• Journal of Digital Convergence
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• v.11 no.5
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• pp.83-94
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• 2013

The e-Learning is one of best ways to generate the substitution effect for classroom learning, and robust and rational distribution structure for e-Learning industry is the key issue for successful educational performance of e-Learning, however the recent e-Learning market has a distribution status quite different from rational structure. This paper focuses on issues of e-Learning distribution status and alternatives for policy making. In order to make this study successful, we discuss about concepts and scopes of e-Learning distribution and various types of distribution structure by business models. We conducted an interview survey for business individual experts for distribution modelling. Based on the result of the survey, this paper describes issues of distribution structure and suggests alternatives for policy making in the Korea e-Learning market.

• Journal of Distribution Science
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• v.21 no.4
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• pp.57-67
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• 2023

Purpose: This study aims to measuring the employee performance distributions of company in using relationship analysis between motivation, organization learning, compensation, and Organizational commitment. Research design and methodology: The study was conducted on 102 employees as a sample. Data were analyzed using Path Analysis in Structural Equation Modeling (SEM) with PLS. Results: the research result has shown that motivation and compensation have a positive significant effect on organizational commitment. While organizational learning has negative and insignificant effect on organizational commitment. Furthermore, motivation, organizational learning and motivation have no significant effect on employee performance distribution and organizational commitment has a positive significant effect on employee performance distribution. Results for mediating effect has obtained where organizational commitment mediates the effect of motivation and compensation on employee performance distribution, but cannot mediate the effect of organizational learning on employee performance distribution. Conclusion: Organizational commitment in this study can make employees feel comfortable and attached to the company so that employees can perform well to achieve company goals. Motivation and compensation are driving factors in improving employee performance distribution and will achieved if employees have good organizational commitment. In this study, organizational learning is not an important factor in improving employee performance distribution.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.441-452
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• 2021

Federated learning provides an efficient integrated model for distributed data, allowing the local training of different data. Meanwhile, the goal of multi-task learning is to simultaneously establish models for multiple related tasks, and to obtain the underlying main structure. However, traditional federated multi-task learning models not only have strict requirements for the data distribution, but also demand large amounts of calculation and have slow convergence, which hindered their promotion in many fields. In our work, we apply the rank constraint on weight vectors of the multi-task learning model to adaptively adjust the task's similarity learning, according to the distribution of federal node data. The proposed model has a general framework for solving optimal solutions, which can be used to deal with various data types. Experiments show that our model has achieved the best results in different dataset. Notably, our model can still obtain stable results in datasets with large distribution differences. In addition, compared with traditional federated multi-task learning models, our algorithm is able to converge on a local optimal solution within limited training iterations.

• Journal of Distribution Science
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• v.21 no.2
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• pp.91-102
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• 2023

Purpose: to explore more deeply the variables of knowledge construction in influencing performance, through entrepreneurial leadership, motivation, organizational learning, and commitment to the performance of midwives in providing maximum service to patients and the community. Research design, data and methodology: using quantitative methods with hypothesis testing, data was obtained through direct visits and surveys to midwife practice locations through coordination with the Indonesian Midwives Association (IBI) regarding surveys to be carried out and needed. Results: there are 3 direct paths that have significant value. The path between the motivation variable to commitment was found to be significant, then the effect of organizational learning on commitment was found to be significant and finally the effect of the path variable from commitment to distribution performance was found to be significant. The indirect effect was found to be insignificant for the influence of entrepreneurial leadership through commitment to distribution performance, but different results found a significant indirect effect for the relationship between motivation through commitment to performance and organizational learning through commitment to distribution performance. Conclusion: there is a high commitment to the work of midwives, commitment as a good mediation in influencing distribution performance between organizational learning and work motivation.

• Journal of Distribution Science
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• v.21 no.4
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• pp.47-56
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• 2023

Purpose: the research aims to analyze the impact of the distribution of knowledge through online learning on the intellectual potential of PhD students and produce recommendations for policy to improve intellectual capacity. During the literature review, it was determined that a large number of studies examined the impact of online learning on the quality of education at different levels. Research design, data and methodology: the research methodology is based on subjective assessment and studying the students' opinions. The basis of the study was a comprehensive analysis of primary data obtained through a sociological survey of PhD students. 324 respondents from humanitarian, medical and natural faculties participated in the survey. Results: the study revealed that online learning helps increase students' intellectual potential. PhD students had a positive attitude towards the transition from traditional education to online learning. It should be noted that, according to the results, the most popular gadgets were laptops and smartphones, which were characterized by high mobility and ease of use. Based on the obtained results, recommendations were developed for the formation of online learning with a focus on increasing students' intellectual potential. Conclusions: based on the results of the assessment of educational and innovative potential, policy recommendations and further research in this area were proposed.

