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2022 2nd International Conference on Electronics, Circuits and Information engineering, ECIE 2022

作者： Liu, Xiaonan He, Ming Wang, Junchao Xie, Haoshan Zhao, Chenyan Information Engineering University State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

As a benchmark for the overall performance of quantum computers, quantum volume has the advantage of being able to reflect the depth of running quantum circuits. But, the quantum volume test code provided by IBM needs to be executed manually, and the simulation result of the quantum simulator is used as the result of the volume test, so that users cannot quickly and accurately test the quantum volume of the actual quantum computer required. In response to this problem, this paper designs an automated quantum volume test program. The program automatically generates quantum volume sequences, selects the number of executions of quantum circuits, and defines real quantum computers to facilitate users to perform quantum volume tests on quantum computers provided by the IBM Quantum Cloud Platform. Simultaneously, according to the automated test program, the quantum volume of IBM's four small superconducting quantum computers was tested. The test results show that (1) the quantum computer is different, and the qubit layout and execution times ntrials are the same, will cause the quantum volume is uncertain;(2) the same quantum computer, whether ntrials is the same, the robustness of qubit coupling will be affected to a certain extent. © Published under licence by IOP Publishing Ltd.

关键词： Benchmarking

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Research on Web application injection vulnerabilities detection method based on pattern matching

Research on Web application injection vulnerabilities detect...

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2022 International Conference on Algorithms, Microchips and Network Applications

作者： Ma, Qican Wu, Zehui Wang, Xinlei Wei, Qiang State Key Laboratory of Mathematical Engineering and Advanced Computing Information Engineering University Zhengzhou450001 China

ISBN: (纸本)9781510653290

Attackers can exploit vulnerabilities in web applications to commit malicious acts such as corrupting application functionality and Trojan horse implantation. For injection vulnerabilities in Web applications, existing methods are limited by the variety of programming languages and the difficulty in extracting semantic information to detect complex vulnerabilities. The paper proposes a pattern matching-based method for identifying injection vulnerabilities in Web applications, which transforms vulnerability identification into path matching in graphical databases by modifying the code property graph to enable it to handle more complex inter-functional relationships in Web applications. In this paper, we designed and implemented a prototype system, VulnFinder. By collecting 100 randomly selected Github high star open-source projects as the dataset for performance testing, we found 262 real vulnerabilities and conducted comparison experiments with static scanning tools RIPS and Cobra, VulnFinder far exceeded the comparison tools in terms of vulnerability determination accuracy, and in terms of the dataset VulnFinder was 94% accurate in determining vulnerabilities in the dataset. In scanning large projects, VulnFinder was approximately 21% more efficient than the comparable methodology tool RIPS. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Pattern matching

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IoT Device Multi-Classification Using Traffic Behavior Analysis 3

IoT Device Multi-Classification Using Traffic Behavior Analy...

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3rd International Conference on Internet of Things and Smart City, IoTSC 2023

作者： Shi, Jiaqi Liu, Tieming Zhang, Yuanyuan Ren, Huajuan Cyberspace Security Department State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Information Service Room Unit 32738 China

ISBN: (纸本)9781510666375

The management of Internet of Things (IoT) devices is becoming increasingly complex. One of the reasons is that IoT device manufacturers are different, and there are different degrees of heterogeneity in service, technology, protocol and other aspects. Accurate identification IoT devices connected to the organization network is an effective way to maintain the organization network security. In this paper, we propose a two-stage machine learning method to identify IoT devices by analyzing network traffic. This method uses the futures of the original traffic advance to classify the types of IoT devices. The method is tested on two public datasets, our method classified IoT devices with an accuracy rate of over 99%. © 2023 SPIE.

关键词： Machine learning

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Meta Transductive Linear Probing for Few-Shot Node Classification

Meta Transductive Linear Probing for Few-Shot Node Classific...

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Pattern Recognition and Machine Learning (PRML), IEEE International Conference on

作者： Mingjing Lan Ningbo Huang Gang Zhou Yi Xia State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (数字)9798350355925

ISBN: (纸本)9798350355932

Graph few-shot learning aims to predict well by training with very few labeled data. Meta learning has been the most popular solution for few-shot learning problem. However, transductive linear probing shows that fine-tuning a simple linear classification head after a pretrained graph neural networks can outperforms most of the sophisticated-designed graph meta learning algorithms. Therefore, in the paper, we propose a meta transductive linear probing methods named Meta-TLP to incorporate the advantages of graph self-supervised and graph meta learning model. Specifically, the graph neural network is firstly pretrained with graph contrastive learning methods. Then we design an unsupervised meta training task construction methods to require meta tasks without relying on labeled data. Finally, we meta training the linear classification head on the meta training tasks to learn to fast adopt to novel classes. Experiment results show that our model can perform better than TLP on three real world datasets.

