• Journal of Korea Water Resources Association
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• v.54 no.8
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• pp.607-616
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• 2021

The purpose of this study is to simulate the transport of nonuniform sediment considering the hiding-exposure effect numerically. In order to calculate the transport of multi-disperse suspended sediment mixtures, the set of advection-diffusion equations for each particle class is solved. The applicability of the numerical model is examined by comparing the simulation results with experimental data. In this study, we calculate the vertical distribution of total concentration of sediment particles using two approaches: (1) by considering the mixture as represented by a single size; and (2) by combining the concentration of the sediment corresponding to several particle size classes; From the simulation results, it is shown that both approaches calculate reasonable results due to the narrow range of size distribution. Under the condition of nonuniform sediment, the critical shear stress of the sediment particle is influenced by the size-selective entrainment, i.e., hiding-exposure effect. It is shown in this study that the effect of hiding-exposure effect on the erosion rates of fine sand is negligibly small.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.3059-3072
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• 2022

A Jacobian-Free Newton Krylov Two-Nodal Coarse Mesh Finite Difference algorithm based on Nodal Expansion Method (NEM_TNCMFD_JFNK) is successfully developed and proposed to solve the three-dimensional (3D) and multi-group reactor physics models. In the NEM_TNCMFD_JFNK method, the efficient JFNK method with the Modified Incomplete LU (MILU) preconditioner is integrated and applied into the discrete systems of the NEM-based two-node CMFD method by constructing the residual functions of only the nodal average fluxes and the eigenvalue. All the nonlinear corrective nodal coupling coefficients are updated on the basis of two-nodal NEM formulation including the discontinuity factor in every few newton steps. All the expansion coefficients and interface currents of the two-node NEM need not be chosen as the solution variables to evaluate the residual functions of the NEM_TNCMFD_JFNK method, therefore, the NEM_TNCMFD_JFNK method can greatly reduce the number of solution variables and the computational cost compared with the JFNK based on the conventional NEM. Finally the NEM_TNCMFD_JFNK code is developed and then analyzed by simulating the representative PWR MOX/UO₂ core benchmark, the popular NEACRP 3D core benchmark and the complicated full-core pin-by-pin homogenous core model. Numerical solutions show that the proposed NEM_TNCMFD_JFNK method with the MILU preconditioner has the good numerical accuracy and can obtain higher computational efficiency than the NEM-based two-node CMFD algorithm with the power method in the outer iteration and the Krylov method using the MILU preconditioner in the inner iteration, which indicates the NEM_TNCMFD_JFNK method can serve as a potential and efficient numerical tool for reactor neutron diffusion analysis module in the JFNK-based multiphysics coupling application.

• Fisheries and Aquatic Sciences
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• v.25 no.4
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• pp.189-201
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• 2022

Jellyfish is an emerging aquaculture species, farmed for Oriental cuisines and nutraceutical ingredients. This study aimed to examine antioxidative and antimicrobial potentials of various fractions of the jellyfish, Acromitus hardenbergi. The bell and oral arms of the jellyfish were sequentially extracted with petroleum ether (PE), dichloromethane (DCM), chloroform (CHCl₃), methanol (MeOH), and water (H₂O) to extract its bioactive in an increasing polarity gradient. Test fractions were assayed for antiradical activities using electron spin resonance spectrometry, β-carotene-linoleate model and Folin-Ciocalteu assay; and antimicrobial activity against 2 Gram-negative bacteria, 4 Gram-positive bacteria and 2 fungal species using the disc diffusion assay. All fractions were also subjected to Fourier Transform Infrared (FTIR) analysis to identify types of functional groups present. It was found that the hydrophilic extracts (H₂O fractions) possessed the most effective radical scavenging activity (p < 0.05) while the lipophilic extracts (PE fractions) the most active antimicrobial activity, especially against Gram-positive bacteria (p < 0.05). Total oxidation substrates content was found to be highest in the PE fractions of jellyfish bell and oral arms (p < 0.05). FTIR data showed that the H₂O and MeOH fractions contains similar functional groups including -OH, -C=O, -N-H and -S=O groups, while the PE, DCM, and CHCl₃ fractions, the -CH₃, -COOH groups. This study showed that A. hardenbergi contains antioxidants and antimicrobials, thereby supporting the traditional claim of the jellyfish as an anti-aging and health-promoting functional food. Bioassay-guided fractionation approach serves as a critical milestone for the strategic screening, purification, and elucidation of therapeutically significant actives from jellyfish.

