• 대한치과교정학회지
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• 제45권5호
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• pp.226-235
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• 2015

Objective: The purpose of this retrospective study was to investigate short-term and long-term skeletodental outcomes of Class III activator treatment. Methods: A Class III activator treatment group (AG) comprised of 22 patients (9 boys, 13 girls) was compared with a Class III control group (CG) comprised of 17 patients (6 boys, 11 girls). The total treatment period was divided into three stages; the initial stage (T1), the post-activator treatment or post-mandibular growth peak stage (T2), and the long-term follow-up stage (T3). Cephalometric changes were evaluated statistically via the Mann-Whitney U-test and the Friedman test. Results: The AG exhibited significant increases in the SNA angle, ANB angle, Wits appraisal, A point-N perpendicular, Convexity of A point, and proclination of the maxillary incisors, from T1 to T2. In the long-term follow-up (T1-T3), the AG exhibited significantly greater increases in the ANB angle, Wits appraisal, and Convexity of A point than the CG. Conclusions: Favorable skeletal outcomes induced during the Class III activator treatment period were generally maintained until the long-term follow-up period of the post-mandibular growth peak stage.

• 대한간호학회지
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• 제30권1호
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• pp.29-38
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• 2000

To determine whether personal history of lactation in premenopausal women influence bone mineral density, a cross-sectional study was conducted. One hundred eighty-four premenopausal women were selected from women who had been checked for bone mineral density by dual energy x-ray absortiometry in lumbar spine, femoral neck, Ward's triangle, and trochanteric site at general hospitals in Seoul and Pusan. They completed a questionnaire including life style factors and reproductive history. In the data analysis, Pearson correlation coefficients were used to test any association between individual variables and bone mineral density and a statistical comparisons between long term lactation(>24 months) and short term lactation(<24 months) were made by one way analysis of covariance. The results were summarized as follows: 1) There was no significant difference in the bone mineral density of the lumbar vertebrae in premenopausal women between the long term lactation group(>24months) and the short term lactation group(<24months). 2) There was no significant difference in the bone mineral density of the femur neck, Ward's triangle, and trochanteric site in premenopausal women between the long term lactation group (>24months) and the short term lactation group (<24months). Considering these results, we suggest prospective studies that measure bone mineral density before and after, in addition to those during lactation. We also suggest the further study with premenopausal women less than 35 who have achieved peak adult bone mass.

• 한국태양에너지학회 논문집
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• 제33권5호
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• pp.1-8
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• 2013

Wind resource data of short-term period has to be corrected a long-term period by using MCP method that Is a statistical method to predict the long-term wind resource at target site data with a reference site data. Because the field measurement for wind assessment is limited to a short period by various constraints. In this study, 2 different MCP methods such as Linear regression and Matrix method were chosen to compare the predictive accuracy between the methods. Finally long-term wind speed, wind power density and capacity factor at the target site for 20 years were estimated for the variability of wind and wind energy. As a result, for 20 years annual average wind speed, Yellow sea off shore wind farm was estimated to have 4.29% for coefficient of variation, CV, and -9.57%~9.53% for range of variation, RV. It was predicted that the annual wind speed at Yellow sea offshore wind farm varied within ${\pm}10%$.

• 대한가정학회지
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• 제38권1호
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• pp.59-73
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• 2000

The purposes of this study were to determine the factors that influence consumer concerns for safety to cow's milk produced using food-related biotechnology and to find the similarity and difference among concern factors relating short-term and long-term risk perception. Telephone interviews were conducted and the data were collected from households(n=1,466) nationwide in the U.S. And the data were analyzed by probit model and LIMDEP softare package. The data demonstrated that consumers were concerned about food safety from consuming milk produced using food-related biotechnology. The concerns were found to be influenced by demographic factors(gender in short-term, gender and age in long-term) as well as psychological aspect such as outrage(heard about bGH, milk belief about naturalness, expected benefit in short-term, heard about bGH, expected benefit in long-term) and attitudinal factors(animal rights group, locus of control in short-term, animal rights group, cancer history, locus of control in long-term). The results suggest that consumers have concerns for safety to cow's milk produced by biotechnology and the most factors influencing consumer concerns were similar between short-term and long-term period, though a few factors such as cancer history, milk belief about naturalness and age were different.

