• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.948-948
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• 2012

합천댐유역에 대한 기후변화에 따른 수문학적 영향을 정량적으로 분석하기 위해, 기상청에서 제공하는 공간해상도 27km의 MM5 RCM(Regional Climate Model)을 사용하였다. RCM의 기상변수들은 공간적 스케일의 상이성과 RCM 기후변수들의 불확실성 때문에 유출모형인 SWAT의 입력자료로 사용하기에는 어려움이 있다. 특히, RCM 변수들 중 강수량의 경우 한반도 지역의 6월과 10월 사이에 연강수량의 67%이상이 집중되는 계절성을 반영하지 못하고 있는 실정이기 때문에 국내 유역의 유출량 산정에 사용하기 위해서는 지역적 상세화(Downscaling)가 필요하다. 본 연구에서는 RCM 기후변수에 내포된 공간적 스케일의 상이성과 불확실성을 최소화하기 위해 강우관측소 지점을 단위로 한 다지점 인공신경망 기법을 적용하여 강수량, 습도, 최고기온 및 최저기온에 대한 상세화를 실시하였다. 강수의 경우 여름철 태풍사상을 모의하기 위한 Stochastic Typhoon Simulation기법과 Baseline(1991~2010)과 Projection(2011~2100) 사이의 강수량 보정을 위한 Dynamic Quantile Mapping 기법을 적용하여, 강수량의 불확실성을 최소화 하고자 하였다. 상세화된 기후자료를 이용한 SWAT 모형의 일(Daily) 단위 강우-유출 모의결과를 2011~2040년, 2041~2070년, 2071~2100년으로 구분하여 추세분석을 실시하였다.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1234-1245
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• 2018

The risk of multi-unit nuclear power plants (NPPs) at a site has received considerable critical attention recently. However, current probabilistic safety assessment (PSA) procedures and computer code do not support multi-unit PSA because the traditional PSA structure is mostly used for the quantification of single-unit NPP risk. In this study, the main purpose is to develop a multi-unit Level 2 PSA method and apply it to full-power operating six-unit OPR1000. Multi-unit Level 2 PSA method consists of three steps: (1) development of single-unit Level 2 PSA; (2) extracting the mapping data from plant damage state to source term category; and (3) combining multi-unit Level 1 PSA results and mapping fractions. By applying developed multi-unit Level 2 PSA method into six-unit OPR1000, site containment failure probabilities in case of loss of ultimate heat sink, loss of off-site power, tsunami, and seismic event were quantified.

• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.72-81
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• 2023

We introduce tightly-coupled GNSS-LiDAR-Inertial state estimator, which is capable of SLAM (Simultaneously Localization and Mapping) and autonomous driving. Long term drift is one of the main sources of estimation error, and some LiDAR SLAM framework utilize loop closure to overcome this error. However, when loop closing event happens, one's current state could change abruptly and pose some safety issues on drivers. Directly utilizing GNSS (Global Navigation Satellite System) positioning information could help alleviating this problem, but accurate information is not always available and inaccurate vertical positioning issues still exist. We thus propose our method which tightly couples raw GNSS measurements into LiDAR-Inertial SLAM framework which can handle satellite positioning information regardless of its uncertainty. Also, with NLOS (Non-light-of-sight) satellite signal handling, we can estimate our states more smoothly and accurately. With several autonomous driving tests on AGV (Autonomous Ground Vehicle), we verified that our method can be applied to real-world problem.

