• Wind and Structures
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• v.34 no.6
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• pp.469-482
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• 2022

The generalized extreme value distribution (GEVD) is frequently used to fit the block maximum of environmental parameters such as the annual maximum wind speed. There are several methods for estimating the parameters of the GEV distribution, including the least-squares method (LSM). However, the application of the LSM with the expected order statistics has not been reported. This study fills this gap by proposing a fitting method based on the expected order statistics. The study also proposes a plotting position to approximate the expected order statistics; the proposed plotting position depends on the distribution shape parameter. The use of this approximation for distribution fitting is carried out. Simulation analysis results indicate that the developed fitting procedure based on the expected order statistics or its approximation for GEVD is effective for estimating the distribution parameters and quantiles. The values of the probability plotting correlation coefficient that may be used to test the distributional hypothesis are calculated and presented. The developed fitting method is applied to extreme thunderstorm and non-thunderstorm winds for several major cities in Canada. Also, the implication of using the GEVD and Gumbel distribution to model the extreme wind speed on the structural reliability is presented and elaborated.

• Geomechanics and Engineering
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• v.30 no.2
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• pp.107-121
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• 2022

Coal pillar assessment is of broad importance to underground engineering structure, as the pillar failure can lead to enormous disasters. Because of the highly non-linear correlation between the pillar failure and its influential attributes, conventional forecasting techniques cannot generate accurate outcomes. To approximate the complex behavior of coal pillar, this paper elucidates a new idea to forecast the underground coal pillar stability using combined unsupervised-supervised learning. In order to build a database of the study, a total of 90 patterns of pillar cases were collected from authentic engineering structures. A state-of-the art feature depletion method, t-distribution symmetric neighbor embedding (t-SNE) has been employed to reduce significance of actual data features. Consequently, an unsupervised machine learning technique K-mean clustering was followed to reassign the t-SNE dimensionality reduced data in order to compute the relative class of coal pillar cases. Following that, the reassign dataset was divided into two parts: 70 percent for training dataset and 30 percent for testing dataset, respectively. The accuracy of the predicted data was then examined using support vector classifier (SVC) model performance measures such as precision, recall, and f₁-score. As a result, the proposed model can be employed for properly predicting the pillar failure class in a variety of underground rock engineering projects.

• Tunnel and Underground Space
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• v.28 no.3
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• pp.232-246
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• 2018

In this study, the relationship between in situ seismic wave velocities and RMR (rock mass rating) was investigated in a test bed for the examination of the basis of rock classification (RMR) based on seismic wave velocity. The seismic wave velocity showed a monotonous increase with depth. It was also found that there was no systematic correlation between the seismic wave velocity (Vp) and other parameters (RQD, joint spacing, UCS, rock core Vp, and RMR) collected at the same depth of the same borehole. However, correlative relation was observed among RMR, RQD, and joint spacing. On the other hand, when all the data in the borehole (three holes) are examined without considering the depth, Vp still shows no correlation with RMR parameters (e.g., correlative coefficient for uniaxial compressive strength and joint spacing are 0.039 and 0.091, respectively), but Vp shows weak correlative relation with RMR and RQD (correlative coefficient for RQD and RMR are 0.193 and 0.211, respectively). Thus, it is found that it is difficult to deduce physical properties of rock mass directly from seismic wave velocities, but the seismic wave velocity can be used as a tool to approximate rock mass properties because of weaker correlation between Vp and RMR with RQD. In addition, the velocity value of for soft and moderate rocks suggested by widely used construction standards is slower than that of the observed velocity, implying that the standards need to be examined and revised.

