• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1285-1294
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• 2021

In recent years, as rainfall is concentrated and rainfall intensity increases worldwide due to climate change, the scale of flood damage is increasing. Rainfall of a previously unobserved magnitude falls, and the rainy season lasts for a long time on record. In particular, these damages are concentrated in ASEAN countries, and at least 20 million people among ASEAN countries are affected by frequent flooding due to recent sea level rise, typhoons and torrential rain. Korea supports the domestic flood warning system to ASEAN countries through various ODA projects, but the communication network is unstable, so there is a limit to the central control method alone. Therefore, in this study, an artificial intelligence-based flood prediction model was developed to develop an observation station that can observe water level and rainfall, and even predict and warn floods at once at one observation station. Training, validation and testing were carried out for 0.5, 1, 2, 3, and 6 hours of lead time using the rainfall and water level observation data in 10-minute units from 2009 to 2020 at Junjukbi-bridge station of Seolma stream. LSTM was applied to artificial intelligence algorithm. As a result of the study, it showed excellent results in model fit and error for all lead time. In the case of a short arrival time due to a small watershed and a large watershed slope such as Seolma stream, a lead time of 1 hour will show very good prediction results. In addition, it is expected that a longer lead time is possible depending on the size and slope of the watershed.

• Journal of Environmental Health Sciences
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• v.37 no.6
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• pp.418-428
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• 2011

Objectives: The purpose of this study was to examine the cross-sectional relationship between low blood lead levels and increasing blood pressure among Korean adults using a nationally representative sample of the Korean population: the Korea National Health and Nutrition Examination Survey (KNHANES) 2008. Methods: A total of 918 subjects aged 40 and older and not currently being treated for hypertension participated in this study. Information about age, gender, smoking status, alcohol consumption, education level, and the use of anti-hypertensive medication was collected. The blood pressure was defined as the mean of the second and the third measurements after three time measurements. Lead levels were determined by an analysis of blood samples. Multiple linear and logistic regression analyses were implemented after adjusting for covariates including age, gender, educational level, smoking status, alcohol consumption, and BMI. Results: This study showed that the average differences in systolic and diastolic blood pressure comparing the lowest to highest quintile of blood lead were 4.33 mmHg (95% CI, 0.66-8.00; p for trend = 0.027) and 2.66 mmHg (95% CI, 0.26-5.06; p for trend = 0.021), respectively. After multivariate adjustment for covariates, the prevalence odds ratio (POR) of subjects in the highest quintile was associated with a 1.70-fold increase in the risks of hypertension (95% CI, 0.83-3.49; p for trend test = 0.112) over those in the lowest quintile of blood lead concentration, However, it was not statistically significant. Conclusions: This study provided evidence for an association between low- levels of blood lead and elevations in blood pressure and risk for hypertension in the general population of Korea.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.4
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• pp.88-96
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• 1997

This paper suggests a new non-linear friction compensation for digital control systems. This control adopts a hysteresis nonlinear element which can introduce the phase lead of the control system to compensate the phase delay comes from the inherent time delay of a digital control. A proper Lyapunov function is selected and the Lyapunov direct method is used to prove the asymptotic stability of the suggested control.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.987-993
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• 1996

This report suggests a new non-linear friction compensation for digital control systems. This control adopts a hysteric nonlinear clement which can introduce the phase lead of the control system to compensate the phase delay comes from the inherent time delay of a digital control. The Lyapunov direct method is used to prove the asymtotic stability of the suggested control, and the stability and the effectiveness are verified analytically and experimentally on a single axis servo driving system.

• Water for future
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• v.28 no.5
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• pp.219-233
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• 1995

A non-stationary multivariate model is selected in which the mean and variance of rainfall are not temporally or spatially constant. And the rainfall prediction system is constructed which uses the recursive estimation algorithm, Kalman filter, to estimate system states and parameters of rainfall model simulataneously. The on-line, real-time, multivariate short-term, rainfall prediction for multi-stations and lead-times is carried out through the estimation of non-stationary mean and variance by the storm counter method, the normalized residual covariance and rainfall speed. The results of rainfall prediction system model agree with those generated by non-stationary multivariate model. The longer the lead time is, the larger the root mean square error becomes and the further the model efficiency decreases form 1. Thus, the accuracy of the rainfall prediction decreases as the lead time gets longer. Also it shows that the mean obtained by storm counter method constitutes the most significant part of the rainfall structure.

• Atmosphere
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• v.28 no.1
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• pp.15-24
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• 2018

Sea ice plays an important role in modulating surface conditions at high and mid-latitudes. It reacts rapidly to climate change, therefore, it is a good indicator for capturing these changes from the Arctic climate. While many models have been used to study the predictability of climate variables, their performance in predicting sea ice was not well assessed. This study examines the predictability of the Arctic sea ice extent from ensemble prediction systems. The analysis is focused on verification of predictability in each model compared to the observation and prediction in particular, on lead time in Sub-seasonal to Seasonal (S2S) scales. The S2S database now provides quasi-real time ensemble forecasts and hindcasts up to about 60 days from 11 centers: BoM, CMA, ECCC, ECMWF, HMCR, ISAC-CNR, JMA, KMA, Meteo France, NCEP and UKMO. For multi model comparison, only models coupled with sea ice model were selected. Predictability is quantified by the climatology, bias, trends and correlation skill score computed from hindcasts over the period 1999 to 2009. Most of models are able to reproduce characteristics of the sea ice, but they have bias with seasonal dependence and lead time. All models show decreasing sea ice extent trends with a maximum magnitude in warm season. The Arctic sea ice extent can be skillfully predicted up 6 weeks ahead in S2S scales. But trend-independent skill is small and statistically significant for lead time over 6 weeks only in summer.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.5
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• pp.694-702
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• 2014

