• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.301-311
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• 2005

This study has conducted to measure the internet banking customer satisfaction using structured equation model. Data was collected by e-mail system. Among survey panel who had experience of using Hanwha-Bank internet banking service, final samples were 2,848 respondents. The results showed that usage convenience and economy factor was most correlated with customer satisfaction. And we found that word-of-mouth behavior was affected customer satisfaction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5182-5199
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• 2017

Recently, Internet of Things (IoT) drives a large variety of research, development, and new type of markets. All type of devices and sensors will be part of the Internet of Things and will be able to communicate not only plain data, but also audio-visual, olfactory, and haptic media data. In addition, as the devices and sensors getting smarter, it is highly probable that they can process acquired media and metadata to extract higher level of information (e.g., semantics). To support such enhanced functionalities, ISO/IEC SC29 WG11 (MPEG) starts a new standard project, ISO/IEC 23093, called Internet of Media Things (IoMT) to provide standard data formats and APIs for media things. This paper presents the standardization activities of IoMT focusing on explaining terms, standard scopes, and major media things with their use cases. One of the use cases, an IoT system for a blind pedestrian navigation assistance, is evaluated to prove its effectiveness.

• Korean Journal of Human Ecology
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• v.13 no.6
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• pp.861-874
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• 2004

The goal of this study is to investigate the relationship between maternal rearing behavior characteristics and elementary school children's Internet use, and to utilize the results as the basic data to develop a program, in which parents learn how to educate their children for better use of the Internet. The subjects were 713 children whose grade are in fourth through sixth in an elementary school. Data were obtained with questionnaires. The instruments employed were Children's Internet Use and Addiction, and maternal rearing behavior characteristics-Rational Guidance, Affection, Authoritarian Control, Overprotection, Achievement Encouragement, and Active Involvement-Scales. The data were analyzed with the SPSS program. They were analyzed by Frequency, Percentage, ANOVA, Duncan's test, and Pearson correlation. The results of this study are as follows: First, 30.2% of the subjects has used Internet for more than three years. 55.6% of the subjects spend less than an hour per day in using the Internet. The two major types of Internet use were playing games(49.9%) and sending e-mails(25.4%). The main reason for playing Internet games was escape from stress(34.7%). 34.5% of the subjects also said that their parents usually encourage them to use the Internet. Second, maternal affection, authoritarian control, and active involvement were significantly different in the types of Internet use. Maternal authoritarian control and overprotection were significantly different in the reasons of doing Internet game. The rational guidance and active involvement of mothers were correlated negatively with children's Internet using time, but their authoritarian control and overprotection were correlated positively with children's Internet using time. Maternal overprotection was correlated positively with parents' encouragement level in the Internet use. Third, the rational guidance, affection, and active involvement of mothers were correlated negatively with children's Internet addiction. In the other hand, maternal authoritarian control and overprotection were correlated positively with children's Internet addiction. Lastly, children's Internet addiction was significantly different by the types of Internet Use and the reasons for doing internet game. Children's Internet using time was correlated positively with children's Internet addiction.

• Journal of Korean Academy of Nursing
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• v.34 no.3
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• pp.541-551
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• 2004

Purpose: This study was to identify the effects of the predictive factors of Internet addiction and to develop a predictive model that explains Internet addiction among adolescents in Korea. Method: Data was collected from 664 adolescents in Puasan and Ulsan. Data analysis was done using the SPSS 10.0 Win Program for descriptive and correlational statistics and the LISREL 8.53 Win Program for Covariance structural analysis. Result: The fit of the hypothetical model to the data was moderate, it was modified by deleting four paths. Compared to the hypothetical model, the revised one had a better fit to the data($\chi^2$/df=6.50, GFI=.99, AGFI=.90, RMR=.02, NNFI=.88, NFI=.98, CN=279). Gender, friend support, and loneliness had significant direct effects on Internet addiction. The direct and indirect effect of self-esteem on Internet addiction was significant. The indirect effect of family support on Internet addiction was significant but its direct effect was insignificant. The direct and indirect effects of stress and impulsiveness on Internet addiction were significant but their total effects were insignificant. Conclusion: Finally, to decrease loneliness, and to increase family support and self-esteem, an effective intervention program and education should be developed to prevent Internet addiction of adolescents.

• Korean Management Science Review
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• v.19 no.1
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• pp.29-38
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• 2002

Due to the rapid increase In the Internet traffic volume, ISPs are faced with the definite need of the expansion of server capacity. In order to Provide prompt services for customers and still prevent excessive facility cost, it is critical to determine the optimum level of internet server capacity. The purpose of this Paper is to provide a simple but effective strategy on the expansion of servers capacity according to the increase in internet traffic. We model an internet server as an M/G/m/m queueing system and derive an efficient method to compute the loss probability which, In turn, Is used as a basis to determine proper server capacity. The Process of estimating the traffic parameter values at each server based on log data analysis is also given. All the procedures are numerically demonstrated through the process of analyzing actual log data collected from a game company.

