• Wind and Structures
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• v.31 no.4
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• pp.363-371
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• 2020

Proper understanding of offshore wind speed variability is of essential importance in practice, which provides useful information to a wide range of coastal and marine activities. In this paper, long-term wind speed data recorded at various offshore stations are analyzed in the framework of fractal dimension analysis. Fractal analysis is a well-established data analysis tool, which is particularly suitable to determine the complexity in time series from a quantitative point of view. The fractal dimension is estimated using the conventional box-counting method. The results suggest that the wind speed data are generally fractals, which are likely to exhibit a persistent nature. The mean fractal dimension varies from 1.31 at an offshore weather station to 1.43 at an urban station, which is mainly associated with surface roughness condition. Monthly variability of fractal dimension at offshore stations is well-defined, which often possess larger values during hotter months and lower values during winter. This is partly attributed to the effect of thermal instability. In addition, with an increase in measurement interval, the mean and minimum fractal dimension decrease, whereas the maximum and coefficient of variation increase in parallel.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.4
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• pp.221-237
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• 2005

For developing the site-specific fertilizer management strategies of crop, it is essential to know the spatial variability of soil factors and to assess their influence on the variability of crop growth and yield. In 2002 and 2003 cropping seasons within-field spatial variability of rice growth and yield was examined in relation to spatial variation of soil properties in the· two paddy fields having each area of ca. $6,600m^2$ in Suwon, Korea. The fields were managed without fertilizer or with uniform application of N, P, and K fertilizer under direct-seeded and transplanted rice. Stable soil properties such as content of clay (Clay), total nitrogen (TN), organic mater (OM), silica (Si), cation exchange capacity (CEC), and rice growth and yield were measured in each grid of $10\times10m$. The two fields showed quite similar spatial variation in soil properties, showing the smallest coefficient of variation (CV) in Clay $(7.6\%)$ and the largest in Si $(21.4\%)$. The CV of plant growth parameters measured at panicle initiation (PIS) and heading stage (HD) ranged from 6 to $38\%$, and that of rice yield ranged from 11 to $21\%$. CEC, OM, TN, and available Si showed significant correlations with rice growth and yield. Multiple linear regression model with stepwise procedure selected independent variables of N fertilizer level, climate condition and soil properties, explaining as much as $76\%$ of yield variability, of which $21.6\%$ is ascribed to soil properties. Among the soil properties, the most important soil factors causing yield spatial variability was OM, followed by Si, TN, and CEC. Boundary line response of rice yield to soil properties was represented well by Mitcherich equation (negative exponential equation) that was used to quantify the influence of soil properties on rice yield, and then the Law of the Minimum was used to identify the soil limiting factor for each grid. This boundary line approach using five stable soil properties as limiting factor explained an average of about $50\%$ of the spatial yield variability. Although the determination coefficient was not very high, an advantage of the method was that it identified clearly which soil parameter was yield limiting factor and where it was distributed in the field.

• Geomechanics and Engineering
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• v.20 no.1
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• pp.19-28
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• 2020

The spatial variability of geotechnical properties can lead to the uncertainty of settlement for frozen soil foundation around the oil pipeline, and it can affect the stability of permafrost foundation. In this paper, the elastic modulus, cohesion, angle of internal friction and poisson ratio are taken as four independent random fields. A stochastic analysis model for the uncertain settlement characteristic of frozen soil foundation around an oil pipeline is presented. The accuracy of the stochastic analysis model is verified by measured data. Considering the different combinations for the coefficient of variation and scale of fluctuation, the influences of spatial variability of geotechnical properties on uncertain settlement are estimated. The results show that the stochastic effects between elastic modulus, cohesion, angle of internal friction and poisson ratio are obviously different. The deformation parameters have a greater influence on stochastic settlement than the strength parameters. The overall variability of settlement reduces with the increase of horizontal scale of fluctuation and vertical scale of fluctuation. These results can improve our understanding of the influences of spatial variability of geotechnical properties on uncertain settlement and provide a theoretical basis for the reliability analysis of pipeline engineering in permafrost regions.

• Korean Journal of Psychosomatic Medicine
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• v.21 no.1
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• pp.55-61
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• 2013

Objectives : Alzheimer's disease(AD) and mild cognitive impairment(MCI) affect several nervous structures involved with the autonomic nervous system. Association between neuropsychiatric deficits and heart rate variability has been observed. But cardiac autonomic function in AD has been scarcely studied and the results reported are conflicting. We investigated autonomic function in normal control, MCI, AD using heart rate variability(HRV) technique. Methods : Time and frequency-domain variability of 5-min R-R interval series was comparatively evaluated in 26 normal control subjects, 22 MCI subjects and 34 AD subjects. Analysis of variance(ANOVA) was used to compare the differences across groups. Correlations between MMSE-KC and HRV components were performed using Pearson's correlation coefficient. Results : No significant difference was observed among the groups in time, frequency-domain analysis of HRV(p>0.05). HRV were not found to be significantly correlated with the degree of cognitive impairment. Conclusions : There were no differences in HRV with MCI, AD subjects when compared with normal controls. Further investigation is required to use HRV technique as noninvasive parameters of MCI and AD.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.594-596
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• 2003

Due to the fact that the composition and variability of aerosols is considered rather complex, it is difficult to employ a simple and straightforward physical model in calculating the aerosol size distribution in the absence of actual data. This complicates the already difficult retrieval of various atmospheric parameters from remotely sensed data. Thus, the main purpose of this study is trying to find an effective aerosol size coefficient that is stable, and can depict the particle size distribution. This paper also attempts to construct an 'effective aerosol size coefficient' database for each respective season, where it can quickly and effectively supply pertinent information of the atmosphere's opacity.