One of the most important devices in an underwater vessel is a propulsion system. It should be a quiet and efficient system for stealthy operations in the large mission area. Hence lead-acid battery system has been used to supply the energy to electric motor. Recent technological developments and improvements, such as polymer electrolyte membrane(PEM) fuel cell and lithium polymer battery and have created the potential to improve overall power and propulsion performance. An underwater vessel always starts their mission with a limited energy and is not easy to refuel. Therefore design of energy elements, such as fuel cell and battery, and their load distribution are important to increase the maximum operating time of underwater vessel. In this paper, the lead-acid battery/PEM fuel cell and lithium polymer battery/PEM fuel cell were suggested as propulsion system and their performances were analyzed by modeling and simulation using Matlab/Simulink. Each model concentrated on representing the characteristics of energy element depending on demand current. As a result the effect of load distribution between battery and fuel cell was evaluated and the operation time of each propulsion system was able to be estimated exactly.

• Atmosphere
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• v.28 no.3
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• pp.291-303
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• 2018

In this study, a new consensus technique for predicting tropical cyclone (TC) intensity in the western North Pacific was developed. The most important feature of the present consensus model is to select and combine the guidance numerical models with the best performance in the previous years based on various evaluation criteria and averaging methods. Specifically, the performance of the guidance models was evaluated using both the mean absolute error and the correlation coefficient for each forecast lead time, and the number of the numerical models used for the consensus model was not fixed. In averaging multiple models, both simple and weighted methods are used. These approaches are important because that the performance of the available guidance models differs according to forecast lead time and is changing every year. In particular, this study develops both a multi-consensus model (M-CON), which constructs the best consensus models with the lowest error for each forecast lead time, and a single best consensus model (S-CON) having the lowest 72-hour cumulative mean error, through on training process. The evaluation results of the selected consensus models for the training and forecast periods reveal that the M-CON and S-CON outperform the individual best-performance guidance models. In particular, the M-CON showed the best overall performance, having advantages in the early stages of prediction. This study finally suggests that forecaster needs to use the latest evaluation results of the guidance models every year rather than rely on the well-known accuracy of models for a long time to reduce prediction error.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.225-231
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• 2002

POSCO $\#2$ Stainless steel making plant produces more than 600 thousand ton per year with a variety of products consisting of austenite and ferrite stainless steel to meet custrmers' needs since 1996. The plant has four different major processes, that are, EAF-AOD-VOD-CC to finally produce semi-product called as slab. In this study, we importantly took AOD process into consideration due to its roles such as to check and verify the final qualities through sampling inspection. But the lead-time from sampling to its verification takes five to ten minutes causing produrtivity loss as muck as the lead-time as a result. Of all indices for quality and process control the plant has, carbon ingredient in liquid type of steel is the most important since it affects in a great way to the characteristics of steel, if any problem. customers not satisfied with quality could issue a claim; therefore there is no way hut to guarantee it before delivery. in this study, to reasonably reduce lead-time ran save a cycle time and finally improve our productivity from a state-or-art alternative just such as applying statistical model based on multi-regression analysis into the A.O.D line by analyzing the statistical and technical relationship between carbon and the relevant some vital independent variables. In consequence, the model with R-square $87\%$ allowed the plant to predict, abbreviating the process in relations to sampling to verification. approximately the value of [C] so that operators could run the process line with reliability on data automatically calculated instead of actual inspection. In the future, we are going to do the best to share this type of methodology with other processes, if possible, to apply into them.

• The Korean Journal of Emergency Medical Services
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• v.9 no.1
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• pp.79-87
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• 2005

Purpose: Investigates the results of CPR operation in visited patients with arrest state, and element to affect the results, and it is checks a problem, and it is made to promote. Methods: As for this study, analysis studied the results that operation CPR with the object arrest patients of 69 visited Jecheon Seoul hospital emergency center for during the period from January 2002 to February 2005. It was played writing partly changed In-hospital Utstein Style, and to stick a record in it. Paramedic which participated in CPR directly did the record of a variable, As for the data processing, use SPSS Version 12.0 for Windows. Results: It was male 68.1% female 31.9% for 69 people, and the sex ratio didn't affect return of spontaneous circulation, with female 8 people to male 16 people for ROSC(Return of spontaneous circulation) 24 people. with female 14 people to male 31 people for NROSC(Non-return of spontaneous circulation) 45 people(p>0.05). The initial EKG rhythm was asystole 34.8%, VF 31.9%, The case that initial EKG was VF compared it to a patient of asystole, and a survivor had a lot of VF and there were a lot of survivors(p<0.05). The wasn't relativity between VF and PEA(p>0.05), The CPR lead time was short in ROSC with NROSC $25.0{\pm}15.0$ minutes, ROSC $11.9{\pm}10.7$ minutes(p<0.01). Epinephrine administer time was NROSC $3.0{\pm}4.1$ minutes, ROSC $2.1{\pm}1.9$ minutes(p>0.05). It was survivor 18 people(21.1%) than 24 hours and the PAM Index affected in ROSC. with $9.0{\pm}1.2$ points NROSC, with $1.6{\pm}1.7$ points ROSC(p<0.01). A correlation was high between a CPR lead time and PAM Index(p<0.02), a correlation was examined by being high between ROSC and a CPR lead time, PAM Index(p<0.01).