• Journal of Distribution Science
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• v.20 no.11
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• pp.99-108
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• 2022

Purpose: The wide distribution of smartphones has changed life and user behavior. This phenomenon has both advantages and disadvantages for users. As smartphones become a part of our daily lives, smartphone addiction has recently become a social issue in many countries. This study explores factors that affect smartphone addiction and the consequences of addictive behaviors. Research design, data and methodology: Our model hypothesizes that four key factors determine addictive behavior: flow, enjoyment, preference for online social life, and escape reality. Commitment and compulsive use are mediating variables that connect key drivers and addictive results. Based on the SEM (structural equation model) analysis of 497 survey responses, these four driving factors each have a significant effect on the compulsive use of smartphones directly or indirectly; the compulsive use of smartphones directly influences the three results Results: We conducted a reliability and validity analysis, and the results were successful. In the hypothesis test, every path is accepted as expected at the significance level of 0.05. Conclusions: Among the four driving factors, escape reality is the vital factor influencing smartphone addiction and its consequences. And anxiety is the number one consequence influenced by the compulsive use of smartphones.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.25 no.1
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• pp.19-37
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• 2014

Server transaction logs containing complete click-through data from a digital library of primarily image-based documents were analyzed to better understand user search session behavior. One month of data was analyzed using descriptive statistics and network analysis methods. The findings reveal iterative search behaviors centered on result views and evaluation and topical areas of focus for the search sessions. The study is novel in its combined analytical techniques and use of click-through data for image collections.

• Management & Information Systems Review
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• v.32 no.3
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• pp.173-188
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• 2013

I guess that e-learning buying behaviors have some selection criteria which are interactivity, contents quality, perceived usefulness, and corporate reputation. And I propose that the effects of selection criteria on adaptation intention are moderated by buyer-user status. To accomplish research purpose, I conducted a field survey with a self-administered questionnaire in both user-buyer and analysed the causal relations among the variables by regression analysis. Findings are these. In all of the customer, interactivity, perceived usefulness, and corporate reputation had positive effects on re-attending intention to another e-learning class. In case of users(students), interactivity, contents quality, and perceived usefulness had positive effects, but buyer(parents) showed both perceived usefulness and corporate reputation had positive effects on re-attending intention.

• Journal of Korean Academy of Nursing
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• v.29 no.5
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• pp.1134-1146
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• 1999

The purpose of this study was to examine the correlation between Juvenile alcohol use and their criminal patterns. The data were collected through questionnaire surveys. Subjects serving for this study were 971 delinquent adolescents in Korea, sampled from 6 juvenile corrective institutions and 2 classification judging institutions, using a census method. Their age range was between 12 and 21. Data were analysed by IBM PC using SAS program. Statistical methods employed were Chi-square and frequency analysis. 1. Of 877 respondents, the number of adolescents committed criminal behaviors while the intoxicated were 230(26.2%), and 647(73.8%) were in a non-intoxicated state. 2. Adolescent under intoxication showed a higher rate of aggressive crimes and assault crimes, whereas adolescents under the non-influence of liquor tended to commit property climes and violations of criminal special law Drunken state adolescents during committing criminal behaviors used knifes, stones or fist-kicking as criminal tools, whereas drug use or without weapons in non drunken state. Most crimes have happened without any tools in both group. 3. In comparison of the alcohol user and the non-user, most alcohol-related crimes among adolescents were committed at AM 0:00 to AM 4:00 during the weekend in the dark, cloudy, and stormy-rainy day, while non-alcohol related crimes were at afternoon of weekday in the clear day. The places that the criminal activities occurred were streets, amusement places such as disco-theque, fields and their own house among alcohol users, whereas victim's house, another person's house and restaurant were chosen among non-alcohol users. 4. The victims assaulted by Juvenile offenders in both drunken and non-drunken state were mostly passer-by(65.4%), followed by their friends(25.1%). And the conditions of victims showed a significant differences between the drunken adolescents and the non-drunken adolescents. The victim's conditions assaulted by intoxicated delinquent adolescents were in quarreling or drunken state, whereas non-alcohol related crimes were directed against victims in a sleeping or irresistible state. 5. Almost over the half of delinquent adolescents perceived their delinquency as wrong behaviors. and alcohol non-user tended to more significantly perceive their criminal acts as wrong conducts. About the half of respondents answered that they committed their criminal acts in spite of having a very good Judgement while doing crimes, the author did not found a significant difference between the two groups. The reasons given for crimes were manifested as follows: it can be seen that ‘to get money for amusements’(30.4 % of all motives) were most common, followed by ‘to commit accidentally the offences’(23.8%), ‘curiosity or heroism’(18.9%). alcohol related crimes tended to be accidental and impulsively without any clear planning, while non-alcohol related crimes tended to be purposeful, directed to make money motivated by curiosity or a desire to live heroically. In Conclusions. the correlation between alcohol use and Juvenile criminal behaviors has been examined in this study. Generally, alcohol use had been found to be highly correlated with aggressive assault crimes including robbery, burglary and rape etc.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.9
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• pp.1127-1132
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• 2013

The failure of reactor internals may have a significant effect on the safe operation and shutdown of a reactor. Various agings related to neutron irradiation occur or can potentially occur in the reactor internals owing to high neutron irradiation levels. Austenitic stainless steel, one of the principal materials constituting the reactor internals, shows different mechanical material behaviors such as tensile/creep properties and fracture toughness with neutron irradiation levels. This variation should be considered when the structural integrity of the reactor internals against agings during the design lifetime or continued operation period is evaluated. In this study, user subroutine programs considering the variation of mechanical material behaviors with neutron irradiation levels were developed. The programs were validated by testing them for various conditions.

