• Title/Summary/Keyword: Uncertainty Evaluation

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Changes in the Treatment Strategies for Helicobacter pylori Infection in Children and Adolescents in Korea

  • Jun, Jin-Su;Seo, Ji-Hyun;Park, Ji-Sook;Rhee, Kwang-Ho;Youn, Hee-Shang
    • Pediatric Gastroenterology, Hepatology & Nutrition
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    • v.22 no.5
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    • pp.417-430
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    • 2019
  • The policies developed for the treatment of Helicobacter pylori infection in adults may not be the most suitable ones to treat children and adolescents. Methods used to treat children and adolescents in Europe and North America may not be appropriate for treating children and adolescents in Korea due to differences in epidemiological characteristics of H. pylori between regions. Moreover, the agreed standard guidelines for the treatment of H. pylori infection in children and adolescents in Korea have not been established yet. In this study, the optimal treatment strategy for H. pylori infection control in children and adolescents in Korea is discussed based on these guidelines, and recent progress on the use and misuse of antimicrobial agents is elaborated. Non-invasive as well as invasive diagnostic test and treatment strategy for H. pylori infection are not recommendable in children aged less than ten years or children with body weight under 35 kg, except in cases of clinically suspected or endoscopically identified peptic ulcers. The uncertainty, whether enough antimicrobial concentrations to eradicate H. pylori can be maintained when administered according to body weight-based dosing, and the costs and adverse effects outweighing the anticipated benefits of treatment make it difficult to decide to eradicate H. pylori in a positive noninvasive diagnostic test in this age group. However, adolescents over ten years of age or with a bodyweight of more than 35 kg can be managed aggressively as adults, because they can tolerate the adult doses of anti-H. pylori therapy. In adolescents, the prevention of future peptic ulcers and gastric cancers is expected after the eradication of H. pylori. Bismuth-based quadruple therapy (bismuth-proton pump inhibitor-amoxicillin/tetracycline-metronidazole) with maximal tolerable doses and optimal dose intervals of 14 days is recommended, because in Korea, the antibiotic susceptibility test for H. pylori is not performed at the initial diagnostic evaluation. If the first-line treatment fails, concomitant therapy plus bismuth can be attempted for 14 days as an empirical rescue therapy. Finally, the salvage therapy, if needed, must be administered after the H. pylori antibiotic susceptibility test.

Water resources potential assessment of ungauged catchments in Lake Tana Basin, Ethiopia

  • Damtew, Getachew Tegegne;Kim, Young-Oh
    • Proceedings of the Korea Water Resources Association Conference
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    • 2015.05a
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    • pp.217-217
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    • 2015
  • The objective of this study was mainly to evaluate the water resources potential of Lake Tana Basin (LTB) by using Soil and Water Assessment Tool (SWAT). From SWAT simulation of LTB, about 5236 km2 area of LTB is gauged watershed and the remaining 9878 km2 area is ungauged watershed. For calibration of model parameters, four gauged stations were considered namely: Gilgel Abay, Gummera, Rib, and Megech. The SWAT-CUP built-in techniques, particle swarm optimization (PSO) and generalized likelihood uncertainty estimation (GLUE) method was used for calibration of model parameters and PSO method were selected for the study based on its performance results in four gauging stations. However the level of sensitivity of flow parameters differ from catchment to catchment, the curve number (CN2) has been found the most sensitive parameters in all gauged catchments. To facilitate the transfer of data from gauged catchments to ungauged catchments, clustering of hydrologic response units (HRUs) were done based on physical similarity measured between gauged and ungauged catchment attributes. From SWAT land use/ soil use/slope reclassification of LTB, a total of 142 HRUs were identified and these HRUs are clustered in to 39 similar hydrologic groups. In order to transfer the optimized model parameters from gauged to ungauged catchments based on these clustered hydrologic groups, this study evaluates three parameter transfer schemes: parameters transfer based on homogeneous regions (PT-I), parameter transfer based on global averaging (PT-II), and parameter transfer by considering Gilgel Abay catchment as a representative catchment (PT-III) since its model performance values are better than the other three gauged catchments. The performance of these parameter transfer approach was evaluated based on values of Nash-Sutcliffe efficiency (NSE) and coefficient of determination (R2). The computed NSE values was found to be 0.71, 0.58, and 0.31 for PT-I, PT-II and PT-III respectively and the computed R2 values was found to be 0.93, 0.82, and 0.95 for PT-I, PT-II, and PT-III respectively. Based on the performance evaluation criteria, PT-I were selected for modelling ungauged catchments by transferring optimized model parameters from gauged catchment. From the model result, yearly average stream flow for all homogeneous regions was found 29.54 m3/s, 112.92 m3/s, and 130.10 m3/s for time period (1989 - 2005) for region-I, region-II, and region-III respectively.

