• The Journal of Society for e-Business Studies
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• v.18 no.3
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• pp.177-193
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• 2013

The study investigated how did Credu pioneer Korean e-Learning market and reinforce their core competencies and how did they promote business diversification analyzing type of learning motives and examining Credu real cases. Under the fierce competition in the current e-Learning market, Credu has maintained their core competencies and strengthened an active communication channels with customers with focusing on investment to core businesses. Credu has introduced more adventurous and challenging products and services with creating a new model for the types of learning motives. This study could introduce the new perspective about the type of learning motives in e-Learning area. Also, the case study of successful e-Learning company, Credu, could contribute to make more spread e-Learning market techniques in this field in practice.

• The KIPS Transactions:PartA
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• v.18A no.4
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• pp.129-134
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• 2011

E-learning in Korea supports different educational needs of diverse learners. E-learning became one of the major source of educational services for schools, higher education, lifelong learning, and for special education. Many e-learning contents offered by cyber universities use HTML, CSS, and Flash, and these are known to have limitations on accessibilities. People with disabilities or aged have problems accessing such contents. The purpose of this study is to evaluate accessibility of Flash e-learning contents offered by 9 cyber universities. AccChecker is used to assess accessibility of the contents. The result shows many errors and warning with Text Equivalents, Keyboard Navigation, Properties, Depth of Tree, and Structures that restrict access. In order to improve the quality and expansion of quality e-learning contents, we need aggressive measures to obtain accessibility of contents, and these should be designed at the planning phase rather than adjusted during the development stage. Furthermore, it is vital to train instructional designers, developers and the CEOs to realize the importance of accessibility and learn appropriate skills to increase accessibilities of e-learning contents.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1005-1012
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• 2021

Recently, the use of various location-based services-based location information systems using maps on the web has been expanding, and there is a need for a monitoring system that can check power demand in real time as an alternative to energy saving. In this study, we developed a deep learning real-time virtual power demand prediction web system using open source-based mapping service to analyze and predict the characteristics of power demand data using deep learning. In particular, the proposed system uses the LSTM(Long Short-Term Memory) deep learning model to enable power demand and predictive analysis locally, and provides visualization of analyzed information. Future proposed systems will not only be utilized to identify and analyze the supply and demand and forecast status of energy by region, but also apply to other industrial energies.

• Journal of Internet Computing and Services
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• v.24 no.2
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• pp.47-56
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• 2023

Hydrogen energy is an eco-friendly energy that produces heat and electricity with high energy efficiency and does not emit harmful substances such as greenhouse gases and fine dust. In particular, smart hydrogen energy is an economical, sustainable, and safe future smart hydrogen energy service, which means a service that stably operates based on 'data' by digitally integrating hydrogen energy infrastructure. In this paper, in order to implement a data-based hydrogen charging station demand forecasting model, three hydrogen charging stations (Chuncheon, Sokcho, Pyeongchang) installed in Gangwon-do were selected, supply and demand data of hydrogen charging stations were secured, and 7 machine learning and deep learning algorithms were used. was selected to learn a model with a total of 27 types of input data (weather data + demand for hydrogen charging stations), and the model was evaluated with root mean square error (RMSE). Through this, this paper proposes a machine learning-based hydrogen charging station energy demand prediction model for optimal hydrogen energy supply and demand.

• Digital Contents
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• no.9 s.148
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• pp.60-63
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• 2005

LCMS의 정의가 바뀌고 있다. 그동안 LCMS는 LMS와 개념 구분조차 이뤄지지 못했던 것에서 벗어나 e러닝 기술의 전반적인 변화와 발전을 수용하는 방향으로 진화하고 있다. 이에 따라 향후 LCMS는 사용자간 데이터와 콘텐츠를 주고받을 수 있는 지능형 서비스를 수행하는 동시에 웹서비스 등 개방형 환경과 연계된 시스템으로 발전될 전망이다.

