• Journal of the Korean Geotechnical Society
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• v.23 no.9
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• pp.5-16
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• 2007

The simple linear elastic-perfectly plastic model with soil parameters $s_u,\;E_u$ and n of undrained condition is usually applied to predict the displacement of a constructed diaphragm wall(DW) on soft soils during excavation. However, the application of this soil model for finite element analysis could not interpret the continued increment of the lateral displacement of the DW for the large and deep excavation area both during the elapsed time without activity of excavation and after finishing excavation. To study the characteristic behaviors of soil behind the DW during the periods without excavation, a series of tests on soft Bangkok clay samples are simulated in the same manner as stress condition of soil elements happening behind diaphragm wall by triaxial tests. Three kinds of triaxial tests are carried out in this research: $K_0$ consolidated undrained compression($CK_0U_C$) and $K_0$ consolidated drained/undrained unloading compression with periodic decrement of horizontal pressure($CK_0DUC$ and $CK_0UUC$). The study shows that the shear strength of series $CK_0DUC$ tests is equal to the residual strength of $CK_0UC$ tests. The Young's modulus determined at each decrement step of the horizontal pressure of soil specimen on $CK_0DUC$ tests decreases with increase in the deviator stress. In addition, the slope of Critical State Line of both $CK_0UC$ and $CK_0DUC$ tests is equal. Moreover, the axial and radial strain rates of each decrement of horizontal pressure step of $CK_0DUC$ tests are established with the function of time, a slope of critical state line and a ratio of deviator and mean effective stress. This study shows that the results of the unloading compression triaxial tests can be used to predict the diaphragm wall deflection during excavation.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.329-352
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• 2022

It is reported that particulate matter(PM) penetrates the lungs and blood vessels and causes various heart diseases and respiratory diseases such as lung cancer. The subway is a means of transportation used by an average of 10 million people a day, and although it is important to create a clean and comfortable environment, the level of particulate matter pollution is shown to be high. It is because the subways run through an underground tunnel and the particulate matter trapped in the tunnel moves to the underground station due to the train wind. The Ministry of Environment and the Seoul Metropolitan Government are making various efforts to reduce PM concentration by establishing measures to improve air quality at underground stations. The smart air quality management system is a system that manages air quality in advance by collecting air quality data, analyzing and predicting the PM concentration. The prediction model of the PM concentration is an important component of this system. Various studies on time series data prediction are being conducted, but in relation to the PM prediction in subway stations, it is limited to statistical or recurrent neural network-based deep learning model researches. Therefore, in this study, we propose four transformer-based models including spatiotemporal transformers. As a result of performing PM concentration prediction experiments in the waiting rooms of subway stations in Seoul, it was confirmed that the performance of the transformer-based models was superior to that of the existing ARIMA, LSTM, and Seq2Seq models. Among the transformer-based models, the performance of the spatiotemporal transformers was the best. The smart air quality management system operated through data-based prediction becomes more effective and energy efficient as the accuracy of PM prediction improves. The results of this study are expected to contribute to the efficient operation of the smart air quality management system.

• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.331-337
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• 2016

Water vapor is main absorption factor of outgoing longwave radiation. So, it is essential to monitoring the changes in the amount of water vapor and to understanding the causes of such changes. In this study, we monitor temporal variability of Total Precipitable Water (TPW) which observed by satellite. Among climate variables, precipitation play an important part to analyze temporal variability of water vapor because it is produced by water vapor. And El $Ni{\tilde{n}}o$ is one of climate variables which appear regularly in comparison with the others. Through them, we analyze relationship between temporal variability of TPW and climate variable. In this study, we analyzed long-term change of TPW from Moderate-Resolution Imaging Spectroadiometer (MODIS) data and change of precipitation in middle area of Korea peninsula quantitatively. After these analysis, we compared relation of TPW and precipitation with El $Ni{\tilde{n}}o$. The aim of study is to research El $Ni{\tilde{n}}o$ has an impact on TPW and precipitation change in middle area of Korea peninsula. First of all, we calculated TPW and precipitation from time series analysis quantitatively, and anomaly analysis is performed to analyze their correlation. As a result, TPW and precipitation has correlation mostly but the part had inverse correlation was found. This was compared with El $Ni{\tilde{n}}o$ of anomaly results. As a result, TPW and precipitation had inverse correlation after El $Ni{\tilde{n}}o$ occurred. It was found that El $Ni{\tilde{n}}o$ have a decisive effect on change of TPW and precipitation.

