• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.478-480
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• 2022

Smart Railway as a next generation railway technology is expected to have rapid evolution with developments of information and communications tehchology. Especially, smart railway will be progressed more evolved transportation means for railway operation and costomer service based with spread of commercial 5G communication. So, it is very important to investigate and analyze trends of smart railway related tehcnology of 5G mobile communication for samrt railway infra structure, server technolgy for AI, big data, deep learning, information security technology, sensor and IoT. In this paper, 5G based communicaion technology and application techology related smart railway is described and trends of new techlogy on this communication tehnology is investigated. The results of this study can be used for smart railway study and implementation, research and development for smart railway communicaion technology, etc.

• Knowledge Management Research
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• v.23 no.4
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• pp.21-41
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• 2022

With the development of AI and digital technologies such as big data, metaverse, and the Internet of Things, Robotic Process Automation (RPA) has brought great development and change to companies. Among these realistic industrial areas by RPA, the call center service area, which consists of a combination of complex high-tech systems and professional operation groups, has now reached the stage where AI is conducting counseling. The evolution of this digital transformation has become an important direction of change in the digital-related industry sector. Along with these changes, there have been many changes in the technical stress of the members of the organization within the RPA organization and their solutions. In this study, the representative psychological mechanisms were presented as Digital Shadow Work (DSW), expressed as 'unpaid work', and Organizational Citizenship Behavior (OCB), which is 'an act that helps organizations other than their duties'. This study theoretically contributes to the extension of the DSW concept to the organizational members.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.127-137
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• 2023

COVID-19 has not only affected all sectors of society, economy and politics, but also had a huge impact on industry. The non-face-to-face exchange method was essential to prevent infectious diseases, and the generation who experienced it recognizes the importance of a platform that can be quickly accessed anytime, anywhere, and attention is focused on the Metaverse that can accommodate it well. Each financial industry uses a differentiated metabus platform strategy, focuses on new customer service and revenue generation, and is also used as an internal and external communication channel. This paper analyzes the theoretical background of the financial sector metaverse and domestic and international cases, and studies and describes the direction of using the financial sector metaverse platform to secure MZ generation contact points.

• Convergence Security Journal
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• v.22 no.5
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• pp.135-143
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• 2022

The defense environment is rapidly changing, such as nuclear and missile threats of North Korea, changes in war patterns, and a decrease in military service resources due to low birth rate. In order to actively respond to these changes, the Korean military is promoting Defense Innovation 4.0 and is trying to foster an army armed with high technology such as artificial intelligence (AI), big data analysis, etc. In this regard, we analyze the effectiveness of the radar-based AI scientific guard system applied by high technology for guard operations using Analytic Hierarchy Process (AHP). We first select evaluation factors that can assess the effectiveness of the scientific guard system, and analyze its relative importance. Each evaluation factor was selected by deriving a significant concept from operating principle and how they work, and by consulting experts on the correlation between each factor and effectiveness of the scientific guard system. We examine the relative effects of the radar-based AI scientific guard system and existing scientific guard system based on the importance of the evaluation factors.

• Journal of Software Assessment and Valuation
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• v.13 no.2
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• pp.9-17
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• 2017

Software compliance is an essential process when Open Source Software is included in software development to avoid such as license violation issue. However, analyzing quite big software which involves many developers requires enormous time and hard difficulty. To resolve these kinds of problem, SPDX formalizes and standardize the metadata about the software package. When the use of SPDX is activated, software package analysis would be simple and could contribute fair Open Source Software distribution. In this paper, we develop blockchain based SPDX distribution platform which fulfills the requirement of SPDX lifecycle to provide SPDX database which does not depend on particular centralized service but serve as distributed ledger and control by user's certification and their purpose. Moreover, to contribute invigoration of blockchain based SPDX distribution platform, we develop SPDX document generation plug-in for integrated development environment such as Visual Studio.

