• Journal of Engineering Education Research
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• v.27 no.2
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• pp.25-34
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• 2024

Due to the Covid-19 pandemic, it seems to have been impossible to run offline training courses. To overcome this situation, online training courses has been emerged. Just moving the educational environment from offline to online instead of re-designing the curriculum, however, is not effective for trainees. To maximize educational effectiveness, it is necessary to re-design the curriculum based on constructivist appoach which gives trainees experience on skills and knowledge about their job. As for re-designing the curriculum into real-time online practical learning based on constructivism, learning satisfaction and work efficacy of trainees may have been increased. From these results, HRD professionals in an IT company should need to consider how to structure the curriculum when they design the real-time online practical learnings.

• Journal of Broadcast Engineering
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• v.23 no.2
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• pp.186-196
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• 2018

In this paper, we propose an on-line tracking method using convolutional neural network (CNN) for tracking object. It is well known that a large number of training samples are needed to train the model offline. To solve this problem, we use an untrained model and update the model by collecting training samples online directly from the test sequences. While conventional methods have been used to learn models by training samples offline, we demonstrate that a small group of samples are sufficient for online object tracking. In addition, we define a loss function containing color information, and prevent the model from being trained by wrong training samples. Experiments validate that tracking performance is equivalent to four comparative methods or outperforms them.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.633-650
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• 2013

All the imputation techniques proposed so far in literature for data imputation are offline techniques as they require a number of iterations to learn the characteristics of data during training and they also consume a lot of computational time. Hence, these techniques are not suitable for applications that require the imputation to be performed on demand and near real-time. The paper proposes a computational intelligence based architecture for online data imputation and extended versions of an existing offline data imputation method as well. The proposed online imputation technique has 2 stages. In stage 1, Evolving Clustering Method (ECM) is used to replace the missing values with cluster centers, as part of the local learning strategy. Stage 2 refines the resultant approximate values using a General Regression Neural Network (GRNN) as part of the global approximation strategy. We also propose extended versions of an existing offline imputation technique. The offline imputation techniques employ K-Means or K-Medoids and Multi Layer Perceptron (MLP)or GRNN in Stage-1and Stage-2respectively. Several experiments were conducted on 8benchmark datasets and 4 bank related datasets to assess the effectiveness of the proposed online and offline imputation techniques. In terms of Mean Absolute Percentage Error (MAPE), the results indicate that the difference between the proposed best offline imputation method viz., K-Medoids+GRNN and the proposed online imputation method viz., ECM+GRNN is statistically insignificant at a 1% level of significance. Consequently, the proposed online technique, being less expensive and faster, can be employed for imputation instead of the existing and proposed offline imputation techniques. This is the significant outcome of the study. Furthermore, GRNN in stage-2 uniformly reduced MAPE values in both offline and online imputation methods on all datasets.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.183-192
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• 2023

This study analyzes the performance of flipped learning, an offline class method conducted in a degree-linked work-learning parallel system. Training in the work-study parallel system, which is conducted as part of job competency improvement, has thoroughly adhered to the offline method, but in line with COVID-19, unlike before, it is changing in the direction of using the online method more actively. However, educational methods such as flipped learning are not new because the degree-linked operation is applied to the academic system and education method of universities and is practically the same form as general university education. Therefore, it is necessary to analyze the educational performance and complementary points of flipped learning, which has recently been expanded in the degree-linked work-study parallel system, considering the characteristics of this system, in which classes are held only on weekends. As a result of statistical analysis based on the survey, some of the outcomes of flipped learning have been confirmed, and in order to increase the performances, it is necessary to continuously seek out specific measures to encourage learning and expand communication between instructors and students.

• International Commerce and Information Review
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• v.8 no.2
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• pp.101-117
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• 2006

"Online Alternative Dispute Resolution" can refer to the use of online methods of dispute resolution to resolve disputes arising either online or offline. The range of disputes covered by online ADR has been broad : from family law to internet domain name disputes : from small transaction to insurance disputes. Online and offline consumer disputes have been a major focus of online ADR sites. This article propsed that the mediator should explain the process and the mediator's role so as to forestall misunderstanding on that score. And mediators should consider including in either usual mediation agreements additional provisions applicable to communications by email. Online ADR sites should be designed 1) to provide a simple, easily understandable process, 2) to provide detailed information on process, cost and speed, 3) to enable users to move between online and offline processes, 4) to have authentication processes for parties and documents, 5) to have automatic translation system for language barriers. And Government should play an important role in assisting people to adapt technically and emotionally to new technology through information, training and ongoing support. The days of live online television-quality videoconferencing have not yet arrived. Until then, we must hone our skills with the written word.

• Journal of The Korean Association For Science Education
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• v.36 no.3
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• pp.399-411
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• 2016

The purpose of this study is to investigate implications for future STEAM education by analyzing the surveys by the in-service teachers who participated in the Advanced STEAM Teacher Training Program(ASTTP) for raising interests and understanding of science and technology and nurturing STEAM literacy and problem-solving ability of students. ASTTP was developed for promoting 'teacher competence for STEAM.' ASTTP is a 60-hour program(4 credits), which includes offline intensive course of 38 hours, online training course of 12 hours, a course of implementation at schools for 5 hours, and a workshop for 5 hours (based on the 2014 program). For the offline intensive course, teachers take various professional development classes and activities, such as open-laboratory tours, advanced experiments, mentoring programs, and team projects as well as lectures on diverse disciplines. For the online course, teachers take online classes freely while they are encouraged to work with other teachers in groups. After taking both online and offline courses, the teachers are required to implement their STEAM lesson plans in their classrooms. Finally at the workshop, some selected teachers share how successfully they have implemented STEAM education. About 700 teachers have successfully taken the program from 2012 to 2014. Based on the surveys by the teachers, the program has been modified and improved. Our analysis shows increased professional development in STEAM education for the participating teachers. This study can provide some implication and helpful insights for people who need to develop and manage teacher training programs for STEAM education and other education programs in general.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3286-3300
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• 2016

High Efficiency Video Coding (HEVC) Standard, as the latest coding standard, introduces satisfying compression structures with respect to its predecessor Advanced Video Coding (H.264/AVC). The new coding standard can offer improved encoding performance compared with H.264/AVC. However, it also leads to enormous computational complexity that makes it considerably difficult to be implemented in real time application. In this paper, based on machine learning, a fast partitioning method is proposed, which can search for the best splitting structures for Intra-Prediction. In view of the video texture characteristics, we choose the entropy of Gray-Scale Difference Statistics (GDS) and the minimum of Sum of Absolute Transformed Difference (SATD) as two important features, which can make a balance between the computation complexity and classification performance. According to the selected features, adaptive decision trees can be built for the Coding Units (CU) with different size by offline training. Furthermore, by this way, the partition of CUs can be resolved as a binary classification problem. Experimental results have shown that the proposed algorithm can save over 34% encoding time on average, with a negligible Bjontegaard Delta (BD)-rate increase.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.271-275
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• 2022

This study analyzed the characteristics that affect the direction change of public fitness in the current COVID-19 situation. As a result of the study, if public and active fitness-related awareness is strengthened and fitness places require a transition from outdoor fitness to home training, fitness activities require a transition from offline fitness to offline + online sports fitness, and finally, in the case of fitness equipment, there is an increase in demand for home training. Based on these characteristics, this study is expected to help the entire nation achieve athletic life and a healthy society by presenting its course of action on the change of direction of popular movement.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.43-50
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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 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.