• 제목/요약/키워드: Bias estimation

검색결과 555건 처리시간 0.028초

Investigating the future changes of extreme precipitation indices in Asian regions dominated by south Asian summer monsoon

  • Deegala Durage Danushka Prasadi Deegala;Eun-Sung Chung
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2023년도 학술발표회
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    • pp.174-174
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    • 2023
  • The impact of global warming on the south Asian summer monsoon is of critical importance for the large population of this region. This study aims to investigate the future changes of the precipitation extremes during pre-monsoon and monsoon, across this region in a more organized regional structure. The study area is divided into six major divisions based on the Köppen-Geiger's climate structure and 10 sub-divisions considering the geographical locations. The future changes of extreme precipitation indices are analyzed for each zone separately using five indices from ETCCDI (Expert Team on Climate Change Detection and Indices); R10mm, Rx1day, Rx5day, R95pTOT and PRCPTOT. 10 global climate model (GCM) outputs from the latest CMIP6 under four combinations of SSP-RCP scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) are used. The GCMs are bias corrected using nonparametric quantile transformation based on the smoothing spline method. The future period is divided into near future (2031-2065) and far future (2066-2100) and then the changes are compared based on the historical period (1980-2014). The analysis is carried out separately for pre-monsoon (March, April, May) and monsoon (June, July, August, September). The methodology used to compare the changes is probability distribution functions (PDF). Kernel density estimation is used to plot the PDFs. For this study we did not use a multi-model ensemble output and the changes in each extreme precipitation index are analyzed GCM wise. From the results it can be observed that the performance of the GCMs vary depending on the sub-zone as well as on the precipitation index. Final conclusions are made by removing the poor performing GCMs and by analyzing the overall changes in the PDFs of the remaining GCMs.

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숲 체험 활동이 유아의 사회성 발달의 효과에 관한 메타분석 (A Meta-Analysis on Effects of Infant's Sociality Development in Forest Experience Activities)

  • 김찬우;박덕병
    • 농촌지도와개발
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    • 제29권4호
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    • pp.225-250
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    • 2022
  • This study aims to examine the effects of infant's social development forest experience activities through meta-analysis. The final nine studies(total of 165 in the experimental group and 159 in the control group) were selected as a method of systematic review. Meta-analysis on overall effect size estimation, chi-square test, significance analysis, publication bias analysis, and subgroup analysis was performed using the R program. The overall effect size of 9 studies was 1.59, indicating a large effect size. As a result of subgroup analysis of the sub-factors of sociality, autonomy showed the largest effect size at 1.47, the adjusted effect size of cooperation was 1.34, the effect size adjusted for peer interaction was 1.29, and the adjusted effect size for perspective-taking ability was 0.97. All were found to have a statistically significant effect. To analyze the moderating effect, a meta-regression analysis was conducted on the participation period(4, 5~6, 7~8weeks), the number of sessions(6~10, 11~15, 16~20), the frequency per week(1, 2, 5), and the participation time(40, 60, 90, 120, 150min), but there was no statistical difference. Although not statistically significant, the effect size was larger when the participation period was 4 weeks, the number of sessions was 16 to 20, the frequency was 2 times per week, and the participation time was 40 minutes. This results can be usefully utilized by policy makers and forest commentators related to the vitalization of forest education through forest experience activities.

New approach to calculate Weibull parameters and comparison of wind potential of five cities of Pakistan

  • Ahmed Ali Rajput;Muhammad Daniyal;Muhammad Mustaqeem Zahid;Hasan Nafees;Misha Shafi;Zaheer Uddin
    • Advances in Energy Research
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    • 제8권2호
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    • pp.95-110
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    • 2022
  • Wind energy can be utilized for the generation of electricity, due to significant wind potential at different parts of the world, some countries have already been generating of electricity through wind. Pakistan is still well behind and has not yet made any appreciable effort for the same. The objective of this work was to add some new strategies to calculate Weibull parameters and assess wind energy potential. A new approach calculates Weibull parameters; we also developed an alternate formula to calculate shape parameters instead of the gamma function. We obtained k (shape parameter) and c (scale parameter) for two-parameter Weibull distribution using five statistical methods for five different cities in Pakistan. Maximum likelihood method, Modified Maximum likelihood Method, Method of Moment, Energy Pattern Method, Empirical Method, and have been to calculate and differentiate the values of (shape parameter) k and (scale parameter) c. The performance of these five methods is estimated using the Goodness-of-Fit Test, including root mean square error, mean absolute bias error, mean absolute percentage error, and chi-square error. The daily 10-minute average values of wind speed data (obtained from energydata.info) of different cities of Pakistan for the year 2016 are used to estimate the Weibull parameters. The study finds that Hyderabad city has the largest wind potential than Karachi, Quetta, Lahore, and Peshawar. Hyderabad and Karachi are two possible sites where wind turbines can produce reasonable electricity.

