• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.463-471
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• 2020

Humanity faces the fourth industrial revolution, a time of technological revolution by the collaboration of various industries including the fields of artificial intelligence(AI) and big data. Many countries are focused on fostering AI talent to prevail in the coming technological revolution. While Korea also provides some strategies to enhance the cultivation of AI talent, it is still difficult for Korean undergraduate students to get involved in AI studies. Through on the implementation of 'Big data analysis based AI education', which allows an easier approach to AI education, this paper examined the changes in the attitudes of undergraduate students regarding general AI education. 'Big data analysis based AI education' was provided at undergraduate level for 5.5 weeks (15 hours). The attitudes of undergraduate students were analyzed by pre-postmortem. The results showed there was a significant improvement in confidence and self-directed in regard to receiving AI education. With these results, further active research to develop basic AI education that also increases confidence and self-initiative can be expected.

• The Journal of the Korea Contents Association
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• v.17 no.4
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• pp.606-620
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• 2017

The purpose of this study was to develop and validate a Children's Play Disposition Scale(CPDS) which could be used to evaluate children's play patterns and preferences. The participants of this study were parents of 437 5-7-year-old children (age range from 51months to 106months). Preliminary items were developed through a review of relevant research, multiple intelligence theory and scales, confirmation of item adequacy and content validity. After the content validity was confirmed by experts, these items were edited down to a final list of 27 items representing 6 factors identified by exploratory factor analysis. The 6 factors of the scale consists of initiative, linguistic activity, logical-mathematical activity, art and craft, physical activity, and sensitivity respectively. Concurrent validity was established by using correlations between each factor of the CPDS and sub-factors and the total scores of Multiple Intelligence Checklist for preschoolers (Multiple Intelligence Institute Co., Ltd, 2008) and Multiple Intelligence Checklist for elementary schoolers (Multiple Intelligence Institute Co., Ltd, 2007). In addition, the reliability of each factor, as measured by Cronbach's ${\alpha}$, ranged from .53 to .79. The CPDS provides the developmental and educational information for strengthening children's developmental forte and for supporting children's developmental weakness. This scale can be used on developing children's play contents and guiding play methods in the future.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.7-10
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• 2003

In the field of financial technology, it is the U.S. initiative, and Japan is obliged to flattery in many respect. Currently Japan is in a too much defenseless situation that the economic structure is based on U.S. theory, In the conventional stochastic theory, it is also face that the prediction sometimes does not hit in the actual problem because it assumes a known probability distribution, none of which illustrates the real situation. A new research and development of management prediction support system is proposed based on fuzzy measures, that deals with the ambiguous, subjective evaluation by the people living in the real world well. Especially, the system will support venture, small and medium companies.

• Electronics and Telecommunications Trends
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• v.31 no.2
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• pp.9-17
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• 2016

인공지능은 미래사회 변혁을 가져올 주요한 기반 기술로 등장하고 있으며 미국, EU, 일본 등에서는 인공지능 기술 확보가 미래 국가 경쟁력을 좌우할 것으로 인식하고, 정부와 글로벌 대기업의 주도 하에 Brain Initiative, Human Brain Project 등 대규모의 R&D를 추진 중이다. IT 분야에서 인공지능 기술은 지능형 시스템의 필수 기반기술로 컴퓨팅 시스템의 성능 한계를 극복하고, 향후 컴퓨팅 환경을 와해적, 변혁적으로 발전시키는 토대가 될 전망이다. 본고에서는 이러한 인공지능의 국내외 기술 및 정책동향을 살펴보고 국내 인공지능 발전을 위한 방향성에 대해 논하고자 한다.

• Asian Journal for Public Opinion Research
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• v.11 no.2
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• pp.107-144
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• 2023

In competitive political contexts, sustaining power is the ultimate goal for political parties. Nominating celebrity politicians can be a double-edged sword for parent brands in attracting votes and influencing voting intention. This study contributes to the moderating role of brand affinity towards celebrity politicians. It considers celebrities' cognitive perceived benefits and voting intention relationship in a multiparty parliamentarian election. A cross-sectional survey with a stratified proportional random sampling technique in fifteen Lebanese districts ensured a representative sample. One thousand two hundred sixty-nine responses were found eligible for analysis. Findings indicate that brand affinity positively moderates the negative relationship between perceived benefits and voting intention. This study offers a new understanding of celebrity politicians' implementation strategy and campaign management and considers the contribution of the affective intelligence theory. It provides implications, limitations, and promising directions for future research on celebrity politicians.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.9-13
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• 2023

In this study, we explored the potential of integrating interactive AI callbot technology into the medical consultation domain as part of a broader service development initiative. Aimed at enhancing patient satisfaction, the AI callbot was designed to efficiently address queries from hospitals' primary users, especially the elderly and those using phone services. By incorporating an AI-driven callbot into the hospital's customer service center, routine tasks such as appointment modifications and cancellations were efficiently managed by the AI Callbot Agent. On the other hand, tasks requiring more detailed attention or specialization were addressed by Human Agents, ensuring a balanced and collaborative approach. The deep learning model for voice recognition for this study was based on the Transformer model and fine-tuned to fit the medical field using a pre-trained model. Existing recording files were converted into learning data to perform SSL(self-supervised learning) Model was implemented. The ANN (Artificial neural network) neural network model was used to analyze voice signals and interpret them as text, and after actual application, the intent was enriched through reinforcement learning to continuously improve accuracy. In the case of TTS(Text To Speech), the Transformer model was applied to Text Analysis, Acoustic model, and Vocoder, and Google's Natural Language API was applied to recognize intent. As the research progresses, there are challenges to solve, such as interconnection issues between various EMR providers, problems with doctor's time slots, problems with two or more hospital appointments, and problems with patient use. However, there are specialized problems that are easy to make reservations. Implementation of the callbot service in hospitals appears to be applicable immediately.