• Journal of Korea Water Resources Association
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• v.45 no.8
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• pp.815-826
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• 2012

The underestimating trend using existing ordinary regression (OR) based trend analysis has been a well-known problem. The existing OR method based on least squares approximate the conditional mean of the response variable given certain values of the time t, and the usual assumption of the OR method is normality, that is the distribution of data are not dissimilar form a normal distribution. In this regard, this study proposed a quantile regression that aims at estimating either the conditional median or other quantiles of the response variable. This study assess trend in annual daily maximum rainfall series over 64 weather stations through both in OR and QR approach. The QR method indicates that 47 stations out of 67 weather stations are a strong upward trend at 5% significance level while OR method identifies a significant trend only at 13 stations. This is mainly because the OR method is estimating the condition mean of the response variable. Unlike the OR method, the QR method allows us flexibly to detect the trends since the OR is designed to estimate conditional quantiles of the response variable. The proposed QR method can be effectively applied to estimate hydrologic trend for either non-normal data or skewed data.

• Journal of Technology Innovation
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• v.23 no.3
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• pp.225-253
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• 2015

The standard is a nation's one of the most important industrial issues that improve the social and economic efficiency and also the basis of the industrial development and trade liberalization. This research analyzes the enactment and the utilization of Korean industrial standards(KS) of various industries. This paper examines Korean industries' KS utilization status based on the KS possession, enactments and inquiry records. First, we implement multidimensional scaling method to visualize and group the KS possession records and the nation's institutional issues. We develop several hypothesis to find the decision factors of how each group's KS possession status impacts on the standard enactment activities of similar industry sectors, and analyzes the data by implementing regression analysis. The results show that the capital intensity, R&D activities and sales revenues affect standardization activities. It suggests that the government should encourage companies with high capital intensity, sales revenues to lead the industry's standard activities, and link the policies with the industry's standard and patent related activities from R&D. Second, we analyze the impacts of each KS data's inquiry records, the year of enactments, the form and the industrial segment on the utilization status by implementing statistical analysis and decision tree method. The results show that the enactment year has significant impact on the KS utilization status and some KSs of specific form and industrial segment have high utilization records despite of short enactment history. Our study suggests that government should make policies to utilize the low-utilized KSs and also consider the utilization of standards during the enactment processes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.2
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• pp.123-131
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• 2011

Characteristics of sea surface temperature(SST) difference around Gwang-Yang steel Mill where can affect marine ecosystem in Gwang-Yang bay using 25 collected Landsat-7 ETM+ thermal infrared band data from 2000 to 2010. To analyze accuracy of SST from the Landsat-7 ETM+ thermal infrared image， satellite-induced SST was verfied by compared Yeo-Su tide station and Landsat thermal image. As a result, SST from Landsat-7 ETM+ is $1.22^{\circ}C$ lower than sea temperature from Yeo-Su tide station and correlation coefficient resulted in above 0.991 which means that correlation coefficient between Landsat image temperature and field sea temperature is relatively high. Five regions were selected to analyze sea surface temperature between near Gwang-Yang steel mill and the open sea and analyzed timeseries of sea surface temperature seasonally and regionally. Moreover, the additional analysis has been carried out by comparing the averaged temperatures of Gwang-Yang and Soon-Cheon bays using the dataset over a year.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.8
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• pp.370-377
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• 2018

