• Tunnel and Underground Space
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• v.13 no.4
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• pp.270-278
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• 2003

Transparency on the Total System Performance Assessment (TSPA) is the key issue to enhance the public acceptance for a permanent high level radioactive repository. Traditionally, the study on features, events and processes (FEPs) and associated scenarios has been regarded as the starting point to open the communicative discussion on TSPA such as what to evaluate, how to evaluate and how to translate outcomes into more friendly language that many stakeholders can easily understand and react with. However, in most cases, it has been limited to one way communication, because it is difficult for stakeholders outside the performance assessment field to assess the details on the story of the safety assessment, scenario and technical background of it. Fortunately, the advent of the internet era opens up the possibility of two way communication from the beginning of the performance assessment so that every stakeholder can exchange their keen opinions on the safety issues. To achieve it, KAERI develops the systematic approach from the FEPs to Assessment methods flow chart. All information is integrated into the web based program named FEAS (FEp to Assessment through Scenario development) under development in KAERI. In parallel, two independent systems are also under development the web based QA(Quality Assurance) system and the PA(Performance Assessment) input database. It is ideal to integrate the input data base with the QA system so that every data in the system can checked whenever necessary. Throughout the next phase R&D starting from the year 2003, these three systems will be consolidated into one unified system.

• Journal of Environmental Health Sciences
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• v.41 no.6
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• pp.425-437
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• 2015

Objectives: Risk assessment is a tool for predicting and reducing uncertainty related to the effects of future activities. Probability approaches are the main elements in risk assessment, but confusion about the interpretation and use of assessment factors often undermines the message of the analyses. The aim of this study is to provide a guideline for systematic reduction plans regarding uncertainty in risk assessment. Methods: Articles and reports were collected online using the key words "uncertainty analysis" on risk assessment. Uncertainty analysis was conducted based on reports focusing on procedures for analysis methods by the World Health Organization (WHO) and U.S. Environmental Protection Agency (USEPA). In addition, case studies were performed in order to verify suggested methods qualitatively and quantitatively with exposure data, including measured data on toluene and styrene in residential spaces and multi-use facilities. Results: Based on an analysis of the data on uncertainty, three major factors including scenario, model, and parameters were identified as the main sources of uncertainty, and tiered approaches were determined. In the case study, the risk of toluene and styrene was evaluated and the most influential factors were also determined. Five reduction plans were presented: providing standard guidelines, using reliable exposure factors, possessing quality controls for analysis and scientific expertise, and introducing a peer review system. Conclusion: In this study, we established a method for reducing uncertainty by taking into account the major factors. Also, we showed a method for uncertainty analysis with tiered approaches. However, uncertainties are difficult to define because they are generated by many factors. Therefore, further studies are needed for the development of technical guidelines based on the representative scenario, model, and parameters developed in this study.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.4 no.1
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• pp.65-75
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• 2006

Transparency on the Total System Performance Assessment (TSPA) is the key issue to enhance the public acceptance for a radioactive repository. To approve it, all performances on TSPA through Quality Assurance is necessary. The integrated Cyber R&D Platform is developed by KAERI using the T2R3 principles applicable for five major steps : planning, research work, documentation, and internal & external audits in R&D's. The proposed system is implemented in the web-based system so that all participants in TSPA are able to access the system. It is composed of three sub-systems; FEAS (FEp to Assessment through Scenario development) showing systematic approach from the FEPs to Assessment methods flow chart, PAID (Performance Assessment Input Databases) being designed to easily search and review field data for TSPA and QA system containing the administrative system for QA on five key steps in R&D's in addition to approval and disapproval processes, corrective actions, and permanent record keeping. All information being recorded in QA system through T2R3 principles is integrated into Cyber R&D Platform so that every data in the system can be checked whenever necessary. Throughout the next phase R&D, Cyber R&D Platform will be connected with the assessment tool for TSPA so that it will be expected to search the whole information in one unified system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4043-4064
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• 2021

Night-time image quality evaluation is an urgent requirement in visual inspection. The lighting environment of night-time results in low brightness, low contrast, loss of detailed information, and colour dissonance of image, which remains a daunting task of delicately evaluating the image quality at night. A new blind quality assessment metric is presented for realistic night-time scenario through a comprehensive consideration of contrast, texture, and colour in this article. To be specific, image blocks' color-gray-difference (CGD) histogram that represents contrast features is computed at first. Next, texture features that are measured by the mean subtracted contrast normalized (MSCN)-weighted local binary pattern (LBP) histogram are calculated. Then statistical features in Lαβ colour space are detected. Finally, the quality prediction model is conducted by the support vector regression (SVR) based on extracted contrast, texture, and colour features. Experiments conducted on NNID, CCRIQ, LIVE-CH, and CID2013 databases indicate that the proposed metric is superior to the compared BIQA metrics.

