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Discovering Association Rules with Graph Patterns in Temporal Networks

Tsinghua science and technology 2023年第2期28卷 344-359页

作者： Chu Huang Qianzhen Zhang Deke Guo Xiang Zhao Xi Wang Science and Technology on Information Systems Engineering Laboratory College of Systems EngineeringNational University of Defense TechnologyChangsha 410073China

Discovering regularities between entities in temporal graphs is vital for many real-world applications(e.g.,social recommendation,emergency event detection,and cyberattack event detection).This paper proposes temporal graph association rules(TGARs)that extend traditional graph-pattern association rules in a static graph by incorporating the unique temporal information and *** introduce quality measures(e.g.,support,confidence,and diversification)to characterize meaningful TGARs that are useful and *** addition,the proposed support metric is an upper bound for alternative metrics,allowing us to guarantee a superset of *** extend conventional confidence measures in terms of maximal occurrences of *** diversification score strikes a balance between interestingness and *** the problem is NP-hard,we develop an effective discovery algorithm for TGARs that integrates TGARs generation and TGARs selection and shows that mining TGARs is feasible over a temporal *** propose pruning strategies to filter TGARs that have low support or cannot make top-k as early as ***,we design an auxiliary data structure to prune the TGARs that do not meet the constraints during the TGARs generation process to avoid conducting repeated subgraph matching for each extension in the search *** experimentally verify the effectiveness,efficiency,and scalability of our algorithms in discovering diversified top-k TGARs from temporal graphs in real-life applications.

关键词： temporal networks graph association rule subgraph pattern matching graph mining big graphs

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Attack and Defense Game with Intuitionistic Fuzzy Payoffs in Infrastructure Networks

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Tsinghua science and technology 2025年第1期30卷 384-401页

作者： Yibo Dong Jin Liu Jiaqi Ren Zhe Li Weili Li Science and Technology on Information Systems Engineering Laboratory National University of Defense TechnologyChangsha 410073China

Due to our increasing dependence on infrastructure networks,the attack and defense game in these networks has draw great concerns from security ***,when it comes to evaluating the payoffs in practical attack and defense games in infrastructure networks,the lack of consideration for the fuzziness and uncertainty of subjective human judgment brings forth significant challenges to the analysis of strategic interactions among decision *** paper employs intuitionistic fuzzy sets(IFSs)to depict such uncertain payoffs,and introduce a theoretical framework for analyzing the attack and defense game in infrastructure networks based on intuitionistic fuzzy *** take the changes in three complex network metrics as the universe of discourse,and intuitionistic fuzzy sets are employed based on this universe of discourse to reflect the satisfaction of decision *** employ an algorithm based on intuitionistic fuzzy theory to find the Nash equilibrium,and conduct experiments on both local and global *** show that:(1)the utilization of intuitionistic fuzzy sets to depict the payoffs of attack and defense games in infrastructure networks can reflect the unique characteristics of decision makers’subjective preferences.(2)the use of differently weighted proportions of the three complex network metrics has little impact on decision makers’choices of different strategies.

关键词： infrastructure networks attack and defense game intuitionistic fuzzy set Nash equilibrium

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Belief reliability modeling and analysis for TPS considering physical principles,degradation mechanism and epistemic uncertainties

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Chinese Journal of Aeronautics 2025年第5期38卷 264-276页

作者： Dayu CHEN Yao LI Yiyang SHANGGUAN Zhiqiang LI Zhenqiang WU Xiaoyang LI Rui KANG School of Reliability and Systems Engineering Beihang University Science and Technology on Reliability and Environmental Engineering Laboratory Science and Technology on Reliability and Environment Engineering Laboratory Beijing Institute of Structure and Environment Engineering

Thermal Protection System(TPS) with thick tiles, low thermal conductivity, and a short re-entry stage stands as a critical element within reusable aircraft, whose reliability is related to the function and changes with their physical properties, external conditions, and degradation. Meanwhile, due to the limitation of testing resources, epistemic uncertainties stemming from the small samples are present in TPS reliability modeling. However, current TPS reliability modeling methods face challenges in characterizing the relationships among reliability and physical properties, external conditions, degradation, and epistemic uncertainties. Therefore, under the framework of belief reliability theory, a TPS reliability model is constructed, which takes into account the physical principle, external conditions, performance degradation, and epistemic uncertainties. A reliability simulation algorithm is proposed to calculate TPS reliability. Through a case study and comparison analysis, the proposed method is validated as more effective than the existing method. Additionally,reliability sensitivity analysis is conducted to identify the sensitive factors of reliability under the condition of small samples, through which suggestions are provided for TPS functional design and improvement.

