• The KIPS Transactions:PartC
• /
• v.12C no.6 s.102
• /
• pp.781-792
• /
• 2005

This study proposes an Architecture for user level End-to-end Quality of Service(QoS) using overlay In Next Generation Network(NGN). Inexisting NGNs, the IMS of a control plane provides user QoS through direct traffic control and resource-reservation over the IP packet transport network of a user plane. Further, a set of torrent studies are ongoing not only to maximize the QoS for users, but also to minimize the quality deterioration for supporting the user End-to-end QoS. Along with that, an extended QoS in user level must be considered, for Instance, differentiating service quality to support users' expectation, providing optimized contents by users' equipments, and so forth. Accordingly, the Overlay Service Network Architecture proposed by this study provides protocol adaptation for maximum throughput on transport layer by using the most efficient transport layer protocol to various network circumstances. Also, the Overlay Service Network Architecture on application layer distributes processing delay from the data transformation process of the user equipment to the network, and it is capable of intermediate processing depending on user service level. application service feature, and equipment circumstance as well. Thus, this study mainly proposes the Overlay Service Network Architecture for user level end-to-end QoS in NGN with the quality control features both on the transport layer and the application layer, an internal component feature, and a service scenario providing the QoS linking with 3GPP.

• Journal of Service Research and Studies
• /
• v.7 no.4
• /
• pp.151-164
• /
• 2017

This study aims to explore the effect of quality factors and learning styles on users' satisfaction in the use of business simulation tools in business education. 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 education using simulation were classified into contents, education environment, interpersonal activities, and instructor support while learning styles were classified into proactive, self-directed, environmental-dependent, and passive styles. The results showed that each quality factors of education using business simulation had a strong positive effect on user satisfaction. Proactive and environment-dependent group had higher satisfaction than other groups. Learning styles had moderating effects on the quality-satisfaction relationship, and the direction and degree varied depending on the quality factors and learning styles. Theoretical and practical implications were drawn from these findings.

• Journal of The Korean Association of Information Education
• /
• v.26 no.4
• /
• pp.249-263
• /
• 2022

The purpose of this study is to investigate the effects of assessment by adopting adaptive learning in higher education that are rarely examined in previous studies. In particular, this study applied research questions: 1) How does technical perception, perceived contents and features, and perceived integration of the AI-based adaptive system with lecture affect overall satisfaction, overall effectiveness, overall usefulness, overall motivation for the study, and intention to use it with other classes? 2) How do overall satisfaction, overall effectiveness, overall usefulness, motivation for the class, and intention to use affect loyalty on the AI-based adaptive system? This study conducted online surveys after the completion of the classes adopted AI-based adaptive learning system, ALEKS. This study applied ANOVA, regression, and factor analyses. The results of this study found that perceived integration of the AI-based adaptive learning system with the lectures on overall satisfaction, effectiveness, motivation, and intention to use for other classes showed significant with higher effect size. The results of this study provides implication that the AI-based learning system help improve learning outcomes in graduate level studies. The results provide policy and managerial implications that the AI-based adaptive learning system should improve better customer relationships in higher education.