• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1700-1709
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• 2019

Recently, many researches have been under way to develop systems (services) to support the safety navigation of ships, and in these studies, common difficulties have been encountered in assessing the usefulness and effectiveness of the developed system. To solve these problems, we propose the DEVS-based ship navigation modeling and simulation technique. Following the preceding study, we analyze the COLREG rules and reflected to officer and helmsman agent models for decision making. Also we propose estimation and interpolation techniques to adopt the motion characteristics of the actual vessel to simulation. In addition, we implement the navigation simulation system to reflect the designed proposed methods, and we present five-scenarios to verify the developed simulation system. And we conduct simulations according to each scenario and the results were reconstructed. The simulation results confirm that the components modelled in each scenario enable to operate according to the navigation relationships.

• Korean Journal of Materials Research
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• v.32 no.8
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• pp.345-353
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• 2022

In this study, using deep learning, super-resolution images of transmission electron microscope (TEM) images were generated for nanomaterial analysis. 1169 paired images with 256 × 256 pixels (high resolution: HR) from TEM measurements and 32 × 32 pixels (low resolution: LR) produced using the python module openCV were trained with deep learning models. The TEM images were related to DyVO₄ nanomaterials synthesized by hydrothermal methods. Mean-absolute-error (MAE), peak-signal-to-noise-ratio (PSNR), and structural similarity (SSIM) were used as metrics to evaluate the performance of the models. First, a super-resolution image (SR) was obtained using the traditional interpolation method used in computer vision. In the SR image at low magnification, the shape of the nanomaterial improved. However, the SR images at medium and high magnification failed to show the characteristics of the lattice of the nanomaterials. Second, to obtain a SR image, the deep learning model includes a residual network which reduces the loss of spatial information in the convolutional process of obtaining a feature map. In the process of optimizing the deep learning model, it was confirmed that the performance of the model improved as the number of data increased. In addition, by optimizing the deep learning model using the loss function, including MAE and SSIM at the same time, improved results of the nanomaterial lattice in SR images were achieved at medium and high magnifications. The final proposed deep learning model used four residual blocks to obtain the characteristic map of the low-resolution image, and the super-resolution image was completed using Upsampling2D and the residual block three times.

• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.269-274
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• 2024

High-quality precipitation data are crucial for various industries, including disaster prevention. In South Korea, long-term high-quality data are collected through numerous ground observation stations. However, data between these stations are reprocessed into a grid format using interpolation methods, which may not perfectly match actual precipitation. A prime example of real-time observational grid data globally is the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG) from National Aeronautics and Space Administration (NASA), while in South Korea, ground radar data are more commonly used. GPM and ground radar data exhibit distinct differences due to their respective processing methods. This study aims to analyze the characteristics of GPM and Constant Altitude Plan Position Indicator(CAPPI),representative real-time grid data, by comparing them with ground-observed precipitation data. The study period spans from 2021 to 2022, focusing on hourly data from Automated Synoptic Observing System (ASOS) sites in South Korea. The GPM data tend to underestimate precipitation compared to ASOS data, while CAPPI shows errors in estimating low precipitation amounts. Through this comparative analysis, the study anticipates identifying key considerations for utilizing these data in various applied fields, such as recalculating design rainfall, thereby aiding researchers in improving prediction accuracy by using appropriate data.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.13-19
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• 2016

This study presented the build-up of three-dimensional soil pollution map for precise analysis. To do this, survey on the existing pollutant region on Dongnae-gu, Busan that is the study subject, showed that it tended to produce 0.72 clusters. So, this study suggested to investigate center of $1km{\times}1km $ grid and, as the results of comparing the pollution map that input pollution figure values based on the actually investigation point showed precise results. And, it divided the standard of pollution into 5 levels in surface and underground space and the map was built up using IDW interpolation against the amount of polluted substance. The pollution of ground surface, flow of polluted substance, coefficient of permeability and ground water level that are 504 geotechnical informations were selected as the influential parameters in pollution analysis of underground space, and it calculated that to 0~20 points by dividing the characteristics. It enables the build-up of pollution map of ground surface-underground with depth that considers the characteristics of soil layers and it is considered that it is possible to analyze the general infiltration. And, it was considered that it enables more accurate forecast about influential analysis per depth and pollution of underground water.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.11
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• pp.771-780
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• 2001

