• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.279-290
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• 2022

A superconducting fault current limiter(SFCL) is a power device that exploits superconducting transition to control currents and enhances the flexibility, stability and reliability of the power system within a few milliseconds. With a high phase transition speed, high critical current densities and little AC loss, high-temperature superconducting (HTS) wires are suitable for a resistive-type SFCL. However, HTS wires due to the lack of optimization research are rather inefficient to directly apply to a fault current limiter in terms of the design and capacity, for the existing method relied the characteristics. Therefore, in order to develop a suitable wire for an SFCL, it is necessary to enhance critical current uniformity, select optimal stabilizer materials and conducted research on the development of uniform stabilizer layering technology. The high temperature superconducting wires manufactured by this study get an average critical current of 804 A/12mm-width at the length of 710m; therefore, conducted research was able to secure economic performance by improving efficiency, reducing costs, and reducing size.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.136-136
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• 2021

In this study, a deep convolutional neural network (DCNN) model is proposed for short-term precipitation forecasting using weather radar-based images. The DCNN model is a combination of convolutional neural networks, autoencoder neural networks, and U-net architecture. The weather radar-based image data used here are retrieved from competition for rainfall forecasting in Korea (AI Contest for Rainfall Prediction of Hydroelectric Dam Using Public Data), organized by Dacon under the sponsorship of the Korean Water Resources Association in October 2020. This data is collected from rainy events during the rainy season (April - October) from 2010 to 2017. These images have undergone a preprocessing step to convert from weather radar data to grayscale image data before they are exploited for the competition. Accordingly, each of these gray images covers a spatial dimension of 120×120 pixels and has a corresponding temporal resolution of 10 minutes. Here, each pixel corresponds to a grid of size 4km×4km. The DCNN model is designed in this study to provide 10-minute predictive images in advance. Then, precipitation information can be obtained from these forecast images through empirical conversion formulas. Model performance is assessed by comparing the Score index, which is defined based on the ratio of MAE (mean absolute error) to CSI (critical success index) values. The competition results have demonstrated the impressive performance of the DCNN model, where the Score value is 0.530 compared to the best value from the competition of 0.500, ranking 16^th out of 463 participating teams. This study's findings exhibit the potential of applying the DCNN model to short-term rainfall prediction using weather radar-based images. As a result, this model can be applied to other areas with different spatiotemporal resolutions.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.4
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• pp.19-28
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• 2020

The Urban Heat Island (UHI) Effect has intensified due to urbanization and heat management at the urban level is treated as an important issue. Green space improvement projects and environmental policies are being implemented as a way to alleviate Urban Heat Islands. Several studies have been conducted to analyze the correlation between urban green areas and heat with linear regression models. However, linear regression models have limitations explaining the correlation between heat and the multitude of variables as heat is a result of a combination of non-linear factors. This study evaluated the Heat Island alleviating effects in Seoul during the summer by using a deep neural network model methodology, which has strengths in areas where it is difficult to analyze data with existing statistical analysis methods due to variable factors and a large amount of data. Wide-area data was acquired using Landsat 8. Seoul was divided into a grid (30m × 30m) and the heat island reduction variables were enter in each grid space to create a data structure that is needed for the construction of a deep neural network using ArcGIS 10.7 and Python3.7 with Keras. This deep neural network was used to analyze the correlation between land surface temperature and the variables. We confirmed that the deep neural network model has high explanatory accuracy. It was found that the cooling effect by NDVI was the greatest, and cooling effects due to the park size and green space proximity were also shown. Previous studies showed that the cooling effects related to park size was 2℃-3℃, and the proximity effect was found to lower the temperature 0.3℃-2.3℃. There is a possibility of overestimation of the results of previous studies. The results of this study can provide objective information for the justification and more effective formation of new urban green areas to alleviate the Urban Heat Island phenomenon in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6B
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• pp.531-539
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• 2011

It has been widely acknowledged that climate system associated with extreme rainfall events was difficult to understand and extreme rainfall simulation in climate model was more difficult. This study developed a new model for extracting rainfall filed associated with extreme events as a way to characterize large scale climate system. Main interests are to derive location, size and direction of the rainfall field and this study developed an algorithm to extract the above characteristics from global climate data set. This study mainly utilized specific humidity and wind vectors driven by NCEP reanalysis data to define the rainfall field. Geometric first and second moments have been extensively employed in defining the rainfall field in selected zone, and an ellipsoid based model were finally introduced. The proposed geometric moments based ellipsoid model works equally well with regularly and irregularly distributed synthetic grid data. Finally, the proposed model was applied to space-time real rainfall filed. It was found that location, size and direction of the rainfall field was successfully extracted.

