• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.3
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• pp.165-175
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• 2006

To analyze the deformation and failure of slopes, generally, two types of model, Polynomial model and Growth model, are applied. These two models are focused on the behavior of the slope by time. Therefore, this research is more focused on predicting of slope failure than analyzing the slope behavior by time. Generally, Growth model is used to analyze the soil slope, to the contrary, Polynomial model is used for rock slope. However, 3-degree polynomial($y=ax^3+bx^2+cx+d$) is suggested to combine two models in this research. The main trait of this model is having an asymptote. The fields to adopt this model are Gosujae Danyang(soil slope) and Youngduk slope(rock slope), which are the cut-slope near national road. Data from Gosujae are shown the failure traits of soil slope, to the contrary, those of Youngduk slope are shown the traits of rock slope. From the real-time monitoring data of the slope, 3-degree polynomial is proved as excellent system to analyze the failure and behavior of slope. In case of Polynomial model, even if the order of polynomials is increased, the $R^2$ value and shape of the curve-fitted graph is almost the same.

• Korean Journal of Remote Sensing
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• v.30 no.2
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• pp.275-292
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• 2014

The objective of this study is to determine Tasseled Cap Transformation (TCT) coefficients for the Geostationary Ocean Color Imager (GOCI). TCT is traditional method of analyzing the characteristics of the land area from multi spectral sensor data. TCT coefficients for a new sensor must be estimated individually because of different sensor characteristics of each sensor. Although the primary objective of the GOCI is for ocean color study, one half of the scene covers land area with typical land observing channels in Visible-Near InfraRed (VNIR). The GOCI has a unique capability to acquire eight scenes per day. This advantage of high temporal resolution can be utilized for detecting daily variation of land surface. The GOCI TCT offers a great potential for application in near-real time analysis and interpretation of land cover characteristics. TCT generally represents information of "Brightness", "Greenness" and "Wetness". However, in the case of the GOCI is not able to provide "Wetness" due to lack of ShortWave InfraRed (SWIR) band. To maximize the utilization of high temporal resolution, "Wetness" should be provided. In order to obtain "Wetness", the linear regression method was used to align the GOCI Principal Component Analysis (PCA) space with the MODIS TCT space. The GOCI TCT coefficients obtained by this method have different values according to observation time due to the characteristics of geostationary earth orbit. To examine these differences, the correlation between the GOCI TCT and the MODIS TCT were compared. As a result, while the GOCI TCT coefficients of "Brightness" and "Greenness" were selected at 4h, the GOCI TCT coefficient of "Wetness" was selected at 2h. To assess the adequacy of the resulting GOCI TCT coefficients, the GOCI TCT data were compared to the MODIS TCT image and several land parameters. The land cover classification of the GOCI TCT image was expressed more precisely than the MODIS TCT image. The distribution of land cover classification of the GOCI TCT space showed meaningful results. Also, "Brightness", "Greenness", and "Wetness" of the GOCI TCT data showed a relatively high correlation with Albedo ($R^2$ = 0.75), Normalized Difference Vegetation Index (NDVI) ($R^2$ = 0.97), and Normalized Difference Moisture Index (NDMI) ($R^2$ = 0.77), respectively. These results indicate the suitability of the GOCI TCT coefficients.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.1
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• pp.1-12
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• 2021

To investigate the effect of freshwater discharge on the seawater circulation in the semi-closed harbor, a 3-D hydrodynamic model was applied to the International Ferry Terminal (IFT). The model run is conducted for 45 days (from May 15 to June 30, 2020), and the reproducibility of the model for time-spatial variability of current velocity and salinity was verified by comparison with model results and observation data. There are two sources of freshwater towards inside of the IFT: Han River and water reservoir located in the eastern part of IFT. In residual current velocity results, the two-layer circulation (the seaward flow near surface and the landward flow near bottom)derived from the horizontal salinity gradient in only considering the discharge from a Han River is more developed than that considering both the Han River and water reservoir. This suggests that the impact of freshwater from the reservoir is greater in the IFT areas than that from a Han River. Additionally, the two-layer circulation is stronger in the IFT located in southern part than Incheon South Port located in northern part. This process is formed by the interaction between tidal current propagating into the port and freshwater discharge from a water reservoir, and flow with a low salinity (near 0 psu) is delivered into the IFT. This low salinity distribution reinforces the horizontal stratification in front of the IFT, and maintains a two-layer circulation. Therefore, local sources of freshwater input are considered to estimate for mass transport process associated with the seawater circulation within the harbor and It is necessary to perform a numerical model according to the real-time freshwater flow rate discharged.

