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A metric normalization of tree edit distance

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Frontiers of Computer Science 2011年第1期5卷 119-125页

作者： Yujian Li (1) liyujian@*** Zhang Chenguang (12) Beijing Univ Technol Coll Comp Sci & Technol Beijing 100124 Peoples R China Hainan Univ Coll Informat Sci & Technol Haikou 570228 Peoples R China

Traditional normalized tree edit distances do not satisfy the triangle inequality. We present a metric normalization method for tree edit distance, which results in a new normalized tree edit distance fulfilling the triangle inequality, under the condition that the weight function is a metric over the set of elementary edit operations with all costs of insertions/deletions having the same weight. We prove that the new distance, in the range [0, 1], is a genuine metric as a simple function of the sizes of two ordered labeled trees and the tree edit distance between them, which can be directly computed through tree edit distance with the same complexity. Based on an efficient algorithm to represent digits as ordered labeled trees, we show that the normalized tree edit metric can provide slightly better results than other existing methods in handwritten digit recognition experiments using the approximating and eliminating search algorithm （AESA） algorithm.

关键词： metric normalization tree edit distance,triangle inequality approximating and eliminating searchalgorithm (AESA)

Behavior pattern extraction by trajectory analysis

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Frontiers of Computer Science 2011年第1期5卷 37-44页

作者： Jia Wen (12) wjyanyuan@*** Chao Li (1) Zhang Xiong (1) Beihang Univ Sch Engn & Comp Sci Beijing 100191 Peoples R China Yanshan Univ Dept Comp Coll Informat Sci & Engn Qinhuangdao 066004 Peoples R China

Trajectory clustering and behavior pattern extraction are the foundations of research into activity perception of objects in motion. In this paper, a new framework is proposed to extract behavior patterns through trajectory analysis. Firstly, we introduce directional trimmed mean distance （DTMD）, a novel method used to measure similarity between trajectories. DTMD has the attributes of anti-noise, self-adaptation and the capability to determine the direction for each trajectory. Secondly, we use a hierarchical clustering algorithm to cluster trajectories. We design a length-weighted linkage rule to enhance the accuracy of trajectory clustering and reduce problems associated with incomplete trajectories. Thirdly, the motion model parameters are estimated for each trajectory＇s classification, and behavior patterns for trajectories are extracted. Finally, the difference between normal and abnormal behaviors can be distinguished.

关键词： trajectory clustering directional trimmedmean distance (DTMD) behavior pattern extraction

Identifying different community members in complex networks based on topology potential

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Frontiers of Computer Science 2011年第1期5卷 87-99页

作者： Yanni Han (1) hyn@*** Deyi Li (12) Teng Wang (1) State Key Laboratory of Software Development Environment Beijing University of Aeronautics and Astronautics Beijing 100191 China Institute of Electronic System Engineering Beijing 100039 China

There has been considerable interest in designing algorithms for detecting community structure in real-world complex networks. A majority of these algorithms assume that communities are disjoint, placing each vertex in only one cluster. However, in nature, it is a matter of common experience that communities often overlap and members often play multiple roles in a network topology. To further investigate these properties of overlapping communities and heterogeneity within the network topology, a new method is proposed to divide networks into separate communities by spreading outward from each local important element and extracting its neighbors within the same group in each spreading operation. When compared with the state of the art, our new algorithm can not only classify different types of nodes at a more fine-grained scale successfully but also detect community structure more effectively. We also evaluate our algorithm using the standard data sets. Our results show that it performed well not only in the efficiency of algorithm, but also with a higher accuracy of partition results.

关键词： complex network community structure,topology potential overlapping nodes

Soft spectral clustering ensemble applied to image segmentation

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Frontiers of Computer Science 2011年第1期5卷 66-78页

作者： Jianhua Jia (12) jjh163yx@*** Bingxiang Liu (1) Licheng Jiao (2) Jingdezhen Ceram Inst Sch Informat Engn Jingdezhen 333002 Peoples R China Xidian Univ Key Lab Intelligent Percept & Image Understanding Minist Educ China Xian 710071 Peoples R China Xidian Univ Inst Intelligent Informat Proc Xian 710071 Peoples R China

An unsupervised learning algorithm, named soft spectral clustering ensemble （SSCE）, is proposed in this paper. Until now many proposed ensemble algorithms cannot be used on image data, even images of a mere 256 × 256 pixels are too expensive in computational cost and storage. The proposed method is suitable for performing image segmentation and can, to some degree, solve some open problems of spectral clustering （SC）. In this paper, a random scaling parameter and Nystrǒm approximation are applied to generate the individual spectral clusters for ensemble learning. We slightly modify the standard SC algorithm to aquire a soft partition and then map it via a centralized logcontrast transform to relax the constraint of probability data, the sum of which is one. All mapped data are concatenated to form the new features for each instance. Principal component analysis （PCA） is used to reduce the dimension of the new features. The final aggregated result can be achieved by clustering dimension-reduced data. Experimental results, on UCI data and different image types, show that the proposed algorithm is more efficient compared with some existing consensus functions.

关键词： spectral clustering (SC) Nystrrm approxi-mation centralized logcontrast transform principal component analysis (PCA) ensemble learning

Impact of chosen force fields and applied load on thin film lubrication

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作者： 12-229

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作者： 12-229

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作者： 12-160

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作者： 12-93

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Friction 2021年第5期9卷 1259-1274页

作者： Thi D.ta Hien D.ta Kiet A.TIEU Bach H.TRAN School of Mechanical MaterialsMechatronicsand Biomedical EngineeringUniversity of WollongongNSW 2522Australia Ho Chi Minh City University of Technology and Education Ho Chi Minh City 800010Vietnam

The rapid development of molecular dynamics(MD)simulations,as well as classical and reactive atomic potentials,has enabled tribologists to gain new insights into lubrication performance at the fundamental ***,the impact of adopted potentials on the rheological properties and tribological performance of hydrocarbons has not been researched *** extensive study analyzed the effects of surface structure,applied load,and force field(FF)on the thin film lubrication of *** lubricant film became more solid‐like as the applied load *** particular,with increasing applied load,there was an increase in the velocity slip,shear viscosity,and *** degree of ordering structure also changed with the applied load but rather *** was also significantly dependent on the surface *** chosen FFs significantly influenced the lubrication performance,rheological properties,and molecular *** adaptive intermolecular reactive empirical bond order(AIREBO)potential resulted in more significant liquid‐like behaviors,and the smallest velocity slip,degree of ordering structure,and shear stress were compared using the optimized potential for liquid simulations of united atoms(OPLS‐UAs),condensed‐phase optimized molecular potential for atomic simulation studies(COMPASS),and ***,classical potentials,such as OPLS‐UA and COMPASS,exhibit more solid‐like behavior than reactive potentials ***,owing to the solid‐like behavior,the lubricant temperatures obtained from OPLS‐UA and COMPASS were much lower than those obtained from AIREBO and *** increase in shear stress,as well as the decrease in velocity slip with an increase in the surface potential parameterζ,remained conserved for all chosen FFs,thus indicating that the proposed surface potential parameterζfor the COMPASS FF can be verified for a wide range of atomic models.

关键词： molecular dynamics simulation force fields applied load tribofilm hydrocarbon