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1st International Conference on Artificial Intelligence and Human-Computer Interaction, ArtInHCI 2023

作者： He, Di Zhao, Changshun Zhang, Kaiyue Yang, Hongrong Liu, Ying University of Electronic Science and Technology of China Chengdu China National Key Laboratory for Complex Systems Simulation Beijing China Officers College of PAP Chengdu China

ISBN: (纸本)9781643685083

This research focuses on the role of trust in human-agent interaction, particularly in the context of home robot systems. The study found that participants were more likely to collaborate when they understood the agent's intentions. The research involved 36 participants working with an agent across three different interfaces to complete household tasks. The results showed that clear agent intentions can increase cooperation and calibrate trust to an appropriate level. © 2024 The Authors.

关键词： Human robot interaction

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A credibility allocation approach of complex simulation systems 35

A credibility allocation approach of complex simulation syst...

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35th European Modeling and simulation Symposium, EMSS 2023

作者： Zhang, Huan Li, Wei Geng, HuaPin Ma, Ping Yang, Ming Control and Simulation Center Harbin Institute of Technology Harbin150080 China National Key Laboratory of Modeling and Simulation for Complex Systems Harbin150080 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9788885741881

complex simulation systems usually need to satisfy the credibility requirements and the credibility of complex simulation systems is inextricably linked to the credibility of simulation sub-systems. Hence, in order to guarantee the credibility of complex simulation systems meets requirements, it is necessary to allocate the credibility of simulation sub-systems. complex simulation systems are composed of several correlative simulation sub-systems and their credibility has correlation relationships, which makes it difficult to obtain the credibility of simulation sub-systems quickly. The existing works mostly ignore the relationships between the sub-systems and are difficult to generate the credibility allocation results of simulation sub-systems. In this paper, we model the credibility allocation problem as a probabilistic inference problem based on the pairwise Markov random field (PMRF). In addition, we apply several inference algorithms to perform the inference exactly and approximately in the credibility PMRF. Finally, experiments are conduted on the air defense combat complex simulation system, and the experiment results demonstrate that the proposed method can obtain the credibility allocation results quickly and accurately. © 2023 The Authors.

关键词： Inference engines

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Interference-assisted energy harvesting short packet communications with hardware impairments

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International Journal of Intelligent Networks 2024年第1期5卷 231-240页

作者： Chen, Dechuan Li, Jin Hu, Jianwei Zhang, Xingang Zhang, Shuai Wang, Dong College of Physics and Electronic Engineering Nanyang Normal University Nanyang473061 China Ministry of Education Nanjing210003 China National Key Laboratory for Complex Systems Simulation Beijing100101 China College of Computer Science and Technology Nanyang Normal University Nanyang473061 China

Radio frequency energy harvesting offers a promising solution to provide low power Internet of Things (IoT) devices with convenient and perpetual energy supply. In this work, we investigate the reliable performance of an energy-constrained transmitter communicating with a receiver over Nakagami-m channel, where the effects of transceiver hardware impairments and finite blocklength coding are jointly considered. Specifically, the communication link between the transmitter and receiver operates within the coverage of an existing wireless system, with radio frequency signal from the existing system serving as an energy signal for the transmitter while acting as an interference signal for the receiver. By utilizing the finite-blocklength information theory, we first derive average block error rate (BLER) and asymptotic average BLER in closed-form expressions, which enable us to quantify the extent of reliability loss. Then, we analyze effective throughput of the system, and determine the optimal blocklength that maximizes the effective throughput. Computer simulations are employed to validate the accuracy of our analytical findings, demonstrating the presence of an outage threshold solely due to hardware impairments. Furthermore, if transmission rate exceeds the outage threshold defined by the level of hardware impairments, reliable communication within the system under consideration cannot be achieved, regardless of the transmit signal-to-noise ratio (SNR). © 2024 The Authors

关键词： Energy harvesting

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An Anomaly Detection Method Based on Adaptive Log and Dual Feature Fusion Analysis for Distributed systems 11

An Anomaly Detection Method Based on Adaptive Log and Dual F...

