• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.439-442
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• 2003

In order to solve the difficulties of parameter settings in SA algorithm, an improved practical SA algorithm is proposed by employing the threading techniques, appropriate software structures, and dynamic adjustments of temperature parameters. Threads provide a mechanism to realize a parallel processing under a disperse environment by controlling the flux of internal information of an application. Thread services divide a process by multiple processes leading to parallel processing of information to access common data. Therefore, efficient search is achieved by multiple search processes, different initial conditions, and automatic temperature adjustments. The proposed are methods are evaluated, for three types of Traveling Salesman Problem (TSP) (random-tour, fractal-tour, and TSPLIB test data)are used for the performance evaluation. The experimental results show that the computational time is 5％ decreased comparing to conventional SA algorithm, furthermore there is no need for manual parameter settings. These results also demonstrate that the proposed method is applicable to real-world vehicle routing problems.

• Current Industrial and Technological Trends in Aerospace
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• v.7 no.1
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• pp.141-152
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• 2009

The simultaneous operation of multiple UAV's makes it possible for us to raise the mission accomplishment and cost efficiency. For this we need an easily scalable control algorithm, and swarm intelligence having the characteristics such as flexibility, robustness, decentralized control and self-organization comes into the spotlight as a practical substitute. In this paper the features of swarm intelligence are described, and various research results are introduced which show that the application of swarm intelligence to the control of multiple UAV's enables the missions of surveillance, path planning, target tracking and attack to be accomplished efficiently by simulations and tests.

• Journal of Korean Society for Quality Management
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• v.48 no.3
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• pp.361-379
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• 2020

Purpose: The purpose of this study was to investigate the relationship between employee authenticity and customer loyalty. This study also examined whether rapport positively mediated the above relationship. In addition this study address the moderating role of customer emotional intelligence in the relationship between employee authenticity and rapport. By developing moderated a mediation model, we addressed indirect conditional effect of customer emotional intelligence on the relationship between employee authenticity and customer loyalty via rapport. Methods: The survey data was collected by customers who used various services in Korea. The main hypotheses were tested using a cross-sectional design, with questionnaires administered to 292 customers. Results: The result of empirical analysis has shown that employee authenticity was significantly positively related to customer loyalty. We have also found that rapport positively mediated the relationship between employee authenticity and customer loyalty. While there was a significant moderating effect of customer emotional intelligence on the relationship between employee authenticity and rapport, the moderated mediating role of customer emotional intelligence was found. Conclusion: The results provide useful theoretical and practical implications to the organizations and managers who want to improve customer loyalty. Future research directions with the limitation of the study were discussed.

• Journal of The Korean Association of Information Education
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• v.26 no.5
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• pp.457-465
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• 2022

The government has proposed various policies to 'extend the time for teaching information education in elementary schools'. However, in the 2022 revised practical arts (technical·home economics) curriculum, information education is still organized for only 17 hours the same as before, and there is not enough connection with the middle school information subject. In this study, policies related to information education in elementary schools such as National Strategy of Artificial Intelligence, Comprehensive Plan of Information Education, Education Policy Direction and Core Tasks in the Artificial Intelligence Era, and Digital Talent Education Plan were analyzed. In addition, after the '2022 revised national curriculum guidelines' was announced in 2021, the problems of the practical arts curriculum were analyzed by analyzing materials of the draft proposal of the curriculum and comments posted on the Public Participation Communication Channel. Finally, I suggested a plan to link the 2022 revised practical arts (technology·home economic) curriculum to the information subject of middle school in detail, and to expand information education in elementary schools.

• The Journal of Industrial Distribution & Business
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• v.11 no.6
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• pp.41-53
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• 2020

Purpose: The purpose of this study is to review the previous studies on the characteristics of the image search service provided by using artificial intelligence, the social impact characteristics, and the moderating effect of perceived anthropomorphism, and conduct empirical analysis to identify the constituent factors affecting purchase intention. To clarify. Through this, I tried to present theoretical and practical implications. Research design, data, and methodology: Research design was that characteristics of image search service (ubiquity and information quality) and social impact characteristics (subjective norms, electronic word of mouth marketing) are affected by mediation of satisfaction and flow, therefore, control of perceived anthropomorphism have an effect on purchase intention to increase. For analysis, research conducted literature review, and developed questionnaires, so that EM firm which is a specialized research institute has collected data. This was conducted on 410 people between the 20s and 50s who have mobile shopping experiences. SPSS Statistics 23 and AMOS 23 had been used to perform necessary analysis such as exploratory factor analysis, reliability analysis, feasibility analysis, and structural equation modeling based on this data. Results: first, ubiquity, information quality and subjective norms were found to have a positive effect on purchase intention through satisfaction and flow parameters. Second, satisfaction and flow were found to have a mediating effect between ubiquity, information quality, and subjective norms and purchase intentions. However, there was no mediating effect between eWOM information and purchase intention. Third, perceived anthropomorphism was found to have a moderating effect between information quality and satisfaction, and it was found that there was no moderating effect on the relationship between information quality and flow. Conclusions: The information quality of image search services using artificial intelligence has a positive effect on satisfaction, and it has been found that there is a positive moderate effect of perceived anthropomorphism in this relationship, which may be an academic contribution to the distribution science utilizing artificial intelligence. Therefore, it is possible to propose a distribution strategy that improves purchase intention by utilizing image search service and anthropomorphism in practical business and providing a more enjoyable immersive experience to customers.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.111-118
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• 2016