• Journal of Distribution Science
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• v.20 no.11
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• pp.121-129
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• 2022

Purpose: Artificial intelligence is widely used, particularly in the popular neural network theory called Deep learning. The improvement of computing speed and capability expedited the progress of Deep learning applications. The application of Deep learning in education has various effects and possibilities in creating and managing educational content and services that can replace human cognitive activity. Among Deep learning, Deep fake technology is used to combine and synchronize human faces with voices. This paper will show how to develop e-Learning content videos using those technologies and open-source tools. Research design, data, and methodology: This paper proposes 4 step development process, which is presented step by step on the Google Collab environment with source codes. This technology can produce various video styles. The advantage of this technology is that the characters of the video can be extended to any historical figures, celebrities, or even movie heroes producing immersive videos. Results: Prototypes for each case are also designed, developed, presented, and shared on YouTube for each specific case development. Conclusions: The method and process of creating e-learning video contents from the image, video, and audio files using Deep fake open-source technology was successfully implemented.

• The Journal of Information Systems
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• v.29 no.2
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• pp.131-147
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• 2020

Purpose The purpose of this study is to develop intelligent vehicle parking distribution system based on LoRa network at the circumstance of traffic congestion during cultural festival in a local city. This paper proposes a parking dispatch and distribution system using a Q-learning algorithm to rapidly disperse traffics that increases suddenly because of in-bound traffics from the outside of a city in the real-time base as well as to increase parking probability in a parking lot which is widely located in a city. Design/methodology/approach The system get information on realtime-base from the sensor network of IoT (LoRa network). It will contribute to solve the sudden increase in traffic and parking bottlenecks during local cultural festival. We applied the simulation system with Queuing model to the Yudeung Festival in Jinju, Korea. We proposed a Q-learning algorithm that could change the learning policy by setting the acceptability value of each parking lot as a threshold from the Jinju highway IC (Interchange) to the 7 parking lots. LoRa Network platform supports to browse parking resource information to each vehicle in realtime. The system updates Q-table periodically using Q-learning algorithm as soon as get information from parking lots. The Queuing Theory with Poisson arrival distribution is used to get probability distribution function. The Dijkstra algorithm is used to find the shortest distance. Findings This paper suggest a simulation test to verify the efficiency of Q-learning algorithm at the circumstance of high traffic jam in a city during local festival. As a result of the simulation, the proposed algorithm performed well even when each parking lot was somewhat saturated. When an intelligent learning system such as an O-learning algorithm is applied, it is possible to more effectively distribute the vehicle to a lot with a high parking probability when the vehicle inflow from the outside rapidly increases at a specific time, such as a local city cultural festival.

• Journal of Distribution Science
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• v.20 no.6
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• pp.57-66
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• 2022

Purpose: Business agility is an important key to survival for SMEs in Indonesia, especially during the COVID-19 pandemic. Indonesian local product distribution and service distribution are mostly served by SMEs. Agile businesses will be able to assist them in the proper distribution of products and services. This research examines how the direct and indirect influence of IT capabilities on business agility through organizational learning and business intelligence for small and medium enterprises in the distribution of Indonesian products and services. Research design, data and methodology: This research uses SEM method with SmartPLS tool. The sample of this research was conducted on small and medium enterprises in the distribution of Indonesian products and services. The sample obtained in this study was 202 SME owners or managers (strategic level). Results: Business intelligence plays a key role in improving business agility. The results of IT capability can directly and indirectly affect business agility through organizational learning. Conclusions: Business intelligence has the biggest role in increasing business agility in SMEs in Indonesia. IT capability has an indirect effect on business agility through organizational learning. The findings of this study prove that IT capabilities do not indirectly affect business agility through business intelligence.

• Journal of Distribution Science
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• v.21 no.4
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• pp.11-20
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• 2023

Purpose: 1) develop a learning model involving design thinking to develop creative economy innovation and the characteristics of digital entrepreneurs. 2) evaluate the impact of design thinking on creative economy innovation 3) evaluate the impact of design thinking on digital entrepreneurial ability. Research design, data and methodology: 1) develop a learning model involving design thinking in order to develop creative economy innovation and the characteristics of digital entrepreneurs. 2) Evaluating creative economy innovation involving design thinking. 3) Assessing the characteristics of digital entrepreneurs based on design concepts. Results: 1) the development of a learning model involving design thinking to develop creative economy innovation and digital entrepreneurial competency 2) The students who studied using the learning model involving a design thinking process had the highest overall scores in terms of creative economy innovation 3) The scores for the assessment of digital entrepreneurial activity for the students who studied by using the design thinking learning model were at a high level. Conclusions: The development of the design thinking learning model can encourage students to be able to develop creative economy innovations and to empower digital entrepreneurs' ability for distribution strategy. Educational institutions that would like to succeed in developing creative economy innovative and digital entrepreneurship characteristics with the support of design thinking.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.2
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• pp.1-8
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• 2011

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The finite failure non-homogeneous Poisson process models presented and the life distribution applied extreme distribution which used to find the minimum (or the maximum) of a number of samples of various distributions. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error.