• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.179-188
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• 2022

The purpose of this study is to analyze the variables affecting the institutional commitment of college students. Based on the relevant literature review, this study subdivided institutional commitment of college students into three; academic integration, social integration and institutional commitment. To achieve the goals, the hierarchical regression analysis was conducted using KELS(Korea Educational Longitudinal Survey) data collected by KEDI in 2018. Major findings are as follows: factors related to college experiences such as learning styles, negligence of learning, college climate, interaction with faculty members or peer group were found to be associated with the institutional commitment of college students. With regard to students' background, male students revealed lower level of academic integration and institutional commitment. The regression model disclosed that students from medicine demonstrated higher social integration compared to other majors. Based on the findings of the study, policy implications were discussed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.877-884
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• 2006

GPS is an essential tool for applications that be required high positioning precision, for the velocity field estimation of tectonic plates. The three years data of eight GPS permanent station were analyzed to estimate crustal deformation velocities using Gipsy-oasis II software. The velocity vectors of GPS stations are estimated by linear regression method in daily solution time series. The velocities have a standard deviation of less than 0.1mm/yr and the magnitude of velocities given by the Korean GPS permanent stations were very small, ranging from 25.1 to 31.1 mm/yr. The comparison between the final solution and other sources, such as IGS velocity result calculated from SOPAC was accomplished and the results generally show good agreement for magnitude and direction in crustal motion. To evaluate the accuracy of our results, the velocities obtained from six plate motion model was compared with the final solution based on GPS observation.

• Economic and Environmental Geology
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• v.44 no.2
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• pp.171-180
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• 2011

For 21 rock samples consisting of granite, sandstone and the effective thermal conductivity (TC) was measured with the LFA-447 Nanoflash, and mineralogical compositions were also determined from XRD analysis. The structural models were used to examine the effects of quartz content and the size of minerals on TC of rocks. The experimental results showed that TC of rocks was strongly related to quartz content with $R^2$ value of 0.75. Therefore, the proposed regression model can be a useful tool for an approximate estimation of TC only from quartz content. Some samples with similar values of quartz content, however, illustrated great differences in TC, presumably caused by differences in the size of minerals. An analysis from structural models showed that TC of rocks with fine-grained minerals was likely to fall in the region between Series and EMT model, and it moved up to ME and Parallel model as the size of minerals increased. This progressive change of structural models implies that change of TC depending on the size of minerals is possibly related to the scale of experiments; TC was measured from a disk sample with a thickness of 3 mm. Therefore, in case of measurements with a thin sample, TC can be overestimated as compared to the real value in the field scale. The experimental data illustrated that the scale effect was more pronounced for rocks with bigger size of minerals. Thus, it is worthwhile to remember that using a measured TC as a representative value for the real field can be misleading when applied to many geothermal problems.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.5
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• pp.28-41
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• 2020

This study selects two linear parks representing each culture and reveals the differences between them using a visitor survey as small data and social media analytics as big data based on the three components of the model of landscape perception. The 606 in Chicago, U.S., and the Gyeongchun Line in Seoul, Korea, are representative parks built on railroads. A total of 505 surveys were collected from these parks. The responses were analyzed using descriptive statistics, principal component analysis, and linear regression. Also, more than 20,000 tweets which mentioned two linear parks respectively were collected. By using those tweets, the authors conducted the clustering analysis and draw the bigram network diagram for identifying and comparing the placeness of each park. The result suggests that more diverse design concept links to less diversity in behavior; that half of the park users use the park as a shortcut; and that same physical exercise provides different benefits depending on the park. Social media analysis showed the 606 is more closely related to the neighborhoods rather than the Gyeongchun Line Forest. The Gyeongchun Line Forest was a more event-related place than the 606.

• Journal of Korea Water Resources Association
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• v.45 no.12
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• pp.1321-1330
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• 2012

In this study, the daily inflow at the basin of Chungju dam is predicted using wavelet-artificial neural network for nonlinear model. Time series generally consists of a linear combination of trend, periodicity and stochastic component. However, when framing time series model through these data, trend and periodicity component have to be removed. Wavelet transform which is denoising technique is applied to remove nonlinear dynamic noise such as trend and periodicity included in hydrometeorological data and simple noise that arises in the measurement process. The wavelet-artificial neural network (WANN) using data applied wavelet transform as input variable and the artificial neural network (ANN) using only raw data are compared. As a results, coefficient of determination and the slope through linear regression show that WANN is higher than ANN by 0.031 and 0.0115 respectively. And RMSE and RRMSE of WANN are smaller than those of ANN by 37.388 and 0.099 respectively. Therefore, WANN model applied in this study shows more accurate results than ANN and application of denoising technique through wavelet transforms is expected that more accurate predictions than the use of raw data with noise.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.7
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• pp.601-608
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• 2015

