• 대한한방내과학회지
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• 제31권2호
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• pp.308-313
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• 2010

Objectives : The weekly variation of ischemic stroke incidence according to the age and sex. Methods : 977 consecutively admitted patients (521 males and 456 females) in a single stroke center from 2006 to 2008. All cases were confirmed with standardized criteria. We used the independent t-test and $x^2$ test in statistical methods. Results : The results demonstrated significant weekly variations of ischemic stroke incidence showing higher incidence on Saturday, Monday and Tuesday and lower incidence on the other days. Difference of ischemic stroke incidence was also shown between transit days, which included the transit days from the weekend to the week and vice versa, and non-transit days. Those aged older than 60 years and females showed more significant differences of weekly variation on transit days than on non-transit days. Conclusions : Ischemic stroke incidence has significant weekly variation, and transit days have higher incidence than non-transit days. Further study is required to identify the general weekly variation by multi-center trial.

• 한국대기환경학회지
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• 제19권2호
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• pp.231-245
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• 2003

Hourly PM$_{10}$ concentrations measured at 11 sites in Seoul and 10 sites in the large cities over South Korea for the period from March 1995 to February 2000 are analyzed to examine annual trend and monthly variations of the PM$_{10}$ concentrations. Further analysis has been carried out by using the one year data from March 1999 to February 2000 to see the seasonal variation, diurnal variation and weekly variation of the seasonally averaged PM$_{10}$ concentrations at each site. Weekly variations of the CO concentrations at the same sites for the same one year period are compared with that of the PM$_{10}$ concentration. There is no significant annual trend in the variation of the PM$_{10}$ concentration at all the sites analyzed. The seasonal and monthly mean concentrations show a minimum concentration in summer and alternative maximum concentration in spring and winter for most sites. The diurnal variation of the seasonally averaged mean PM$_{10}$ concentrations is strongly affected by traffic loads and meteorological conditions. The weekly variation of seasonal averaged concentrations of CO and PM$_{10}$ shows a high concentration for weekdays in spring, autumn and winter while high concentration for weekends in summer.nds in summer.

• 동의생리병리학회지
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• 제23권5호
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• pp.1167-1171
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• 2009

Ischemic stroke has been the leading cause deaths and the critical disability. In addition, the clinical problem of ischemic stroke have the poor prognosis and high mortality rate. The study aim was to identify the incidence variation of ischemic stroke by days of the week and its relationship with residences in males. We analyzed 607 males patients with ischemic stroke diagnosed by magnetic resonance image or computerized tomography. They were admitted to the oriental hospital of Kyunghee, Daejeon, Wonkwang university. We analyzed the onset of ischemic stroke using a ${\chi}2$ test. The results showed significant weekly variation of ischemic stroke onset and the differences of weekly variation according to residences. A deeper knowlegde of the underlying weekly variation could be provide more effective insights for preventive approach.

• 대한전기학회논문지
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• 제45권4호
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• pp.511-516
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• 1996

In this paper, weekly maximum power demand forecasting method in consideration of temperature estimation using a time series model was presented. The method removing weekly, seasonal variations on the load and irregularities variation due to unknown factor was presented. The forecasting model that represent the relations between load and temperature which get a numeral expected temperature based on the past 30 years(1961~1990) temperature was constructed. Effect of holiday was removed by using a weekday change ratio, and irregularities variation was removed by using an autoregressive model. The results of load forecasting show the ability of the method in forecasting with good accuracy without suffering from the effect of seasons and holidays. Percentage error load forecasting of all seasons except summer was obtained below 2 percentage. (author). refs., figs., tabs.

• Journal of Nutrition and Health
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• 제37권10호
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• pp.917-927
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• 2004

