• Journal of Digital Convergence
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• v.15 no.12
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• pp.35-45
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• 2017

This study aims to explore the effect of quality factors and learning styles on users' satisfaction in e-Learning context. 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 e-Learning were classified into contents, system, service, and interpersonal activities while learning styles were classified into positive-cooperative, self-directed, environmental-dependent, and passive styles. The results showed that each quality factors of e-Learning has a strong positive effect on user satisfaction, and self-directed group has higher satisfaction than other groups. Learning styles have moderating effects on the quality-satisfaction relationship, and especially, the group of passive learning style has a strong moderating effect on the interpersonal activities. Theoretical and practical implications and future research directions are drawn from these findings.

• Journal of Broadcast Engineering
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• v.10 no.3
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• pp.313-320
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• 2005

The increasing popularity of multimedia streaming services introduces new challenges in content distribution. Especially, it is important to provide the QoS guarantees as they are increasingly expected to support the multimedia applications. Multimedia streams typically experience the high start-up delay due to the large protocol overhead, the delay, and the loss properties of the wireless networks. The service providers can improve the performance of multimedia streaming by caching the initial segment (prefix) of the popular streams at proxies near the requesting clients. The proxy can initiate transmission to the client while requesting the remainder of the stream from the server. In this paper, we propose the traffic based caching algorithm (TSLRU) to improve the performance of caching proxy. TSLRU classifies the traffic into three types, and improve the performance of caching proxy by reflecting the several elements such as traffic types, recency, frequency, object size when performing the replacement decision. In simulation, TSLRU performs better than the existing schemes in terms of byte hit rate, hit rate, startup latency, and throughput.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.475-478
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• 2014

최근 인터넷이 발전함에 따라 월드와이드웹(World Wide Web) 기반의 웹 서비스가 급격한 발전을 이루었다. 또한 이 웹 서비스를 바탕으로 다양한 컨텐츠들과 이를 이용하는 사용자의 수도 함께 증가하였다. 그러나 이와 같은 웹 서비스의 보편화가 증대될수록 이를 악용하려는 사이버 범죄 또한 비례하여 증가하고 있다. 최근에는 공격자들이 스마트폰을 대상으로 악성코드를 전파하기 위한 방법으로 웹 서비스를 활용하기 시작하면서 웹 서비스의 보안에 대한 중요성이 더욱 강조되고 있다. 이러한 웹 서비스 보안의 필요성을 인지하고, 많은 사람들이 무료로 쉽게 웹 서비스 보안취약점을 진단 할 수 있도록 여러 오픈소스 기반의 보안 취약점 진단도구가 연구, 개발되고 있다. 하지만 웹 서비스의 보안약점을 진단하는 도구의 적합성 평가 및 기능 분류가 명확하지 않아서 진단도구를 선택하고 활용함에 있어 어려움이 따른다. 본 논문에서는 OWASP에서 위험도에 따라 선정한 웹 서비스의 보안 취약점 Top 10 항목과 소프트웨어 보안약점 진단가이드 등을 통해 웹 서비스 보안 취약점을 진단하는 도구에 대한 분석 기준을 제시한다. 이후 오픈소스로 공개된 테스트 기반 취약점 탐지도구와 소스 기반 취약점 진단도구들에 대해 제시한 기준을 이용하여 분석한다. 본 논문의 분석결과로 웹 서비스의 안전성을 평가하기 위해 활용할 수 있는 진단 도구에 대한 분석정보를 제공함으로써 보다 안전한 웹 서비스의 개발과 운영에 기여할 것으로 기대한다.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.339-345
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• 2019

This study explores the Experiential Theory of John Dewey and Donald Norman's definition of user experiences to analyze the new cultural experience of trying on Hanbok among the young generation. In order to find out the demographic characteristics, the survey was conducted online. An in-depth interview was held among six women in their 20's who were randomly selected to obtain diverse consumer's opinions. According to the interview, rather than recognizing the traditional beauty of Hanbok, the interviewers recognized the aesthetic sensibility of modernized Hanbok. In addition, the uniqueness of wearing Hanbok which has become the non-ordinary culture and the desire to share the experience is analyzed through characteristics such as particularity. In order to develop cultural contents that are highly marketable, consistent analyzation and research of the fluctuating desire of customers are essential since users perceive their experience to be special.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.151-161
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• 2021