Artificial intelligence (AI) is making computer systems intelligent to do right thing. The AI is used today in a variety of fields, such as journalism, medical, industry as well as entertainment. The impact of AI is becoming larger day after day. In general, the AI system has to lead the optimal decision under uncertainty. But it is difficult for the AI system can derive the best conclusion. In addition, we have a trouble to represent the intelligent capacity of AI in numeric values. Statistics has the ability to quantify the uncertainty by two approaches of frequentist and Bayesian. So in this paper, we propose a methodology of the connection between statistics and AI efficiently. We compute a fixed value for estimating the population parameter using the frequentist learning. Also we find a probability distribution to estimate the parameter of conceptual population using Bayesian learning. To show how our proposed research could be applied to practical domain, we collect the patent big data related to Apple company, and we make the AI more intelligent to understand Apple's technology.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.3
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• pp.421-430
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• 2017

In this research, we propose a methodology for assessing security vulnerability of the national defense intelligence system, considering not only target elements but also the interconnection relationship of the whole system. Existing approaches decide the security vulnerability of the whole system by assessing only target elements. However, those approaches have an issue with potentially showing the same outcome for the systems that have identical target elements but the different types of interconnection relationships. We propose a more practical assessment method which takes the interconnection relationship of a whole system into consideration based on the concept of SNA(Social Network Analysis).

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.182-190
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• 2024

Various artificial intelligence neural network models that have emerged since 2014 enable the creation of new content beyond the existing level of information discrimination and withdrawal, and the recent generative artificial intelligences such as ChatGPT and Gall-E2 create and present new information similar to actual data, enabling natural interaction because they create and provide verbal expressions similar to humans, unlike existing chatbots that simply present input content or search results. This study aims to present a model that can improve the ChatGPT communication skills of university students through curriculum research on ChatGPT, which can be participated by students from all departments, including engineering, humanities, society, health, welfare, art, tourism, management, and liberal arts. It is intended to design a way to strengthen competitiveness to embody the practical ability to solve problems through ethical attitudes, AI-related technologies, data management, and composition processes as knowledge necessary to perform tasks in the artificial intelligence era, away from simple use capabilities. It is believed that through creative education methods, it is possible to improve university awareness in companies and to seek industry-academia self-reliant courses.

• Asia pacific journal of information systems
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• v.32 no.3
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• pp.496-513
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• 2022

Artificial intelligence or big data technologies can benefit finance companies such as those in the insurance sector. With artificial intelligence, companies can develop better customer segmentation methods and eventually improve the quality of customer relationship management. However, the application of AI-based customer segmentation in the insurance industry seems to have been unsuccessful. Findings from our interviews with sales agents and customer service managers indicate that current customer segmentation in the Korean insurance company relies upon individual agents' heuristic decisions rather than a generalizable data-based method. We propose guidelines for AI-based customer segmentation for the insurance industry, based on the CRISP-DM standard data mining project framework. Our proposed guideline provides new insights for studies on AI-based technology implementation and has practical implications for companies that deploy algorithm-based customer relationship management systems.

• Korean Security Journal
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• no.34
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• pp.259-278
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• 2013

With advances of information technology (IT) and the Internet, it became much easier to search and collect information through many different types of web search engine. Such information only restricted to the intelligence services became available to the public, and the increased open source changed the intelligence collection activities of governments. Open Source Intelligence (OSINT) was introduced to organize and analyze the large volumes of information. OSINT is actively used after the 9/11 terrorist attack, and the United States government invest a huge amount of budget to conduct research and develope technology about OSINT. Although many Western countries recognize the importance of OSINT and deal with open source as priority, South Korea has not fully understand the important role of OSINT. Therefore, this study introduces the fundamental principles of OSINT and provides practical examples of OSINT usage. OSINT is an effective source to prevent terrorist attacks as well as a variety of crimes. Extensive discussion and suggestions for future usages are provided.