• Korean Journal of Applied Biomechanics
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• v.25 no.2
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• pp.191-198
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• 2015

Objective : The purpose of this study was to conduct biomechanical analysis of varying backpack loads on the lower limb movements during downhill walking over $-20^{\circ}$ ramp. Method : Thirteen male university students (age: $23.5{\pm}2.1yrs$, height: $175.7{\pm}4.6cm$, weight: $651.9{\pm}55.5N$) who have no musculoskeletal disorder were recruited as the subjects. Each subject walked over $20^{\circ}$ ramp with four different backpack weights (0%, 10%, 20% and 30% of body weight) in random order at a speed of $1.0{\pm}0.1m/s$. Five digital camcorders and two force plates were used to obtain 3-d data and kinetics of the lower extremity. For each trial being analyzed, five critical instants were identified from the video recordings. Ground reaction force, loading rate, decay rate, and resultant joint moment of the ankle and the knee were determined by the inverse dynamics analysis. For each dependent variable, one-way ANOVA with repeated measures was used to determine whether there were significant differences among four different backpack weight conditions (p<.05). When a significant difference was found, post hoc analyses were performed using the contrast procedure. Results : The results of this study showed that the medio-lateral GRFs at RHC in 20% and 30% body weight were significantly greater than the corresponding value in 0% of body weight. A consistent increase in the vertical GRFs as backpack loads increased was observed. The valgus joint movement of the knee at RTO in 30% body weight was significantly greater than the corresponding values in 0% and 10% body weight. The increased valgus moment of 30% body weight observed in this phase was associated with decelerating and stabilizing effects on the knee joint. The results also showed that the extension and valgus joint moments of the knee were systematically affected by the backpack load during downhill walking. Conclusion : Since downhill walking while carrying heavy external loads in a backpack may lead to excessive knee joint moment, damage can occur to the joint structures such as joint capsule and ligaments. Therefore, excessive repetitions of downhill walking should be avoided if the lower extremity is subjected to abnormally high levels of load over an extended period of time.

• Journal of the Earthquake Engineering Society of Korea
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• v.11 no.2 s.54
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• pp.81-94
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• 2007

In most experimental researches on the liquefaction phenomenon, an earthquake as a random vibration has been regraded as a sinusoidal wave or a triangular wave with an equivalent amplitude. Together with the development in the part of signal control and data acquisition, dynamic experimental equipments in the soil dynamics have also developed rapidly and further more, several real earthquakes have been simulated in the large model test such as shaking table tests and centrifuge tests. In Korea, several elementary laboratory tests to simulate the real earthquake load were performed. From these test results, it was reported that the sinusoidal wave cannot reliably reflect the soil dynamic behavior under the real earthquake motion. In this study, 4 types of dynamic motions such as the sinusoidal wave, the triangular wave, the incremental triangular wave and several real earthquake motions which were classified with shock-type and vibration-type were loaded to find something new to explain the change of the excess pore water pressure under the real earthquake load. Through the detailed investigation and comparison on all test results, it is found that the dynamic flow is generated by the soil plastic deformation and the velocity head of dynamic flow is changed the pressure head in the un-drained condition. It can be concluded that the change of the excess pore water pressure is related to the pressure head of dynamic flow. Lastly, a new hypothesis to explain such a liquefaction initiation phenomenon under the real earthquake load is also proposed and verified.

• Science of Emotion and Sensibility
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• v.8 no.2
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• pp.95-101
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• 2005

This study is based on previous information regarding reduced cardiac vagal activity in patients with coronary artery disease(CAD), on reduced variance(SDNN : standard deviation of all normal RR intervals), low-frequency power(LF), and the complexity of heart rate variability(HRV) in patients with chronic heart failure(CHF), and on the normalized high-frequency power of HRV is the highest in the right lateral decubitus position among 3 recumbent postures in patients with CAD, However, nothing is known about the nonlinear dynamics of HRV for the 3 recumbent postures in patients with CAD. To investigate the linear and non-linear characteristics of HRV in patients with CAD, 29 patients as CAD group and 23 patients as control group were studied. Electrocardiogram(ECG) with lead II channel was measured on these patients for 3 recumbent postures in random order. The HRV from ECG was analyzed with linear method(for time and frequency domains) and nonlinear method. The lower the high-frequency power in normalized unit(nHF) in the supine or left lateral decubitous position, the higher the increase in nHF when the position was changed from supine or left lateral decubitous to right lateral decubitous. Among the 3 recumbent postures in patients with severe CAD, the right lateral decubitus position was observed to induce the highest vagal modulation, the lowest sympathetic modulation, and the highest complexity of human physiology system.

