• 제목/요약/키워드: Spatial Statistical Analysis Methods

검색결과 145건 처리시간 0.02초

미계측 지역 지하수 함양량 추정을 위한 통계적 접근 (Statistical Approach to Groundwater Recharge Rate Estimation for Non-Measured Areas of Water Levels)

  • 김규범;김기영
    • 한국지반환경공학회 논문집
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    • 제9권7호
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    • pp.73-85
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    • 2008
  • 우리나라에는 1995년부터 전국에 지하수 관측소를 설치하여 2005년에 320개소를 완료하였으며, 일 4회 지하수위 자료가 자동 측정되고 있다. 지하수 수위 강하곡선법으로 산정한 관측 지점에서의 지하수 함양율 자료의 평균값을 유역 평균 함양율로 사용하는 것은 대표성이 결여되어 있기 때문에 한계가 있다. 따라서, 본 연구에서는 지하수위 미계측 지역을 대상으로 지하수 함양율을 추정할 수 있도록 223개 관측 지점의 특성 인자와 지하수 함양율과의 관계를 통계적 기법을 활용하여 분석하고 이를 토대로 회귀모형을 구축하였다. 본 연구에서는 군집분석을 통하여 분석대상 관측정을 선정하고, 분산분석을 통하여 지하수 함양량 추정에 필요한 4가지 인자(대상 지점 인근하천의 규모, 하천까지 거리, 지형 경사도, 암석 성인)를 추출하였으며, 이들 인자에 대한 각 관측지점의 특성 자료를 수집하여 회귀 모형에 적합시킨 결과 미계측 지역의 지하수 함양율 추정이 가능한 것으로 평가되었다.

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품질 향상에 적용되는 전산 실험의 계획과 분석 (Design and Analysis of Computer Experiments with An Application to Quality Improvement)

  • Jung Wook Sim;Jeong Soo Park;Jong Sung Bae
    • 응용통계연구
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    • 제7권1호
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    • pp.83-102
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    • 1994
  • 컴퓨터 시뮬레이션 실험을 이용한 제반 연구의 효율성을 높이기 위한 통계적 실험 계획법으로서 최적 실험법과 라틴 하이퍼큐브 계획법에 대하여 연구하여 최적 라틴 하이퍼큐브 계획법을 제시하였다. 또한 전산 실험 자료의 분석을 위하여, 공간적 예측모형을 택하여 자료로부터의 모수추정과 이 모형에 적합한 예측방법 및 최적 실험 계획법 등이 고려되었다. 최적 라틴 하이퍼큐브 실험계획법을 구성하기 위한 2단계 (2점 교환법 및 뉴톤방법) 알고리즘과 그것에 의한 결과를 제시하였고, 나아가 축차적(최적) 라틴 하이퍼큐브 계획법의 구축을 위한 한 방법을 제시하였다. 이와같은 접근법은 주요인 그림과 축차적인 계획 및 분석을 이용하여 집적회로 계획의 최적화 문제로 응용되어 결국 품질향상에 도움이 되도록 하는 실예를 통하여 그 실제적 적용성이 예증되었다.

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Geographical Information System 기법을 이용한 방문간호 중재 평가 (Evaluation of Visiting Nursing Care Using Geographical Information System(GIS) Technology)

  • 이숙정;박정모
    • 대한간호학회지
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    • 제36권6호
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    • pp.1042-1054
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    • 2006
  • Purpose: Previous evaluation studies of the visiting nursing program explained an average change of the participants' health status, without considering socio-ecological characteristics and their impacts. However, these factors must affect individual health problems and lifestyles. For effective and appropriate community based programs, the Geographical Information System(GIS) can be utilized. GIS is a computer-based tool for mapping and analyzing things that happen on earth, and integrates statistical analysis with unique visualization. The purpose of this study was to evaluate visiting nursing care and to advocate the usefulness of planning and evaluating visiting nursing programs using Exploratory Spatial Data Analysis(ESDA) with GIS technology. Methods: One hundred eighty-four elderly participants with cerebrovascular risk factors who lived in 13 areas of one community received visiting nursing care. The data analyzed characteristics of pre-post change and autocorrelation by ESDA using GIS technology. Results: Visiting nursing care showed an improvement in the participants' lifestyle habits, and family management ability and stress level, while the improvements were different depending on the regions. The change of family management ability and stress level correlated with neighborhoods (Morgan's I=0.1841, 0.1675). Conclusions: Community health providers need to consider the individual participant's health status as well as socio-ecological factors. Analysis using GIS technology will contribute to the effective monitoring, evaluation and design of a visiting nursing program.

