• Proceedings of the Korean Information Science Society Conference
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• 2006.06a
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• pp.391-393
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• 2006

인터넷의 급속한 확산과 대량 정보의 이동은 문서의 요약을 더욱 필요로 하고 있다. 본 논문은 비음수 행렬 인수분해로(NMF, non-negative matrix factorization) 얻어진 비음수 의미 가변 행렬(NSVM, non-negative semantic variable matrix)을 이용하여 자동으로 포괄적 문서요약 하는 새로운 방범을 제안하였다. 제안된 방법은 인간의 인식 과정과 유사한 비음수 제약을 사용한다. 이 결과 잠재의미색인에 비해 더욱 의미 있는 문장을 선택하여 문서를 요약할 수 있다. 또한, 비지도 학습에 의한 문서요약으로 사전 전문가에 의한 학습문장이 필요 없으며, 적은 계산비용을 통하여 쉽게 문장을 추출할 수 있는 장점을 갖는다.

• 한국디지털정책학회:학술대회논문집
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• 2003.12a
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• pp.551-568
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• 2003

이러닝은 지식 정보 사회에서 온라인 상에서 이루어지는 여러 산업 중에서 가장 각광 받고 있는 산업의 하나로, 점차 그 잠재적 성장 가능성을 인정받고 있다. 초고속 인터넷 인프라와 높은 교육열을 가진 우리나라는 이러닝 선진국이 되기 위한 하드웨어와 그것을 운용할 인적자원에 대한 기본적인 준비는 갖춘 상태라 하겠다. 하지만 그런 우수한 하드웨어와 인적자원만으로는 이러닝의 성공을 보장할 수 없다는 것은, 인간과 하드웨어를 연결하고 두 요소간에 혈액 같은 흐름을 맡게 될 소프트 스킬, 즉 교수 설계, 컨텐트 개발과 학습 운영 등에 대한 준비가 충분히 되었는가에 대한 의문이 나타나기 때문이다. 본 고에서는 차세대 성장 동력 사업의 하나라고 지목되고 있는 이러닝이 성공적으로 자리를 잡아가고, 나아가 국제 경쟁력을 갖추기 위해 요구되는 과제들이 무엇인가를 도출하고자 현재 이러닝의 실시 현황을 살펴보고, 국내외 성공적인 사례와 선진 동향에서 교훈을 찾아내었고 국가적 차원에서 성장 동력 사업으로 시급히 검토되어야 할 문제들로 보이는 항목들에 대해 살펴보았다. 무엇보다 이러닝의 지속적이고 안정적인 성장을 위해서는 전문 인력의 육성이 시급하다고 보며 협의의 이러닝 (학습 매체)이 아닌 광의의 이러닝 (성과 매체)으로 거듭 나야 함을 주장하고 있다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.293-296
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• 2005

최근 우리나라는 가계신용의 급신장과 신용불량의 급증 등으로 개인 신용부문이 금융기관의 건전성 유지에 부정적인 영향을 미치고 있다. 이러한 잠재적 문제를 사전에 방지하기 위해 금융기관 등에서는 개인 신용평가에 대한 수요가 커지고 있는 실정이다. 주어진 데이터로부터의 반복적인 학습 과정을 거쳐 패턴을 분류하고 또한 모델과 학습 방법에 따라 입력변수와 목적변수의 속성이 연속형이나 이산형인 경우를 모두 다룰 수 있는 신경망 모델은 개개인의 다양하고 복잡한 데이터를 입력변수로 받아서 신용등급을 나누는데 우수한 능력을 보여줄 수 있다. 본 논문에서는 신경망 모델을 이용해 개인의 신용등급을 객관적이고 일률적으로 평가해서 등급을 나누어주는 알고리즘을 제안하고자 한다.

• Korean Journal of School Psychology
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• v.11 no.1
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• pp.253-274
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• 2014

The present study classified groups based on latent profile of self-determination motivation(amotivation, external motivation, intrinsic motivation), and examined the determinants for each group. The data was collected through panel data of Korea Education Longitudinal Study(KELS), total 5,459 participants who answered questionnaires of self-determination motivation of two times both second grade of middle school and second grade of high school. To identify the change motivational type, standardized residual was conducted using SPSS 17.0., and the latent classes for the change of motivational type was investigated using M-Plus in the frame work of Latent Profile Analysis(LPA). The results indicated that five groups(increase of self-determination, self-determination maintenance, self-determination developmental delay, elf-determination confusion, decrease of self-determination group) were classified based on latent profile. In addition, parental control, academic self-concept, teacher-student relationship, test anxiety, avoidance orientation, gender, father's education, and income were significantly related to each group. Lastly, the implications for directions of the adolescent counseling, limitations and future research are discussed.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1605-1609
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• 2010

