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Alarm Log Data Augmentation Algorithm Based on a GAN Model and Apriori

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Journal of Computer Science & technology 2024年第4期39卷 951-966页

作者： Yang Yang Yu-Ting Li Yong-Hua Huo Zhi-Peng Gao Lan-Lan Rui State Key Laboratory of Network and Switching technology Beijing University of Posts and TelecommunicationsBeijing 100876China The 54th Research Institute of China Electronics technology Group Corporation Shijiazhuang 050081China

The complexity of alarm detection and diagnosis tasks often results in a lack of alarm log *** to the strong rule associations inherent in alarm log data,existing data augmentation algorithms cannot obtain good results for alarm log *** address this problem,this paper introduces a new algorithm for augmenting alarm log data,termed APRGAN,which combines a generative adversarial network(GAN)with the Apriori *** generates alarm log data under the guidance of rules mined by the rule ***,we propose a new dynamic updating mechanism to alleviate the mode collapse problem of the *** addition to updating the real reference dataset used to train the discriminator in the GAN,we dynamically update the parameters and the rule set of the Apriori algorithm according to the data generated in each *** extensive experimentation on two public datasets,it is demonstrated that APRGAN surpasses other data augmentation algorithms in the domain with respect to alarm log data augmentation,as evidenced by its superior performance on metrics such as BLEU,ROUGE,and METEOR.

关键词： data augmentation alarm log data Apriori generative adversarial network(GAN)

A gas sensing neural circuit for an olfactory neuron

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Communications in Theoretical Physics 2024年第10期76卷 26-40页

作者： Xi-Kui Hu Song Zhu Juan Yang Zhao Yao Ping Zhou Jun Ma School of Science Chongqing University of Posts and Telecommunications School of Physics and Electronics Central South University Department of Physics Lanzhou University of Technology

A gas sensor can convert external gas concentration or species into electric voltage or current signals by physical adsorption or chemical changes. As a result, a gas sensor in a nonlinear circuit can be used as a sensitive sensor for detecting external gas signals from the olfactory system. In this paper, a gas sensor and a field-effect transistor are incorporated into a simple FithzHugh–Nagumo neural circuit for capturing and encoding external gas signals. An improved functional neural circuit is obtained, and the effect of gas concentration, gas species and neuronal activity can be discerned as the gate voltage, threshold voltage and activation coefficient of the field-effect transistor, respectively. The gas concentration can affect the neural activities from quiescent to normal working and, finally, to saturation state in bursting, spiking, periodic and chaotic firings with different frequencies. The effects of gas species and neuronal activity on the firing state can also be achieved in this functional neural circuit. In addition, variations in the gate voltage, threshold voltage and activation coefficient can cause switching between different firing modes. These results can be helpful in designing artificial olfactory devices for bionic gas recognition and other coupled systems arising in applied sciences.

关键词： bifurcation field-effect transistor gas sensor olfactory neural circuit

Cross-Modal Graph Semantic Communication Assisted by Generative AI in the Metaverse for 6G

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Research 2024年第2期2024卷 19-27页

作者： Mingkai Chen Minghao Liu Congyan Wang Xingnuo Song Zhe Zhang Yannan Xie Lei Wang Key Laboratory of Broadband Wireless Communication and Sensor Network technology Nanjing University of Posts and TelecommunicationsNanjng 210003China State Key Laboratory of Organic Electronics and Information Displays&Institute of Advanced Materials(IAM) Nanjing University of Posts and TelecommunicationsNanjing 210023China

Recently, the development of the Metaverse has become a frontier spotlight, which is an important demonstration of the integration innovation of advanced technologies in the Internet. Moreover, artificial intelligence (AI) and 6G communications will be widely used in our daily lives. However, the effective interactions with the representations of multimodal data among users via 6G communications is the main challenge in the Metaverse. In this work, we introduce an intelligent cross-modal graph semantic communication approach based on generative AI and 3-dimensional (3D) point clouds to improve the diversity of multimodal representations in the Metaverse. Using a graph neural network, multimodal data can be recorded by key semantic features related to the real scenarios. Then, we compress the semantic features using a graph transformer encoder at the transmitter, which can extract the semantic representations through the cross-modal attention mechanisms. Next, we leverage a graph semantic validation mechanism to guarantee the exactness of the overall data at the receiver. Furthermore, we adopt generative AI to regenerate multimodal data in virtual scenarios. Simultaneously, a novel 3D generative reconstruction network is constructed from the 3D point clouds, which can transfer the data from images to 3D models, and we infer the multimodal data into the 3D models to increase realism in virtual scenarios. Finally, the experiment results demonstrate that cross-modal graph semantic communication, assisted by generative AI, has substantial potential for enhancing user interactions in the 6G communications and Metaverse.

