Earticle

클로버는 잔디의 대표적 유해 식물로 양지식물인 잔디보다 일찍 생육활동을 시작하여 잔디의 상부에 수관을 형성하고 잔디의 광합성과 성장을 방해한다. 이로 인해 두 식생종 간 경쟁에서 대부분, 클로버 영역은 확산되고 잔디의 경우는 훼손과 고사가 진행되게 된다. 훼손된 부분은 장마 및 생장 휴면 기간 중, 토양표출 확산으로 전개되어 잔디 복구에 심리적 스트레스 및 많은 경제적 부담을 초래하고 있다. 본 연구의 목적은 잔디의 대표적 유해식물인 클로버를 구분하고 클로버의 확산에 따른 훼손지역 분포, 퇴치 전·후의 식생변화 추이를 고찰하는 것이다. 이를 위해 RGB, BG-NIR 센서를 탑재한 융·복합 드론기반 영상을 활용, 3가지 식생지수의 시계열 분석을 통해 선별적 퇴치를 위한 식생구분, 복구전략 수립을 위한 잔디 훼손 분포 등을 고찰하였다. 특히, 인력 및 기기에 의한 선별적 제초 및 예초 전·후, 클로버의 생태변화 추이를 시계열로 분석하였다. 또한, 잔디와 클로버의 성장 중반기 기간 중, 식생 종간 구분 방안도 모색하였다. 연구결과, 잔디와 클로버 생육 특성에 따른 RGB 및 BGNIR 드론영상의 MGRVI 및 NDVI, MSAVI 지수의 시계열 분석을 통해 잔디 훼손과 클로버 퇴치 후 변화 추이 분석의 활용성을 확인하여 잔디 유해 잡초에 대한 효율적 관리의 활용 가능성을 입증할 수 있었다.

The Rabbit grass(Trifolium Repens, call it 'Clover') is a representative harmful plant of lawn, and it starts growing earlier than lawn, forming a water pipe on top of the lawn and hindering the photosynthesis and growth of the lawn. As a result, in competition between lawn and clover, clover territory spreads, but lawn is damaged and dried up. Damage to the affected lawn area will accelerate during the rainy season as well as during the plant's rear stage, spreading the area where soil is exposed. Therefore, the restoration of damaged lawn is causing psychological stress and a lot of economic burden. The purpose of this study is to distinguish clover which is a representative harmful plant on lawn, to identify the distribution of damaged areas due to the spread of clover, and to review of changes in vegetation before and after the eradication of clover. For this purpose, a time series analysis of three vegetation indices calculated based on images of convergence Drone with RGB(Red Green Blue) and BG-NIR(Near Infra Red)sensors was reviewed to identify the separation between lawn and clover for selective eradication, and the distribution of damaged lawn for recovery plan. In particular, examined timeseries changes in the ecology of clover before and after the weed-whacking by manual and brush cutter. And also, the method of distinguishing lawn from clover was explored during the mid-year period of growth of the two plants. This study shows that the time series analysis of the MGRVI(Modified Green-Red Vegetation Index), NDVI(Normalized Difference Vegetation Index), and MSAVI(Modified Soil Adjusted Vegetation Index) indices of drone-based RGB and BG-NIR images according to the growth characteristics between lawn and clover can confirm the availability of change trends after lawn damage and clover eradication.

연구지역인 강원도 삼척시 도계읍의 사면은 지형변화가 발생하는 지역으로 2009년 사면 절취공사를 수행하여 사면경사완화공법이 적용되었다. 하지만 사면의 상부에 위치한 폐석적치장의 영향으로 2개월 뒤 절취사면의 상부를 확장하여 안정성을 도모하였다. 최근 사면 하부에 위치한 옹벽의 배부름 현상이 발견되고 절취사면의 균열이 나타나 지형변화가 다시 발생하고 있는 것으로 보이고 있다. 이러한 문제를 파악하기 위하여 본 연구에서는 UAV를 이용하여 사진측량을 수행해 지형변화가 발생하는지 확인하고자 하였다. 2019년 4월과 10월 각각 정사영상을 추출하고 Digital Surface Model(DSM)를 추출하여 고해상도의 지형변화를 비교 분석하였다. 10월의 지형은 4월의 지형형상을 그대로 유지한채 앞으로 밀려 나간 모습을 보여 이러한 지형변화는 땅밀림인 것으로 분석하였다.