关键词： Thermal protection system Physical principle Epistemic uncertainty Performance degradation Belief reliability modeling

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China's poverty assessment and analysis under the framework of the UN SDGs based on multisource remote sensing data

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地球空间信息科学学报（英文版） 2024年第1期27卷 111-131页

作者： Mengjie Wang Yanjun Wang Fei Teng Shaochun Li Yunhao Lin Hengfan Cai Hunan Provincial Key Laboratory of Geo-Information Engineering in Surveying Mapping and Remote SensingHunan University of Science and TechnologyXiangtanChina National-Local Joint Engineering Laboratory of Geo-spatial Information Technology Hunan University of Science and TechnologyXiangtanChina School of Earth Sciences and Spatial Information Engineering Hunan University of Science and TechnologyXiangtanChina Hunan Provincial Key Laboratory of Geo-Information Engineering in Surveying Mapping and Remote SensingHunan University of Science and TechnologyXiangtanChina National-Local Joint Engineering Laboratory of Geo-spatial Information Technology Hunan University of Science and TechnologyXiangtanChina

Poverty has always been a global concern that has restricted human *** first goal(SDG 1)of the United Nations Sustainable Development Goals(SDGs)is to eliminate all forms of poverty all over the *** establishment of a scientific and effective localized SDG 1 evaluation and monitoring method is the key to achieving SDG *** paper proposes SDG 1 China district and county-level localization evaluation method based on multi-source remote sensing data for the United Nations Sustainable Development *** temporal and spatial distribution characteristics of China's poverty areas and their SDG 1 evaluation values in 2012,2014,2016,and 2018 have been *** on the SDGs global indicator framework,this paper first constructed SDG 1 China's district and county localization indicator system and then extracted multidimensional feature factors from nighttime light images,land cover data,and digital elevation model ***,we establish SDG 1 China's localized partial least squares estimation model and SDG 1 China's localized machine learning estimation ***,we analyze and verify the spatiotemporal distribution characteristics of China's poverty areas and counties and their SDG 1 evaluation *** results show that SDG 1 China's district and county localization indicator system proposed in this study and SDG 1 China's localized partial least squares estimation model can better reflect the poverty level of China's districts and *** estimated model R2 is 0.65,which can identify 72.77%of China's national poverty *** 2012 to 2018,the spatial distribution pattern of SDG evaluation values in China's districts and counties is that the SDG evaluation values gradually increase from western China to eastern *** addition,the average SDG 1 evaluation value of China's districts and counties increased by 23%from 2012 to *** paper is oriented to the United Nations SDGs frame-work,explores the SDG 1 localized evalu

关键词： Multisource remote sensing data Sustainable Development Goals(SDGs) poverty indicator system partial least squares machine learning

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Randomly coupled trench-assisted multicore fibers with different arrangements for high tolerance of manufacturing errors

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science China(information sciences) 2023年第11期66卷 260-272页

作者： Yongneng JIANG Jiajing TU Shecheng GAO Weiping LIU Zhaohui LI Department of Electronic Engineering College of Information Science and Technology Jinan University School of Electronics and Information Technology Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems Sun Yat-sen University Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)

Randomly coupled multicore fibers(RC-MCFs) are promising candidates for long-haul transmission. However, the degree of coupling between the homogeneous cores of an RC-MCF is weakened if manufacturing errors appear. Therefore, a low-index trench layer is introduced into the coupled cores to investigate the effects of its position and thickness on the group index to enhance the tolerance of manufacturing errors. A depressed region is designed in the center of the core to solve the problem of the effective area decreasing because of the confinement of the low-index trench. Additionally, it is important to study the effective arrangement of the coupled cores to obtain a smaller group delay spread(GDS) within the limited 125-μm cladding; we discuss the single-layer and double-layer arrangements. A moderate range is found for both the bending radius and core pitch to minimize the GDS. For the single-layer arrangement, the degree of mixing is weak, and the degeneracy state does not easily change the bending conditions; thus, it may be a good candidate for designing systemically coupled multicore fibers. For the double-layer arrangement, the bending and twisting factors can induce sufficient mixing among the different modes to reduce GDS; thus,this arrangement is more suitable for the design of RC-MCFs.

