• Atmosphere
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• v.31 no.5
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• pp.637-656
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• 2021

The United States has been known as the world's major producer of crops such as wheat, corn, and soybeans. Therefore, using meteorological long-term forecast data to project reliable crop yields in the United States is important for planning domestic food policies. The current study is part of an effort to improve the seasonal predictability of regional-scale precipitation across the United States for estimating crop production in the country. For the purpose, a dynamic downscaling method using Weather Research and Forecasting (WRF) model is utilized. The WRF simulation covers the crop-growing period (March to October) during 2000-2020. The initial and lateral boundary conditions of WRF are derived from the Pusan National University Coupled General Circulation Model (PNU CGCM), a participant model of Asia-Pacific Economic Cooperation Climate Center (APCC) Long-Term Multi-Model Ensemble Prediction System. For bias correction of downscaled daily precipitation, empirical quantile mapping (EQM) is applied. The downscaled data set without and with correction are called WRF_UC and WRF_C, respectively. In terms of mean precipitation, the EQM effectively reduces the wet biases over most of the United States and improves the spatial correlation coefficient with observation. The daily precipitation of WRF_C shows the better performance in terms of frequency and extreme precipitation intensity compared to WRF_UC. In addition, WRF_C shows a more reasonable performance in predicting drought frequency according to intensity than WRF_UC.

• Wind and Structures
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• v.34 no.5
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• pp.421-435
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• 2022

To investigate the non-Gaussian properties of fluctuating wind pressures and the error margin of extreme wind loads on a long-span curved roof with matching and mismatching ratios of turbulence integral scales to depth (L_u^x/D), a series of synchronized pressure tests on the rigid model of the complex curved roof were conducted. The regions of Gaussian distribution and non-Gaussian distribution were identified by two criteria, which were based on the cumulative probabilities of higher-order statistical moments (skewness and kurtosis coefficients, S_k and K_u) and spatial correlation of fluctuating wind pressures, respectively. Then the characteristics of fluctuating wind-loads in the non-Gaussian region were analyzed in detail in order to understand the effects of turbulence integral-scale. Results showed that the fluctuating pressures with obvious negative-skewness appear in the area near the leading edge, which is categorized as the non-Gaussian region by both two identification criteria. Comparing with those in the wind field with matching L_u^x/D, the range of non-Gaussian region almost unchanged with a smaller L_u^x/D, while the non-Gaussian features become more evident, leading to higher values of S_k, Ku and peak factor. On contrary, the values of fluctuating pressures become lower in the wind field with a smaller L_u^x/D, eventually resulting in underestimation of extreme wind loads. Hence, the matching relationship of turbulence integral scale to depth should be carefully considered as estimating the extreme wind loads of long-span roof by wind tunnel tests.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.428-430
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• 2022

Image processing is playing an important part in automation and artificial intelligence systems, such as object tracking, object recognition and classification, and the importance of IoT technology and automation is emphasizing as interest in automation increases. However, in a system that requires detailed data such as an image boundary, a precise noise removal algorithm is required. Therefore, in this paper, we propose a filtering algorithm based on the pixel value distribution pattern to minimize the information loss in the filtering process. The proposed algorithm finds the distribution pattern of neighboring pixel values with respect to the pixel values of the input image. Then, a weight mask is calculated based on the distribution pattern, and the final output is calculated by applying it to the filtering mask. The proposed algorithm has superior noise removal characteristics compared to the existing method and restored the image while minimizing blurring.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.43.1-43.1
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• 2020

