• 한국수자원학회논문집
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• 제46권6호
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• pp.667-681
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• 2013

본 연구에서는 삽교천유역에 위치한 19개 수질관측지점의 16년간(1995~2010) 월별 용존산소(dissolved oxygen: DO)자료를 이용하여 월별 및 계절별 용존산소 추세를 분석하였다. 추세분석을 위해 Mann-Kendall 추세분석과 Sen's slope 방법을 적용하였다. 또한 삽교천 유역을 4개 구역(삽교호, 삽교천본류, 무한천 및 곡교천)으로 구분하여 카이스퀘어 동질성 검정(chi-square homogeneity test)을 실시하여 각 구역의 월별, 그리고 계절별 용존산소추세의 동질성 유무를 분석하였다. 분석결과 대부분 수질관측지점의 월별, 계절별 용존산소는 증가추세를 보이거나 혹은 유의한 추세를 보이지 않았다. 또한 삽교천 유역 수질관측지점들의 계절별 용존산소추세는 서로 동질성을 보인 반면에 월별 용존산소추세는 수질관측지점이 저수지에 위치한 지점의 경우 동질성을 보이지 않았다. 전반적으로 삽교천 유역 수질관측지점의 용존산소 추세는 각 수질관측지점의 위치와 계절에 따라서 다른 양상을 보였다.

• 한국환경생물학회:학술대회논문집
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• 한국환경생물학회 2004년도 학술대회
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• pp.29-29
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• 2004

• ALGAE
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• 제19권1호
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• pp.39-47
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• 2004

Production dynamics of eelgrass, Zostera marina was examined in Jindong Bay on the south of the Korea peninsula. Eelgrass leaf productivities and environmental factors such as underwater photon flux density, water temperature, and nutrient availabilities in the water column and sediments were monitored from March 2002 to December 2003. While water temperature exhibited a distinct seasonal trend, underwater irradiance and nutrient availabilities exhibited high degree of fluctuation, and did not show a seasonal trend throughout the experimental periods. Eelgrass leaf elongation and production rates showed significant seasonal variations. Leaf productivity was highest in May (30.0 mg dry wt sht$^{-1}$ d$^{-1}$ or 3.7g dry wt m$^{-2}$d$^{-1}$) and lowest in November (3.2 mg dry wt sht$^{-1}$ d$^{-1}$ or 0.12 g dry wt m $^{-2}$ d$^{-1}$). Eelgrass leaf productivities did not show a strong correlation with underwater irradiance or environmental nutrient availabilities. The production rates, however, were positively correlated with water temperature during spring periods, and were correlated negatively at high water temperature exceeded 20℃ during summer months. While relative growth rates were highest in spring and lowest in high water temperature periods, plastochrone interval was longest during summer and shortest during spring. These results imply that seasonal growth dynamics of eelgrass, Z. marina was mainly controlled by water temperature.

• 대기
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• 제19권2호
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• pp.155-168
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• 2009

Characteristics of seasonal mean diurnal temperature range (DTR) and their causes over South Korea are investigated using the 60 stations data of Korea Meteorological Administration from 1976 to 2005. In general, the seasonal mean DTR is greatest during spring (in inland area) and least during summer (urban and coastal area). The spatial and seasonal variations of DTR are closely linked with the land surface conditions (especially vegetation activity and soil moisture) and atmospheric conditions (cloud amount, precipitation, local circulation). The seasonal mean DTR shows a decreasing trend at the major urban areas and at the north-eastern part of South Korea. Whereas, it shows an increasing trend at the central area of the southern part. Decreasing and increasing trends of DTR are more significant during summer and fall, and during spring and winter. The decrease (increase) of DTR is mainly caused by the stronger increase of daily minimum (maximum) temperature than daily maximum (minimum) temperature. The negative effects of precipitation and cloud amount on the DTR are greater during spring and at the inland area than during winter and at the coastal area. And the effect of daytime precipitation on the DTR is greater than that of nighttime precipitation.

• 정보과학회 논문지
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• 제41권12호
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• pp.1066-1074
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• 2014

본 논문에서는 시공간 정보를 포함하는 트윗 스트림에서 비정상적인 이벤트에 대한 상관관계를 사용자에게 시각적으로 분석하는 방법을 다양한 실험을 통하여 제안한다. 제안하는 방법으로는 트윗에서 토픽 모델링을 수행한 다음 계절요인과 추세요인을 반영한 시계열 분석 기법을 이용하여 비정상적인 이벤트 후보군을 추출한다. 추출된 토픽이 포함되어 있는 데이터를 대상으로 다시 한 번 토픽을 추출하여 시계열 분석을 수행한 다음 앞서 추출한 토픽과의 상관관계를 분석하여 비정상적인 이벤트를 탐지할 수 있도록 하였다. 비정상 이벤트를 탐지하는 모든 과정에 시각적 분석 방법을 이용하여 단순한 수치 정보가 아닌 시각적 패턴 형태로 나타냄으로써 사용자는 직관적으로 비정상 이벤트의 동향과 주기적인 패턴을 분석할 수 있도록 하였다. 실험은 2014년 1월 1일부터 2014년 6월 30일까지 국내에서 발생한 트윗을 대상으로 2개의 사건[경주 마우나 리조트 붕괴 사건(2014.02.17.), 진도 여객선 침몰 사건(2014.04.16.)]에 대해 시각적 분석 시스템을 적용하여 사용자는 쉽게 데이터를 분석하고 이해할 수 있음을 보였다.