关键词： manufacturing errors randomly coupled multicore fibers trench-assisted core single-layer arrangement double-layer arrangement

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Efficient Multi-AGV Real-time Collaborative Operation in Large-scale Intelligent Warehouses

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-16页

作者： Liu, MengTing Qiao, Yan Wu, NaiQi Institute of Systems Engineering and the Collaborative Laboratory for Intelligent Science and Systems Macau University of Science and Technology Macao

Nowadays, large warehouses operate in an unmanned way by using automated guided vehicles (AGVs). In such a system, large number of AGVs perform their transportation tasks concurrently, leading to high probability of conflicts. It is very challenging to manage the operations of these AGVs. This paper studies the operation problem of a warehouse where an unloaded AGV can travel under the shelves, which is different from the ones studied in the literature. In this paper, the problem is described by a graphic model. Based on the model, we propose a multi-AGV real-time collaborative operation (MARTCO) method. By this method, each AGV operates autonomously and determines its traveling path itself. We design a number of priority rules and an improved A* algorithm. The AGVs collaborate by applying these rules. Each AGV can dynamically adjust its path by using MARTCO to avoid conflicts. In this way, the method is computationally efficient such that it can deal with the operation of warehouses with more than 100 AGVs. Also, with the improved A* algorithm, the number of returns and nodes to be searched is significantly reduced, which improves the throughput of the system. Large number of experiments are done to verify the proposed method. IEEE

关键词： Real time systems

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Multiplayer Reach-Avoid Differential Games in 3D Space Inspired by Harris'Hawks'Cooperative Hunting Tactics

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Research 2024年第2期2023卷 41-54页

作者： Wanying Ruan Haibin Duan Yongbin Sun Wanmai Yuan Jie Xia State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical EngineeringBeihang UniversityBeijingChina Peng Cheng Laboratory ShenzhenChina Information Science Academy of CETC BeijingChina

This paper investigates a multiplayer reach-avoid differential game in 3-dimensional(3D)space,which involves multiple pursuers,multiple evaders,and a designated target *** evaders aim to reach the target region,while the pursuers attempt to guard the target region by capturing the *** class of research holds significant practical ***,the complexity of the problem escalates substantially with the growing number of players,rendering its solution extremely *** this paper,the multiplayer game is divided into many subgames considering the cooperation among pursuers,reducing the computational burden,and obtaining numerically tractable strategies for ***,the Apollonius sphere,a fundamental geometric tool for analyzing the 3D differential game,is formulated,and its properties are *** on this,the optimal interception point for the pursuer to capture the evader is derived and the winning conditions for the pursuer and evader are ***,based on the Apollonius sphere,the optimal state feedback strategies of players are designed,and simultaneously,the optimal one-to-one pairings are ***,the Value function of the multiplayer reach-avoid differential game is explicitly given and is proved to satisfy Hamilton-Jacobi-Isaacs(HJI)***,the matching algorithm for the case with pursuers outnumbered evaders is provided through constructing a weighted bipartite graph,and the cooperative tactics for multiple pursuers are proposed,inspired by the Harris'Hawks intelligent cooperative hunting ***,numerical simulations are conducted to illustrate the effectiveness of the theoretical results for both cases where the number of adversary players is equal and unequal between the 2 groups.

关键词： holds satisfy rendering

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Multi-parameter ultrasound imaging for musculoskeletal tissues based on a physics informed generative adversarial network

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Chinese Physics B 2025年第4期34卷 442-455页

作者： Pengxin Wang Heyu Ma Tianyu Liu Chengcheng Liu Dan Li Dean Ta Institute of Biomedical Engineering&Technology Academy for Engineering and TechnologyFudan UniversityShanghai 200433China State Key Laboratory of Integrated Chips and Systems Fudan UniversityShanghai 201203China Department of Electronic Engineering School of Information Science and TechnologyFudan UniversityShanghai 200438China Department of Biomedical Engineering School of Information Science and TechnologyFudan UniversityShanghai 200438China