关键词： modal frontier guarantee

Confidence Estimation Transformer for Long-Term Renewable Energy Forecasting in Reinforcement Learning-based Power Grid Dispatching

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CSEE Journal of Power and Energy Systems 2024年第4期10卷 1502-1513页

作者： Xinhang Li Nan Yang Zihao Li Yupeng Huang Zheng Yuan Xuri Song Lei Li Lin Zhang Beijing University of Posts and telecommunications Beijing 100876China Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation technology

Expansion of renewable energy could help realize the goals of peaking carbon dioxide emissions and carbon *** existing grid dispatching methods integrating short-term renewable energy prediction and reinforcement learning(RL)have been proven to alleviate the adverse impact of energy fluctuations ***,these methods omit long-term output prediction,which leads to stability and security problems on optimal power *** paper proposes a confidence estimation Transformer for long-term renewable energy forecasting in reinforcement learning-based power grid dispatching(Conformer-RLpatching).Conformer-RLpatching predicts long-term active output of each renewable energy generator with an enhanced Transformer to ensure stable operation of the hybrid energy grid and improve the utilization rate of renewable energy,thus boosting dispatching ***,a confidence estimation method is proposed to reduce the prediction error of renewable ***,a dispatching necessity evaluation mechanism is put forward to decide whether the active output of a generator needs to be *** carried out on the SG-126 power grid simulator show that Conformer-RLpatching achieves great improvement over the second best algorithm DDPG in security score by 25.8%and achieves a better total reward compared with the golden medal team in the power grid dispatching competition sponsored by State Grid Corporation of China under the same simulation *** are outsourced in https://***/BUPT-ANTlab/Conformer-RLpatching.

关键词： Conformer-RLpatching optimal power flow reinforcement learning renewable energy prediction

Nonlinear empirical failure criterion for rocks under triaxial compression

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International Journal of Mining Science and technology 2024年第3期34卷 351-369页

作者： Hongtao Liu Zhou Han Zijun Han Zihan Chen Qinyu Liu Hongkai Zhang Rongguang Zhang Linfeng Guo School of Energy&Mining Engineering China University of Mining and Technology-BeijingBeijing 100083China China National Coal association Beijing 100010China

Based on existing triaxial compression experimental data,a new empirical failure criterion with wide applicability was proposed considering hydrostatic pressure,second stress invariance,and maximum shear *** fitting evaluation indicators were used to verify the consistency of the new failure criterion,and the differences with the other 6 failure criteria were *** characteristics of the new failure criteria in the principal stress space were finally *** results indicate that(1)the new failure criterion exhibits strong predictive ability for triaxial experiments and has good applicability for both intact and jointed rocks;(2)the influence of hydrostatic pressure on the failure surface exhibits a non-linear trend,and different hydrostatic pressure also exhibits different distribution patterns on the deviatoric stress plane,with a distribution characteristic pattern of hexagonal snowflake-regular *** maximum shear stress has a torsional effect on the new criterion,in the three-dimensional failure *** parameters a and b of the rock have an impact on the failure surface morphology of the new criterion function on the offset surface.

关键词： surface. criterion hydrostatic

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A New Framework for Software Vulnerability Detection Based on an Advanced Computing

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Computers, Materials & Continua 2024年第6期79卷 3699-3723页

作者： Bui Van Cong Cho do Xuan Department of Information technology University of Economics and Technical IndustriesHanoi100000Vietnam Faculty of Information Security Posts and Telecommunications Institute of TechnologyHanoi100000Vietnam

The detection of software vulnerabilities written in C and C++languages takes a lot of attention and interest *** paper proposes a new framework called DrCSE to improve software vulnerability *** uses an intelligent computation technique based on the combination of two methods:Rebalancing data and representation learning to analyze and evaluate the code property graph(CPG)of the source code for detecting abnormal behavior of software *** do that,DrCSE performs a combination of 3 main processing techniques:(i)building the source code feature profiles,(ii)rebalancing data,and(iii)contrastive *** which,the method(i)extracts the source code’s features based on the vertices and edges of the *** method of rebalancing data has the function of supporting the training process by balancing the experimental ***,contrastive learning techniques learn the important features of the source code by finding and pulling similar ones together while pushing the outliers *** experiment part of this paper demonstrates the superiority of the DrCSE Framework for detecting source code security vulnerabilities using the Verum *** a result,the method proposed in the article has brought a pretty good performance in all metrics,especially the Precision and Recall scores of 39.35%and 69.07%,respectively,proving the efficiency of the DrCSE *** performs better than other approaches,with a 5%boost in Precision and a 5%boost in ***,this is considered the best research result for the software vulnerability detection problem using the Verum dataset according to our survey to date.

