• Knowledge Management Research
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• v.9 no.4
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• pp.17-33
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• 2008

This study proposes University 2.0 as a model case of open, flexible, and distributed learning environment for higher education based on theoretical foundations and perspectives. As web 2.0 technologies emerge into the field of education, ways of generating and disseminating information and knowledge have been drastically changed. Professors are no longer the only source of knowledge. Students using internet often become prosumers of knowledge who search and access information through the web as well as publish their own knowledge using the web. A concept and framework of University 2.0 is introduced for implementing the new interactive learning paradigm with an open, flexible and distributed learning environment for higher education. University 2.0 incorporates online and offline learning environments with various educational media. Furthermore, it employs various learning strategies and integrates formal and informal learning through learning communities. Both instructors and students in University 2.0 environment are expected to be active knowledge generators as well as creative designers of their own learning and teaching.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.117-135
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• 2016

Performance enhancement is one of the most important issues in high performance distributed computing systems. In such computing systems, online users submit their jobs anytime and anywhere to a set of dynamic resources. Jobs arrival and processes execution times are stochastic. The performance of a distributed computing system can be improved by using an effective load balancing strategy to redistribute the user tasks among computing resources for efficient utilization. This paper presents a multi-class load balancing strategy that balances different classes of user tasks on multiple heterogeneous computing nodes to minimize the per-class mean response time. For a wide range of system parameters, the performance of the proposed multi-class load balancing strategy is compared with that of the random distribution load balancing, and uniform distribution load balancing strategies using simulation. The results show that, the proposed strategy outperforms the other two studied strategies in terms of average task response time, and average computing nodes utilization.

• Journal of the Korea Society for Simulation
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• v.13 no.4
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• pp.43-53
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• 2004

The distributed OCSP (Online Certificate Status Protocol), composed of multiple responders, is a model that enhances the utilization of each responder and reduces the response time. In a multi-user distributed environment, load balancing mechanism must be developed for the improvement of the performance of the whole system. Conservative load balancing algorithms often ignore the communication cost of gathering the information of responders. As the number of request is increased, however, fail to consider the communication cost may cause serious problems since the communication time is too large to disregard. We propose an adaptive load balancing algorithm and evaluate the effectiveness by performing modeling and simulation. The principal advantage of new algorithm is in their simplicity: there is no need to maintain and process system state information. We evaluated the quality of load balancing achieved by the new algorithm by comparing the queue size of responders and analyzing the utilization of these responders. The simulation results show how efficiently load balancing is done with the new algorithm.

• Journal of Technologic Dentistry
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• v.43 no.4
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• pp.186-193
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• 2021

Purpose: The purpose of the study was to determine the general characteristics of students in dental technology departments; the correlations among their immersion in learning, class satisfaction, and academic achievement; factors influencing online learning experience; ways to improve students' class satisfaction; and basic data for designing effective online courses. Methods: A total of 300 questionnaires were produced and distributed to dental technology students from September 29 through October 8, 2020. The outcome was analyzed using IBM SPSS Statistics ver. 25.0. A significance level of α=0.05 was used for reliable verification. Results: Immersion in learning, class satisfaction, and academic achievement were relatively high among students who studied on a regular basis, and class satisfaction and academic achievement were relatively high among students who studied with almost no interruption. Concerning the correlations between academic achievement, immersion in learning, and class satisfaction in online learning, the correlation between academic achievement and class satisfaction was the highest at r=0.862. Class satisfaction was the largest factor that influenced academic achievement, and the higher students' immersion in learning and class satisfaction were, the higher their academic achievement was. Conclusion: The research is a case study that investigated the general characteristics of dental technology department students and the correlations among their immersion in learning, class satisfaction, and academic achievement. The study outcome could be used in determining factors that influence online learning and designing effective online courses that improve learner satisfaction.

• Journal of Communications and Networks
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• v.13 no.3
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• pp.277-285
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• 2011

Real-time multimedia streaming over the Internet is rapidly increasing with the popularity of user-created contents, Web 2.0 trends, and P2P (peer-to-peer) delivery support. While many homes today are broadband-enabled, the quality of experience (QoE) of a user is still limited due to frequent interruption of media playout. The vulnerability of TCP (transmission control protocol), the popular transport-layer protocol for streaming in practice, to the packet losses, retransmissions, and timeouts makes it hard to deliver a timely and persistent flow of packets for online multimedia contents. This paper presents TCP-real-time online multimedia environment (ROME), a novel transport-layer framework that allows the establishment and coordination of multiple many-to-one TCP connections. Between one client with multiple home addresses and multiple co-located or distributed servers, TCP-ROME increases the total throughput by aggregating the resources of multiple TCP connections. It also overcomes the bandwidth fluctuations of network bottlenecks by dynamically coordinating the streams of contents from multiple servers and by adapting the streaming rate of all connections to match the bandwidth requirement of the target video.

