• Title/Summary/Keyword: Global e-learning

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Designing a Adaptive Advisement Learning of the LMS applying the SCORM2004 S&N and the Traffic-Signal-Lamp Metaphor (SCORM2004 S&N과 교통 신호 메타포를 적용한 LMS에서의 적응적 조언 학습 설계)

  • Bang Chan-ho;Kim Ki-Seok
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.07a
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    • pp.76-78
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    • 2005
  • e-Learning분야에서 표준안으로 인정받고 있는 ADL의 SCORM에서 발표한 SCORM2004 Sequencing&Navigation은 동일한 학습객체를 사용하여 학습객체간의 다양한 상호관계를 설계, 적용할 수 있게 하였다. 그리고, 학습자와 학습객체와의 개별 상호작용을 추적, 평가하여 학습흐름을 안내함으로써 개별 적응적 조언 학습의 가능성을 보여주었다. 본 논문에서는 SCORM1.2기반의 LMS에 SCORM2004 S&N과 적응적 탐색을 지원하는 교통신호메타포를 구현하고 실제적으로 적용하고자 한다. 이로써, 학습설계에 따라 정해진 학습객체 상호간의 S&N규칙이 개별 학습자의 학습상태와 평가에 의해 다른 순서로 전달하거나 생략되어지고, 학습상태를 시각적으로 제공함으로써 적응적 조언 학습 설계에 대한 가능성을 실현할 수 있었다.

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A Block-based Computer Graphics Educational Software Model using WebGL (WebGL을 이용한 블록 기반 컴퓨터 그래픽스 교육용 소프트웨어 모델)

  • Pyun, Hae-Gul;Park, Jinho
    • Journal of Korea Game Society
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    • v.15 no.3
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    • pp.189-200
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    • 2015
  • These days computer graphics technology has been applied in diverse IT fields. Needs for computer graphics such as 3D Printer, Head Mount Display, VR & AR are growing rapidly. Computer graphics will be more specialized and demanding for graphics specialists will be also increased. However, serious mathematical background obstructs people to learning computer graphics. An efficient computer graphics learning system would be helpful for graphics experts training. By analyzing the graphics theory, we propose an educational software system with that students can effectively learn computer graphics. Our system focuses on theoretical objects of computer graphics and enhances accessibility and intuition using web and blocks.

A Corpus-based Analysis of EFL Learners' Use of Discourse Markers in Cross-cultural Communication

  • Min, Sujung
    • English Language & Literature Teaching
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    • v.17 no.3
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    • pp.177-194
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    • 2011
  • This study examines the use of discourse markers in cross-cultural communication between EFL learners in an e-learning environment. The study analyzes the use of discourse markers in a corpus of an interactive web with a bulletin board system through which college students of English at Japanese and Korean universities interacted with each other discussing the topics of local and global issues. It compares the use of discourse markers in the learners' corpus to that of a native English speakers' corpus. The results indicate that discourse markers are useful interactional devices to structure and organize discourse. EFL learners are found to display more frequent use of referentially and cognitively functional discourse markers and a relatively rare use of other markers. Native speakers are found to use a wider variety of discourse markers for different functions. Suggestions are made for using computer corpora in understanding EFL learners' language difficulties and helping them become more interactionally competent speakers.

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A Study of the Application of Machine Learning Methods in the Low-GloSea6 Weather Prediction Solution (Low-GloSea6 기상 예측 소프트웨어의 머신러닝 기법 적용 연구)

  • Hye-Sung Park;Ye-Rin, Cho;Dae-Yeong Shin;Eun-Ok Yun;Sung-Wook Chung
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.16 no.5
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    • pp.307-314
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    • 2023
  • As supercomputing and hardware technology advances, climate prediction models are improving. The Korean Meteorological Administration adopted GloSea5 from the UK Met Office and now operates an updated GloSea6 tailored to Korean weather. Universities and research institutions use Low-GloSea6 on smaller servers, improving accessibility and research efficiency. In this paper, profiling Low-GloSea6 on smaller servers identified the tri_sor_dp_dp subroutine in the tri_sor.F90 atmospheric model as a CPU-intensive hotspot. Applying linear regression, a type of machine learning, to this function showed promise. After removing outliers, the linear regression model achieved an RMSE of 2.7665e-08 and an MAE of 1.4958e-08, outperforming Lasso and ElasticNet regression methods. This suggests the potential for machine learning in optimizing identified hotspots during Low-GloSea6 execution.

Policy Advice on the E-Government ODA Strategy : Focus on E-Gov ODA in the Developing Countries (전자정부 해외진출 활성화를 위한 정책방안 : 개발도상국 ODA 지원 전략을 중심으로)

  • Chung, Choong Sik
    • Journal of Information Technology Services
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    • v.12 no.3
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    • pp.231-252
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    • 2013
  • The Republic of Korea has made major strides in Information and Communication Technology (ICT) over the last five decades. After going through continuous efforts in e-Government and national informatization, Korea has become one of the global E-government leaders. Korea's E-government Development Index ranking assessed by the United Nations improved from 15th in 2001 to the top in 2010 and 2012 out of 192 countries worldwide, and its E-participation Index ranking was also ranked 1st in 2010& 2012. In addition, many of Korea's E-government practices until now have been introduced to the world as the best cases and received worldwide acknowledgement. The importance of official development aid/assistance (ODA) through informatization is especially gaining attention as Korea has joined the OECD Development Assistance Committee (DAC) and its status has significantly improved within international organizations. The Korean government has selected countries that have high potential in trade, economic, and E-government cooperation or those that are selected as ODA priority countries by the international community and has carried out various activities including ICT consultation, ICT Cooperation Center operation, and ICT learning programs. With joining the OECD DAC, Korea's overseas aid projects are expected to increase and be carried out in a more systematic manner. Also in the area of informatization, the importance of not only the overseas aid 'in ICT' itself but also the overseas aid 'through ICT' is increasing along with the expanding scale for more efficient and influential support. The Korean government's comprehensive reach of international projects in the ICT arena, aims to foster the global partnership for development by sharing and expanding the benefits of ICTs. The Korean government recognizes its advances and has endeavored to share them with others through participation in international forums and hosting of workshops.

