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Measuring Financial Systemic Risk:Net Liability Clearing Mechanism and Contagion Effect

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Journal of Systems science & Complexity 2024年第3期37卷 1114-1146页

作者： MA Jiali ZHU Shushang LI Duan College of Big data Statistics Guizhou University of Finance and EconomicsGuiyang 550025China school of Business Sun Yat-Sen UniversityGuangzhou 510275China school of data science City University of Hong KongHong Kong 999077China

Following the framework of E-N model(Eisenberg and Noe,2001),the authors consider a new clearing mechanism based on net liabilities among financial institutions since the liabilities between the counterparties should be deducted accordingly when clearing in *** the basis for systemic risk measurement,similar to the original E-N model,the authors first establish some good properties for the clearing payment vector according to a more general ***,the authors investigate how risk spreads among institutions through the liability network forming the risk contagion ***,the authors illustrate with a specific example that the original E-N clearing mechanism may misidentify the systemic important institutions,and theoretically show that it may also overestimate the risk compared with the netting clearing mechanism.

关键词： Clearing mechanism contagion net liability network systemic risk

Limit Theorems for Critical Galton-Watson Processes with Immigration Stopped at Zero

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Acta Mathematica Sinica,English Series 2024年第2期40卷 435-450页

作者： Dou Dou LI Mei ZHANG Xian Yu ZHANG College of Statistics and data science Faculty of ScienceBeijing University of TechnologyBeijing 100124P.R.China Laboratory of mathematics and Complex Systems(Ministry of Education) School of Mathematical SciencesBeijing Normal UniversityBeijing 100875P.R.China

In this paper,we consider a critical Galton-Watson branching process with immigration stopped at zero *** precise estimation on the probability generating function of the n-th population are obtained,and the tail prob... 详细信息

关键词： Branching immigration critical life period limit theorems

Practical approach for detecting k-nonseparability of multipartite quantum states

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science China(Physics,Mechanics & Astronomy) 2024年

作者： Jie Guo Jinchuan Hou Xiaofei Qi Kan He College of mathematics Taiyuan University of Technology school of mathematics and Statistics Shanxi University Key Laboratory of Complex Systems and data science of Ministry of Education Shanxi University

The instantaneous detection of entanglement in quantum states poses a significant challenge in the fields of quantum computation and quantum information, and there are no practical methods or tools to complete this task satisfactorily so far. We propose a sufficient and necessary criterion of k-nonseparability for any n-partite finite or infinite dimensional systems, 2≤k≤n. This criterion serves as the foundation for a practical scheme designed to detect entanglement and k-nonseparability across multipartite finite-dimensional systems. To exemplify the application of our scheme, we have developed a software tool that facilitates swift and precise identification of entanglement, k-nonseparability, and genuine entanglement within n-qubit systems, specifically tailored for systems with 2≤n≤4.

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A NOTE ON THE GENERAL STABILIZATION OF DISCRETE FEEDBACK CONTROL FOR NON-AUTONOMOUS HYBRID NEUTRAL STOCHASTIC SYSTEMS WITH A DELAY

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Acta Mathematica Scientia 2024年第3期44卷 1145-1164页

作者：冯立超张春艳曹进德武志辉 College of science North China University of Science and TechnologyTangshan063210China school of mathematics Southeast UniversityNanjing210096China Department of mathematics Harbin University of Science and TechnologyHarbin150080China

Discrete feedback control was designed to stabilize an unstable hybrid neutral stochastic differential delay system(HNSDDS) under a highly nonlinear constraint in the H_∞ and exponential ***,the existing work just adapted to autonomous cases,and the obtained results were mainly on exponential *** comparison with autonomous cases,non-autonomous systems are of great interest and represent an important ***,discrete feedback control has here been adjusted with a time factor to stabilize an unstable non-autonomous HNSDDS,in which new Lyapunov-Krasovskii functionals and some novel technologies are *** should be noted,in particular,that the stabilization can be achieved not only in the routine H_∞ and exponential forms,but also the polynomial form and even a general form.

关键词： hybrid neutral stochastic differential delay system discrete feedback control general stabilization polynomial stabilization

ON THE EMPTY BALLS OF A CRITICAL OR SUBCRITICAL BRANCHING RANDOM WALK

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Acta Mathematica Scientia 2024年第5期44卷 2051-2072页

作者： Shuxiong ZHANG Jie XIONG school of mathematics and Statistics Anhui Normal UniversityWuhu241002China Department of mathematics and SUSTech International Center for mathematics Southern University of Science and TechnologyShenzhen518055China

Let{Z_(n)}_(n)≥0 be a critical or subcritical d-dimensional branching random walk started from a Poisson random measure whose intensity measure is the Lebesugue measure onℝ^(d).Denote by R_(n):=sup{u>0:Z_(n)({x∈ℝ^(... 详细信息

关键词： empty ball dimension branching random walk super-Brownian motion

CBA: multi source fusion model for fast and intelligent target intention identification

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Journal of Systems Engineering and Electronics 2024年第2期35卷 406-416页

作者： WAN Shichang LI Qingshan WANG Xuhua LU Nanhua school of Computer science and Technology Xidian UniversityXi’an 710071China school of mathematics and Computer Application Shangluo UniversityShangluo 726000China

How to mine valuable information from massive multisource heterogeneous data and identify the intention of aerial targets is a major research focus at present. Aiming at the longterm dependence of air target intention recognition, this paper deeply explores the potential attribute features from the spatiotemporal sequence data of the target. First, we build an intelligent dynamic intention recognition framework, including a series of specific processes such as data source, data preprocessing,target space-time, convolutional neural networks-bidirectional gated recurrent unit-atteneion (CBA) model and intention recognition. Then, we analyze and reason the designed CBA model in detail. Finally, through comparison and analysis with other recognition model experiments, our proposed method can effectively improve the accuracy of air target intention recognition,and is of significance to the commanders’ operational command and situation prediction.