• Spatial Information Research
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• v.18 no.2
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• pp.57-65
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• 2010

Users often visit many stores while comparing the products for purchasing products or products related to it. Given a service providing location information of these stores, users can make their purchase efficiently because of reducing the time and effort they spent for wandering around and obtaining new purchase opportunities by knowing a kind of relevant stores near there. In this paper, for the purpose of providing relevant stores information efficiently, we suggest an Ambient Service Model that consists of three layers: "structured(purchase-related) information space", "real space", and "ambient information space". In the model, stores information collected from the web is grouped and structured automatically by relationships in terms of purchase. And users search relevant stores information by using an Ambient Query that is created by their context in real space. Finally, users obtain relevant stores information that is in the form of hierarchy structure on map interface. Then, users can search other kinds of relevant stores information additionally by using hierarchy structure. Consequently, It is possible to develope a service that users can obtain relevant stores information intuitively without complex search processes through the model. Also, we expect that the model can be used for developing services that provide objects information related to various objects besides stores.

• Journal of the Korean Geotechnical Society
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• v.25 no.5
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• pp.53-64
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• 2009

Many slope failures are induced by rainfall infiltration. A lot of recent researches are therefore focused on rainfall-induced slope instability and the rainfall infiltration is recognized as the important triggering factor. The rainfall infiltrates into the soil slope and makes the matric suction lost in the slope and even the positive pore water pressure develops near the surface of the slope. They decrease the resisting shear strength. In Korea, a few public institutions suggested conservative slope design guidelines that assume a fully saturated soil condition. However, this assumption is irrelevant and sometimes soil properties are misused in the slope design method to fulfill the requirement. In this study, a more relevant slope stability evaluation method is suggested to take into account the real rainfall infiltration phenomenon. Unsaturated soil properties such as shear strength, soil-water characteristic curve and permeability for Korean weathered soils were obtained by laboratory tests and also estimated by artificial neural network models. For real-time assessment of slope instability, failure warning criteria of slope based on deterministic and probabilistic analyses were introduced to complement uncertainties of field measurement data. The slope stability evaluation technique can be combined with field measurement data of important factors, such as matric suction and water content, to develop an early warning system for probably unstable slopes due to the rainfall.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.95-102
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• 2024

Due to technological advances, the cruising speed of high-speed trains is increasing, and aerodynamic noise generated from the flow outside the train has been an important consideration in the design stage. To accurately predict the flow-induced noise, high-resolution generation of sound sources in the near field and low-dissipation of sound propagation in the far field are required. This should be accompanied by a numerical grid and time resolution that can properly consider both temporal and spatial scales for each component of the real high-speed train. To overcome these challenges, this research simultaneously calculates the external flow and acoustic fields of five high-speed train cars of real-scale and at operational running speeds using a threedimensional unsteady Large Eddy Simulation technique. To verify the numerical analysis, the measurements of the wall pressure fluctuation and numerical results are compared. The Ffowcs Williams and Hawking equation is used to predict the acoustic power radiated from the high-speed train. This research is expected to contribute to noise reduction based on the analysis of the aerodynamic noise generation mechanism of high-speed trains.