A Proposal of Descent Multi-point Search Method and Its Learning Algorithm for Optimum Value (최적치 계산을 위한 점감다점탐색법과 그 학습 알고리즘의 제안)

  • 김주홍;공휘식;이광직
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.17 no.8
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    • pp.846-855
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    • 1992
  • In this paper, the decrease multipoint search method and Its learning algorithm for optimum value computatlon method of object function Is proposed. Using this method, the number of evaluation point according to searching time can t)e reduced multipoint of the direct search method by applying the unlivarlate method. And the learning algorithm can reprat the same search method in a new established boundary by using the searched result. In order to Investigate the efficience of algorithm, this method this method is applied to Rosenbrock and Powell, Colvelle function that are Impossible or uncertain in traditional direct search method. And the result of application, the optimum value searching oil every function Is successful. Especially, the algorithm is certified as a good calculation method for producing global(absolute) optimum value.

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An Empirical Study on User Acceptance of Micro e-Payment Systems : System Features, Transaction Cost, and Provider (소액 전자결제시스템 수용의지에 관한 실증연구 : 시스템 특성, 거래비용과 제공업체를 중심으로)

  • Chung, Suk-Kyun;Ryoo, Chang-Wan;Ku, Tae-Yong
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.33 no.4
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    • pp.130-137
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    • 2010
  • This paper analyzes the main factors affecting user selection of a small-sum electronic payment system using survey data of 396 users. Several findings emerge. First, users consider three pillars and eight factors in adopting a new system : system features(stability, security, and flexibility), transaction cost(payment commission and settlement period), and financial capability of provider(stability of financial structure, risk management capability, and funding capability). Second, the stability of the financial structure of the system provider is the most important factor to user acceptance of a new e-payment system. Users tend to consider uncertainty risk more seriously than transaction cost. This reflects the reality that electronic payment system service industry has not fully fledged yet. Third, some moderating effects exist according to payment methods and business usages. As for payment methods, speedy settlement cycle for wired/wireless phone payment, system stability for credit card and account transfer payment, and security for advance payment means are crucial factors. As for business usages, the stability of financial structure for online game content, system stability for music and video content, proxy payment commission for e-learning content, flexibility of the payment system for digital adult content, and security for public services are decisive ones.

Development of Security Anomaly Detection Algorithms using Machine Learning (기계 학습을 활용한 보안 이상징후 식별 알고리즘 개발)

  • Hwangbo, Hyunwoo;Kim, Jae Kyung
    • The Journal of Society for e-Business Studies
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    • v.27 no.1
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    • pp.1-13
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    • 2022
  • With the development of network technologies, the security to protect organizational resources from internal and external intrusions and threats becomes more important. Therefore in recent years, the anomaly detection algorithm that detects and prevents security threats with respect to various security log events has been actively studied. Security anomaly detection algorithms that have been developed based on rule-based or statistical learning in the past are gradually evolving into modeling based on machine learning and deep learning. In this study, we propose a deep-autoencoder model that transforms LSTM-autoencoder as an optimal algorithm to detect insider threats in advance using various machine learning analysis methodologies. This study has academic significance in that it improved the possibility of adaptive security through the development of an anomaly detection algorithm based on unsupervised learning, and reduced the false positive rate compared to the existing algorithm through supervised true positive labeling.

A Study on the Ubiquitous for Building Life-long Educational System (평생교육체제를 구축하기 위한 유비쿼터스에 관한 연구)

  • Shin, Jae-Heub
    • The Journal of Sustainable Design and Educational Environment Research
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    • v.4 no.4
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    • pp.39-54
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    • 2004
  • In this study, the following findings were obtained: First, life-long educational system should be reinforced that can train and educate people to fit their situation and provide the necessary manpower in a just-in-time manner by getting away from the school-centered education and rapidly introducing the knowledge required in both the world market and the domestic market. This can be said to be the global trend in the ubiquitous age. Second, government should make efforts to build up the life-long educational system that can make the persons trained and educated in schools the manpower required by the state and society. Third, Life-long learning policy starts with providing for the system of lifting all kinds of limits and obstacles so that anyone needing learning can learn and his learning may not discriminated from schooling. For this policy or system to be effectively promoted, government should reinforce administrative and financial support system for investment in and research on the ubiquitous department. Fourth, It is quiet right that the very effort we are going give the super to the ubiquitous education is a shortcut to solving rapidly lots of problems heaped on our present life-long educational system.

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Win-Loss Prediction Using AOS Game User Data

  • Ye-Ji Kim;Jung-Hye Min
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.12
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    • pp.23-32
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    • 2023
  • E-sports, a burgeoning facet of modern sports culture, has achieved global prominence. Particularly, Aeon of Strife (AOS) games, emblematic of E-sports, blend individual player prowess with team dynamics to significantly influence outcomes. This study aggregates and analyzes real user gameplay data using statistical techniques. Furthermore, it develops and tests win-loss prediction models through machine learning, leveraging a substantial dataset of 1,149,950 individual data points and 230,234 team data points. These models, employing five machine learning algorithms, demonstrate an average accuracy of 80% for individual and 95% for team predictions. The findings not only provide insights beneficial to game developers for enhancing game operations but also offer strategic guidance to general users. Notably, the team-based model outperformed the individual-based model, suggesting its superior predictive capability.