• Korean journal of aerospace and environmental medicine
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• v.30 no.3
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• pp.100-107
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• 2020

Internet of Things (IoT) is a technology that communicates data between devices, which are things, using an embedded sensor connected through network backbone such as the internet. Here, data communication technology, sensor technology, and actuator (interface) technology are fused into IoT and it turns devices into smart things. As a result, vast sized data are being generated and that data is being processed into useful actions that can control the things that are devices to make our lives much fruitful. Nowadays, the IoT, early defined as Machine-to-Machine (M2M) connection, becomes a key technology powered by growing innovation of wireless communication trends in the internet connectivity through mobile networking. This paper gives an overview of Internet of Things and brief information about major technologies and its applications in various fields focusing aviation.

• Journal of Service Research and Studies
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• v.1 no.1
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• pp.61-69
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• 2011

Data mining that can not be extracted with a simple query in the form of "useful" means to find information in large databases from the existing and unknown knowledge. It is based on this insight about the data can be defined as a gain. In this paper, we use the Internet to find useful patterns on the Web or saved data to the target Web site, which is to analyze the characteristics of users. A general statistical information on Internet users to the data by applying a relevance analysis, Internet use affect the amount of time to analyze the characteristics of Internet users. Only through experiments extracting data from the association rules, producing optimal results apply for the data pre-processing and algorithm for mining the Web to Internet users. characteristics were analyzed.

• Research in Community and Public Health Nursing
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• v.20 no.3
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• pp.316-326
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• 2009

Purpose: The purpose of this study was to examine teenagers' Internet addiction and to find factors influencing it. Methods: Data were collected from 596 middle and high school students between June 1 and June 20, 2009 with a self-rating questionnaire. The data were processed with SPSS/WIN 12.0. Results: (1) 20.3% of the students were spending over three hours a day in Internet use. The percentages of mild and serious Internet addiction were 22.3 and 2.1, respectively. (2) The stronger Internet addiction was, the higher stress was and the lower social support was. There was a negative correlation between stress and social support (r=-.296, p<.01). There was also a positive correlation between Internet addiction and stress (r=.264, p<.01) while a negative correlation between Internet addiction and social support (r=-.127, p<.01). (3) Among the subjects' characteristics, sex, school and family type, frequency of processed food intake, average daily Internet use hour and sleeping hour, subjective health perception, and satisfaction level with parents and family made difference in the Internet addiction level. Conclusion: The result of this study will provide useful background data for the selection of target population, stress management and social support promotion programs to prevent teenagers' Internet addiction.

• Journal of Korean Foot and Ankle Society
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• v.25 no.3
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• pp.126-132
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• 2021

Purpose: This study examined whether there are seasonal variations in the number of plantar fasciitis cases from the database of the Korean Health Insurance Review & Assessment Service and an internet search of the volume data related to plantar fasciitis and whether there are correlations between variations. Materials and Methods: The number of plantar fasciitis cases per month was acquired from the Korean Health Insurance Review & Assessment Service from January 2016 to December 2019. The monthly internet relative search volumes for the keywords "plantar fasciitis" and "heel pain" were collected during the same period from DataLab, an internet search query trend service provided by the Korean portal website, Naver. Cosinor analysis was performed to confirm the seasonality of the monthly number of cases and relative search volumes, and Pearson and Spearman correlation analysis was conducted to assess the correlation between them. Results: The number of cases with plantar fasciitis and the relative search volume for the keywords "plantar fasciitis" and "heel pain" all showed significant seasonality (p<0.001), with the highest in the summer and the lowest in the winter. The number of cases with plantar fasciitis was correlated significantly with the relative search volumes of the keywords "plantar fasciitis" (r=0.632; p<0.001) and "heel pain" (r=0.791; p<0.001), respectively. Conclusion: Both the number of cases with plantar fasciitis and the internet search data for related keywords showed seasonality, which was the highest in summer. The number of cases showed a significant correlation with the internet search data for the seasonality of plantar fasciitis. Internet big data could be a complementary resource for researching and monitoring plantar fasciitis.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.3
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• pp.135-148
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• 2003

In this paper we introduce the Internet-based purchase support systems using data mining and case-based reasoning (CBR). Internet Business activity that involves the end user is undergoing a significant revolution. The ability to track users browsing behavior has brought the vendor and end customer's closer than ever before. It is now possible for a vendor to personalize his product message for individual customers at massive scale. Most of former researchers, in this research arena, used data mining techniques to pursue the customer's future behavior and to improve the frequency of repurchase. The area of data mining can be defined as efficiently discovering association rules from large collections of data. However, the basic association rule-based data mining technique was not flexible. If there were no inference rules to track the customer's future behavior, association rule-based data mining systems may not present more information. To resolve this problem, we combined association rule-based data mining with CBR mechanism. CBR is used in reasoning for customer's preference searching and training through the cases. Data mining and CBR-based hybrid purchase support mechanism can reflect both association rule-based logical inference and case-based information reuse. A Web-log data gathered in the real-world Internet shopping mall is given to illustrate the quality of the proposed systems.