Convergence acceleration and accuracy improvement in power bus impedance calculation with a fast algorithm using cavity modes

Based on the cavity-mode model, we have developed a fast algorithm for calculating power bus impedance in multilayer printed circuit boards. The fast algorithm is based on a closed-form expression for the impedance Z matrix of a rectangular power bus structure; this expression was obtained by reducing the original double infinite series into a single infinite series under an approximation. The convergence of the single series is further accelerated analytically. The accelerated single summation enables much faster computation, since use of only a few terms is enough to obtain good accuracy. In addition, we propose two ways to compensate for the error due to the approximation involved in the process of reducing the double series to the single series, and have demonstrated that these two techniques are almost equivalent

Data augmentation technique for construction engineering regression surrogate model

The objective of this study is to predict the degree of danger to the human body from motion information such as acceleration, velocity and displacement during a collision between a car and a human body. As a preliminary step, the maximum bending moment that occurs in the leg was predicted using a convolutional neural network. The responses which are represented by learning data generated by 1D-CAE system. A number of training data sets are varied in order to show the enough number to predict. The predictor's accuracy is evaluated by the test data sets. We'd like to discuss necessisty of a total number of training data sets and effectiveness of data augmentation technique. In addition, the technique to utilize classification by the t-SNE method to improve accuracy is also examined. t-SNE is based on classification algorithm, however an engineering interpolation should be computed based on physical meanings and influential parameters

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

Construction of a surrogate model for crash box corruption

The structural strength evaluation of crash boxes is predicted by machine learning in this study. The training data was obtained from the dynamic elastic plastic analysis of the crash box. The input physical quantities are barrier angle, box thickness, material properties and mass equivalent to vehicle weight. The output physical quantity is the reaction force. Buckling occurs in the analysis and different directions of corruptions are one of the most interesting phenomenon from a point of engineering view

Aerosol Extinction Coefficient Continuously Measured with Polarized Mie Scattering Lidar

Aerosol extinction coefficients of clouds and dust were continuously measured in the year of 2002 with a polarized Mie-scattering lidar controlled by an automatic and remotely operating system utilizing internet services. Measured cloud extinctions were greater than 1.0 km(-1) below the altitude 6 km, 0.17 - 1.0 km(-1) between 6 and 10 km, and 0.091 - 0.3 km(-1) beyond 10km. Extinction of dust were 0.10 and 0.20 km(-1) for Asian dust and 0.057 km(-1) for urban dust

Pulse Timing Control of Multiple Signal Interconnections for Reduction of EMI

This paper presents pulse timing control method to reduce electromagnetic emission from multiple signal interconnections. Pulse timing control gives intentional skew between signals. Higher order harmonics are canceled because of the difference of the phase between the signals. Using this property, pulse timing control can reduce the EMI in wide frequency range. In this paper, we show that radiated electromagnetic field from multiple signal lines reduces its intensity to the same level of the field from one line by using pulse timing control. The result of measurement shows that EMI from four differential transmission lines can be reduced more than 9 dB in the 200 MHz to 800 MHz frequency range

α-Synuclein Transgenic Drosophila As a Model of Parkinson's Disease and Related Synucleinopathies

α-Synuclein (α-Syn) is a major component of protein inclusions known as Lewy bodies, which are hallmarks of synucleinopathies such as Parkinson's disease (PD). The α-Syn gene is one of the familial PD-causing genes and is also associated with an increased risk of sporadic PD. Numerous studies using α-Syn expressing transgenic animals have indicated that α-Syn plays a critical role in the common pathogenesis of synucleinopathies. Drosophila melanogaster has several advantages for modeling human neurodegenerative diseases and is widely used for studying their pathomechanisms and therapies. In fact, Drosophila models expressing α-Syn have already been established and proven to replicate several features of human PD. In this paper, we review the current research on synucleinopathies using α-Syn Drosophila models and, moreover, explore the possibilities of these models for comprehensive genetic analyses and large-scale drug screening towards elucidating the molecular pathogenesis and developing therapies for synucleinopathies

Application of segmentation method to analysis of power/ground plane resonance in multilayer PCBs

The fast algorithm developed for calculating the resonant characteristics of the power/ground planes in multilayer PCBs, is extended to the case of that the pattern of the power/ground planes consists of several "segments" of rectangles, using the so-called segmentation method. Good agreements between the calculated and measured results have demonstrated the usefulness and accuracy of our fast algorithm and the segmentation method.</p

Proposal of Crack Propagation Criterion Considered Constraint Effect under Extremely Low Cycle Fatigue; Evaluation by 1.5T-CT Specimen

The prediction of fracture behavior under extremely low cycle fatigue due to excessive loading is necessary for the life assessment of structures. This study evaluates the validity of the crack propagation criterion proposed in a previous study by performing generation phase and application phase analysis based on the results of fracture tests on a&nbsp;1.5T-CT specimen (SGV410). The analysis show that the crack propagation criterion in the previous study predicted the experimental behavior well, however crack shape was incomplete in reproducing the crack shape