• Journal of Korean Library and Information Science Society
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• v.45 no.1
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• pp.297-317
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• 2014

This study is to produce baseline data, in its purpose of improving the quality of life of industrial workers as well as the business competitiveness, though improvements in reading culture. The data produced in this study will be based on questionnaire, regarding sub-topics of the reading environment, the status of reading culture, and remaining demands. The results argue that the responding workers in Siheung Smart Hub Complex had inadequate environment of reading, while had weak status of reading culture. We propose the ways of improvements in the reading culture of the worker in Siheung Smart Hub Complex, as well as their reading infrastructure.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.348-353
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• 2006

Autonomous and intelligent resource model (AIR-model) defines a building-block of complex systems to pursue value creation by means of diverse resources, referred to as an AIR-unit, and presents a collaboration model with the AIR-units. An AIR-unit represents a piece of resources, such as machines, labor, raw materials, and other assets, considered individually by a complex system as means to accomplish given tasks. It is defined with its own service capability and a goal, and pursues achieving the goal by means of the capability. Moreover, an Air-unit is equipped with autonomy and intelligence, whereby it makes a decision on its course of action on its own initiative. Air-units collaborate on system operations with each other through goal-oriented negotiations. In this research, distinctive features of the AIR-model are addressed and described in detail. Principal components of the AIR-model are also designed via object-oriented modeling techniques. A prototype system based on the AIR-model is finally presented as an embodiment tool of a fractal manufacturing system (FrMS).

• Journal of National Security and Military Science
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• s.2
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• pp.261-283
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• 2004

To build up the military strength based on information oriented armed forces, the Korean ministry of national defense (MND) promotes the defense CALS (Continuous Acquisition and Life cycle Support) initiative for the reductions of acquisition times, improvements of system qualities, and reductions of costs. These defense CALS activities are the major component of the underlying mid and long term defense digitization program and the ultimate goal of program is to bring a quick victory by providing real-time battlefield intelligence and the economical operations of the military. The concept of defense CALS is to automate the acquisition and disposition of defense systems throughout their life cycle. For implementing defense CALS, the technology for exchange and sharing CALS standard data that is created once and used many times should be considered. In order to develop an efficient CALS information exchange and sharing system, it is required to integrate distributed and heterogeneous data sources and provide systematic search tools for those data. In this study, we developed a content based search engine technology which is essential for the construction of integrated data environments. The developed technology provides the environment of sharing the CALS standard data such as SGML(Standard Generalized Markup Language) and STEP(Standard for The Exchange of Product model data). Utilizing this technology, users can find and access distributed and heterogeneous data sources without knowing its actual location.

• Information and Communications Magazine
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• v.29 no.11
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• pp.3-10
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• 2012

정보통신기술의 급속한 발전으로 인해 인터넷은 사회 전분야를 변화시키고 있으며 다양하고 폭넓은 이용 행태에 따라 지금 이 순간에도 엄청난 데이터를 생산해 내고 있다. 대부분의 인터넷 데이터는 제한적인 활용 이외 단순 생성과 소멸을 반복해 왔으나 최근 들어 빅데이터(Big Data)라는 핵심 키워드의 부상으로 인터넷 데이터에 대한 관심이 고조되고 있다. 과거에도 데이터 마이닝(Data Mining), 비즈니스 인텔리전스(Business Intelligence), 라이프 로그(Life Log) 등을 통해 데이터 기반의 부가가치를 창출하려는 노력은 시도되어 왔다. 그렇다면 왜 다시 빅데이터라는 이름으로 재부상 하고 있는 것일까? 이는 정보통신기술의 진화와 맞물려 새롭게 부상하고 있는 인터넷 글로벌 기업들이 지속적으로 생성되는 다양한 데이터들을 확보하고 그 속에서 숨겨진 가치를 찾고 인사이트(Insight)를 도출하려는 시도를 통해 데이터 보유와 활용이 새로운 경쟁력이 될 수 있음을 입증하고 있기 때문이다. 이러한 시도들은 빅데이터를 다양한 분야에서 중요한 이슈로 자리매김하게 하고 있다. 이러한 상황에서 과연 우리는 빅데이터 시대를 어떻게 리드하고 무엇에 집중하여야 할 것인가? 본 연구는 현재 뜨거운 감자로 부상한 빅데이터를 정의하고 빅데이터 시장분석, 사례분석, 정책분석을 통해 시사점을 도출하여 향후 다가올 빅데이터 시대의 국가경쟁력 확보를 위한 빅데이터 이니셔티브(Initiative)의 필요성과 중점 방향 등을 제언하고자 한다.