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5th Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2024

作者： Su, Wenyi Zhang, Lu Wang, Yao Zhu, Liping Li, Guodong Guilin University of Electronic Technology School of Mathematics and Computing Science Guilin541004 China Changji University School of Mathematics and Data Science Changji831100 China

ISBN: (纸本)9798350374407

With the widespread adoption of the internet, humanity has entered an irreversible era of information. Highquality pseudorandom numbers play a crucial role in ensuring secure communication, necessitating pseudorandom number generators with excellent performance. Therefore, research on pseudorandom number generators based on chaos theory is of vital importance. In this paper, a pseudorandom sequence generator based on the Cross-Coupled Chebyshev Lattice (CCML) model is proposed. CCML is a typical model in spatiotemporal chaos and exhibits better chaotic characteristics compared to low-dimensional chaotic systems. The generator first utilizes the classical Logistic map to generate the initial state values for each lattice cell. It then employs the Tent map to dynamically perturb the coupling coefficients between the lattice cells, enhancing the chaotic properties of the system. The local function in the model is a transformed Chebyshev map. The generator combines several one-dimensional chaotic mappings to demonstrate the excellent performance of a composite system. The pseudo-random sequences generated by the generator obtain high scores in the $0-1$ test, and the spectral entropy is significantly higher than that of other classical chaotic mappings, reaching a level close to that of white noise. It shows that the generator is capable of generating chaotic sequences with high complexity. © 2024 IEEE.

关键词： White noise

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Bicriteria Algorithms for Approximately Submodular Cover Under Streaming Model

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Tsinghua Science and technology 2023年第6期28卷 1030-1040页

作者： Yijing Wang Xiaoguang Yang Hongyang Zhang Yapu Zhang Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing 100190China School of Mathematics and Statistics Ningbo UniversityNingbo 315211China Beijing Institute for Scientific and Engineering Computing Beijing University of TechnologyBeijing 100124China

In this paper,we mainly investigate the optimization model that minimizes the cost function such that the cover function exceeds a required threshold in the set cover problem,where the cost function is additive linear,and the cover function is non-monotone approximately *** study the problem under streaming model and propose three bicriteria approximation ***,we provide an intuitive streaming algorithm under the assumption of known optimal objective *** intuitive streaming algorithm returns a solution such that its cover function value is no less thanα(1−ϵ)times threshold,and the cost function is no more than(2+ϵ)^(2)/(ϵ^(2)ω^(2))⋅κ,whereκis a value that we suppose for the optimal solution andαis the approximation ratio of an algorithm for unconstrained maximization problem that we can call *** we present a bicriteria streaming algorithm scanning the ground set multi-pass to weak the assumption that we guess the optimal objective value in advance,and maintain the same bicriteria approximation *** we modify the multi-pass streaming algorithm to a single-pass one without compromising the performance ***,we also propose some numerical experiments to test our algorithm’s performance comparing with some existing methods.

关键词： approximately submodular linear additive streaming model bicriteria algorithm

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Scaled aggregation operations over three-dimensional extended intuitionistic fuzzy index matrices

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Journal of Intelligent and Fuzzy Systems 2025年第1-2期48卷 123-139页

作者： Shi, Xiaolong Kosari, Saeed Rangasamy, Parvathi Nivedhaa, R.K. Rashmanlou, Hossein Institute of Computing Science and Technology Guangzhou University Guangzhou China Department of Mathematics Vellalar College for Women Tamil Nadu Erode India School of Physics Damghan University Damghan Iran

Modern image processing techniques are improving beyond old methods, which include advanced approaches, for example deep learning. Convolutional Neural Networks (CNNs) are excellent at automatic feature extraction, whereas Generative Adversarial Networks (GANs) produce realistic images. Transfer learning uses pre-trained models, whereas semantic segmentation identifies pixels in images. Super-resolution, style transfer, and attention mechanisms can increase the quality of images and understanding. Adversarial defenses address purposeful manipulations, while 3D image processing handles three-dimensional data. These advancements make use of improved computational power and massive datasets to revolutionize image processing capabilities. Traditional image processing algorithms frequently fail to handle the complex and multidimensional structure of color images, particularly when dealing with uncertainty and imprecision. In this study, the 3D-EIFIM frame work is extented and scaled aggregation operations 3D-EIFIM tailored for image data are proposed. By representing each pixel as an entry of 3D-EIFIM and applying aggregation techniques to enable more effective image analysis, manipulation, and enhancement. The practical implications of this research are significant, as it can lead to advancements in fields such as computer vision, medical imaging, and remote sensing. © 2025 – IOS Press. All rights reserved.