Cassiopeia A (Cas A) is a young supernova remnant (SNR) where we observe the interaction of SNR blast wave with circumstellar medium. From the early optical studies, dense, slowly-moving, N-rich "quasi-stationary flocculi" (QSF) have been known. These are probably dense CNO-processed circumstellar knots that have been engulfed by the SNR blast wave. We have carried out near-infrared, high-resolution (R=45,000) spectroscopic observations of ~40 QSF, and here we present the result on a QSF knot (hereafter 'Knot 24') near the SNR boundary of Cas A. The average [Fe II] 1.644 um spectrum of Knot 24 has a remarkable shape with a narrow (~8 km/s) line superposed on the broad (~200 km/s) line emitted from shocked gas. The spatial morphology and the line parameters indicate that Knot 24 has been partially destroyed by a shock wave and that the narrow line is emitted from the unshocked material heated/ionized by the shock radiation. This is the first detection of the emission from the pristine circumstellar material of the Cas A supernova progenitor. We also detected H Br gamma and other [Fe II] lines corresponding to the narrow [Fe II] 1.644 um line. For the main clump where we can clearly identify the shock emission associated with the unshocked material, we analyze the observed line ratios using a shock model that includes radiative precursor. The analysis indicates that the majority of Fe in the unshocked material is in the gas phase, not depleted onto dust grains as in the general interstellar medium. We discuss the non-depletion of Fe in QSF and its implications on the immediate progenitor of the Cas A supernova.

• Journal of Fashion Business
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• v.27 no.3
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• pp.35-49
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• 2023

The purpose is to derive its aesthetic characteristics by objectifying the visual image of the YouTube campaign into adjectives. As a result, we intend to identify advertising strategies that use them as basic data for setting fashion design concepts. A group of experts in fashion majors watched each of them, wrote adjectives, and collected 75 adjectives. By analyzing the frequency of adjectives, aesthetic characteristics were derived with adjectives recording the upper number of times, and the results were obtained that they had the characteristics of deconstruction. The conclusions of this study are as follows. First, Tamburin's Jenny appeared to be strange, scary, rambling and charming. Among the internal meanings of deconstruction due to spatial, social, and psychological distance from consumers, it can be said that T.P.O's mutual textuality and play of interaction. Second, Gucci Cruise be chosen rural, strange, wild, unharmonious, and difficult, which is a mixture of intertextuality and play of T.P.O. Third, The Excise Gucci Campaign parodies that juxtaposes six films directed by Stanley Kubrick, making them strange, retro, difficult, interesting, and wrong. Deconstructionist de-genre and de-boundary Fourth, Kenzo World is weird, dynamic, wrong, difficult, difficult, and confused, which correspond to T.P.O's interactive textuality, play of the second half, and destruction and decomposition among the external expressions of deconstruction. Fifth, Burberry Hero emphasized the aesthetic value of traditional men, so it was ostensibly wild, free, powerful, sensual, and fantastic. Compared to the lifestyle of men who usually work at work, this corresponds to play of second best.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5B
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• pp.481-488
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• 2006

This paper suggests a novel approach of integrating the quasi-distributed watershed model SWAT with the fully-distributed groundwater model MODFLOW. Since the SWAT model has semi distributed features, its groundwater components hardly considers distributed parameters such as hydraulic conductivity and storage coefficient. Generating a detailed representation of groundwater recharge, head distribution and pumping rate is equally difficult. To solve these problems, the method of exchanging the characteristics of the hydrologic response units (HRUs) in SWAT with cells in MODFLOW by fully combined manner is proposed. The linkage is completed by considering the interaction between the stream network and the aquifer to reflect boundary flow. This approach is provisionally applied to Gyungancheon basin in Korea. The application demonstrates a combined model which enables an interaction between saturated zones and channel reaches. This interaction plays an essential role in the runoff generation in the Gyungancheon basin. The comprehensive results show a wide applicability of the model which represents the temporal-spatial groundwater head distribution and recharge.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.25-41
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• 2024

For the scenario of open pit mining, at present, manual periodic verification is mainly carried out in China with the help of video surveillance, which requires continuous investment in labor cost and has poor timeliness. In order to solve this difficult problem of early warning and monitoring, this paper researches a spatialized algorithmic model and designs an early warning system for open-pit mine transboundary mining, which is realized by calculating the coordinate information of the mining and extracting equipments and comparing it with the layer coordinates of the approval range of the mines in real time, so as to realize the determination of the transboundary mining behavior of the mines. By taking the Pingxiang area of Jiangxi Province as the research object, after the field experiment, it shows that the system runs stably and reliably, and verifies that the target tracking accuracy of the system is high, which can effectively improve the early warning capability of the open-pit mines' overstepping the boundary, improve the timeliness and accuracy of mine supervision, and reduce the supervision cost.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.27 no.1
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• pp.17-29
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• 2024