It is indispensable to use the process and device simulation tool in order to analyze accurately the electrical characteristics of ULSI CMOS devices, in addition to developing and manufacturing those devices. The 3D Monte Carlo (MC) simulation result is not efficient for large-area application because of the lack of simulation particles. In this paper is reported a new efficient simulation strategy for 3D MC ion implantation into large-area application using the 3D MC code of TRICSI(TRansport Ions into Crystal Silicon). The strategy is related to our newly proposed split-trajectory method and ion-splitting method(ion-shadowing approach) for 3D large-area application in order to increase the simulation ions, not to sacrifice the simulation accuracy for defects and implanted ions. In addition to our proposed methods, we have developed the cell based 3D interpolation algorithm to feed the 3D MC simulation result into the device simulator and not to diverge the solution of continuous diffusion equations for diffusion and RTA(rapid thermal annealing) after ion implantation. We found that our proposed simulation strategy is very computationally efficient. The increased number of simulation ions is about more than 10 times and the increase of simulation time is not twice compared to the split-trajectory method only.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.29 no.5
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• pp.239-246
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• 2017

In case of observing only wave height and period in the field, various wave characteristics are mainly calculated by wave by wave analysis method. In this paper, an wave by wave analysis program using MATLAB language is developed. It is possible to perform a function such as 1) correction for mean water level, 2) calculation for zero crossing time, 3) calculation for individual wave height, 4) time interval by using zero upcrossing and downcrossing method. The applicability of the developed program to the data of 0.2 second interval observed by using the WaveGuide Radar installed on HeMOSU-1 was examined. Tidal level variation removal and zero crossing time estimation were determined by linear or quadratic interpolation. It was judged that the Goda method was appropriate for calculating individual wave height, and the method proposed in this study seems to be improved through subsequent research. Due to the fineness of the sample, it can be seen that characteristics of representative waves are different from the results calculated by zero upcrossing and downcrossing method.

• Journal of the Korean Geotechnical Society
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• v.34 no.5
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• pp.19-35
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• 2018

The necessity of predicting the spatial information of the site-specific seismic response, which is essential information for the comprehensive earthquake disaster countermeasures, is increasing for the mid-west urban areas where the earthquake-induced damages can be increased due to frequent occurrence of mid-scale earthquake such as 2016 Gyeongju Earthquake and 2017 Pohang Earthquake. Especially, researches on strategic securing of site survey datasets and understanding the site-specific site response characteristics were conducted for Gyeonggi-do, South Korea. In this study, a GIS-based framework for site-specific assessment of site response and induced vulnerable area in Gyeonggi-do, South Korea was proposed. Geo-Data based on GIS platform was constructed for regional estimation of geotechnical characteristics by collecting borehole and land coverage datasets. And the geo-spatial grid information was developed for deriving spatial distribution of geotechnical layer and site response parameters based on the optimization of the geostatistical interpolation method. Accordingly, base information for Improving earthquake preparedness measures was derived as seismic zonation map with administrative sub-units considering the quantitative site effect of Gyeonggi-do.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.61-69
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• 2020

This study examined the braking characteristics of a heavy haul freight train with P4a distribution valves applied to domestic high-speed freight trains. A freight train was composed of 50 cars, which is twice the normal operation. A braking test was performed to confirm the characteristics of the braking of a heavy haul. The brake cylinder pressures were measured for emergency and service braking on the 1st, 10th, 20th, 30th, and 50th cars. Because the brake signal is transmitted to the pressure through the braking tube connected to the end of the train, the rear vehicle is braking later than the vehicle ahead. Therefore, it is necessary to predict the brake pressures in all cars in a train to supplement the results of the limited tests and calculate the braking distance. The pressure in each car was determined using empirical models of linear interpolation, stepwise, and exponential models, which provided reliable information. The predictive results of the empirical models were compared with the measured results, and the exponential model was predicted relatively accurately. These results are expected to contribute to the safe operation of heavy haul freight trains and can be used to predict the braking distance and calculate the level of impact between vehicles during braking.