关键词： Semantic Segmentation

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Two-step Runge–Kutta methods for Volterra integro-differential equations

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International Journal of Computer mathematics 2024年第1期101卷 37-55页

作者： Wen, Jiao Huang, Chengming Guan, Hongbo College of Mathematics and Information Science Zhengzhou University of Light Industry Zhengzhou China School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan China

In this paper, we investigate two-step Runge–Kutta methods to solve Volterra integro-differential equations. Two-step Runge–Kutta methods increase the order of convergence in comparing the classical Runge–Kutta method without extra computational cost. First, the local order conditions and convergence theorem are derived. Then, stability properties of two-step Runge–Kutta methods corresponding to the basic and convolution test equations are analysed. Furthermore, one-stage method with order four and two-stage method with order six are constructed and we plot the stability regions. Numerical examples are presented to confirm the theoretical analyses. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Stability

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Multi-Perspective Data Fusion Framework Based on Hierarchical BERT: Provide Visual Predictions of Business Processes

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Computers, Materials & Continua 2024年第1期78卷 1227-1252页

作者： Yongwang Yuan Xiangwei Liu Ke Lu School of Mathematics and Big Data Anhui University of Science and TechnologyHuainan232001China School of Economics and Management Anhui University of Science and TechnologyHuainan232001China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji UniversityShanghai201804China

Predictive Business Process Monitoring(PBPM)is a significant research area in Business Process Management(BPM)aimed at accurately forecasting future behavioral *** present,deep learning methods are widely cited in PBPM research,but no method has been effective in fusing data information into the control flow for multi-perspective process ***,this paper proposes a process prediction method based on the hierarchical BERT and multi-perspective data ***,the first layer BERT network learns the correlations between different category attribute ***,the attribute data is integrated into a weighted event-level feature vector and input into the second layer BERT network to learn the impact and priority relationship of each event on future predicted ***,the multi-head attention mechanism within the framework is visualized for analysis,helping to understand the decision-making logic of the framework and providing visual ***,experimental results show that the predictive accuracy of the framework surpasses the current state-of-the-art research methods and significantly enhances the predictive performance of BPM.

关键词： Business process prediction monitoring deep learning attention mechanism BERT multi-perspective

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Design and Application of Pseudo-Random Sequence Base on Logistic Map 5

Design and Application of Pseudo-Random Sequence Base on Log...

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5th International Conference on Artificial Intelligence and Advanced Manufacturing, AIAM 2023

作者： Pan, Qiufeng Chen, Xiangkun Luo, Linbin Xu, Wenxia School of Mathematics and Computing Science Guilin University of Electronic Technology Guilin China

ISBN: (纸本)9781839539848

Digital image is an important information carrier. In order to prevent information from being stolen and leading to information leakage, it’s very important to protect the digital image. This paper proposes a pseudo-random sequence based on logistic map and studies the encryption algorithm. First, use the logistic map to generate a logistic chaotic sequence, remove the previously poor chaotic terms and obtain a chaotic sequence with good chaotic properties. Second, sort the chaotic sequence according to certain rules and use the index of the sorted sequence to scramble the pixels of the plaintext image. Then, diffuse the scrambled image pixel matrix. By combining chaotic sequences and using the bitwise XOR method, the distribution of grayscale values in the scrambled image is changed to further improve the encryption effect. Finally, combined with the characteristics of S-box, the pixel values of the digital image are changed and complete a further encryption process. After a series of operations such as scrambling, diffusion, and pixel value replacement, the ciphertext image has reached a good confidentiality state. This paper comprehensively evaluates the encryption effect and security of the method proposed in this paper from four aspects: key analysis, histogram analysis, correlation coefficient analysis, and information entropy analysis. It is believed that the encryption effect of the algorithm is good. © The Institution of Engineering & technology 2023.

关键词： Cryptography

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PMBM FILTER WITH TREE TRAJECTORY MODEL FOR SPAWNING EXTENDED TARGET TRACKING

PMBM FILTER WITH TREE TRAJECTORY MODEL FOR SPAWNING EXTENDED...