Currently, Korea is ahead of the forest sector such as forest management, forest investigation and forest management, which is not insufficient compared with the forest advanced countries (Germany, Japan, Austria). However, there is a lack of systematic and advanced forest management plan and related research, and it is not enough to construct GIS for practical and complex analysis. Therefore, in order to perform forest analysis effectively, this study maps forest basic statistics (2010, 2015) based on GIS to map forest information. As a result, the forest area, growing stock, average growing stock, and forest rate could be produced with the maximized visual effect by detailed administrative districts, and systematic analysis of the time series changes was also possible. Forest area increased only in Goseong, Sejong, Cheolwon, Yeoncheon, Daejeon, and Seoul Guro-gu, and decreased in all other areas, while growing stock increased in most areas, Uljin, Ulleung, Seoul Nowon-gu, and Seoul Gangdong-gu. The average growing stock was found to increase in most areas excluding the four administrative districts and the forest rate was higher in 10 regions (Goseong, Yeoncheon, Gongju, Busan Dong-gu, Daegu Seo-gu, etc.) but it decreased in most regions excluding 10 regions. Based on this research, we plan to produce and analyze forest information maps for smaller administrative districts and more.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.607-615
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• 2020

The purpose of this study was to analyze the research status and trends related to the industrial mathematics based on text mining techniques with a sample of 4910 papers collected in the SIAM Journal on Applied Mathematics from 1970 to 2019. The R program was used to collect titles, abstracts, and key words from the papers and to analyze topic modeling techniques based on LDA algorithm. As a result of the coherence score on the collected papers, 20 topics were determined optimally using the Gibbs sampling methods. The main results were as follows. First, studies on industrial mathematics were conducted in a variety of mathematics fields, including computational mathematics, geometry, mathematical modeling, topology, discrete mathematics, probability and statistics, with a focus on analysis and algebra. Second, 5 hot topics (mathematical biology, nonlinear partial differential equation, discrete mathematics, statistics, topology) and 1 cold topic (probability theory) were found based on time series regression analysis. Third, among the fields that were not reflected in the 2015 revised mathematics curriculum, numeral system, matrix, vector in space, and complex numbers were extracted as the contents to be covered in the high school mathematical curriculum. Finally, this study suggested strategies to activate industrial mathematics in Korea, described the study limitations, and proposed directions for future research.

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.416-427
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• 2018

As the loan size of real estate PF is huge, its market ripple effect gets bigger when overdue occurs. Accordingly, the management of the delinquency rate and macroeconomic analysis are required. As the preceding research mainly proceeded with microeconomic analysis through the real estate PF data of individual banks to evaluate importance of list or analyzed core factors for delinquency, it lacked research on comprehensive real estate PF size. In order to overcome the limitations of such data, this research studied real estate PF delinquency rate of the entire market and effect relationship by the size. The research utilized the size of real estate PF loans, money supply, interest rate, consumer price index(CPI), and GDP data. Also, it applied the first model of VECM as linear relationship between at least two or more variables, following the result of co-integration test. As a result of Granger-causality test, the real estate PF loans delinquency rate is influenced by their loan size, and as a result of impulse response analysis, the interest rate is shown to be affecting delinquency rate the most. Interest rate could risesomeday and aggravate the delinquency rate of real estate PF. Also, risk exposure could be serious as the loan size increases.Therefore, the management of real estate PF delinquency rate requires continuous monitoring, tracking and observing issued loans from a macro point of view. The plans to prevent delinquency will be necessary.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.3
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• pp.13-21
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• 2004

The dissemination of commercial satellite images. which have the high spatial resolution such as aerial photos, are the active trend in remote sensing community because of the recent development in satellite and sensor technology. Such high resolution satellite images provide a unique tool for the monitoring of ongoing urban land use change. Especially KOMPSAT-1, which was launched at December 1999 and successfully operated up to now, provides repeatedly panchromatic images over Korean peninsula, which has the spatial resolution of 6.6m. Based upon this KOMPSAT-1 EOC image data we can try to analyze and assess the temporal urban land use change, which could not be done because lack of such data. The aim of this paper is to analyze and assess the spatial land use characteristics of Daejeon Metropolitan City based on KOMPSAT-1 EOC data. The land use map of year 2001 is generated through the modification of the year 2000 land use map, which is published by National Geographic Information Institute, using visual interpretation of KOMPSAT-1 EOC image which is acquired in year 2001. This study can be the start point of the time series analysis of the long term land use change monitoring mit KOMPSAT-1 EOC data.