This study was performed to examine component of variance in nutrient intakes and to estimate the level of accuracy with varying degree of precision in order to achieve estimates of usual nutrient intakes. Three-day dietary records including both weekdays and weekends were collected every 4 season over a I-year period from 36 males and 93 females aged 40 - 65 y. For each nutrient, we partitioned total intake variance into weekly (weekday vs weekend), seasonal, within- and between- individual variation as components of variance, using analysis of variance. It was found that major components of variance were within- and between-individual variation. Particularly, within-individual variation (57.2 - 87.1 %) was greater than between-individual variation (12.2 - 37.4%) for all nutrients. Weekly and seasonal variation contributed small components of variance for most nutrients. For protein, fat and carbohydrate, there were a little significant weekly variation (0.00 - 1.35%) in females but not in males. For some micronutrients, there were moderately significant seasonal variation (0.15 - 5.48%) in both sexes. Ratio of within- to between- individual variation ranged 1.4 (vitamin B$_2$) -4.5 (vitamin B$_1$) in males and 1.6 (carbohydrate) -2.9 (fat) in females. With total 12-day dietary records data, the maximum percentage deviation of observed intakes from usual (true) intakes ranged 12-37%. To estimate usual individual intakes within 20% of the true mean with 90% confidence level, 3 - 9 days of dietary survey were required for energy, protein, carbohydrate, phosphorus and iron, 13 - 19 days for fat and calcium, 25 - 29 days for vitamin A and vitamin C. Correlation coefficients between observed and true nutrient intakes were 0.71 - 0.91 for males, 0.81-0.91 for females. In conclusion, mean intakes of several nutrients can be reliably measured with the record method, using a limited number of days. Both nutrients of interest and the primary objectives should be taken account when planning method of assessment and number of replicates.

• Ocean and Polar Research
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• 제43권1호
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• pp.31-43
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• 2021

To understand the temporal variation of prokaryotic communities in a temperate coastal area, prokaryotic abundance, activity, and community composition were investigated every week for over a year at a coastal monitoring station of Yeong-do, Busan. The prokaryotic abundances fluctuated about 10 times, ranging from 2.0 to 20.1 × 10⁵ cells mL^-1 and tended to be high in spring when phytoplankton bloom occurred. The prokaryotic thymidine incorporation rates (TTI) varied in a low range between 0.2 and 11.5 pmol L^-1 h^-1 in winter. However, in summer, TTI were increased up to a range of 8.3 to 17.4 pmol L^-1 h^-1, showing an increasing pattern in summer. During the study period, Alphaproteobacteria was the most dominant class for most of the year, followed by Flavobacteria. While the seasonal variation of prokaryotic composition was not apparent at the class level, many prokaryotic species showed a distinct temporal or seasonal variation for the year. In the coastal site, prokaryotic biomass and activity did not show significant correlations with temperature and chlorophyll-a, which are well known to regulate prokaryotic growth in marine environments, suggesting that the study area may be affected by diverse sources of organic matter for their growth.

• 보건행정학회지
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• 제23권3호
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• pp.260-265
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• 2013

Background: The aim of this study was to examine the seasonal variation of death from intentional self-harm by hanging, strangulation and suffocation (HSS: Korean Standard Classification of Diseases-6 code: X70) using the 2011 death registry data. Methods: The analysis was based on data of 8,359 HSS deaths from 2011 national vital statistics in Korea. Daily, weekly, and monthly death pattern on HSS were used to examine the relationship seasonal variation and HSS deaths. Results: A total of 8,359 HSS deaths occurred in 2011, with a mean age of 50.6 years. The HSS death rate (per 100,000) was 25.5 in male and 10.8 in female. In one day 17.6 males and 8.0 females occurred HSS death on average. The number of HSS death per day was the highest on 8th June (45 deaths), and lowest on 1st February (7 deaths) during the period. The variations of daily HSS death showed wide fluctuation from a peak of 34 to 45 deaths (29th May to 9th June) to a trough of 17-26 deaths (10th-13th September: the Korean thank-giving consecutive holidays), 13-20 deaths (2nd-5th February: the new year's day by the lunar calendar) and 8-9 deaths (24th-25th December: Christmas holidays). There were no significant difference between gender and seasonal variation (month, season, and week). Conclusion: The mean number of HSS death per day was highest in June (30.6 deaths), and months with the lowest number of deaths was January and December (range, 19.4 to 19.6 deaths). HSS death were more prevalent during summer and spring and were less likely to occur during winter. On Saturdays (21.0 deaths), the number of HSS death per day was the lowest, and Monday (27.9 deaths) was the highest. HSS death was less likely to occur on holidays (21.4 deaths). There was significant seasonal variation in HSS death by weekly and monthly (p<0.01).

