• Korean journal of food and cookery science
• /
• v.32 no.3
• /
• pp.353-362
• /
• 2016

Purpose: This study examined the influence of restaurant quality attributes on customers' satisfaction and their intention to revisit by investigating the moderating effects of customers' electronic word of mouth evaluation about ethnic restaurants. The study was based on a total of 215 samples obtained from social networking service users in a metropolitan area from July 10 to 25, 2015. The major findings are as follows. Methods: The data were analysed using frequency, factor analysis, regression analysis and hierarchical regression analysis. Results: According to the results of factor analysis, quality attributes were separated into three factors: food, service, and atmosphere. According to the results, food attributes, service attributes and atmosphere attributes had an affect on customers' satisfaction, between quality attributes and revisit intention, only food attribute had an affect on revisit intention. It showed also that customers' satisfaction had an affect on revisit intention. Customers' electronic word of mouth (eWOM) evaluation was found to moderate the relationships between service quality attributes and satisfaction. Conclusion: Implications and future research were also discussed.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.9
• /
• pp.34-41
• /
• 2017

Wireless mesh networks contain multi-hop routing protocols between wireless nodes and are connected to the Internet through a gateway. These networks perform a role as a backbone and are scalable for main applications. We propose the design of QoS supporting mechanisms for wireless mesh networks using software defined networking. Our proposed scheme is cost-effective and features adaptive QoS mechanisms for wireless router's resource constraints. The QoS mechanisms use software defined networking technology with Openflow protocol based on diffserv and intserv models with MPLS mechanism and RSVP respectively. A performance evaluation model is suggested to verify the validity of the proposed scheme using several QoSmetrics of the wireless mesh networks.

• The Korean Journal of Health Service Management
• /
• v.2 no.1
• /
• pp.125-136
• /
• 2008

Government came to enforce long-term care insurance system in preparation for the rapid aging society. Whether this system is successful or not depends on the professionalism of long-term care-givers who are professional population in charge of care service. Currently in the early stage of enforcement, such problems as a race cutting fee resulted from numerical increase of educational facilities, insolvent operation, degradation of education level resulted from unprofessional instructor, are pointed out. As a mean of manpower-training on long-term care insurance system, this study is to research public-private-university network model of the Academy of Continuing Education attached to Ko Sin University which is the case of Yong Do Gu Busan city. Networking between the vision and development strategy of Yong Do Gu on continuing education city, education system on community manpower-training supported by Ko Sin University, and service field of welfare for the elderly can not only contribute to the professionalism of long-term care-givers but also play an ideal role in manpower-utilization and arrangement of community. Through this networking, high quality of education level and circumstance, using the existing infra, manpower-training and utilization for continuing education of Yong Do Gu can be accomplished. Additionally, the connection with facilities related with welfare for the elderly can contribute to professionalism and accountability of manpower-networking.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.5
• /
• pp.1077-1093
• /
• 2013

This paper proposes a new network coordinator node design to select the most suitable wireless technology for WBANs by using fuzzy logic. Its goal is to select a wireless communication technology available considering the user/application requirements and network conditions. A WBAN is composed of a set of sensors placed in, on, or around human body, which monitors the human body functions and the surrounding environment. In an effort to send sensor readings from human body to medical center or a station, a WBAN needs to stay connected to a local or a wide area network by using various wireless communication technologies. Nowadays, several wireless networking technologies may be utilized in WLANs and/or WANs each of which is capable of sending WBAN sensor readings to the desired destination. Therefore, choosing the best serving wireless communications technology has critical importance to provide quality of service support and cost efficient connections for WBAN users. In this work, we have developed, modeled, and simulated some networking scenarios utilizing our fuzzy logic-based NCN by using OPNET and MATLAB. Besides, we have compared our proposed fuzzy logic based algorithm with widely used RSSI-based AP selection algorithm. The results obtained from the simulations show that the proposed approach provides appropriate outcomes for both the WBAN users and the overall network.

• International Journal of Knowledge Content Development & Technology
• /
• v.7 no.4
• /
• pp.27-50
• /
• 2017

The impact of social networking is varied from good to bad. Online activities have also been categorized into pros and cons of social networking, either as reported as hiding Internet activities among teenagers or killing loneliness among elderly. In terms of relationships, there have been argument over its closeness and quality of an online relationship in Internet settings. Looking at the contradiction in an innovative interaction between classic community communication and social media, there is an unknown scent of the future struggling and challenging both human communication and relationships in the presence of digital culture. This research uses Diffusion of Innovation to study the wide and continuous spread of digital culture in human communication; and, Media Dependency in learning and structuring the cognitive, affective and behavioral effects of social media on each person uses the media in different ways. This research will be using online survey to gain opinions from a social network site as an update of views and reflection of self-awareness to all levels of people. Social media like Facebook (FB) is perceived as a good tool of communication that it is able to bring closeness among the family members. The results show that social media like FB brings positive impact towards family members; it would help to build a better and harmonic society; and, relationships among family members and communication shall be improved and enhanced to the level of a united society.

