• International Journal of Contents
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• v.18 no.2
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• pp.1-17
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• 2022

As of September 2021, COVID-19 is still seriously impacting people globally. To better control the epidemic, the Chinese government adopted a nationwide quarantine policy at the early stage of the discovery of COVID-19, which has significantly changed people's production and life. China's Douyin app (International version: TikTok) is an extremely influential entertainment and social tool. During COVID-19, a large number of short videos about COVID-19 appeared. Publishers included government agencies, professionals, and self-media. The content released has made Douyin a tool for people to receive COVID-19 information in addition to entertainment and social functions. This is a quantitative study. By exploring the impact of the Douyin app on Chinese college students during COVID-19, this study provides suggestions from the level of social media such as TikTok to enable Korea's epidemic prevention to be more effective. This study established variable questions such as Douyin's information perceived value, information usage channels, information awareness, anti-epidemic policy attitude, trust of public institution and preventive behavioral intention, and conducted a questionnaire survey. Using SPSS to analyze the obtained data, this study found that: 1. The short video information usage channels about COVID-19 in Douyin have a positive impact on the audience's information awareness; 2. The information perceived value in Douyin has a positive impact on the audience's information awareness; 3. Information awareness and trust of public institution in Douyin have a positive impact on the audience's anti-epidemic policy attitude; 4. Information awareness and trust of public institutions in Douyin have a positive impact on the audience's preventive behavioral intention; 5. The audience's anti-epidemic policy attitude has a positive effect on preventive behavioral intention.

• Journal of Information Technology Services
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• v.17 no.2
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• pp.111-128
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• 2018

About 3.9 million apps and 24 primary categories can be approved on Apple iTunes Store. Making accurate categorization can potentially receive many benefits for developers, app stores, and users, such as improving discoverability and receiving long-term revenue. However, current categorization problems may cause usage inefficiency and confusion, especially for cross-attribution, etc. This study focused on evaluating the reliability of app categorization on Apple iTunes Store by using several rounds of inter-rater reliability statistics, locating categorization problems based on Machine Learning, and making more accurate suggestions about representative functionality stems for each primary category. A mixed methods research was performed and total 4905 popular apps were observed. The original categorization was proved to be substantial reliable but need further improvement. The representative functionality stems for each category were identified. This paper may provide some fusion research experience and methodological suggestions in categorization research field and improve app store's categorization in discoverability.

• Korea Journal of Hospital Management
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• v.26 no.1
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• pp.1-16
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• 2021

Purpose: The purpose of the study is to identify the influence of the hospital mobile app service quality on consumer satisfaction, involvement, and re-use intention of consumers who have experience in hospital mobile app service. Methodology: The survey was conducted on 230 users. The collected data were analyzed using correlation analysis, multiple regression analysis, and the Process Model in Hayes(2013). Findings: (1)The usability, reliability, and medical information provision among the service quality factors of hospital mobile apps had an effect on reuse intention, and consumer satisfaction partially mediated. (2)The usability and the provision of medical information were partially mediated by the involvement, which also affected the intention to reuse. (3)Only reliability showed an age-moderated effect. In reliability and re-use intent, age was a moderated mediating effect that controlled the effect of consumer satisfaction. Practical Implications: The results of this study provide initial data of mobile app services centered on hospitals and prove the type of consumer usage. It suggests that it can be used to attract potential consumers of hospitals and strategies to increase the use of mobile apps.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.487-500
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• 2022

This study aims to examine visitors' usage intention of the mobile AR(Augmented reality) application for tourism in Korea. For this purpose, the study analyzed how three attributes of AR tourguide app such as interactivity, vividness, and novelty have influenced on the tourist in terms of three realms of their flow, their experience (education, entertainment, esthetics, and escapism), and their usage intention for the future. It conducted an online survey from 20 to 30 year-old 291 participants and used a structural equation modeling. Survey findings show that first, novelty has a positive influence on the state of flow in AR application after vividness; Interactivity does not any significant effect on the tourists' flow. Second, when tourists explore the flow in the AR tourguide app, it affects all realms of experience economy of education, entertainment, esthetics, and escapism. Third, when using AR tour guide app in the context of historical heritage site, the two dimensions of entertainment and education influence the usage intention but the other two of esthetics and escapism does not. This study has presented a theoretical contribution that it focuses on historical sites as one type of tourist attractions and suggests a new modeling integrating AR attributes, flow, experience, and usage intention. In addition, it can be used to become a practical reference for revising an user-oriented AR application and customer-tailored AR tourism.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.399-410
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• 2018

In Android smartphones, many apps are developed as service apps to run in the background. If the memory is insufficient, Android forcibly terminates not only user apps that have not used the CPU for a long time, but also service apps. However, a service app is automatically re-launched after a short period of time, so that it continuously consumes memory space. This paper analyzes the number of running service apps and their memory usage in users' smartphones. The number of service apps accounts for up to 65% of the total number of running apps, and their memory usage accounts for up to 55% of the total memory. Moreover, we investigate the effect of the number of running service apps on the response time of smartphones and apps. As the number of service apps increases, the launching time of user apps increases to 22 times. The booting time and app installation time significantly increase with the number of service apps.