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IET International Radar Conference 2023, IRC 2023

作者： Cai, Ruhua Yang, Yingzhuang Wu, Sunyong Xue, Qiutiao Liu, Jinxin School of Mathematics and Computing Science Guilin University of Electronic Technology Guilin China

ISBN: (纸本)9781839539954

In extended target tracking, target spawning is a significant event. The conventional Poisson multi-Bernoulli mixture (PMBM) filter encounters challenges in determining the prior distributions for spawning extended targets and experiences a degradation in tracking performance within clutter environments. This paper proposes a modified PMBM method known as the Extended Target Tree Trajectory PMBM filter (ET-TrPMBM). This method entails the representation of the complete trajectory's continuous information and genealogies of an original extended target, as well as its subsequently spawning descendants, as a tree trajectory variable, which is employed as an input within the PMBM recursion process. To effectively extract the trajectory of an individual spawning target from the intricate tree trajectory, an independent and identically distributed (IID) Bernoulli cluster is deployed. This cluster operates as an approximation tool for the posterior distribution of the tree trajectory, and the optimal approximation is achieved by the KL divergence minimisation. Furthermore, this study encompasses the application of gamma Gaussian inverse Wishart (GGIW) distribution within the context of tree trajectories, and provides the close-form solutions for the ET-TrPMBM filter. Simulation results verify the effectiveness of the proposed method. © The Institution of Engineering & technology 2023.

关键词： Target tracking

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360-Degree Point Cloud Compression with Adaptive Rate Control Optimisation for Regions of Interest 25

360-Degree Point Cloud Compression with Adaptive Rate Contro...

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25th International Conference on Digital Image computing: Techniques and Applications, DICTA 2024

作者： Nabil, Rashidul Hasan Murshed, Manzur Paul, Manoranjan Luo, Wei School of Information Technology Deakin University VIC Australia School of Computing Mathematics and Engineering Charles Sturt University NSW Australia

ISBN: (纸本)9798350379037

The growing use of point cloud technology across various sectors has emerged as a significant research area, focusing on compressing point clouds for improved storage and transmission. Geometry-based point cloud compression (G-PCC), one of the latest standards for point cloud compression, has been considered to compress any static point clouds. G-PCC is primarily designed for general purposes, employing a uniform quantisation strategy that does not account for object positions. This is because most point clouds are captured from various angles, focusing on a central location with a limited number of objects. However, applications such as driverless cars use 360-degree cameras to capture more objects at different distances, making it essential to preserve the quality of objects in different regions, or Regions of Interest (ROIs). In this paper, we propose a non-uniform quantisation strategy within the G-PCC framework to maintain high-quality ROIs without compromising overall rate-distortion performance. Our experimental results show that the proposed method improves PSNR-D1 and PSNR-D2 of ROI by more than 2.5 dB while maintaining the overall rate-distortion performance of G-PCC. © 2024 IEEE.

关键词： Cloud platforms

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ASYMPTOTICAL STABILITY OF NEUTRAL REACTION-DIFFUSION EQUATIONS WITH PCAS AND THEIR FINITE ELEMENT METHODS

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Acta Mathematica Scientia 2023年第4期43卷 1865-1880页

作者：韩豪张诚坚 School of Mathematics and Statistics Huazhong University of Science and TechnologyWuhan 430074China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and TechnologyWuhan 430074China

This paper focuses on the analytical and numerical asymptotical stability of neutral reaction-diffusion equations with piecewise continuous ***,for the analytical solutions of the equations,we derive their expressions and asymptotical stability ***,for the semi-discrete and one-parameter fully-discrete finite element methods solving the above equations,we work out the sufficient conditions for assuring that the finite element solutions are asymptotically ***,with a typical example with numerical experiments,we illustrate the applicability of the obtained theoretical results.

关键词： neutral reaction-diffusion equations piecewise continuous arguments asymptotical stability finite element methods numerical experiment

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Cherenkov Radiation:A Stochastic Differential Model Driven by Brownian Motions

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Computer Modeling in Engineering & Sciences 2023年第4期135卷 155-168页

作者： Qingqing Li Zhiwen Duan Dandan Yang School of Mathematics and Statistics Huazhong University of Science and TechnologyWuhan430074China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and TechnologyWuhan430074China

With the development of molecular imaging,Cherenkov optical imaging technology has been widely *** studies regard the partial boundary flux as a stochastic variable and reconstruct images based on the steadystate diffusion *** this paper,time-variable will be considered and the Cherenkov radiation emission process will be regarded as a stochastic *** on the original steady-state diffusion equation,we first propose a stochastic partial differential *** numerical solution to the stochastic partial differential model is carried out by using the finite element *** the time resolution is high enough,the numerical solution of the stochastic diffusion equation is better than the numerical solution of the steady-state diffusion equation,which may provide a new way to alleviate the problem of Cherenkov luminescent imaging *** addition,the process of generating Cerenkov and penetrating in vitro imaging of 18 F radionuclide inmuscle tissue are also first proposed by GEANT4Monte *** result of the GEANT4 simulation is compared with the numerical solution of the corresponding stochastic partial differential equations,which shows that the stochastic partial differential equation can simulate the corresponding process.

关键词： Cherenkov radiation stochastic partial differential equations numerical approximation and analysis GEANT4 Monte Carlo simulation

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