• Journal of the Korean Society of Food Culture
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• v.14 no.5
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• pp.447-454
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• 1999

The empirical research was conducted to investigate women's consumption pattern of Korean rice cakes and to analyze the preference of them by their demographic backgrounds. The results of this study provide useful informations for a systematic development of Korean rice cake. A self-completed questionnaire survey of 281 women in Seoul was undertaken and detailed information was collected from each. A questionnaire consisted of three parts including demographic backgrounds, consumption pattern and preference of Korean rice cakes, and the need assessment. Demographic variables of respondents included age, marital status, education, family style, monthly income etc. Most of them(82.6%) were married with the average age of $36.3{\pm}8.4$ year old. The results of eating frequency rate showed that about half of women(49.1%) had Korean rice cake once or twice a month followed by once a week(23.1%), once per two months(13.9%), once per six months(8.2%), and once per three months(3.9%). Average preference score of 14 Korean rice cakes was $3.08{\pm}1.49$ out of 5, indicating 'so-and-so'. Ingeolmi received the highest score of 4.02, whereas Duteopteok had the lowest score of 0.18. The preference score of Korean rice cake and the respondents' knowledge of them showed significantly strong positive correlation. The need-assessment score for improving the quality of Korean rice cake was $3.72{\pm}1.35$ out of 5, showing moderate willingness for improvement of Korean rice cake.

• Proceedings of the Korea Water Resources Association Conference
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• 2001.05a
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• pp.7-14
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• 2001

In this study, we characterized the variation of sampling errors using the Waymire-Gupta-rodriguez-Iturbe multi-dimensional rainfall model (WGR model). The parameters used for this study are those derived by Jung et al. (2000) for the Han River Basin using a genetic algorithm technique. The sampling error problems considering in this study are those far using raingauge network, satellite observation and also for both combined. The characterization of sampling errors was done for each month and also for the downstream plain area and the upstream mountain area, separately. As results of the study we conclude: (1) The pattern of sampling errors estimated are obviously different from the seasonal pattern of mentally rainfall amounts. This result may be understood from the fact that the sampling error is estimated not simply by considering the rainfall amounts, but by considering all the mechanisms controlling the rainfall propagation along with its generation and decay. As the major mechanism of moisture source to the Korean Peninsula is obviously different each month, it seems rather norma1 to provide different pattern of sampling errors from that of monthly rainfall amounts. (2) The sampling errors estimated for the upstream mountain area is about twice higher than those for the down stream plain area. It is believed to be because of the higher variability of rainfall in the upstream mountain area than in the down stream plain area.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.20 no.2
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• pp.102-110
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• 2010

Personal exposure relies on characteristics of time activity patterns of the population of concern as human activities impact the timing, location, and level of personal exposure. The information about time spent in microenvironments plays a critical role for personal exposure to air pollutants. It is useful to determine the precise times of the day that the subjects are in certain locations or engaging in specific activities because exposure to some air pollutants can depend on temporal trends. This study investigated time activity pattern for workers of Korean population over 19 years old with 8,778 workers in weekday. The residential indoor times were 12 hours. Time activity was different by gender and the mean times stayed at home in weekday were 12.9 hours in female and 11.42 hours in male, respectively. The major factors on residential indoor time and workplace time were age, monthly income, occupation and industry type, work position, education, and gender. Considering shorter than those in other countries, Korean workers spent less time at home after the working hours. Determinants of time activity pattern need to be taken into account in exposure assessment, epidemiological analyses, exposure simulations, as well as in the development of preventive strategies. Since there are substantial difference of Korean worker activity pattern, this information can be critical for exposure assessment in Korea.

• Atmosphere
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• v.27 no.1
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• pp.55-65
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• 2017

This study investigates how Eurasian snow cover in spring (March and April) is associated with Korean temperature during summer (June-July-August). Two leading modes of Eurasian snow cover variability in spring for 1979~2015 are obtained by Empirical Orthogonal Function (EOF) analysis. The first EOF mode of Eurasian snow cover is characterized by a zonally elongated pattern over the whole Eurasian region and its principal component is more correlated with Korean temperature during June. On the other hand, the second EOF mode of Eurasian snow cover is characterized by an east-west dipole-like pattern, showing positive anomalies over eastern Eurasian region and negative anomalies over western Eurasian region. This dipole-like pattern is related with Korean temperature during August. The first leading mode of Eurasian snow cover is associated with anomalous high (low) pressure over Korea (Sea of Okhotsk) during June, which might be induced by much evaporation of soil moisture in Eurasia during March. On the other hand, the second mode of Eurasian snow cover is associated with a wave train resembling with Eurasian (EU)-like pattern in relation to the Atlantic sea surface temperature forcing, leading to the anomalous high pressure over Korea during August. Understanding these two leading modes of snow cover in Eurasian continent in spring may contribute to predict Korean summer temperature.