• Asia-Pacific Journal of Business
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• v.12 no.3
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• pp.1-36
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• 2021

Purpose - This empirical study, aims to identify the determinants of adoption and acceptance of mobile payment as to understand why it is successful in some countries in Sub-Saharan Africa but failing in others. A comparative study of a successful mobile payment service and a purported failed one was done as to have some insights to the factors affecting acceptance of the technology. Design/methodology/approach - The strength of three notable theories: theory of diffusion of innovation (DOI), the extended unified theory of user acceptance of information technology (UTAUT2) and self-efficacy theory were use. The self-efficacy of government support inclusion as, a moderating variable in the form of infrastructure, securing transaction and price value revealed the relevance of government in the success of mobile payment service. By means of a field survey of 705 subjects in two separate regions of Africa (East and West), the data was collected and use to test the research model. Findings - The study result shows the importance of the moderating factor of government support to the success of mobile payment of any nation. The result also shows the importance of the perception of relative advantage, compatibility, complexity, social influence as already revealed by other studies. Research implications or Originality - Mobile payment success in some part of Sub-Saharan Africa is well known but also suggested to fail in some Sub-Saharan African countries. Buttressing the need for understanding of the factors affecting mobile payment acceptance. This article empirically examined the factors influencing the success of mobile payment, and we implicated that if the implementation of mobile payment is to be successful for mobile commerce in any nation, adoption, acceptance and use by its citizen is imperative.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.3
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• pp.471-481
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• 2023

Digital twin is considered as a key technology of industry 4.0, thus being essential for the future of industrial production. Despite the significance, a systematic analysis of its technological landscape is lacking. This study aims to investigate the technological development trends and newly emerging technological convergence opportunities in the domain of digital twin by exploiting patent information derived from U SPTO. For this purpose, this study visualized and predicted the convergence dynamics among patent classification codes by adopting patent co-classification analysis and link prediction approach. The findings show that the number of digital twin-related patent applications has increased significantly since 2018. The CPC code G06F showed the highest eigenvector centrality, while G05B was characterized by highest betweenness centrality. According to the predictive model, 41 novel links were revealed, acting as potential technology convergence opportunities. These links were then categorized into 11 different domains. The most dominant category was "digital data processing and artificial intelligence", which could play a foundational role in the diffusion of digital twin technology. The presence of digital twin technology is dominant in manufacturing, but its applications are expected to expand, including "climate change", "healthcare" and "aerospace engineering". The derived insights can support R&D managers and policy makers in formulating R&D strategies and directing future R&D investment decisions.

• Korean Journal of Radiology
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• v.25 no.3
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• pp.224-242
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• 2024

The emergence of Chat Generative Pre-trained Transformer (ChatGPT), a chatbot developed by OpenAI, has garnered interest in the application of generative artificial intelligence (AI) models in the medical field. This review summarizes different generative AI models and their potential applications in the field of medicine and explores the evolving landscape of Generative Adversarial Networks and diffusion models since the introduction of generative AI models. These models have made valuable contributions to the field of radiology. Furthermore, this review also explores the significance of synthetic data in addressing privacy concerns and augmenting data diversity and quality within the medical domain, in addition to emphasizing the role of inversion in the investigation of generative models and outlining an approach to replicate this process. We provide an overview of Large Language Models, such as GPTs and bidirectional encoder representations (BERTs), that focus on prominent representatives and discuss recent initiatives involving language-vision models in radiology, including innovative large language and vision assistant for biomedicine (LLaVa-Med), to illustrate their practical application. This comprehensive review offers insights into the wide-ranging applications of generative AI models in clinical research and emphasizes their transformative potential.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.137-154
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• 2018

Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.

