• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.1-15
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• 2012

Marine scientific monitoring, including monitoring of oil pollution, marine ecosystems, and the marine environment in general, has been being carried out continuously in order to assess the impact of oil pollution since the Hebei Spirit oil spill in December 2007. GIS thematic maps containing visual and summarized information are very useful for conducting exploratory analyses on the spatio-temporal variability of the marine environment and marine ecosystems due to oil pollution. Defining map types and building a legend in accordance with data characteristics are essential elements for mapping. In the present study, map types were defined according to the data attributes and GIS data types for each data item and classification of data intervals for the legend was defined by using two data distribution types through a histogram analysis. The data interval method was defined as follows: If the histogram of data has a uniform distribution, an equal interval method is applied; in the case of a normal distribution, a standard deviation method is applied. In addition, thematic map templates were made for each map type through the definition of marginal elements. Through the establishment of systematic mapping methods and procedures in this study, it was possible to effectively make standardized thematic maps for various kinds of marine scientific data.

• Journal of the Korean Geotechnical Society
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• v.38 no.3
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.

• Korean Journal of Radiology
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• v.22 no.8
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• pp.1266-1278
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• 2021

Objective: We aimed to compare the aortic valve area (AVA) calculated using fast high-resolution three-dimensional (3D) magnetic resonance (MR) image acquisition with that of the conventional two-dimensional (2D) cine MR technique. Materials and Methods: We included 139 consecutive patients (mean age ± standard deviation [SD], 68.5 ± 9.4 years) with aortic valvular stenosis (AS) and 21 asymptomatic controls (52.3 ± 14.2 years). High-resolution T2-prepared 3D steady-state free precession (SSFP) images (2.0 mm slice thickness, 10 contiguous slices) for 3D planimetry (3DP) were acquired with a single breath hold during mid-systole. 2D SSFP cine MR images (6.0 mm slice thickness) for 2D planimetry (2DP) were also obtained at three aortic valve levels. The calculations for the effective AVA based on the MR images were compared with the transthoracic echocardiographic (TTE) measurements using the continuity equation. Results: The mean AVA ± SD derived by 3DP, 2DP, and TTE in the AS group were 0.81 ± 0.26 cm², 0.82 ± 0.34 cm², and 0.80 ± 0.26 cm², respectively (p = 0.366). The intra-observer agreement was higher for 3DP than 2DP in one observer: intraclass correlation coefficient (ICC) of 0.95 (95% confidence interval [CI], 0.94-0.97) and 0.87 (95% CI, 0.82-0.91), respectively, for observer 1 and 0.97 (95% CI, 0.96-0.98) and 0.98 (95% CI, 0.97-0.99), respectively, for observer 2. Inter-observer agreement was similar between 3DP and 2DP, with the ICC of 0.92 (95% CI, 0.89-0.94) and 0.91 (95% CI, 0.88-0.93), respectively. 3DP-derived AVA showed a slightly higher agreement with AVA measured by TTE than the 2DP-derived AVA, with the ICC of 0.87 (95% CI, 0.82-0.91) vs. 0.85 (95% CI, 0.79-0.89). Conclusion: High-resolution 3D MR image acquisition, with single-breath-hold SSFP sequences, gave AVA measurement with low observer variability that correlated highly with those obtained by TTE.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.30 no.2
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• pp.188-202
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• 1997

The seasonal variability of the sea surface winds over the last Sea of Korea (Japan Sea) is investigated by means of empirical orthogonal function (EOF) analysis. The combined representation of fields of three climatic variables by empirical orthogonal functions is discussed. The eigenvectors are derived from daily sea level pressure, wind speed and 10-day mean sea surface temperature (SST) during 15 years $(1978\~1992)$. The spatial patterns of the mean pressure are characterized by the high pressure in the western part and the low pressure in the eastern part. The spatial distribution of the standard deviation (SD) of pressure are characterized by max SD of 6.6 mb near the Vladivostok, and minima along the coast of the Japan. In Vladivostok, the maxima of SD of SST and south-north wind (WV) were also occurred. The representation of fields of individual meteorological variables by EOF shows that the first mode of the west-east wind (WU) explain over $47.3\%$ of the variance and the second mode of WU represents $30\%$. Especially, the first mode of the WV explain $70.9\%$ of the variance and their time series coefficients show 1-cpy, 0.5-cpy frequency spectrum. The spatial distribution of the first mode eigenvectors of SST are characterized by maximum near Vladivostok. The combined representation of fields of several variables (pressure, wind, SST) reveals that the first mode magnitudes of the variance of the combined eigenvectors (WU-PR) are increased. By means of this result, the 1-year peak and the 6-months peak are remarkable. In the three combined patterns (wind, pressure, SST), the second mode of the eigenvector (wind) is affected by the SST. Their time coefficients of the first mode show noticeable 1-year peak. The spectral analysis of the second mode shows broad seasonal signal with the period of 4-months and a significant peak of variability at 3-month period.