关键词： intention massive data deep network artificial intelligence

FNNWV: farthest-nearest neighbor-based weighted voting for class-imbalanced crowdsourcing

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science China(Information sciences) 2024年第10期67卷 172-188页

作者： Wenjun ZHANG Liangxiao JIANG Ziqi CHEN Chaoqun LI school of Computer science China University of Geosciences Key Laboratory of Artificial Intelligence Ministry of Education school of mathematics and Physics China University of Geosciences

In crowdsourcing scenarios, we can hire crowd workers to label crowdsourced tasks and then use label integration algorithms to infer the integrated label for each instance in the tasks. As more and more label integration algorithms are proposed, the performance of inference based only on the information of the inferred instance gradually converges. Recent algorithms attempt to exploit the information of the inferred instance's nearest neighbors to infer and achieve good performance. However, when crowdsourced tasks are class-imbalanced, negative instances are more easily to occur in the nearest neighbors because negative instances are the majority, and thus recent algorithms are more easily biased toward the negative class. To this end, in this paper, we propose a novel label integration algorithm called farthest-nearest neighbor-based weighted voting(FNNWV) for class-imbalanced crowdsourcing. Specifically, FNNWV considers the nearest neighbors to be more similar to the inferred instance and thus uses them to vote ayes in weighted voting. Yet at the same time, FNNWV considers the farthest neighbors to be more different from the inferred instance and thus uses them to vote nays in weighted voting. Since negative instances are easier to occur in both the nearest neighbors and the farthest neighbors, FNNWV weakens the effect of negative instances by voting ayes and nays. The experimental results on 22 simulated and one real-world crowdsourced datasets show that FNNWV significantly outperforms all the other state-of-the-art competitors.

关键词： crowdsourcing label integration nearest neighbor farthest neighbor weighted voting

BSTFNet:An Encrypted Malicious Traffic Classification Method Integrating Global Semantic and Spatiotemporal Features

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Computers, Materials & Continua 2024年第3期78卷 3929-3951页

作者： Hong Huang Xingxing Zhang Ye Lu Ze Li Shaohua Zhou school of Computer science and Engineering Sichuan University of Science&EngineeringYibin644002China school of mathematics and Statistics Sichuan University of Science&EngineeringYibin644002China

While encryption technology safeguards the security of network communications,malicious traffic also uses encryption protocols to obscure its malicious *** address the issues of traditional machine learning methods relying on expert experience and the insufficient representation capabilities of existing deep learning methods for encrypted malicious traffic,we propose an encrypted malicious traffic classification method that integrates global semantic features with local spatiotemporal features,called BERT-based Spatio-Temporal Features Network(BSTFNet).At the packet-level granularity,the model captures the global semantic features of packets through the attention mechanism of the Bidirectional Encoder Representations from Transformers(BERT)*** the byte-level granularity,we initially employ the Bidirectional Gated Recurrent Unit(BiGRU)model to extract temporal features from bytes,followed by the utilization of the Text Convolutional Neural Network(TextCNN)model with multi-sized convolution kernels to extract local multi-receptive field spatial *** fusion of features from both granularities serves as the ultimate multidimensional representation of malicious *** approach achieves accuracy and F1-score of 99.39%and 99.40%,respectively,on the publicly available USTC-TFC2016 dataset,and effectively reduces sample confusion within the Neris and Virut *** experimental results demonstrate that our method has outstanding representation and classification capabilities for encrypted malicious traffic.

关键词： Encrypted malicious traffic classification bidirectional encoder representations from transformers text convolutional neural network bidirectional gated recurrent unit

The Necessary and Sufficient Conditions of Exponential Stability for Heat and Wave Equations with Memory

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Journal of Systems science & Complexity 2024年第3期37卷 1037-1051页

作者： LI Lingfei ZHANG Xiaoyi ZHOU Xiuxiang school of science Northeast Electric Power UniversityJilin 132012China school of mathematics and Statistics Lingnan Normal UniversityZhanjiang 524048China

This paper is addressed to a study of the stability of heat and wave equations with *** necessary and sufficient conditions of the exponential stability are investigated by the theory of Laplace transform. The results show that the stability depends on the decay rate and the coefficient of the kernel functions of the memory. Besides, the feedback stabilization of the heat equation is obtained by constructing finite dimensional controller according to unstable eigenvalues. This stabilizing procedure is easy to operate and can be applicable for other parabolic equations with memory.

关键词： Memory stability stabilization