Future drought risk assessment under CMIP6 GCMs scenarios

  • Thi, Huong-Nguyen;Kim, Jin-Guk;Fabian, Pamela Sofia;Kang, Dong-Won;Kwon, Hyun-Han
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2022년도 학술발표회
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    • pp.305-305
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    • 2022
  • A better approach for assessing meteorological drought occurrences is increasingly important in mitigating and adapting to the impacts of climate change, as well as strategies for developing early warning systems. The present study defines meteorological droughts as a period with an abnormal precipitation deficit based on monthly precipitation data of 18 gauging stations for the Han River watershed in the past (1974-2015). This study utilizes a Bayesian parameter estimation approach to analyze the effects of climate change on future drought (2025-2065) in the Han River Basin using the Coupled Model Intercomparison Project Phase 6 (CMIP6) with four bias-corrected general circulation models (GCMs) under the Shared Socioeconomic Pathway (SSP)2-4.5 scenario. Given that drought is defined by several dependent variables, the evaluation of this phenomenon should be based on multivariate analysis. Two main characteristics of drought (severity and duration) were extracted from precipitation anomalies in the past and near-future periods using the copula function. Three parameters of the Archimedean family copulas, Frank, Clayton, and Gumbel copula, were selected to fit with drought severity and duration. The results reveal that the lower parts and middle of the Han River basin have faced severe drought conditions in the near future. Also, the bivariate analysis using copula showed that, according to both indicators, the study area would experience droughts with greater severity and duration in the future as compared with the historical period.

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Uncertainty Analysis based on LENS-GRM

  • Lee, Sang Hyup;Seong, Yeon Jeong;Park, KiDoo;Jung, Young Hun
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2022년도 학술발표회
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    • pp.208-208
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    • 2022
  • Recently, the frequency of abnormal weather due to complex factors such as global warming is increasing frequently. From the past rainfall patterns, it is evident that climate change is causing irregular rainfall patterns. This phenomenon causes difficulty in predicting rainfall and makes it difficult to prevent and cope with natural disasters, casuing human and property damages. Therefore, accurate rainfall estimation and rainfall occurrence time prediction could be one of the ways to prevent and mitigate damage caused by flood and drought disasters. However, rainfall prediction has a lot of uncertainty, so it is necessary to understand and reduce this uncertainty. In addition, when accurate rainfall prediction is applied to the rainfall-runoff model, the accuracy of the runoff prediction can be improved. In this regard, this study aims to increase the reliability of rainfall prediction by analyzing the uncertainty of the Korean rainfall ensemble prediction data and the outflow analysis model using the Limited Area ENsemble (LENS) and the Grid based Rainfall-runoff Model (GRM) models. First, the possibility of improving rainfall prediction ability is reviewed using the QM (Quantile Mapping) technique among the bias correction techniques. Then, the GRM parameter calibration was performed twice, and the likelihood-parameter applicability evaluation and uncertainty analysis were performed using R2, NSE, PBIAS, and Log-normal. The rainfall prediction data were applied to the rainfall-runoff model and evaluated before and after calibration. It is expected that more reliable flood prediction will be possible by reducing uncertainty in rainfall ensemble data when applying to the runoff model in selecting behavioral models for user uncertainty analysis. Also, it can be used as a basis of flood prediction research by integrating other parameters such as geological characteristics and rainfall events.

