• Communications for Statistical Applications and Methods
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• 제9권3호
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• pp.665-674
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• 2002

The advantage of internet survey compared to the traditional survey methods are speedy in data collection, cost-effective, high performed design and able to data process and analysis at the same time. The other side are difficult to select sample, come from serious nonresponse errors. We suggest the new internet survey method to the questionnaire design that have the high response rate, enough to advanced preparations and system stability.

• 가정과삶의질연구
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• 제27권4호
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• pp.127-139
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• 2009

The purpose of this study was to develop a standardized scale to measure consume's impulse purchasing in internet shopping mall. As internet shopping is expanding rapidly, the consumer's impulse purchasing in the internet shopping is also increased. A preliminary 26-item scale was developed through a literature review. 1230 consumers responded to an online survey using the preliminary scale. This research was made with the intention of not only supplying the academic data on the consumer's impulse purchasing but also understanding the consume's basic behavior patterns in internet shopping mall. Then A series of tests, such as test-retest, item-to-total correlation, Cronbach's reliability coefficient and factor analysis, were conducted using the survey data. The final scale with 20-items was constructed in the end. The consume's impulse purchasing in internet shopping mall Scale for Consumers consisted of 4 factors.

• Journal of Information Technology Applications and Management
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• 제11권1호
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• pp.83-100
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• 2004

Understanding characteristics of Internet businesses from a cross-cultural perspective could offer valuable insights on developing business strategies and policies. This work is concerned with revealing divergence and convergence of Internet businesses in their financial performance, given organizational conditions and cultural context. For this, we studied the association between static organizational attributes (core activity, origination, firm age, and industry type) and a firms financial performance (gross revenue and net income). Relevant data was gathered from representative Internet firms in Korea and U.S. Data analysis indicated that, besides industry type, overall connection between selected organizational variables and financial performance was weak. Cross-national comparison showed that Korean firms financial performance was comparable to U.S firms during the period of economic turbulence. A noticeable difference was that Korean Internet firms and their business models were more service-oriented than U.S. counterparts.

• 한국전자거래학회지
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• 제6권2호
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• pp.39-55
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• 2001

As the Proliferation of the Internet, especially World Wide Web, numerous information resources have been constructed. The characteristics of information resources on the Internet are that the information resources are distributed, autonomous, and heterogeneous. Moreover each information resource has its own query method, data representation, and schema structure. The integration of information resources is one of the most important research issues in the Internet data management. The task of information resources integration system is to answer queries that require extracting and combining data from multiple information sources. In this paper, we propose an XML-based Mediation Framework(XMF) for integrating the Internet information resources.

• 지역사회간호학회지
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• 제26권1호
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• pp.52-60
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• 2015

Purpose: The study was performed in order to identify the relationship between health behaviors and Internet use among adolescents. Methods: The study used raw data from the Korean Youth Risk Behavior Web-Based Survey that was performed in 2012. Data of a total of 74,186 students were analyzed using SPSS/WIN 18. The data were analyzed using descriptive statistics, t-test, and Pearson's correlation. Results: Internet use and health behaviors were significantly related to gender, depression, suicidal intent, parents' educational level, cohabitation with parents at home, school location, and grade. There was a significant association between Internet use and health behaviors in adolescents. Conclusion: Health promotion and education programs need to consider factors found relevant in this study.

• 전자통신동향분석
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• 제34권6호
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• pp.123-132
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• 2019

The Internet is evolving into a fundamental social infrastructure, similar to electricity and water. In particular, the role of the Internet is becoming more critical as the global digital transformation infrastructure of the 4th industrial revolution. Based on this trend, we note that the Internet is monopolized by a few large organizations even though it was originally designed as a purely distributed system. In this paper, we have reviewed the domination trends, especially in terms of data consolidation. In addition, we have summarized the corresponding research activities from the Internet Society, EU Horizon-2020, and Decentralized web. Further, this paper proposes an approach to address the data consolidation issue from the Korean perspective.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권6호
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• pp.1600-1619
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• 2023