关键词： Source code vulnerability source code vulnerability detection code property graph feature profile contrastive learning data rebalancing

Automatically identifying imperfections and attacks in practical quantum key distribution systems via machine learning

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Science China(Information Sciences) 2024年第10期67卷 359-372页

作者： Jiaxin XU Xiao MA Jingyang LIU Chunhui ZHANG Hongwei LI Xingyu ZHOU Qin WANG Institute of Quantum Information and technology Nanjing University of Posts and Telecommunications Telecommunication and Networks National Engineering Research CenterNanjing University of Posts and Telecommunications Henan Key Laboratory of Quantum Information and Cryptography Strategic Support Force Information Engineering University

The realistic security of quantum key distribution(QKD) systems is currently a hot research topic in the field of quantum communications. There are always defects in practical devices, and eavesdroppers can make use of the security risk points of various devices to obtain key information. To date, current types of security analysis tend to analyze each security risk point individually, thereby posing great challenges for the overall security evaluation of QKD systems. In this paper, for the first time, we employ machine learning algorithms to identify the defects of different devices and certain attacks in real time, with an accuracy of 98%. It provides a novel solution for the practical security evaluation of QKD systems, thereby addressing the bottleneck problem of multiple risk points being difficult to address simultaneously in QKD systems,thus paving the way for the future large-scale application of quantum communication networks.

关键词： quantum key distribution device imperfections eavasdropping attacks real-time detection machine learning algorithms

Distributed Nash Equilibrium Seeking Strategies Under Quantized Communication

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 103-112页

作者： Maojiao Ye Qing-Long Han Lei Ding Shengyuan Xu Guobiao Jia IEEE the School of Automation Nanjing University of Science and TechnologyNanjing 210094China the School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia the Institute of Advanced technology Nanjing University of Posts and TelecommunicationsNanjing 210023China

This paper is concerned with distributed Nash equi librium seeking strategies under quantized communication. In the proposed seeking strategy, a projection operator is synthesized with a gradient search method to achieve the optimization o players' objective functions while restricting their actions within required non-empty, convex and compact domains. In addition, a leader-following consensus protocol, in which quantized informa tion flows are utilized, is employed for information sharing among players. More specifically, logarithmic quantizers and uniform quantizers are investigated under both undirected and connected communication graphs and strongly connected digraphs, respec tively. Through Lyapunov stability analysis, it is shown that play ers' actions can be steered to a neighborhood of the Nash equilib rium with logarithmic and uniform quantizers, and the quanti fied convergence error depends on the parameter of the quan tizer for both undirected and directed cases. A numerical exam ple is given to verify the theoretical results.

关键词： Consensus distributed Nash equilibrium seeking projected gradient play quantized communication

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Memristive oscillator to memristive map,energy characteristic

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Science China(Technological Sciences) 2024年第5期67卷 1567-1578页

作者： GUO YiTong MA Jun ZHANG XiaoFeng HU XiKui College of Electrical and Information Engineering Lanzhou University of TechnologyLanzhou730050China Department of Physics Lanzhou University of TechnologyLanzhou730050China School of Science Chongqing University of Posts and TelecommunicationsChongqing400065China

Most of nonlinear oscillators composed of capacitive and inductive variables can obtain the Hamilton energy by using the Helmholtz theorem when the models are rewritten in equivalent vector *** energy functions for biophysical neurons can be obtained by applying scale transformation on the physical field energy in their equivalent neural *** dynamical systems often have exact energy functions,while some mathematical models just suggest generic Lyapunov functions,and the energy function is effective to predict mode *** this paper,a memristive oscillator is approached by two kinds of memristor-based nonlinear circuits,and the energy functions are defined to predict the dependence of oscillatory modes on energy *** absence of capacitive variable for capacitor,the physical time t and charge q are converted into dimensionless variables by using combination of resistance and inductance(L,R),e.g.,τ=t×R/*** energy function for each memristive map is proposed by applying the similar weights as energy function for the memristive *** example,energy function for the map is obtained by replacing the variables and parameters of the memristive oscillator with corresponding variables and parameters for the memristive *** memristive map prefers to keep lower average energy than the memristive oscillator,and chaos is generated in a discrete system with two *** scheme is helpful for energy definition in maps,and it provides possible guidance for verifying the reliability of maps by considering the energy characteristic.

关键词： Hamilton energy memristor Helmholtz theorem scale transformation memristive circuit

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