• Journal of Korea Water Resources Association
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• v.46 no.12
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• pp.1249-1263
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• 2013

In order to minimize the damages caused by long-term drought, appropriate drought management plans of the basin should be established with the drought forecasting technology. Further, in order to build reasonable adaptive measurement for future drought, the duration and severity of drought must be predicted quantitatively in advance. Thus, this study, attempts to forecast drought in Korea by using an Artificial Neural Network Model, and drought index, which are the representative statistical approach most frequently used for hydrological time series forecasting. SPI (Standardized Precipitation Index) for major weather stations in Korea, estimated using observed historical precipitation, was used as input variables to the MLP (Multi Layer Perceptron) Neural Network model. Data set from 1976 to 2000 was selected as the training period for the parameter calibration and data from 2001 to 2010 was set as the validation period for the drought forecast. The optimal model for drought forecast determined by training process was applied to drought forecast using SPI (3), SPI (6) and SPI (12) over different forecasting lead time (1 to 6 months). Drought forecast with SPI (3) shows good result only in case of 1 month forecast lead time, SPI (6) shows good accordance with observed data for 1-3 months forecast lead time and SPI (12) shows relatively good results in case of up to 1~5 months forecast lead time. The analysis of this study shows that SPI (3) can be used for only 1-month short-term drought forecast. SPI (6) and SPI (12) have advantage over long-term drought forecast for 3~5 months lead time.

• Geophysics and Geophysical Exploration
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• v.2 no.4
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• pp.180-183
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• 1999

A proto-type seismic measurement system with a reference was developed to improve S/N (signal-to-noise ratio) of seismic data, especially in noisy urban areas. Two pairs of correlation measurements (the one for microphone and geophone, and another for electromagnetic (EM) loop and geophone) were carried out near Kimpo Airport and at Kimje. The spectrum analyses were also performed to investigate the correlation of two pairs of time series; one for microphone and geophone, and another for EM loop and geophone. The sound waves measured with the microphone and the geophone are highly correlated. However, differences in the reponses are readily identifiable across 200 Hz; in the vicinity of 100 Hz, the spectral energy for geophone is 20 dB higher than that for microphone, and at near 500 Hz, the spectral energy for microphone is 30 dB higher than that for geophone. Overall, the spectral energy appears concentrated on the frequency window below 600 Hz for geophone. It contrasts with the observation of dominant frequency at the range of above 200 Hz for microphone. The wave forms of EM noise (due to an ACDC inverter) measured with EM loop and geophone are consistently and highly correlated each other. The power spectrum of the EM noise for EM loop shows that the spectral energies at odd harmonic frequencies of 60 Hz are higher than those at even harmonic frequencies of 60 Hz. It is compared to the power spectrum for geophone; the spectral energies at odd harmonics are nearly same as those at even harmonic frequencies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.4
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• pp.153-163
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• 2017

This research is based on the previous research that personally preferred safe distance, rotating angle and speed are differentiated. Thus, we use machine learning model for recognizing maneuvering modes trained per personal or per similar driving pattern groups, and we evaluate automatic driving according to maneuvering modes. By utilizing driving knowledge, we subdivided 8 kinds of longitudinal modes and 4 kinds of lateral modes, and by combining the longitudinal and lateral modes, we build 21 kinds of maneuvering modes. we train the labeled data set per time stamp through RNN, LSTM and Bi-LSTM models by the trips of drivers, which are supervised deep learning models, and evaluate the maneuvering modes of automatic driving for the test data set. The evaluation dataset is aggregated of living trips of 3,000 populations by VTTI in USA for 3 years and we use 1500 trips of 22 people and training, validation and test dataset ratio is 80%, 10% and 10%, respectively. For recognizing longitudinal 8 kinds of maneuvering modes, RNN achieves better accuracy compared to LSTM, Bi-LSTM. However, Bi-LSTM improves the accuracy in recognizing 21 kinds of longitudinal and lateral maneuvering modes in comparison with RNN and LSTM as 1.54% and 0.47%, respectively.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.831-841
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• 2017

The irrational number ${\pi}$ is defined as the ratio of circumference of a circle to its radius and always becomes constant. This article does Monte Carlo approximation of its value using the famous Buffon's needle experiment and shows that its convergence is not always proportional to the sample size. We also do Monte Carlo simulations to see the convergence of the computed ${\pi}$ values from the random walk series with independent normal increment. Finally we apply the theoretical derivation to various financial time series data such as KOSPI, stock prices of Korean big firms, global stock indices and major foreign exchange rates. The historical data shows that log transformed data random walk process but most of their first lagged data don't follow a normal distribution. More importantly the computed value from the ratio of the regression coefficient ${\pi}$ tend to converge a constant, unfortunately not ${\pi}$. Using this result we could doubt on the efficient market hypothesis, and relate the degree of the hypothesis with the amount of deviation of the estimated ${\pi}$ values.