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11th International Conference on Information systems and Computing technology, ISCTech 2023

作者： Jia, Yijiang Li, Kefei Lu, Ping Xie, Baodi Wang, Huayang Chen, Jincai Huazhong University of Science and Technology School of Computer Science and Technology Wuhan China Huazhong University of Science and Technology Wuhan National Laboratory for Optoelectronics Wuhan China National Key Laboratory of Modeling and Simulation for Complex Systems Beijing China

ISBN: (纸本)9798350342406

In this study, we present a middleware-based approach for detecting anomalies in distributed systems. Our method facilitates the dynamic collection of logs at various levels of detail and incorporates an a priori dictionary-based compression strategy to process and transmit logs, minimizing the performance impact on distributed systems. Additionally, we utilize a dual feature fusion technique to analyze the logs. We evaluate the effectiveness of our approach by performing anomaly detection in a publish/subscribe distributed system and comparing it with existing methods. The results illustrate that our method outperforms other approaches, demonstrating superior performance. © 2023 IEEE.

关键词： Anomaly detection

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Stochastic Block Models for complex Network Analysis: A Survey

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ACM Transactions on Knowledge Discovery from Data 2025年第3期19卷 1-35页

作者： Liu, Xueyan Song, Wenzhuo Musial, Katarzyna Li, Yang Zhao, Xuehua Yang, Bo College of Computer Science and Technology Jilin University Changchun China School of Information Science and Technology Northeast Normal University Changchun China Complex Adaptive Systems Lab Data Science Institute University of Technology Sydney Sydney Australia Aviation University of the Air Force Changchun China School of Digital Media Shenzhen Institute of Information Technology Shenzhen China Key Laboratory of Symbolic Computation and Knowledge Engineer Jilin University Ministry of Education Changchun China

complex networks enable to represent and characterize the interactions between entities in various complex systems which widely exist in the real world and usually generate vast amounts of data about all the elements, their behaviors and interactions over time. The studies concentrating on new network analysis approaches and methodologies are vital because of the diversity and ubiquity of complex networks. The stochastic block model (SBM), based on Bayesian theory, is a statistical network model. SBMs are essential tools for analyzing complex networks since SBMs have the advantages of interpretability, expressiveness, flexibility and generalization. Thus, designing diverse SBMs and their learning algorithms for various networks has become an intensively researched topic in network analysis and data mining. In this article, we review, in a comprehensive and in-depth manner, SBMs for different types of networks (i.e., model extensions), existing methods (including parameter estimation and model selection) for learning optimal SBMs for given networks and SBMs combined with deep learning. Finally, we provide an outlook on the future research directions of SBMs. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： complex Networks Structural Pattern Discovery Stochastic Block models Learning Methods of SBMs

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Satellite Interference Signal Classification Using Improved MLP Model

Satellite Interference Signal Classification Using Improved ...

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2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Xie, Liwei Zhuang, Yaqiang Zhuang, Xuebin Zeng, Xiaohui School of Systems Science and Engineering Sun Yat-Sen University Guangzhou China School of Integrated Circuits and Electronics Beijing Institute of Technology Beijing Key Laboratory of Millimeter Wave and Terahertz Technology Beijing China Science and Technology On Complex Aviation Systems Simulation Laboratory Beijing China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

In response to the existing style of deceptive jamming of Global Position System (GPS) receivers by aerial jammer carriers, a method using improved multi-layer perceptron (MLP) model is proposed to identify and classify interference sources based on the rate of change of satellite incoming angle. The work firstly constructs an airborne GPS interference source localization deployment model, then analyzes and verifies the rationality of this simulation data model, and finally emphasizes the superiority of the proposed method using the classical classification algorithm as a comparison method. The simulation results indicated that the proposed method is capable to identify the corresponding interferers with a greater rate of recognition compared with other method in the built multi-interference source environment, which provides a reference for dealing with the interference identification and classification in the networked GPS interference source deployment environment. © 2022 IEEE.

关键词： Antennas

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Evolutionary Interest Representation Network for Click-Through Rate Prediction

Evolutionary Interest Representation Network for Click-Throu...

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2023 IEEE International Conference on Web Services, ICWS 2023

作者： Zhou, Renjie Jin, Zhenming Wan, Jian Zhang, Jilin Guo, Xingyu Liu, Qiang Hangzhou Dianzi University Key Laboratory of Complex Systems Modeling and Simulation of the Ministry of Education School of Computer Science and Technology Hangzhou China Hangzhou Dianzi University Key Laboratory of Complex Systems Modeling and Simulation of the Ministry of Education Itmo Joint Institute Hangzhou China Zhejiang University of Science and Technology School of Information and Electronic Engineering Hangzhou China Zhejiang Police College Dept. of Computer and Information Technology Hangzhou China

