• Journal of the Korean Society of Systems Engineering
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• v.16 no.2
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• pp.27-37
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• 2020

The Fukushima Daiichi accident in 2011 revealed some vulnerabilities of existing Nuclear Power Plants (NPPs) under extended Station Blackout (SBO) accident conditions. One of the key Severe Accident Management (SAM) strategies developed post Fukushima accident is the In-Vessel Retention (IVR) Strategy which aims to retain the structural integrity of the Reactor Pressure Vessel (RPV). RELAP/SCDAPSIM/MOD3.4 is selected to predict the thermal-hydraulic response of APR1400 undergoing an extended SBO. To assess the effectiveness of the IVR strategy, it is essential to quantify the underlying uncertainties. In this work, both the epistemic and aleatory uncertainties are considered to identify the success window of the IVR strategy. A set of in-vessel relevant phenomena were identified based on Phenomena Identification and Ranking Tables (PIRT) developed for severe accidents and propagated through the thermal-hydraulic model using Wilk's sampling method. For this work, a Systems Engineering (SE) approach is applied to facilitate the development process of assessing the reliability and robustness of the APR1400 IVR strategy. Specifically, the Kossiakoff SE method is used to identify the requirements, functions and physical architecture, and to develop a design verification and validation plan. Using the SE approach provides a systematic tool to successfully achieve the research goal by linking each requirement to a verification or validation test with predefined success criteria at each stage of the model development. The developed model identified the conditions necessary for successful implementation of the IVR strategy which maintains the vessel integrity and prevents a melt-through.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.75-93
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• 2022

Machine learning (ML) data-driven meta-model is proposed as a surrogate model to reduce the excessive computational cost of the physics-based model and facilitate the real-time prediction of a nuclear power plant's transient response. To forecast the transient response three machine learning (ML) meta-models based on recurrent neural networks (RNNs); specifically, Long Short Term Memory (LSTM), Gated Recurrent Unit (GRU), and a sequence combination of Convolutional Neural Network (CNN) and LSTM are developed. The chosen accident scenario is a control element assembly withdrawal at power concurrent with the Loss Of Offsite Power (LOOP). The transient response was obtained using the best estimate thermal hydraulics code, MARS-KS, and cross-validated against the Design and control document (DCD). DAKOTA software is loosely coupled with MARS-KS code via a python interface to perform the Best Estimate Plus Uncertainty Quantification (BEPU) analysis and generate a time series database of the system response to train, test and validate the ML meta-models. Key uncertain parameters identified as required by the CASU methodology were propagated using the non-parametric Monte-Carlo (MC) random propagation and Latin Hypercube Sampling technique until a statistically significant database (181 samples) as required by Wilk's fifth order is achieved with 95% probability and 95% confidence level. The three ML RNN models were built and optimized with the help of the Talos tool and demonstrated excellent performance in forecasting the most probable NPP transient response. This research was guided by the Systems Engineering (SE) approach for the systematic and efficient planning and execution of the research.

• Journal of Forest and Environmental Science
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• v.39 no.1
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• pp.1-12
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• 2023

To understand the health conditions and growth patterns of forest estate for environmental resilience and climate change mitigation, assessment of structure and species diversity is paramount. This study aimed at assessing the structure, alpha, and beta diversities of tree species in three ecological zones in Taraba, Nigeria for management purposes. In recent time, no research has been reported on the structure and beta diversity of the study areas. A systematic sampling design was used for data collection. Five sample plots of 50×50 m were laid in each of the six natural forest areas. The result showed a mean DBH (42.5 cm) and a tree height (15.0 m) from the forests. The forests have a structure of an inverse "J-shape," which is typical of natural forests in the tropics. The southern Guinea savanna zone had the highest mean Shannon-Weiner diversity index (2.8). The least beta diversity index (0.02) was between Baissa and Jen Gininya forest areas. Baissa and Bakin Dutse Protected Forest Areas (PFAs) contained 76.5% of the tree species. There is a high chance of all tree species to be found in these 2 forest areas. Proximity to a location influences how similar two tree species are, according to the least beta diversity index (0.02) recorded. The Federal Government's method of management for the forest, known as Gashaka Gumti National Park, may be responsible for the high beta diversity index in the Montane ecozone. Therefore, it should be strongly encouraged to practice strict oversight of natural areas, as their contributions to reducing climate change in Taraba State, Nigeria, cannot be overstated.