The study area is a slope in Dogye-eup, Samcheok-si, Gangwon-do. The cutting method was applied to this slope for stabilization in 2009 due to the influence of the waste-rock dump located at the top of slope. Recently, soil cracks and creep have occurred on this slope, and the drainage channel was damaged. Therefore, it was analyzed the topography change through photogrammetry using a UAV. Orthophotos were taken in April and October 2019 respectively. From the Orthophots, Digital Surface Model (DSM) was extracted. Time series analysis was performed by comparing each DSM. The topography of October was pushed forward while maintaining the topography of April. Through these features, it is judged that the soil creep is occurring in this study area.

기초연구 분야는 정부의 적극적인 지원으로 양적 확대가 큰 폭으로 이루어지는 반면, 체계적인 투자계획이나 데이터에 기반한 재정소요를 제시하는 연구 및 정책자료가 전무하여 관련 연구가 요구되는 시점이다. 이에 본 연구는 시계열 예측모형을 활용하여 기초연구지원사업의 향후 재정소요를 전망하였다. 기초연구분야의 특성을 포함한 다양한 요인들을 종합적으로 고려하기 위하여 시간에 따른 단일 종속변수의 값을 예측하는 ARIMA 모형이 아닌, 다변수의 영향을 반영할 수 있는 ARIMAX 모형을 선택하였다. 모형 적합성 판단을 위해 ARIMAX 모형과 ARIMA 모형의 예측값을 비교한 결과 ARIMAX 모형에서 예측오차율이 개선됨을 확인하였다. ARIMAX 모형에 기반하여 2017년에서 2021년까지 5년 간의 기초연구지원사업 재정소요를 전망하였다. 본 연구는 기초연구지원사업의 재정소요를 통계적 접근방법인 시계열모형을 적용해 전망한 시범적 연구를 수행하였다는 점과, 단변량이 아닌 다변량을 고려하여 예측력을 개선했다는 점에서 의의를 지닌다. 또한 현 정부 국정과제인 '기초연구 예산 2배 확대' 등 기초연구 투자의 중요성이 꾸준히 강조되는 정책기조를 고려할 때 향후 기초연구 투자전략 수립 시 참고자료로 활용 될 수 있다.

In the basic research field, quantitative expansion is carried out with active support from the government, but there is no research and policy data suggesting systematic investment plans or data-based financial requirements yet. Therefore, this study predicted future financial requirements of basic research support programs by using time series prediction model. In order to consider various factors including the characteristics of the basic research field, we selected the ARIMAX model which can reflect the effect of multi valuable factors rather than the ARIMA model which predicts the value of single factor over time. We compared the predictions of ARIMAX and ARIMA models for model suitability and found that the ARIMAX model improves the prediction error rate. Based on the ARIMAX model, we predicted the fiscal spending of basic research support programs for five years from 2017 to 2021. This study has significance in that it considers the financial requirements of the basic research support programs as a pilot research conducted by applying a time series model, which is a statistical approach, and multi-variate rather than single-variate. In addition, considering the policy trends that emphasize the importance of basic research investment such as 'the expansion of basic research budget twice', which is the current government's national policy task, it can be used as reference data in establishing basic research investment strategy.

초고빈도(ultra high frequency; UHF)시계열의 함수적 변동성 측정을 위한 최신 기법인 함수적 변동성 functional GARCH : fGARCH(1, 1) 모형을 소개하고 설명하였다. 실증분석을 위해 R-code fGARCH(1, 1) 프로그램을 KOSPI/현대차 초고빈도 수익률 자료에 적합하여 예시하였다.

When a financial time series consists of daily (closing) returns, traditional volatility models such as autoregressive conditional heteroskedasticity (ARCH) and generalized ARCH (GARCH) are useful to figure out daily volatilities. With high frequency returns in a day, one may adopt various multivariate GARCH techniques (MGARCH) (Tsay, Multivariate Time Series Analysis With R and Financial Application, John Wiley, 2014) to obtain intraday volatilities as long as the high frequency is moderate. When it comes to the ultra high frequency (UHF) case (e.g., one minute prices are available everyday), a new model needs to be developed to suit UHF time series in order to figure out continuous time intraday-volatilities. Aue et al. (Journal of Time Series Analysis, 38, 3-21; 2017) proposed functional GARCH (fGARCH) to analyze functional volatilities based on UHF data. This article introduces fGARCH to the readers and illustrates how to estimate fGARCH equations using UHF data of KOSPI and Hyundai motor company.

