• Journal of Families and Better Life
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• v.22 no.6 s.72
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• pp.233-242
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• 2004

The main objective of this study is to provide baseline data and materials to be used for developing an manners education program. Such an educational program will help enhance the manners of university students. A stratified random sampling method was applied to collect data. Originally, 800 questionnaires were distributed to university students during the period between May 10 and May 31, 2m, and of the completed questionnaires, 7n3 were used for data analysis. 'The following findings were obtained:1. University students 'level of everyday manners was shown to be moderate, and the mean score was 6.76 (67.61/100 Points). 2. The level of demands for everyday manners education was shown to be high and the mean score was 8.05 (67.61/100 Points). 3. The variable that had the greatest impact on the level of everyday manners was the subjective knowledge about everyday manners, whereas gender affected the demand for education the most strongly.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.421-423
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• 2001

Restructuring of electricity industry is going on for the purpose of introducing competition and after separation of generation and retail business and introduction of competition, substantial change is expected in overall electric power system. In other words, DSM projects are divided with public projects and private projects. Particularly for public project, it is essential to evaluate the DSM volumes by program. This paper tries to derive the ways for achieving the necessary DSM goal in the electricity industry in Korea. First of all, by analyzing the load in Korea, we forecast the standard demand and estimate the technological potentials of each program in considering DSM technological indicators. Moreover, by using economic analysis by program, we estimate economic potentials and finally, we estimate the potentials by program in considering the DSM policy. We estimate the potentials by using random method because application methodology and procedures by program are not established until now, which leads to not obtaining transparency for implementation effect by program. Therefore, this paper estimates the future potentials of DSM projects by using the logical and systematic analytic method and establishing database for DSM basic indicator. The DSM goals estimated by this method will be reflected to mid/long term nation-wide resource planning, which will mitigate anticipated power supply shortage and be applied to derive desirable energy demand/supply structure.

• Journal of the Earthquake Engineering Society of Korea
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• v.13 no.4
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• pp.37-45
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• 2009

The identification of significant structural components under seismic loading through a probabilistic approach is of interest to many structural engineers. The First-Order Second Moment method can be used to achieve this goal by estimating uncertainty in the seismic demand of a structural system induced by the capacity uncertainties of each structural component. Significant structural components are those to which the seismic demand of the structure is more sensitive than it is to other ones. The developed procedure demonstrated by a ductile reinforced concrete frame shows that it is computationally effective and robust in terms of identifying significant structural components.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.4
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• pp.1-20
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• 2021

Due to the recent rapid increase in passenger and cargo air transport demand, the capacity of Jeju International Airport has been approaching its limit. Even though in COVID-19 crisis which has started from Nov 2019, Jeju International Airport still suffers from strong demand in terms of air passenger and cargo transportation. However, it is an undeniable fact that the delay has also increased in Jeju International Airport. In this study, we analyze the correlation between weather and delayed departure operation based on both datum collected from the historical airline operation information and aviation weather statistics of Jeju International Airport. Adopting machine learning techniques, we then analyze weather condition Jeju International Airport and construct a delay prediction model. The model presented in this study is expected to play a useful role to predict aircraft departure delay and contribute to enhance aircraft operation efficiency and punctuality in the Jeju International Airport.

• International Commerce and Information Review
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• v.14 no.3
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• pp.31-47
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• 2012

The Eurozone was launched to set a goal on using the single currency perfectly in 1999. Using the Euro could get rid of exchange cost and cost of Foreign exchange risk management which was approximately 1% of each member's GDP. It was possible that members has maintained a stable level of inflation and stimulate investment and employment with low interest rate. In addition, they could lead to economic growth and investment as well as increase the Euro demand in financial market. Especially, members has used the Euro as the method of payment on trade each other so that the volume of trade among the Eurozone members has increased continuously which was called "the effect of single market." This paper analyzes the correlation between using the Euro and members' export/import by using random effect estimation and fixed effect estimation. As a result, Eurozone members can get export decreasing effect of 4.68% and import increasing effect of 10.5% respectively on average by using the Euro.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.15 no.3
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• pp.77-81
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• 2009

There has been an increasing demand on measurement of the vibration levels in commercial truck shipments, where all packaged products are exposed to some levels of random vibration and shock. In this study, bear glass bottles loaded at the front, middle, and rear positions of 11 tonne truck bed was shipped from Kwangju to Waegouan. Vertical direction vibration levels were analysed and matching laboratory random vibration test was performed using power spectral density (PSD) profiles derived from truck transit records. Also, the effects of drop hight on glass bottles were evaluated. As expected, the maximum vibration levels were recorded at the rear of truck bed. No breakage of bottles were observed during truck transit and laboratory random vibration testing set at 0.52 $G_{rms}$. In drop test, glass bottles were not damaged by bottom side impact, while short side drop impact caused about twice higher bottle breakage rate than that of long side drop impact at 30 cm and 40 cm drop hight.

