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Labeling-based centrality approaches for identifying critical edges on temporal graphs

Frontiers of computer science 2025年第2期19卷 89-104页

作者： Tianming ZHANG Jie ZHAO Cibo YU Lu CHEN Yunjun GAO Bin CAO Jing FAN Ge YU School of Computer Science and Technology Zhejiang University of TechnologyHangzhou 310023China School of Computer Science and Technology Zhejiang UniversityHangzhou 310013China Department of Computer Science Northeastern UniversityShenyang 110819China

Edge closeness and betweenness centralities are widely used path-based metrics for characterizing the importance of edges in *** general graphs,edge closeness centrality indicates the importance of edges by the shortest distances from the edge to all the other *** betweenness centrality ranks which edges are significant based on the fraction of all-pairs shortest paths that pass through the ***,extensive research efforts go into centrality computation over general graphs that omit time ***,numerous real-world networks are modeled as temporal graphs,where the nodes are related to each other at different time *** temporal property is important and should not be neglected because it guides the flow of information in the *** state of affairs motivates the paper’s study of edge centrality computation methods on temporal *** introduce the concepts of the label,and label dominance relation,and then propose multi-thread parallel labeling-based methods on OpenMP to efficiently compute edge closeness and betweenness centralities *** types of optimal temporal *** edge closeness centrality computation,a time segmentation strategy and two observations are presented to aggregate some related temporal edges for uniform *** edge betweenness centrality computation,to improve efficiency,temporal edge dependency formulas,a labeling-based forward-backward scanning strategy,and a compression-based optimization method are further proposed to iteratively accumulate centrality *** experiments using 13 real temporal graphs are conducted to provide detailed insights into the efficiency and effectiveness of the proposed *** with state-ofthe-art methods,labeling-based methods are capable of up to two orders of magnitude speedup.

关键词： temporal graph closeness centrality between-ness centrality temporal path

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Enhanced Acceleration for Generalized Nonconvex Low-Rank Matrix Learning

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Chinese Journal of Electronics 2025年第1期34卷 98-113页

作者： Hengmin Zhang Jian Yang Wenli Du Bob Zhang Zhiyuan Zha Bihan Wen School of Electrical and Electronic Engineering Nanyang Technological University School of Computer Science and Engineering Nanjing University of Science and Technology School of Information Science and Engineering East China University of Science and Technology Department of Electrical and Computer Engineering University of Macau

Matrix minimization techniques that employ the nuclear norm have gained recognition for their applicability in tasks like image inpainting, clustering, classification, and reconstruction. However, they come with inherent biases and computational burdens, especially when used to relax the rank function, making them less effective and efficient in real-world scenarios. To address these challenges, our research focuses on generalized nonconvex rank regularization problems in robust matrix completion, low-rank representation, and robust matrix regression. We introduce innovative approaches for effective and efficient low-rank matrix learning, grounded in generalized nonconvex rank relaxations inspired by various substitutes for the ?0-norm relaxed functions. These relaxations allow us to more accurately capture low-rank structures. Our optimization strategy employs a nonconvex and multi-variable alternating direction method of multipliers, backed by rigorous theoretical analysis for complexity and *** algorithm iteratively updates blocks of variables, ensuring efficient convergence. Additionally, we incorporate the randomized singular value decomposition technique and/or other acceleration strategies to enhance the computational efficiency of our approach, particularly for large-scale constrained minimization problems. In conclusion, our experimental results across a variety of image vision-related application tasks unequivocally demonstrate the superiority of our proposed methodologies in terms of both efficacy and efficiency when compared to most other related learning methods.

