• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.25-40
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• 2022

This study is about how the quality of M2M big data that provides real-time information affects users. Recently, there are many difficulties in acquiring and managing data because data types such as variety, data volume, and data velocity are changing rapidly and diversified. This not only leads to a decrease in data quality but also it can give a negative impact when making decisions using data. Generally, the quality of data is defined as 'suitability for use', which means that data quality must meet the expectations of user needs. Therefore, data providers need activities to improve data quality for this purpose, and the key is to identify data quality dimensions in each field where data is used and provide data suitable for the level of user needs. In this study, the relationship between the quality area of real-time M2M data used in the traffic information system and user satisfaction was analyzed. Research models and hypotheses were established to analyze the effects between variables related to M2M big data. In order to test the hypothesis, a causal relationship between the major factors was identified by conducting a survey and analyzing the data users.

• The Korean Journal of Archival Studies
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• no.75
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• pp.177-212
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• 2023

Private archives are an important indicator of understanding a society that contains various memories, the lives and experiences of members, daily lives, morality, and values. Recently, as diversity has emerged as an important value in Korean society, a number of individuals and communities have been appeared based on different bases and purposes, and the contents, types, and categories of private archives produced from their voluntary activities have also diversified. These private organizations and communities are potential targets for producing and holding private archives, but most of them do not have the minimum infrastructure or system for management of archives, and the foundation for management of archives is weak only to be supported with the voluntary will and activities of the private sector. Therefore, there is a need for a plan to support activities to manage archives suitable for each organization's level while respecting the unique characteristics and methods of the private sector within the national management system of archives. In addition, since it is difficult to solve all issues related to management of archives in the private sector with only a small number of process topics, a cooperative system should be established to sustain activities to manage archives on its own through networks between private sectors. In this study, we intend to propose a 'private archives information network platform (hereinafter referred to as a platform)' as a way to establish a communication and network foundation between private sectors and share resources with each other. Based on the results of analysis of cases of building network between private sectors and expected user requirements, we would like to establish a vision and target model of the platform and discuss ways to continuously operate the platform.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.43-53
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• 2023

In this detailed and comprehensive study, our primary focus has been placed on accurately gauging the number of visitors and their real-time locations in commercial spaces. Particularly, in a real cafe, using security cameras, we have developed a system that can offer live updates on available seating and predict future congestion levels. By employing YOLO, a real-time object detection and tracking algorithm, the number of visitors and their respective locations in real-time are also monitored. This information is then used to update a cafe's indoor map, thereby enabling users to easily identify available seating. Moreover, we developed a model that predicts the congestion of a cafe in real time. The sophisticated model, designed to learn visitor count and movement patterns over diverse time intervals, is based on Long Short Term Memory (LSTM) to address the vanishing gradient problem and Sequence-to-Sequence (Seq2Seq) for processing data with temporal relationships. This innovative system has the potential to significantly improve cafe management efficiency and customer satisfaction by delivering reliable predictions of cafe congestion to all users. Our groundbreaking research not only demonstrates the effectiveness and utility of indoor location tracking technology implemented through security cameras but also proposes potential applications in other commercial spaces.

• Journal of the Korean Society for information Management
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• v.39 no.4
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• pp.23-48
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• 2022

The purpose of this study is to investigate the flow of domestic information literacy education research using keyword network analysis and topic modeling and to explore the direction of information literacy education in the future. For this reason, 306 academic papers related to information literacy education published in academic journals of the library and information science field in Korea were chosen. And through the preprocessing process for abstracts of the paper, total keyword appearance frequency, keyword appearance frequency by period, and keyword simultaneous occurrence frequency were analyzed. Subsequently, keyword network analysis analyzed the degree centrality, between centrality, and eigenvector centrality of keywords. Using structural topic modeling analysis, 15 topics -curriculum, information literacy effect, contents of information literacy education, school library education, information media literacy, information literacy ability evaluation index, library anxiety, public library program, health information literacy ability, digital divide, library assisted instruction improvement, research trend, information literacy model, and teacher role-were derived. In addition, the trend of topics by year was analyzed to confirm the change in relative weight by topic. Based on these results, the direction of information literacy education and the suggestions for follow-up research were presented.

• Knowledge Management Research
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• v.23 no.4
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• pp.275-294
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• 2022

In recent years, with the continuous integrative development of e-commerce and social media, social commerce, as a trust-centered social transaction mode, has become an important performance form of e-commerce. The good experience of online community and abundant user-generated content (UGC) attract more and more users and businesses to participate in the community contribution. In this context, the cost of accessing information is continuously decreasing, which not only makes the purchase process more concise and efficient, but also greatly increases the possibility of consumers' impulsive consumption. However, there are very few empirical studies on the internal influencing mechanism of consumers' impulsive consumption based on the characteristics of UGC for social commerce. In view of this, based on S-O-R model, this study constructs a model of consumers' impulsive consumption in the context of social commerce from the characteristics of UGC, with perceived risk as the mediating variable and tie strength as the moderating variable. The results show that content authenticity, content usefulness, and content valence of UGC have significant negative impacts on consumers' risk perception in the process of purchase decision-making, and consumers' perceived risk has a significant negative impact on consumers' impulsive consumption. Meanwhile, the tie strength between UGC producer and UGC receiver plays a moderating role between content usefulness and perceived risk, as well as between perceived risk and impulsive consumption. Finally, combined with the above findings, this study provides effective suggestions for relevant participants in social commerce in terms of business management.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.3
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• pp.353-362
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• 2023