• Journal of the Korean Society for Marine Environment & Energy
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• v.10 no.4
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• pp.187-192
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• 2007

Impact on cylindrical surface caused by plunging breaking waves is investigated experimentally. The breaking waves are generated in a wave flume by decreasing the wave maker frequencies linearly and focusing the generated wave components at one specific location. The breaking wave packets are based on constant wave steepness spectrum. Three inclination angles of cylinder are applied to examine the effect of contact angle between cylinder and front surface of breaking waves. Also, the effect of cylinder diameter on pressure distribution and its peak value is investigated by adopting three cylinders with different diameters. The longitudinal location of cylinder is slightly moved in eight different points to find out a probable maximum value of impact pressure. The pressures and total force on cylinder surface are measured by piezo-electric pressure sensors and 3-components load cell with 30kHz sampling rate. The variation of peak impact pressures and forces is analyzed in terms of cylinder diameter, inclination angle and location. Also, the pressure distribution on cylindrical surface is examined. The cylinder location and surface position are more important parameters that govern the magnitude and shape of peak pressures, while the cylinder diameter and inclined angle are relatively insignificant. In a certain conditions, the impact phenomenon becomes very unstable which results in a large variation of measured valves in repeated runs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3344-3352
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• 2015

The purpose of this study is to investigate the effects of Korean computer-based cognitive rehabilitation program (CoTras) on frontal-executive functions in patients with traumatic brain injury (TBI). This study was performed at C hospital in Changwon, Gyeongsangnam-do, Korea from August 2013 to March 2014. Ten patients with TBI were randomly divided into two groups. The experimental group had been given CoTras once a day, five times a week for four weeks, whereas the control group had performed self-cognitive training under the same conditions. To verify the effect of intervention, the following executive function measures were used: Korean Montreal Cognitive Assessment (K-MoCA), Executive Clock Drawing Test (ECDT), Trail Making Test (TMT), Rey-Complex Figure Test (RCFT). Intervention group showed significant increase in K-MoCA, TMT, RCFT-delayed recall (p<.05). However, control group showed no significant change in any test. There was significant difference of changed scores (post test-pre test) between two groups in K-MoCA, TMT and RCFT-delayed recall (p<.05). This study showed that CoTras is effective to improve frontal-executive functions in patients with traumatic brain injury.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.5
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• pp.278-293
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• 2019

The joint distribution of wave height and period has been maltreated despite of its great engineering value due to the absence of any analytical model for wave period, and as a result, no consensus has been reached about the effect of nonlinearity on these joint distribution. On the other hand, there was a great deal of efforts to study the effects of non-linearity on the wave height distribution over the last decades, and big strides has been made. However, these achievements has not been extended to the joint distribution of wave height and period. In this rationale, we first express the joint distribution of wave height and period as the product of the marginal distribution of wave heights with the conditional distribution of associated periods, and proceed to derive the joint distribution of wave heights and periods utilizing the models of Longuet-Higgins (1975, 1983), and Cavanie et al. (1976) for conditional distribution of wave periods, and height distribution derived in this study. The verification was carried out using numerically simulated data based on the Wallops spectrum, and the nonlinear wave data obtained via the numerical simulation of random waves approaching toward the uniform beach of 1:15 slope. It turns out that the joint distribution based on the height distribution for finite banded nonlinear waves, and Cavanie et al.'s model (1976) is most promising.

• Journal of Korea Water Resources Association
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• v.54 no.6
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• pp.365-379
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• 2021

Hydrological model parameters are essential for model simulation and can vary over time due to topography, climatic conditions, climate change and human activity. Consequently, the use of fixed parameters can lead to inaccurate stream flow simulations. The aim of this study is to investigate an appropriate method of estimating time-varying parameters using stream flow observations, and how the simulation efficiency changes when stream flow data are assimilated into the model. The data assimilation method can be used to automatically estimate the parameters of a hydrological model by adapting to a variety of changing environments. Stream flow observations were assimilated into a two parameter monthly water balance model using a particle filter. The simulation results using the time-varying parameters by the data assimilation method were compared with the simulation results using the fixed parameters by the SCEM method. First, we conducted synthesis experiments based on various scenarios to investigate if the particle filter method can adequately track parameters that change over time. After that, it was applied to actual watersheds and compared with the predictive performance of stream flow when using parameters that change with time and fixed parameters. The conclusions obtained through this study are as follows: (1) The predictive performance of the overall monthly stream flow time series was similar between the particle filter method and the SCEM method. (2) The monthly runoff prediction performance in the period except the rainy season was better in the simulation by the periodically changing parameters using the data assimilation method. (3) Uncertainty in the observational data of stream flow used for assimilation played an important role in the predictive performance of the particle filter.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1407-1419
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• 2020

Long time-series gridded data is crucial for the analyses of Earth environmental changes. Climate reanalysis and satellite images are now used as global-scale periodical and quantitative information for the atmosphere and land surface. This paper examines the feasibility of DCT-PLS (penalized least square regression based on discrete cosine transform) for the spatial gap filling of gridded data through the experiments for multiple variables. Because gap-free data is required for an objective comparison of original with gap-filled data, we used LDAPS (Local Data Assimilation and Prediction System) daily data and MODIS (Moderate Resolution Imaging Spectroradiometer) monthly products. In the experiments for relative humidity, wind speed, LST (land surface temperature), and NDVI (normalized difference vegetation index), we made sure that randomly generated gaps were retrieved very similar to the original data. The correlation coefficients were over 0.95 for the four variables. Because the DCT-PLS method does not require ancillary data and can refer to both spatial and temporal information with a fast computation, it can be applied to operative systems for satellite data processing.

• Journal of Navigation and Port Research
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• v.48 no.3
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• pp.181-191
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• 2024

Ports play a crucial role in the complex global supply chain. While many researchers have used social network analysis (SNA) to study active networks, there is a lack of SNA cohesion analysis specifically related to logistics and trade. Therefore, this study aims to identify time-series structural changes in all domestic import and export logistics networks, including regions, ports, and airports, by utilizing techniques such as k-core and community analysis. To carry out this analysis, we rely on data from the Korea Customs Service's Import and Export Logistics Statistical Yearbook spanning from 2004 to 2022. The findings from the k-core and community analysis indicate that the cohesion of the domestic import and export logistics network has continuously strengthened over time. Moreover, it reveals that regions, ports, and airports are becoming more cohesive and homogeneous, with Busan Port emerging as the central hub of a large community. These insights are expected to enhance our understanding of global logistics dynamics and contribute to the development of policies and sustainable import and export logistics processes.