• Food Science of Animal Resources
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• v.43 no.6
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• pp.1002-1016
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• 2023

This study aimed to develop appropriate temperature management practices and provide scientific evidence to support the development of sell-by-date guidance for eggs. Washed and unwashed eggs were subjected to storage under six different scenarios, and both types of eggs were stored at temperatures up to 35℃ to evaluate the sell-by-date. Despite temperature fluctuations or continuous storage at 30℃ for 5 days, subsequent storage at 10℃ resulted in significantly higher Haugh unit and yolk index on day 15. These results indicate that refrigerating eggs from retail sales until consumption is effective for egg quality management, despite the exposure of up to 35℃ during distribution. In terms of sell-by-date evaluation, washed eggs retained class B quality for an additional 37 days beyond the recommended sell-by-date at 15℃, which is above the regulated storage temperature. However, unwashed eggs maintained class B quality for approximately 20 days at 30℃-35℃, emphasizing the need for sell-by-date guidelines for unwashed eggs. This study is the first to provide appropriate egg-handling practices based on the actual distribution environment in Korea.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.5
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• pp.105-119
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• 2020

Although there have been a lot of efforts to improve water quality in the estuarine reservoir, overall the water quality problems of the estuarine reservoirs remain. So, it is essential to establish water quality management plans under a comprehensive understanding of the environmental characteristics of the estuarine reservoir. Therefore, in this study, a resilience analysis framework for evaluating the estuarine reservoir's water quality was suggested for improving existing assessment method for water quality management plan. First, as a result of analyzing the static resilience to each scenario, it was found that from the S3 scenario in which dredging was conducted considerably, the resilience of about 30% more than the current estuarine reservoir system was restored. Second, as a result of analyzing the dynamic resilience, if cost and time are considered, there is no significant difference in robustness and resourcefulness, so it can be seen that the resilience of the estuarine reservoir can be efficiently improved by simply performing dredging up to the level of Scenario 3. Finally, as a result of comparing static and dynamic resilience, since static resilience is only presented as a single value, the differences and characteristics of the resilience capacity of the estuarine reservoir might be overlooked only by the static resilience analysis. However, in the aspect that it is possible to interpret the internal recovery capacity of the estuarine reservoir in multiple ways with various indicators (robustness, redundancy, resourcefulness, rapidity), evaluating water quality based on dynamic resilience analysis is useful.

• Environmental Engineering Research
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• v.24 no.4
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• pp.582-590
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• 2019

Currently, the waterfront facility was constructed in New Songdo City, South Korea. It has the various water leisure areas and especially an artificial urban canal with filtered seawater by re-circulating flow system. However, due to excessive amount of nutrients from seawater combined with complicated geometry, it is highly vulnerable to deterioration of water quality. In this study, flow characteristics and pollutant transport were analyzed with comprehensive numerical models, MIKE 3 FM and ECO-lab. Based on these numerical results, notable sampling points were selected for field measurements and comparison between modeling and measured results were conducted. In addition, the integrated water quality evaluation index, Water Quality Index was applied to analyze various water quality issues. We also set up scenarios to control the two kinds of water quality factors, dissolved oxygen (DO), and total phosphorus (TP). As a result, the effect of 20% reduction of TP was less than 10% and it was almost ineffective for a year but it was reduced by up to 40% in case of scenario which DO is increased by 20%. Therefore, it was recommended to control the DO concentration, usually by applying re-aeration facility, rather than TP in artificial urban canal with seawater.

• Journal of Korean Society on Water Environment
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• v.28 no.3
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• pp.444-452
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• 2012

This study aims at assessing vulnerability of water quality and aquatic ecosystem to climate change by using proxy variables. Vulnerability to climate change is defined as a function of exposure to climate, sensitivity, and adaptive capacity. Detailed proxy variables were selected considering availability and then standardized by re-scaling concept. After adequate weights were assigned to standardized proxy variables by Delphi technique, vulnerability index was calculated. As results, vulnerability of adjacent regions to coastal areas include water quality and aquatic ecosystem is relatively higher than that of inland areas, and especially adjacent region to the western and southeast seas, and Jeju show high vulnerabilities. Vulnerability in the future was performed based on A1B scenario (IPCC, 2000). Temporally, the increase of vulnerability from 2050s to 2100s may be larger than the increase from 2000s to 2050s. Because vulnerability index was estimated through the relationship among various proxy variables, it is important to consider characteristics of local region with measurements and policies for reduction of sensitivity and enhancement of adaptive capacity on climate change. This study is expected to be useful in planning adaptation measures and selecting priority to the policy on climate change.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.6
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• pp.83-96
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• 2018