• Sleep Medicine and Psychophysiology
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• v.19 no.1
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• pp.27-34
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• 2012

Objectives: The analysis of heart rate variability (HRV) is a useful non-invasive tool to investigate the autonomic nerve function. Previous studies on the relationship between HRV and depression have been reported controversial results. Similarly, the correlation between the serum lipids and depression is debatable. The purpose of this study is to examine the relationship between heart rate variability, lipid profile and depression. Methods: A total of 42 patients with major depressive disorder (MDD) and 32 age and sex-matched normal subjects who had no previous history of major medical and mental illnesses were recruited for this study. A structured-interview was used to assess the general characteristics and psychiatric illness. HRV measures were assessed by time-domain and frequency-domain analyses. Psychological symptoms were measured using the Hamilton rating scale for anxiety (HAM-A), Hamilton rating scale for depression (HAM-D). In addition, the evaluation for lipid profile was performed by blood test. Results: In serum lipid profile test, MDD group showed higher cholesterol ($197.68{\pm}42.94$ mg/dL vs. $176.85{\pm}34.68$ mg/dL, p=0.044), TG ($139.45{\pm}92.54$ mg/dL vs. $91.4{\pm}65.68$ mg/dL, p=0.018), LDL ($130.03{\pm}33.18$ vs. $106.62{\pm}27.08$, p=0.004) level than normal control group. In HRV time domain analyses, the standard deviation of the NN interval (SDNN) was decreased in MDD group than normal control group, but was not significant ($32.82{\pm}14.33$ ms vs. $40.36{\pm}21.40$ms, p=0.078). ApEn (Approximate Entrophy) was significantly increased in MDD group than normal control group ($1.13{\pm}0.11$ vs. $0.91{\pm}0.18$, p<0.001). ApEn was correlated with LDL level (r=0.277, p=0.028), HAM-D scores (r=0.534, p<0.001) and HAM-A scores (r=0.470, p<0.001). Conclusions: MDD patients showed increased ApEn, one of the HRV measurement. And this ApEn was correlated with LDL, HAM-D and HAM-A scores. In this study, the analysis of ApEn would be a useful test of MDD.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.20 no.2
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• pp.137-147
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• 2008

A reliability analysis has been performed to investigate the systematic stability of multi-failure modes of rubble-mound breakwaters. The reliability functions of four different failure modes are established straightforwardly. AFDA(Approximate Full Distribution Approcah) reliability models for each failure modes are directly developed and satisfactorily calibrated through the comparison with CIAD's results. In the reliability analysis of single failure mode, the probabilities of failure are calculated and the influence coefficients of random variables in the failure modes are properly evaluated. Meanwhile, three different models such as uni-modal bounds, bimodal bounds, and PNET are applied to evaluate the probabilities of failure of multi-failure modes for rubble-mound breakwaters. It may be found that uni-modal bounds tend to overestimate the probability of failure of multi-failure modes. Therefore, for the systematic reliability analysis of multi-failure modes, it is recommended to use bi-modal bounds or PNET which consider the correlation between the failure modes for rubble-mound breakwaters. By introducing the reliability analysis of multi-failure modes, it could be possible to find out the additional probabilities of failure occurred by the multi-failure modes of a multi-component system such as rubble-mound breakwaters.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.16 no.4
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• pp.233-240
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• 2004

For the development of empirical equation of run-up height, a new surf parameter called' wave action slope' $S_x$ is introduced. Approximate equation has been produced for each band of water depth for the computation of wave run-up height using the laboratory graph of Saville(1958). On the other hand using the laboratory data of Ahrens(1988) and Mase(1989), empirical equations of run-up height have been developed for the general application with considering roughness effect covering a wide range of water depth and wall slope. When Mase tried to relate the run-up height to the Iribarren number, nonlinear relation has been obtained and hence the empirical equation has a power law. But when the wave action slope is adopted as a major factor for the estimation of run-up height the empirical equation shows a linear relationship with very good correlation for the wide range of water depth and wall slope.

• Journal of the Korean Geotechnical Society
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• v.31 no.7
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• pp.41-52
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• 2015

Volcanic rocks in Jeju Island have vesicular structure caused by various environmental factors, and indicate the differences in geological and mechanical characteristics from region to region. In addition, the bedrock of Jeju Island shows stratified structure, that is, soft layers composed of pyroclastic rocks or cavities are irregularly developed between the basalt layers by several times of volcanic activity. In this study, various physical tests and unconfined compressive strength test were conducted for intact rocks sampled in northwestern onshore and offshore of Jeju Island. The results obtained in the tests were compared with the physical and mechanical characteristics of intact rocks sampled in southeastern offshore of Jeju Island. As a results, it was confirmed that the physical and mechanical characteristics of basalts sampled in northwestern Jeju Island were similar to those of basalts sampled in southeastern offshore of Jeju Island. In addition, it was possible to estimate approximate design parameters from the correlation of mechanical properties with physical properties of basalts in Jeju Island.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.34-40
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• 2006

