• Electronics and Telecommunications Trends
• /
• v.28 no.3
• /
• pp.170-182
• /
• 2013

카자흐스탄은 한국의 기술과 문화에 대해 높게 평가하고 있으며 한국을 자국 경제발전의 롤모델로 인식하고 양국 간 관계를 전략적 동반자 관계로 격상시키는 한편 협력 분야를 에너지, 자원 분야에서 기초과학과 IT 분야로 확대하고 있다. ICT는 카자흐스탄이 산업 다각화를 위해 전략적으로 육성하고자 하는 분야로 막대한 ICT 프로젝트를 제시하며 세계적인 경쟁력을 가진 우리 ICT 기업의 투자와 참여를 적극 요청하고 있다. 카자흐스탄과는 과거 (주)대우의 카작텔레콤 인수를 시작으로 ETRI의 우정, 이러닝 등 기술 지원 사업과 정책자문 등 다양한 협력 사업 경험을 가지고 있다. 그러나 양국 정부의 지원을 바탕으로 협력 사업을 진행하는 공공기관이나 충분한 자체 사업 역량을 보유한 대기업에 비해 모든 면에서 열세인 중소기업은 정확한 정보를 바탕으로 구체적인 전략을 수립하고 현지에 진출해야만 성공할 가능성이 높다. 따라서 본고에서는 우리 ICT 기업의 카자흐스탄 시장 진출을 지원하기 위한 사전 연구로서 ICT 시장 현황을 파악하고 현지 시장 진출 시 고려해야 할 요인들을 소개하고, 전략적 접근 방법을 제시하고자 한다.

• The Journal of the Convergence on Culture Technology
• /
• v.4 no.2
• /
• pp.197-204
• /
• 2018

One of the hottest issues in our 21st century is AI. Just as the automation of manual labor has been achieved through the Industrial Revolution in the agricultural society, the intelligence information society has come through the SW Revolution in the information society. With the advent of Google 'Alpha Go', the computer has learned and predicted its own machine learning, and now the time has come for the computer to surpass the human, even to the world of Baduk, in other words, the computer. Machine learning ML (machine learning) is a field of artificial intelligence. Machine learning ML (machine learning) is a field of artificial intelligence, which means that AI technology is developed to allow the computer to learn by itself. The time has come when computers are beyond human beings. Many companies use machine learning, for example, to keep learning images on Facebook, and then telling them who they are. We also used a neural network to build an efficient energy usage model for Google's data center optimization. As another example, Microsoft's real-time interpretation model is a more sophisticated translation model as the language-related input data increases through translation learning. As machine learning has been increasingly used in many fields, we have to jump into the AI industry to move forward in our 21st century society.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.10 no.1
• /
• pp.55-67
• /
• 2015

This study examines innovation resistance to smart learning, an emerging innovative technology for startups and corporate ventures in the education market. The study explores whether the relative advantage, compatibility and complexity of an innovation, attitudes toward existing learning method(s), and perceived self-efficacy significantly affect innovation resistance. Additionally, the effects of such innovation resistance on future use and the moderating effect according to demographic characteristics are examined. The results of the analysis using a structural equation model showed that all the factors considered (except relative advantage) affects innovation resistance, innovation resistance significantly affects intention to use.

• Smart Media Journal
• /
• v.11 no.3
• /
• pp.74-89
• /
• 2022

Due to the unique recipes and processes of each company, not only differences among the results of dyeing textile materials exist but they are also difficult to predict. This study attempted to develop a color prediction model based on deep learning to optimize color realization in the dyeing process. For this purpose, deep learning-based models such as multilayer perceptron, CNN and LSTM models were selected. Three forecasting models were trained by collecting a total of 376 data sets. The three predictive models were compared and analyzed using the cross-validation method. The mean of the CMC (2:1) color difference for the prediction results of the LSTM model was found to be the best.

• Annual Conference on Human and Language Technology
• /
• 2018.10a
• /
• pp.584-586
• /
• 2018

사이버 공격 기법이 다양해지고 지능화됨에 따라 침해사고 발생이 증가하고 있으며, 그에 따른 피해도 확산되고 있다. 이에 따라 보안 기업들은 다양한 침해사고를 파악하고 빠르게 대처하기 위하여 위협정보를 정리한 인텔리전스 리포트를 배포하고 있다. 하지만 인텔리전스 리포트의 형식이 정형화되어 있지 않고 점점 증가하고 있어, 인텔리전스 리포트를 수작업을 통해 분류하기 힘들다는 문제점이 있다. 이와 같은 문제를 해결하기 위해 본 논문에서는 개체명 인식 시스템을 활용하여 비정형 인텔리전스 리포트에서 위협정보를 자동으로 탐지하고 추출할 수 있는 모델을 제안한다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2024.01a
• /
• pp.1-4
• /
• 2024