This study is a descriptive qualitative study to understand the virtual reality-based simulation experiences of nursing students. The study recruited 53 students who conducted virtual reality-based simulation while attending the course of Adult Nursing I and II in the third year of the department of nursing at a university. The data was analyzed using a content analysis method from a reflection journal created anonymously by students. The results emerged 5 categories and 12 subcategories. The categories were consisted of "realizing the necessity of nursing competence", "expanding nursing knowledge", "receiving safety psychologically", "thinking focused on problem" and "getting satisfaction". It suggests that virtual reality online program can have a positive effect on thoughts and expansion of knowledge in a safe educational environment. Therefore, it needs to develop various contents for the virtual reality education and training.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.833-842
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• 2020

Global platforms such as Netflix, Amazon, and YouTube have developed a precise recommendation system based on various information from large set of customers and many of the items recommended here are leading to actual purchases. In this paper, a cluster analysis was conducted according to the attribute of the content, expecting that there would be a difference in user preferences according to the attribute of the recommended content. Gower distance was used for use regardless of the type of variables. In this paper, using the data of movie rating site 'The Movie Dataset', the users were grouped hierarchically and recommended movies based on genre, director and actor variables. To evaluate the recommended systems proposed, user group was divided into train set and test set to examine the precision. The results showed that proposed algorithms have far higher precision than UBCF.

• Journal of Industrial Convergence
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• v.20 no.4
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• pp.31-37
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• 2022

Research on what factors affect the success of the movie market is very important for reducing risks in related industries and developing the movie industry. In this study, in order to find out the degree of correlation of independent variables that affect movie performance, a survey was conducted on film experts using the AHP method and the importance of each measurement factor was evaluated. In addition, we hypothesized that factors derived from big data related to search portals and SNS will affect the success of movies due to the increase in the spread and use of smart phones. And a prediction model that reflects both the expert survey information and big data mentioned above was proposed. In order to check the accuracy of the prediction of the proposed model, it was confirmed that it was improved (10.5%) compared to the existing model as a result of verification with real data.Therefore, it is judged that the proposed model will be helpful in decision-making of film production companies and distributors.

• International Commerce and Information Review
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• v.14 no.3
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• pp.539-558
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• 2012

The purpose of this study is examining the differences of mobile SNS's service quality, which consists data quality and system quality, among the groups that are classified by commitment and customer loyalty. For the experimental analysis, the frequency analysis was performed for general characteristics of sample. The variables were selected by factor analysis that also prove the validity of variables. The value of Cronbach's alpha was calculated to check the reliability of variables. In addition, the group was determined by the both hierarchical and hierarchical cluster analysis, then ANOVA was performed to test the hypotheses that there are differences of mobile SNS's service quality, among the groups that are classified by commitment and customer loyalty. The results of this study support that there are differences among the groups toward mobile SNS's service quality and also shows the more commitment and loyalty group is the higher recognition of mobile SNS's service quality. Thus, the companies have to realize that mobile SNS is very important key factor to success in rapidly changing business environment. In conclusion, the companies implement different customized strategy for the different group and develop the contents and the applications to maximize the commitment and loyalty of for the mobile SNS users.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2878-2884
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• 2015

Twitter, one of online social network services, is one of the most popular micro-blogs, which generates a large number of automated programs, known as tweet bots because of the open structure of Twitter. While these tweet bots are categorized to legitimate bots and malicious bots, it is important to detect tweet bots since malicious bots spread spam and malicious contents to human users. In the conventional work, temporal information was utilized for the classficiation of human and bot. In this paper, by utilizing geo-tagged tweets that provide high-precision location information of users, we first identify both Twitter users' exact location. Then, we propose a new tweet bot detection algorithm by using both an entropy based on geographic variable of each user and device information of each user. As a main result, the proposed algorithm shows superior bot detection and false alarm probabilities over the conventional result which only uses temporal information.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.1-6
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• 2002

Many customers consult the Internet before making purchase goods and using contents. The systems in the Internet could store a lot of data and classify the data into information to get relationship between a company and customers. To do that, let's consider a knowledge-assisted hybrid system that utilizes individually a customer's preference to make an optimal solution in the his/her decision making. The knowledge made by using the preference is employed to select an domain set appropriate to him/her business, and the process of selecting definitely provides the customer some benefits: elimination of discomfort from unknown information and reduction of costs and search time for forming an suitable domain set. To effectively adopt individual customer's preference and actively adapt change of business situation, this study propose an architecture of the system which includes rule presentations and an inference engine, and integrates a knowledge-based component into a quadratic programming component. In the experimental results, it is found that a knowledge-assisted hybrid system implemented by this idea is more flexible than existing systems in extension of knowledge about an customer's preference and goes beyond the traditional models.