• The Journal of Korean Association of Computer Education
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• v.18 no.3
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• pp.15-24
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• 2015

Appropriate distribution and utilization of learning time in class are regarded as essential and basic conditions for successful education. Nonetheless, among studies about UCR(User Created Robot) based instruction so far is difficult to find the research related to the class. For these reasons, we attempt to analyze the ALT(Actual Learning Time) and unuse of learning time in UCR based instruction. For these purpose, we observed three students who were with third and fourth grade integrated class of elementary school and interviewed the teachers at pre-post class. The result of this study showed the following results: (1) UCR based instruction present lower ALT than traditional classes. (2) Most of the unnecessary time used in their classes tend to be used in preparing and arranging the robot module, a little is used unnecessarily because of the students' unrelated behaviors for their learning, decentralized behaviors and other external influences.

• ETRI Journal
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• v.35 no.6
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• pp.1058-1067
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• 2013

An approach for game bot detection in massively multiplayer online role-playing games (MMORPGs) based on the analysis of game playing behavior is proposed. Since MMORPGs are large-scale games, users can play in various ways. This variety in playing behavior makes it hard to detect game bots based on play behaviors. To cope with this problem, the proposed approach observes game playing behaviors of users and groups them by their behavioral similarities. Then, it develops a local bot detection model for each player group. Since the locally optimized models can more accurately detect game bots within each player group, the combination of those models brings about overall improvement. Behavioral features are selected and developed to accurately detect game bots with the low resolution data, considering common aspects of MMORPG playing. Through the experiment with the real data from a game currently in service, it is shown that the proposed local model approach yields more accurate results.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.717-723
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• 2019

Smart systems and services aim to facilitate growing urban populations and their prospects of virtual-real social behaviors, gig economies, factory automation, knowledge-based workforce, integrated societies, modern living, among many more. To satisfy these objectives, smart systems and services must comprises of a complex set of features such as security, ease of use and user friendliness, manageability, scalability, adaptivity, intelligent behavior, and personalization. Recently, artificial intelligence (AI) is realized as a data-driven technology to provide an efficient knowledge representation, semantic modeling, and can support a cognitive behavior aspect of the system. In this paper, an integration of AI with the smart systems and services is presented to mitigate the existing challenges. Several novel researches work in terms of frameworks, architectures, paradigms, and algorithms are discussed to provide possible solutions against the existing challenges in the AI-based smart systems and services. Such novel research works involve efficient shape image retrieval, speech signal processing, dynamic thermal rating, advanced persistent threat tactics, user authentication, and so on.

• Information Systems Review
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• v.23 no.1
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• pp.1-22
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• 2021

This study aims to analyze online game user's game items transacting behaviors for the two game genres such as MMORPG and sports game. For the sake of conducting the analysis, we adopted a fuzzy logic agent-based modeling. In the online game fields, game items transactions are crucial to game company's profitability. However, there are lack of previous studies investigating the online game user's game items transacting activities. Since many factors need to be addressed in a complicated way, ABM (agent-based modeling) simulation mechanism is adopted. Besides, a fuzzy logic is also considered due to the fact that a number of uncertainties and ambiguities exist with respect to online game user's complex behaviors in transacting game items. Simulation results from applying the fuzzy logic ABM method revealed that MMORPG game users are motivated to pay expensive price for high-performance game items, while sports game users tend to transact game items within a reasonable price range. We could conclude that the proposed fuzzy logic ABM simulation mechanism proved to be very useful in organizing an effective strategy for online game items management and customers retention.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.603-610
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• 2021

In this paper, we extract the user's power consumption patterns, and model the optimal consumption patterns by applying the user's environment and emotion. Based on the comparative analysis of these two patterns, we present an efficient power consumption method through changes in the user's power consumption behavior. To extract significant consumption patterns, vector standardization and binary data transformation methods are used, and learning about the ensemble's ensemble with k-means clustering is applied, and applying the support factor according to the value of k. The optimal power consumption pattern model is generated by applying forced and emotion-based control based on the learning results for ensemble aggregates with relatively low average consumption. Through experiments, we validate that it can be applied to a variety of windows through the number or size adjustment of clusters to enable forced and emotion-based control according to the user's intentions by identifying the correlation between the number of clusters and the consistency ratios.