The daytime(7 a.m to 10 p.m.) and the nighttime(10 p.m. to 7 a.m.) used to calculate existing $L_{dn}$ is different from the domestic daytime(6 a.m to 10 p.m.) and nighttime(10 p.m. to 6 a.m.) periods. The difference of a time periods makes too difficult for converting measured $L_{eq}$ during daytime($L_d$) and nighttime($L_n$) periods to $L_{dn}$. Thus, it is difficult to directly compare with $L_{dn}$ standard of a foreign country. The pupose of paper is to propose a proper experimental equations that make up for the problems. The data of this paper used road traffic noise data of Auto-Network System(ANS) that generates $L_{eq}$ TNI, $L_{NP}$ for 1 hour. A method of this paper is as follows.(1) The data of ANS converted 24 hour $L_{eq}$ which measured every 1 hour to existing $L_{dn}$ and to $L_{dn}$ of an experimental equations.(2) The existing Lan is compared to results of $L_{dn}$ from experimental equations. The paper proposes a three experimental equations. This paper select an approximate equation that was most similar, to existing $L_{dn}$ out of these equations. When $L_{eq}$ data of different daytime and nighttime periods are converted to $L_{dn}$, an experimental equation of this paper can be used and applied to $L_{dn}$'s calculation.

• Journal of Microbiology and Biotechnology
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• v.24 no.2
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• pp.209-216
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• 2014

The efficiency of gamma irradiation (0, 1, 5, 10, 15, 20, and 30 kGy) as a sterilization method of corn samples (30 g) artificially contaminated with Fusarium moniliforme stored at normal condition ($25^{\circ}C$ with approximate relative humidity (RH) of 55%) and optimal condition ($25^{\circ}C$ with a controlled RH of 97%) was studied. The results showed that the fungal growth and the amount of fumonisin were decreased as the dose of gamma irradiation increased. Gamma irradiation at 1-5 kGy treatment significantly inhibited the growth of F. moniliforme by 1-2 log reduction on corn samples (P < 0.05). Sublethal effect of gamma irradiation was observed at 10-20 kGy doses after storage, and a complete inactivation required 30 kGy. Fungal growth and fumonisin production increased with higher humidity and longer storage time in all corn samples. This study also demonstrated that there was no strict correlation between fungal growth and fumonisin production. Storage at normal condition significantly resulted in lower growth and fumonisin production of F. moniliforme as compared with those stored at optimal condition (P < 0.05). Gamma irradiation with the dose of ${\geq}5$ kGy followed by storage at normal condition successfully prolonged the shelf life of irradiated corns, intended for human and animal consumptions, up to 7 weeks.

• BMB Reports
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• v.31 no.5
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• pp.459-467
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• 1998

A new set of functional group interaction energy descriptors relevant to the ACE (Angiotensin-Converting Enzyme) inhibitory peptide, QSAR (Quantitative Structure Activity Relationships), is presented. The functional group interaction energies approximate the charged interactions and distances between functional groups in molecules. The effective energies of the computationally derived geometries are useful parameters for deriving 3D-QSAR models, especially in the absence of experimentally known active site conformation. ACE is a regulatory zinc protease in the renin-angiotensin system. Therapeutic inhibition of this enzyme has proven to be a very effective treatment for the management of hypertension. The non bond interaction energy values among functional groups of six-feature of ACE inhibitory peptides were used as descriptor terms and analyzed for multivariate correlation with ACE inhibition activity. The functional group interaction energy descriptors used in the regression analysis were obtained by a series of inhibitor structures derived from molecular mechanics and semi-empirical calculations. The descriptors calculated using electrostatic and steric fields from the precisely defined functional group were sufficient to explain the biological activity of inhibitor. Application of the descriptors to the inhibition of ACE indicates that the derived QSAR has good predicting ability and provides insight into the mechanism of enzyme inhibition. The method, functional group interaction energy analysis, is expected to be applicable to predict enzyme inhibitory activity of the rationally designed inhibitors.