• Korean Journal of Human Ecology
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• v.21 no.2
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• pp.349-362
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• 2012

This paper explores differences demonstrated by changes of consumers' clothing expenditure in Korea and the United States since the mid-1990s. Evidence for this study was extrapolated from annual data provided by the Household Expenditure Survey, which was carried out in Korea between 1996 and 2008, and the Consumer Expenditure Survey, which was carried out in the United States during the same time period. The results include: (1) The proportion of the clothing expenditure decreased during the subject period in both Korea and the United States; (2) The decrease in proportional clothing expenditure was greater in Korea than in the United States; (3) Although the relative prices of clothes decreased greatly during this period in both countries, it was determined that the decrease in clothing prices in the United States was greater when compared to those in Korea; and (4) By using the DID(Difference in difference) model, the author contends that a decrease in clothing purchases contributed to the decrease of prices for clothing in the United States, while in Korea, the decrease in prices for clothing was also impacted by other factors including changes in household expenditures for education and communication.

• The Journal of Fisheries Business Administration
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• v.39 no.2
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• pp.61-79
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• 2008

The objectives of this paper are to identify the causes of the corporate distress and to develop a distress prediction model with the financial information in fishery industry. In this study, the corporate distress is defined as economic failure and technical insolvency. Economic failure occurs by reduction, shut - down, or change of the business and technical insolvency results from failure to pay the financial debt of companies. The 33 distressed firms from 1991 to 2003 were composed by 14 economic failure companies, 15 technical insolvency companies. 4 companies applied to the both cases. The analysis of distress prediction of fishery companies were accomplished according to the distress definition. The analysis was carried out as two steps. The first step was the univariate analysis, which was used for checking the prediction power of individual financial variable. The t - test is used to identify the differences in financial variables between the distressed group and the non - distressed group. The second step was to develop distress prediction model with logistic regression. The variables showed the significant difference in univariate analysis were selected as the prediction variables. The financial ratios, used in the logistic regression model, were selected by backward elimination method. To test stability of the distress prediction model, the whole sample was divided as three sub-samples, period 1(1990 - 1993), period 2(1994 - 1997), period 3(1998 - 2002). The final model built from whole sample appled each three sub - samples. The results of the logistic analysis were as follows. the growth, profitability, stability ratios showed the significant effect on the distress. the some different result was found in the sub - sample (economic failure and technical insolvency). The growth and the profitability were important to predict the economic failure. The profitability and the activity were important to predict technical insolvency. It means that profitability is the really important factor to the fishery companies.

• Wind and Structures
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• v.39 no.2
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• pp.85-100
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• 2024

In light of extreme value distribution probability, an improved prediction method of the Recurrence Period Wind Speed (RPWS) is constructed considering wind direction, with the Equivalent Independent Wind Direction Number (EIWDN) introduced as a parameter variable. Firstly, taking the RPWS prediction of Beijing city as an example, the traditional Cook method is used to predict the RPWS of each wind direction based on the measured wind speed data in Beijing area. On basis of the results, the empirical formulae to determine the parameter variables are fitted to construct an improved expression of the non-exceedance probability of the RPWS. In this process, the statistical model of the optimal threshold is established, and thus the independent wind speed samples exceeding the threshold are extracted and fitted to follow the Generalized Pareto Distribution (GPD) model for analysis. In addition, the Extreme Value Type I (EVT I) distribution model is used to predict and analyze the RPWS. To verify its wide applicability, the improved method is further used in cities like Jinan, Nanjing, Wuxi, Shanghai and Shenzhen to predict and analyze the RPWS of each wind direction, and the prediction results are compared against those gained via the traditional Cook method and the whole direction. Results show that the 50-year RPWS results predicted by the improved method are basically consistent with those predicted by the traditional method, and the RPWS prediction values of most wind directions are within the envelope range of the whole wind direction prediction value. Compared with the traditional method, the improved method can readily predict the RPWS under different return periods through empirical formulae, and avoid the repeated operation process and some assumptions in the traditional Cook method, and then improve the efficiency of prediction. In addition, the improved RPWS prediction results corresponding to the GPD model are slightly larger than those of the EVT I distribution model.

