• Water for future
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• v.18 no.4
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• pp.317-325
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• 1985

In the analysis, monthly streamflow records atthe gauging station in Nakdong, Han and Geum river were used. Also, the fitness of monthly streamflow to Gamma and Long-normal distribution was tested by Kolomogorv-Smirnov test. The results obtained in this study can be summarized as follws (1) The fitness of monthly streamflow to two-parameter Gamma distribution was tested by Kolomorov-Smirnov test, which fits well to this Gamma distribution (2) The Run-length and Run-sum were simulated by the Gamma model. In this result, run-length and Run-sum of monthly streamflow were fit for Gamma model (3) The mean decreases (increases) the expected surplus (deficit) Run-Sum of the monthly streamflow. The higher the truncation level of negative Run-length and Run-sum the larger is the effect of mean.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.4
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• pp.466-476
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• 2012

This study calculated monthly and sectoral (for industry, energy industry, transport, residential, commercial and public sectors) greenhouse gas (GHG) emissions of Seoul, Korea from 1999 until 2009 with following the IPCC 2006 Guideline for National Greenhouse Gas Inventories through an analysis on available monthly data of fossil fuel and electricity consumption for the period. The time series analysis showed that GHG emissions had significant cyclical pattern season by season with the highest peak in August and the lowest peak in January throughout the period. The analysis on monthly and sectoral energy consumption showed that residential, commercial and public sectors had emitted about 65% of total GHG emissions of Seoul and had consumed more energy in winter for heating. About 30% GHG of Seoul was emitted from transport sector but its monthly energy consumption showed irregular pattern and it consumed 80% petroleum (in 2009) of Seoul. Hopefully together with further study on this subject, it is expected that this study can be used as basic data for various research regarding Greenhouse gas baseline emission, energy consumption pattern and estimation for future GHG emission of Seoul.

• Journal of Wetlands Research
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• v.10 no.1
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• pp.1-9
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• 2008

This study describes the WASMOD, water balance model which can consider the snowmelting. The pilot study basin is the Soyang River basin with outlet at Soyang Dam Site and compute long-term monthly streamflow, The advantage of the WASMOD is that the input data is simple and the user can operate easily. To optimize for the parameters of the model, the WASMOD used VA05A of automatic fitting technique. The observed and simulated monthly streamflow hydrographs were compared. The model performance on corrleation coefficient between the observed and the simulated streamflow for the verification periods was above 0.89. It was shown that the WASMOD reproduces the observed monthly streamflow hydrographs very well. This evidence suggests that the WASMOD might be appropriate for the simulation of monthly streamflow

• Magazine of the Korean Society of Agricultural Engineers
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• v.35 no.3
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• pp.117-129
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• 1993

This study was conducted to get reasonable and abundant hydrological time series of monthly flows simulated by a best fitting stochastic simulation model for the establishment of rational design and the rationalization of management for agricultural hydraulic structures including reservoirs. Comparative analysis carried out for both statistical characteristics and synthetic monthly flows simulated by the multi-season first order Markov model based on Gamma distribution which is confirmed as good one in the first report of this study and by Harmonic synthetic model analyzed in this report for the six watersheds of Yeong San and Seom Jin river systems. 1.Arithmetic mean values of synthetic monthly flows simulated by Gamma distribution are much closer to the results of the observed data than those of Harmonic synthetic model in the applied watersheds. 2.In comparison with the coefficients of variation, index of fluctuation for monthly flows simulated by two kinds of synthetic models, those based on Gamma distribution are appeared closer to the observed data than those of Harmonic synthetic model both in Yeong San and Seom Jin river systems. 3.It was found that synthetic monthly flows based on Gamma distribution are considered to give better results than those of Harmonic synthetic model in the applied watersheds. 4.Continuation studies by comparison with other simulation techniques are to be desired for getting reasonable generation technique of synthetic monthly flows for the various river systems in Korea.

• Magazine of the Korean Society of Agricultural Engineers
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• v.38 no.4
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• pp.110-124
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• 1996

This study was conducted to simulate long seres of synthetic monthly flows by multi-season first order Markov model with selection of best fitting frequency distribution, harmonic synthetic and harmonic regression models and to make a comparison of statistical parameters between observes and synthetic flows of five watersheds in Geum river system. The results obtained through this study can be summarized as follow. 1. Both gamma and two parameter lognormal distributions were found to be suitable ones for monthly flows in all watersheds by Kolmogorov-Smirnov test. 2. It was found that arithmetic mean values of synthetic monthly flows simulated by multi-season first order Markov model with gamma distribution are much closer to the results of the observed data in comparison with those of the other models in the applied watersheds. 3. The coefficients of variation, index of fluctuation for monthly flows simulated by multi-season first order Markov model with gamma distribution are appeared closer to those of the observed data in comparison with those of the other models in Geum river system. 4. Synthetic monthly flows were simulated over 100 years by multi-season first order Markov model with gamma distribution which is acknowledged as a suitable simulation modal in this study.

