• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.33-40
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• 2022

In this paper, we propose a system that analyzes drone photographic images of panel-type factory roofs and conducts abnormal detection of bolts. Currently, inspectors directly climb onto the roof to carry out the inspection. However, safety accidents caused by working conditions at high places are continuously occurring, and new alternatives are needed. In response, the results of drone photography, which has recently emerged as an alternative to the dangerous environment inspection plan, will be easily inspected by finding the location of abnormal bolts using deep learning. The system proposed in this study proceeds with scanning the captured drone image using a sample image for the situation where the bolt cap is released. Furthermore, the scanned position is discriminated by using AI, and the presence/absence of the bolt abnormality is accurately discriminated. The AI used in this study showed 99% accuracy in test results based on VGGNet.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.6
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• pp.646-653
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• 2018

Marine accidents caused by dragging anchors occur constantly due to enlargement of ships' size and unusual weather conditions. Nevertheless, vessel operators rely on their experience because the calculations of actual holding power and external forces are complex and inconvenient. The purpose of this study was to propose a program for the anchor dragging risk assessment in order to provide crew and VTSO with the information to determine easily the danger of dragging and take appropriate action. The input data in this program were composed of the ship's basic particulars, anchoring condition, and external environment etc. on calculating for the wind pressure, frictional force, drift force, and holding power. Three dragging anchor accidents were applied to the program's data input at the time of the day, then the result was assessed by 'warning', which was verified with a high confidence. As a result, the risk of dragging anchors can be predicted in advance through this program. In further studies, it is necessary to simplify the input data and improve user convenience through automatic input from various equipment.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.481-481
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• 2021

서울시는 '10년, '11년, '18년의 기록적인 호우로 인해 막대한 재산피해를 기록하였다. 이로 인해 서울시는 수재해 최소화 대책의 필요성을 인지하여 방재시설물 확충 등의 구조적 대책과 함께 침수지역 예측, 호우 영향 예보와 관련된 비구조적 대책 수립을 위해 노력하고 있다. 그 일환으로 2018~2019년 『서울시 강한 비구름 유입경로 및 침수위험도 예측 용역』 수행을 통해 레이더 실황강우 기반의 강한 비구름 이동경로 추정 기술, 강우시나리오 기반의 침수위험지역추정 기술이 적용된 서울시 도시침수 예측시스템을 개발하였다. 또한, 침수피해에 선제적으로 대응하기 위해 2019~2020년 『서울시 내수침수 위험지역 실시간 예측기술 개발』을 통하여 이류모델 기반의 예측강우정보 추정 기술, 예측강우정보 기반의 실시간 침수위험지역 추정기술을 적용하였다. 현재 서울시 도시침수 예측시스템은 서울시 전역의 강우 및 침수정보를 제공하며, 관로 113,286개(전체 385,768개), 맨홀 106,097개(전체 272,133개), 빗물펌프장 117개소(전체 121개소)가 반영되어 있다. 서울시 도시침수 예측시스템에서는 서울시 25개 자치구를 대상으로 실황 및 예측 강우정보, 강한 비구름에 대한 이동경로정보, 시나리오 및 실시간 침수정보를 제공하고 있다. 강우정보는 10분 및 1시간 단위 AWS 실황정보와 10분 단위 이류모델 기반 예측정보, 1시간 단위 LDAPS 기반 예측정보를 제공한다. 또한, 레이더 실황정보를 통해 판별된 강한 비구름에 대해 10분 단위 1시간 예측경로를 제공한다. 침수정보는 총강우량, 강우지속기간, 빗물받이효율 조건을 반영한 강우시나리오 기반의 6m 고해상도 격자단위 침수시나리오 정보와 자치구별 침수위험정보를 제공한다. 또한, 이류모델 기반의 레이더 예측정보를 이용하여 실시간 침수 예측정보를 제공한다. 향후 서울시 내 모든 수방시설물의 적용, 관로 유출구별 기점수위 반영, 관측자료를 이용한 도시유출 및 도시침수 모델 최적화 등 지속적으로 고도화를 수행하고자 하며, 서울시 도시침수 예측시스템을 통해 서울시 및 자치구 풍수해 담당자가 침수피해를 대비, 대응할 수 있을 것으로 기대된다.

• Journal of the Korean Geotechnical Society
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• v.31 no.6
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• pp.59-69
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• 2015

Recently, landslide and debris-flow disasters caused by severe rain storms have frequently occurred. Many researches related to landslide susceptibility analysis and debris-flow hazard analysis have been conducted, but there are not many researches related to mobilization analysis for landslides transforming into debris-flow in slope areas. In this study, statistical analyses such as discriminant analysis and logistic regression analysis were conducted to develop a mobilization criterion using geomorphological and geological factors. Ten parameters of geomorphological and geological factors were used as independent variables, and 466 cases (228 non-mobilization cases and 238 mobilization cases) were investigated for the statistical analyses. First of all, Fisher's discriminant function was used for the mobilization criterion. It showed 91.6 percent in the accuracy of actual mobilization cases, but homogeneity condition of variance and covariance between non-mobilization and mobilization groups was not satisfied, and independent variables did not follow normal distribution, either. Second, binomial logistic analysis was conducted for the mobilization criterion. The result showed 92.3 percent in the accuracy of actual mobilization cases, and all assumptions for the logistic analysis were satisfied. Therefore, it can be concluded that the mobilization criterion for debris-flow using binomial logistic regression analysis can be effectively applied for the prediction of debris-flow hazard analysis.

