• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.415-436
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• 2022

This study was conducted by the customer survey of 15 to 65 years old in order to identify the user behavioral effects of perception and characteristics on the common essential applications of smartphones with the United Theory of Acceptance and Use of Technology (UTAUT) and Value-based Acceptance Model (VAM). As a result, it was found that performance expectancy, enjoyment, facilitating conditions, effort expectancy, and social influences, excluding information privacy concern, have a positive effect on use behavior. The moderating effect by age was found that the youth was higher between perceived value and behavioral intention, and the middle-aged was higher between enjoyment and perceived value. This study has significance in providing implications for establishing strategies on designing and pre-loading apps, and increasing usage rate.

• Journal of the Korean School Mathematics Society
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• v.25 no.2
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• pp.195-224
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• 2022

In this study, pre-service mathematics teachers cultivated technology content teaching knowledge (TPACK) in the regular curriculum of the College of Education. The course was designed to enhance pre-service teachers' mathematical communication skills by using an application, which is a mobile mathematics learning content for the development of group creativity of high school students. The educational program to improve mathematics teaching expertise using the application for group creativity expression consists of pre-education, goal setting, planning, teaching at school, and evaluation. In this process, pre-service teachers evaluated technology tools. They also wrote a task dialogue, lesson play, reflective journal, and lesson plan to guide high school students to develop group creativity in both app activities. As a result of the educational program, pre-service mathematics teachers cultivated TPACK and enhanced their mathematical communication skills with high school students to develop group creativity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1696-1707
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• 2021

With the recent growth of information technology, various literacy such as digital literacy, data literacy, AI literacy is being studied. In this paper, we focus on data visualization literacy as visualization is an essential part of big data analysis and is used in several mobile apps. Visualization Literacy Assessment Test(VLAT) was developed in 2016 and we introduce how the test was developed and modified to a Korean version, K-VLAT. K-VLAT is consisted of 12 visualizations and 53 questions through a website. Additionally, to understand the research trend in visualization literacy we analyzed 81 papers that had cited the VLAT publication. We categorized the research into 4 categories with 11 sub-categories. The area of studies visualization literacy related to was understanding the relation with cognition, expanding the literacy measures, relation with education, utilization for developing user-centric dashboards or using the test to show effectiveness of visualizations. At last, we discuss about different ways to utilize K-VLAT for future research.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.61-66
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• 2023

As the use of smartphones expands to various areas and the level of multitasking increases, the support of swap is becoming increasingly important. However, swap support in smartphones is known to cause excessive storage traffic, resulting in memory thrashing. In this paper, we analyze how the thrashing of swaps that occurred in early smartphones has changed with the advancement of smartphone hardware. As a result of this analysis, we show that the swap thrashing problem can be resolved to some extent when the memory size increases. However, we also show that thrashing still occurs when the number of running apps continues to increase. Based on further analysis, we observe that this thrashing is caused by some hot data and suggest a way to solve this through an NVM-based architecture. Specifically, we show that a small size NVM with judicious management can resolve the performance degradation caused by smartphone swap.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.157-167
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• 2023

The use of big data for transportation often involves using data that includes personal information, such as the driver's driving routes and coordinates. This study explores the creation of a route choice prediction model using a large dataset from mobile navigation apps using federated learning. This privacy-focused method used distributed computing and individual device usage. This study established preprocessing and analysis methods for driver data that can be used in route choice modeling and compared the performance and characteristics of widely used learning methods with federated learning methods. The performance of the model through federated learning did not show significantly superior results compared to previous models, but there was no substantial difference in the prediction accuracy. In conclusion, federated learning-based prediction models can be utilized appropriately in areas sensitive to privacy without requiring relatively high predictive accuracy, such as a driver's preferred route choice.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.644-656
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• 2014

In recent years, a series of large-scale disastrous accidents have been occurred frequently both in public and private sector. Such disasters become catastrophe due to poor early response and delayed prompt rescue. Damage from catastrophe could have been drastically reduced or minimized with effective response and recovery management. The smart phone-based mobile applications have important potentials in providing solutions for the effective response and recovery management. Mobile applications can greatly improve risk communication in case of disasters by integrating process of exchange information and data on risk among risk evaluators, risk managers, and other interested parties. In this light of potentials, this study investigates the measures and management to better manage early responses and to effectively deal with domestic disaster-related of the status of public applications service, and utilization. This study examines how disaster applications can be better used and how effective information dissemination through applications could help the post-disaster management process. Based on this findings, it proposes a guideline of effective disaster-related applications by public sector for the future development of actual services and activation solutions. The results show that "User Promptness Side" and "Content Believability Side" factors found to be the two most significant factors in the disaster-related applications by public sector. Discussion and implications are discussed.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.189-196
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• 2022