• Journal of the Korean Operations Research and Management Science Society
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• v.12 no.2
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• pp.5-20
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• 1987

This paper addresses sensitivity analysis for a deterministic multi-period production and inventory model. The model assumes a piecewise linear cost structure, but permits backlogging of unsatisfied demand. Our approach to sensitivity analysis here can be divided into two basic steps; (1) to find the optimal production policy through a forward dynamic programming algorithm similar to the backward version of Zangwill [1966] and (2) to apply the penalty network approach by the author [1986] in order to derive sensitivity ranges for various model parameters. Computational aspects are discussed and topics of further research are suggested.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.2
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• pp.1-17
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• 2015

In this paper, we propose a portfolio selection model utilizing a Markov chain for investing in the foreign exchange market based on market forecasts and exchange rate movement predictions. The proposed model is utilized to compute optimum investment portfolio weights for investing in margin-based markets such as the FX margin market. We further present an objective investment algorithm for applying the proposed model in real-life investments. Empirical performance of the proposed model and investment algorithm is evaluated by conducting an experiment in the FX market consisting of the 7 most traded currency pairs, for a period of 9 years, from the beginning of 2005 to the end of 2013. We compare performance with 1) the Dollar Index, 2) a 1/N Portfolio that invests the equal amount in the N target assets, and 3) the Barclay BTOP FX Index. Performance is compared in terms of cumulated returns and Sharpe ratios. The results suggest that the proposed model outperforms all benchmarks during the period of our experiment, for both performance measures. Even when compared in terms of pre- and post-financial crisis, the proposed model outperformed all other benchmarks, showing that the model based on objective data and mathematical optimization achieves superior performance empirically.

• Korean Journal of Ecology and Environment
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• v.41 no.4
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• pp.472-484
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• 2008

The calibrated Andong Reservoir hydro-dynamic module (PART I) of the 2-dimensional hydrodynamic and water quality model, CE-QUAL-W2 [v3.2], was applied to examine the dynamics of total phosphorus, and chlorophyll $\alpha$ concentration within Andong Reservoir. The modeling effort was supported with the data collected in the field for a five year period. In general, the model achieved a good accuracy throughout the calibration period for both chlorophyll ${\alpha}$ and total phosphorus concentration. The greatest deviation in algal concentration occurred on $10^{th}$ October, starting at the layer just beneath the surface layer and extending up to the depth of 35 m. This deviation is principally attributed to the effect of temperature on the algal growth rate. Also, on the same date, the model over-predicts hypolimnion and epilimnion total phosphorus concentration but under-predicts the high concentrated plume in the metalimnion. The large amount of upwelling of finer suspended solid particles, and re-suspension of the sediments laden with phosphorus, are thought to have caused high concentration in the epilimnion and hypolimnion, respectively. Nevertheless, the model well reproduced the seasonal dynamics of both chlorophyll a and total phosphorus concentration. Also, the model tracked the interflow of high phosphorus concentration plume brought by the turbid discharge during the Asian summer monsoon season. Two different hypothetical discharge scenarios (discharge from epilimnetic, and hypolimnetic layers) were analyzed to understand the response of total phosphorus interflow plume on the basis of differential discharge gate location. The simulated results showed that the hypolimnetic discharge gate operation ($103{\sim}113\;m$) was the most effective reservoir structural control method in quickly discharging the total phosphorus plume (decrease of in-reservoir concentration by 219% than present level).

• 한국해양학회지
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• v.21 no.4
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• pp.245-258
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• 1986

A two-dimensional numerical model is developed to investigate the phenomenon of forced seiche caused by the incident long waves. This model is applied to Young-il Bay and Pohang New Harbor, where the seiche is most frequently observed and the damage of the seiche is serious compared with the other harbors in Korea. Some results on this study are as follows; 1. The natural periods of the first two modes obtained from the present model are about 70 and 25 minutes respectively for Young-il Bay, and about 25 and 7.5 minutes for Pohang New Harbor. These results are well consistent with those obtained by the theoretical formula, the spectral analysis, and the statistical investigation of the recorded data. 2. Since the fundamental natural period of Pohang New Harbor is almost the same as the second natural period of Young-il Bay, the seiche in Pohang New Harbor can be strongly amplified by the Oscillation in Young-il Bay. Therefore, the most strong seiche in Pohang New Harbor can occur when the long wave of about 25-minute period come into Young-il Bay.