关键词： Training Metalearning Design methodology Data visualization Prediction algorithms Magnetic heads Data models Graph neural networks Pattern recognition Few shot learning

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Synergistically enhanced dielectric, insulating and thermally conductive performances of sandwich PMMA based dielectric films

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Progress in Natural Science:Materials International 2024年第3期34卷 591-597页

作者： Dongmei Zhang Yufan Li Yuchao Li Zhonggui Sun Hanxue Zhu Lujia Yang Yanhu Zhan Yankai Li Shi Wang Jun-Wei Zha School of Mathematical Sciences Liaocheng University School of Materials Science and Engineering Liaocheng University State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM) Nanjing University of Posts & Telecommunications School of Chemistry and Biological Engineering University of Science and Technology Beijing

A tri-layered(B-G-B) dielectric films were simply prepared by alternatively spin-coating boron nitride/polymethylmethacrylate(BN/PMMA, B) and graphene nanosheets(GNS/PMMA, G) compound solutions. The structure, morphology, thermal conductivity, and particularly the dielectric and relaxation behaviors were systematically studied. Results showed that a good exfoliation and dispersion of BN and GNS can be simply achieved through intensive mechanical compounding with PMMA in the internal mixer. The dielectric constant and breakdown strength of the obtained 1-3-1(B-G-B) sandwich composite film reached 4.3(@1 kHz) and 458.6kV/mm, being 119 % and 113 % higher than that of pure PMMA, respectively. Furthermore, the overall thermal conductivity of sandwich 1-3-1 composite increased by 112 % due to the addition of thermally conductive BN and GNS. The sandwich design strategy provided an effective way of achieving good permittivity, high insulation, and improved thermal conductivity simultaneously, showing potential applications in the miniaturization and integration of electronic devices.

关键词： Sandwich structure Breakdown strength Thermal conductivity Dielectric constant Composites

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On greedy randomized coordinate updating iteration methods for solving symmetric eigenvalue problems

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Applied Numerical Mathematics 2025年 216卷 76-97页

作者： Bai, Zhong-Zhi State Key Laboratory of Mathematical Sciences Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China State Key Laboratory of Scientific/Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences P.O. Box 2719 Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China

In order to compute the smallest eigenvalue and its corresponding eigenvector of a large-scale, real, and symmetric matrix, we propose a class of greedy randomized coordinate updating iteration methods based on the principle that the indices of larger entries in absolute value of the current residual are selected with a higher probability and, with respect to this index set, the next iterate is updated from the current iterate along with the selected coordinate such that the corresponding entry of the residual is annihilated, resulting in fast convergence rates of the proposed iteration methods. Under appropriate conditions, we prove the convergence of both sequences of the Rayleigh-quotients and the acute angles between the iterates and the eigenvector in terms of the expectation. By numerical experiments, we show that this class of greedy randomized coordinate updating iteration methods are advantageous over the parameterized power method and the coordinate descent method in both iteration counts and computing times. Moreover, with theoretical analysis and computational performance, we confirm that the convergence property of this class of iteration methods can be improved significantly by suitably choosing the arbitrary nonnegative parameter involved in the greedy probability criterion. © 2025 IMACS

关键词： Eigenvalues and eigenfunctions

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A GAN-based Method for Generating SQL Injection Attack Samples 10

A GAN-based Method for Generating SQL Injection Attack Sampl...

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10th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022

作者： Lu, Dongzhe Fei, Jinlong Liu, Long Li, Zecun Information Engineering University Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (数字)9781665422079

ISBN: (纸本)9781665422079

Due to the simplicity of implementation and high threat level, SQL injection attacks are one of the oldest, most prevalent, and most destructive types of security attacks on Web-based information systems. With the continuous development and maturity of artificial intelligence technology, it has been a general trend to use AI technology to detect SQL injection. The selection of the sample set is the deciding factor of whether AI algorithms can achieve good results, but dataset with tagged specific category labels are difficult to obtain. This paper focuses on data augmentation to learn similar feature representations from the original data to improve the accuracy of classification models. In this paper, deep convolutional generative adversarial networks combined with genetic algorithms are applied to the field of Web vulnerability attacks, aiming to solve the problem of insufficient number of SQL injection samples. This method is also expected to be applied to sample generation for other types of vulnerability attacks. © 2022 IEEE.

关键词： Generative adversarial networks

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IBM Small-Scale Superconducting Quantum Computer Not Gate Error Test

IBM Small-Scale Superconducting Quantum Computer Not Gate Er...