• Journal of KIISE:Databases
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• v.33 no.6
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• pp.600-619
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• 2006

According to recent technical advances on sensors and mobile devices, processing of data streams generated by the devices is becoming an important research issue. The data stream of real values obtained at continuous time points is called streaming time-series. Due to the unique features of streaming time-series that are different from those of traditional time-series, similarity matching problem on the streaming time-series should be solved in a new way. In this paper, we propose an efficient algorithm for streaming time- series matching problem that supports normalization transform. While the existing algorithms compare streaming time-series without any transform, the algorithm proposed in the paper compares them after they are normalization-transformed. The normalization transform is useful for finding time-series that have similar fluctuation trends even though they consist of distant element values. The major contributions of this paper are as follows. (1) By using a theorem presented in the context of subsequence matching that supports normalization transform[4], we propose a simple algorithm for solving the problem. (2) For improving search performance, we extend the simple algorithm to use $k\;({\geq}\;1)$ indexes. (3) For a given k, for achieving optimal search performance of the extended algorithm, we present an approximation method for choosing k window sizes to construct k indexes. (4) Based on the notion of continuity[8] on streaming time-series, we further extend our algorithm so that it can simultaneously obtain the search results for $m\;({\geq}\;1)$ time points from present $t_0$ to a time point $(t_0+m-1)$ in the near future by retrieving the index only once. (5) Through a series of experiments, we compare search performances of the algorithms proposed in this paper, and show their performance trends according to k and m values. To the best of our knowledge, since there has been no algorithm that solves the same problem presented in this paper, we compare search performances of our algorithms with the sequential scan algorithm. The experiment result showed that our algorithms outperformed the sequential scan algorithm by up to 13.2 times. The performances of our algorithms should be more improved, as k is increased.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.17 no.4
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• pp.225-242
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• 2012

This is the first attempt to produce simultaneous surface current field from satellite altimeter data for the entire East Sea and to provide surface current information to users with formal description. It is possible to estimate surface geostrophic current field in near real-time because satellite altimeters and coastal tide gauges supply sea level data for the whole East Sea. Strength and location of the major currents and meso-scale eddies can be identified from the estimated surface geostrophic current field. The mean locations of major surface currents were explicated relative to topographic, ocean-surface and undersea features with schematic representation of surface circulation. In order to demonstrate the practical use of this surface current information, exemplary descriptions of annual, seasonal and monthly mean surface geostrophic current distributions were presented. In order to objectively classify surface circulation patterns in the East Sea, empirical orthogonal function (EOF) analysis was performed on the estimated 16-year (1993-2008) surface current data. The first mode was associated with intensification or weakening of the East Korea Warm Current (EKWC) flowing northward along the east coast of Korea and of the anti-cyclonic circulation southwest of Yamato Basin. The second mode was associated with meandering paths of the EKWC in the southern East Sea with wavelength of 300 km. The first and second modes had inter-annual variations. The East Sea surface circulation was classified as inertial boundary current pattern, Tsushima Warm Current pattern, meandering pattern, and Offshore Branch pattern by the time coefficient of the first two EOF modes.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.171-181
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• 2013

Recently, ground penetrating radar(GPR) has been widely used in detecting metallic and nonmetallic buried landmines and a number of related researches have been reported. A novel preprocessing method is proposed in this paper to flag potential locations of buried mine-like objects from GPR array measurements. GPR operates by measuring the reflection of an electromagnetic pulse from discontinuities in subsurface dielectric properties. As the GPR pulse propagates in the geologic medium, it suffers nonlinear attenuation as the result of absorption and dispersion, besides spherical divergence. In the proposed algorithm, a logarithmic transformed regression model which successfully represents the time-varying signal amplitude of the GPR data is estimated at first. Then, background signals may be densely distributed near the regression model and candidate signals of targets may be far away from the regression model in the time-amplitude space. Based on the observation, GPR signals are decomposed into candidate signals of targets and background signals using residuals computed from the estimated value by regression and the measurement of GPR. Candidate signals which may contain target signals and noise signals need to be refined. Finally, targets are detected through the refinement of candidate signals based on geometric signatures of mine-like objects. Our algorithm is evaluated using real GPR data obtained from indoor controlled environment and the experimental results demonstrate remarkable performance of our mine-like object detection method.