The quality of printed circuit board(PCB)micro-hole processing directly determines the stability of the inner and outer circuit connections.Micro-hole drilling technology is a typical method for PCB micro-hole process...The quality of printed circuit board(PCB)micro-hole processing directly determines the stability of the inner and outer circuit connections.Micro-hole drilling technology is a typical method for PCB micro-hole processing.The problem of optimal control of its drilling force is one of the main factors affecting the quality of micro-hole machining.To address this problem,the thrust forces and torques in PCB drilling were first modeled and analyzed,and the corresponding prediction models were established.The drilling force analysis was carried out through the micro-hole drilling experiment,the specific cutting energy under different feed rates was calculated,the influence of the size effect was clarified,and the accuracy of the prediction model was verified.The result shows that during the drilling of glass fiber cloth,changes in the material removal mechanism are induced as the feed per revolution is varied.When the feed per revolution is less than the tool edge radius,the glass fiber is not cut by the main cutting edge,but is crushed and broken.When the feed per revolution is greater than the radius of the tool edge,the glass fiber is cut by the main cutting edge.At the same time,the established analytical model can accurately reflect the influence of the size effect on the drilling torque in PCB micro-hole drilling,and the error is within 10%.This method has certain practical application value in controlling PCB micro hole processing quality.展开更多
Heterogeneous information networks,which consist of multi-typed vertices representing objects and multi-typed edges representing relations between objects,are ubiquitous in the real world.In this paper,we study the pr...Heterogeneous information networks,which consist of multi-typed vertices representing objects and multi-typed edges representing relations between objects,are ubiquitous in the real world.In this paper,we study the problem of entity matching for heterogeneous information networks based on distributed network embedding and multi-layer perceptron with a highway network,and we propose a new method named DEM short for Deep Entity Matching.In contrast to the traditional entity matching methods,DEM utilizes the multi-layer perceptron with a highway network to explore the hidden relations to improve the performance of matching.Importantly,we incorporate DEM with the network embedding methodology,enabling highly efficient computing in a vectorized manner.DEM's generic modeling of both the network structure and the entity attributes enables it to model various heterogeneous information networks flexibly.To illustrate its functionality,we apply the DEM algorithm to two real-world entity matching applications:user linkage under the social network analysis scenario that predicts the same or matched users in different social platforms and record linkage that predicts the same or matched records in different citation networks.Extensive experiments on real-world datasets demonstrate DEM's effectiveness and rationality.展开更多
基金National Natural Science Foundation of China(No.51805079)Fundamental Research Funds for the Central Universities,China(No.2232021D-15)Shanghai Science and Technology Program(No.20DZ2251400)。
文摘The quality of printed circuit board(PCB)micro-hole processing directly determines the stability of the inner and outer circuit connections.Micro-hole drilling technology is a typical method for PCB micro-hole processing.The problem of optimal control of its drilling force is one of the main factors affecting the quality of micro-hole machining.To address this problem,the thrust forces and torques in PCB drilling were first modeled and analyzed,and the corresponding prediction models were established.The drilling force analysis was carried out through the micro-hole drilling experiment,the specific cutting energy under different feed rates was calculated,the influence of the size effect was clarified,and the accuracy of the prediction model was verified.The result shows that during the drilling of glass fiber cloth,changes in the material removal mechanism are induced as the feed per revolution is varied.When the feed per revolution is less than the tool edge radius,the glass fiber is not cut by the main cutting edge,but is crushed and broken.When the feed per revolution is greater than the radius of the tool edge,the glass fiber is cut by the main cutting edge.At the same time,the established analytical model can accurately reflect the influence of the size effect on the drilling torque in PCB micro-hole drilling,and the error is within 10%.This method has certain practical application value in controlling PCB micro hole processing quality.
基金supported by the National Natural Science Foundation of China Youth Fund under Grant No.61902001.
文摘Heterogeneous information networks,which consist of multi-typed vertices representing objects and multi-typed edges representing relations between objects,are ubiquitous in the real world.In this paper,we study the problem of entity matching for heterogeneous information networks based on distributed network embedding and multi-layer perceptron with a highway network,and we propose a new method named DEM short for Deep Entity Matching.In contrast to the traditional entity matching methods,DEM utilizes the multi-layer perceptron with a highway network to explore the hidden relations to improve the performance of matching.Importantly,we incorporate DEM with the network embedding methodology,enabling highly efficient computing in a vectorized manner.DEM's generic modeling of both the network structure and the entity attributes enables it to model various heterogeneous information networks flexibly.To illustrate its functionality,we apply the DEM algorithm to two real-world entity matching applications:user linkage under the social network analysis scenario that predicts the same or matched users in different social platforms and record linkage that predicts the same or matched records in different citation networks.Extensive experiments on real-world datasets demonstrate DEM's effectiveness and rationality.