• Journal of the Korean Society of Systems Engineering
• /
• v.18 no.2
• /
• pp.94-107
• /
• 2022

Accidents prevention and mitigation is the highest priority of nuclear power plant (NPP) operation, particularly in the aftermath of the Fukushima Daiichi accident, which has reignited public anxieties and skepticism regarding nuclear energy usage. To deal with accident scenarios more effectively, operators must have ample and precise information about key safety parameters as well as their future trajectories. This work investigates the potential of machine learning in forecasting NPP response in real-time to provide an additional validation method and help reduce human error, especially in accident situations where operators are under a lot of stress. First, a base-case SGTR simulation is carried out by the best-estimate code RELAP5/MOD3.4 to confirm the validity of the model against results reported in the APR1400 Design Control Document (DCD). Then, uncertainty quantification is performed by coupling RELAP5/MOD3.4 and the statistical tool DAKOTA to generate a large enough dataset for the construction and training of neural-based machine learning (ML) models, namely LSTM, GRU, and hybrid CNN-LSTM. Finally, the accuracy and reliability of these models in forecasting system response are tested by their performance on fresh data. To facilitate and oversee the process of developing the ML models, a Systems Engineering (SE) methodology is used to ensure that the work is consistently in line with the originating mission statement and that the findings obtained at each subsequent phase are valid.

• Computers and Concrete
• /
• v.32 no.6
• /
• pp.577-594
• /
• 2023

Engineered cementitious composites with calcined clay limestone cement (LC³-ECC) as a kind of green, low-carbon and high toughness concrete, has recently received significant investigation. However, the complicated relationship between potential influential factors and LC³-ECC compressive strength makes the prediction of LC³-ECC compressive strength difficult. Regarding this, the machine learning-based prediction models for the compressive strength of LC³-ECC concrete is firstly proposed and developed. Models combine three novel meta-heuristic algorithms (golden jackal optimization algorithm, butterfly optimization algorithm and whale optimization algorithm) with support vector regression (SVR) to improve the accuracy of prediction. A new dataset about LC³-ECC compressive strength was integrated based on 156 data from previous studies and used to develop the SVR-based models. Thirteen potential factors affecting the compressive strength of LC³-ECC were comprehensively considered in the model. The results show all hybrid SVR prediction models can reach the Coefficient of determination (R²) above 0.95 for the testing set and 0.97 for the training set. Radar and Taylor plots also show better overall prediction performance of the hybrid SVR models than several traditional machine learning techniques, which confirms the superiority of the three proposed methods. The successful development of this predictive model can provide scientific guidance for LC³-ECC materials and further apply to such low-carbon, sustainable cement-based materials.

• Asia pacific journal of information systems
• /
• v.19 no.3
• /
• pp.151-179
• /
• 2009

The purpose of this study is to make an empirical analysis on the factors affecting the intention for the continuous use of the BSC system, which has been recently spread in the public sector. Because the object of acceptance is the performance management system based on BSC (Balanced Scorecard) implemented in the form of information systems, this study proposes a research model by applying TAM (Technology Acceptance Model). Independent variables are factors affecting the acceptance of BSC system such as training, communication, IS support, CEO support and personal innovativeness, and we examine their effects on the dependent variable, namely, intention on continuous use via mediating variables: perceived usefulness and perceived ease of use. A questionnaire survey was conducted with public institutions(firms) that had introduced and were operating the BSC system; 264 valid questionnaires are adopted. Collected data are analyzed using SPSS 16.0 and AMOS 7.0. Results of reliability test show that all analyzed data are reliable. In validity test, one item regarding communication was excluded; 9 latent variables and 34 observed variables are used in the final analysis. Based on the results of the hypothesis test through path analysis using a structural equation model, 10 out of 16 hypotheses are accepted. Factors affecting perceived usefulness are training and IS(Information System) support. The analysis results indicate that perceived ease of use is mainly affected by IS support, CEO support, and personal innovativeness among the factors related to the acceptance of the BSC system. This suggests that, contrary to the expectation that the BSC system may be used without difficulty, the management's active support is required in order to attain expected improvement in productivity and work efficiency. This was also pointed out in case studies on the construction of the BSC system in public sectors. On the other hand, perceived ease of use is found to affect perceived usefulness. This supports the results of previous researches on TAM. Perceived ease of use and perceived usefulness are found to affect the attitude towards the use of the system. The intention on continuous use is affected more by perceived usefulness than by the attitude towards the use of system. This result supports the results of previous researches on TAM, showing that the BSC system is utilized substantially in worksites. This study is considered meaningful in that it was actually performed on users at public institutions(firms) that had introduced the BSC system and that it empirically tested hypotheses on the acceptance of the BSC system by applying TAM to the research model.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.23 no.7
• /
• pp.66-71
• /
• 2019