• Atmosphere
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• v.34 no.3
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• pp.283-304
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• 2024

This study analyzed the variability and correlation between ground-level air pollutant concentrations and the atmospheric mixing layer height using data from four types of air pollutants (PM_2.5, PM₁₀, NO₂, and O₃) collected at AirKorea monitoring stations nationwide over a five-year period (2018~2022), and aerosol backscatter data observed by the Vaisala CL31 to derive atmospheric mixing layer heights. The five-year trends and variability of ground-level air pollutant concentrations under seasonal and hourly conditions were examined, as well as the seasonal distribution and diurnal variation of the atmospheric mixing layer height. Five correlation coefficient methodologies were applied to analyze the correlations between ground-level air pollutants and atmospheric mixing layer height under various seasonal and hourly conditions, confirming the dilution effect of the atmospheric mixing layer height. The results showed that PM_2.5, PM₁₀, and NO₂ generally had negative correlations with the atmospheric mixing layer height, while O₃ showed a strong positive correlation up to an altitude of 1,200~1,500 meters, and a negative correlation beyond that altitude. It was also shown that a single high concentration event (e.g., PM₁₀) can alter the overall correlation. The correlation can also vary depending on the characteristics of the correlation coefficient methodology, highlighting the importance of applying the appropriate methodology for each case during the analysis process.

• Journal of the Korean Society of Radiology
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• v.84 no.5
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• pp.1110-1122
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• 2023

Purpose This study aimed to assess the variability of transrectal shear wave elastography (SWE) using a designed phantom. Materials and Methods In a phantom, the SWE values were examined by two radiologists using agarose and emulsion silicone of different sizes (1, 2, and 3 cm) and shapes (round, cubic) at three depths (1, 2, and 3 cm), two region of interest (ROI) and locations (central, peripheral) using two ultrasound machines (A, B from different vendors). Variability was evaluated using the coefficient of variation (CV). Results The CVs decreased with increasing phantom size. Significant changes in SWE values included; agarose phantom at 3 cm depth (p < 0.001; machine A), 1 cm depth (p = 0.01; machine B), emulsion silicone at 2 cm depth (p = 0.047, p = 0.020; both machines). The CVs increased with increasing depth. Significant changes in SWE values included; 1 cm agarose (p = 0.037, p = 0.021; both machines) and 2 cm agarose phantom (p = 0.047; machine A). Significant differences in SWE values were observed between the shapes for emulsion silicone phantom (p = 0.032; machines A) and between ROI locations on machine B (p ≤ 0.001). The SWE values differed significantly between the two machines (p < 0.05). The intra-/inter-operator agreements were excellent (intraclass correlation coefficient > 0.9). Conclusion The phantom size, depth, and different machines affected the variability of transrectal SWE.

• Journal of the Korean Solar Energy Society
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• v.33 no.5
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• pp.1-8
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• 2013

Wind resource data of short-term period has to be corrected a long-term period by using MCP method that Is a statistical method to predict the long-term wind resource at target site data with a reference site data. Because the field measurement for wind assessment is limited to a short period by various constraints. In this study, 2 different MCP methods such as Linear regression and Matrix method were chosen to compare the predictive accuracy between the methods. Finally long-term wind speed, wind power density and capacity factor at the target site for 20 years were estimated for the variability of wind and wind energy. As a result, for 20 years annual average wind speed, Yellow sea off shore wind farm was estimated to have 4.29% for coefficient of variation, CV, and -9.57%~9.53% for range of variation, RV. It was predicted that the annual wind speed at Yellow sea offshore wind farm varied within ${\pm}10%$.

• Journal of the Korean GEO-environmental Society
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• v.7 no.2
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• pp.33-42
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• 2006

Eighteen biotite granites on Andong area and twenty seven igneous rocks(diorite, granite, andesite, rhyolite) on Yeosu area were tested to evaluate the correlations between the uniaxial compressive strength values, as determined by the standard uniaxial compression test, and the corresponding results of the ultrasonic velocity. The variability of test results for each test was evaluated by calculating the coefficient of determination or variation. Results indicate that strong correlations exist between the results of uniaxial compression vs the point load, Schmidt hammer and ultrasonic velocity test. The correlation equations for predicting compressive strength using different methods are presented along with their confidence limits. Ultrasonic velocity test used provide reliable estimates of compressive strength.

• The Plant Pathology Journal
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• v.29 no.3
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• pp.344-349
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• 2013

Intraspecific variation in morphometry of pine wood nematodes Bursaphelenchus xylophilus and B. mucronatus in relation to geographical locations in South Korea was investigated using morphometric characters (body length, a, b and c ratio, stylet length, and spicule length for a male nematode and V (%) value for a female nematode). B. xylophilus was isolated from Pinus thunbergii in Jinju (1998), Ulsan (2000), Yangsan (2000), Mokpo (2001) and Jeju (2004), and from P. densiflora in Gumi (2001). B. mucronatus was isolated from P. thunbergii in Jinju (1991) and from P. densiflora in Milyang (2001). The body length of male and female B. xylophilus had the highest coefficient of variability and showed significant differences among geographical locations. The V (%) value for female B. xylophilus showed the lowest coefficient of variability, changing little with geographical area and host plant. All morphometric characters in B. mucronatus except for stylet length and female body length showed no significant differences between locations or hosts, suggesting they may not be affected by geographical area or host plant.