• International Journal of Contents
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• v.7 no.4
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• pp.108-115
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• 2011

The current study aims to analyze the acceptance of International Standard Terminology (IST) related to herbs and formulas used in Korea. It also intends to examine limitations of each term source by linking texts for herbal medicine research and formula research used in schools of oriental medicine with medicinal substance-formula classification names within the IST framework. This study examined 64 medicinal classification names of IST, including synonyms, 41 formula classification names, 65 classification names of "Herbal Medicine Study," 89 medicinal classification names of "Shin's Clinical Herbal Medicine Study," and lastly 83 formula classification names of "Formula Study." Data on their chief virtue, efficacy and characteristics as medicinal substances were extracted from their definitions, and such data were used to perform Chinese character-English mapping using the IST. The outcomes of the mapping were then analyzed in terms of both lexical matching and semantic matching. In terms of classification names for medicinal substances, "Herbal Medicine Study" had 60.0% lexical matching, whereas "Shin's Clinical Herbal Medicine Study" had 48.3% lexical matching. When semantic matching was also applied, "Herbal Medicine Study" showed a value of 87.7% and "Shin's Clinical Herbal Medicine Study" 74.2%. In terms of formula classification names, lexical matching was 28.9% of 83 subjects, and when semantic matching was also considered, the value was 30.1%. When the conceptual elements of this study were applied, some IST terms that are classified with other codes were found to be conceptually consistent, and some terms were not accepted due to different depths in the classification systems of each source.

• Journal of muscle and joint health
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• v.26 no.3
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• pp.223-231
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• 2019

Purpose: This study aimed to design user interfaces of a mobile application for managing pressure injury patients in a long-term care hospital based on the user's needs. Methods: To reflect users' needs in the mobile application, the user interfaces in this study were designed in five steps: brainstorming and mind mapping, persona and scenario, needs list and priority, a draft version of flow chart and user interfaces and expert review. These steps were conducted with a step nurse at a long-term care hospital, a professor who majored in nursing informatics, a professor who had lots of research experiences about pressure injury and a wound ostomy continence nurse. Results: Two personas, scenarios and needs' lists were derived. Listed Needs included the followings; Accurate staging of pressure injury; Appropriate management by staging; Acquisition of professional knowledge about pressure injury; Acquisition of easy pressure injury information through text, picture and video; and Sharing pressure injury information in unit. The structure, menus and features of the pressure injury mobile application were visualized with user flow based on two personas' scenarios and needs' lists. Conclusion: Our study suggests and visualizes the key features of the 'Pressure Injury Guide', a pressure injury management mobile application for nurses in a long-term care hospital, which can be utilized by nurses, application developers, and related researchers.

• Atmosphere
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• v.29 no.1
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• pp.13-20
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• 2019

Since 1985, the Dobson Spectrophotometer has been operated at Yonsei University, and this instrument has monitored the daily representative total ozone in Seoul. Climatological value for total ozone in Seoul is updated by using the daily representative observation data from 1985 to 2017. After updating the daily representative total ozone data, seasonal and inter-annual variation of total ozone in Seoul is also estimated after calculating inter-comparison between ground (Dobson Spectrophotometer) and satellite [Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instrument (OMI)] observations. The global average of total ozone measured by satellite is 297 DU, and its recent amount is about 3.5% lower than the global amount in 1980s. In Seoul, daily representative total ozone is ranged from 225 DU to 518 DU with longterm mean value of 324.3 DU. In addition, monthly mean total ozone is estimated from 290 DU (October) to 362 DU (March), and yearly average of total ozone have been continuously increased since 1985. For the long-term trend of total ozone in Seoul, this study is considered the seasonal variation, Solar Cycle, and Quasi-Biennial Oscillation. In addition to the natural oscillation effect, this study also considered to the long-term variation of sudden increase of total ozone due to the secondary ozone peak. By considering these natural effects, the long-term total ozone trends from 1985 to 2017 are estimated to be 1.11~1.46%/decade.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.522-541
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• 2016

Network virtualization provides an effective way to overcome the Internet ossification problem. As one of the main challenges in network virtualization, virtual network embedding refers to mapping multiple virtual networks onto a shared substrate network. However, existing heuristic embedding algorithms evaluate the embedding potential of the nodes simply by the product of different resource attributes, which would result in an unbalanced embedding. Furthermore, ignoring the hops of substrate paths that the virtual links would be mapped onto may restrict the ability of the substrate network to accept additional virtual network requests, and lead to low utilization rate of resource. In this paper, we introduce and extend five node attributes that quantify the embedding potential of the nodes from both the local and global views, and adopt the technique for order preference by similarity ideal solution (TOPSIS) to rank the nodes, aiming at balancing different node attributes to increase the utilization rate of resource. Moreover, we propose a novel two-stage virtual network embedding algorithm, which maps the virtual nodes onto the substrate nodes according to the node ranks, and adopts a shortest path-based algorithm to map the virtual links. Simulation results show that the new algorithm significantly increases the long-term average revenue, the long-term revenue to cost ratio and the acceptance ratio.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.169-176
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• 2021