• Industrial Engineering and Management Systems
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• 제7권1호
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• pp.9-22
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• 2008

As an extension of a previous work by the authors (Song and Esogbue, 2006), a new algorithm for automated modeling of nonstationary seasonal time series is presented in this paper. Issues relative to the methodology for building automatically seasonal time series models and periodic time series models are addressed. This is achieved by inspecting the trend, estimating the seasonality, determining the orders of the model, and estimating the parameters. As in our previous work, the major instruments used in the model identification process are correlograms of the modeling errors while the least square method is used for parameter estimation. We provide numerical illustrations of the performance of the new algorithms with respect to building both seasonal time series and periodic time series models. Additionally, we consider forecasting and exercise the models on some sample time series problems found in the literature as well as real life problems drawn from the retail industry. In each instance, the models are built automatically avoiding the necessity of any human intervention.

• Communications for Statistical Applications and Methods
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• 제12권1호
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• pp.101-115
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• 2005

We propose in this article a procedure for testing unit and fractional orders of integration, with the roots simultaneously occurring in the trend, the seasonal and the cyclical component of the time series. The tests have standard null and local limit distributions. However, finite sample critical values are computed, and several Monte Carlo experiments conducted across the paper show that the rejection frequencies against unit (and fractional) orders of integration are relatively high in all cases. The tests are applied to the UK consumption and income series, the results showing the importance of the roots corresponding to the trend and the seasonal components and, though the unit roots are found to be fairly suitable models, we show that fractional processes (including one for the cyclical component) may also be plausible alternatives in some cases.

• 패션비즈니스
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• 제11권1호
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• pp.1-14
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• 2007

This study was aimed at giving help to the people intending to change their own hair color design and also providing the guide line to the cosmetic circles for developing new hair color design and promoting sales by statistically analyzing seasonal changes of hair colors puplished on women's magazines(Vogue Korea, Estetica Korea, Woman Chosun, Ce.ci) from 2003 to 2006. The researching methods were as follows; (1) hair colors published on women's magazines from september 2003 to August 2006 were measured by N.C.S. color reader(4 magazines $\times$10 main hair colors/magazine $\times$ 12 months $\times$ 3 years = 1,440 colors). (2) N.C.S. tone is made of percentage, so measured values and chromas were statistically analyzed by mean, standard deviation, and seasonal deferences were statistically analyzed by t-test and specified on high significant values. But hues were not made of percentage, so these were statistically analyzed by cross tabulation analysis, $x^2$ -test and specified on high significant values. These all had been analyzed by SPSS program(ver. 11.0). The results were as follows; (1) Usually seasonal changes of hair values were significant, specially in foreign licensed magazines, and bright values appeared in S/S and dark values in F/W. (2) Seasonal changes of hair hues were significant only on foreign women's magazines. Therefore seasonal changes of korean hair colors were not significant compared by foreign hair colors because of hardness of color changes of dark black hair and hair damages by hair tints and bleaches and trends of well being and hair care. But hair color changes have been developed gradually and will developed furthermore. So korean hair cosmetic circles have to present hair color trends deferenciated by seasons. And S/S hair values have to be brignt and F/W have to be dark. And new seasonal hair hues matched by korean have to be developed and presented.

• Journal of the Korean Statistical Society
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• 제24권1호
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• pp.77-90
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• 1995

The Lagrange multiplier test statistics for seasonal unit roots are derived and the asymptotic distributions of the derived statistics are obtained. The relationship between the derived LM test statistics and the "DHF" type regression t statistics are shown.are shown.

• 경영과학
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• 제20권1호
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• pp.103-124
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• 2003

The seasonal adjustment is an essential process in analyzing the time series of economy and business. There are various methods to adjust seasonal effect such as moving average, extrapolation, smoothing and X11. One of the powerful adjustment methods is X11-ARIMA Model which is popularly used in Korea. This method was delivered from Canada. However, this model has been developed to be appropriate for Canadian and American environment. Therefore, we need to review whether the Xl1-ARIMA Model could be used properly in Korea. In this study, we have applied the method to the annual sales of refrigerator sales in A electronic company. We appreciated the adjustment by result analyzing the time series components such as seasonal component, trend-cycle component, and irregular component, with the proposed method.