In this paper, a study was conducted on the method of using GPR data to predict rebar thickness inside a facility. As shown in the cases of poor construction, such as the use of rebars below the domestic standard and the construction of reinforcement, information on rebar thickness can be found to be essential for precision safety diagnosis of structures. For this purpose, the B-scan data of GPR was obtained by gradually increasing the diameter of rebars by making specimen. Because the B-scan data of GPR is less visible, the data was converted into the heatmap image data through migration to increase the intuition of the data. In order to compare the results of application of commonly used B-scan data and heatmap data to CNN, this study extracted areas for rebars from B-scan and heatmap data respectively to build training and validation data, and applied CNN to the deployed data. As a result, better results were obtained for the heatmap data when compared with the B-scan data. This confirms that if GPR heatmap data are used, rebar thickness can be predicted with higher accuracy than when B-scan data is used, and the possibility of predicting rebar thickness inside a facility is verified.

• Journal of Korea Entertainment Industry Association
• /
• v.15 no.5
• /
• pp.115-128
• /
• 2021

The purpose of this study is to examine the importance and satisfaction perceived in the purchase of goods and the use of a court in badminton club members. The results will be used for basic data to increase club members and present the methods to activate badminton. The survey on goods, price, programs, facilities, staff, and publicity was conducted. The IPA matrix was applied for data processing. The following conclusions were drawn. First, as a result of analyzing the ranking of importance and satisfaction, the first place of importance was coach's professionalism of staff factors, followed by safety of facility factors and program contents and effects of program factors. The first place of satisfaction was cleanliness and management of facility factors, followed by coach's professionalism of staff factors and staff's kindness of staff factors. Second, as a result of the IPA matrix of importance and satisfaction, Quadrant I included appropriateness of training time and program contents and effect of program factors, parking size and cleanliness and management of facility factors, coach's professionalism and staff's service attitude of staff factors, and customer service and complaint resolution of publicity factors. Quadrant II showed appropriateness of price, value for money, and discount policy of price factors and materials and design of goods factors. Quadrant III included excellent customer service of goods of goods factors, various program construction of program factors, court location and accessibility, and various convenient facilities of facility factors, and various publicity and event programs, website construction, and various publicity strategies of publicity factors. Quadrant IV showed brand value of goods, awareness, and brand specialty of goods of goods factors.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.23 no.4
• /
• pp.354-364
• /
• 2017

The importance of marine pollution prevention is increasing day by day both at home and overseas. Against this context, this study proposes policy directions to forge an improved system of coastal control for local governments. I have analyzed the coastal pollution response capacity of local governments to find out how the central government can better support these efforts to reinforce capacity. For the purposes of this research, I carried out a number of case studies on large-scale marine pollution accidents that occurred at home and abroad. According to the results, I identified the implications of the coastal pollution response capacity of local governments and suggested several alternatives such as construction of step by step response system, strengthening education and training, part of human network activation, establishment of grounds for securing response resources, and establishment of dedicated department to prepare for potential future marine pollution accidents. However, as little research has been done on the coastal pollution response capacity of local governments, this work may be regarded as an experimental study to help facilitate follow-up research in the future.

• Journal of Korea Water Resources Association
• /
• v.53 no.6
• /
• pp.395-408
• /
• 2020

This paper aims to develop and apply three different machine learning approaches (i.e., artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), and wavelet-based neural networks (WNN)) combined with an evolutionary optimization algorithm and the k-fold cross validation for multi-step (days) streamflow forecasting at the catchment located in Algeria, North Africa. The ANN and ANFIS models yielded similar performances, based on four different statistical indices (i.e., root mean squared error (RMSE), Nash-Sutcliffe efficiency (NSE), correlation coefficient (R), and peak flow criteria (PFC)) for training and testing phases. The values of RMSE and PFC for the WNN model (e.g., RMSE = 8.590 ㎥/sec, PFC = 0.252 for (t+1) day, testing phase) were lower than those of ANN (e.g., RMSE = 19.120 ㎥/sec, PFC = 0.446 for (t+1) day, testing phase) and ANFIS (e.g., RMSE = 18.520 ㎥/sec, PFC = 0.444 for (t+1) day, testing phase) models, while the values of NSE and R for WNN model were higher than those of ANNs and ANFIS models. Therefore, the new approach can be a robust tool for multi-step (days) streamflow forecasting in the Seybous River, Algeria.

