• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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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.

• 항공우주산업기술동향
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• 제7권1호
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• pp.141-152
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• 2009

복수 무인기의 동시 운용을 통하여 임무 수행 효율성 및 경제성 제고를 꾀할 수 있으며 이를 위해서는 확장성이 용이한 제어 알고리듬을 필요로 하게 되는데 유연성, 강건성, 분산형 제어 및 자기조직화의 특징을 갖는 무리 지능이 현실적인 대안으로 각광받고 있다. 본 논문에서는 무리 지능의 특징과 이를 복수 무인기 제어에 응용함으로써 정찰, 경로 계획, 표적 추적 및 공격 등 다양한 임무를 효율적으로 수행할 수 있음을 시뮬레이션과 시험으로 입증하고 있는 다양한 연구결과를 소개한다.

• 품질경영학회지
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• 제48권3호
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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.

• 정보교육학회논문지
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• 제26권5호
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• pp.457-465
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• 2022

정부는 그동안 '초등학교에서 정보교육 시수를 확대하겠다'는 다양한 정책을 제시하였다. 그러나 2022 개정 실과(기술·가정) 교육과정에서는 여전히 정보 교육을 이전과 동일하게 17시간만을 편성하고 있고, 중학교 정보교과와의 연계성을 충분히 제시하지 않고 있다. 본 연구에서는 2019년 이후 발표된 인공지능 국가 전략, 정보교육 종합 계획, 인공지능 시대의 교육 정책 방향과 핵심 과제, 디지털 인재 양성 방안 등 초등학교 정보교육 관련 정책들을 살펴보았다. 또한, 2021년에 '2022 개정 교육과정 총론 주요 사항'이 발표된 이후, 2022년부터 시작된 실과(기술·가정) 교육과정 시안과 관련된 공청회 자료집을 분석하고, 국민참여소통채널에 올라온 댓글들을 분석한 후 실과(기술·가정) 교육과정의 문제점을 살펴보았다. 끝으로, 2022 개정 실과(기술·가정) 교육과정을 중학교 정보교과와 연계하기 위한 방안을 구체적으로 제안하고, 초등학교에서의 정보 교육을 활성화기 위한 방안을 제안하였다.

• 산경연구논집
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• 제11권6호
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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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• 제16권2호
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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.

• 한국군사과학기술학회지
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• 제20권3호
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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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• 제16권1호
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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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• 제32권3호
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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.

• 시큐리티연구
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• 제34호
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• pp.259-278
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• 2013

21세기 정보통신기술의 발달과 급격한 인터넷의 확산으로 비밀 출처정보에서만 수집이 가능했던 정보(Information)가 인터넷을 통해 쉽게 검색이 가능하게 되었다. 공개정보(Open Source)가 폭발적으로 증가하면서 정보수집활동에 큰 변화가 일어나고 있으며, 이러한 변화는 국가정보기관에서의 정보수집활동에도 영향을 미치고 있다. 공개출처정보(Open Source Intelligence: OSINT)는 이렇게 넘쳐나는 정보를 효과적으로 처리하고 분석하기위해 등장하였다. OSINT는 주로 9.11테러 이후에 빠르게 적용되었으며, 국가정보기관에서는 이와 관련된 연구와 기술개발에도 적극 참여하고 있다. 이렇게 서구국가에서는 OSINT의 중요성을 인지하고 공개정보(Open Source)를 분석하는 일이 최우선 순위로 떠오르고 있다. 하지만 국내에서는 공개정보(Open Source)의 중요성에 대한 인식이 미흡한 실정이다. 본 연구에서는 OSINT를 소개하고 중요성을 제고하는 것을 목적으로 하였다. 감당하기 힘들 정도로 늘어나는 많은 양의 공개정보(Open Source)를 효과적으로 이용하기 위하여 OSINT의 운용사례와 방법을 소개하고 중요성을 논의하였다. 이는 국가안보를 위협하는 테러뿐만 아니라 각종 범죄를 효과적으로 대응하기위한 방안이기도 하다.