• Journal of Advanced Marine Engineering and Technology
• /
• v.34 no.6
• /
• pp.852-857
• /
• 2010

In this paper, we proposed and demonstrated an indoor visible-light communication system using an array of light-emitting diodes (LEDs). The main idea is based on that the LEDs can be used not only for lighting but also for free-space optical communications. Because LEDs offer advantageous properties such as high brightness, reliability, lower power consumption and long lifetime, the indoor visible-light communication systems are going to provide high quality of service by the high radiation power of the LED lighting. Prototype of simplex channel for audio and the full-duplex channel for text message were developed. Results indicates the viability of creating inexpensive free-space optical communication transceivers that might be embedded in commercial light products to supports indoor wireless networking.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2018.07a
• /
• pp.43-44
• /
• 2018

본 논문에서는 SDN환경에서 트래픽 분류를 위한 특징 선택 기법을 제안한다. 최근 들어 다양한 스마트폰 어플리케이션이나 다양한 IoT 기기들이 등장하고 있다. 다양한 IoT 기기나 어플리케이션은 엄청난 양의 트래픽을 발생시킨다. 엄청난 양의 트래픽은 전송속도를 저하시킬 뿐만 아니라, 높은 Quality of Service(QoS)를 보장하기가 힘들다. 또한 이러한 문제점들을 보안하기 위해 Software Defined Networking(SDN)이라는 기술이 빠른속도로 발전하고 있으며, 본 논문에서는 다양한 어플리케이션과 IoT 기기의 트래픽을 SDN환경에서 분류 하며, 트래픽의 분류 정확도와 더 빠른 분류를 위해 트래픽의 특징 선택 기법을 제안한다. 특징 선택을 수행한 뒤, 트래픽 분류를 진행하면 트래픽 분류 정확도를 높이고, 트래픽 분류시간은 줄어드는 효과를 보이며, 높은 QoS를 보장함으로써, 기존 네트워크 트래픽의 부하가 줄어드는 우수한 성능을 보인다.

• Transactions on Electrical and Electronic Materials
• /
• v.12 no.6
• /
• pp.241-244
• /
• 2011

An isolator transmits light in the forward direction and blocks light from passing in the reverse direction. It is regarded an essential optical component in medical, industrial, and research lasers for blocking reflection beams that cause optical damage and noise. It is also used as a communicative light intensifier to expand the lifespan of devices and enhance transmission quality. This study analyzed the characteristics of the core components in the construction of a polarization-independent isolator, namely, the walk-off polarizer and the Faraday rotator. Measurement of the extinction ratio of the resultant walk-off polarizer revealed that the ratio between the vertical and horizontal rays was 1,050:1 with a laser output of 0.032 W and 1,010:1 with a laser output of 2.68 W, thus presenting ratios similar to 1,000:1. In addition, the walk-off polarizer and Faraday rotator constructed in this study were used to compare output changes according to changes in power of input light and to check the penetration ratio. Results from the study presented variations in output value according to changes in power of input light. However, the average penetration ratio remained relatively consistent (~81.4%).

• Journal of Internet Computing and Services
• /
• v.22 no.5
• /
• pp.27-33
• /
• 2021

With the broad adoption of the Internet of Things (IoT) in a variety of scenarios and application services, management and orchestration entities require upgrading the traditional architecture and develop intelligent models with ultra-reliable methods. In a heterogeneous network environment, mission-critical IoT applications are significant to consider. With erroneous priorities and high failure rates, catastrophic losses in terms of human lives, great business assets, and privacy leakage will occur in emergent scenarios. In this paper, an efficient resource slicing scheme for optimizing federated learning in software-defined IoT (SDIoT) is proposed. The decentralized support vector regression (SVR) based controllers predict the IoT slices via packet inspection data during peak hour central congestion to achieve a time-sensitive condition. In off-peak hour intervals, a centralized deep neural networks (DNN) model is used within computation-intensive aspects on fine-grained slicing and remodified decentralized controller outputs. With known slice and prioritization, federated learning communications iteratively process through the adjusted resources by virtual network functions forwarding graph (VNFFG) descriptor set up in software-defined networking (SDN) and network functions virtualization (NFV) enabled architecture. To demonstrate the theoretical approach, Mininet emulator was conducted to evaluate between reference and proposed schemes by capturing the key Quality of Service (QoS) performance metrics.

• ETRI Journal
• /
• v.44 no.5
• /
• pp.733-745
• /
• 2022

In software-defined wireless networking (SDWN), the optimal routing technique is one of the effective solutions to improve its performance. This routing technique is done by many different methods, with the most common using integer linear programming problem (ILP), building optimal routing metrics. These methods often only focus on one routing objective, such as minimizing the packet blocking probability, minimizing end-to-end delay (EED), and maximizing network throughput. It is difficult to consider multiple objectives concurrently in a routing algorithm. In this paper, we investigate the application of machine learning to control routing in the SDWN. An intelligent routing algorithm is then proposed based on the machine learning to improve the network performance. The proposed algorithm can optimize multiple routing objectives. Our idea is to combine supervised learning (SL) and reinforcement learning (RL) methods to discover new routes. The SL is used to predict the performance metrics of the links, including EED quality of transmission (QoT), and packet blocking probability (PBP). The routing is done by the RL method. We use the Q-value in the fundamental equation of the RL to store the PBP, which is used for the aim of route selection. Concurrently, the learning rate coefficient is flexibly changed to determine the constraints of routing during learning. These constraints include QoT and EED. Our performance evaluations based on OMNeT++ have shown that the proposed algorithm has significantly improved the network performance in terms of the QoT, EED, packet delivery ratio, and network throughput compared with other well-known routing algorithms.