• The Journal of Industrial Distribution & Business
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• v.9 no.9
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• pp.63-74
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• 2018

Purpose - The current study is to compare the cognition of stakeholders on hosting a mega sports event between Korea and the United States. In particular, to understand their cognition and perceptual conflict towards hosting a mega sports event, the study employed conflict theory. Furthermore, the study reviewed the role of social capital in the process of managing the mega sports events. Research Design, Data, and Methodology - Of homogeneous sampling, purposeful sampling method and criterion-based selection approach were used to collect interview data from key stakeholders who have been involved in hosting a mega sports events in Korea and the United States. In-depth interview transcripts were reviewed multiple tiems after transcription to extract concepts and meanings that were pertinenet to the experience involving hosting a mega sports event. Further member checks was conducted to increase the credibility of the results. Results - Results can be summarized as followed: First, stakeholders of Korea have a strong desire for positive economic effects of a mega sports event, compared to those in the United States who are more concerned in enhancing the public interests and concerns. Second, in Korea, various socio-political issues emerged at the same time and conflicts among multiple stakeholders have aggravated the situations to coordinate the issues. This was because legal system supporting socio-trust has not been established. On the other hand, major stakeholders of the United States consisted of community members who have socio-trust and networks. Thereby these social resources have been found playing a key role in building social capital that assists the stakeholders to coordinate the current issues and to solve them. Conclusions - The current study analyzed the cognition and perceptual conflict of stakehoders in a mega sports event. Social capital has beend found as a key catalyst to increase a network and cooperation among stakeholders. In order to enhance social capital in managing a mega sports event hosted in Korea, legal systems that establish networks and relationships among the related stakeholders need to be developed. Furthermore, the systematic guideline needs to be developed, organizing the sub-committees according to the types of stakeholders and the categorized common needs.

• Korean Journal of Radiology
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• v.22 no.8
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• pp.1240-1252
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• 2021

Objective: To compare the accuracy for detecting breast cancer in the diagnostic setting between the use of digital breast tomosynthesis (DBT), defined as DBT alone or combined DBT and digital mammography (DM), and the use of DM alone through a systematic review and meta-analysis. Materials and Methods: Ovid-MEDLINE, Ovid-Embase, Cochrane Library and five Korean local databases were searched for articles published until March 25, 2020. We selected studies that reported diagnostic accuracy in women who were recalled after screening or symptomatic. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. A bivariate random effects model was used to estimate pooled sensitivity and specificity. We compared the diagnostic accuracy between DBT and DM alone using meta-regression and subgroup analyses by modality of intervention, country, existence of calcifications, breast density, Breast Imaging Reporting and Data System category threshold, study design, protocol for participant sampling, sample size, reason for diagnostic examination, and number of readers who interpreted the studies. Results: Twenty studies (n = 44513) that compared DBT and DM alone were included. The pooled sensitivity and specificity were 0.90 (95% confidence interval [CI] 0.86-0.93) and 0.90 (95% CI 0.84-0.94), respectively, for DBT, which were higher than 0.76 (95% CI 0.68-0.83) and 0.83 (95% CI 0.73-0.89), respectively, for DM alone (p < 0.001). The area under the summary receiver operating characteristics curve was 0.95 (95% CI 0.93-0.97) for DBT and 0.86 (95% CI 0.82-0.88) for DM alone. The higher sensitivity and specificity of DBT than DM alone were consistently noted in most subgroup and meta-regression analyses. Conclusion: Use of DBT was more accurate than DM alone for the diagnosis of breast cancer. Women with clinical symptoms or abnormal screening findings could be more effectively evaluated for breast cancer using DBT, which has a superior diagnostic performance compared to DM alone.

