• Journal of Korea Society of Industrial Information Systems
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• v.16 no.3
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• pp.35-45
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• 2011

Due to people's internet use growth and proliferation of ubiquitous technology, the internet addiction is becoming a social issue. However, the current adults' self-diagnosis measure about internet addiction, the K-scale, is a normal diagnostic method, which it does not consider user characteristics. In this research, we will propose a new internet addiction diagnostic method based on users' non-duty internet activities by using some questionnaire items to collect users' basic internet patterns used on duty related or non-duty related web sites. Since we simply ask for the basic internet usage pattern to each user who does not like to check frankly questionnaire items in the K-scale, the proposed method can find some hidden internet addicts compared to the K-scale with the SPSS statistical analysis tool.

• Journal of Korea Game Society
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• v.19 no.4
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• pp.27-36
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• 2019

Approaches to find hidden values using various and enormous amount of data are on the rise. As big data processing becomes easier, companies directly collects data generated from users and analyzes as necessary to produce insights. User-based data are utilized to predict patterns of gameplay, in-game symptom, eventually enhancing gaming. Accordingly, in this study, we tried to analyze the gaming strategy and user activity patterns utilizing Battlegrounds in-game data to detect the in-game hack.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.346-348
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• 2022

Media Contents Recommendation Web Service (service name 'mobodra') is a web service that analyzes media types and genre tastes for each user and recommends content accordingly. Users select some of the works randomly provided on the web when signing up for membership and analyze their tastes based on this. Based on this analysis, preferred content for each user is recommended. In this paper, we implement a content recommendation algorithm through item-based collaborative filtering. When the user's activity data or preference is re-examined, the above process is executed again to update the user's taste.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.117-140
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• 2019

As the aging phenomenon accelerates and various social problems related to the elderly of the vulnerable are raised, the need for effective elderly care solutions to protect the health and safety of the elderly generation is growing. Recently, more and more people are using Smart Toys equipped with ICT technology for care for elderly. In particular, log data collected through smart toys is highly valuable to be used as a quantitative and objective indicator in areas such as policy-making and service planning. However, research related to smart toys is limited, such as the development of smart toys and the validation of smart toy effectiveness. In other words, there is a dearth of research to derive insights based on log data collected through smart toys and to use them for decision making. This study will analyze log data collected from smart toy and derive effective insights to improve the quality of life for elderly users. Specifically, the user profiling-based analysis and elicitation of a change in quality of life mechanism based on behavior were performed. First, in the user profiling analysis, two important dimensions of classifying the type of elderly group from five factors of elderly user's living management were derived: 'Routine Activities' and 'Work-out Activities'. Based on the dimensions derived, a hierarchical cluster analysis and K-Means clustering were performed to classify the entire elderly user into three groups. Through a profiling analysis, the demographic characteristics of each group of elderlies and the behavior of using smart toy were identified. Second, stepwise regression was performed in eliciting the mechanism of change in quality of life. The effects of interaction, content usage, and indoor activity have been identified on the improvement of depression and lifestyle for the elderly. In addition, it identified the role of user performance evaluation and satisfaction with smart toy as a parameter that mediated the relationship between usage behavior and quality of life change. Specific mechanisms are as follows. First, the interaction between smart toy and elderly was found to have an effect of improving the depression by mediating attitudes to smart toy. The 'Satisfaction toward Smart Toy,' a variable that affects the improvement of the elderly's depression, changes how users evaluate smart toy performance. At this time, it has been identified that it is the interaction with smart toy that has a positive effect on smart toy These results can be interpreted as an elderly with a desire to meet emotional stability interact actively with smart toy, and a positive assessment of smart toy, greatly appreciating the effectiveness of smart toy. Second, the content usage has been confirmed to have a direct effect on improving lifestyle without going through other variables. Elderly who use a lot of the content provided by smart toy have improved their lifestyle. However, this effect has occurred regardless of the attitude the user has toward smart toy. Third, log data show that a high degree of indoor activity improves both the lifestyle and depression of the elderly. The more indoor activity, the better the lifestyle of the elderly, and these effects occur regardless of the user's attitude toward smart toy. In addition, elderly with a high degree of indoor activity are satisfied with smart toys, which cause improvement in the elderly's depression. However, it can be interpreted that elderly who prefer outdoor activities than indoor activities, or those who are less active due to health problems, are hard to satisfied with smart toys, and are not able to get the effects of improving depression. In summary, based on the activities of the elderly, three groups of elderly were identified and the important characteristics of each type were identified. In addition, this study sought to identify the mechanism by which the behavior of the elderly on smart toy affects the lives of the actual elderly, and to derive user needs and insights.

• Journal of Environmental Impact Assessment
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• v.24 no.3
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• pp.217-232
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• 2015

This study is to examine the section-based stream management with environmental characteristics and user monitoring. In Jeonjucheon, upstream section located near to Jeonju Hanok village has very good water quality and natural stream landscape. In case of mid/down streams, water quality is good and heavy concentration of facility leads to high use rates of these sections. The questionnaire consists of 5 parts: user characteristics, use behavior, citizen participation, importance rank, and Importance-Satisfaction(IS). 383 out of 454 responses with listwise deletion are used for demographic analysis and IS Analysis. In terms of citizen participation through 'ecological experience activity' and 'stream stewardship activity', 'occasional participation' shows the average of 78% in all three sections. For importance rank, the results arranged in order of priority show 'water quality' > 'green corridor' > 'trail' in up/down streams and 'water quality' > 'vegetation management' > 'trail' in midstream. Therefore, 'water quality' appears to be the most important variable among 13 variables. At last, the results of ISA indicate that all 10 variables need to be improved as satisfaction is lower than importance. In addition, 'plant management' variable falls into 'concentrate here' quadrant where importance is high and satisfaction is low.

