• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.17 no.3
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• pp.279-298
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• 2019

This study comprehensively addresses recent progress at KAERI in waste treatment technology to cope with waste produced by pyroprocessing, which is used to effectively manage spent fuel. The goal of pyroprocessing waste treatment is to reduce final waste volume, fabricate durable waste forms suitable for disposal, and ensure safe packaging and storage. KAERI employs grouping of fission products recovered from process streams and immobilizes them in separate waste forms, resulting in product recycling and waste volume minimization. Novel aspects of KAERI approach include high temperature treatment of spent oxide fuel for the fabrication of feed materials for the oxide reduction process, and fission product concentration or separation from LiCl or LiCl-KCl salt streams for salt recycling and higher fission-product loading in the final waste form. Based on laboratory-scale tests, an engineering-scale process test is in progress to obtain information on the performance of scale-up processes at KAERI.

• The Journal of Society for e-Business Studies
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• v.24 no.1
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• pp.29-48
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• 2019

Recently, product design innovation to improve user experience has been perceived as a core element of enterprise competitiveness due to the fierce market competition and decrease of the technological gap between companies, but there is insufficient services to support the product experience evaluation of small and medium-sized companies (SMCs). The aim of this study is to develop a web-based product user experience evaluation and certification system supporting product design practices for SMCs. For system interface design, we conducted systematic functional requirement elicitation methods such as user survey, workflow analysis, user task definition, and function definition. Then main functions, information structure, navigation method, and detailed graphic user interfaces were developed with consideration of user interactions and requirements. In particular, it provides the databases for evaluation efficiency to support the evaluation process above a certain level of performance and efficiency, and knowledge databases to utilize in the evaluation and product design improvement. With help of the developed service platform, It is expected that the service platform would enhance SMCs' product development capability with regard to the user experience evaluation by connecting the consulting firms with SMCs.

• Convergence Security Journal
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• v.18 no.1
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• pp.19-31
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• 2018

As the ICT technologies advance, the unprecedently large amount of digital data is created, transferred, stored, and utilized in every industry. With the data scale extension and the applying technologies advancement, the new services emerging from the use of large scale data make our living more convenient and useful. But the cybercrimes such as data forgery and/or change of data generation time are also increasing. For the data security against the cybercrimes, the technology for data integrity and the time verification are necessary. Today, public key based signature technology is the most commonly used. But a lot of costly system resources and the additional infra to manage the certificates and keys for using it make it impractical to use in the large-scale data environment. In this research, a new and far less system resources consuming signature technology for large scale data, based on the Hash Function and Merkle tree, is introduced. An improved method for processing the distributed hash trees is also suggested to mitigate the disruptions by server failures. The prototype system was implemented, and its performance was evaluated. The results show that the technology can be effectively used in a variety of areas like cloud computing, IoT, big data, fin-tech, etc., which produce a large-scale data.

• Journal of the Korea Convergence Society
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• v.10 no.9
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• pp.55-61
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• 2019

The purpose of this study was to investigate the correlation between the hand dexterity and grip strength of 8-10 year elementary school children and 20-24 year college students. This study was conducted on 77 elementary school children aged 8-10 years old and 50 college students aged 20-24 years. The chopsticks manipulation test (CMT) and dymanomenter were used to evaluated hand dexterity and grip strength. In this study, the correlation between hand dexterity and grip strength, and the age, hand dexterity and grip strength of the subjects were compared. hand dexterity between 8-10 year old and 20-24 year old students were statistically different between 8 and 9 year olds, and the control was between 8 and 20-24 year old students. There were statistically significant differences. In addition, in the correlation between age, hand dexterity and grip strength, age and grip strength were positively correlated, and age and hand dexterity were negatively correlated. These results may contribute to the development of children's hand function and the fusion approach.

• Journal of Navigation and Port Research
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• v.43 no.1
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• pp.23-32
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• 2019

In this paper, we proposed a multi-chain Time of Arrival (ToA) positioning method to estimate positions using all received Loran-C signals from multiple chains without constraining to a single chain. Conventionally, we have to choose only one chain among several available chains for position estimation using Loran-C. Therefore, the number of signals to be used for positioning is limited to three to five. In general, if more signals are used for positioning estimation, its performance tends to be improved in terms of accuracy and availability. To validate the proposed method for multi-chain Loran-C, we firstly carried out a static positioning test in land. By analyzing the test results, we confirmed that the proposed method works well under a multi-chain Loran-C scenario. Subsequently, another mobile positioning test was conducted on board a vessel under a practical application scenario. From this second test, we successfully demonstrated that the multi-chain ToA positioning method even in situations where the conventional single-chain Loran-C approach fails for positioning.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.3
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• pp.303-310
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• 2021

Cracks in bridges are important factors that indicate the condition of bridges and should be monitored periodically. However, a visual inspection conducted by a human expert has problems in cost, time, and reliability. Therefore, in recent years, researches to apply a deep learning model are started to be conducted. Deep learning requires sufficient data on the situations to be predicted, but bridge crack data is relatively difficult to obtain. In particular, it is difficult to collect a large amount of crack data in a specific situation because the shape of bridge cracks may vary depending on the bridge's design, location, and construction method. This study developed a crack detection model that generates and trains insufficient crack data through a Generative Adversarial Network. GAN successfully generated data statistically similar to the given crack data, and accordingly, crack detection was possible with about 3% higher accuracy when using the generated image than when the generated image was not used. This approach is expected to effectively improve the performance of the detection model as it is applied when crack detection on bridges is required, though there is not enough data, also when there is relatively little or much data f or one class.