• Journal of the Korea Concrete Institute
• /
• v.22 no.1
• /
• pp.19-27
• /
• 2010

Aging and severe environments are major causes of damage in reinforced concrete (RC) structures such as buildings and bridges. Deterioration such as concrete cracks, corrosion of steel, and deformation of structural members can significantly degrade the structural performance and safety. Therefore, effective and easy-to-use methods are desired for repairing and strengthening such concrete structures. Various methods for strengthening and rehabilitation of RC structures have been developed in the past several decades. Recently, FRP composite materials have emerged as a cost-effective alternative to the conventional materials for repairing, strengthening, and retrofitting deteriorating/deficient concrete structures, by externally bonding FRP laminates to concrete structural members. The main purpose of this study is to investigate the effectiveness of adaptive neuro-fuzzy inference system (ANFIS) in predicting behavior of circular type concrete column retrofitted with FRP. To construct training and testing dataset, experiment results for the specimens which have different retrofit profile are used. Retrofit ratio, strength of existing concrete, thickness, number of layer, stiffness, ultimate strength of fiber and size of specimens are selected as input parameters to predict strength, strain, and stiffness of post-yielding modulus. These proposed ANFIS models show reliable increased accuracy in predicting constitutive properties of concrete retrofitted by FRP, compared to the constitutive models suggested by other researchers.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.31 no.1
• /
• pp.67-87
• /
• 2020

The purpose of this study is to analyze current status and teacher librarians' perceptions of school library space composition and indoor environment, and propose some methods for the school library to be a basic educational facility. The space most secured by the 126 teacher librarians who participated in the survey was the free reading area, and the space with the lowest level was the media production and group project area. The most important types of spaces for teacher librarians are the teaching area and the free reading area, while the recognition of the importance of media production and group project areas is relatively low. Among the elements of indoor environmental assessment, they showed that safety and comfort were the most important but diversity and flexibility were relatively less important. The result of this analysis is different from the school and library policy direction that emphasizes the learning commons and maker spaces. Teacher librarians still seem to appreciate the importance of traditional library space. Therefore, it is necessary to include the establishment and operation of maker spaces and learning commons in the teacher librarians training and retraining process. In addition, it is necessary to increase the participation of users such as teachers, students, and parents in space composition and interior design initiatives to increase the user's interior environment satisfaction.

• Journal of Radiation Protection and Research
• /
• v.47 no.4
• /
• pp.237-245
• /
• 2022

Background: The current study reports measurements of activity concentrations of radon (²²⁰Rn) and thoron (²²⁰Rn) in dwellings, followed by inhalation dose assessment of the public, and then by the development of regulation and the national radon action plan (NRAP) in Cameroon. Materials and Methods: Radon, thoron, and thoron progeny measurements were carried out from 2014 to 2017 using radon-thoron discriminative detectors (commercially RADUET) in 450 dwellings and thoron progeny monitors in 350 dwellings. From 2019 to 2020, radon track detectors (commercially RADTRAK) were deployed in 1,400 dwellings. It was found that activity concentrations of radon range in 1,850 houses from 10 to 2,620 Bq/㎥ with a geometric mean of 76 Bq/㎥. Results and Discussion: Activity concentrations of thoron range from 20 to 700 Bq/㎥ with a geometric mean of 107 Bq/㎥. Thoron equilibrium factor ranges from 0.01 to 0.6, with an arithmetic mean of 0.09 that is higher than the default value of 0.02 given by UNSCEAR. On average, 49%, 9%, and 2% of all surveyed houses have radon concentrations above 100, 200, and 300 Bq/㎥, respectively. The average contribution of thoron to the inhalation dose due to radon and thoron exposure is about 40%. Thus, thoron cannot be neglected in dose assessment to avoid biased results in radio-epidemiological studies. Only radon was considered in the drafted regulation and in the NRAP adopted in October 2020. Reference levels of 300 Bq/㎥ and 1,000 Bq/㎥ were recommended for dwellings and workplaces. Conclusion: Priority actions for the coming years include the following: radon risk mapping, promotion of a protection policy against radon in buildings, integration of the radon prevention and mitigation into the training of construction specialists, mitigation of dwellings and workplaces with high radon levels, increased public awareness of the health risks associated with radon, and development of programs on the scientific and technical aspects.