The purpose of this research is to find out the differences of participation in common activities and life satisfaction of Swedish senior cohousing residents between the years of 2001 and 2010 by conducting a longitudinal study. The same questionnaire were surveyed nationwide to 186 residents of 8 Senior $G{\aa}rden$ cohousings in 2001 and 127 residents of 4 +40 cohousings in 2010, resulting in total 313 respondents' data. The results show that the +40 cohousing respondents are more likely than Senior $G{\aa}rden$ cohousing respondents to participate in all common activities, especially common meals and common coffee meetings. However, the subjective evaluation of the quantity as well as the contents of participating in common activities does not statistically differ in the two groups and life satisfaction is similarly high with a few differences. The +40 cohousing respondents are less likely to stay at and more likely to move into age-mixed cohousing if they have a chance to move when compared to their Senior $G{\aa}rden$ cohousing counterparts. The result of this research reveals that the general characteristics of senior cohousing residents have been changed and they have become more likely to be active participants of various common activities and have high life satisfaction.

낙동강 하구역은 과거 30여 년 간 하구둑, 산업단지, 항구 등의 건설로 인해 인위적인 영향을 받아왔다. 낙동강의 이러한 변화는 연안사주의 기능에 영향을 줄 수 있고, 환경적인 변화를 야기하고 있다. 따라서 낙동강 하구의 변화를 관측하는 것은 매우 중요하다고 판단된다. 이에 따라 본 연구에서는 1984년부터 2015년까지 Landsat TM, ETM+ 영상을 기반으로 낙동강 하구의 연안사주의 지형의 면적변화를 관측하고자 한다. 또한, 조위에 따라 현재 존재하고 있는 사주 하부의 사질퇴적물이 나타나는 면적을 분석하고자 한다. 이는 사주 하부에 축적된 사질 퇴적물의 높이와 양을 추정할 수 있을 것이며, 이러한 결과는 향후 사구의 지형변화를 예측하는데 기반이 될 것으로 기대된다. 따라서 본 연구에서는 31년간의 Landsat 영상을 기반으로 국립해양조사원에서 제공한 조위 값을 이용하여 조위에 따른 하구역 지형의 면적변화를 연구하였다. 1지역은 3,015 m² , 2지역은 167,550 m² , 3지역은 14,596 m²만큼의 평균 면적변화가 나타난 것으로 계산되었다. 이 결과는 낙동강 퇴적물의 지속적인 변화를 관측하는데 매우 유용할 것으로 판단된다.

Nakdong river barrage was affected by artificial interference such as construction of port, industrial complex and estuary barrage. This change in Nadong river lead to environmental changes and affected the ability of barrier islands. Therefore, it is decided that the observation of changes in the Nakdong river estuary is very important. In this paper, the topographic change of the Nakdong river barrage observe based on Landsat TM, ETM+ images from 1984 to 2015. In addition, this study tried to conduct a comparative analysis on the area for change of sandy sediment according to tide level. This results could estimate height and volume about sandy sediment accumulated on the lower sand dune. Also, these results are expected to be the basis for prediction of the changing topography of the sand dune. The area of the average change in region 1,2,3 was calculated as 3,015m², 167,550m², 14,596m². This result is expected to be very useful for the continuous observation for sediment changes of Nakdong river.

There is a need to analyze unconfined groundwater behavior since the demand of groundwater use has been increasing. While unconfined groundwater temperature is tend to be affected by air temperature, it is hard to find an empirical study in South Korea. In this research, we try to determine the relationship between daily average air temperature and daily average groundwater temperature by time-sequential analysis of groundwater monitoring wells in Galshin basin in Yesan-Gun, Chungcheongnam-Do. In addition, models to estimate groundwater temperature from air temperature were developed. In this research 101-day moving average method with measured air temperature is used to estimate groundwater temperature. To verify the developed model, estimated values of average groundwater temperature with 101 moving average are compared to the measured data from September 10 2007 to September 9 2008. And, Nash-Stucliff Efficiency and Coefficient of Determination were 0.970 and 0.976, therefore it was concluded that the model allowing groundwater temperature estimation from air temperature is with reasonable applicability.