• Knowledge Management Research
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• v.15 no.2
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• pp.23-41
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• 2014

Firms increasingly utilize Social Networking Service(SNS) to lead user's voluntary behavior. In the web-based environment, users show coexist loyal behavior which is represented by 'web-based pro-organization citizenship behavior' and 'anti-citizenship behavior'. To measure genuine performance of web-activity, we separated degree of compliance based on credibility, 'deep-level' and 'surface-level' to comprehend different behavior after compliance. The analysis result shows that contents credibility is important to enhance deep-level of compliance which has significant influence on web-based pro-organization citizenship behavior. Contrastively, surface-level of compliance has influence on anti-citizenship behavior. Based on the results of these analyses, the directions of web-based activities for the common good and self-interests of the stakeholders of the web-based activities will be proposed.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.189-199
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• 2009

The amount of information on the Web is explosively growing as the Internet gains in popularity. However, only a small portion of the information on the Web is truly relevant or useful to the user. Thus, offering suitable information according to user demand is an important subject in information retrieval. In e-commerce, the recommender system is essential to revitalize commercial transactions, raise user satisfaction and loyalty towards the information provider. The existing recommender systems are mostly based on user data collected at servers, so user data are dispersed over several servers. Therefore, web servers that lack sufficient user behavior data cannot easily infer user preferences. Also, if the user visits the server infrequently, it may be hard to reflect the dynamically changing user's interest. This paper proposes a novel personalization system analyzing the user preference based on web documents that are accessed by the user on a user device. The system also identifies non-content blocks appearing repeatedly in the dynamically generated web documents, and adds weight to the keywords extracted from the hyperlink sentence selected by the user. Therefore, the system establishes at an early stage recommendation strategies for the web server that has little user data. Also, user profiles are generated rapidly and more accurately by identifying the information blocks. In order to evaluate the proposed system, this study collected web data and purchase history from users who have current purchase activity. Then, we computed the similarity between purchase data and the user profile. We confirm the accuracy of the generated user profile since the web page containing the purchased item has higher correlation than other item pages.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.4
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• pp.338-345
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• 2004

Personal Digital Assistants (PDAs) have become ubiquitous and continued to gain popularity. Since PDAs have some special contexts such as mobility and limited screen size, icons are utilized frequently because icons allow us to do tasks more rapidly and effectively on PDAs like another information appliances. The study presents a cognitive approach to study human factors affecting icon design with multidimensional Scaling (MDS) analysis. In the experiment, a real PDA was used to investigate 29 attributes and2 preference ratings for 22 PDA icons by 20 Korean subjects. As a result, cognitive positioning about icons, attributes, and preference data were arranged on the two dimensional perceptual map. Attributes were grouped by simplicity, universality, activity, complexity, abstraction, static, and alphanumeric time. Subjects preferences were highly related with simplicity attributes group and positive to universality and activity attributes groups. It was also confirmed that there are some icons unfitted to the mental model of Korean. However, when icons are designed for PDAs or similar information appliances to Korean, it should be designed simply and actively with universal image fitted on target users mental model.

• Architectural research
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• v.19 no.1
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• pp.7-11
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• 2017

Energy consumption in university building has steadily increased over the last decade, and a strong upward trend in recent years. This study was undertaken to analyze the relationship between energy consumption and their affecting factors, six academic buildings were considered. The factors limited to heating and cooling, which is the main end use (nearly 60 per cent of total energy consumption in university buildings), encompassing system and operating schedules (user activity) and area use. To understand how to building is used, operated and managed, walk-through assessment was conducted as well as interview with university staff. The results show that the energy consumption of the humanities building was somewhat smaller than the consumption of the science and engineering building, and its range was from $31.26kgoe/m^2$ to $23.52kgoe/m^2$, depending on heating and cooling system and area use. And the energy consumption of the science and engineering building was related to operating schedules (user activity) as well as laboratory equipment characteristics. More analysis on a larger number of buildings is required in the future, including building form and material performance level to generalize the significant factors influencing building energy consumption.

• Journal of Biomedical Engineering Research
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• v.19 no.3
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• pp.261-268
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• 1998

Electrogastrography(EGG), the cutaneous recording of the myoelectrical activity of the stomach using surface electrodes, is a non-invasive technique to detect gastric motility disorder, We developed a detection and analysis system for the EGG signal, which consists of hardware(bio-amplifier, filter) and softwere(user interface, analysis algorithm, patient database). The EGG signal was amplified and filtered by 3 channel bio-amplifiers, and simultaneously digitized and stored on IBM PC with a sampling frequency of 16 Hz. The stored EGG signal was analyzed using developed algorithm to extract clinically useful information from the signal. The developed system has tested through animal experiments, and is under clinical evaluation.