffusion MRI, CDMRI 2024, held in conjunction with 27th International Conference on Medical Image computing and Computer-Assisted Intervention, MICCAI 2024

作者： Xiao, Taohui Cheng, Jian Fan, Wenxin Yang, Jing Li, Cheng Dong, Enqing Wang, Shanshan School of Mechanical Electrical and Information Engineering Shandong University Weihai264209 China State Key Laboratory of Software Development Environment Beihang University Beijing China Key Laboratory of Data Science and Intelligent Computing Institute of International Innovation Beihang University Zhejiang Hangzhou China Paul C. Lauterbur Research Center for Biomedical Imaging Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China Peng Cheng Laboratory Guangdong Shenzhen China

ISBN: (纸本)9783031869198

Neurite Orientation Dispersion and Density Imaging (NODDI) is an important imaging technology used to evaluate the microstructure of brain tissue, which is of great significance for the discovery and treatment of various neurological diseases. Current deep learning-based methods perform parameter estimation through diffusion magnetic resonance imaging (dMRI) with a small number of diffusion gradients. These methods speed up parameter estimation and improve accuracy. However, the diffusion directions used by most existing deep learning models during testing needs to be strictly consistent with the diffusion directions during training. This results in poor generalization and robustness of deep learning models in dMRI parameter estimation. In this work, we first verify that the parameter estimation performance of current mainstream methods will significantly decrease when the testing diffusion directions and the training diffusion directions are inconsistent. A robust NODDI parameter estimation method with adaptive sampling under continuous representation (RobNODDI) is proposed. Furthermore, long short-term memory (LSTM) units and fully connected layers are selected to learn continuous representation signals. To this end, we use a total of 100 subjects to conduct experiments based on the Human Connectome Project (HCP) dataset, of which 60 are used for training, 20 are used for validation, and 20 are used for testing. The test results indicate that RobNODDI improves the generalization performance and robustness of the deep learning model, enhancing the stability and flexibility of deep learning NODDI parameter estimatimation applications. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Deep learning

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A Further Understanding of Differential-Linear Cryptanalysis

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Chinese Journal of Electronics 2020年第4期29卷 660-666页

作者： REN Jiongjiong CHEN Shaozhen State Key Laboratory of Mathematical Engineering and Advanced Computing State Key Laboratory of Cryptology

Differential-linear cryptanalysis has attracted much attention since proposed to attack DES in 1994, and then some generalized theories are developed to complement and unify the ***, the links between differential-linear cryptanalysis and other important cryptanalysis methods have been still *** motivation is to fix the *** establishing some boolean equations, we propose the mathematical links among differential, linear and differential-linear *** then generalise the definition of capacity and present some properties of the capacity of differential *** links and properties are employed to explore the relationships between multidimensional differential-linear hulls and integral *** show that a multidimensional differential-linear hull of certain correlation always implies the existence of an integral distinguisher and a zero-correlation linear hull, while a special integral distinguisher indicates the existence of a multidimensional differential-linear hull.

关键词： Block cipher Differential cryptanalysis Linear cryptanalysis Differential-linear cryptanalysis Integral distinguisher Zero-correlation

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