• 한국수자원학회논문집
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• 제38권8호
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• pp.617-629
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• 2005

본 논문은 비단조적으로 변동하는 시계열자료를 단조적으로 변화하는 구간으로 분할하여 경향성을 분석함으로써 자료의 시변동에 대한 동질성을 향상시키고 그에 따라 경향성 분석기법의 탐지력을 향상시킬 수 있다는 가설을 전제로 하고 있다. 이를 검토하기 위한 기법으로서 시계열자료의 변동경향을 파악하기 위한 필터링 방법으로 LOWESS smoothing을 적용하였고, 시계열자료의 경향성분석은 seasonal Kendall test를 적용하였다. 인위적으로 발생시킨 시계열자료와 대청호의 수온, 유량, 기온, 일사량 등의 시계열자료를 대상으로 검토한 결과 비단조적인 변화를 보이는 시계열자료를 단조적인 변화구간으로 분할하여 경향성을 분석함으로써 자료의 변동 경향성과 기울기 판정의 정확도를 높일 수 있었다. 그리고, 자료의 시변동에 대한 동질성 향상은 계절 변동성의 동질성에 대한 변화를 보다 정확하게 분석하는데 도움을 주는 것으로 보였으며 이것은 자연현상에 대한 인간활동의 영향을 고찰할 수 있는 자료로서 앞으로 이에 대한 연구가 더 필요할 것으로 보인다. 본 논문에서 제시한 방법은 시계열자료의 단조적인 경향성을 분석하는 기법들에 대해 적용 가능하며, 이를 통하여 환경변화의 경향성에 대한 보다 정확한 분석과 판단이 가능해질 것으로 기대한다.

• 한국수산과학회지
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• 제5권4호
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• pp.108-114
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• 1972

한국 남해의 동물성 플랑크톤 현존량은 $1963\~1971$년간의 자료로 분석한 결과 63개월을 일주기로 주기 변동을 하고 있으며. 그 주기성은 자기 상관 계수 $\gamma_k$=0.86으로 강한 편이다. 계절 순환 변동은 4월과 10월을 극대기로 하는 쌍봉성 변동을 하며, 그 경향은 대단히 뚜렷한데, 이것은 이 해역에 있어서 식물성 플랑크톤의 양적 소장과 중요한 관련성을 가지는 것으로 고찰된다.

• 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 Ecology and Environment
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• 제31권3호
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• pp.207-211
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• 2008

We investigated the leaf demography of a temperate woody liana, Akebia trifoliata, in a temperate forest in Japan, Akebia is semi-evergreen: some leaves are shed before winter, while others remain through the winter. Previous studies of semi-evergreen species found that variation in leaf life span was caused by variation in the timing of leaf emergence, Leaves that appeared just before winter over-wintered, while leaves appearing earlier were shed, However, it is unclear whether leaves of the same cohort (i.e., leaves that appear at the same time within a single site) show variation in life span under the effect of strong seasonality. To separate variation in life span among the leaves in each cohort from variation among cohorts, we propose a new method - the single leaf diagram, which shows the emergence and death of each leaf. Using single leaf diagrams, our study revealed that Akebia leaves within a cohort showed substantial variation in life span, with some over-wintering and some not. In addition, leaves on small ramets in the understory showed great variation in life span, while leaves on large ramets, which typically reach higher positions in the forest canopy, have shorter lives, As a result, small ramets were semi-evergreen, whereas large ramets were deciduous, The longer lives of leaves on small ramets can be interpreted as a shade-adaptive strategy in understory plants.

• 한국환경과학회지
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• 제14권11호
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• pp.1049-1056
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• 2005

[ $NO_2$ ] concentration characteristics of Busan metropolitan city was analysed by statistical method using hourly $NO_2$ concentration data$(1998\~2000)$ collected from air quality monitoring sites of the metropolitan city. 4 representative regions were selected among air quality monitoring sites of Ministry of environment. Concentration data of $NO_2$, 5 air pollutants, and data collected at AWS was used. Both Stepwise Multiple Regression model and ARIMA model for prediction of $NO_2$ concentrations were adopted, and then their results were compared with observed concentration. While ARIMA model was useful for the prediction of daily variation of the concentration, it was not satisfactory for the prediction of both rapid variation and seasonal variation of the concentration. Multiple Regression model was better estimated than ARIMA model for prediction of $NO_2$ concentration.

• 한국환경과학회지
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• 제7권1호
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• pp.67-73
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• 1998

Surface heat budget of the Deukryang Bay from July 1, 1992 to September 12, 1993 is analyzed by us- ing the meteorological data (by Changhung Observatory and Mokpo Meteorological Station) and oceanogaphical data (by Research Center for Ocean Industrial Development. Pukyong National University). Each flux element at the sea surface which has annual variation Is derived with application of an aerodynamical bulk method and empirical formulae. The solar radiation Is the maximum In spring and sensible heat are the maximum in autumn and water. and minimum in summer The heat .storage rate is calclilated by using the rate of water temperature variation according to the depth. The oceanic transport heat is estimated as a residual. The net heat flux, the heat storage rate are positive In spring and summer, while they are negative in autumn and winter. The oceanic transport heat Is convergence In winter and divergence In the rest of seasons.