Time series of the dynamic response of a slender marine structure was predicted using quadratic Volterra series. The wave-structure interaction system was identified using the NARX(Nonlinear Autoregressive with Exogenous Input) technique, and the network parameters were determined through the supervised training with the prepared datasets. The dataset used for the network training was obtained by carrying out the nonlinear finite element analysis on the freely standing riser under random ocean waves of white noise. The nonlinearities involved in the analysis were both large deformation of the structure under consideration and the quadratic term of relative velocity between the water particle and structure in Morison formula. The linear and quadratic frequency response functions of the given system were extracted using the multi-tone harmonic probing method and the time series of response of the structure was predicted using the quadratic Volterra series. In order to check the applicability of the method, the response of structure under the realistic ocean wave environment with given significant wave height and modal period was predicted and compared with the nonlinear time domain simulation results. It turned out that the predicted time series of the response of structure with quadratic Volterra series successfully captures the slowly varying response with reasonably good accuracy. It is expected that the method can be used in predicting the response of the slender offshore structure exposed to the Morison type load without relying on the computationally expensive time domain analysis, especially for the screening purpose.

In this paper, we investigate the statistical correlation of the time series for temperature measured at the heat box in the automobile drying process. We show, in terms of the sample variance, that a significant non-linear correlation exists in the time series that consist of absolute temperature changes. To investigate further the non-linear correlation, we utilize the volatility, an important concept in the financial market, and induce volatility time series from absolute temperature changes. We analyze the time series of volatilities in terms of the de-trended fluctuation analysis (DFA), a method especially suitable for testing the long-range correlation of non-stationary data, from the correlation perspective. We uncover that the volatility exhibits a long-range correlation regardless of the window size. We also analyze the cross correlation between two (inlet and outlet) volatility time series to characterize any correlation between the two, and disclose the dependence of the correlation strength on the time lag. These results can contribute as important factors to the modeling of forecasting and management of the heat box's temperature.

The purpose of this study was to evaluate the current state of foodservice and clinical nutrition management in a hospital-based nutrition department. Nutritional guidelines and survey reports of hospital evaluation programs from 2004 to 2009 were analyzed. In total, 275 hospitals in the first period and 288 hospitals in the second period were evaluated. The division of knife and chopping board use decreased from 97.2% in 2005 to 89.7% in 2008, the maintenance of a proper freezer temperature (below $-18^{\circ}C$) increased from 82.1% in 2004 to 97.7% in 2007 (88.9% to 97.4% from large hospitals and 69.8% to 86.5% from small/medium hospitals in 2005 and 2008, respectively). In tube-feeding management, the performance rate of material cold storage and the offer rate of tube-feeding were 65.9% and 94.2% in 2007, respectively. The cold storage of material, proper use within 24 hours after opening or production, and the use of an appropriate label were 47.3%, 71.2% and 67.2% in 2009, respectively. The rate of a management system for undernourished patients was 86.0% in 2007 (56.4% for large hospitals, 18.9% for small/medium hospitals) and 14.3% in 2009. In standards of nutrition support management, the performance rates of constructing a nutrition support team, the nutrition support team activity, and organizing multidisciplinary team were 66.7%, 43.6%, and 64.1% respectively, in 2004. For large hospitals, those rates were 61.1%, 36.1%, and 58.3%, in 2005, 93.0%, 62.8%, and 91.9% in 2007, and 69.2%, 43.6%, and 69.2% in 2008, respectively. The results of this study suggest standards on sanitary foodservice preparation, production, and tube-feeding production need to correspond with HACCP regulations for small/meidium hospitals in standards of a healthcare accreditation system. It will be necessary to understand the operating conditions of nutrition departments in convalescent hospitals, psychiatric hospitals, and geriatrics hospitals. As the application of accreditation is required from 2013, standards will need to be improved and continuously updated for healthcare accreditation.