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2021 International Conference on Electronic Communication, Computer Science and Technology, ECCST 2021

作者： He, Ming Liu, Xiaonan Wang, Junchao An, Jiale State Key Laboratory of Mathematical Engineering and Advanced Computing Information Engineering University Henan Zhengzhou450001 China

Quantum NOT gates play an important role in the process of quantum information conversion. However, when the X-gate operation is executed on a real quantum computer, there is a large deviation between the actual operation result and the theory, which will lead to inaccurate results when the quantum algorithm containing the X-gate operation is executed. In order to facilitate users to understand the error fluctuations of the X gate in time before executing the quantum algorithm containing the X gate operation on the IBM quantum cloud platform, this paper proposes a method to measure the X gate error. By measuring the X-gate error of four small-scale superconducting quantum computers on the back end of the IBM quantum cloud platform, analyze the degree of fluctuation of the actual measurement value of the quantum device;at the same time, under different execution times shots, the influence of the X-gate test is analyzed. The test results show that the measured value of each qubit of different quantum devices fluctuates to different degrees;the execution times of shots are different, and the test results of X-gate error will be affected to different degrees. This test method helps users select the optimal performance of the qubits before executing quantum algorithms with X gate on IBM's small-scale quantum computers. © Published under licence by IOP Publishing Ltd.

关键词： Errors

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On Isodual Double Toeplitz Codes

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Journal of Systems Science & Complexity 2024年第5期37卷 2196-2206页

作者： SHI Minjia XU Li SOLÉ Patrick Key Laboratory of Intelligent Computing and Signal Processing Ministry of EducationSchool of Mathematical SciencesAnhui UniversityHefei 230601China State Key Laboratory of Information Security Institute of Information EngineeringChinese Academy of SciencesBeijing 100093China CNRS University of Aix MarseilleCentrale MarseilleI2MMarseille 13284France

Double Toeplitz(shortly DT)codes are introduced here as a generalization of double circulant *** authors show that such a code is isodual,hence formally self-dual(FSD).FSD codes form a far-reaching generalization of self-dual codes,the most important class of codes of rate ***-dual DT codes are characterized as double circulant or double ***,even binary DT codes are characterized as double *** examples obtained by exhaustive search show that the codes constructed have best-known minimum distance,up to one unit,amongst formally self-dual codes,and sometimes improve on the known *** q=2,the authors find four improvements on the best-known values of the minimum distance of FSD *** F4 an explicit construction of DT codes,based on quadratic residues in a prime field,performs equally *** authors show that DT codes are asymptotically good over ***,the authors construct DT codes arbitrarily close to the asymptotic Varshamov-Gilbert bound for codes of rate one half.

关键词： Double circulant codes double Toeplitz codes isodual codes formally self-dual codes

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An algorithm/hardware co-optimized method to accelerate CNNs with compressed convolutional weights on FPGA

An algorithm/hardware co-optimized method to accelerate CNNs...

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作者： Shang, Jiangwei Zhang, Zhan Zhang, Kun Li, Chuanyou Qian, Lei Liu, Hongwei School of Computer Science and Technology Harbin Institute of Technology Harbin China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China School of Computer Science and Engineering Southeast University Nanjing China

Convolutional neural networks (CNNs) have shown remarkable advantages in a wide range of domains at the expense of huge parameters and computations. Modern CNNs still tend to be more complex and larger to achieve better inference accuracy. However, the complex and large structures of CNNs could slow down the inference speed. Recently, Compressing the convolutional weights to be sparse by pruning the unimportant parameters has been demonstrated as an efficient way to reduce the computations of CNNs. On the other hand, field-programmable gate arrays (FPGAs) have been a popular hardware platform to accelerate CNN inference. In this paper, we propose an algorithm/hardware co-optimized method for accelerating CNN inference on FPGAs. For the algorithm, we take advantage of unstructured and structured parameter sparsifying methods to achieve high sparsity and keep the regularity of convolutional weights. Correspondingly, hardware-friendly index representations of sparse convolutional weights are proposed. For the hardware architecture, we propose row-wise input-stationary dataflow, which is tightly coupled with the algorithm. A row-wise computing engine (RConv Engine) is proposed, which is based on the dataflow. Inside the RConv Engine, the scalar-vector structure is applied to implement the basic processing elements (PEs). To flexibly calculate the feature map with various sizes, the PEs are organized in a 2D structure with two work modes. The experimental results demonstrate that our co-optimized method implements high sparsity of convolutional weights, and the computing engine achieves high computation efficiency. Compared with other accelerators, our co-optimized method implements a 10.9 (Formula presented.) speedup on FPS at most with the highest sparsity of convolutional weights and negligible accuracy loss. © 2024 John Wiley & Sons Ltd.

关键词： Engines

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