• Computers and Concrete
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• v.29 no.3
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• pp.145-159
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• 2022

In this study, the extreme learning machine and deep learning models were devised to estimate the bond strength of corroded reinforcement in concrete. The six inputs and one output were used in this study. The compressive strength, concrete cover, bond length, steel type, diameter of steel bar, and corrosion level were selected as the input variables. The results of bond strength were used as the output variable. Moreover, the Analysis of variance (Anova) was used to find the effect of input variables on the bond strength of corroded reinforcement in concrete. The prediction results were compared to the experimental results and each other. The extreme learning machine and the deep learning models estimated the bond strength by 99.81% and 99.99% accuracy, respectively. This study found that the deep learning model can be estimated the bond strength of corroded reinforcement with higher accuracy than the extreme learning machine model. The Anova results found that the corrosion level was found to be the input variable that most affects the bond strength of corroded reinforcement in concrete.

• Journal of Korea Water Resources Association
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• v.46 no.11
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• pp.1089-1101
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• 2013

The study uses a regional climate model to check future changes in extreme climate, to calculate extreme indexes presented by STARDEX, and to analyze the trends to predict the continuity and changes in the spatial distribution of extreme climate in the future. An analysis of extreme climate indices showed that they are likely to increase in the Seoul metropolitan area, in Gyeonggi-do, in Yongdong in Gangwon-do, and in the southern shore region of Korea. It is, however, forecasted to diminish in the central inland region. The analysis also showed that the average temperature in Korea will increase because of climate change. On the other hand, an analysis of extreme rainfall indexes showed that the trend of heavy rainfall threshold is 0.229 in Seogwipo, the greatest five-day rainfall is 5.692 in Seogwipo, and the longest dry period is 0.099 in Sokcho. Of extreme temperature indexes, the trend of Hotdays threshold is 0.777 in Incheon and the longest heat wave is 0.162 in Uljin. The Coldnight threshold is 0.075 in Inje and -0.193 in Tongyeong, according to the analysis.

• Journal of the Ergonomics Society of Korea
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• v.27 no.3
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• pp.53-60
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• 2008

The work-related musculoskeletal disorders have constantly increased since it became an issue in 1996. In 2002, the Government established the risk factors analysis system in order to prevent musculoskeletal disorders. The proclamation by the Ministry of Labor defined eleven spheres of work associated with musculoskeletal disorders. As a result, business proprietors, who have workers engaged in tasks associated with musculoskeletal disorders, are required to conduct the risk factor analysis on a regular basis every three years. However, numerous issues have been raised while carrying out the risk factor analysis in various industries. One of the issues is that even though work sampling is an ideal method in risk factor analysis, most cases have selected extreme task postures, which is judged by an expert, due to limited time. This study will propose the desired direction of the risk factor analysis by comparing task assessment results between work sampling scenes and extreme task scenes.

• Journal of the Korean Geographical Society
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• v.47 no.3
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• pp.459-470
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• 2012

This study attempts to estimate the economic effects of extreme climate events on agriculture with the case of Gangwon-do, drawing upon the Ricardian approach based upon the panel data on extreme climate events, soil and geography, farmland prices, and economic and social variables for the 11 municipal units of Gangwon-do during the period of 1993-2010. Our empirical analysis shows that the heavy rainfall-related extreme climate variable negatively affects the prices of rice paddy and dry farm field. The summer-related extreme temperature variables have negative economic impacts on the land values of both farmlands, while the winter-related ones positively affect them except for the extreme cold wave variable.

• Journal of the Korean earth science society
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• v.44 no.4
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• pp.255-263
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• 2023

Western coastal area of Chungnam, including Cheonsu Bay and Garorim Bay, has suffered from hot and cold extremes. In this study, the extreme sea surface temperature on the western coast of Chungnam was analyzed using the quantile regression method, which extracts the linear regression values in all quantiles. The regional MOHID (MOdelo HIDrodinâmico) model, with a high resolution on a 1/60° grid, was constructed to reproduce the extreme sea surface temperature. For future prediction, the SSP5-8.5 scenario data of the CMIP6 model were used to simulate sea surface temperature variability. Results showed that the extreme sea surface temperature of Cheonsu Bay in August 2017 was successfully simulated, and this extreme sea surface temperature had a significant negative correlation with the Pacific decadal variability index. As a result of future climate prediction, it was found that an average of 2.9℃ increased during the simulation period of 86 years in the Chungnam west coast and there was a seasonal difference (3.2℃ in summer, 2.4℃ in winter). These seasonal differences indicate an increase in the annual temperature range, suggesting that extreme events may occur more frequently in the future.