• Journal of the Ergonomics Society of Korea
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• v.31 no.2
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• pp.309-317
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• 2012

Objective: The aim of this paper is to inquire into the influences form factors and control types affect a search time and comfort at list menu of full touch phone. Background: Various studies have been proceeded that are related to the optimum touch area for enhancing usability of control and legibility in mobile touch device. In the environment of list menu which is widely used to provide various information effectively, however, not only comprehensive consideration for legibility and control is to be seek but also research for control type which is to scroll a list. Method: This study executed form factor experiment to inquire into the influence that font size, height of row and fixed area affect searching time and comfort in the while information processing even if the information on the list is unsorted in alphabetical order. Among the result of form factor experiment, control type experiment was executed by selecting shortest performance time, highest legibility comfort and control comfort. Control type experiment was implemented to figure out the influence which existing flicking type, scrolling bar type, newly established button page type and button raw types affect performance time and subjective comfort depending on location of the information. Results: Font size 12pt, height of row 7mm and fixed area 15mm was shortest performance time and got highest comfort and legibility score in form factor experiment. A Button page which was newly proposed type was shortest performance time and got highest comprehensive comfort in control type experiment. Conclusion: Form factor experiment showed similar results with the study through reading a long passage of character or controlling a grid icon type. However, height of row turned out to affect not only touch area for control but also legibility by ruling space between the lines. Button page type which was newly proposed showed shortest performance time and got highest comprehensive comfort. Because Button page type needs few finger movements than other control types and implements search in the fixed form, unlikely other type which list keeps moving. Application: This study should be applied in deciding form factors and control type for scroll when designing a list menu of full touch phone.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.47 no.4
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• pp.390-402
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• 2011

A preliminary study on species composition of a Korean purse seine catch landed at cannery was conducted in April 2011. In the cannery, all tuna catch are sliding through a sorting grid panel that filters and drops fish in the buckets by size class (above 9kg, 3.4-9kg, 1.8-3.4kg, 1.4-1.8kg and below 1.4kg). In cannery processing, species sorting was made for skipjack tuna and yellowfin tuna only from catches greater than 3.4kg during filtering but not for bigeye tuna because of difficulties in species identification between bigeye tuna and yellowfin tuna under frozen state. As no species identification was carried out for catch groups less than 3.4kg in the cannery process, this study focused on sorting out skipjack tuna and yellowfin tuna from these groups and then identifying bigeye tuna from all size groups of yellowfin tuna. Using the mixture rate of species obtained from the samples taken, species composition of the landed catch was estimated. As results, cannery research showed 95% for skipjack tuna, 3% for yellowfin tuna and 2% for bigeye tuna in species composition, while vessel logbook data represented 96%, 3% and 1% for skipjack tuna, yellowfin tuna and bigeye tuna, respectively. The proportion of bigeye tuna identified in the cannery was slightly higher than shown in logbook data by 1%.

• Journal of Biosystems Engineering
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• v.33 no.5
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• pp.362-369
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• 2008