• Journal of Korean Academy of Nursing
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• v.26 no.2
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• pp.359-371
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• 1996

This study has been done for the purpose of testing the effect of health education on the performance of health promoting behavior in college students, and identifying the factors affecting health promoting behaviors. A Nonequivalent control group posttest research design was used. Two hundred thirty college students at K College in T city were studied. Of them, 114 who attended a systematic health education session for three hours a week during one semester were the experimental group. And 116 college students who were chosen of matched sampling of grade, class and sex were the control group. This study was conducted from March 1 to July 2, 1995. The instruments used for this study included a survey of general characteristics, perceived health status, self-esteem, health promoting behavior and health locus of control. Analysis of data was done by use of mean, 1-test, Pearson correlation coefficient and multiple regression. The results of this study are summarized as follows : 1) The average item score for the health promoting behavior was low at 2.52. In the sub-categories, the highest degree of performance was ‘harmonious relationships’, following ‘sanitary life’, ‘self-esteem’, ‘rest and sleep’, and ‘emotional support’ and the lowest degree was ‘professional health management’. 2) Hypothesis 1 that the college students who get health education will have a higher degree of health promoting behavior than the college students who do not get health education was accepted. There was a statistically significant difference between the average of the experimentalgroup, 2.60, and the average of the control group, 2.45.（t＝11.30, p＝0.0009）. 3) Hypothesis 2 that the college students who get health education will have a higher score of perceived health status than college students who do not get the health education was rejected. （t＝1.13, p＝0.289） 4) Performance of health promoting behavior was positively correlated with self-esteem and grade and negatively correlated with perceived health status. 5) The most important factor affecting performance of health promoting behavior was self-esteem. The following suggestions are made based on the above results : 1) Replication of the research is needed to confirm effects of health education. 2) More effective health education programs need to be developed through by modification of teaching methods and content analysis of health education. 3) Other factors affecting health promoting behavior should be identified. 4) Nursing colleges or departments of nursing should make an effort to develop and carry out various health education programs for the health promotion of all college students.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.4
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• pp.1-7
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• 2020

This study quantified annual uptake and storage of carbon by urban greenspace in institutional lands and suggested improvement of greenspace structures to enhance carbon reduction effects. The study selected a total of five study cities including Seoul, Daejeon, Daegu, Chuncheon, and Suncheon, based on areal size and nationwide distribution. Horizontal and vertical greenspace structures were field-surveyed, after institutional greenspace lots were selected using a systematic random sampling method on aerial photographs of the study cities. Annual uptake and storage of carbon by woody plants were computed applying quantitative models of each species developed for urban landscape trees and shrubs. Tree density and stem diameter (at breast height) in institutional lands averaged 1.4±0.1 trees/100 ㎡ and 14.9±0.2 cm across the study cities, respectively. Of the total planted area, the ratio of single-layered planting only with trees, shrubs, or grass was higher than that of multi-layered structures. Annual uptake and storage of carbon per unit area by woody plants averaged 0.65±0.04 t/ha/yr and 7.37±0.47 t/ha, which were lower than those for other greenspace types at home and abroad. This lower carbon reduction was attributed to lower density and smaller size of trees planted in institutional lands studied. Nevertheless, the greenspace in institutional lands annually offset carbon emissions from institutional electricity use by 0.6 (Seoul)~1.9% (Chuncheon). Tree planting in potential planting spaces was estimated to sequester additionally about 18% of the existing annual carbon uptake. Enhancing carbon reduction effects requires active tree planting in the potential spaces, multi-layered/clustered planting composed of the upper trees, middle trees and lower shrubs, planting of tree species with greater carbon uptake capacity, and avoidance of the topiary tree maintenance. This study was focused on finding out greenspace structures and carbon offset levels in institutional lands on which little had been known.