보의 건설 및 하천 단면의 증가는 하천 수위 상승과 호우기 유출량의 증가를 가져왔다. 낙동강 중하류에 설치된 23개의 지하수 관측망 지하수위 자료를 사용하여 보 담수 전후의 지하수위 시계열 변동 유형의 변화를 분석하였다. 월평균 지하수위 자료를 토대로 담수 전후의 지하수위를 비교한 결과 보의 직상류 주변 지역에서 지하수위 변동이 가장 크게 나타났으며, 8월의 경우 하천 수위 조절 효과로 월평균 지하수위가 0.1 m 감소하였으나 10월에는 1.3 m 상승한 것으로 나타났다. 지하수위 시계열 자료와 하천 수위 자료를 사용하여 군집분석을 실시한 결과, 담수 이전에는 7개 지하수 관측망의 자료가 하천 수위와 유사성 거리가 가까운 그룹이었으나, 담수 이후에는 14개로 증가하여 하천 수위와 유사한 그룹의 범위가 넓어졌다. 지하수위 시계열에 대한 주성분분석 결과, 담수 이전에는 하천 변동성을 대표하는 주성분(주성분 1과 주성분 2)의 설명력이 총 82%이었으나, 담수 이후에는 하천 변동성을 설명하는 주성분(주성분 1)의 설명력이 45%로 줄어들어 지하수위 자료를 설명하는데 하천 요인의 기여도가 줄고 인위적인 양수 등과 같은 기타 요인의 기여도가 높아졌다. 이와 같이 변화되는 수문 환경에 대비하여 지속적인 조사 및 관측이 필요하며, 하천 주변에서는 지표수와 연계되는 지하수 관리 정책이 수립될 필요가 있다.

Increasing the river cross-section by barrage construction causes rises in the average river water levels and discharge rates in the rainy season. The time series patterns for groundwater levels measured at 23 riverside monitoring wells along the lower Nakdong River are compared for two cases: before and after water-filling at the Changnyeong-Haman Barrage. Monthly average groundwater levels indicate a distinct increase in groundwater levels in the upstream riverside close to the barrage. River-water level management by barrage gate control in August, during the rainy season, resulted in a 0.1 m decrease in groundwater levels, while water-filling at the barrage in December caused a 1.3 m increase in groundwater levels. The results of hierarchical cluster analysis indicate that seven groundwater monitoring wells and river water levels were in the same group before barrage construction, but that this number increased to 14 after barrage construction. Principal component analysis revealed that the explanation power of two principal components corresponding to river fluctuation, PC1 and PC2, was approximately 82% before barrage construction but decreased to 45% after construction. This finding indicates that the effect of the river level component that contributes to change in groundwater level, decreases after barrage construction; consequently, other factors, including groundwater pumping, become more important. Continuous surveying and monitoring is essential for understanding change in the hydrological environment. Water policy that takes groundwater-surface water interaction into consideration should be established for riverside areas.

본 논문에서는 금융시계열자료를 분석하는데 있어서 비대칭 변동성과 지속성효과를 가지는 시계열 자료에 적합한 모형인 I-TGARCH를 제시하였다. 국내 금융시계열 자료를 바탕으로 I-TGARCH의 적합성을 검증하기 위해 기존연구에서 많이 쓰이고 있는 TGARCH, IGARCH, EGARCH 모형과 함께 분석하여 비교하였다. 그 결과, I-TGARCH모형이 경제 위기의 영향으로 변동성이 커진 현재의 주가 분석에 적합하다는 사실을 알 수 있었다. 특히, 비대칭적 변동성의 특징을 관찰하기 위해 News impact curve를 이용해서 호재와 악재에 다르게 반응하는 주가변동에 대해서 알아본 결과, 대부분의 주가변동이 비대칭적인 경향을 보이고 있다는 사실을 관찰했다. 또한, 실제 일별수익율 데이터를 I-TGARCH 모형에 적합시키고 모형이 얼마나 효율적인지를 검정하였다. I-TGARCH의 적합성을 검증하기 위해 VaR의 사후검정을 이용하였다. 그 결과 대부분의 금융시계열이 I-TGARCH가 다른 비교모형 보다 우수하거나 비슷한 것으로 검증되었다. 이는 변동성의 비대칭성을 고려한 TGARCH에서 지속-변동성 효과(persistent effect) 또한 존재할 수 있다는 사실을 금융시계열자료를 통해 알 수 있었다.