• Journal of the Society of Naval Architects of Korea
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• v.57 no.2
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• pp.80-87
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• 2020

As the Arctic sea ice decreases due to various reasons such as global warming, the demand for ships and offshore structures operating in the Arctic region is steadily increasing. In the case of sea ice, the anisotropy is caused by the uncertainty inside the material. For most of the research, nevertheless, estimating the ice load has been treated deterministically. With regard to this, in this paper, a four-point bending strength analysis of an ice specimen was attempted using a stochastic finite element method. First, spatial distribution of the material properties used in the yield criterion was assumed to be a multivariate Gaussian random field. After that, a direct method, which is a sort of stochastic finite element method, and a sensitivity method using the sensitivity of response for random variables were proposed for calculating the probabilistic distribution of ice specimen strength. A parametric study was conducted with different mean vectors and correlation lengths for each material property used in the above procedure. The calculation time was about ten seconds for the direct method and about three minutes for the sensitivity methods. As the cohesion and correlation length increased, the mean value of the critical load and the standard deviation increased. On the contrary, they decreased as the friction angle increased. Also, in all cases, the direct and sensitivity methods yielded very similar results.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.426-426
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• 1999

;There are many sources of uncertainty in a typical production and inventory system. There is uncertainty as to how many items customers will demand during the next day, week, month, or year. There is uncertainty about delivery times of the product. Uncertainty exacts a toll from management in a variety of ways. A spurt in a demand or a delay in production may lead to stockouts, with the potential for lost revenue and customer dissatisfaction. Firms typically hold inventory to provide protection against uncertainty. A cushion of inventory on hand allows management to face unexpected demands or delays in delivery with a reduced chance of incurring a stockout. The proposed strategies are used for the design of a probabilistic inventory system. In the traditional approach to the design of an inventory system, the goal is to find the best setting of various inventory control policy parameters such as the re-order level, review period, order quantity, etc. which would minimize the total inventory cost. The goals of the analysis need to be defined, so that robustness becomes an important design criterion. Moreover, one has to conceptualize and identify appropriate noise variables. There are two main goals for the inventory policy design. One is to minimize the average inventory cost and the stockouts. The other is to the variability for the average inventory cost and the stockouts The total average inventory cost is the sum of three components: the ordering cost, the holding cost, and the shortage costs. The shortage costs include the cost of the lost sales, cost of loss of goodwill, cost of customer dissatisfaction, etc. The noise factors for this design problem are identified to be: the mean demand rate and the mean lead time. Both the demand and the lead time are assumed to be normal random variables. Thus robustness for this inventory system is interpreted as insensitivity of the average inventory cost and the stockout to uncontrollable fluctuations in the mean demand rate and mean lead time. To make this inventory system for robustness, the concept of utility theory will be used. Utility theory is an analytical method for making a decision concerning an action to take, given a set of multiple criteria upon which the decision is to be based. Utility theory is appropriate for design having different scale such as demand rate and lead time since utility theory represents different scale across decision making attributes with zero to one ranks, higher preference modeled with a higher rank. Using utility theory, three design strategies, such as distance strategy, response strategy, and priority-based strategy. for the robust inventory system will be developed.loped.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.723-734
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• 2021

Wind energy is one of the rapidly developing renewable energies which is being developed and invested in response to climate change. As renewable energy policies and power plant installations are promoted, the supply of wind power in Korea is gradually expanding and attempts to accurately predict demand are expanding. In this paper, the ARIMA and ARIMAX models which are Time series techniques and the SVR, Random Forest and XGBoost models which are machine learning models were compared and analyzed to predict wind power generation in the Jeonnam and Gyeongbuk regions. Mean absolute error (MAE) and mean absolute percentage error (MAPE) were used as indicators to compare the predicted results of the model. After subtracting the hourly raw data from January 1, 2018 to October 24, 2020, the model was trained to predict wind power generation for 168 hours from October 25, 2020 to October 31, 2020. As a result of comparing the predictive power of the models, the Random Forest and XGBoost models showed the best performance in the order of Jeonnam and Gyeongbuk. In future research, we will try not only machine learning models but also forecasting wind power generation based on data mining techniques that have been actively researched recently.

• The Journal of the Korea Contents Association
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• v.13 no.7
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• pp.361-368
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• 2013

This research aims to offer the information required for demand increase on marketing strategy level by investigating Mudeungsan visitors' demographic characteristics and social economical variables. To accomplish this study, the proper analyzing model needs to be applied because a grave error of parameters will be led if regression model appropriate for analyzing the data of a continuous probability variable is applied, in case that dependent variable is a discrete random variable which have a discrete probability distribution. Therefore data analysis was performed with Poisson model. However, as the data was showing an overdispersion, parameter was estimated with the Binomial Poisson model able to cover the problem. As a result, some explanatory variables turned out to be significant such as visitor's age, occupation, preferred season to visit, type of company, five days working, and preferring type of tourism. Author could offer to the national park the information about characteristics of core market revealed and marketing strategy for it, based on those influential variables.