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The Effect of Attitude toward Parent Brand on Trial Intention of Brand Extensions and the Moderating Role of Perceived Similarity and Consumption Experience of Parent (모브랜드 태도가 브랜드확장 제품의 시용의도에 미치는 영향과 지각된 유사성과 모브랜드 소비경험의 조절역할)

  • Park, JI-Yeon
    • Journal of Convergence for Information Technology
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    • v.9 no.4
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    • pp.59-67
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    • 2019
  • Most of the prior researches in brand extension evaluation have utilized purchase intention as a n effective variable to assess the effectiveness of brand extensions. In contrast, the author proposes that trial intention is to better predict consumers' behavioral response in the newly launched brand extension markets where relate to high risk and uncertainty. Furthermore, the study explores the effects of attitude toward parent brand and consumers' characteristics (perceived similarity and consumption experience) on trial intention of brand extensions. In order to achieve the purpose of the study, the data collection was conducted for actual consumers who had experience using parent brand products. This study employed experiment and questionnaire survey and collected data of 186 was analyzed using clustering analysis and regression analysis. The main results are as follows. First, attitude toward parent brand has a positive effect on trial intention of the extensions. Second, perceived similarity and consumption experience of parent brand have moderating effects on the relation of attitude toward parent brand and trial intention of brand extensions. The results provide that both industry and academic researchers with a guide to process trial intention of brand extension from a comprehensive perspective.

Evaluation of the Standard Support Pattern in Large Section Tunnel by Numerical Analysis and Field Measurement (수치해석 및 현장계측에 의한 대단면 터널 표준지보패턴의 적정성 검증)

  • Byun, Yoseph;Chung, Sungrae;Song, Simyung;Chun, Byungsik;Park, Duhee
    • Journal of the Korean GEO-environmental Society
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    • v.12 no.7
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    • pp.5-12
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    • 2011
  • When choosing the support pattern of tunnel, the characteristics of rock are identified from the result of the surface geologic survey, boring, and geophysical prospecting and laboratory test. And a rock mass rating is classified and excavation method and standard support pattern are designed considering rock classification, domestic and international construction practices, numerical analysis. According to the revised design standard for tunnel, it was recommended to classify the rock mass rating for the design of tunnel into a rating based on RMR. If necessary, it proposed a flexible standard allowed applying more atomized the rock mass rating and Q-System. Also, the resonable verification of the support pattern must be accompanied because the factors affecting the structure and behavior of ground during the construction of tunnel are the main factors of uncertainty factors such as the nature of ground, ground water and the characteristics of structural materials. These days, such verification method is getting more specialized and diversified. In this study, the empirical method, numerical analysis and comparative analysis of in situ measurements were used to prove the reasonableness in the support pattern by RMR and Q-value on the Imha Dam emergency spillway.