TGARCH models characterized by asymmetric volatilities have been useful for analyzing various time series in financial econometrics. We are concerned with persistent volatility in the TGARCH context. Park et al. (2009) introduced I-TGARCH process exhibiting a certain persistency in volatility. This article applies I-TGARCH model to various financial time series in Korea and it is obtained that I-TGARCH provides a better fit than competing models.

In order to examine the effects of micrometeorological and climatological influences on urban scale particulate air pollutants observed in Busan, power spectrum analysis was applied to the observed particulate matter with aerodynamic diameter ${\le}10{\mu}m$ ($PM_{10}$) for the period from 1991 to 2006. Power spectrum analysis has been employed to the daily mean $PM_{10}$ concentrations obtained at 13 sites to identify different scales of periodicities of $PM_{10}$ concentrations. The results show that, aside from the typical and well-known periodicities such as diurnal and annual variations caused by anthropogenic emission influences, another two significant peaks of power spectrum density were identified: 21 day and $3{\sim}4$ year of periodicities. Cospectrum analysis indicates that the intraseasonal 21 day periodicity are found to be negatively correlated with wind speed and surface pressure but shows consistently positive with relative humidity and temperature. This result implied that 21 day periodicity is presumably relevant to the secondary aerosol formation processes through the photochemical reaction that can be subsequently resulted from hygroscopic characteristics of aerosol formation. However, the interannual $3{\sim}4$ year of periodicity is found to have positive correlation with pressure, and negative with temperature and relative humidity, which is rather consistent with both characteristics of air mass during the Asian dust event and the occurrence frequency of Asian dust whose periodicities have been recorded inter-annually over the Korean peninsula.

The traditional demand prediction was based on the technique wherein electric power corporations made monthly or seasonal estimation of electric power consumption for each area and subscription type for the next one or two years to consider both seasonally generated and local consumed amounts. Note, however, that techniques such as pricing, power generation plan, or sales strategy establishment were used by corporations without considering the production, comparison, and analysis techniques of the predicted consumption to enable efficient power consumption on the actual demand side. In this paper, to calculate the predicted value of electric power consumption on a short-term basis (15 minutes) according to the amount of electric power actually consumed for 15 minutes on the demand side, we performed comparison and analysis by applying a 15-minute interval prediction technique to the average and that to the time series analysis to show how they were made and what we obtained from the simulations.

The purpose of this study is analyzing temporal flow about 20 detailed performance items in the "Housing Performance Grading Indication System". This study try to figure out situations according grade in detailed performance item and to analyze change item about 112 cases(2 cases in 2006, 15 cases in 2007, 46 cases in 2008, 49 cases in 2009), from January 9, 2006 which system is undertaken, to October, 2009. This system consists of 5 main performance section, 14 performance categories and 20 detailed performance items. 5 main performance parts are Noise and Acoustics(Light-weight impact sound control, heavy-weight impact sound control, sound control of toilet, sound control of party wall), Long-life(flexibility, remodeling & maintenance, durability), Landscape & Indoor Environment(landscape, formaldehyde control & ventilation, daylighting, thermal environment), Welfare & Barrier-free(playground and community center, welfare space, barrier-free design), Fire Safety(fire safety, safe place, fire-resisting quality). Total efficiency about housing can understand systematically of 20 perfomance items though this research.