关键词： Learning systems Image recognition Minimization Computational efficiency Complexity theory Matrix decomposition Optimization Image reconstruction Singular value decomposition Convergence

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A recover-then-discriminate framework for robust anomaly detection

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science China(Information sciences) 2025年第4期68卷 300-318页

作者： Peng XING Dong ZHANG Jinhui TANG Zechao LI School of Computer Science and Engineering Nanjing University of Science and Technology Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology

Anomaly detection(AD) has been extensively studied and applied across various scenarios in recent years. However, gaps remain between the current performance and the desired recognition accuracy required for practical *** paper analyzes two fundamental failure cases in the baseline AD model and identifies key reasons that limit the recognition accuracy of existing approaches. Specifically, by Case-1, we found that the main reason detrimental to current AD methods is that the inputs to the recovery model contain a large number of detailed features to be recovered, which leads to the normal/abnormal area has not/has been recovered into its original state. By Case-2, we surprisingly found that the abnormal area that cannot be recognized in image-level representations can be easily recognized in the feature-level representation. Based on the above observations, we propose a novel recover-then-discriminate(ReDi) framework for *** takes a self-generated feature map(e.g., histogram of oriented gradients) and a selected prompted image as explicit input information to address the identified in Case-1. Additionally, a feature-level discriminative network is introduced to amplify abnormal differences between the recovered and input representations. Extensive experiments on two widely used yet challenging AD datasets demonstrate that ReDi achieves state-of-the-art recognition accuracy.

关键词： recovery network HOG prompt discriminative network self-correlation loss anomaly detection

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Improving Machine Translation Formality with Large Language Models

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computers, Materials & Continua 2025年第2期82卷 2061-2075页

作者： Murun Yang Fuxue Li School of Computer Science and Engineering Northeastern UniversityShenyang110819China College of Electrical Engineering Yingkou Institute of TechnologyYingkou115014China

Preserving formal style in neural machine translation (NMT) is essential, yet often overlooked as an optimization objective of the training processes. This oversight can lead to translations that, though accurate, lack formality. In this paper, we propose how to improve NMT formality with large language models (LLMs), which combines the style transfer and evaluation capabilities of an LLM and the high-quality translation generation ability of NMT models to improve NMT formality. The proposed method (namely INMTF) encompasses two approaches. The first involves a revision approach using an LLM to revise the NMT-generated translation, ensuring a formal translation style. The second approach employs an LLM as a reward model for scoring translation formality, and then uses reinforcement learning algorithms to fine-tune the NMT model to maximize the reward score, thereby enhancing the formality of the generated translations. Considering the substantial parameter size of LLMs, we also explore methods to reduce the computational cost of INMTF. Experimental results demonstrate that INMTF significantly outperforms baselines in terms of translation formality and translation quality, with an improvement of +9.19 style accuracy points in the German-to-English task and +2.16 COMET score in the Russian-to-English task. Furthermore, our work demonstrates the potential of integrating LLMs within NMT frameworks to bridge the gap between NMT outputs and the formality required in various real-world translation scenarios.

关键词： Neural machine translation formality large language model text style transfer style evaluation reinforcement learning

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Dynamic event-triggered data-driven iterative learning bipartite tracking control for nonlinear MASs with prescribed performance

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science China(Information sciences) 2025年第1期68卷 292-305页

作者： Tao SHI Wei-Wei CHE School of Mechatronic Engineering and Automation Shanghai University State Key Laboratory of Synthetical Automation for Process Industries Northeastern University College of Information Science and Engineering Northeastern University

This article proposes a distributed dynamic event-triggered data-driven iterative learning control(DET-DDILC)scheme under a predefined performance to tackle the bipartite tracking control problem for multiagent systems(MASs). An improved dynamic linearization technique is utilized to convert the nonlinear MASs into an iterative linear data model. First,a peer-to-peer mapping function is introduced to map the constrained distributed system output homeomorphism to an unconstrained one. In addition, a DET mechanism based on a time-iteration-varying function is devised to conserve network communication resources. Based on the unconstrained transformation and the designed DET mechanism, the DET-DDILC algorithm is devised to ensure that the bipartite tracking performance of MASs can be within the preset range. Finally, the effectiveness and feasibility of the designed control scheme are demonstrated via a simulation case by a comparison.