The static aeroelastic analysis and optimization of flexible wings are conducted for steady state conditions while both aerodynamic and structural parameters can be used as optimization variables. The system of multidisciplinary design optimization as a robust methodology to couple commercial codes for a static aeroelastic optimization purpose to yield a convenient adaptation to engineering applications is developed. Aspect ratio, taper ratio, sweepback angle are chosen as optimization variables and the skin thickness of the wing. The real-coded adaptive range multi-objective genetic algorithm code, which represents the global multi-objective optimization algorithm, was used to control the optimization process. The support vector regression(SVR) is applied for optimization, in order to reduce the time of computation. For this multi-objective design optimization problem, numerical results show that several useful Pareto optimal designs exist for the flexible wing.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.203-209
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• 2006

SAR (Synthetic Aperture Radar) technology, which is not influenced by cloud cover because of using electromagnetic wave of long wavelength, has an advantage in mapping the earth. NASA, recognizing these strong points of SAR, launched SRTM (Shuttle Radar Topography Mission), and acquired the topographic information of the earth. SRTM and NED (National Elevation Data) of USGS were used for the research and vegetation height map was produced through differentiating the two data. Correlation between SRTM-NED and planting year was analyzed to see the relationship. Strong correlation was detected and it shows the feasibility of estimating timber age and eventually creating timber age map from SRTM-NED. Additional analyses were conducted to check if the linearity is influenced by regional characteristics and forest uniformity. As results, the correlation between SRTM-NED and timber age is influenced by roughness of the terrain. Overall, this paper shows that timber age estimation using SRTM and NED can be sufficiently practical.

• Smart Media Journal
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• v.7 no.1
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• pp.16-23
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• 2018

In this paper, we used the Deep Neural Network (DNN) to predict the number of daily spectators of Gwangju - KIA Champions Field in order to provide marketing data for the team and related businesses and for managing the inventories of the facilities in the stadium. In this study, the DNN model, which is based on an artificial neural network (ANN), was used, and four kinds of DNN model were designed along with dropout and batch normalization model to prevent overfitting. Each of four models consists of 10 DNNs, and we added extra models with ensemble model. Each model was evaluated by Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). The learning data from the model randomly selected 80% of the collected data from 2008 to 2017, and the other 20% were used as test data. With the result of 100 data selection, model configuration, and learning and prediction, we concluded that the predictive power of the DNN model with ensemble model is the best, and RMSE and MAPE are 15.17% and 14.34% higher, correspondingly, than the prediction value of the multiple linear regression model.

• International Journal of Highway Engineering
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• v.10 no.4
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• pp.151-159
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• 2008

Performances of retroreflectivity vary place to place, according to traffic volumes and time lengths after striping, depending on pavement marking materials and colors. The present paper uses the nation wide data of retroreflectivity, which has been collected from freeways and then tries to develop the regression curve setting traffic volume and service life as independent variables and retroreflectivities as dependent variables. The DB system includes two year's measurement in $2005{\sim}2006$ over Korean freeway pavement marking at an interval of three months for the period. The mobile measurement system, a laserlux, was employed for the purpose. The DB has provided a lot of information about materials and performance of the specific pavement marking such as geometric features, traffic volumes, material characteristics and the installation date. This study provides the comparison of pavement marking performances under diversified conditions. Based on accumulated pavement marking performances, this study provides performance curves based on the diversified factors. The goal of the retroreflectivity modeling is to develop equations that can be used to estimate an average retroreflectivity of pavement markings as a function time since application and traffic volume. After representing the variation of retroreflectivities and estimating regression curves by linear, exponential, logarithmic and power function, the regression curve which had the highest coefficient of determination and the value similar to the last field measurement was regarded as the retroreflectivity decay model. As a result of verification, the decay model showed the signification within the 90% confidence level and especially showed the clear relation with field data according to increase of cumulative vehicle exposure. Accordingly, these models can be used to determine service lives, retroreflectivity degradation rates, and retroreflectivity of new markings.

• Journal of Korean Society of Steel Construction
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• v.25 no.1
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• pp.15-24
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• 2013

This paper presents the results from a systematic finite element study on the bending moment resisting capacity of double web-angle connection for a CFT(concrete filled tube) composite frame subjected to cyclic loading. The three-dimensional nonlinear finite element models are constructed to investigate the rotational stiffness, bending moment capacity, and failure modes of the partially restrained composite CFT connections. A wide scope of additional structural behaviors explain the different influences of the double web-angle connections parameters, such as the different thickness of connection angles and the gage distances of high strength steel connection bar. The moment-rotation angle relationships obtained statically from the finite element analysis are compared with those from Richard's theoretical equation.