• The Journal of Society for e-Business Studies
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• v.12 no.4
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• pp.185-209
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• 2007

The development of information technologies has contributed on-line training as one of important education methods. On-line training in firms, which is similar to e-learning or virtual education, provides trainees with more education opportunities in diverse ways. It has developed a range of innovative services with a one-stop solution of education within the electronic sector. Also under the on-line training environment, trainees can undertake customized training packages at anytime and any places. Moreover, information technology allows both the trainers and other trainees to be decoupled in any of the elements of tune, place, and space. Two research questions are investigated : what are the determinants affecting the on-line training effectiveness and how those variables affect the two aspects of training effectiveness: learning performance and transfer performance. Based on the previous literature conducted on the traditional training environment, the determinants of training effectiveness are derived. Eight hypotheses are developed based on literature reviews and tested by questionnaires survey data. The collected data have been analyzed by LISREL. It is found that the relationship between individual, organizational and on-line site design variables and training effectiveness (learning and transfer) are significant. The contribution and limitations of this research are also discussed with future studies.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.33-38
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• 2021

Recently, transfer learning techniques with a base convolutional neural network (CNN) model have widely gained acceptance in early detection and classification of crop diseases to increase agricultural productivity with reducing disease spread. The transfer learning techniques based classifiers generally achieve over 90% of classification accuracy for crop diseases using dataset of crop leaf images (e.g., PlantVillage dataset), but they have ability to classify only the pre-trained diseases. This paper provides with an evaluation scheme on selecting an effective base CNN model for crop disease transfer learning with regard to the accuracy of trained target crops as well as of untrained target crops. First, we present transfer learning models called CDC (crop disease classification) architecture including widely used base (pre-trained) CNN models. We evaluate each performance of seven base CNN models for four untrained crops. The results of performance evaluation show that the DenseNet201 is one of the best base CNN models.

• The Journal of Korean Association of Computer Education
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• v.15 no.6
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• pp.53-64
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• 2012

This study was to compare and analyze actual conditions and awareness of high school students' mobile learning. Survey was used as a research method and percentile, t-test and F-test were conducted for the statistical analyses. Results revealed that in the case of actual conditions on mobile device and mobile learning, slight differences were shown in various sub-variables, depending on independent variables (gender, grade, track); year 2010 can be the most important year for the mobile learning; high school students seldom utilize mobile learning in a small piece of time; mobile learning using Apps was not widespread yet. In the case of awareness of mobile learning, statistically significant differences were found in the use capacity of mobile devices, the increase of learning performance, and the continual interests of mobile devices.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.2031-2039
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• 2010

This article first defines the concept of ubiquitous learning, and then examine ways to design the educational environment for e-Learning and u-Learning. Next, identifies some disadvantages before seeking possible solutions. Finally, the article explores visions of how ubiquitous learning might look in the future. With the advent of information, communication and computer technologies, the needs and demands for ubiquitous learning are largely emerging, enabling students to easily access everything they want anytime, anywhere. In particular, the advance of high-speed broadband networks such as DMB, WiBro and WCDMA and the proliferation of portable digital devices including DMB, PDA and high-performance mobile phones will encourage the widespread adoption of u-Learning.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.11
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• pp.1107-1111
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• 2004

As an information technology is developed, more intelligent system considering emotional factor for implementing the personality is required. In this paper, Reactive Learning Inference System considering emotional factor is proposed. Emotional Facter(E) is defined for a criterion for representing the personal preference. This system is designed to have functions of Reactive filtering by Emotional factor, Incremental learning, perception & inference and knowledge retrieval. This system is applied to the area for analysis of customer's tastes and its performance is analyzed and compared.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.372-381
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• 2009