CGCM3.1 SRES B1 시나리오의 2D 변수들을 입력값으로 인공신경망 모형을 이용한 스케일 상세화기법으로 강부식(2009)은 소양강댐 유역의 월 누적강수 경향분석을 실시하였다. 원시 GCM 시나리오를 스케일 상세화 시키기 위한 기법의 하나로 인공신경망 모형을 사용할 수 있는데, 이 경우 GCM에서 모의되는 강수플럭스, 해면기압, 지표면 근처에서의 일 평균온도, 지표면 근처에서의 일평균온도, 지표면으로부터 발생하는 잠열플럭스 등과 같은 22개의 변수를 잠재적인 예측인자로 사용하여 신경망을 구성하게 된다. 입력변수세트의 구성은 인공신경망의 계산 효율을 좌우하는 중요한 요소라 할 수 있다. 본 연구에서는 변수의 물리적 특성을 고려하여 순차적인 변수선택을 통한 신경망 입력변수 세트를 구성하고 입력세트 간의 학습성과 비교를 통하여, 최적 입력변수 선정 및 신경망의 학습효과를 높일 수 있는 방법에 대해 연구하였다. 물리적 상관성이 높다고 판단되는 GCM_Prec, huss, ps를 입력변수로 하여 순차적인 케이스를 학습해본 결과 huss와 ps를 입력변수로 하는 케이스에 대해서 적은 오차와 높은 상관성을 보였다, 또한, 신경망의 학습 효과를 높이기 위해 홍수기와 비홍수기로 구분하여 학습한 결과 홍수기와 비홍수기로 구분하여 신경망을 구성하였을 경우가 향상된 모의값을 나타내었다. 기후변화모의자료는 CCCma(Canadian Center for Climate Modeling and Analysis)에서 제공되는 CGCM3.1/T63 20C3M 시나리오를 사용하였으며, 관측값으로는 AWS에서 제공된 일 누적강수를 사용하였다. 인공신경망의 학습기간은 1997년부터 2000년이며, 검증기간은 2001년부터 2004년으로 구성하였다.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.205-213
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• 2022

This study is to analyze the relationship among potential variables of self-development, social development, learning readiness, and academic ability using data from the Panel Study on Korean Children, which was surveyed in 2014, and to find factors affecting the academic ability of preschool children will be. The subjects of this study were 6-year-old children of 1113 households among 2150 households in the 7th Panel Study on Korean Children(2014) data, excluding non-responders and system-missing 1037 households. As a result of analyzing the path effect of the research model, it was found that, between self-development and academic skills, self-development had a direct effect on academic skills and also had a significant indirect effect through social development and learning readiness as a medium. In addition, it was found that learning readiness had the greatest influence among self-development, social development, and learning readiness on academic skills. As a result, the academic skills of preschool-age children should be treated with great importance in order to develop them into talents with creativity and problem-solving ability.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.161-165
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• 2022

The purpose of this study was to improve children's positive perceptions of the future by examining the relationship between parental attachment, parental involvement in learning, and children's perceptions of the future, and by identifying the specific influence of each variable on children's perceptions of the future. Frequency analysis and descriptive statistical analysis were performed on data from the 12th year of the Korean Children's Panel (2019), and Pearson's moment correlation coefficient was calculated for correlation analysis between variables. Multiple regression analysis was performed to examine the explanatory power of parental attachment to children's perception of the future and parental participation in learning. The research results are as follows. First, the correlations among all the latent variables of parental attachment, parental participation in learning, and children's future perception showed significant correlations. Second, the explanatory power of children's perception of the future was found in the order of 'mother' trust, 'family'-based participation, 'father' trust, and 'mother' communication. These results suggested that parental trust and warm, warm participation in home-based learning were important variables in children's positive perception of the future.

• Journal of The Korean Association of Information Education
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• v.14 no.4
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• pp.589-603
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• 2010

Game addiction is the one of side effects from current knowledge-based society, So it is very important to find students with game addiction and treat them as early as possible. In this paper, first of all, a measure scale is developed for diagnosing game addiction. The scale is made based on the literature reviews. Also, a game model is developed based on virtues education. The proposed model has the following characteristics. First, it can induce active participation of students. Second, it helps students find and decide a moral standard related to online game addiction for themselves. Third, students can learn a moral standard naturally through narratives related to various real-life situations. The followings are concluded after applying the proposed game to elementary school students with game addiction. First, game addiction is relieved for those students, specially for "high risk" and "potential" groups. Second, the proposed game can improve respect to others and individual responsibility.

• Journal of the Korea Computer Graphics Society
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• v.25 no.4
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• pp.9-16
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• 2019

In this paper, we propose a hydrodynamic scene separation method for wave propagation from video imagery using autoencoder. In the coastal area, image analysis methods such as particle tracking and optical flow with video imagery are usually applied to measure ocean waves owing to some difficulties of direct wave observation using sensors. However, external factors such as ambient light and weather conditions considerably hamper accurate wave analysis in coastal video imagery. The proposed method extracts hydrodynamic scenes by separating only the wave motions through minimizing the effect of ambient light during wave propagation. We have visually confirmed that the separation of hydrodynamic scenes is reasonably well extracted from the ambient light and backgrounds in the two videos datasets acquired from real beach and wave flume experiments. In addition, the latent representation of the original video imagery obtained through the latent representation learning by the variational autoencoder was dominantly determined by ambient light and backgrounds, while the hydrodynamic scenes of wave propagation independently expressed well regardless of the external factors.

• School Mathematics
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• v.5 no.1
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• pp.97-114
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• 2003

This study is a basic step research for developing mathematics teacher education program using the potential power of explorative softwares for learning geometry. This study investigates the characteristics of the softwares and noteworthy points in its applying process. Analizing an impact of this softwares on the mathematics leaching and learning, this study presents the desirable direction for developing the teacher education program for mathematics teachers to be ableto teach successfully. Focusing on GSP as an to manage classrooms of the 21st century successfully. Focusing on GSP as an excellent explorative software used widely in the current mathematics classrooms, this study investigates the potential contents to be used in the teacher education program for mathematics teachers to get new kinds of experiences about the softwares and suggests implications for choosing contents and instructional methods of the program using the softwares.