• Science of Emotion and Sensibility
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• v.9 no.2
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• pp.111-118
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• 2006

The purpose of the study is to examine the effects of the positive menial stress, eustress, on autonomic nervous system(ANS) and human health. For this, we analyzed heart rate variability(HRV) parameters, the most promising markers of ANS function to assess the changes of emotional and physiological states of human body. We measured HRV Signal of World Cup group(281 male subjects: $29.8{\pm}5.6yr$., 187 female subjects: $29.0{\pm}5.4yr$.) in two stadiums at least an hour before the game during '2002 FIFA World Cup Korea/Japan' event. We also measured control group's(331 male subjects: $30.9{\pm}4.7 yr$., 344 female subjects: $30.2{\pm}5.2 yr$.) in the health promotion centers in two university hospitals at least a month before and after the world cup event period. Considering physiological differences between males and females, the data analysis was applied to 'male group' and 'female group' separately. As a result, some tendency was observed that is different from what we have known as the stress reaction. In general, all parameter values except that of mean heart rate tend to decrease under stressed condition. However, under eustressed condition, both heart rate and standard deviation of the Normal to Normal intervals(SDNN) were higher then those of normal condition(p<0.05). Especially, in case of female group, contrary to distressed condition, every frequency-domain powers showed tile higher value(p<0.05, p<0.001). Considering that decrease of HRV indicates the loss of one's health, the increase of SDNN and frequency parameters means that homeostasis control mechanism of ANS is functioning positively. Accordingly, induction of eustress from international sports event may affect positively to the people's health.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.661-676
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• 2017

This study suggests a new method not only to produce the 1 km-resolution seasonal prediction but also to improve the seasonal prediction skill of temperature over South Korea. This method consists of four stages of experiments. The first stage, EXP1, is a low-resolution seasonal prediction of temperature obtained from Pusan National University Coupled General Circulation Model, and EXP2 is to produce 1 km-resolution seasonal prediction of temperature over South Korea by applying statistical downscaling to the results of EXP1. EXP3 is a seasonal prediction which considers the effect of temperature changes according to the altitude on the result of EXP2. Here, we use altitude information from ASTER GDEM, satellite observation. EXP4 is a bias corrected seasonal prediction using genetic algorithm in EXP3. EXP1 and EXP2 show poorer prediction skill than other experiments because the topographical characteristic of South Korea is not considered at all. Especially, the prediction skills of two experiments are lower at the high altitude observation site. On the other hand, EXP3 and EXP4 applying the high resolution elevation data based on remote sensing have higher prediction skill than other experiments by effectively reflecting the topographical characteristics such as temperature decrease as altitude increases. In addition, EXP4 reduced the systematic bias of seasonal prediction using genetic algorithm shows the superior performance for temporal variability such as temporal correlation, normalized standard deviation, hit rate and false alarm rate. It means that the method proposed in this study can produces high-resolution and high-quality seasonal prediction effectively.

• The Journal of the Petrological Society of Korea
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• v.18 no.4
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• pp.315-336
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• 2009

We have studied the orientational characteristics of microcrack frequency, it's length and density in Tertiary crystalline tuff from the northeastern part of the Gyeongsang Basin. 134 sets of microcracks on horizontal surfaces of 3 rock samples from Heunghae-eup were distinguished by enlarged photomicrographs of the thin sections. The variability in patterns among microcrack length-frequency histograms for three rock samples from different altitudes were derived. The pattern of histograms changes progressively from negative exponential form to log-normal form in proportion to altitude. The distribution pattern for rock sample no.1 from lower altitude shows the broad length distribution characterized by higher mean and median, and higher standard deviation. Meanwhile, this distribution pattern corresponds with characteristics of joint length distribution in sedimentary rocks of the lower part of the Gyeongsang Supergroup. The occurrence frequency of shorter microcracks increases toward both NW and NE directions from the $N0{\sim}10^{\circ}W$, with the dominant direction of $N80{\sim}90^{\circ}W$ and $N80{\sim}90^{\circ}E$, respectively. This distribution pattern represents the relative differences in formation timing among microcrack sets and the result of the new initiation of shorter microcracks. Meanwhile, the longest microcracks within $N60{\sim}70^{\circ}W$($L_{max}$:1.18 mm) and $N0{\sim}10^{\circ}W$($L_{max}$:0.80 mm) directions are seen, but this kind of microcracks are very limited in number. Whole domain of the directional angle($\theta$)-frequency(N), length(L) and density($\rho$) chart can be divided into five sections in terms of phases of the distribution of related curves. From the distribution chart, density curve shows five distinct peaks in the WNW-ESE($N70{\sim}80^{\circ}W$), NS~NNE-SSW($N0{\sim}10^{\circ}W$, $N10{\sim}20^{\circ}E$), ENE-WSW($N50{\sim}60^{\circ}E$), and nearly EW($N80{\sim}90^{\circ}E$) directions, respectively. Especially, main directions of faults correspond with the directional angle showing high density. Consequently, these distribution patterns of density curve reflect the representative maximum principal stress orientations suggested in previous studies.