Prediction of warp distortion in circuit board using machine learning

A convolutional neural network, which reproduce a function by data, was used to predict the amount of warp distortion of a four-layer circuit board in a reflow soldering process. The data used for training are material properties such as Young's modulus, board thickness, and residual copper content as input data, and the predicted warp distortion data is the amount of warpage of the circuit board obtained from the measurement. Since a number of distortion data to be predicted was insufficient to be used for training, a newly proposed data augmentation method used to increase a number of data. The augmentation method is evaluated through the result of the predictions and discussed

Estimation of Ground Resisitivity Distribution Using 3D DRM Charge Simulation Modelling

Resistivity distribution sounding of the non-homogeneous earth is important for electrical ground system design, geophysical prospecting and survey or monitoring the groundwater flow level. The previous paper presented that the direct inversion of the electric resistivity distribution in a domain is possible from the impedance data measured over the domain boundary using the dual reciprocity boundary element modelling in two-dimentional field [1]. The proposed inversion technique is extended to the distribution in three-dimensional space [2]. This technique is capable of inversion without iteration and meshing of the domain. Electric field with spatially varying conductivity is governed by Laplace equation, which is transformed into a Poisson-type expression with an inhomogeneous term involving the conductivity difference as a source term. Dual reciprocity method (DRM) is a technique for transforming the domain integral associated with the inhomogeneous term in Poisson equation into the boundary integral expression. The resistivity distribution in the field can thus be identified from the data observed over its boundary, for which some examples are demonstrated [2]. In this paper, the examination is extended to the case where only the data measured over the single surface is used for the inversion

Induction of Oocyte Maturation by Calyculin A in Starfish(Developmental Biology)

Volume: 8Start Page: 201End Page: 20