Maritime monitoring requirements have been beyond human operators capabilities due to the broadness of the coverage area and the variety of monitoring activities, e.g. illegal migration, or security threats by foreign warships. Abnormal vessel movement can be defined as an unreasonable movement deviation from the usual trajectory, speed, or other traffic parameters. Detection of the abnormal vessel movement requires the operators not only to pay short-term attention but also to have long-term trajectory trace ability. Recent advances in deep learning have shown the potential of deep learning techniques to discover hidden and more complex relations that often lie in low dimensional latent spaces. In this paper, we propose a deep autoencoder-based clustering model for automatic detection of vessel movement anomaly to assist monitoring operators to take actions on the vessel for more investigation. We first generate gridded trajectory images by mapping the raw vessel trajectories into two dimensional matrix. Based on the gridded image input, we test the proposed model along with the other deep autoencoder-based models for the abnormal trajectory data generated through rotation and speed variation from normal trajectories. We show that the proposed model improves detection accuracy for the generated abnormal trajectories compared to the other models.

• Geomechanics and Engineering
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• v.37 no.4
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• pp.395-418
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• 2024

The epicentral region of earthquakes is typically where liquefaction-related damage takes place. To determine the maximum distance, such as maximum epicentral distance (R_e), maximum fault distance (R_f), or maximum hypocentral distance (R_h), at which an earthquake can inflict damage, given its magnitude, this study, using a recently updated global liquefaction database, multiple ML models are built to predict the limiting distances (R_e, R_f, or R_h) required for an earthquake of a given magnitude to cause damage. Four machine learning models LSTM (Long Short-Term Memory), BiLSTM (Bidirectional Long Short-Term Memory), CNN (Convolutional Neural Network), and XGB (Extreme Gradient Boosting) are developed using the Python programming language. All four proposed ML models performed better than empirical models for limiting distance assessment. Among these models, the XGB model outperformed all the models. In order to determine how well the suggested models can predict limiting distances, a number of statistical parameters have been studied. To compare the accuracy of the proposed models, rank analysis, error matrix, and Taylor diagram have been developed. The ML models proposed in this paper are more robust than other current models and may be used to assess the minimal energy of a liquefaction disaster caused by an earthquake or to estimate the maximum distance of a liquefied site provided an earthquake in rapid disaster mapping.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.3
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• pp.92-106
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• 2008

The purpose of this study is to identify land use types and to develop and evaluate biotope maps for Gangseo-Gu (ward) in Busan Metropolitan City, South Korea, using the Degree of Hemeroby. Hemeroby is a measurement concept or tool to assess the magnitude of human impact on ecosystems. Gangseo-Gu is the second largest Gu in Busan and is under strong development pressure. Before the field survey, biotopes were pre-classified based on digital maps, aerial photos and high-resolution satellite images. The method employed in biotope survey and mapping was adopted from the modified method used in Seoul, which carried out the first biotope mapping in Korea in 2000. In the field survey, a comprehensive biotope mapping method was used. The results showed that the total surface area of biotopes in Gangseo-gu was $172,620,207m^2$(42,655 acres) and there were 29 biotope types with 13,631 polygons. The ratio of urban or built-up area 22.6% and the remaining areas were forest and open spaces, of which 22.6% were actual forest areas and 35.6% were paddy fields and other field areas. The Hemeroby Index of Gangseo-gu was 54.7, which suggests that Gangseo-gu has not yet been developed extensively and needs a long-term conservation and coordinated development plan.