Skyline query is a scheme for exploring objects that are suitable for user preferences based on multiple attributes of objects. Existing skyline queries return search results as batch processing, but the need for real-time search results has increased with the advent of interactive apps or mobile environments. Online algorithm for Skyline improves the return speed of objects to explore preferred objects in real time. However, the object navigation process requires unnecessary navigation time due to repeated comparative operations. This paper proposes a Pre-processing Online Algorithm for Skyline Query (POA) to eliminate unnecessary search time in Online Algorithm exploration techniques and provide the results of skyline queries in real time. Proposed techniques use the concept of range-limiting to existing Online Algorithm to perform pretreatment and then eliminate repetitive rediscovering regions first. POAs showed improvement in standard distributions, bias distributions, positive correlations, and negative correlations of discrete data sets compared to Online Algorithm. The POAs used in this paper improve navigation performance by minimizing comparison targets for Online Algorithm, which will be a new criterion for rapid service to users in the face of increasing use of mobile devices.

• Information Systems Review
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• v.24 no.2
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• pp.41-66
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• 2022

With the development of IT, mobile apps and the expansion of contactless services due to COVID-19, "smart orders" have recently been activated in the food and beverage service. Even in recent years, when sales have declined, the number of orders made by smart orders has been steadily increasing, and this ordering method can accumulate customer data, enabling effective customized services in the future. In the present study, satisfaction with smart orders and continuous use intention were studied based on the technology acceptance model (TAM). And it focused on whether there is a difference in personality when using smart orders. For this purpose, a survey was conducted on 317 smart order users, and the hypothesis was verified by structural equation model analysis. Perceived benefits had a significant effect on satisfaction; also, satisfaction had a significant effect on continuous use intention. There is a significant disparity between introvert and extrovert type. As a consequence, the introverted type has a greater intention to perceive usefulness of smart orders and continuously use them. These results suggest that the customer's personality type should be considered in future customer customization strategies.

• Journal of Korean Library and Information Science Society
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• v.51 no.2
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• pp.355-379
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• 2020

Digital Library System(DLS) for the school library is a key access tool for school library materials. The purpose of this study was to find ways to improve the accessibility of materials through analysis of students' information search behavior in DLS. Data were collected through recording of 42 participants' DLS search process, and questionnaire. As a result, the search success rate and search satisfaction were found to be lower when the main purpose of DLS is simple leisure reading, information needs are relatively ambiguous, and when user experiences the complicated situations in the search process. The satisfaction level of search time sufficiency was the highest, and the search result satisfaction was the lowest. Besides, there was a need to improve DLS, such as integrated search of other library collection information, the recommendation of related materials, the print output of collection location, voice recognition through mobile apps, and automatic correction of search errors. Through this, the following can be suggested. First, DLS should complement the function of providing career information by reflecting the demand of education consumers. Second, improvements to DLS functionality to the general information retrieval system level must be made. Third, an infrastructure must be established for close cooperation between school library field personnel and DLS management authorities.

• Knowledge Management Research
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• v.22 no.3
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• pp.253-271
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• 2021

Due to the spread of COVID-19, the use of O2O order·delivery applications are becoming very common. Unlike the past, where customers could choose the desired transaction method and channel, these days, where customers' choices are very limited, it is urgent to consider the concept of shadow labor which has been hindered by the convenience and the benefits of order·delivery app. To this end, in this study, the service quality factors perceived by users of O2O order·delivery app and their shadow work attributes were identified, and priorities according to their relative importance and satisfaction level were suggested. In order to fulfill research objectives, first, after collecting user reviews for an O2O order·delivery app, the subject words were derived using topic modeling. Research variables were selected by linking 11 keywords with the concepts of previous studies on service quality of mobile apps and those about shadow labor. Eight variables of usefulness, ease of use, stability, design quality, personalization, responsiveness, update, and presence were selected. Based on 32 measurement items from the variables, a revised IPA was conducted, and finally, 'keep', 'concentrate', 'low priority', or 'overkill' service quality factors are revealed.