공간분석을 이용한 지역별 비만율에 영향을 미치는 요인분석 (Analysing the Effects of Regional Factors on the Regional Variation of Obesity Rates Using the Geographically Weighted Regression)

  • 김다양;곽진미;서은원;이광수
    • 보건행정학회지
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    • 제26권4호
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    • pp.271-278
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    • 2016
  • Background: This study purposed to analyze the relationship between regional obesity rates and regional variables. Methods: Data was collected from the Korean Statistical Information Service (KOSIS) and Community Health Survey in 2012. The units of analysis were administrative districts such as city, county, and district. The dependent variable was the age-sex adjusted regional obesity rates. The independent variables were selected to represent four aspects of regions: health behaviour factor, psychological factor, socio-economic factor, and physical environment factor. Along with the traditional ordinary least square (OLS) regression analysis model, this study applied geographically weighted regression (GWR) analysis to calculate the regression coefficients for each region. Results: The OLS results showed that there were significant differences in regional obesity rates in high-risk drinking, walking, depression, and financial independence. The GWR results showed that the size of regression coefficients in independent variables was differed by regions. Conclusion: Our results can help in providing useful information for health policy makers. Regional characteristics should be considered when allocating health resources and developing health-related programs.

보행행태조사방법론의 변화와 모바일 빅데이터의 가능성 진단 연구 - 보행환경 분석연구 최근 사례를 중심으로 - (Changes in Measuring Methods of Walking Behavior and the Potentials of Mobile Big Data in Recent Walkability Researches)

  • 김현주;박소현;이선재
    • 대한건축학회논문집:계획계
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    • 제35권1호
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    • pp.19-28
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    • 2019
  • The purpose of this study is to evaluate the walking behavior analysis methodology used in the previous studies, paying attention to the demand for empirical data collecting for urban and neighborhood planning. The preceding researches are divided into (1)Recording, (2) Surveys, (3)Statistical data, (4)Global positioning system (GPS) devices, and (5)Mobile Big Data analysis. Next, we analyze the precedent research and identify the changes of the walkability research. (1)being required empirical data on the actual walking and moving patterns of people, (2)beginning to be measured micro-walking behaviors such as actual route, walking facilities, detour, walking area. In addition, according to the trend of research, it is analyzed that the use of GPS device and the mobile big data are newly emerged. Finally, we analyze pedestrian data based on mobile big data in terms of 'application' and distinguishing it from existing survey methodology. We present the possibility of mobile big data. (1)Improvement of human, temporal and spatial constraints of data collection, (2)Improvement of inaccuracy of collected data, (3)Improvement of subjective intervention in data collection and preprocessing, (4)Expandability of walking environment research.

공간적 상관구조를 포함하는 선형회귀모형을 이용한 강수량 자료 분석 (Precipitation Analysis Based on Spatial Linear Regression Model)

  • 정지용;진서훈;박만식
    • 응용통계연구
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    • 제21권6호
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    • pp.1093-1107
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    • 2008
  • 매년 전 세계는 여러 자연재해로 인하여 많은 피해를 받고 있다 그 중에서도 강수와 관련한 집중호우와 가뭄, 홍수, 상수원 부족 등으로 많은 손실을 입고 있다. 이러한 재해에 의한 피해를 줄이기 위해서는 기상에 대한 정확한 예측이 필요하다. 따라서 강수량에 대한 정확한 예측을 실시하여 수자원을 적절하게 이용하고 재해에 의한 피해를 줄이기 위하여 많은 연구가 진행되고 있다. 본 연구에서는 강수량을 측정하는 지상기상관측지점자료에 대해 공간적 상관구조를 포함하는 선형회귀모형(크리깅)을 고려하여 세미베리오그램을 기반으로한 최소제곱법과 코베리오그램을 기반으로한 최대우도추정방법으로 남한지역의 공간적 특성을 적절하게 파악할 수 있는 모형들을 찾고 이 모형들을 비교하였다. 공간적 선형회귀모형들에 대한 신뢰성을 검증하기 위하여 자동기상관측지점과 항공기상관측지점에서 측정된 실제값과 예측값을 비교하고 이를 바탕으로 강수량 예측에 관한 발전 및 개선방향에 대해 알아보았다.

언어네트워크 분석을 통한 재난안전정보와 관련한 국내 연구동향 분석 (Analysis of Trends on Disaster Safety Information based on Language Network Analysis Methods)

  • 정지나;정힘찬;김용
    • 한국비블리아학회지
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    • 제28권3호
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    • pp.67-93
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    • 2017
  • 본 연구는 언어 네트워크 분석을 통해 재난정보와 관련한 국내 연구동향 분석을 목적으로 한다. 이를 위하여 학술연구정보서비스(RISS)를 검색하여 2008년부터 2017년 사이에 발간된 재난정보와 관련한 국내 학위논문 및 학술지논문 312건을 수집하였다. 그리고 논문들의 서지사항을 토대로 통계분석을 실시하였다. 뿐만 아니라 연구논문들의 논문명을 대상으로 키워드를 추출하여 빈도분석 및 언어 네트워크 분석을 실시하였다. 분석 결과, 최근 재난분야에서 빅데이터와 관련한 연구가 급증하였으며, 재난정보 공유 및 활용의 중요성이 증대되고 있다. 또한 재난대응을 위하여 공간정보, 실시간정보, 지리정보 등 다양한 유형의 재난정보가 활용되고 있었다.