In this research, the usage status and characteristics of user big data of Mobike, a dockless bike sharing service introduced in Suwon city, were analyzed, and multiple regression analysis was performed to identify factors influencing the demand for dockless bike sharing service. For analysis, usage data of bike sharing system in Suwon city in 2019 were obtained, and they were organized by areas. As a result of analyzing the characteristics of the influencing factors selected for each area, it was found that the extension of bicycle roads shows high in areas with high demand for bicycles or adjacent areas. Also, the population of 10-30's shows high in areas with high demand for bicycles or adjacent areas. In addition, it was analyzed that the use of bike sharing system is high in areas with high maintenance rate of bicycle roads and large-scale residential and commercial facilities near residential districts and adjacent areas. As a result of the multiple regression analysis, it is analyzed that length of bicycle·pedestrian roads (non-separated), population of 10-30's, number of railway stations, number of schools, number of commercial facilities, number of industrial facilities factors were significant. It is expected that it may be possible to create an environment in which citizens want to use dockless bike sharing service by identifying factors affecting the number of stationless shared bicycles. Also, the results of data analysis are considered to be contributing to policy data to promote the use of dockless bike sharing.

• 한국체육학회지인문사회과학편
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• v.55 no.3
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• pp.349-363
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• 2016

The purpose of this study was to perceived interactivity about experience of using dance video contents and intention to use. This study was examine an adaptive model of Technology Acceptance Model and focused on YouTube. In order to achieve the purpose of this study, total 350 questionnaires were surveyed and 311 data were finally analyzed. All data were processed through SPSS for Windows 20.0 version and AMOS 18.0. For the analysis of data, frequency analysis, reliability analysis, confirmatory factor analysis, correlation analysis, model evaluation, and structural equation modeling techniques. The results were as follows. first. Perceived Interactivity had not affect on perceived usefulness but two-way communication, user control among the sub-factor in perceived Interactivity had a positive effect on perceived ease of use. second, perceived ease of use had a positive effect on perceived usefulness. Lastly, Perceived usefulness had not affect intention to use, but perceived ease of use had a positive effect on intention use.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.166-178
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• 2023

This study aims to introduce and assess CNN Deep Learning methods to analyze visual landscape images on social media with embedded user perceptions and experiences. This study analyzed visual landscape images by focusing on a healing place. For the study, seven adjectives related to healing were selected through text mining and consideration of previous studies. Subsequently, 50 evaluators were recruited to build a Deep Learning image. Evaluators were asked to collect three images most suitable for 'healing', 'healing landscape', and 'healing place' on portal sites. The collected images were refined and a data augmentation process was applied to build a CNN model. After that, 15,097 images of 'healing' and 'healing landscape' on portal sites were collected and classified to analyze the visual landscape of a healing place. As a result of the study, 'quiet' was the highest in the category except 'other' and 'indoor' with 2,093 (22%), followed by 'open', 'joyful', 'comfortable', 'clean', 'natural', and 'beautiful'. It was found through research that CNN Deep Learning is an analysis method that can derive results from visual landscape image analysis. It also suggested that it is one way to supplement the existing visual landscape analysis method, and suggests in-depth and diverse visual landscape analysis in the future by establishing a landscape image learning dataset.

• 한국노년학
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• v.30 no.4
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• pp.1179-1195
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• 2010

In this study, we investigated the effects of ego integrity on QoL(Quality of Life) of elderly living alone, where we focused on moderating role of SF36 health factors. To investigate the cause and effect of factors, we purposively collected 282 samples from senior welfare centers in Jeonju city and exploited reliability analysis, confirmatory factor analysis and SEM(Structural Equation Modeling) for 265 cases excluding some cases with missing values. As the results, first, we confirmed ego integrity was positive predictor of QoL. Second, it was proven that the effect of ego integrity on QoL of elderly living alone was stronger in the lower physical functioning group than higher physical functioning group. Third, we also verified that the group with more difficulties in activities or work as a result of poor physical health showed higher effect of ego integrity on QoL. Based on the results, we could explain the reason of conflicts regarding how elderly's health influenced on ego integrity. Also, in the practice of intervention to elderly's problem, we found the health factors could be an indicator of direction or effect of the intervention

• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.1-31
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• 2023

This study conducted user experience evaluation by introducing various text mining techniques along with topic modeling techniques for mobile menstrual cycle measurement applications that are closely related to women's health and analyzed the results by combining them with a honeycomb model. To evaluate the user experience revealed in the menstrual cycle measurement application review, 47,117 Korean reviews of the menstrual cycle measurement application were collected. Topic modeling analysis was conducted to confirm the overall discourse on the user experience revealed in the review, and text network analysis was conducted to confirm the specific experience of each topic. In addition, sentimental analysis was conducted to understand the emotional experience of users. Based on this, the development strategy of the menstrual cycle measurement application was presented in terms of accuracy, design, monitoring, data management, and user management. As a result of the study, it was confirmed that the accuracy and monitoring function of the menstrual cycle measurement of the application should be improved, and it was observed that various design attempts were required. In addition, the necessity of supplementing personal information and the user's biometric data management method was also confirmed. By exploring the user experience (UX) of the menstrual cycle measurement application in-depth, this study revealed various factors experienced by users and suggested practical improvements to provide a better experience. It is also significant in that it presents a methodology by combines topic modeling and text network analysis techniques so that researchers can closely grasp vast amounts of review data in the process of evaluating user experiences.