• KNOM Review
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• v.24 no.1
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• pp.20-28
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• 2021

Extensive use of social media applications and mobile devices continues to increase data traffic. Social media applications generate an endless and massive amount of multimedia traffic, specifically video traffic. Many social media platforms such as YouTube, Daily Motion, and Netflix generate endless video traffic. On these platforms, only a few popular videos are requested many times as compared to other videos. These popular videos should be cached in the user vicinity to meet continuous user demands. MEC has emerged as an essential paradigm for handling consistent user demand and caching videos in user proximity. The problem is to understand how user demand pattern varies with time. This paper analyzes three publicly available datasets, MovieLens 20M, MovieLens 100K, and The Movies Dataset, to find the user request pattern over time. We find hourly, daily, monthly, and yearly trends of all the datasets. Our resulted pattern could be used in other research while generating and analyzing the user request pattern in MEC-based video caching scenarios.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.593-595
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• 2003

The introduction of electricity industry provides generators incentives to recover the related cost through the market. Hence, the generator should sell his/her electricity at high market-clearing price with optimal operation of his/her power plant. The maintenance of power plant is the most critical factor in affecting generators' decision-making. This paper analyzes technique for establishing maintenance schedule reflecting recovery cost and considers differences in monthly load pattern in minimizing LOLP.

• Journal of Plant Biology
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• v.30 no.2
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• pp.117-133
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• 1987

The diatoms were investigated at three lowland swamps in Haman county form July, 1983 to July, 1984 on monthly interval. Seasonal changes of standing crops, the variation of dominant species and species composition were studied. The maximum of standing crops showed bimodal pattern at Chilnalpol and Yujnnup. Dominant species were Navicula crytocephala, Cocconeis placentula, Achnanthes minutissima, Achnanthes lanceolata, Synedra ulna, Eunotia lunaris. Dominant species changed seasonally. Total 166species of diatom were identified. Three lowland swamps supported a rich diatom flora composed of many species typically associated with benthic diatom.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2B
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• pp.199-213
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• 2008

The goal of this research is to develop and apply the integrational operation method (IOM) for the modeling of the monthly pan evaporation (PE) and the alfalfa reference evapotranspiration ($ET_r$). Since the observed data of the alfalfa $ET_r$ using lysimeter have not been measured for a long time in Republic of Korea, Penman-Monteith (PM) method is used to estimate the observed alfalfa $ET_r$. The IOM consists of the application of the stochastic and neural networks models, respectively. The stochastic model is applied to generate the training dataset for the monthly PE and the alfalfa $ET_r$, and the neural networks models are applied to calculate the observed test dataset reasonably. Among the considered six training patterns, 1,000/PARMA(1,1)/GRNNM-GA training pattern can evaluate the suggested climatic variables very well and also construct the reliable data for the monthly PE and the alfalfa $ET_r$. Uncertainty analysis is used to eliminate the climatic variables of input nodes from 1,000/PARMA(1,1)/GRNNM-GA training pattern. The sensitive and insensitive climatic variables are chosen from the uncertainty analysis of the input nodes. Finally, it can be to model the monthly PE and the alfalfa $ET_r$ simultaneously with the least cost and endeavor using the IOM.

• Fashion & Textile Research Journal
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• v.15 no.1
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• pp.116-129
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• 2013

This research analyzes the status of clothes purchase and the size fit of the clothes for kindergarten children in the Daegu city area. The total of 344 questionnaires were analyzed. The summary and the conclusion are as follows: First, the frequency of accompanying children when purchasing appeared mostly 'sometimes accompany'. Second, the parents appeared 'sometimes reflect children's opinions'. Third, the main information source was 'store display'. The main place of purchase was large discount stores, internet home-shopping, and department stores (respectively) with significant differences in the age of the parent(p<.05) and monthly incomes(p<.001). In the clothes size selection, 72.1% of the parents selected 'one size larger' at time purchase and showed asignificant difference by monthly income. Repair-experience after purchase appeared in 31.4% of the samples because of the inadequate length and width of the clothes. The unfit clothes parts were in the order of pant length, sleeve length, waist part, jacket length, pant width, hip part, and crotch, which showed a significant difference in children based on gender. The salient purchasing point for child clothing was in the order of 'size fit', 'color and pattern', 'design' and 'convenience in action'. It is important to consider that kindergarten children need adequate size for growing and convenient pattern designs (that include materials at stretching parts) for positive acting because they are in a period of frequent activity and growth.

• Journal of Korean Society for Atmospheric Environment
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• v.4 no.2
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• pp.72-81
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• 1988

The typical ARIMA model which was developed by Box and Jenkins, was applied to the monthly $SO_2$ data collected at Seoungsoo and Oryudong in metropolitan area over five years, 1982 to 1986. To find out the changing pattern of $SO_2$ concentration, autocorrelation and partial autocorrelation analysis were undertaken. The three steps of time series model building were followed and the residual series was found to be a random white noise. The results of this study is summarized as follows. 1) The monthly $SO_2$ series was found to be a non-stationary series which which has a periodicity of 12 months. After eliminating the periodicity by differencing, the monthly $SO_2$ series became a stationary series. 2) The ARIMA seasonal model of the $SO_2$ was determined to be ARIMA $(1, 0, 0)(0, 1, 0,)_{12}$ model. 3) The model equations based on the prediction were: for Seoungsoodong: $Y_t = 0.5214Y_{t-1} + Y_{t-12} - 0.5214Y_{t-13} + a_t$ for Oryudong: $Y_t = 0.8549Y_{t-1} + Y_{t-12} - 0.8549Y_{t-13} + a_t$ 4) The validity of the model identified was checked by compairing the measured $SO_2$ values and one-month-ahead predicted values. The result of correlation and regression analysis is as follows. Seoungsoodong: $Y = 0.8710X + 0.0062 r = 0.8768$ Oryudong : $Y = 0.8758X + 0.0073 r = 0.9512$