• Journal of Korean Society of Forest Science
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• v.96 no.6
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• pp.730-736
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• 2007

The heterogeneity of forest environment plays an important role in the structure and dynamics of tree population, the composition of forest community, and the maintenance of species diversity. Based upon the research data of the nine hectare permanent plot in the typical mixed broadleaved-Korean pine forest, this study was conducted to analyze the characteristics of spatial pattern of Acer tegmentosum population for seedlings, saplings, and living and dead trees so as to evaluate the effect of micro-topography on spatial pattern of the species. The results noted that A. tegmentosum preferred to gentle slopes. There was no difference in density of seedlings by the variation of aspect, but the density of saplings, and living and dead trees was high on the western and southeastern slopes. Living trees of A. tegmentosum showed the clumped pattern for all scales within 150 m and highest at the scale of 30 m. Dead stems of the species indicated the clumped pattern within 111 m, highest at the scale of 72 m, and random pattern beyond the scale of 111 m (P < 0.01 ). The similarity of occurrence by developmental stages of A. tegmentosum showed that seedlings vs. saplings, saplings vs. living trees, and living trees vs. dead stems had highly positive correlation to each other, respectively (P < 0.01 ), indicating that the occurrence of previous developmental stages was positively correlated to following stages.

• Korea journal of population studies
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• v.20 no.2
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• pp.67-98
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• 1997

This study examines multi-level factors geographic proximities between elderly parents and their children in the United States and Japan. Despite their similar economies, the United States and Japan show a significant difference in their patterns of generational proximity. In 1993, half of US non-Hisapnic white parents aged 70 or over lived separately but within 10 miles of their nearest children and a majority of them lived far from their non-nearest children. The family geographic network for Japanese elderly parents is more hierarchial. In 1989, 74 percent of Japanese parents aged 70 and over lived with their nearest children but most of them lived far from their non-nearest children. To explain this distinctive pattern of inter- and intra-family differences in generational proximities in the two societies, this study employs a multi-level analysis which compares the relative importance of life course conditions of elderly parents and their children and economic and ecological characteristics of elderly parent's places of residence in influencing generational proximities.

• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.577-589
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• 2021

Soil seed bank community contributes to the long-term conservation of plant diversity and vegetation dynamics, and their decreasing diversity and density with soil depth provide critical perspectives (deterministic and stochastic) for understanding the community disassembly process. We analyzed changes in species composition and diversity and structuring patterns by soil layer (top and bottom), including surface vegetation, in Gwangneung Forest, a mature forest with a vegetation climate in the temperate central part of the Korean Peninsula. From two layers of soil collected with a vertical difference of 10 cm, 934 specimens of 27 families, 40 genera, 44 species, three varieties, and 47 taxa, germinated. Although species diversity and germination density decreased in most comparative characteristics, including growth type, there was no statistical significance due to large deviations. Within-group variability of species composition was similar in the upper and lower soils, as was the decline pattern in co-occurred species (ζ-diversity) and change in species retention probability. The structuring process of the community composition in the two soil layers was fitted with an exponential correlation rather than a power function, demonstrating the dominance of the stochastic process. The pattern in diversity and species turnover according to soil depth in Gwangneung Forest was discovered to be structured by stochastic random events, such as seed vertical movement rather than interaction with trait characteristics.

• Wind and Structures
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• v.34 no.1
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• pp.127-136
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• 2022

In this work a multi-fidelity non-intrusive polynomial chaos (MF-NIPC) has been applied to a structural wind engineering problem in architectural design for the first time. In architectural design it is important to design structures that are safe in a range of wind directions and speeds. For this reason, the computational models used to design buildings and bridges must account for the uncertainties associated with the interaction between the structure and wind. In order to use the numerical simulations for the design, the numerical models must be validated by experi-mental data, and uncertainties contained in the experiments should also be taken into account. Uncertainty Quantifi-cation has been increasingly used for CFD simulations to consider such uncertainties. Typically, CFD simulations are computationally expensive, motivating the increased interest in multi-fidelity methods due to their ability to lev-erage limited data sets of high-fidelity data with evaluations of more computationally inexpensive models. Previous-ly, the multi-fidelity framework has been applied to CFD simulations for the purposes of optimization, rather than for the statistical assessment of candidate design. In this paper MF-NIPC method is applied to flow around a rectan-gular 5:1 cylinder, which has been thoroughly investigated for architectural design. The purpose of UQ is validation of numerical simulation results with experimental data, therefore the radius of curvature of the rectangular cylinder corners and the angle of attack are considered to be random variables, which are known to contain uncertainties when wind tunnel tests are carried out. Computational Fluid Dynamics (CFD) simulations are solved by a solver that employs the Finite Element Method (FEM) for two turbulence modeling approaches of the incompressible Navier-Stokes equations: Unsteady Reynolds Averaged Navier Stokes (URANS) and the Large Eddy simulation (LES). The results of the uncertainty analysis with CFD are compared to experimental data in terms of time-averaged pressure coefficients and bulk parameters. In addition, the accuracy and efficiency of the multi-fidelity framework is demonstrated through a comparison with the results of the high-fidelity model.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1477-1482
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• 2023