Recently, the number of children of multi-cultural family is increasing and the achievement gap between city and farming village is getting larger. It will be alternatives to develop e-learning contents which students can study by themselves where there are internet connected computers. As one of the solutions to improve students' writing ability, we developed animation e-learning contents about manuscript paper usage and sentence signs. As a result of applying e-learning contents to students, we can make sure that e-learning contents are more effective than existing means such as workbook-centered education and web contents persuaded by text in academic interesting, satisfaction and achievement. Consequently, we offer this training methods as alternatives which can increase academic performance for multi-cultural family and Korean students who are behind the other students in language ability.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.235-242
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• 2013

Reputation systems aggregate users' feedback after the completion of a transaction and compute the "reputation" of products, services, or providers, which can assist other users in decision-making in the future. With the rapid growth of online e-Learning content providing services, a suitable reputation system for more credible e-Learning content delivery has become important and is essential if educational content providers are to remain competitive. Most existing reputation systems focus on generating ratings only for user reputation; they fail to consider the reputations of products or services(item reputation). However, it is essential for B2C e-Learning services to have a reliable reputation rating mechanism for items since they offer guidance for decision-making by presenting the ranks or ratings of e-Learning content items. To overcome this problem, we propose a novel collaborative filtering based reputation rating method. Collaborative filtering, one of the most successful recommendation methods, can be used to improve a reputation system. In this method, dual information sources are formed with groups of co-oriented users and expert users and to adapt it to the reputation rating mechanism. We have evaluated its performance experimentally by comparing various reputation systems.

• The Journal of the Korea Contents Association
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• v.7 no.7
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• pp.104-113
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• 2007

The purpose of this study is to develop contents and management strategies of Social Welfare Education e-Learning. For this study, Data were collected from students who were attended to Introduction to Social Welfare e-Learning in K center between first semester, 2006 and first semester, 2007 as well as professors and system operator. It is important meaning to performance as the first empirical study which is on the e-Learning of social welfare studies. As a results, it has been proved that systematic preparation process, study contents which is centered field, active interaction among students, study management in time efficiency, technological supports for system improvement are significant factors on construction and development of Social Welfare e-Learning.

• The Korean Journal of Applied Statistics
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• v.37 no.3
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• pp.355-380
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• 2024

In this paper, we compare the performance of graph-based deep learning models using OECD test guideline (TG) data. OECD TG are a unique tool for assessing the potential effects of chemicals on health and environment. but many guidelines include animal testing. Animal testing is time-consuming and expensive, and has ethical issues, so methods to find or minimize alternatives are being studied. Deep learning is used in various fields using chemicals including toxicity prediciton, and research on graph-based models is particularly active. Our goal is to compare the performance of graph-based deep learning models on OECD TG data to find the best performance model on there. We collected the results of OECD TG from the website eChemportal.org operated by the OECD, and chemicals that were impossible or inappropriate to learn were removed through pre-processing. The toxicity prediction performance of five graph-based models was compared using the collected OECD TG data and MoleculeNet data, a benchmark dataset for predicting chemical properties.

• Industry Promotion Research
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• v.4 no.1
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• pp.57-66
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• 2019

The extant research literature is scant in telling us how organizations actually implement lifelong learning practices and policies. Hence, the purpose of this paper is to describe how lifelong learning is grounded in practice. We do this by introducing a new conceptual framework that was developed on the basis of interviews with a number of leading edge corporations from Canada, the USA, India and Korea. At the heart of our model, and any effective lifelong learning system, is a performance management system. The performance management system allows for an ongoing interaction between managers and employees whereby challenging performance and learning goals are set, and concrete plans are made to achieve them. Those plans involve three types of learning activities. First, employees may be encouraged to engage in formal learning. This could be provided in-house, or the employee may take a leave of absence and return to school. Second, managers may deploy their subordinates to different departments or teams, so that they can take part in new work-based learning opportunities. Finally, employees may be encouraged to learn on their own time. By this we mean learning after organizational hours through firm-sponsored 5 programs, such as e-learning courses. Fueled by the performance management system, we posit that these three learning outlets lead to effective lifelong learning in organizations.