• Journal of the Korean Home Economics Association
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• v.38 no.1
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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.

• Fisheries and Aquatic Sciences
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• v.16 no.2
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• pp.117-124
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• 2013

We investigated the short-term and local changes in the thermohaline front in the Jeju Strait, Korea, which is usually formed during winter and spring. To do so, we compared Real-Time Observation System by Ferryboat (RTOSF) data with wind data and routinely collected oceanographic data. During February and April 2007, a thermohaline front formed in the Jeju Strait around the 13-$14^{\circ}C$ isotherms and 33.0-33.5 isohalines. The thermohaline was clearly weakened and began moving southward in mid-March. The variations in the surface temperature and salinity showed a continuous north-south oscillation of the thermohaline front with a period of 3-10 days. The speed of the short-term and local fluctuation of thermohaline front was about 5-30 cm/s. We confirmed these findings by examining the variation in the maximum temperature gradient and $14^{\circ}C$ isotherm during the study period. These short-term and local changes had not been previously detected using serial oceanographic and satellite data. Analysis of local wind data revealed a northerly wind fluctuation with a period of 3-10 days, which was clearly related to the short-term and local changes in the thermohaline front. The short-term and local changes of the thermohaline front in the Jeju Strait originated from local changes in the winter monsoon in this area.

• The korean journal of orthodontics
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• v.45 no.5
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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.

• Journal of Korean Academy of Nursing
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• v.30 no.1
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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.

• Korean Journal of Remote Sensing
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• v.27 no.3
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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.

• Journal of the Korean Solar Energy Society
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• v.33 no.5
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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 ${\pm}10%$.

• Communications for Statistical Applications and Methods
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• v.22 no.6
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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.

• Journal of the Korea Safety Management & Science
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• v.10 no.2
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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.

• Proceedings of the KIEE Conference
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• 2005.05a
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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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.9
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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.