This study examines marine heat wave (MHW) in the Northeast Asia region from 2012 to 2021, utilizing geostationary satellite Communication, Ocean, and Meteorological Satellite (COMS)/Meteorological Imager sensor (MI) and GEO-KOMPSAT-2A (GK-2A)/Advanced Meteorological Imager sensor (AMI) Sea Surface Temperature (SST) data. Our analysis has identified an increasing trend in the frequency and intensity of MHW events, especially post-2018, with the year 2020 marked by significantly prolonged and intense events. The statistical validation using Optimal Interpolation (OI) SST data and satellite SST data through T-test assessment confirmed a significant rise in sea surface temperatures, suggesting that these changes are a direct consequence of climate change, rather than random variations. The findings revealed in this study serve the necessity for ongoing monitoring and more granular analysis to inform long-term responses to climate change. As the region is characterized by complex topography and diverse climatic conditions, the insights provided by this research are critical for understanding the localized impacts of global climate dynamics.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.1
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• pp.29-41
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• 2019

Terrestrial Gross Primary Production (GPP) is the largest global carbon flux, and forest ecosystems are important because of the ability to store much more significant amounts of carbon than other terrestrial ecosystems. There have been several attempts to estimate GPP using mechanism-based models. However, mechanism-based models including biological, chemical, and physical processes are limited due to a lack of flexibility in predicting non-stationary ecological processes, which are caused by a local and global change. Instead mechanism-free methods are strongly recommended to estimate nonlinear dynamics that occur in nature like GPP. Therefore, we used the mechanism-free machine learning techniques to estimate the daily GPP. In this study, support vector machine (SVM), random forest (RF) and artificial neural network (ANN) were used and compared with the traditional multiple linear regression model (LM). MODIS products and meteorological parameters from eddy covariance data were employed to train the machine learning and LM models from 2006 to 2013. GPP prediction models were compared with daily GPP from eddy covariance measurement in a deciduous forest in South Korea in 2014 and 2015. Statistical analysis including correlation coefficient (R), root mean square error (RMSE) and mean squared error (MSE) were used to evaluate the performance of models. In general, the models from machine-learning algorithms (R = 0.85 - 0.93, MSE = 1.00 - 2.05, p < 0.001) showed better performance than linear regression model (R = 0.82 - 0.92, MSE = 1.24 - 2.45, p < 0.001). These results provide insight into high predictability and the possibility of expansion through the use of the mechanism-free machine-learning models and remote sensing for predicting non-stationary ecological processes such as seasonal GPP.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.427-435
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• 2023

Changes in flowering time due to weather fluctuations impact plant growth and ecosystem dynamics. Accurate prediction of flowering timing is crucial for effective forest ecosystem management. This study uses a process-based model to predict flowering timing in 2023 for five major tree species in Korean forests. Models are developed based on nine years (2009-2017) of flowering data for Abeliophyllum distichum, Robinia pseudoacacia, Rhododendron schlippenbachii, Rhododendron yedoense f. poukhanense, and Sorbus commixta, distributed across 28 regions in the country, including mountains. Weather data from the Automatic Mountain Meteorology Observation System (AMOS) and the Korea Meteorological Administration (KMA) are utilized as inputs for the models. The Single Triangle Degree Days (STDD) and Growing Degree Days (GDD) models, known for their superior performance, are employed to predict flowering dates. Daily temperature readings at a 1 km spatial resolution are obtained by merging AMOS and KMA data. To improve prediction accuracy nationwide, random forest machine learning is used to generate region-specific correction coefficients. Applying these coefficients results in minimal prediction errors, particularly for Abeliophyllum distichum, Robinia pseudoacacia, and Rhododendron schlippenbachii, with root mean square errors (RMSEs) of 1.2, 0.6, and 1.2 days, respectively. Model performance is evaluated using ten random sampling tests per species, selecting the model with the highest R². The models with applied correction coefficients achieve R² values ranging from 0.07 to 0.7, except for Sorbus commixta, and exhibit a final explanatory power of 0.75-0.9. This study provides valuable insights into seasonal changes in plant phenology, aiding in identifying honey harvesting seasons affected by abnormal weather conditions, such as those of Robinia pseudoacacia. Detailed information on flowering timing for various plant species and regions enhances understanding of the climate-plant phenology relationship.