Evaluation of conceptual rainfall-runoff models for different flow regimes and development of ensemble model (개념적 강우유출 모형의 유량구간별 적합성 평가 및 앙상블 모델 구축)

  • Yu, Jae-Ung;Park, Moon-Hyung;Kim, Jin-Guk;Kwon, Hyun-Han
    • Journal of Korea Water Resources Association
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    • v.54 no.2
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    • pp.105-119
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    • 2021
  • An increase in the frequency and intensity of both floods and droughts has been recently observed due to an increase in climate variability. Especially, land-use change associated with industrial structure and urbanization has led to an imbalance between water supply and demand, acting as a constraint in water resource management. Accurate rainfall-runoff analysis plays a critical role in evaluating water availability in the water budget analysis. This study aimed to explore various continuous rainfall-runoff models over the Soyanggang dam watershed. Moreover, the ensemble modeling framework combining multiple models was introduced to present scenarios on streamflow considering uncertainties. In the ensemble modeling framework, rainfall-runoff models with fewer parameters are generally preferred for effective regionalization. In this study, more than 40 continuous rainfall-runoff models were applied to the Soyanggang dam watershed, and nine rainfall-runoff models were primarily selected using different goodness-of-fit measures. This study confirmed that the ensemble model showed better performance than the individual model over different flow regimes.

MLP-based 3D Geotechnical Layer Mapping Using Borehole Database in Seoul, South Korea (MLP 기반의 서울시 3차원 지반공간모델링 연구)

  • Ji, Yoonsoo;Kim, Han-Saem;Lee, Moon-Gyo;Cho, Hyung-Ik;Sun, Chang-Guk
    • Journal of the Korean Geotechnical Society
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    • v.37 no.5
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    • pp.47-63
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    • 2021
  • Recently, the demand for three-dimensional (3D) underground maps from the perspective of digital twins and the demand for linkage utilization are increasing. However, the vastness of national geotechnical survey data and the uncertainty in applying geostatistical techniques pose challenges in modeling underground regional geotechnical characteristics. In this study, an optimal learning model based on multi-layer perceptron (MLP) was constructed for 3D subsurface lithological and geotechnical classification in Seoul, South Korea. First, the geotechnical layer and 3D spatial coordinates of each borehole dataset in the Seoul area were constructed as a geotechnical database according to a standardized format, and data pre-processing such as correction and normalization of missing values for machine learning was performed. An optimal fitting model was designed through hyperparameter optimization of the MLP model and model performance evaluation, such as precision and accuracy tests. Then, a 3D grid network locally assigning geotechnical layer classification was constructed by applying an MLP-based bet-fitting model for each unit lattice. The constructed 3D geotechnical layer map was evaluated by comparing the results of a geostatistical interpolation technique and the topsoil properties of the geological map.

Providing the combined models for groundwater changes using common indicators in GIS (GIS 공통 지표를 활용한 지하수 변화 통합 모델 제공)

  • Samaneh, Hamta;Seo, You Seok
    • Journal of Korea Water Resources Association
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    • v.55 no.3
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    • pp.245-255
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    • 2022
  • Evaluating the qualitative the qualitative process of water resources by using various indicators, as one of the most prevalent methods for optimal managing of water bodies, is necessary for having one regular plan for protection of water quality. In this study, zoning maps were developed on a yearly basis by collecting and reviewing the process, validating, and performing statistical tests on qualitative parameters҆ data of the Iranian aquifers from 1995 to 2020 using Geographic Information System (GIS), and based on Inverse Distance Weighting (IDW), Radial Basic Function (RBF), and Global Polynomial Interpolation (GPI) methods and Kriging and Co-Kriging techniques in three types including simple, ordinary, and universal. Then, minimum uncertainty and zoning error in addition to proximity for ASE and RMSE amount, was selected as the optimum model. Afterwards, the selected model was zoned by using Scholar and Wilcox. General evaluation of groundwater situation of Iran, revealed that 59.70 and 39.86% of the resources are classified into the class of unsuitable for agricultural and drinking purposes, respectively indicating the crisis of groundwater quality in Iran. Finally, for validating the extracted results, spatial changes in water quality were evaluated using the Groundwater Quality Index (GWQI), indicating high sensitivity of aquifers to small quantitative changes in water level in addition to severe shortage of groundwater reserves in Iran.