• Water for future
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• v.11 no.2
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• pp.54-61
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• 1978

An attemption of synthesizing and forecasting of monthly river flow has been made by employing a linear stochastic difference equation model. As one of the linear stochestic difference equation model, an ARIMA Type is tested to find the suitability of the model to the monthly river flows. On the assumption of the stationary covariacne of differenced monthly river flows the model is identrfield and is evaluated so that the residuale have the minimum variance. Finally a test is performed to finld the residerals beings White noise. Monthly river flows at six stations in Han River Basin are applied for case studies. It was found that the difference operator is a good measure of forecasting the monthly river flow.

• The Research Journal of the Costume Culture
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• v.31 no.1
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• pp.1-17
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• 2023

This study analyzed requirements for medical masks and difference in satisfaction based on demographic characteristics and side effects experience caused by wearing medical masks. Three factors related to requirements for medical masks were identified: wearing comfort and usability, blocking function for harmfulness, and design. As a result of the difference analysis for requirements of medical masks based on demographic characteristics, all three factors showed a significant difference in gender and occupation. Design did in age and monthly income. As a result of the presence or absence of breathing difficulties experience, design factor was significant. As a result of the presence or absence of skin trouble experience, wearing comfort and usability showed a significant difference. As a result of the difference in satisfaction with medical masks based on demographic characteristics and side effect experience caused by wearing medical masks, breathing, ear string tightness, blocking harmful substances, price, and over all wearing comfort showed a significant difference by gender, marital status, age, occupation, and monthly income, and the presence of absence of breathing difficulty experience and skin trouble experience, respectively. As a result of the interaction effect analysis between demographic characteristics and side effects experience caused by wearing medical masks, it showed a significant interaction effect between gender and monthly income, between marital status and monthly income, between monthly income and breathing difficulties experience, and between monthly income and skin trouble experience.

• The Korean Journal of Applied Statistics
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• v.36 no.5
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• pp.457-471
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• 2023

The monthly series is an aggregation of daily values. In the absence of observable daily data, calendar effects such as trading day and holidays are estimated using a RegARIMA model. However, if the daily series were observable, these calendar effects could be estimated directly from the daily series, potentially improving the seasonal adjustment of the monthly time series. In this paper, we propose a method to improve the seasonal adjustment of monthly time series by using calendar variation estimation based on daily time series. We apply this seasonal adjustment method to three monthly time series and compare our results with those obtained using X-13ARIMA-SEATS.

• Clinical and Experimental Reproductive Medicine
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• v.51 no.2
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• pp.120-124
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• 2024

Objective: Seasonal variations in semen quality are known to occur in temperate regions, but results regarding tropical areas remain inconclusive. The aim of this study was to determine whether monthly variations in semen parameters are present among men in a tropical region. Methods: Data were retrospectively collected from semen analyses of 3,000 men over a 10-year period, from 2012 to 2022. Analysis of variance and the independent-samples t-test were employed to observe variations in semen parameters throughout the entire period and between months, respectively. Results: The mean±standard deviation sperm concentration was significantly lower in June, at 42.5±31.4 million/mL, compared to other months. The highest sperm concentration was found in March, at 57.8±42.6 million/mL, constituting a mean difference of 15.3 million/mL between the lowest and highest concentrations. The total sperm count displayed a similar pattern of monthly variation, with a difference of 47.2 million between the highest and lowest months. No significant monthly differences were observed in other parameters, such as sperm motility, morphology, and semen volume. Conclusion: Significant monthly variations in sperm concentration and total sperm count were evident in this Sri Lankan population. March, which displayed the highest sperm counts, is in the spring in temperate regions, while the month with the lowest counts, July, is part of the summer. Fluctuations in photoperiod appear to most strongly influence these variations.

• Journal of Distribution Research
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• v.17 no.3
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• pp.115-132
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• 2012

This study empirically examines the impact of SSM market entry on changes in market shares among retailing types. The data is monthly time-series data spanning over the period from January 2000 to December 2010, and the effect of SSM market entry on market shares of retailing types is analyzed by utilizing several key factors such as the number of new SSM monthly entrants, total number of SSMs, the proportion of new SSM entrant that is smaller than $165m^2$ to total new SSM entrants. According to the Korean Standard Industrial Classification codes, the retailing type is classified into 5 groups: department stores, retail sale in other non-specialized large stores(big marts), supermarkets, convenience stores, and retail sale in other non-specialized stores with food or beverages predominating (others). The market shares of retailing types are calculated by the ratio of each retailing type monthly sales to total monthly retailing sales in which total retailing sales is the sum of each retailing type sales. The empirical model controls for the size effects with the number of monthly employees for each retailing type and the macroeconomic effects with M2. The empirical model employed in this study is as follows; $$MS_i=f(NewSSM,\;CumSSM,\;employ_i,\;under165,\;M2)$$ where $MS_i$ is the market share of each retailing type (department stores, big marts), supermarkets, convenience stores, and others), NewSSM is the number of new SSM monthly entrants, CumSSM is total number of SSMs, $employ_i$ is the number of monthly employees for each retailing type, and under165 is the proportion of new SSM entrant that is smaller than $165m^2$ to total new SSM entrants. The correlation among these variables are reported in