• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.254-257
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• 2020

최근 악성코드에 의한 피해사례가 매년 증가하고 있다. 전통적인 시그니처 기반 안티바이러스 솔루션은 제로데이 공격이나 랜섬웨어처럼 전례가 없는 새로운 위협에 속수무책일 정도로 취약하다. 그럼에도 불구하고 많은 기업이 다중 엔드포인트 보안 전략의 일환으로 시그니처 기반 안티바이러스 솔루션을 유지하고 있다. 이에 응하고자 다양한 악성코드 분석기술이 출현해왔으며, 최근의 연구들은 부분 머신러닝을 이용하여 기존에 진행했던 시그니쳐 기반의 한계를 보완하고 노력하고 있다. 본 논문은 머신러닝을 이용한 바이러스 분석 모델과 머신러닝 알고리즘 중 GRU를 이용한 솔루션 시스템을 제안한다. 기존 DB Server를 통해 머신러닝을 학습 시키며 다양한 샘플과 형식을 이용하여 머신러닝을 학습하고 이를 이용해 새로운 악성코드, 변조된 악성코드의 탐지율을 높일 수 있다.

• Journal of Convergence for Information Technology
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• v.8 no.4
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• pp.247-253
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• 2018

This study was designed to analyze the difference in attendance and academic achievement based on spatio-temporal data relate to e-Learning patterns of university e-Learning learners. This study collected e-Learning data from 68 e-Learning classes, 13,611 learners during 3 years. Collected data were analyzed by t-test and two-way ANOVA. Major study findings were as follows. Firstly, e-Learning learners in school received higher than those of learners outside school both in attendance and academic achievement, while that academic achievement showed statistical significance. Secondly, the attendance and academic achievement by the day was in the order of e-Learning learners mainly in the morning, those in the afternoon and those at night, in addition there was statistical significance. Lastly e-Learning learners in the weekdays appeared higher than those of learners in the weekends both in attendance and academic achievement, also both of them showed statistical significance.

• Journal of Korea Society of Industrial Information Systems
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• v.10 no.2
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• pp.82-86
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• 2005

E-learning programs in every organizations are increasing rapidly every year. As the internet and multimedia tool spreads into every departments of organization work settings, the paradigm of education has changed. In the context of government and public organization, e-Learning has merits in the convenience of access, the reduction of costs, self-directed learning and so on. The purpose of this study is to find out some insights and lessons from the case analysis of e-Learning introduction strategies in ministry of labor.

• Proceedings of the Korea Contents Association Conference
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• 2005.05a
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• pp.36-50
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• 2005

e-Learning has been mushrooming with wide range of learning groups from pedagogy to andragogy. Despite of increasing e-learning opportunities, many people doubt whether e-learning learners really learn something. The related research papers emphasized that e-Learning would be a failure in terms of understanding of e-learners and intuitive learning activities for activating learner's long-term memory span. The current learning strategies in e-Learning may be based on the traditional classroom, and this results in boring and ineffective learning outcomes. This paper analyzed that how learners have received e-Learning for the last few years from the research and explained what could be the failing aspects of e-Learning. To be successful, e-Learning should consider the e-Learner's individualized teaming style and thinking patterns. When considering of various e-Learning components, the quality of e-learning should not be focused on any specific single factor, but develop every individual factor to the high level of quality. In conclusion, this paper suggest that we need new understand of e-Learning and e-Learner. Also the e-Learning strategies should be examined throughly whether they are on the side of learners and realized how they learn from e-Learning. Finally, we should add enormous imagination into e-Learning for next generation because their teaming patterns significantly differ from their parent's generation.

• The Journal of Korean Association of Computer Education
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• v.10 no.4
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• pp.73-82
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• 2007

The purpose of the study was to develope e-Learning multimedia resource management system to support developing of e-Learning contents. This system is to create and manage multimedia resources like video, audio, and image more easily. We analyzed and redesigned media asset management system that would be used in broadcast, press, and industry. This system has SCORM metadata and is consisted of Windows 2003 server and RDBMS. The survey was conducted to investigate usability and satisfaction for the developed system.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.2
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• pp.31-40
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• 2017

This study validate effectiveness of Online Entrepreneurship Education based on PBL(Problem-based Learning) and flipped learning. This study reveals online education of entrepreneurship based on PBL and flipped learning method has positive effect on personal entrepreneurship, will to be an entrepreneur, and problem-solving skills. First, the results show that entrepreneurship education based on PBL and flipped learning can improve entrepreneurship more than a previous learning method. Second, PBL and flipped learning based online education affects will to be an entrepreneur in positive way. Experimental group who experienced problem solving activity and flipped learning has more will to be entrepreneur than control group who takes previous learning method. Lastly, PBL and flipped learning method based entrepreneurship education also has positive effect on personal problem-solving techniques. This results show that online entrepreneurship education based on PBL and flipped learning has positive impacts on entrepreneurship, will to be an entrepreneur, and improving problem-solving skills significantly.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.45-48
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• 2016