본 논문에서는 단일 색인을 사용하는 임의 계수의 이동평균 변환 지원 서브시퀀스 매칭 방법을 제안한다. 단일 색인을 사용함으로써, 제안한 방법은 색인 저장 공간 및 색인 관리의 오버헤드를 크게 줄일 수 있다. 이동평균 변환은 시계열 데이타 내의 노이즈 영향을 감소시킴으로써, 시계열 데이타 전체의 경향을 파악하는데 매우 유용하다. 그런데, 기존 연구에서는 임의 계수를 지원하기 위해 여러 색인을 생성해야 하고, 이에 따라 색인 저장 공간의 오버헤드와 색인 관리의 오버헤드가 발생하는 문제점이 있다. 본 논문에서는 우선 이동평균 변환의 정의를 확장한 다계수 이동평균 변환(poly-order moving average transform) 개념을 제시한다. 다계수 이동평균 변환이란, 각 윈도우를 하나의 이동평균 계수에 대해서 이동평균 변환하는 것이 아니라, 여러 계수에 대해서 이동평균 변환하여 윈도우의 집합을 구성하는 변환으로서, 이동평균 변환의 정의를 여러 계수로 구성된 집합에 대해서 확장한 것이다. 다음으로, 이러한 다계수 이동평균 변환 개념을 사용한 서브시퀀스 매칭 방법의 이론적 근거인 정확성을 정리로서 제시하고 증명한다. 또한, 다계수 이동평균 변환을 기존 서브시퀀스 매칭 연구인 Faloutsos 둥의 방법 및 DualMatch에 각각 적용하여, 두 가지 이동평균 변환 지원 서브시퀀스 매칭 방법을 제시한다. 실험 결과, 제안한 두 가지 서브시퀀스 매칭 방법은 모든 경우에 있어서 순차 스캔보다 성능을 크게 향상시킨 것으로 나타났다. 실제 주식 데이타에 대한 실험 결과, 제안한 방법은 순차 스캔에 비해서 평균 22.4배${\~}$33.8배까지 성능을 향상시킨 것으로 나타났다. 또한, 각 계수에 대해 모두 색인을 생성하는 경우와 비교할 때, 성능 저하는 매우 적은 반면 필요한 색인 공간은 크게 줄인 것으로 나타났다(일곱 개의 계수를 사용한 경우, 성능 저하는 평균 $9\%{\~}42\%$에 불과한 반면 색인 공간은 약 1/7.0로 크게 줄인다). 이와 같이 성능 측면과 색인 공간 및 관리 측면에서의 우수성에 덧붙여, 제안한 방법은 이동평균 변환 이외의 다른 변환을 지원하는 서브시퀀스 매칭으로 일반화 될 수 있는 장점이 있다 따라서, 제안한 방법은 이동평균 변환을 포함하는 많은 다른 종류의 변환을 지원하는 서브시퀀스 매칭에 폭넓게 적용되는 우수한 연구결과라 사료된다.

We propose a single Index approach for subsequence matching that supports moving average transform of arbitrary order in time-series databases. Using the single index approach, we can reduce both storage space overhead and index maintenance overhead. Moving average transform is known to reduce the effect of noise and has been used in many areas such as econometrics since it is useful in finding overall trends. However, the previous research results have a problem of occurring index overhead both in storage space and in update maintenance since tile methods build several indexes to support arbitrary orders. In this paper, we first propose the concept of poly-order moving average transform, which uses a set of order values rather than one order value, by extending the original definition of moving average transform. That is, the poly-order transform makes a set of transformed windows from each original window since it transforms each window not for just one order value but for a set of order values. We then present theorems to formally prove the correctness of the poly-order transform based subsequence matching methods. Moreover, we propose two different subsequence matching methods supporting moving average transform of arbitrary order by applying the poly-order transform to the previous subsequence matching methods. Experimental results show that, for all the cases, the proposed methods improve performance significantly over the sequential scan. For real stock data, the proposed methods improve average performance by 22.4${\~}$33.8 times over the sequential scan. And, when comparing with the cases of building each index for all moving average orders, the proposed methods reduce the storage space required for indexes significantly by sacrificing only a little performance degradation(when we use 7 orders, the methods reduce the space by up to 1/7.0 while the performance degradation is only $9\%{\~}42\%$ on the average). In addition to the superiority in performance, index space, and index maintenance, the proposed methods have an advantage of being generalized to many sorts of other transforms including moving average transform. Therefore, we believe that our work can be widely and practically used in many sort of transform based subsequence matching methods.

최근 유해성이 강한 지표오존농도가 대기환경의 주요한 문제로 부각되고 있다. 본 연구에서는 경기도 평택과 서울 정동지역의 오존농도를 설명 변수를 사용할 수 있는 다변량 시계열 모형인 ARE(자기회귀오차) 모형으로 분석하였다. ARE모형에서는 오존 전체자료를 사용한 전체모형과 오존농도가 41ppb 이상 되는 자료를 사용한 부분모형 두 가지 모형을 비교하였다. ARE의 오존농도 설명변수로는 오존농도와 연관 있는 8종류의 기상자료와 4종류의 대기오염자료를 고려하였다. 기상자료의 8가지 설명변수로 일 최고온도, 일사량, 풍속, 상대습도, 강수량, 이슬점온도, 수증기압, 운량 자료를 사용하였다. 대기오염자료의 4가지 설명변수로는 아황산가스(SO2), 이산화질소(NO2), 코발트(CO)와 프로메툼 10(PM10)를 사용하였다.