Full waveform inversion(FWI)has showed great potential in the detection of musculoskeletal ***,FWI is an ill-posed inverse problem and has a high requirement on the initial model during the imaging *** inaccurate initial model may lead to local minima in the inversion and unexpected imaging results caused by cycle-skipping *** learning methods have been applied in musculoskeletal imaging,but need a large amount of data for *** by work related to generative adversarial networks with physical informed constrain,we proposed a method named as bone ultrasound imaging with physics informed generative adversarial network(BUIPIGAN)to achieve unsupervised multi-parameter imaging for musculoskeletal tissues,focusing on speed of sound(SOS)and *** the in-silico experiments using a ring array transducer,conventional FWI methods and BUIPIGAN were employed for multiparameter imaging of two musculoskeletal tissue *** results were evaluated based on visual appearance,structural similarity index measure(SSIM),signal-to-noise ratio(SNR),and relative error(RE).For SOS imaging of the tibia–fibula model,the proposed BUIPIGAN achieved accurate SOS imaging with best *** specific quantitative metrics for SOS imaging were SSIM 0.9573,SNR 28.70 dB,and RE 5.78%.For the multi-parameter imaging of the tibia–fibula and human forearm,the BUIPIGAN successfully reconstructed SOS and density distributions with SSIM above 94%,SNR above 21 dB,and RE below 10%.The BUIPIGAN also showed robustness across various noise levels(i.e.,30 dB,10 dB).The results demonstrated that the proposed BUIPIGAN can achieve high-accuracy SOS and density imaging,proving its potential for applications in musculoskeletal ultrasound imaging.

关键词： ultrasound image physics informed generative adversarial network musculoskeletal imaging

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Nonparametric Statistical Feature Scaling Based Quadratic Regressive Convolution Deep Neural Network for Software Fault Prediction

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Computers, Materials & Continua 2024年第3期78卷 3469-3487页

作者： Sureka Sivavelu Venkatesh Palanisamy School of Computer Science Engineering and Information Systems Vellore Institute of TechnologyVellore632014India

The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software with defects negatively impacts operational costs and finally affects customer satisfaction. Numerous approaches exist to predict software defects. However, the timely and accurate software bugs are the major challenging issues. To improve the timely and accurate software defect prediction, a novel technique called Nonparametric Statistical feature scaled QuAdratic regressive convolution Deep nEural Network (SQADEN) is introduced. The proposed SQADEN technique mainly includes two major processes namely metric or feature selection and classification. First, the SQADEN uses the nonparametric statistical Torgerson–Gower scaling technique for identifying the relevant software metrics by measuring the similarity using the dice coefficient. The feature selection process is used to minimize the time complexity of software fault prediction. With the selected metrics, software fault perdition with the help of the Quadratic Censored regressive convolution deep neural network-based classification. The deep learning classifier analyzes the training and testing samples using the contingency correlation coefficient. The softstep activation function is used to provide the final fault prediction results. To minimize the error, the Nelder–Mead method is applied to solve non-linear least-squares problems. Finally, accurate classification results with a minimum error are obtained at the output layer. Experimental evaluation is carried out with different quantitative metrics such as accuracy, precision, recall, F-measure, and time complexity. The analyzed results demonstrate the superior performance of our proposed SQADEN technique with maximum accuracy, sensitivity and specificity by 3%, 3%, 2% and 3% and minimum time and space by 13% and 15% when compared with the two sta

关键词： Software defect prediction feature selection nonparametric statistical Torgerson-Gower scaling technique quadratic censored regressive convolution deep neural network softstep activation function nelder-mead method

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2P3FL:A Novel Approach for Privacy Preserving in Financial Sectors Using Flower Federated Learning

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Computer Modeling in engineering & sciences 2024年第8期140卷 2035-2051页

作者： Sandeep Dasari Rajesh Kaluri School of Computer Science Engineering and Information Systems Vellore Institute of TechnologyVellore632014India

The increasing data pool in finance sectors forces machine learning(ML)to step into new *** data has significant financial implications and is *** users data from several organizations for various banking services may result in various intrusions and privacy *** a result,this study employs federated learning(FL)using a flower paradigm to preserve each organization’s privacy while collaborating to build a robust shared global ***,diverse data distributions in the collaborative training process might result in inadequate model learning and a lack of *** address this issue,the present paper proposes the imple-mentation of Federated Averaging(FedAvg)and Federated Proximal(FedProx)methods in the flower framework,which take advantage of the data locality while training and guaranteeing global *** improves the privacy of the local *** analysis used the credit card and Canadian Institute for Cybersecurity Intrusion Detection Evaluation(CICIDS)***,recall,and accuracy as performance indicators to show the efficacy of the proposed strategy using FedAvg and *** experimental findings suggest that the proposed approach helps to safely use banking data from diverse sources to enhance customer banking services by obtaining accuracy of 99.55%and 83.72%for FedAvg and 99.57%,and 84.63%for FedProx.

关键词： Federated learning FedAvg FedProx flower framework privacy preservation financial sectors

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