• Journal of The Korea Institute of Healthcare Architecture
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• v.29 no.4
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• pp.45-56
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• 2023

Purpose: Recently, Korea has been promoting smart cities that combine artificial intelligence(AI), big data, ICT, and the Internet of Things(IoT), and these technologies are being applied to housing services and are developing into smart housing services. This study try to analyze what is the most necessary and important the AI smart housing services for the housing disadvantaged persons through a survey of experts and the housing disadvantaged persons. And by collecting these necessary and important services, we aim to present elements and directions for the AI smart housing services policy for the housing disadvantaged persons. Methods: Firstly, we asked 11 experts, Secondly, the desire and necessity for the above smart housing service was identified through an online survey targeting the housing disadvantaged persons. Thirdly, the survey was analyzed and reliability was measured through descriptive statistical analysis using SPSS program. Fourthly, based on the results of descriptive statistics analysis, the necessity and importance of AI smart housing services from the perspective of the housing disadvantaged were derived. Results: The results of this study are that firstly, both experts and the housing disadvantaged persons viewed safety and health-related services as the most important and necessary among AI smart housing services, secondly, there is a difference in perspectives on the services that should be priority between experts and people with disabilities, and lastly there are differences in perspectives and needs for services that should be priority between the disabled and the elderly.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.121-130
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• 2023

In the school field, AI convergence education is recommended, which utilizes AI in education to change the paradigm of society. This study was conducted to define the terms of AI and AI convergence education to minimize the confusion of terms and to analyze the educational needs of teachers from the perspective of conducting AI convergence education. To achieve the purpose, 19 experts' opinions were collected, and a self-administered questionnaire was administered to 125 secondary school teachers enrolled in the AI convergence major at the Graduate School of Education. As a result of the analysis, the experts defined AI convergence education as a methodology for problem solving, not AI-based or utilization education. In the analysis of teachers' educational needs, "AI and big data" was ranked first, followed by "AI convergence education methodology" and "learning practice using AI". The significance of this study is that it defined the terminology by collecting the opinions of experts amidst the confusion of various terms related to AI, and presented the educational direction of AI convergence education for in-service teachers.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• 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.

• The Korean Journal of Franchise Management
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• v.8 no.4
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• pp.33-43
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• 2017

Purpose - Previous studies about corporate image generally explore how corporate image affects a company's effectiveness from the consumer view. However this study attempts to explore the impacts of corporate image (reliability, friendly, corporate social responsibility, and innovation) on employees' altruistic behaviors in the franchise industry context. This study also examine whether organizational trust and affective commitment play a mediating role in the relationship between corporate image and employees' altruistic behaviors. The authors developed several hypotheses to achieve these purposes. Research design, data, and methodology - The data were collected from employees in food-service franchise companies located in Seoul, Korea. Among a total of 363 questionnaires distributed, 294(response rate of 81%) questionnaires were returned. After excluding 18 invalid respondent questionnaires, 276 valid questionnaires(response rate of 76%) were coded and analyzed using frequency, confirmatory factor analysis, correlations analysis, and structural equation modeling with SPSS 21 and SmartPLS 3.0. Result - The findings of the study are as follows: First, friendly, CSR, and innovation had positive effects on organizational trust, but reliability did not have a significant effect on organizational trust. Second, reliability and friendly of corporate image had positive effects on affective commitment, but CSR and innovation did have a significant effect on affective commitment. Third, organizational trust and affective commitment had positive effects on employees' altruistic behaviors. Conclusions - The aim of this study is to investigate the franchise corporate image as a significant influencing factor of employees' altruistic behaviors. The data were collected from only employees from franchising companies. The findings might vary from position to position. Future studies need to collect and compare data from managers. Future studies need to consider other variables that affect employees' altruistic behaviors. For example, leadership and market orientation might influence employees' attitude and behaviors. Also, future research should include other variables and it may have limitations in sample representative because of sampling franchise corporate in Seoul. Future studies will include franchise corporate all over the country. Future studies can also consider other variables (e.g., job performance and turnover intentions) to measure employee performance at the level of individuals and identify the impact of employee performance on business performance at the level of corporate.