• Smart Media Journal
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• v.12 no.6
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• pp.27-34
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• 2023

As Netflix usage has increased due to the COVID-19 pandemic, users' experiences with the service have also increased. Therefore, this study aims to conduct topic modeling analysis based on Netflix review data to explore the changes in Netflix user experience and service before and after the COVID-19 pandemic. We collected Netflix app review data from the Google Play Store using the Google Play Scraper library, and used topic modeling to examine keyword differences between app reviews before and after the pandemic. The analysis revealed four main topics: Netflix app features, Netflix content, Netflix service usage, and Netflix overall reviews. After the pandemic, when user experience increased, users tended to use more diverse and detailed keywords in their reviews. By using Netflix review data to analyze users' opinions, this study shows the changes in user experience of Netflix services before and after the pandemic, which can be used as a guide to strengthen competitiveness in the competitive OTT market.

• Convergence Security Journal
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• v.12 no.4
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• pp.9-15
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• 2012

In recently years, repackaged malwares are becoming increased rapidly in Android smartphones. The repackaging is a technique to disassemble an app in a market, modify its source code, and then re-assemble the code, so that it is commonly used to make malwares by inserting malicious code in an app. However, it is impossible to collect all the apps in many android markets including too many apps. To solve the problem, we propose RePAD (RePackaged App Detector) scheme that is composed of a client and a remote server. In the smartphone-side, the client extracts the information of an app with low CPU overhead when a user installs the app. The remote server analyzes the information to decide whether the app is repackaged or not. Thus, the scheme reduces the time and cost to decide whether apps are repackaged. For the experiments, the client and server are implemented as an app on Galaxy TAB and PC respectively. We indicated that seven pairs of apps among ones collected in official and unofficial market are repackaged. Furthermore, RePAD only increases the average of CPU overhead of 1.9% and the maximum memory usage of 3.5 MB in Galaxy TAB.

• Journal of Korean Association for Spatial Structures
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• v.17 no.1
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• pp.93-100
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• 2017

With increasing number construction of high-rise building which has about 40 to 60 floors there have been many kinds of problem which related with usage from vibration. To predict response acceleration, it is important to assess correct natural frequency. However, due to the noise of MEMS sensor, it is difficult to measure dynamic characteristic such as natural frequency when measuring ambient vibration using MEMS sensor within cell phone. Therefore, a comparative analysis on vibration measuring applications was performed after measuring ambient vibration of 2 skyscrappers which have height between 133.5~244.3m that are located in Seoul and Observation tower using I-jishin APP with noise reduction function of MEMS sensor in order to verify the effectiveness of low noise type vibration measurement APP.

• Convergence Security Journal
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• v.14 no.2
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• pp.3-9
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• 2014

As the subscribers of the digital cable and IPTV broadcasting are increasing, the VOD service has established a solid foothold as a profit model of the broadcasting industries. And what's more, the VOD service is emerging as a key application of the N-screen technologies. In the circumstance, broadcasting companies are trying to provide mobile services to improve the satisfaction of their VOD services usage. The paper introduces a VOD mobile app (of a domestic digital cable broadcasting), which includes the functions of promoting the VOD programs printed on a VOD guide book, directly transmitting the information (e.g., book-marking, remote-control signals) generated by the VOD mobile app to a set-top box, and watching the video contents stored in the mobile device on TV.

• Journal of Multimedia Information System
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• v.9 no.3
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• pp.201-208
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• 2022

Customized service is a vital and mandatory element for apps in improving their technical performance and app customer analysis. While apps require users' consent for their data extraction and usage, many of the terms and agreement forms are written intricately, making it harder for users to fully understand the whole concept of users' data collection for customized services. Ever since the Facebook-Cambridge Analytica scandal, personal data privacy has been re-examined, forcing many app companies to reinforce a reliable solution to data privacy issues. However, there has not been a secured solution, which worries many people about the future advanced issues when metaverse platforms are actively used in daily apps. The research aims to collect the reactions and behaviors of everyday app users who utilize apps with customized services to understand the nature of privacy data issues and the users' opinions about the future implementation of metaverse platforms. The method of the research was an online questionnaire that targeted university students. The study revealed many fearful and anxious reactions about personal data and further metaverse issues where most app users were uneducated about how current apps collect and utilize users' private data.