关键词： bipartite tracking control prescribed performance event-triggered iterative learning control multiagent systems

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Online Queue-Aware Service Migration and Resource Allocation in Mobile Edge Computing

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IEEE Transactions on Vehicular Technology 2025年第5期74卷 8063-8078页

作者： Du, An Jia, Jie Chen, Jian Wang, Xingwei Huang, Ming Northeastern University School of Computer Science and Engineering Engineering Research Center of Security Technology of Complex Network System Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Shenyang110819 China Northeastern University School of Computer Science and Engineering Shenyang110819 China

Mobile edge computing (MEC) integrated with Network Functions Virtualization (NFV) helps run a wide range of services implemented by Virtual Network Functions (VNFs) deployed at MEC networks. This emerging paradigm offers flexible edge resource management for Internet Service Providers (ISPs) and improves service satisfaction of diverse applications. However, a critical challenge lies in processing extremely unpredictable and bursty traffic flow, especially in event-trigger sensing tasks. In this paper, we study queue-aware service migration and resource allocation in an MEC network, where different devices with different arrival patterns request different network services. To this end, we first formulate a novel long-term operation cost minimization problem subject to the stability of multiple queues by adopting a simultaneous migration scheme and determining resource allocation dynamically. To address the problem efficiently, we propose an online control framework to make decisions without any prior system information. We first adopt the Lyapunov optimization technique to decompose the long-term optimization problem into multi-per-slot subproblems. Then, we adopt a decoupled optimization algorithm based on the coordinate descent method and augmented Lagrangian method to solve the offline mixed integer non-linear programming (MINLP) subproblems. Extensive results reveal that the proposed online optimization framework can efficiently balance queue stability and cost consumption. © 1967-2012 IEEE.

关键词： Mobile edge computing

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Microstructure and mechanical properties of in-situ nano TiC reinforced Ni-based alloy composites prepared by spark plasma sintering

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材料科学技术（英文版） 2025年第3期206卷 100-112页

作者： Xuetong Zeng Haitao Liu Shasha Yang Chengtao Yu Minghui Chen Fuhui Wang School of Materials Science and Engineering Northeastern UniversityShenyang 110819China Beijing Aerospace Technology Institute Beijing 10074China School of Materials Science and Engineering Northeastern UniversityShenyang 110819China School of Mechanical Engineering Ningxia Institute of Science and TechnologyShizuishan 753000China

Carbide dispersion reinforcing has been demonstrated to be an effective way of strengthening metal ma-trix ***,plagued by the nerve-wracking fact that the carbide particles tend to aggregate at the grain boundary of the metal matrix,grow up,and form an incoherent interface with it,their im-provement in mechanical strength tends to be *** this study,spark plasma sintering(SPS)was used to prepare the bulk alloy Ni20Cr and its composites with different carbides including TiC,SiC,and *** leads to discharge and elevates temperature at the interface to melt the Ni20Cr alloy par-ticles *** cooled down,the alloy is heterogeneously solidified on the surface of the carbide and builds up a coherent interface with *** to the decomposition of Ti3SiC2 during sintering,it completely transformed into nanosized TiC particles,which are engulfed by the outer melted layer of Ni20Cr and well dispersed within the alloy *** comparison to the Ni20Cr alloy,the composite with merely 4 wt％Ti3SiC2 gains over three times enhancement in yield strength to 879 MPa,while keeping a moderate high elongation of 17.8％.Finite element analysis demonstrated that the combination of SPS and precursor MAX phase of Ti3SiC2,which results in the in-situ precipitation of coherent ultrafine TiC particles in alloy grains,plays the key role in getting a good balance between mechanical strength and ductility for the Ni20Cr matrix composites.

关键词： Metal matrix composites Spark plasma sintering Interfaces Mechanical properties

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Atomic Ionic-scale Mechanism on Inclusion Modification by Calcium Treatment in the Electroslag Remelting Process Based on Ion and Molecule Coexistence Theory and Molecular Dynamics Simulation

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ISIJ International 2025年第3期65卷 350-359页

作者： Dong Li, Diyue Tian, Jialong Jiang, Zhouhua School of Metallurgy Northeastern University Shenyang China School of Materials Science and Engineering Northeastern University Shenyang China