• The Korean Journal of Franchise Management
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• v.5 no.1
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• pp.49-64
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• 2014

The purpose of this work is to analyze successful business strategy of Daekyo Noonnoppi. Daekyo Noonnoppi, a franchise company of educational service, activated education business by establishing new way of providing education opportunity: self-directed learning center. They introduced not only the concept of learning center but also sustainable business strategies, which leads to remarkable success in the education business field. Daekyo Noonnoppi deployed three managerial concepts for study achievement: goal management, study management, and environment management. This Franchise company has three advantages of its success: Goal, Study and environment management: First, the goal management helps students to develop self-directed attitudes by making(appropriate) atmosphere which is able to build study goal and plan. In addition, this company provides information to their students to searches ways of study through the test reflecting their tendency. Furthermore, this company offers a variety of events for motivating study. Second, study management is helpful for students to develop holistic fundamental knowledge through its textbooks of this company and provides solutions and time management for study through 1 on 1 study advice. Third, environment management is used to making atmosphere to develop self-directed learning way for its students and provides spaces for students equipped with multimedia systems and cyber learning infrastructures.

• Smart Media Journal
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• v.11 no.5
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• pp.48-55
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• 2022

Tomato crops are easy to expose to disease and spread in a short period of time, so late measures against disease are directly related to production and sales, which can cause damage. Therefore, there is a need for a service that enables early prevention by simply and accurately diagnosing tomato diseases in the field. In this paper, we construct a system that applies a deep learning-based model in which ImageNet transition is learned in advance to classify and serve nine classes of tomatoes for disease and normal cases. We use the input of MobileNet, ResNet, with a deep learning-based CNN structure that builds a lighter neural network using a composite product for the image set of leaves classifying tomato disease and normal from the Plant Village dataset. Through the learning of two proposed models, it is possible to provide fast and convenient services using MobileNet with high accuracy and learning speed.

• Journal of Digital Contents Society
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• v.9 no.1
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• pp.41-51
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• 2008

In a circumstance that the development of mobile media through the on-line consumer desire in the era of Web 2.0 has promoted extension of personal mobile media on the part of consumers, this study examined consumer trends depending on use of e-learning contents through mobile media. In connection with tendencies through mobile prosumers' consumption patterns and use of mobile educational contents, I analyzed user demands based on characteristics of personal media centering around a communities of e-learning portals. Direction of e-learning technological development calls on mobile communication companies to open their networks and share platform following digital convergence. E-learning contents should be produced in a custom-made way for the personal media. This study is aimed at contributing for advancement of e-learning contents consumers' user convenience implicating examination into consumer demands which are necessary to invigorate e-learning contents.

• Journal of Broadcast Engineering
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• v.21 no.5
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• pp.739-748
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• 2016

This study quantitatively measured the impact of blended learning with smart devices for learning satisfaction. It is targeted in specialized domestic company with IT Service which build smart learning systems and utilize for employee training. Specifically, it empirically analyzed that learning attitude(Self-efficacy, Self-innovativeness, Perceived usefulness, Perceived ease of use) with smart devices affect acceptance of smart learning and offline face-to-face learning satisfaction. As a result, the learning attitude of the smart learning gave a positive effect on the acceptance of the smart learning and then acceptance of the smart learning gave a positive effect on offline face-to-face learning satisfaction. Additionally learning the attitude of the smart learning even gave a positive impact, as well as the acceptance of smart learning experience in offline training. It imply that this variables of smart-learning attitude affect the self-directed learning and positive learning experience.

• Journal of Digital Convergence
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• v.15 no.12
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• pp.35-45
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• 2017

This study aims to explore the effect of quality factors and learning styles on users' satisfaction in e-Learning context. For this purpose, statistical methods such as reliability test, factor analysis, ANOVA, regression analysis were carried out using the survey data from university students. The quality factors of e-Learning were classified into contents, system, service, and interpersonal activities while learning styles were classified into positive-cooperative, self-directed, environmental-dependent, and passive styles. The results showed that each quality factors of e-Learning has a strong positive effect on user satisfaction, and self-directed group has higher satisfaction than other groups. Learning styles have moderating effects on the quality-satisfaction relationship, and especially, the group of passive learning style has a strong moderating effect on the interpersonal activities. Theoretical and practical implications and future research directions are drawn from these findings.