• ETRI Journal
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• v.33 no.2
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• pp.219-229
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• 2011

In this paper, we propose a transformation scheme used to analyze online gaming traffic properties and develop a traffic model. We analyze the packet size and the inter departure time distributions of a popular first-person shooter game (Left 4 Dead) and a massively multiplayer online role-playing game (World of Warcraft) in order to compare them to the existing scheme. Recent online gaming traffic is erratically distributed, so it is very difficult to analyze. Therefore, our research focuses on a transformation scheme to obtain new smooth patterns from a messy dataset. It extracts relatively heavy-weighted density data and then transforms them into a corresponding dataset domain to obtain a simplified graph. We compare the analytical model histogram, the chi-square statistic, and the quantile-quantile plot of the proposed scheme to an existing scheme. The results show that the proposed scheme demonstrates a good fit in all parts. The chi-square statistic of our scheme for the Left 4 Dead packet size distribution is less than one ninth of the existing one when dealing with erratic traffic.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.9-17
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• 2021

This is a descriptive investigative study which attempts to confirm the mediating effect of learning motivation in the relationship between self-directed learning, learning commitment, and learning persistence intention of university students in an online learning environment. The questionnaires were randomly distributed online and the agreed questionnaires were retrieved, with a total of 338 copies used for analysis. The following is the summary of the findings. First, there were significant differences in learning persistence intention according to general characteristics depending on age, major, part-time job, and academic level. Second, the results showed a positive correlation between self-directed learning, learning commitment, learning motivation, and learning persistence intentions of the subjects were statistically significant. Third, after checking the mediating effect of learning motivation in relation to self-directed learning, learning commitment and learning motivation, the learning motivation has a partial mediating effect on learning and 23% explanatory power, and the learning commitment was found to have a complete mediating effect on the impact of learning motivation on learning intentions with 21% explanatory power. Based on these results, it is necessary to provide a more diverse educational environment, such as operating a motivation semester program that can improve learning motivations along with learning commitment, and the use of a variety of contents that can focus the learner's interest or attention.

• Journal of the Korean Data and Information Science Society
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• v.24 no.5
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• pp.989-998
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• 2013

We cannot analyze big data, which attracts recent attentions in industry and academy, by batch processing algorithms developed in data mining because big data, by definition, cannot be uploaded and processed in the memory of a single system. So an imminent issue is to develop various leaning algorithms so that they can be applied to big data. In this paper, we review various algorithms for support vector machines in the literature. Particularly, we introduce online type and parallel processing algorithms that are expected to be useful in big data classifications and compare the strengths, the weaknesses and the performances of those algorithms through simulations for linear classification.

• The Journal of Industrial Distribution & Business
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• v.11 no.2
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• pp.17-23
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• 2020

Purpose: The purpose of this study is to understand the effect of the unique product recommendation system on customer satisfaction. Research design, data and methodology: The survey method used the self-recording way in which the respondents selected for the study and distributed 300 questionnaires, and with due personal care, researchers collected all the distributed questionnaires. Results: The result implies that the characteristics of the product recommendation system should be more secure and developed. Conclusions: The aspects of the product recommendation system were selected as factors of price fairness, accuracy, and quality through previous studies, and the empirical analysis of the effect of the characteristics of the product recommendation system on customer satisfaction was summarized as follows. Among the attributes of the product recommendation system, the attributes of price fairness, accuracy, and quality affect customer satisfaction. Among them, the beta value of quality was the highest, and the effect of quality was the largest among the three factors. Based on the results of the study, the implications for the characteristics of the product recommendation system are summarized as follows. The aspects of the product recommendation system have a positive effect on customer satisfaction, so it is necessary to fill the needs of consumers based on the survey focused on quality

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.4
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• pp.879-888
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• 2018

Along with the recent worldwide development of fintech, FIDO (Fast IDentity Online) using biometric technology is rapidly growing in the mobile payment market, replacing the existing password system. This FIDO authentication must be processed in a reliable environment that requires high level of security, as sensitive biometrics is being processed. However, this environment is currently dependent on the manufacturer as it is supported by certain hardware on the smartphone. Therefore, this thesis proposes a server-based authentication model using distributed management of compliance based biometric information that can be used universally safely without the need for specific hardware in mobile environments.