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Assessments of the GEMS NO2 Products Using Ground-Based Pandora and In-Situ Instruments over Busan, South Korea

  • Serin Kim;Ukkyo Jeong;Hanlim Lee;Yeonjin Jung;Jae Hwan Kim
    • 대한원격탐사학회지
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    • 제40권1호
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    • pp.1-8
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    • 2024
  • Busan is the 6th largest port city in the world, where nitrogen dioxide (NO2) emissions from transportation and port industries are significant. This study aims to assess the NO2 products of the Geostationary Environment Monitoring Spectrometer (GEMS) over Busan using ground-based instruments (i.e., surface in-situ network and Pandora). The GEMS vertical column densities of NO2 showed reasonable consistency in the spatiotemporal variations, comparable to the previous studies. The GEMS data showed a consistent seasonal trend of NO2 with the Korea Ministry of Environment network and Pandora in 2022, which is higher in winter and lower in summer. These agreements prove the capability of the GEMS data to monitor the air quality in Busan. The correlation coefficient and the mean bias error between the GEMS and Pandora NO2 over Busan in 2022 were 0.53 and 0.023 DU, respectively. The GEMS NO2 data were also positively correlated with the ground-based in-situ network with a correlation coefficient of 0.42. However, due to the significant spatiotemporal variabilities of the NO2, the GEMS footprint size can hardly resolve small-scale variabilities such as the emissions from the road and point sources. In addition, relative biases of the GEMS NO2 retrievals to the Pandora data showed seasonal variabilities, which is attributable to the air mass factor estimation of the GEMS. Further studies with more measurement locations for longer periods of data can better contribute to assessing the GEMS NO2 data. Reliable GEMS data can further help us understand the Asian air quality with the diurnal variabilities.

주요 수간곡선식 비교에 따른 남부지역 곰솔 수간재적표 개발 (Developing Stem Volume Table of Pinus thunbergii Parl. in Southern Region Based on Comparison of Major Taper Equations)

  • 김현수;정수영;이광수
    • 한국환경과학회지
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    • 제33권7호
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    • pp.453-462
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    • 2024
  • This study was carried out for the purpose of selecting the most appropriate taper equation for the actual stands of Pinus thunbergii in the southern coastal region of Korea and then developing a stem volume table to provide basic data for rational management. To develop a volume table of Pinus thunbergii in this region of Korea, 59 sample trees with various diameter distributions were selected and stem analysis was performed. As a result of stem analysis, two trees with abnormal diameter and height growth as the age increased were rejected, and 57 trees were analyzed. To develop the taper equation, seven major variable exponential equations were used, including Kozak 1988, 1994, 2001, 2002, Bi 2000, Muhairwe 1999, and Sharma and Parton 2009. As a result of parameter estimation and statistical verification, the Kozak 1988 model showed the highest goodness of fit with Fit I (Fit Index), RMSE 1.5620, Bias 0.0031, and MAD 1.0784. The diameter of each 10cm stem ridge for the selected model was estimated, and a stem volume table was produced using the mensuration of division (end area formula) using the Smalian equation. As a result of two-sample T-test for volume table of this study and current yield table, the volume for this study was found to be significantly larger at all observation points (p < 0.001). Even for the same tree species, it is judged that differentiated volume tables are needed for each growth environment characteristic.

Exploring the variations of the pancreatic ductal system: a systematic review and meta-analysis of observational studies

  • Adil Asghar;Ravi Kant Narayan;Nagavalli Basavanna Pushpa;Apurba Patra;Kumar Satish Ravi;R. Shane Tubbs
    • Anatomy and Cell Biology
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    • 제57권1호
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    • pp.31-44
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    • 2024
  • The exocrine part of the pancreas has a duct system called the pancreatic ductal system (PDS). Its mechanism of development is complex, and any reorganization during early embryogenesis can give rise to anatomical variants. The aim of this study is to collect, classify, and analyze published evidence on the importance of anatomical variants of the PDS, addressing gaps in our understanding of such variations. The MEDLINE, Web of Science, Embase, and Google Scholar databases were searched to identify publications relevant to this review. R studio with meta-package was used for data extraction, risk of bias estimation, and statistical analysis. A total of 64 studies out of 1,778 proved suitable for this review and metanalysis. The meta-analysis computed the prevalence of normal variants of the PDS (92% of 10,514 subjects). Type 3 variants and "descending" subtypes of the main pancreatic duct (MPD) predominated in the pooled samples. The mean lengths of the MPD and accessory pancreatic duct (APD) were 16.53 cm and 3.36 cm, respectively. The mean diameters of the MPD at the head and the APD were 3.43 mm and 1.69 mm, respectively. The APD was present in only 41% of samples, and the long type predominated. The pancreatic ductal anatomy is highly variable, and the incorrect identification of variants may be challenging for surgeons during ductal anastomosis with gut, failure to which may often cause ductal obstruction or pseudocysts formation.