• Ocean and Polar Research
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• 제40권4호
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• pp.191-202
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• 2018

In this study we conducted a weekly monitoring exercise at a fixed station in the saltwater zone during the dry season (Jan-Mar, 2013) and wet season (Jun-Aug, 2013) to understand the fluctuations in phytoplankton communities and environmental factors in the Youngsan River estuary altered by a dike constructed in the coastal area. Phytoplankton communities displayed seasonality; diatoms were dominant during the dry season whereas dinoflagellates were dominant during the wet season. T-test analysis showed that water temperature was significantly different between the seasons whereas freshwater discharge from the dike was not significantly different. This suggests that seasonal variations of phytoplankton are more likely affected by water temperature than freshwater discharge. However, a short-term fluctuation was also observed in response to freshwater discharge; freshwater species appeared during or after the discharge in the dry and wet seasons and blooms of harmful species developed after the discharge. Phytoplankton communities may be affected by changes in physical factors such as turbidity and salinity and nutrient supply resulting from freshwater discharge. Especially, the nutrient supply may directly contribute to the harmful algal blooms (HABs) composed of dinoflagellates which can adapt to low salinity after freshwater discharge.

• Asian-Australasian Journal of Animal Sciences
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• 제20권1호
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• pp.19-24
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• 2007

Covariance components and genetic parameters of weekly live body weight from hatching to six weeks of age and age of sexual maturation were estimated in a laying type Japanese quail line. The univariate and bivariate animal model analysis included hatching group and sex as fixed effects. Each trait was analysed with animal as random effect to fit the additive direct effect. Additional random effects incorporated in the models were changed according to the trait examined. The best model for a trait was chosen based on a likelihood ratio test, comparing the models with and without maternal additive genetic and maternal permanent environmental effects. Heritability estimates of live-weight at hatch and one to six weeks of age with their standard errors were 0.22${\pm}$0.088, 0.39${\pm}$0.099, 0.31${\pm}$0.086, 0.38${\pm}$0.056, 0.46${\pm}$0.055, 0.50${\pm}$0.059, and 0.56${\pm}$0.062, respectively. Direct heritability value of age of sexual maturation was moderate (0.24${\pm}$0.055). The variances due to permanent environmental effect of dam after one week of age and maternal genetic effect after two weeks of age were not important sources of variation. The correlations between direct and maternal genetic effects were negative and ranged from high to moderate values (-0.21 to -0.83). Among the weekly live weights, genetic correlations were generally high between not only successive but also early and late weightings. It suggests that selection for final weight may be based on early weight records. Genetic correlations between age of sexual maturation and live weights were low, favourable but had high standard errors. These results indicate that selection for high weight will potentially result in lower age of sexual maturation only with accurate determination of breeding values.

• 한국정보시스템학회지:정보시스템연구
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• 제31권3호
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• pp.197-220
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• 2022

Purpose The purpose of this study is to identifies the demand pattern categorization of repair parts of Automotive After-sales Service(A/S) and proposes a demand prediction model for Auto repair parts using Long Short-Term Memory (LSTM) of artificial neural networks (ANN). The optimal parts inventory quantity prediction model is implemented by applying daily, weekly, and monthly the parts demand data to the LSTM model for the Lumpy demand which is irregularly in a specific period among repair parts of the Automotive A/S service. Design/methodology/approach This study classified the four demand pattern categorization with 2 years demand time-series data of repair parts according to the Average demand interval(ADI) and coefficient of variation (CV²) of demand size. Of the 16,295 parts in the A/S service shop studied, 96.5% had a Lumpy demand pattern that large quantities occurred at a specific period. lumpy demand pattern's repair parts in the last three years is predicted by applying them to the LSTM for daily, weekly, and monthly time-series data. as the model prediction performance evaluation index, MAPE, RMSE, and RMSLE that can measure the error between the predicted value and the actual value were used. Findings As a result of this study, Daily time-series data were excellently predicted as indicators with the lowest MAPE, RMSE, and RMSLE values, followed by Weekly and Monthly time-series data. This is due to the decrease in training data for Weekly and Monthly. even if the demand period is extended to get the training data, the prediction performance is still low due to the discontinuation of current vehicle models and the use of alternative parts that they are contributed to no more demand. Therefore, sufficient training data is important, but the selection of the prediction demand period is also a critical factor.