In the course of industrial electroslag remelting (ESR), large-size Ca–Al–Mg–O nonmetallic inclusions were prone to form in 4Cr13 die steels and will deteriorate mechanical properties and service life seriously. In order to reveal the underlying mechanism, this work delves into the origins of Ca–Al–Mg–O inclusions in 4Cr13 die steel, establishing a correlation between inclusion characteristics and ESR slag composition. Utilizing molecular dynamics simulations, this work examines the CaO–Al2O3–CaF2–SiO2–MgO slag system, analyzing slag microstructure and the mean square displacement of Ca2+ ions. Combining the ion and molecule coexistence theory (IMCT), it was demonstrated that the key factor determining the total calcium (***) content and large-size Ca–Al–Mg–O inclusions in ESR steel is the concentration of free Ca2+ ions in the slag. In addition, a model for calculating free Ca2+ ions concentration in slag has been formulated based on IMCT. This model elucidates the influence of CaF2 and CaO on the concentration of free Ca2+ ions in slag. The empirical data facilitated the development of a modified slag composition with reduced CaF2 content, aiming to lower the *** content in steel and reduce the quantity and size of Ca–Al–Mg–O inclusions. These hypotheses have been verified through a series of laboratory and industrial trials. This is crucial for optimizing the ESR slag composition and enhancing the metallurgical quality of ESR steels. © 2025 The Iron and Steel Institute of Japan.

关键词： Slags

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Aligning enhanced feature representation for generalized zero-shot learning

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science China(Information sciences) 2025年第2期68卷 74-88页

作者： Zhiyu FANG Xiaobin ZHU Chun YANG Hongyang ZHOU Jingyan QIN Xu-Cheng YIN School of Computer & Communication Engineering University of Science and Technology Beijing

Constructing an effective common latent embedding by aligning the latent spaces of cross-modal variational autoencoders（VAEs） is a popular strategy for generalized zero-shot learning（GZSL）. However, due to the lack of fine-grained instance-wise annotations, existing VAE methods can easily suffer from the posterior collapse problem. In this paper, we propose an innovative asymmetric VAE network by aligning enhanced feature representation（AEFR） for GZSL. Distinguished from general VAE structures, we designed two asymmetric encoders for visual and semantic observations and one decoder for visual reconstruction. Specifically, we propose a simple yet effective gated attention mechanism（GAM） in the visual encoder for enhancing the information interaction between observations and latent variables, alleviating the possible posterior collapse problem effectively. In addition, we propose a novel distributional decoupling-based contrastive learning（D2-CL） to guide learning classification-relevant information while aligning the representations at the taxonomy level in the latent representation space. Extensive experiments on publicly available datasets demonstrate the state-of-the-art performance of our method. The source code is available at https://***/seeyourmind/AEFR.

关键词： generalized zero-shot learning gated attention mechanism contrastive learning multi-modal alignment

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A critical review on oxidation behavior of Co-based superalloys

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Chinese Journal of Aeronautics 2025年第3期38卷 183-206页

作者： Chenghao PEI Qingshuang MA Qiuzhi GAO Yue YANG Yuhang DU Hailian ZHANG Huijun LI School of Materials Science and Engineering Northeastern UniversityShenyang 110819China School of Resources and Materials Northeastern University at QinhuangdaoQinhuangdao 066004China School of Materials Science and Engineering Tianjin UniversityTianjin 300354China School of Mechanical Materials and Mechatronic EngineeringUniversity of WollongongWollongongNSW 2522Australia

The novel Co-based superalloys are extensively used in gas-powered and jet engine turbines due to their excellent high-temperature performance, achieved by strengthening the L12-γ′ ordered phase. This review presents an overview of the research progress on oxidation behavior of Co-based superalloys, including oxidation kinetics, oxides morphology, the formation and spallation of oxide layers, and importantly, the synergistic effects of alloying elements on oxidation resistance—a critical area considering the complex interactions with multiple alloying elements. Additionally, this review compares the oxidation resistance of single crystal versus polycrystalline alloys. The effect of phase interface and dislocations on oxidation behavior is also discussed. While significant progress has been achieved, areas necessitating further investigation include optimizing alloy compositions for enhanced oxidation resistance and understanding the long-term stability of oxide layers. The future prospects for Co-based superalloys are promising as ongoing research aims to address the existing challenges and unlock new applications at even higher operating temperatures.

关键词： Cobalt Superalloys Oxidation Alloying elements Microstructure Temperature

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