Organizations and other institutions have recently started using cloud service providers to store and share information in light of the Internet of Things (IoT). The major issues with this storage are preventing unauthorized access and data theft from outside parties. The Block chain based Security Sharing scheme with Data Access Control (BSSDAC) was implemented to improve access control and secure data transaction operations. The goal of this research is to strengthen Data Access Control (DAC) and security in IoT applications. To improve the security of personal data, cypher text-Policy Attribute-Based Encryption (CP-ABE) can be developed. The Aquila Optimization Algorithm (AOA) generates keys in the CP-ABE. DAC based on a block chain can be created to maintain the owner's security. The block chain based CP-ABE was developed to maintain secures data storage to sharing. With block chain technology, the data owner is enhancing data security and access management. Finally, a block chain-based solution can be used to secure data and restrict who has access to it. Performance of the suggested method is evaluated after it has been implemented in MATLAB. To compare the proposed method with current practices, Rivest-Shamir-Adleman (RSA) and Elliptic Curve Cryptography (ECC) are both used.

• Child Health Nursing Research
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• 제12권1호
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• pp.34-43
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• 2006

Purpose: The purpose of this study was to identify the degree of internet addiction and factors affecting internet addiction in elementary school students. Method: The participants in this study were 1,328 students in 4, 5 or 6 grades of elementary school. They were recruited from two elementary schools. Data collection was conducted using of 6 questionnaires that were modified by the investigator. The data were analyzed with the SPSS win 10.0 program using descriptive statistics, Pearson correlation coefficients and stepwise multiple regression. Results: 1) The mean of total item score for internet addiction was 2.1, which was slightly low. Of respondents in this research 48.4% normally use the internet, while 48.5% addictively use the internet and as high as 3.1% were serious internet-addicted. 2) There was a significant correlation between internet addiction, self-esteem, aggression, impulsivity, parent's support and friend's support(γ= -.15 ～ .44). 3) Stepwise multiple regression analysis showed that amount of time spent on the internet per day, impulsivity, aggression, gender, self-esteem, duration to use of internet, father's age, and the major place where the internet was used were the predictors of internet addiction and accounted for 47% of the variance in internet addiction. Conclusion: Time spend on the internet per day, impulsivity, aggression, gender, self-esteem, duration to use of internet, father's age, the major place where the internet was used accounted for internet addiction in elementary school students. Therefore it is necessary to develop nursing interventions and to further identify the depth of the relationship of the related factors in order to decrease internet addiction.

• Child Health Nursing Research
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• 제15권1호
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• pp.24-33
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• 2009

Purpose: The purpose of this study was to explore the parent related factors that influence internet game addiction among elementary school students. Method: Data was collected through self-administered questionnaires and descriptive statistics, t-test, ANOVA, correlation and stepwise multiple regression were used to analyze the data. Data survey was conducted with 739 conveniently selected students who were in grades 4, 5, and 6 of elementary schools in Seoul or Gyung-gi province. Results: The addiction groups were classified as general user group (84.3%), potential risk group (10.0%) and high risk group (5.7%). There were significant internet game addiction differences by gender, grade, expense of internet cafe, religion, school record, place where child played, economic status, and duration and frequency of game play. The addiction was negatively correlated to parents' attachment, supervision, attitude to child nurturing, and expectations regarding school study. The most significant variables were both parents' attitude to child nurturing, and mother's supervision. These three variables explained 20.7% of internet game addiction in elementary school students. Conclusion: These findings are expected to make a contribution to the creation of ideal interventions at school, home, and counselling centers to prevent internet game addiction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권11호
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• pp.5427-5445
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• 2019

While deep neural networks have achieved remarkable performance in representation learning, a huge amount of labeled training data are usually required by supervised deep models such as convolutional neural networks. In this paper, we propose a new representation learning method, namely generative adversarial networks (GAN) based bagging deep convolutional autoencoders (GAN-BDCAE), which can map data to diverse hierarchical representations in an unsupervised fashion. To boost the size of training data, to train deep model and to aggregate diverse learning machines are the three principal avenues towards increasing the capabilities of representation learning of neural networks. We focus on combining those three techniques. To this aim, we adopt GAN for realistic unlabeled sample generation and bagging deep convolutional autoencoders (BDCAE) for robust feature learning. The proposed method improves the discriminative ability of learned feature embedding for solving subsequent pattern recognition problems. We evaluate our approach on three standard benchmarks and demonstrate the superiority of the proposed method compared to traditional unsupervised learning methods.