ISBN: (纸本)9798350304855

The rapid development of the Internet has revo-lutionized our lives, providing us with an array of convenient services. However, this revolution has also led to the problem of data overload. Personalized recommendation services have been widely recognized as an effective solution to this problem by both the industrial and academic communities. Accurate prediction of click-through rate (CTR) is a critical task in personalized recommendation systems since it can improve the user's shopping experience, ultimately increasing revenue for the platform. To achieve accurate CTR prediction, it is crucial to capture user interests. While several methods for interest modeling exist, challenges related to user interest evolution and user behavior noise need further attention. This paper proposes a novel CTR prediction model named the Evolutionary Interest Representation Network (EIRN), which learns the evolving interest representation of users from their behaviors, profiles, and environmental attributes. In the model, we introduce an advertisement correlation graph decomposition layer and a noise filter layer to enhance and purify the user behavior representation. An interest extraction layer is designed to capture sequential correlations and common characteristics between user behaviors, representing their interests. Additionally, as user interests evolve over time and their importance changes, an attention-based interest evolution layer is designed to track the evolution of user interests. Our proposed method is validated using four public datasets and an industrial dataset, showing its superiority over existing CTR prediction methods. © 2023 IEEE.

关键词： Forecasting

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The Application of Two-dimensional Subsection Simpson Integration on Artillery Firing Efficiency simulation Modeling

The Application of Two-dimensional Subsection Simpson Integr...

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第24届中国系统仿真技术及其应用学术年会（CCSSTA24th 2023）

作者： Zhao Zhiqiang Wang Guizhen Science and Technology on Complex Land Systems Simulation Laboratory 32179 Unit

The evaluation model of artillery firing efficiency is widely applied to firepower command&control and large-scale simulation, it is very important for improving precision and speed of calculation to enhance capability of firepower command&control and large-scale simulation. Two-dimensional subsection Simpson integration was introduced to evaluation the artillery firing efficiency model, the analysis of two-dimensional subsection Simpson integration in theory showed that convergence speed of two-dimensional subsection Simpson integration enhance to O(h4). The simulation results indicate that, speed of two-dimensional subsection Simpson integration is higher 20 times than statistics experiment method, precision of two-dimensional subsection Simpson integration is a little higher than the typical numerical integration such as midpoint formula integration and statistical experiment method, but it can promote precision by 10% than approximate computation method.

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Secure short-packet communications using a full-duplex receiver

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International Journal of Intelligent Networks 2023年第1期4卷 349-354页

作者： Chen, Dechuan Li, Jin Hu, Jianwei Zhang, Xingang Zhang, Shuai College of Physics and Electronic Engineering Nanyang Normal University Nanyang473061 China Ministry of Education Nanjing210003 China National Key Laboratory for Complex Systems Simulation Beijing100101 China College of Computer Science and Technology Nanyang Normal University Nanyang473061 China

In this work, we consider the physical layer security in short-packet communications, where a full-duplex (FD) receiver receives information signals from a source while generating artificial noise (AN) to confuse an eavesdropper. Taking into account the finite blocklength coding and the self-interference (SI) in FD mode, we derive new approximation closed-form expression for the secrecy throughput. Moreover, we analyze the asymptotic secrecy throughput in two distinct scenarios, i.e., high signal-to-noise ratio (SNR) regime and infinite blocklength coding, to gain more insights. Our examination illustrates the correctness of our expressions and shows how the critical system variables affect the secrecy throughput. © 2023 The Authors

关键词： Finite difference method

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Modeling the dynamic alignment of business and information systems via the lens of human-centered architecture evolution

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Journal of systems Engineering and Electronics 2021年第4期32卷 881-888页

作者： ZHANG Mengmeng YI Shuanghui CHEN Honghui LUO Aimin LIU Junxian ZHANG Xiaoxue Science and Technology on Information Systems Engineering Laboratory National University of Defense TechnologyChangsha 410072China National Key Laboratory for Complex System Simulation Military Academy of SciencesBeijing 100080China

The complexity of business and information systems(IS)alignment is a growing concern for researchers and practitioners *** extant research on alignment architecture fails to consider the human viewpoint,which makes it difficult to embrace emergent *** paper contributes to the extant literature in the following ***,we combine an enterprise architecture(EA)framework with a human viewpoint to address alignment issues in the architecture design phase;second,we describe a dynamic alignment model by developing a humancentered meta-model that explains first-and second-order changes and their effects on alignment *** paper provides better support for the theoretical research and the practical application of dynamic alignment.

关键词： business and information systems(IS)alignment human viewpoint enterprise architecture(EA) meta-model dynamic alignment

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