• Journal of Korean Institute of Industrial Engineers
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• v.35 no.3
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• pp.203-212
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• 2009

The bullwhip effect refers to the phenomenon where demand variability is amplified when one moves upward a supply chain. In this paper, we exactly quantify the bullwhip effect for cases of seasonal demand processes in a two-echelon supply chain with a single retailer and a single supplier. In most of the previous research, some measures of performance for the bullwhip effect are developed for cases of non-seasonal demand processes. The retailer performs demand forecast with a multiplicative seasonal mixed model by using the minimum mean square error forecasting technique and employs a base stock policy. With the developed bullwhip effect measure, we investigate the impact of seasonal factor on the bullwhip effect. Then, we prove that seasonal factor plays an important role on the occurrence of the bullwhip effect.

• Journal of Navigation and Port Research
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• v.31 no.9
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• pp.793-799
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• 2007

The effect of seasonal wind on the tidal circulation in Jeju harbor was examined by using a numerical shallow water model. A finite element for analyzing shallow water flow is presented. The Galerkin method is employed for spatial discretization. Two step explicit finite element scheme is used to discretize the time function, which has advantage in problems treating large numbers of elements and unsteady state. The numerical simulation is compared with three cases; Case 1 does not consider the effect of wind, Case 2 and Case 3 consider the effect of summer and winter seasonal wind, respectively. According to result considering effect of seasonal wind, velocity of current vector shows slightly stronger than that of case 1 in the flow field. It can be concluded that the present method is a useful and effective tool in tidal current analysis.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.4
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• pp.91-112
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• 2009

The bullwhip effect means the phenomenon of increasing demand variation as moving UP to the upstream in the supply chain. Therefore, it is recognized that the bullwhip effect is problematic for effective supply chain operations. In this paper, we exactly quantifies the bullwhip effect for the case of stochastic lead time and seasonal demand in two-echelon supply chain where retailer employs a base-stock policy considering SARMA demand processes and stochastic lead time. We also investigate the behavior of the proposed measurement for the bullwhip effect with autoregressive and moving average coefficient, stochastic lead time, and seasonal factor.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.326-326
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• 2018

The study will assess the seasonal effect of hydrological models on performance and parameters for streamflow simulation. TPHM, GR4J, CAT, and TANK-SM hydrological models will be applied for simulating streamflow in ten small and large watersheds located in South Korea. The readily available hydrometeorological data will be applied as an input to the four hydrological models and the potential evapotranspiration will be computed using the Penman-Monteith equation. The SCE-UA algorithm implemented in PEST will be used to calibrate the models considering similar objective functions bedside the calibration will be renewed to capture the seasonal effects on the model performance and parameters. The seasonal effects on the model performance and parameters will be presented after assessing the four hydrologic models results. The conventional approach and season-based results will be evaluated for each model in the tested watersheds and a conclusion will be made based on the finding of the results.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.10 no.2
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• pp.173-179
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• 1998

An experimental study was conducted on the effect of compressor capacity control range of heat pump on the seasonal energy efficiency ratio with variation of the maximum and minimum compressor input frequencies. To obtain seasonal energy efficiency ratio, steady state test at the maximum, minimum and intermediate compressor speed and cyclic test at the minimum compressor speed should be conducted. Maximum input frequency was varied to 95Hz, 105Hz, and 115Hz, and the minimum input frequency was varied to 35Hz, 45Hz, and 55Hz. The seasonal energy efficiency ratio increased as the input frequency of the compressor decreased. The maximum input frequency had only slight effects on the SEER.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.513-523
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• 2000

The X-12-ARIMA program was utilized on the analysis of the time series trend on 76 Korean industrial activities data in order to ensure that the trading day effect adjustment as well as the seasonal effect adjustment is needed to extract the fundamental trend-cycle factors from various economic time series data. The trading day effect is strongly correlated with the activity of production and shipping but not with the activity of inventory. Furthermore, the industrial activities were classified with respect to the sensitivity on the tranding day effect.

• The Journal of Korean Medicine
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• v.34 no.1
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• pp.136-145
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• 2013

Objectives: Recently, Korean medicine has been explored by employing mathematical methods, which is an effort to raise Korean medicine to a higher level of scientific research. In that vein, we propose a mathematical model, analyzing the effects of seasonal cycle as an external factor in addition to the internal interactions of five-states, the engendering and the restraining. Methods: Some modified differential equations with 5-state variables were given to describe the interactions of the engendering and the restraining, and effect of seasonal cycle, and are numerically analyzed by Runge-Kutta method. We then simulated it along with time and dynamically analyzed it by Moran's I, a spatial autocorrelation. Results: We showed the effects of seasonal cycle on yin-yang five-states and applied it to the human life cycle. Conclusions: Our result is comparable to previous results in the respect that we consider the seasonal cycle and its effect on five-states, unlike others' mainly focusing on internal interaction. Furthermore, we suggest some follow-up study taking into consideration the complexity and diversity of external factors.

• Journal of the Korean Home Economics Association
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• v.30 no.4
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• pp.15-26
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• 1992

To investigate the seasonal effects on physiological responses of human body, clothing micro-climate, and subjective sensation, selected the cloths the most frequently dressed by men in spring and fall, and completed wearing trials in the climatic chamber. The results are as follows: 1. Rectal temp. ranged 36.8-37.1$^{\circ}C$ in either spring or fall, and no seasonal effect was found. 2. In skin temp., there was no seasonal effect in forehead, abdomen, and forearm. Skin temp. of chest was higher in spring than in fall. On the contrary, reverse was true in high and leg. Average skin temp. ranged 32.2-33.2$^{\circ}C$ in spring and 32.9-34.$0^{\circ}C$ in fall. 3. Average total sweat rate of spring, 79.4g/hr, was smaller than that of fall, 110.9g/hr. 4. Clothing temp. ranged 28.1-32.8$^{\circ}C$ in spring and 27.6-31.$0^{\circ}C$ in fall. Clothing humidity ranged 36.9-48.9% in spring and 38.2-51.1% in fall. Therefore, clothing microclimate was higher during fall than during spring. As results, skin temp. of the body core except chest did not show seasonal variation, but there was obvious seasonal variation in skin temp. of the extremities. Therefore, seasonal variation should be take into consideration in the experiments related to the cloth. In addition, standard for each season and the degree of work performance should be re-established in clothing micro-climate.

• Journal of the Korean Data and Information Science Society
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• v.20 no.1
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• pp.117-124
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• 2009

If time series data with seasonal effect exist, various statistical models like winters for successful forecasts could be used. But if the data are not enough to estimate seasonal effect, not much methods are available. This paper proposes the statistical forecasting method based on cumulative data when the data are not enough to estimate seasonal effect. We apply this method to real cosmetic sales data and show its better performance over moving average method.

• Korean Management Science Review
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• v.20 no.1
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• pp.103-124
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• 2003

The seasonal adjustment is an essential process in analyzing the time series of economy and business. There are various methods to adjust seasonal effect such as moving average, extrapolation, smoothing and X11. One of the powerful adjustment methods is X11-ARIMA Model which is popularly used in Korea. This method was delivered from Canada. However, this model has been developed to be appropriate for Canadian and American environment. Therefore, we need to review whether the Xl1-ARIMA Model could be used properly in Korea. In this study, we have applied the method to the annual sales of refrigerator sales in A electronic company. We appreciated the adjustment by result analyzing the time series components such as seasonal component, trend-cycle component, and irregular component, with the proposed method.