Evaluation of Hippocampal Volume Based on Various Inversion Time in Normal Adults by Manual Tracing and Automated Segmentation Methods

  • Kim, Ju Ho;Choi, Dae Seob;Kim, Seong-hu;Shin, Hwa Seon;Seo, Hyemin;Choi, Ho Cheol;Son, Seungnam;Tae, Woo Suk;Kim, Sam Soo
    • Investigative Magnetic Resonance Imaging
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    • 제19권2호
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    • pp.67-75
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    • 2015
  • Purpose: To investigate the value of image post-processing software (FreeSurfer, IBASPM [individual brain atlases using statistical parametric mapping software]) and inversion time (TI) in volumetric analyses of the hippocampus and to identify differences in comparison with manual tracing. Materials and Methods: Brain images from 12 normal adults were acquired using magnetization prepared rapid acquisition gradient echo (MPRAGE) with a slice thickness of 1.3 mm and TI of 800, 900, 1000, and 1100 ms. Hippocampal volumes were measured using FreeSurfer, IBASPM and manual tracing. Statistical differences were examined using correlation analyses accounting for spatial interpretations percent volume overlap and percent volume difference. Results: FreeSurfer revealed a maximum percent volume overlap and maximum percent volume difference at TI = 800 ms ($77.1{\pm}2.9%$) and TI = 1100 ms ($13.1{\pm}2.1%$), respectively. The respective values for IBASPM were TI = 1100 ms ($55.3{\pm}9.1%$) and TI = 800 ms ($43.1{\pm}10.7%$). FreeSurfer presented a higher correlation than IBASPM but it was not statistically significant. Conclusion: FreeSurfer performed better in volumetric determination than IBASPM. Given the subjective nature of manual tracing, automated image acquisition and analysis image is accurate and preferable.

An Iterative Normalization Algorithm for cDNA Microarray Medical Data Analysis

  • Kim, Yoonhee;Park, Woong-Yang;Kim, Ho
    • Genomics & Informatics
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    • 제2권2호
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    • pp.92-98
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    • 2004
  • A cDNA microarray experiment is one of the most useful high-throughput experiments in medical informatics for monitoring gene expression levels. Statistical analysis with a cDNA microarray medical data requires a normalization procedure to reduce the systematic errors that are impossible to control by the experimental conditions. Despite the variety of normalization methods, this. paper suggests a more general and synthetic normalization algorithm with a control gene set based on previous studies of normalization. Iterative normalization method was used to select and include a new control gene set among the whole genes iteratively at every step of the normalization calculation initiated with the housekeeping genes. The objective of this iterative normalization was to maintain the pattern of the original data and to keep the gene expression levels stable. Spatial plots, M&A (ratio and average values of the intensity) plots and box plots showed a convergence to zero of the mean across all genes graphically after applying our iterative normalization. The practicability of the algorithm was demonstrated by applying our method to the data for the human photo aging study.

Correlation Analysis of Atmospheric Pollutants and Meteorological Factors Based on Environmental Big Data

  • Chao, Chen;Min, Byung-Won
    • International Journal of Contents
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    • 제18권1호
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    • pp.17-26
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    • 2022
  • With the acceleration of urbanization and industrialization, air pollution has become increasingly serious, and the pollution control situation is not optimistic. Climate change has become a major global challenge faced by mankind. To actively respond to climate change, China has proposed carbon peak and carbon neutral goals. However, atmospheric pollutants and meteorological factors that affect air quality are complex and changeable, and the complex relationship and correlation between them must be further clarified. This paper uses China's 2013-2018 high-resolution air pollution reanalysis open data set, as well as statistical methods of the Pearson Correlation Coefficient (PCC) to calculate and visualize the design and analysis of environmental monitoring big data, which is intuitive and it quickly demonstrated the correlation between pollutants and meteorological factors in the temporal and spatial sequence, and provided convenience for environmental management departments to use air quality routine monitoring data to enable dynamic decision-making, and promote global climate governance. The experimental results show that, apart from ozone, which is negatively correlated, the other pollutants are positively correlated; meteorological factors have a greater impact on pollutants, temperature and pollutants are negatively correlated, air pressure is positively correlated, and the correlation between humidity is insignificant. The wind speed has a significant negative correlation with the six pollutants, which has a greater impact on the diffusion of pollutants.