This study was conducted to select the restoration priority of forest damage sites in Gangwon Province. We first identified the status of damaged areas. We then selected restoration evaluation indicators through a literature review. We then set weights for these indicators through expert surveys. We next acquired data that can represent these indicators and spatially mapped them. Finally, we prioritized the restoration target sites by taking the weights. The results of the study showed that disaster sensitivity and ecologicality are important criteria for selecting the restoration priority of damage sites. The analysis showed that damage sites in Doam, Jeongseon, Samcheok and Inje are in urgent need of restoration. The results of this study are significant in that they selected the restoration priority of damage sites in Gangwon Province based on the restoration priority evaluation criteria selected based on expert surveys. However, the priority restoration areas derived from the results of this study are not actually implementing restoration projects at present. Therefore, it is judged that it would be efficient in various aspects to establish the restoration priority area based on scientific analysis techniques and carry out the project for efficient implementation of the restoration project. In this study, it can be pointed out that the priority of restoration of damage sites was derived based on data from the past due to the limitation of data acquisition. However, the fact that the priority restoration area inferred based on past data has been restored over time has improved the reliability of the study by verifying the usefulness of the priority extraction technique. In the future, if the priority of damage sites is extracted by extracting the restoration target area boundary through the latest data based on the methodology applied in this study, it is considered that it will be available as a result that can be applied to the field.

• Atmosphere
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• v.34 no.2
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• pp.83-95
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• 2024

Atmospheric rivers (ARs) are closely related to local precipitation which can be both beneficial and destructive. Although several studies have evaluated their predictability, there is a lack of studies on East Asian ARs. This study evaluates the prediction skill of East Asian ARs in the Korean Integrated Model (KIM) for 2020~2022 summer. The spatial distribution of AR frequency in KIM is qualitatively similar to the observation but overestimated. In particular, the model errors greatly increase along the boundary of the western North Pacific subtropical high as the forecast lead time increases. When the prediction skills are quantitatively verified by computing the Anomaly Correlation Coefficient and Mean Square Skill Score, the useful prediction skill of daily AR around the Korean Peninsula is found up to 5 days. Such prediction limit is primarily set by the wind field errors with a minor contribution of moisture distribution errors. This result suggests that the improved prediction of atmospheric circulation field can improve the prediction of East Asian summer ARs and the associated precipitation.

• Journal of Korean Society of Rural Planning
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• v.30 no.3
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• pp.75-84
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• 2024

This study developed the procedure and method for the accuracy assessment of unmanned boat survey data, based on the reservoir water depth data of Misan Reservoir, measured by the manned and unmanned boats in 2009 by Korea Rural Community Corporation. In the first step, this study devised the method to extract the contour map of NGIS data in AutoCAD to generate easily the reservoir boundary map used to set the survey range of reservoir water depth and to test the survey accuracy. The surveyed data coordinate systems of the manned and the unmanned boat were also unified by using ArcGIS for the standards of accuracy assessment. In the accuracy assessment, the spatial correlation coefficient of the grid maps of the two measurement results was 0.95, showing high pattern similarity, although the average error was high at 78cm. To analyze in more detail assessment, this study generated randomly the 3,250m transverse profile route (PR), and then extracted grid values of water depth on the PR. In the results of analysis to the extracted depth data on PR, the error average difference of the unmanned boat measurements was 73.18cm and the standard deviation of the error was 55cm compared to the manned boat. This study set these values as the standard for the correction value by average shift and noise removal of the unmanned boat measurement data. By correcting the unmanned boat measurements with these values, this study has high accuracy results, the reservoir water depth and surface area curve with R² = 0.97 and the water depth and storage volume curve with R² = 0.999.