코로나 19(Covide-19)이후 가상과 현실이 융·복합 되어 사회·경제·문학활동과 가치 창출이 가능한 메타버스가 차세대 핵심산업으로 부상하고 있다. 이에 자사 보유 기술, IP(Intellectual Property) 등을 활용하여 메타버스 플랫폼을 구축하고자 하는 기업들이 증가하여 지식재산권을 둔 법적 이슈들이 새롭게 나타나고 있다. 따라서 본 논문에서는 상표권 침해를 보호하기 위하여 딥 러닝 기반 객체 탐지모델인 YOLOv5 모델을 활용한 메타버스 환경에서의 상표권 탐지 시스템을 제안한다.

• Journal of Convergence for Information Technology
• /
• v.10 no.6
• /
• pp.59-69
• /
• 2020

This study is a qualitative study in which a focus group interview is applied to explore nursing students' perception of blended learning. 21 students in the 4th grade of nursing department were divided into 4 groups to collect data through interviews and content analysis was conducted. As a result of the study, it was categorized into four topics: 'Application and operation that are not thoroughly prepared', 'Loss of direction and departure from learning', 'One-way listening', and 'Convenience'. Students were satisfied with blended learning which is free from time and space constraints and repetitive, but felt inadequacy and unsatisfactoriness about quality of online contents, system, and preparation for applying blended learning. In order to apply blended learning in the future nursing classes, high-quality online content should be developed based on the effective design of online and offline classes considering the curriculum, and a systematic, administrative, financial, and institutional foundation to support online course should be prepared. In addition, a support system should be created to guide students' self-directed learning activities in online classes of blended learning.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.16 no.4
• /
• pp.189-196
• /
• 2016

The purpose of this study is to investigate the causal relationships among self-efficacy, perceived usefulness, supervisor and peer support, satisfaction, and transfer intentions in the corporate mobile learning. For this study, the web survey was administered to 302 mobile learning learners of the A domestic corporation in South Korea. Structural equation modeling(SEM) analysis was conducted in order to examine the causal relationships among the variables. The results indicated that first, self-efficacy, perceived usefulness, and supervisor and peer support had positive effects on satisfaction. Second, supervisor and peer support and satisfaction had positive effects on transfer intentions. Third, satisfaction mediated the relationship between self-efficacy and perceived usefulness, while it did partially the relationship between supervisor and peer support and transfer intentions. Based on the result of the research, the study proposes organizational environment with cooperative supervisor and peer support should be made in order to improve the level of learners' transfer intentions. In addition, learning strategies that facilitate learners' self-efficacy and mobile information technology acceptance are needed to develop for enhancing the learners' satisfaction.

• Journal of Korea Technology Innovation Society
• /
• v.21 no.2
• /
• pp.818-837
• /
• 2018

Technological innovation has inherent difficulties, largely due to the uncertainties of technology. Thus, the forecasting methodology to reduce the risk of uncertainty in the innovation process has been presented both in quantitative and qualitative fields. On the other hand, big data and artificial intelligence have attracted great interest recently, and deep learning, which is one of the algorithms of AlphaGo, is showing excellent performance. In this study, deep learning methodology was applied to the prediction of innovation performance. To make the prediction model, we used KIS 2016 data. The input factors were importance of information source and innovation objectives and the output factor was innovation performance index, which was calculated for this study. As a result of the analysis, it can be confirmed that the accuracy of prediction is improved compared with the previous studies. As learning progressed, the degree of freedom of prediction also improved.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2021.07a
• /
• pp.363-366
• /
• 2021

본 연구에서는 콘크리트의 균열을 추출하여 추출한 균열을 분석하고 시각화하여 나타내는 방법을 제안한다. 추출한 균열을 분석하여 길이, 넓이, 평균 폭 등의 주요 지표를 측정하여 균열 부위에 대한 세부 정보를 파악할 수 있게 하였다. 특히 균열 분석 과정에서 기존의 균열 중심부와 에지 간의 직선 최단 거리 계산을 통한 균열 폭 측정 방식이 아닌 내접원 탐색 방식을 적용하여 다각형의 균열에 대한 폭 측정 방식을 제안하고 있다. 또한 분석 결과를 Wavefront 3D OBJ 모델과 CAD 파일로 생성하였고, 이를 웹 브라우저를 통해 입체적으로 볼 수 있도록 시각화 하였다.