Evaluation of extreme rainfall estimation obtained from NSRP model based on the objective function with statistical third moment (통계적 3차 모멘트 기반의 목적함수를 이용한 NSRP 모형의 극치강우 재현능력 평가)

  • Cho, Hemie;Kim, Yong-Tak;Yu, Jae-Ung;Kwon, Hyun-Han
    • Journal of Korea Water Resources Association
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    • v.55 no.7
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    • pp.545-556
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    • 2022
  • It is recommended to use long-term hydrometeorological data for more than the service life of the hydraulic structures and water resource planning. For the purpose of expanding rainfall data, stochastic simulation models, such as Modified Bartlett-Lewis Rectangular Pulse (BLRP) and Neyman-Scott Rectangular Pulse (NSRP) models, have been widely used. The optimal parameters of the model can be estimated by repeatedly comparing the statistical moments defined through a combination of parameters of the probability distribution in the optimization context. However, parameter estimation using relatively small observed rainfall statistics corresponds to an ill-posed problem, leading to an increase in uncertainty in the parameter estimation process. In addition, as shown in previous studies, extreme values are underestimated because objective functions are typically defined by the first and second statistical moments (i.e., mean and variance). In this regard, this study estimated the parameters of the NSRP model using the objective function with the third moment and compared it with the existing approach based on the first and second moments in terms of estimation of extreme rainfall. It was found that the first and second moments did not show a significant difference depending on whether or not the skewness was considered in the objective function. However, the proposed model showed significantly improved performance in terms of estimation of design rainfalls.

Deep Learning-based Forest Fire Classification Evaluation for Application of CAS500-4 (농림위성 활용을 위한 산불 피해지 분류 딥러닝 알고리즘 평가)

  • Cha, Sungeun;Won, Myoungsoo;Jang, Keunchang;Kim, Kyoungmin;Kim, Wonkook;Baek, Seungil;Lim, Joongbin
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1273-1283
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    • 2022
  • Recently, forest fires have frequently occurred due to climate change, leading to human and property damage every year. The forest fire monitoring technique using remote sensing can obtain quick and large-scale information of fire-damaged areas. In this study, the Gangneung and Donghae forest fires that occurred in March 2022 were analyzed using the spectral band of Sentinel-2, the normalized difference vegetation index (NDVI), and the normalized difference water index (NDWI) to classify the affected areas of forest fires. The U-net based convolutional neural networks (CNNs) model was simulated for the fire-damaged areas. The accuracy of forest fire classification in Donghae and Gangneung classification was high at 97.3% (f1=0.486, IoU=0.946). The same model used in Donghae and Gangneung was applied to Uljin and Samcheok areas to get rid of the possibility of overfitting often happen in machine learning. As a result, the portion of overlap with the forest fire damage area reported by the National Institute of Forest Science (NIFoS) was 74.4%, confirming a high level of accuracy even considering the uncertainty of the model. This study suggests that it is possible to quantitatively evaluate the classification of forest fire-damaged area using a spectral band and indices similar to that of the Compact Advanced Satellite 500 (CAS500-4) in the Sentinel-2.

Evaluating SR-Based Reinforcement Learning Algorithm Under the Highly Uncertain Decision Task (불확실성이 높은 의사결정 환경에서 SR 기반 강화학습 알고리즘의 성능 분석)

  • Kim, So Hyeon;Lee, Jee Hang
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.8
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    • pp.331-338
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    • 2022
  • Successor representation (SR) is a model of human reinforcement learning (RL) mimicking the underlying mechanism of hippocampal cells constructing cognitive maps. SR utilizes these learned features to adaptively respond to the frequent reward changes. In this paper, we evaluated the performance of SR under the context where changes in latent variables of environments trigger the reward structure changes. For a benchmark test, we adopted SR-Dyna, an integration of SR into goal-driven Dyna RL algorithm in the 2-stage Markov Decision Task (MDT) in which we can intentionally manipulate the latent variables - state transition uncertainty and goal-condition. To precisely investigate the characteristics of SR, we conducted the experiments while controlling each latent variable that affects the changes in reward structure. Evaluation results showed that SR-Dyna could learn to respond to the reward changes in relation to the changes in latent variables, but could not learn rapidly in that situation. This brings about the necessity to build more robust RL models that can rapidly learn to respond to the frequent changes in the environment in which latent variables and reward structure change at the same time.