• 대한토목학회논문집
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• 제31권1C호
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• pp.29-38
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• 2011

소형 콘은 해상도가 뛰어나 국부영역의 탐지를 위하여 다양하게 활용되고있다. 소형 콘은 변형률계 부착 면적이 부족하여 half-bridge 형태로 회로를 구성하고 있으며, 이는 주변온도 변화에 의하여 민감하게 반응하는 것으로 알려져있다. 본 논문의 목적은 이러한 온도영향을 해소하기 위하여 소형 콘의 온도보상 기법에 관한 연구를 수행하는 것이다. 본 연구를 수행하기 위하여 직경과 길이가 각각 15mm 그리고 56mm인 소형 콘을 개발하였다. 로드셀은 온도변화만을 반영할 수 있는 공간을 확보하기 위하여 후면으로 54mm 연장하여 제작되었다. 온도보상회로는 스트레인 게이지를 선단저항 부분, 주면마찰 부분 그리고 연장한 로드셀에 부착하여 소형 콘 내에서 휘트스톤 브리지(Wheatstone bridge) 회로를 구성하였다. 소형 콘의 일반적 회로구성인 half-bridge도 내부에 함께 구성하여 상호간의 결과값을 비교 및 고찰하였다. 여름과 겨울의 계절적인 온도변화에 따라 측정값의 오차를 검증하기 위하여 계절적 온도 변화 실험을 수행하였다. 또한 지반다짐 실험으로 지반의 상대밀도를 증가시켜 관입 시 주변 온도변화에 따라 측정값 변화도 관찰하였다. 측정결과 온도보상회로를 이용하여 측정한 값은 half-bridge 회로로 측정한 값과 차이를 보였으며, 더욱 안정화되고 이상적인 경향을 보였다. 본 논문은 소형 콘 사용시 온 도 영향에 대한 문제를 해소하고 더욱 신뢰성 높은 측정값을 획득할 수 있는 기법에 대하여 제시하였다.

• Journal of Nutrition and Health
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• 제29권5호
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• pp.507-516
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• 1996

This study was undertaken to estimate seasonal variation of riboflavin status and investigate the relationship between riboflavin intake and its biochemical status in rural women. Dietary intake was measured by determining both 24hr recall method and conventient method. The riboflavin intake was also estimated by food frequency method. Ribofiavin biochemeical status was assessed by erythrocyte glutathione reductase activity coefficient(EGR AC) and urinary riboflavin excretion. All information was repeatly collected in three seasons ; farming season (June), harvest season(October), nonfarming season(February). Mean daily riboflavin intake was below RDA for Koreans in all seasons. Cereal & pulse, vegetable were the primary sources of riboflavin intake and provided above 60% of the total dietary riboflavin intake in all seasons. Riboflavin biochemical status was significantly different among seasons(EGR AC P<0.005, 24hr urinary riboflavin excretion P<0.05), and riboflavin biochemical deficiency was highest in February. The mean values of EGR AC revealed riboflavin deficiency in all seasons. However the mean values of urinary riboflavin excretion were within the normal range except 24hr urinary riboflavin excretion in February. On the basis of EGR AC criteria, 44.7% of subjects were at risk of deficiency in June, 44.7% in October, 81.6% in February. Result of individual riboflavin status assessed by EGR AC or 24hr urinary riboflavin excretion criteria was quite alike. Urinary riboflavin excretion per gram of creatinine underestimated riboflavin deficiency. Significant correlations were observed among biochemical indexes. It also appeared that riboflavin intake measured by food frequency method showed significant correlation with biochemical indexes, especially high correlation with EGR AC (P<0.001). The results indicated that the prevalence of riboflavin deficiency seems to be high among rural women in all seasons and the inadequacy of dietary riboflavin intake was reflected in the abnormalcy of riboflavin biochemical status assessed by EGR, AC. Therefore EGR AC seems to be more sensitive measure of impaired riboflavin status compared to urinary excretion.

• 한국환경보건학회지
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• 제18권1호
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• pp.63-68
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• 1992

This study was performed to investigate the seasonal variation of the composition of domestic solid wastes and the characteristics of the leachate sampled in In-Cheon sanitary landfill site. The results were as follows 1. Combustible part was larger than incombustible part of the domestic solid wastes in spring and sumer. 2. The food waste was major source of solid wastes in In-Cheon city as 36.5%, and its variation by seasons was negligible. 3. BOD of the leachate was in the range of 853~7, 350mg/l, and fluctuated by seasons. 4. The mean of COD$_{cr}$ Was 5, 044mg/l, the mean of COD$_{Mn}$ was 2, 212mg/l. Namely, the method by $K_{2}Cr_{2}O_{7}$ was more sensitive than the method by KMnO$_{4}$. 5. TOC was in the range of 773~3, 958mg/l, it was lower than BOD.

• 대기
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• 제17권1호
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• pp.27-44
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• 2007

The purpose of this study is to investigate predictability of the seasonal simulation by the METRI (Meteorological Research Institute) AGCM (Atmospheric General Circulation Model), which is a long-term prediction model for the METRI 3-month prediction system. We examine the performance skill of climate simulation and predictability by the analysis of variance of the METRI AGCM, focusing on the precipitation, 850 hPa temperature, and 500 hPa geopotential height. According to the result, the METRI AGCM shows systematic errors with seasonal march, and represents large errors over the equatorial region, compared to the observation. Also, the response of the METRI AGCM by the variation of the sea surface temperature is obvious for the wintertime and springtime. However, the METRI AGCM does not show the significant ENSO-related signal in autumn. In case of prediction over the east Asian region, errors between the prediction results and the observation are not quite large with the lead-time. However, in the predictability assessment using the analysis of variance method, longer lead-time makes the prediction better, and the predictability becomes better in the springtime.