There is developing interest in precision agriculture in Korea, despite the fact that typical Korean fields are less than 1 ha in size. Describing within-field variability in typical Korean production settings is a fundamental first step toward determining the size of management zones and the inter-relationships between limiting factors, for establishment of site-specific management strategies. Measurements of rice (Oriza Sativa L) yield, chlorophyll content, and soil properties were obtained in a small (100-m by 30-m) Korean rice paddy field. Yield data were manually collected on 10-m by 5-m grids (180 samples with 3 samples in each of 60 grid cells) and chlorophyll content was measured using a Minolta SPAD 502 in 2-m by 2-m grids. Soil samples were collected at 275 points to compare results from sampling at different scales. Ten soil properties important for rice production in Korea were determined through laboratory analyses. Variogram analysis and point kriging with and without median polishing were conducted to determine the variability of the measured parameters. Influence of variogram model selection and other parameters on the interpretation of the data was investigated. For many of the data, maximum values were greater than double the minimum values, indicating considerable spatial variability in the small paddy field, and large-scale spatial trends were present. When variograms were fit to the original data, the limits of spatial dependency for rice yield and SP AD reading were 11.5 m and 6.5 m, respectively, and after detrending the limits were reduced to 7.4 m and 3.9 m. The range of spatial dependency for soil properties was variable, with several having ranges as short as 2 m and others having ranges greater than 30 m. Kriged maps of the variables clearly showed the presence of both large-scale (trend) variability and small-scale variability in this small field where it would be reasonable to expect uniformity. These findings indicate the potential for applying the principles and technology of precision agriculture for Korean paddy fields. Additional research is needed to confirm the results with data from other fields and crops.d similar tendency with the result for the frequency less than 20 Hz, but the width of change was reduced highly.

• The KIPS Transactions:PartD
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• v.11D no.6
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• pp.1221-1230
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• 2004

In mobile environments, the locations of moving objects such as vehicles, airplanes and users of wireless devices continuously change over time. For efficiently processing moving object information, the database system should be able to deal with large volume of data, and manage indexing efficiently. However, previous research on indexing method mainly focused on query performance, and did not pay attention to update operation for moving objects. In this paper, we propose a novel moving object indexing method, named ACAR-Tree. For processing efficiently frequently updating of moving object location information as well as query performance, the proposed method is based on fixed grid structure with auxiliary R-Tree. This hybrid structure is able to overcome the poor update performance of R-Tree which is caused by reorganizing of R-Tree. Also, the proposed method is able to efficiently deal with skewed-. or gaussian distribution of data using auxiliary R-Tree. The experimental results using various data size and distribution of data show that the proposed method has reduced the size of index and improve the update and query performance compared with R-Tree indexing method.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.1
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• pp.28-38
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• 2004

The purpose of this study is to analyze the urban hydrologic state by the use of GIS, resolution and interpolation. The determination coefficient($R^2$) and Regression Formula were derived from the contour of digital map for the accuracy, and DEM data was made by using TIN interpolation by the size of the grid. By using the observed DEM data, topographical factors were extracted from the small basin, size, the width of a basin and the slope, and were applied in the urban runoff model. Through the model, we tried to find out the most suitable runoff model in a small basin of Yosu-Munsu area. As a result of applying models to the drainage considered, the runoff hydrograph estimated by SWMM model was closer to the observed one than that estimated by ILLUDAS model. The difference between the runoff hydrograph by SWMM and the observed one is maximum error of 19%, minimum error of 5% and average error of 13%. The influence of duration in contrast to pick time is insignificant in a urban small basin. As a conclusion of this study, SWMM model was more suitable and applicable for the urban runoff model than ILLUDAS model due to its accuracy and various abilities.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.165-178
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• 2021

We studied driftwood behaviors including generation and deposition in a tsunami using a numerical simulation. We used an integrated two-dimensional numerical model, which included a driftwood dynamics model. The study area was Sendai, Japan. Observation data collected by Inagaki et al. (2012) were used to verify the simulation results by comparing them with driftwood deposition patterns. A simplified model was developed to consider the threshold of driftwood generation by the drag force of water flows. To consider the volume of driftwood generated, we estimated the total wood number in the study area using Google Earth. Therefore, we simulated more than 13,000 pieces of driftwood that were generated and transported inland from approximately 300,000 trees that were growing in the forest. The final distribution of the driftwood was similar to the observation data. The reproducibility of the generation and deposition patterns of driftwood showed good agreement in terms of longitudinal deposition pattern. In the future, a sensitivity analysis on driftwood parameters, such as the size of the wood, boundary conditions, and grid size, will be implemented to predict the travel patterns of driftwood. Such modeling will be a useful methodology for disaster prediction based on water flow and driftwood.