• Journal of the Korean earth science society
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• v.40 no.6
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• pp.613-623
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• 2019

Over the past decades, daily sea surface temperature (SST) composite data have been produced using periodically and extensively observed satellite SST data, and have been used for a variety of purposes, including climate change monitoring and oceanic and atmospheric forecasting. In this study, we evaluated the accuracy and analyzed the error characteristic of the SST composite data in the sea around the Korean Peninsula for optimal utilization in the regional seas. We evaluated the four types of multi-satellite SST composite data including OSTIA (Operational Sea Surface Temperature and Sea Ice Analysis), OISST (Optimum Interpolation Sea Surface Temperature), CMC (Canadian Meteorological Centre) SST, and MURSST (Multi-scale Ultra-high Resolution Sea Surface Temperature) collected from January 2016 to December 2016 by using in-situ temperature data measured from the Ieodo Ocean Research Station (IORS). Each SST composite data showed biases of the minimum of 0.12℃ (OISST) and the maximum of 0.55℃ (MURSST) and root mean square errors (RMSE) of the minimum of 0.77℃ (CMC SST) and the maximum of 0.96℃ (MURSST) for the in-situ temperature measurements from the IORS. Inter-comparison between the SST composite fields exhibited biases of -0.38-0.38℃ and RMSE of 0.55-0.82℃. The OSTIA and CMC SST data showed the smallest error while the OISST and MURSST data showed the most obvious error. The results of comparing time series by extracting the SST data at the closest point to the IORS showed that there was an apparent seasonal variation not only in the in-situ temperature from the IORS but also in all the SST composite data. In spring, however, SST composite data tended to be overestimated compared to the in-situ temperature observed from the IORS.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.2
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• pp.47-61
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• 2000

Agroclimatic zoning was done for paddy rice culture in North Korea based on a simulation experiment. Daily weather data for the experiment were generated by 3 steps consisting of spatial interpolation based on topoclimatological relationships, zonal summarization of grid cell values, and conversion of monthly climate data to daily weather data. Regression models for monthly climatological temperature estimation were derived from a statistical procedure using monthly averages of 51 standard weather stations in South and North Korea (1981-1994) and their spatial variables such as latitude, altitude, distance from the coast, sloping angle, and aspect-dependent field of view (openness). Selected models (0.4 to 1.6$^{\circ}C$ RMSE) were applied to the generation of monthly temperature surface over the entire North Korean territory on 1 km$\times$l km grid spacing. Monthly precipitation data were prepared by a procedure described in Yun (2000). Solar radiation data for 27 North Korean stations were reproduced by applying a relationship found in South Korea ([Solar Radiation, MJ m$^{-2}$ day$^{-1}$ ] =0.344 + 0.4756 [Extraterrestrial Solar Irradiance) + 0.0299 [Openness toward south, 0 - 255) - 1.307 [Cloud amount, 0 - 10) - 0.01 [Relative humidity, %), $r^2$=0.92, RMSE = 0.95 ). Monthly solar irradiance data of 27 points calculated from the reproduced data set were converted to 1 km$\times$1 km grid data by inverse distance weighted interpolation. The grid cell values of monthly temperature, solar radiation, and precipitation were summed up to represent corresponding county, which will serve as a land unit for the growth simulation. Finally, we randomly generated daily maximum and minimum temperature, solar irradiance and precipitation data for 30 years from the monthly climatic data for each county based on a statistical method suggested by Pickering et a1. (1994). CERES-rice, a rice growth simulation model, was tuned to accommodate agronomic characteristics of major North Korean cultivars based on observed phenological and yield data at two sites in South Korea during 1995~1998. Daily weather data were fed into the model to simulate the crop status at 183 counties in North Korea for 30 years. Results were analyzed with respect to spatial and temporal variation in yield and maturity, and used to score the suitability of the county for paddy rice culture.