• Title/Summary/Keyword: 계층적 Bayesian 모형

Search Result 43, Processing Time 0.021 seconds

Predicting the Effect of Puzzle-based Computer Science Education Program for Improving Computational Thinking (컴퓨팅 사고력 신장을 위한 퍼즐 기반 컴퓨터과학 교육 프로그램의 효과 예측)

  • Oh, Jeong-Cheol;Kim, Jonghoon
    • Journal of The Korean Association of Information Education
    • /
    • v.23 no.5
    • /
    • pp.499-511
    • /
    • 2019
  • The preceding study of this study developed puzzle-based computer science education programs to enhance the computational thinking of elementary school students over 1 to 3 times. The preceding study then applied such programs into the field, categorized the effects of education into CT creativity and CT cognitive ability to improve the education programs. Based on the results of these preceding studies, the hierarchical Bayesian inference modeling was performed using age and CT thinking ability as parameters. From the results, this study predicted the effectiveness of puzzle-based computer science education programs in middle and high schools and proposed major improvement areas and directions for puzzle-based computer science education programs that are to be deployed in the future throughout middle and high schools.

Automated K-Means Clustering and R Implementation (자동화 K-평균 군집방법 및 R 구현)

  • Kim, Sung-Soo
    • The Korean Journal of Applied Statistics
    • /
    • v.22 no.4
    • /
    • pp.723-733
    • /
    • 2009
  • The crucial problems of K-means clustering are deciding the number of clusters and initial centroids of clusters. Hence, the steps of K-means clustering are generally consisted of two-stage clustering procedure. The first stage is to run hierarchical clusters to obtain the number of clusters and cluster centroids and second stage is to run nonhierarchical K-means clustering using the results of first stage. Here we provide automated K-means clustering procedure to be useful to obtain initial centroids of clusters which can also be useful for large data sets, and provide software program implemented using R.

Assessing the public preference and acceptance for renewable energy participation initiatives - focusing on photovoltaic power (재생에너지 사업 참여에 대한 국민 선호와 수용성 분석 - 태양광 발전을 중심으로)

  • Ham, AeJung;Kang, SeungJin
    • Journal of Energy Engineering
    • /
    • v.27 no.4
    • /
    • pp.36-49
    • /
    • 2018
  • This study analyzed the public preference and acceptance regarding renewable energy projects through Choice Based Conjoint Analysis. The results show that the surveyed respondents consider the leading authority of the projects, as the most important factor when considering participating in renewable energy initiatives. Following this, the mode of participation and profit distribution and the power plant location are also viewed as important, whereas participation through decision making regarding the projects was less important. Also when participating in renewable energy projects, respondents tend to prefer to financially participating through loans or owning shares rather than volunteering support for the business such as sharing information, stating one's views, or providing cooperation and coordination. Therefore, the focus is on distributional justice, such as financial investment and profit distribution, rather than procedural justice, for instance decision making. When analyzing the part-worths utilities for the participation attribute, the respondents most preferred to receiving dividends based on earnings by owning shares with the local government in charge of the entire projects. As a consequence, the results suggest that it is important to have local government get involved and have trust-worthy governing systems in place for the initiation of the public participating-renewable energy projects.