• Journal of the Korean earth science society
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• v.31 no.6
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• pp.563-572
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• 2010

Both multi-channel temperature monitoring and geophysical electric survey were performed together for an embankment to assess the leakage zone. Temperature variation according to space and time on the inner parts of engineering constructions (e.g.: dam and slope) can be basic information for diagnosing their safety problem. In general, as constructions become superannuated, structural deformation (e.g.: cracks and defects) could be generated by various factors. Seepage or leakage of water through the cracks or defects in old dams will directly cause temperature anomaly. This study shows that the position of seepage or leakage in dam body can be detected by multi-channel temperature monitoring using thermal line sensor. For that matter, diverse temperature monitoring experiments for a leakage physical model were performed in the laboratory. In field application of an old earth fill dam, temperature variations for water depth and for inner parts of boreholes located at downstream slope were measured. Temperature monitoring results for a long time at the bottom of downstream slope of the dam showed the possibility that temperature monitoring can provide the synthetic information about flowing path and quantity of seepage of leakage in dam body. Geophysical data by electrical method are also added to help interpret data.

• Korean Journal of Social Welfare
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• v.61 no.1
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• pp.163-194
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• 2009

The purposes of the presented study were to investigate the characteristics related to the acculturation strategies and to investigate characteristics which discriminated the acculturation strategies among immigrated women in Korea based on the multidimensional perspective on acculturation. The study was designed as a social survey study. Data from 346 immigrated women were analyzed. Findings indicated that 37% of the respondents were marginalization, 30% were integration, 18% were segregation, and 15% were assimilation. Integration was associated with Vietnam nationality, younger age, lower level of education. Assimilation was related to longer period of residence, higher number of children, lower level of resilience. Marginalization was associated with North Korea, Japan, China nationality, older age, higher level of education. Segregation was related to older age, higher level of education, lower number of children. Also, Southeast nationality, age, level of education, spouse, and number of children significantly discriminated the acculturation strategies. Especially, the rate of correct discrimination was 80% only for integration. Practical implications from this study were discussed.

• Management & Information Systems Review
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• v.28 no.3
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• pp.1-23
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• 2009

Prior bankruptcy studies have established that bankrupt firm's pre-filing financial ratios are different from those of healthy firms or of randomly selected going concerns. However, they may not be sufficiently different from the financial ratios of other firms in financial distress to allow the development of a ratio-based model that predicts bankruptcy with reasonable accuracy. As the result, in the multiple discriminant model, independent variables divided firms into bankrupt firms and healthy firms are retained earnings to total asset, receivable turnover, net income to sales, financial expenses, inventory turnover, owner's equity to total asset, cash flow to current liability, and current asset to current liability. Moreover four variables Retained earnings to total asset, net income to sales, total asset turnover, owner's equity to total asset indicate that these valuables classify bankrupt firms and distress firms. On the other hand, Owner's Equity to borrowed capital, Ordinary income to Net Sales, Operating Income to Total Asset, Total Asset Turnover and Inventory Turnover are selected to predict bankruptcy possibility in the Logistic regression model.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.3
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• pp.95-100
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• 2009

Fine fuel moisture code (FFMC), a main component of forest fire weather index(FWI) in the Canadian forest fire danger rating system(CFFDRS), indicated a probability of ignition through expecting a dryness of fine fuels. According to this code, a rising of temperature and wind velocity, a decreasing of precipitation and decline of humidity in a weather condition showed a rising of a danger rate for the forest fire. In this study, we analyzed a weather condition during 5 years in Kangwon province, calculated a FFMC and examined an application of FFMC. Very low humidity and little precipitation was a characteristic during spring and fall fire season in Kangwon province. 75% of forest fires during 5 years occurred in this season and especially 90% of forest fire during fire season occurred in spring. For developing of the prediction model for a forest fire occurrence probability, we used a logistic regression function with forest fire occurrence data and classified mean FFMC during 10 days. Accuracy of a developed model was 63.6%. To improve this model, we need to deal with more meteorological data during overall seasons and to associate a meteorological condition with a forest fire occurrence with more research results.

• The Journal of the Korea Contents Association
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• v.17 no.6
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• pp.98-105
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• 2017

The medical institution considers liability management problems as a direct factor in managerial risks, such as bankruptcy. Cash Flow provides useful information to necessary funds and predicting bankruptcy. The study for 24 general hospitals and 23 hospitals, a regression analysis was performed to determine the impact of cash flows on the debt repayment capability, a multivariate discrimination analysis was conducted to find out how to manage cash flow for the risk posed by debt. The analysis results, For general hospitals, the level of debt repayment capability was done to net income, increase of payables from operating activities and decrease of patient receivables and inventories from operating activities. If there is no dept repayment capability, it is necessary to increase the net income, increase the expenses not involving cash outflows, decrease of patient receivables and increase of payables from operating activities. For hospitals, the level of debt repayment capability was done to net income, increase of expenses not involving cash outflows and payables from operating activities, decrease of income not involving cash inflows, decrease of patient receivables and inventories from operating activities. If there is no dept repayment capability, it is necessary to increase of payables from operating activities.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.12
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• pp.6098-6104
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• 2012

Currently, dozens of CCTVs are widely used in railway station for monitoring passengers in danger and security areas. The most frequent accidents occur at the platform area where passengers boarding the train. However, It is almost impossible that station operator monitors dozens of CCTV screens and recognizes immediately accidents and handle them. Therefore, railway platform monitoring system using image processing technology which automatically detects platform accidents is needed, and in order to that, preferentially, accurate determination of train state in the platform is required. In the paper, we propose train state detection algorithm for vision based railway platform monitoring system. the proposed algorithm determines four different states i.e. trains approach(IN), departure(OUT), stop(ON), and empty(OFF) of the train, in the platform. To evaluate the proposed algorithm, we present the train detection results for the Seoul Metro Line 4 Dongjak and Namtaeryeong Station.