서브밴드 가중치를 적용한 스펙트럼 최소값 추적을 이용하는 수정된 IMCRA 기반의 음성 향상 기법 (Speech Enhancement Based on Modified IMCRA Using Spectral Minima Tracking with Weighted Subband Selection)

  • 박윤식;박규석;이상민
    • 대한전자공학회논문지SP
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    • 제49권3호
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    • pp.89-97
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    • 2012
  • 본 논문에서는 잡음환경에서 음성 향상 (speech enhancement)을 위한 새로운 잡음전력 추정 방법을 제안한다. 음성 향상 알고리즘에 널리 적용되고 있는 IMCRA (improved minima controlled recursive averaging) 기법은 오염된 음성신호로부터 추정된 최소 전력 스펙트럼에 기반하여 잡음전력을 추정하는 기존의 방법을 개선하기 위해 간단한 음성 검출 알고리즘을 이용하여 대략적으로 음성 성분이 제거된 전력 스펙트럼에서 최소값을 추정함으로써 음성구간에서 발생할 수 있는 음성왜곡 문제점을 개선하였다. 하지만 비정상 잡음이나 신호 대 잡음 비 (SNR signal-to-noise ratio)가 낮은 환경에서는 음성 검출 성능이 저하되어 음성구간에서 음성왜곡이 발생되는 기존의 문제점이 여전히 발생된다. 따라서 제안된 방법에서는 향상된 잡음전력 추정을 위하여 기존의 IMCRA에서 추정된 최소 전력 스펙트럼에 대하여 스펙트럼 최소값 추적 (SMT, spectral minima tracking) 기법을 적용하고 IMCRA에 의한 최소값과 SMT에 의해 추정된 최소값을 서브밴드 (subband)에 따라 가중치를 적용하여 결합한다. 제안된 알고리즘은 기존의 방법과 주관적 및 객관적 음질평가 테스트를 통해 비교 평가한 결과 다양한 배경잡음 환경에서 향상된 성능을 보였다.

붓스트랩 기법을 이용한 TCS 데이터로부터 차종별 교통량 추정모형 구축 (Construction of vehicle classification estimation model from the TCS data by using bootstrap Algorithm)

  • 노정현;김태균;차경준;박영선;남궁성;황부연
    • 대한교통학회지
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    • 제20권1호
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    • pp.39-52
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    • 2002
  • 차종별 교통량자료는 자료의 출처별로 차종이 동일하지 않아 자료간 호환이 어려우며 이들 자료의 활용도 또한 매우 낮다. 특히, 고속도로의 경우에는 전수자료인 TCS 자료가 있음에도 불구하고 TCS의 타종분류는 차종 내에 승용, 승합, 화물차가 혼재 되어있어 실질적으로 활용도가 매우 낮다. 이에 본 연구에서는 각 출처별 자료들의 차종구분과 호환할 수 있도록 타종구분을 표준화하고 고속도로 톨게이트 유출입 차종별 교통량을 표준화된 차종별로 추정하기 위한 모형을 개발하였다. 즉, 톨게이트를 그 특성에 따라 몇 개의 카테고리로 분류하였고, 각 카테고리별로 각 타종의 구성비를 점추정량을 이용한 기법(산술평균, 기하평균, 조화평균)과 비모수적 통계기법인 붓스트랩을 이용하여 표준화 분류별 교통량을 추정하는 모형을 개발하였다. 그 결과 두 방법 모두 비교적 유의한 수준의 결과가 도출되었으나, 표본의 크기에 따라 발생할 수 있는 극단치에 대한 오추정 문제를 감안할 수 있는 붓스트랩기법이 우수한 것으로 나타났다. 본 연구의 결과로 향후 TCS 자료의 활용성 증대와 TCS 자료를 이용한 고속도로 구간교통량 추정과 고속도로 정기교통량 조사자료의 좀더 구체적인 비교가 가능할 것으로 기대된다.