• 전기의세계
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• v.26 no.2
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• pp.66-71
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• 1977

A mathematical model, which can be used for the study of an influenza epidemic, was derived. The model of influenza takes into full consideration the incubation period and inapparent infection. That was analysed by means of digital computer under the conditions of changing the infection rate, .betha., from 4 to 5, for three types of communities (First type: the initial distribution of population, x$_{1}$(0)=89% susceptibles, x$_{2}$(0)=3% incubatives, x$_{3}$(0)=0.5% carriers, x$_{4}$(0)=7.5% immunes; Second type: x$_{1}$(0)=79%, x$_{2}$(0)=3%, x$_{3}$(0)=0.5%, x$_{4}$(0)=17.5%; Third type: x$_{1}$(0)=69%, x$_{2}$(0)=3%, x$_{3}$(0)=0.5%, x$_{4}$(0)=27.5%, considering the rate of population increase, in Seoul. In conclusion, the outcomes of this study are summarized as follow. 1) The new model is quite reasonable in representing many phenomena connected with influenza spread. 2) The more influenza does prevail, the smaller the valve of attack rate becomes, while the contagious period becomes slightly longer. 3) The average infection rate, .betha., of influenza is approximately 5 per week time and X$_{4}$(0) is about 27.5 percent of the total population in Seoul spring 1961. 4) The number of carriers of influenza in Seoul spring 1961 becomes maximum within approximately 2.4 weeks after the attack of diseases. 5) About 68 percent of all cases in the contagious period is infected with influenza from 5 to 15 days after the attack of diseases. The auther believes that the method to study the influenza models in this paper will be helpful to study the characteristics of other epidemics. It will also contribute to public healthe management and the preventive policy decision against epidemics.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.6
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• pp.811-815
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• 2006

The objective of this study was to evaluate the effect of electric fan installation for milk production improvement of dairy cattle in Thailand. The study was conducted using 2 small-holder dairy farms in Chiang Mai province, during April to August 2004. Electric fans were installed in front of each row of cows. Each of the two rows of cows in the barn was defined as an experimental unit, thus each farm had two experimental units. The fans were operated alternately in 7-day intervals between rows of cows within each farm during the day or between 8.00 am to 8.00 pm. Non-operation periods were used as control. Milk yields were recorded. Data on environmental temperature and humidity were obtained from Chiang Mai Meteorological Center. Result from statistically analysis of milk record suggested an interaction between lactation period and fan installation. Therefore, this interaction term of lactation period and fan installation (PERIOD_FAN) was added as a variable to the regression model. Due to the repeated data collection of milk yield from the same cow (alternate week), milk yield was analyzed by repeated measure analysis (Mixed model). Least square means were calculated for all levels and used to compare between each pair-wise values. The final data were collected from the total of 18 cows with 2,072 data. Overall means and SEM of milk yields and days in milk separated into farm were $14.7{\pm}0.06kg/day$ and $176.3{\pm}2.2days$, and $15.2{\pm}0.22kg/day$ and $202.5{\pm}3.7$ days for farm A and farm B, respectively. For multivariable analysis, only PERIOD_FAN and humidity were significantly associated with milk yield. Only the first period of lactation showed that the amount of milk yields during fan installation was higher than that of non-fan installation (p<0.05). Cows with fan installation produced approximately 1.2 kg/cow more milk than cows without fan installation during this period. In conclusion, the use of electric fan operated during the day time increased milk production of cows during the first period of lactation.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.297-307
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• 2017

The epidemic model is used to model the spread of disease and to control the disease. In this research, we utilize SEIR model which is one of applications the SIR model that incorporates Exposed step to the model. The SEIR model assumes that a people in the susceptible contacted infected moves to the exposed period. After staying in the period, the infectee tends to sequentially proceed to the status of infected, recovered, and removed. This type of infection can be used for research in cases where there is a latency period after infectious disease. In this research, we collected respiratory infectious disease data for the Middle East Respiratory Syndrome Coronavirus (MERSCoV). Assuming that the spread of disease follows a stochastic process rather than a deterministic one, we utilized the Poisson process for the variation of infection and applied epidemic model to the stochastic chemical reaction model. Using observed pandemic data, we estimated three parameters in the SIER model; exposed rate, transmission rate, and recovery rate. After estimating the model, we applied the fitted model to the explanation of spread disease. Additionally, we include a process for generating the Exposed trajectory during the model estimation process due to the lack of the information of exact trajectory of Exposed.