• Earthquakes and Structures
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• v.2 no.4
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• pp.357-376
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• 2011

Ground motion models predict the mean and standard deviation of the logarithm of spectral acceleration, as a function of predictor variables such as earthquake magnitude, distance and site condition. Such models have been developed for a variety of seismic environments throughout the world. Some calculations, such as the Conditional Mean Spectrum calculation, use this information but additionally require knowledge of correlation coefficients between logarithmic spectral acceleration values at multiple periods. Such correlation predictions have, to date, been developed primarily from data recorded in the Western United States from active shallow crustal earthquakes. This paper describes results from a study of spectral acceleration correlations from Japanese earthquake ground motion data that includes both crustal and subduction zone earthquakes. Comparisons are made between estimated correlations for Japanese response spectral ordinates and correlation estimates developed from Western United States ground motion data. The effect of ground motion model, earthquake source mechanism, seismic zone, site conditions, and source to site distance on estimated correlations is evaluated and discussed. Confidence intervals on these correlation estimates are introduced, to aid in identifying statistically significant differences in correlations among the factors considered. Observed general trends in correlation are similar to previous studies, with the exception of correlation of spectral accelerations between orthogonal components, which is seen to be higher here than previously observed. Some differences in correlations between earthquake source zones and earthquake mechanisms are observed, and so tables of correlations coefficients for each specific case are provided.

• Science of Emotion and Sensibility
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• v.26 no.1
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• pp.17-32
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• 2023

This study aims to study the impact of pet attachment on subjective well-being, focusing on individuals who live with pets. In addition, it is to recognize that their basic psychological requirement mediates between pet attachment and subjective well-being. For this purpose, a survey was performed on 358 adults living with pets nationwide. The final data of 319 people were evaluated after excluding invalid information. Dependent on the theoretical approach of the attachment theory, the human-pet relationship was examined by dividing it into two orthogonal dimensions pet attachment prevention and pet attachment anxiety(Zilcha-Mano et al., 2011). The mediating effects were investigated as an in-depth mechanism that mediates between pet attachment and subjective well-being, the mediating effects were examined, in terms of the three basic psychological needs of Self-Determination Theory, which are autonomy, competence, and relatedness. As an outcome, first, pet attachment prevention and pet attachment anxiety both revealed a negative correlation with subjective well-being. Second, basic psychological needs, which are autonomy, competence, and relatedness, are mediated between pet attachment and subjective well-being. Autonomy, competence, and relatedness fully mediated the relationship between pet attachment avoidance and subjective well-being. Meanwhile, in the case of pet attachment anxiety, only autonomy among basic psychological needs is fully mediated between pet attachment anxiety and subjective well-being in the case of pet attachment avoidance. This means that pet attachment prevention or pet attachment anxiety correlates with subjective well-being by satisfying basic psychological needs instead of directly affecting personal well-being. Regarding the pet effect, it is meaningful to find an in-depth mechanism that the human-pet relationship has for an adaptive and positive impact on humans.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.06a
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• pp.31-31
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• 2010

The growth of the high-quality GaN epilayers is of significant technological importance because of their commercializedoptoelectronic applications as high-brightness light-emitting diodes (LEDs) and laser diodes (LDs) in the visible and ultraviolet spectral range. The GaN-based heterostructural epilayers have the polar c-axis of the hexagonal structure perpendicular to the interfaces of the active layers. The Ga and N atoms in the c-GaN are alternatively stacked along the polar [0001] crystallographic direction, which leads to spontaneous polarization. In addition, in the InGaN/GaN MQWs, the stress applied along the same axis contributes topiezoelectric polarization, and thus the total polarization is determined as the sum of spontaneous and piezoelectric polarizations. The total polarization in the c-GaN heterolayers, which can generate internal fields and spatial separation of the electron and hole wave functions and consequently a decrease of efficiency and peak shift. One of the possible solutions to eliminate these undesirable effects is to grow GaN-based epilayers in nonpolar orientations. The polarization effects in the GaN are eliminated by growing the films along the nonpolar [$11\bar{2}0$] ($\alpha$-GaN) or [$1\bar{1}00$] (m-GaN) orientation. Although the use of the nonpolar epilayers in wurtzite structure clearly removes the polarization matters, however, it induces another problem related to the formation of a high density of planar defects. The large lattice mismatch between sapphiresubstrates and GaN layers leads to a high density of defects (dislocations and stacking faults). The dominant defects observed in the GaN epilayers with wurtzite structure are one-dimensional (1D) dislocations and two-dimensional (2D) stacking faults. In particular, the 1D threading dislocations in the c-GaN are generated from the film/substrate interface due to their large lattice and thermal coefficient mismatch. However, because the c-GaN epilayers were grown along the normal direction to the basal slip planes, the generation of basal stacking faults (BSFs) is localized on the c-plane and the generated BSFs did not propagate into the surface during the growth. Thus, the primary defects in the c-GaN epilayers are 1D threading dislocations. Occasionally, the particular planar defects such as prismatic stacking faults (PSFs) and inversion domain boundaries are observed. However, since the basal slip planes in the $\alpha$-GaN are parallel to the growth direction unlike c-GaN, the BSFs with lower formation energy can be easily formed along the growth direction, where the BSFs propagate straightly into the surface. Consequently, the lattice mismatch between film and substrate in $\alpha$-GaN epilayers is mainly relaxed through the formation of BSFs. These 2D planar defects are placed along only one direction in the cross-sectional view. Thus, the nonpolar $\alpha$-GaN films have different atomic arrangements along the two orthogonal directions ($[0001]_{GaN}$ and $[\bar{1}100]_{GaN}$ axes) on the $\alpha$-plane, which are expected to induce anisotropic biaxial strain. In this study, the anisotropic strain relaxation behaviors in the nonpolar $\alpha$-GaN epilayers grown on ($1\bar{1}02$) r-plane sapphire substrates by metalorganic chemical vapor deposition (MOCVO) were investigated, and the formation mechanism of the abnormal zigzag shape PSFs was discussed using high-resolution transmission electron microscope (HRTEM).