The objective of this study was to estimate the climate change impact on water quantity and quality to Saemanguem watershed using SWAT (Soil and water assessment tool) model. The SWAT model was calibrated and validated using observed data from 2008 to 2017 for the study watershed. The $R^2$ (Determination coefficient), RMSE (Root mean square error), and NSE (Nash-sutcliffe efficiency coefficient) were used to evaluate the model performance. RCP scenario data were produced from 10 GCM (General circulation model) and all relevant grid data including the major observation points (Gusan, Jeonju, Buan, Jeongeup) were extracted. The systematic error evaluation of the GCM model outputs was performed as well. They showed various variations based on analysis of future climate change effects. In future periods, the MIROC5 model showed the maximum values and the CMCC-CM model presented the minimum values in the climate data. Increasing rainfall amount was from 180mm to 250mm and increasing temperature value ranged from 1.7 to $5.9^{\circ}C$, respectively, compared with the baseline (2006~2017) in 10 GCM model outputs. The future 2030s and 2070s runoff showed increasing rate of 16~29% under future climate data. The future rate of change for T-N (Total nitrogen) and T-P (Total phosphorus) loads presented from -26 to +0.13% and from +5 to 47%, respectively. The hydrologic cycle and water quality from the Saemanguem headwater were very sensitive to projected climate change scenarios so that GCM model should be carefully selected for the purpose of use and the tendency analysis of GCM model are needed if necessary.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.18-18
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• 2011

Climate change is impacting and will increasingly impact both the quantity and quality of the world's water resources in a variety of ways. In some areas warming climate results in increased rainfall, surface runoff, and groundwater recharge while in others there may be declines in all of these. Water quality is described by a number of variables. Some are directly impacted by climate change. Temperature is an obvious example. Notably, increased atmospheric concentrations of $CO_2$ triggering climate change increase the $CO_2$ dissolving into water. This has manifold consequences including decreased pH and increased alkalinity, with resultant increases in dissolved concentrations of the minerals in geologic materials contacted by such water. Climate change is also expected to increase the number and intensity of extreme climate events, with related hydrologic changes. A simple framework has been developed in New Zealand for assessing and predicting climate change impacts on water resources. Assessment is largely based on trend analysis of historic data using the non-parametric Mann-Kendall method. Trend analysis requires long-term, regular monitoring data for both climate and hydrologic variables. Data quality is of primary importance and data gaps must be avoided. Quantitative prediction of climate change impacts on the quantity of water resources can be accomplished by computer modelling. This requires the serial coupling of various models. For example, regional downscaling of results from a world-wide general circulation model (GCM) can be used to forecast temperatures and precipitation for various emissions scenarios in specific catchments. Mechanistic or artificial intelligence modelling can then be used with these inputs to simulate climate change impacts over time, such as changes in streamflow, groundwater-surface water interactions, and changes in groundwater levels. The Waimea Plains catchment in New Zealand was selected for a test application of these assessment and prediction methods. This catchment is predicted to undergo relatively minor impacts due to climate change. All available climate and hydrologic databases were obtained and analyzed. These included climate (temperature, precipitation, solar radiation and sunshine hours, evapotranspiration, humidity, and cloud cover) and hydrologic (streamflow and quality and groundwater levels and quality) records. Results varied but there were indications of atmospheric temperature increasing, rainfall decreasing, streamflow decreasing, and groundwater level decreasing trends. Artificial intelligence modelling was applied to predict water usage, rainfall recharge of groundwater, and upstream flow for two regionally downscaled climate change scenarios (A1B and A2). The AI methods used were multi-layer perceptron (MLP) with extended Kalman filtering (EKF), genetic programming (GP), and a dynamic neuro-fuzzy local modelling system (DNFLMS), respectively. These were then used as inputs to a mechanistic groundwater flow-surface water interaction model (MODFLOW). A DNFLMS was also used to simulate downstream flow and groundwater levels for comparison with MODFLOW outputs. MODFLOW and DNFLMS outputs were consistent. They indicated declines in streamflow on the order of 21 to 23% for MODFLOW and DNFLMS (A1B scenario), respectively, and 27% in both cases for the A2 scenario under severe drought conditions by 2058-2059, with little if any change in groundwater levels.