오늘날의 고객은 다양한 정보를 통해 넓은 선택의 기회를 가진다. 이러한 상황에서 기업들은 고객과의 지속적인 관계를 유지하기 어려워짐에 따라 고객 유지와 신규 고객 유치를 위한 마케팅 비용을 천문학적으로 지출하고 있다. 기업들이 이탈하는 고객의 속성을 분석하고 이탈 시점을 예측할 수 있다면 마케팅에 사용되는 비용과 노력을 최소화할 수 있을 것으로 예측된다. 이를 위해 본 논문에서는 효과적인 고객 이탈 예측을 위한 딥러닝 기반의 이탈 예측 모델을 제안한다. 이 모델은 모바일 RPG 게임 고객의 시계열적인 행동 패턴을 이용하여 이탈을 예측하는 모델로, 예측을 위한 학습을 할 때 모델링된 고객 데이터를 분석하여 이탈 고객의 특성을 파악할 수 있게 한다. 실험을 통해 이탈 고객과 미 이탈 고객의 모델링된 값이 각각 특정 속성에 치중되어 있는 것을 확인하였고, 제안 모델이 합리적으로 고객의 이탈을 예측하는 것을 보였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.01a
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• pp.331-333
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• 2015

본 논문에서는 최근에 외국어로서의 한국어 학습 수요가 증가하고 있는 현실을 반영하여, 한국어를 외국어로 사용하는 한국어 수요자의 접근성을 고려한 초보적인 한국어 읽기 학습을 지원하는 학습지원 시스템을 설계하여 제시한다. 우리나라는 경제개발에 성공하고 주요 기간산업에서 세계적인 기업이 탄생하여 세계적으로 관심을 끌고 있다. 이런 현상에 따라서 결혼 이민자는 물론 국내 산업체에 취업하기 위해 입국하는 동남아시아를 중심으로 하는 근로자는 물론 첨단산업에 종사하기 위해 고학력의 외국인들이 많이 입국하고 있으며, k-pop을 비롯한 '한류'에 대한 관심이 고조되어, 다양한 국가의 다양한 계층에서 한국어에 대한 관심이 증가하고 있다. 이와 같은 현실에 비하여 특히 경제력과 학습수준이 낮은 외국인들은 정규적인 교육의 기회를 갖지 못하게 되어 여러 가지의 문제를 야기하고 있다. 이런 현실을 반영하여 초보적인 한국어 학습, 특히 읽기 학습을 지원하는 한국어 이러닝 시스템을 설계하여 제시하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.687-690
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• 2019

웹 사이트 사용자들은 자신의 취향에 맞춘 웹 사이트 개인화 서비스를 원한다. 이에 따라 관련 기업들은 웹 사이트의 회원가입을 통해 사용자들의 개인 정보를 관리하여 개인화 서비스를 지원하고 있다. 하지만 기업들의 개인 정보 유출 사고와 잘못된 기업 간 공유로 개인 정보보호 관리에 어려움이 있다는 문제점이 있다. 본 논문에서는 클라이언트 기반 딥러닝(Client-based Deep Learning)과 웹 브라우저 표준 데이터베이스 IndexedDB를 사용하여 검색 카테고리 추천 시스템을 구현한다.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.1-20
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• 2021

As the Great Reset is discussed at the World Economic Forum due to the COVID-19 pandemic, artificial intelligence, the driving force of the 4th industrial revolution, is also in the spotlight. However, corporate research in the field of artificial intelligence is still scarce. Since 2000, related research has focused on how to create value by applying artificial intelligence to existing companies, and research on how startups seize opportunities and enter among existing businesses to create new value can hardly be found. Therefore, this study analyzed the cases of startups using the comprehensive framework of the multi-level perspective with the research question of how artificial intelligence based startups, a sub-industry of software, have different innovation patterns from the existing software industry. The target firms are gazelle firms that have been certified as venture firms in South Korea, as start-ups within 7 years of age, specializing in machine learning modeling purposively sampled in the medical, finance, marketing/advertising, e-commerce, and manufacturing fields. As a result of the analysis, existing software companies have achieved process innovation from an enterprise-wide integration perspective, in contrast machine learning technology based startups identified unit processes that were difficult to automate or create value by dismantling existing processes, and automate and optimize those processes based on data. The contribution of this study is to analyse the birth of artificial intelligence-based startups and their innovation patterns while validating the framework of an integrated multi-level perspective. In addition, since innovation is driven based on data, the ability to respond to data-related regulations is emphasized even for start-ups, and the government needs to eliminate the uncertainty in related systems to create a predictable and flexible business environment.