• The Korean Journal of Franchise Management
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• v.10 no.3
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• pp.25-35
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• 2019

Purpose - The major objective of this study was to investigate the effect of franchisor's (economic and philanthropic) CSR in inspiring franchisee's loyalty for the franchisor. Another aim of this investigation also was to clarify the mediating role of economic and social satisfaction in the relationship between franchisor's CSR and franchisee's loyalty. Research design, data, and methodology - This study explores the structural relationship between franchisor's CSR and franchisee's loyalty and in these relationships, the mediating role of relationship satisfaction. Data were gathered from employees(above manager) in food-service franchisee companies in Seoul, Korea. The questionnaires were distributed to managers of the franchise stores. A total of 251 questionnaires were collected. Data management and analysis were performed using SPSS 21.O and SmartPLS 3.0. Evaluation of measurement model and structural model was carried out using confirmatory factor analysis and correlation analysis. Result - The results of this study show as follows. First, economic CSR had positive effects on economic satisfaction and social satisfaction. Second, philanthropic CSR had positive effects on social satisfaction. Third, economic satisfaction and social satisfaction had positive effects on franchisee's loyalty to the franchisor. Conclusions - The important implications of this study have as follows. First, this study has found that economic CSR can create a high economic satisfaction and social satisfaction of franchisee. Second, this findings suggest that the philanthropic CSR can improve the social satisfaction of franchisee. Third, this results demonstrate, for the first time, that the economic satisfaction and social satisfaction of franchisees can play a crucial role to improve their loyalty for the franchisor and pursue mutual development by maintaining the stable business relationship with a franchisor. In this investigation there are at least three limitations. First, Because the research sample is limited to the foodservice franchisee in Seoul, it is not possible to be representativeness of the national franchisee. Second, CSR activities are mostly focused on large franchise companies. Therefore, there is a limit to the research approach. Finally, this study examined the effect of economic CSR and philanthropic CSR on the loyalty of franchisors, but in the future study, it is necessary to analyze the relationship between CSR and loyalty of franchise companies by collecting specific quantitative data such as re-contract rate and management performance of franchisees.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.4
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• pp.61-75
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• 2011

Recently, there is significant increasing of massive attacks, which try to infect PCs that visit websites containing pre-implanted malicious code. When visiting the websites, these hidden malicious codes can gain monetary profit or can send various cyber attacks such as BOTNET for DDoS attacks, personal information theft and, etc. Also, this kind of malicious activities is continuously increasing, and their evasion techniques become professional and intellectual. So far, the current signature-based detection to detect websites, which contain malicious codes has a limitation to prevent internet users from being exposed to malicious codes. Since, it is impossible to detect with only blacklist when an attacker changes the string in the malicious codes proactively. In this paper, we propose a novel approach that can detect unknown malicious code, which is not well detected by a signature-based detection. Our method can detect new malicious codes even though the codes' signatures are not in the pattern database of Anti-Virus program. Moreover, our method can overcome various obfuscation techniques such as the frequent change of the included redirection URL in the malicious codes. Finally, we confirm that our proposed system shows better detection performance rather than MC-Finder, which adopts pattern matching, Google's crawling based malware site detection, and McAfee.

• Knowledge Management Research
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• v.22 no.2
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• pp.1-17
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• 2021

In this study, we predicted the bitcoin prices of Bithum and Coinbase, a leading exchange in Korea and USA, using ARIMA and Recurrent Neural Networks(RNNs). And we used news articles from each country to suggest a separated RNN model. The suggested model identifies the datasets based on the changing trend of prices in the training data, and then applies time series prediction technique(RNNs) to create multiple models. Then we used daily news data to create a term-based dictionary for each trend change point. We explored trend change points in the test data using the daily news keyword data of testset and term-based dictionary, and apply a matching model to produce prediction results. With this approach we obtained higher accuracy than the model which predicted price by applying just time series prediction technique. This study presents that the limitations of the time series prediction techniques could be overcome by exploring trend change points using news data and various time series prediction techniques with text mining techniques could be applied to improve the performance of the model in the further research.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.1
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• pp.21-35
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• 2021

Based on social capital theory, this study investigated the influence of the start-up founder's social competence on the start-up's access to funding sources and performance through the mediating role of the type of social network. This study aimed to examine two types of social networks empirically (i.e., personal networks and business networks) as social capital in analyzing the effect of the founder's social competence and social capital on the method of accessing funding sources. A self-report questionnaire was administered to 252 South Korean start-up founders whose businesses are based in South Korea. Path analysis and mediation effect analysis were performed by structural equation modeling(SEM) using STATA 16.1. This study examined the full mediating effect of the founder's social competence on his/her personal and business networks, respectively, and how the effect leads to different methods to approach funding sources. This is the first study in South Korea to analyze empirically how social competence has contrasting effects on personal and business networks as well as how each type of network varies in its influence on the method founders use to attract investment. This study is also significant in that it proposed a new methodology by utilizing the position generator as the measure of personal and business networks to analyze social networks in detail. The analyses of 252 survey data collected over a period of six months will be a valuable resource that may provide researchers, founders, investors, and other stakeholders in the start-up ecosystem with meaningful implications.