DISCRETE SINGULAR CONVOLUTION METHOD WITH PERFECTLY MATCHED ABSORBING LAYERS FOR THE WAVE SCATTERING BY PERIODIC STRUCTURES

A new computational algorithm is introduced for solving scattering problem in periodic structure. The PML technique is used to deal with the difficulty on truncating the unbounded domain while the DSC algorithm is utilized for the spatial discretization. The present study reveals that the method is efficient for solving the problem.

REQUIREMENTS AND DESIGN METHOD FOR MATCHING AIRCRAFT GUNS WITH THEIR SUPPORTING STRUCTURE

In aircraft structural dynamic design the matching of guns with their supporting structure is one of the most important tasks on which hinges the success or failure of the structural design. The design curves for matching guns with their supporting structure can be obtained from response calculations of the plate-spring system supporting the gun on the ground,the model structure tested on the ground and the actual structure.A set of matching curves is given for engineering application.Then,the matching design can be accomplished by means of impact load spectrograms so as to perform an optimal structural design and to make further improvements on dynamic design program.

Heuristic Backtrack Algorithm for Structural Match and Its Applications

The concept WALKING on structures is proposed, and the partial ordering between a structure and a query structure (substructure) is also created by means of WALKING. Based upon the above concepts, authors create the Heuristic-Backtracking Algorithm (HBA) of structural match with high performance. In the last part of the paper, the applications of HBA in molecular graphics, synthetic planning, spectrum simulation , the representation and recognition of general structures are discussed.

Financial Structure,Technology,and Economic Growth:A Structural Matching Perspective

Different types of capital are better suited to financing technologies with different risk profiles,and structural matching between finance and technology may critically influence economic growth.Using cross-province panel data from China,we estimated the impact of the matching relationship between regions'financial structure and technology level on economic growth.We show that:(ⅰ)the matching relationship had a statistically significant positive impact on economic growth;(ⅱ)structural mismatching reduced economic growth in comparison with the optimal matching point;(ⅲ)structural matching better facilitated economic growth in more developed regions;and(ⅳ)capital accumulation and technological progress were two of the main channels through which matching influenced economic growth.We address potential endogeneity concerns and perform robustness checks,and our results remain valid.Our findings provide convincing evidence for the optimalfinancial structure theory and explain China's rapid growth despite its comparatively underdeveloped securities market.

Research on Damage Localization of Plate-like Structure Using Mode Acoustic Emission and Matching Pursuit

Based on mode acoustic emission theory,the paper analyses the acoustic emission analog signal of thin steel plate using matching pursuit,then obtains the characteristics interpretation of the different frequency signal energy concentration degree; Combined with four-point arc positioning method,the papers researches the damage localization of the plate-like structure. Simulation experiment shows that this method can accurately detect and locate the damage. This can provide data support for further imaging research based on time reverse theory.

Matching user identities across social networks with limited profile data

Privacy preservation is a primary concern in social networks which employ a variety of privacy preservations mechanisms to preserve and protect sensitive user information including age,location,education,interests,and others.The task of matching user identities across different social networks is considered a challenging task.In this work,we propose an algorithm to reveal user identities as a set of linked accounts from different social networks using limited user profile data,i.e,user-name and friendship.Thus,we propose a framework,ExpandUIL,that includes three standalone al-gorithms based on(i)the percolation graph matching in Ex-pand FullName algorithm,(i)a supervised machine learning algorithm that works with the graph embedding,and(ii)a combination of the two,ExpandUserLinkage algorithm.The proposed framework as a set of algorithms is significant as,(i)it is based on the network topology and requires only name feature of the nodes,(i)it requires a considerably low initial seed,as low as one initial seed suffices,(ii)it is iterative and scalable with applicability to online incoming stream graphs,and(iv)it has an experimental proof of stability over a real ground-truth dataset.Experiments on real datasets,Instagram and VK social networks,show upto 75%recall for linked ac-counts with 96%accuracy using only one given seed pair.