• Journal of Power System Engineering
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• v.19 no.6
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• pp.5-11
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• 2015

The 6DOF (degrees of freedom) Parallel Manipulators have some advantages that are high power, high rigidity, high precision for positioning and compact mechanism compared with conventional serial link manipulators. For these Parallel Manipulators, it can be expected to work in the new fields such that the medical operation, high-precision processing technology and so on. For this expectation, it is necessary to control the action reaction pair of forces which act between the Parallel Manipulator and the operated object. In this paper, we analyze the dynamics of the 6DOF Parallel Manipulator and present numerical simulation results.

• International Journal of Naval Architecture and Ocean Engineering
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• v.5 no.2
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• pp.179-187
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• 2013

Floating production storage and offloading (FPSO) facilities are used at most of the offshore oil fields worldwide. FPSO usage is expected to grow as oil fields move to deeper water, thus requiring the reliability and stability of mooring wires and risers in extreme environmental conditions. Except for the case of predictable attack angles of external loadings, FPSO facilities with turret single point mooring (SPM) systems are in general use. There are two types of turret systems: permanent systems and disconnectable turret mooring systems. Extreme environment criteria for permanent moorings are usually based on a 100-year return period event. It is common to use two or three environments including the 100-year wave with associated wind and current, and the 100-year wind with associated waves and current. When fitted with a disconnectable turret mooring system, FPSOs can be used in areas where it is desirable to remove the production unit from the field temporarily to prevent exposure to extreme events such as cyclones or large icebergs. Static and dynamic mooring analyses were performed to evaluate the stability of a spider buoy after disconnection from a turret during cyclone environmental conditions.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.537-537
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• 2015

In recent decades, the independence and identical distribution (iid) assumption for extreme events has been shown to be invalid in many cases because long-term climate variability resulting from phenomena such as the Pacific decadal variability and El Nino-Southern Oscillation may induce varying meteorological systems such as persistent wet years and dry years. Therefore, in the current study we propose a new parameter estimation method for probability distribution models to more accurately predict the magnitude of future extreme events when the iid assumption of probability distributions for large-scale climate variability is not adequate. The proposed parameter estimation is based on a metaheuristic approach and is derived from the objective function of the rth power probability-weighted sum of observations in increasing order. The combination of two distributions, gamma and generalized extreme value (GEV), was fitted to the GEV distribution in a simulation study. In addition, a case study examining the annual hourly maximum precipitation of all stations in South Korea was performed to evaluate the performance of the proposed approach. The results of the simulation study and case study indicate that the proposed metaheuristic parameter estimation method is an effective alternative for accurately selecting the rth power when the iid assumption of extreme hydrometeorological events is not valid for large-scale climate variability. The maximum likelihood estimate is more accurate with a low mixing probability, and the probability-weighted moment method is a moderately effective option.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.3
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• pp.97-110
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• 2022

The case study looks into the case of the "extreme" market segmentation strategy of company L with its top luxury windows and door brand "Lonchel". Company L has long enjoyed a leading position in the Korean windows and doors mass market. However, it went against their already well-established flagship brand and created a completely new one called "Lonchel", pursuing an extreme market segmentation strategy focusing on the small niche market of highest-income customers exclusively. The strategy has turned out to be successful and the company has gained long-lasting competitive advantages. In this vein this study analyzes the market environment in which the top-tier brand "Lonchel" appeared, the concept of the extreme positioning and the smallest viable market, the characteristics of target customers, the company's analysis of and response to them, and the analysis of products to meet their needs. The brand operation plan and promotion will be also reviewed. Through this, we intend to draw implications related to the extreme positioning strategy that a company may pursue in a target market of small groups of people.

• Journal of Korea Water Resources Association
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• v.43 no.4
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• pp.337-351
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• 2010

There is a growing dissatisfaction with use of conventional statistical methods for the prediction of extreme events. Conventional methodology for modeling extreme event consists of adopting an asymptotic model to describe stochastic variation. However asymptotically motivated models remain the centerpiece of our modeling strategy, since without such an asymptotic basis, models have no rational for extrapolation beyond the level of observed data. Also, this asymptotic models ignored or overestimate the uncertainty and finally decrease the reliability of uncertainty. Therefore this article provide the research example of the extreme rainfall event and the methodology to reduce the uncertainty. In this study, the Bayesian MCMC (Bayesian Markov Chain Monte Carlo) and the MLE (Maximum Likelihood Estimation) methods using a quadratic approximation are applied to perform the at-site rainfall frequency analysis. Especially, the GEV distribution and Gumbel distribution which frequently used distribution in the fields of rainfall frequency distribution are used and compared. Also, the results of two distribution are analyzed and compared in the aspect of uncertainty.