This study is performed to examine the relationship between air pollution exposure and mortality in Daejeon for the years of 1998 - 2001. Daily counts of death were analyzed by general additive Poisson model, with adjustment for effects of seasonal trend, air temperature, humidity, and day of the week as confounders in a nonparametric approach. Daily death counts were associated with CO(4 day before), $O_3$(current day), $PM_10$(4 day before), $NO_2$(6 day before), $SO_2$(2 day before). Increase of $31.07{\mu}g/m^3$(interquartile range) in $PM_10$ was associated with 2.0 % (95% CI = 0.5 % - 3.5 %)) increase in the daily number of death. This effect was greater in children(less than 15 aged) and elderly(more than 65 aged). We concluded that Daejeon had 2 - 4 % increase in mortality in association with IQR in air pollutants. Daily variations in air pollution within the range currently occurring in Daejeon might have an adverse effect on daily mortality. These findings also support the hypothesis that air pollution at levels below the current ambient air quality standards of Korea except PM10, is harmful to sensitive subjects, such as children or elderly.

There are so many methods to estimate the groundwater recharge. These methods can be categorized into four groups. First groupis related to the water balance analysis, second group is concerned with baseflow/springflow recession, and third group is interested in some types of tracers; environmental tracers and/or temperature profile. The limitation of these types of methods is that the estimated results of recharge are presented in the form of an average over some time period. Forth group has a little different approach. They use the time series data of hydraulic head and specific yield evaluated from field test, and the results of estimation are described in the sequential form. But their approach has a serious problem. The estimated results in forth typeof methods are generally underestimated because they cannot consider the discharge phase of water table fluctuation coupled with the recharge phase. Ketchum el. at. (2000) proposed calibrated method, considering recharge- and discharge-coupled water table fluctuation. But the dischargeis considered just as the areal average with discharge rate. On the other hand, there are many methods to estimate the source wavelet with observed data set in geophysics/signal processing and geophysical methods are rarely applied to the estimation of groundwater recharge. The purpose this study is the evaluation of the applicability of one of the geophysical method in the estimation of sequential recharge rate. The applied geophysical method is called minimum entropy deconvolution (MED). For this purpose, numerical modeling with linearized Boussinesq equation was applied. Using the synthesized hydraulic head through the numerical modeling, the relative sequenceof recharge is calculated inversely. Estimated results are very concordant with the applied recharge sequence. Cross-correlations between applied recharge sequence and the estimated results are above 0.985 in all study cases. Through the numerical test, the availability of MED in the estimation of the recharge sequence to groundwater was investigated

본 연구에서는 신경망 모형을 이용한 시계열 예측에 있어서 분석할 시계열의 특성에 맞는 적응적 학습률을 구하고 초기 값의 동적인 적용을 통한 개선된 학습방법을 이용하여 신경망 예측을 하고 통계적인 Box-Jenkins예측 결과와 비교해 봄으로써 두 방법간의 시계열 예측 효율성을 비교한다. 신경망 모형에 맞는 적응적 학습률은 표준 직교 배열표에 의해 실험계획을 한 25가지의 모수 조합으로부터 구하고, 신경망 학습의 초기값은 Easton의 제어상자를 동적으로 적용하여 실시간으로 선택할 수 있도록한다. 실증분석에 적용된 시계열자료는 1700년부터 1988년까지의 태양 흑점 자료이다.

In this work, we consider the forecasting performance between nearal network and Box-Jenkins method for time series data. A modified learning process is developed for neural network approach at time eries data, ie, properly adaptive learning rates selecting by orthogonal arrays and dynamic selecting of initial values using Easton's cotroller box. We can obtain good starting points with dynamic graphics approach. We use real data sets for this study : the Wolf yearly sunspot numbers between 1700 and 1988.