• Communications for Statistical Applications and Methods
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• 제22권6호
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• pp.675-683
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• 2015

In the 21st century, we now face the serious problems of the enormous consumption of the energy resources. Depending on the power consumption increases, both China and South Korea face a reduction in available resources. This paper considers the regression models and time-series models to compare the performance of the forecasting accuracy based on Mean Absolute Percentage Error (MAPE) in order to forecast the electricity demand accurately on the short-term period (68 months) data in Northeast China and find the relationship with Korea. Among the models the support vector regression (SVR) model shows superior performance than time-series models for the short-term period data and the time-series models show similar results with the SVR model when we use long-term period data.

• 대한안전경영과학회지
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• 제10권2호
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• pp.195-203
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• 2008

The purpose of this study is to develop a guideline of process capability evaluation and to apply this guideline improving the quality of products, especially in the small and medium enterprises. In this study we deal in the concept of process capability evaluation, the calculation of process capability index, and the application of a case study. Man must compare the state of process with the standards in evaluating of the process capability. Control chart can be used as a yardstick for judgement for the long term period and the distribution shape of histogram for the short term period. Man should regard to the significant figure by the calculation of process capability index.

• 대한원격탐사학회지
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• 제27권3호
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• pp.259-276
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• 2011

Short-term land cover changes, such as forest fire scar and crop harvesting, can be detected by high temporal resolution satellite imagery like MODIS and AVHRR. Because these optical satellite images are often obscured by clouds, the static cloud-free composite methods (maximum NDVI, minblue, minVZA, etc.) has been used based on non-overlapping composite period (8-day, 16-day, or a month). Due to relatively long time lag between successive images, these methods are not suitable for observing short-term land cover changes in near-real time. In this study, we suggested a new dynamic cloud-free composite algorithm that uses cut-and-patch method of cloud-masked daily MODIS data using MOD35 products. Because this dynamic composite algorithm generates daily cloud-free MODIS images with the most recent information, it can be used to monitor short-term land cover changes in near-real time. The dynamic composite algorithm also provides information on the date of each pixel used in compositing, thereby makes accurately identify the date of short-term event.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.21-23
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• 2005

NARX(Nonlinear AutoRegressive with eXogenous input) neural network was used for prediction of nuclear reactor behavior which was influenced by control rods in short-term period and also by xenon and boron in long-term period in load following operations. The developed model was designed to predict reactor power, xenon worth and axial offset with different burnup rates when control rod and boron were adjusted in load following operations. Data of UCN 3 were collected by ONED94 code. The test results presented exhibit the capability of the NARX neural network model to capture the long term and short term dynamics of the reactor core and seems to be utilized as a handy tool for the use of a plant simulation.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권9호
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• pp.567-569
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• 2005

NARX(Nonlinear AutoRegressive with eXogenous input) neural network was used for prediction of nuclear reactor behavior which was influenced by control rods in short-term period and also by the concentration of xenon and boron in long-term period in load following operations. The developed model was designed to predict reactor power, xenon worth and axial offset with different burnup states when control rods and boron were adjusted in load following operations. Data of the Korea Next Generation PWR were collected by ONED94 code. The test results presented exhibit the capability of the NARX neural network model to capture the long term and short term dynamics of the reactor core and the developed model seems to be utilized as a handy tool for the use of a plant simulation.

• Journal of Electrical Engineering and Technology
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• 제10권4호
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• pp.1480-1491
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• 2015

In new deregulated electricity market, short-term price forecasting is key information for all market players. A better forecast of market-clearing price (MCP) helps market participants to strategically set up their bidding strategies for energy markets in the short-term. This paper presents a new prediction strategy to improve the need for more accurate short-term price forecasting tool at spot market using an artificial neural networks (ANNs). To build the forecasting ANN model, a three-layered feedforward neural network trained by the improved Levenberg-marquardt (LM) algorithm is used to forecast the locational marginal prices (LMPs). To accurately predict LMPs, actual power generation and load are considered as the input sets, and then the difference is used to predict price differences in the spot market. The proposed ANN model generalizes the relationship between the LMP in each area and the unconstrained MCP during the same period of time. The LMP calculation is iterated so that the capacity between the areas is maximized and the mechanism itself helps to relieve grid congestion. The addition of flow between the areas gives the LMPs a new equilibrium point, which is balanced when taking the transfer capacity into account, LMP forecasting is then possible. The proposed forecasting strategy is tested on the spot market of the Nord Pool. The validity, the efficiency, and effectiveness of the proposed approach are shown by comparing with time-series models