• Journal of Korea Water Resources Association
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• v.53 no.8
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• pp.627-636
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• 2020

Debris flow disasters primarily occur in mountainous terrains far from cities. As such, they have been underestimated to cause relatively less damage compared with other natural disasters. However, owing to urbanization, several residential areas and major facilities have been built in mountainous regions, and the frequency of debris flow disasters is steadily increasing owing to the increase in rainfall with environmental and climate changes. Thus, the risk of debris flow is on the rise. However, only a few studies have explored the characteristics of flooding and reduction measures for debris flow in areas designated as steep slopes. In this regard, it is necessary to conduct research on securing independent disaster prevention technology, suitable for the environment in South Korea and reflective of the topographical characteristics thereof, and update and improve disaster prevention information. Accordingly, this study aimed to calculate the amount of debris flow, depending on disaster prevention performance targets for regions designated as steep slopes in South Korea, and develop an independent model to not only evaluate the impact of debris flow but also identify debris barriers that are optimal for mitigating damage. To validate the reliability of the two-dimensional debris flow model developed for the evaluation of debris barriers, the model's performance was compared with that of the hydraulic model. Furthermore, a 2-D debris model was constructed in consideration of the regional characteristics around the steep slopes to analyze the flow characteristics of the debris that directly reaches the damaged area. The flow characteristics of the debris delivered downstream were further analyzed, depending on the specifications (height) and installation locations of the debris barriers employed to reduce the damage. The experimental results showed that the reliability of the developed model is satisfactory; further, this study confirmed significant performance degradation of debris barriers in areas where the barriers were installed at a slope of 20° or more, which is the slope at which debris flows occur.

• Asia Marketing Journal
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• v.10 no.2
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• pp.1-29
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• 2008

The objective of our study is to provide an exploratory model for forecasting sales take-off timing of a product in the context of multi-national markets. We evaluated the usefulness of key predictors such as multiple market information, product attributes, price, and sales for the forecasting of sales take-off timing by applying the suggested model to monthly sales data for PDP and LCD TV provided by a Korean electronics manufacturer. We have found some important results for global companies from the empirical analysis. Firstly, innovation coefficients obtained from sales data of a particular product in other markets can provide the most useful information on sales take-off timing of the product in a target market. However, imitation coefficients obtained from the sales data of a particular product in the target market and other markets are not useful for sales take-off timing of the product in the target market. Secondly, price and product attributes significantly influence on take-off timing. It is noteworthy that the ratio of the price of the target product to the average price of the market is more important than the price ofthe target product itself. Lastly, the cumulative sales of the product are still useful for the prediction of sales take-off timing. Our model outperformed the average model in terms of hit-rate.

• Korean Journal of Construction Engineering and Management
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• v.15 no.5
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• pp.31-39
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• 2014

It has been a long time since cars had become important means of transportation in human life. Since 1970s, cars have been increasing steadily because of rising individual income and changing lifestyle toward leisure and convenience. The number of cars is just 1.8 per thousand populations in 1970s, however, in 2012, it has increased to 291.15. Forecasting the demand for cars would be useful to plan, construction or management in the field of motor industry, road building and establishing facilities. Our study predicts the demand of cars through estimating the growth curve model. Especially, we include ageing variables to forecasting identifying the effect of ageing on the demand of cars. The main findings are as follows. In 2045, the number of cars is expected to reach 486.8 per thousand populations with passing a primary saturation point at early 2020s. Also, due to effect of ageing, the predicted demand of cars is about 10% lower than in case of which if ageing effect not exist.