• Culinary science and hospitality research
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• v.23 no.7
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• pp.97-111
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• 2017

As a single-person household emerges as an important consumer group, an Online-to-Offline or Offlineto-Online(O2O) service market is rapidly growing. This study attempted to verify the effects of convenience and webrooming characteristics of O2O service using the Technology Acceptance Model (TAM). The purpose of this study was to investigate the effects of the convenience and webrooming of food O2O service on users' perceived ease of use and perceived usefulness, and the effects of perceived ease of use and perceived usefulness on purchase intention of O2O services. Using a convenience sampling technique, an online survey was conducted through Google survey from April 16 to April 30, 2017 and was distributed to 447 O2O service users. A total of 320 questionnaires were included in the final analysis. The results showed that convenience had a significant effect on users' perceived ease of use as well as perceived usefulness. In addition, users' perceived ease of use had a significant impact on users' perceived usefulness. Finally, both perceived ease of use and perceived usefulness positively affected users' purchase intention of O2O services. These findings suggest that differentiated events, promotions, and store information should be provided when launching O2O service because webrooming is a more important factor in enhancing perceived usefulness than the perceived ease of use.

• Korean Journal of Clinical Pharmacy
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• v.33 no.3
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• pp.202-209
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• 2023

Background: With the emergent transition of online learning during the COVID-19 pandemic, the need for online/offline blended learning that can effectively be utilized in a team-based learning (TBL) course has emerged. Methods: We used the online metaverse platforms, Gather and Zoom, along with face-to-face teaching methods in a team-based Introductory Pharmacy Practice Experience (IPPE) course and examined students' learning satisfaction and achievement, as well as their preferences to the learning platforms. A survey questionnaire was distributed to the students after the IPPE course completion. All data were analyzed using Excel and SPSS. Results: Students had high levels of course satisfaction (4.61±0.57 out of 5) and achievement of course learning objectives (4.49±0.70 out of 5), and these were positively correlated with self-directed learning ability. While students believed that the face-to-face platform was the most effective method for many of the class activities, they responded that Gather was the most effective platform for team presentations. The majority of students (64.3%) indicated that blended learning was the most preferred method for a TBL course. Conclusion: Students in a blended TBL IPPE course had high satisfaction and achievements with the use of various online/offline platforms, and indicated that blended learning was the most preferred learning method. In the post-COVID-19 era, it is important to utilize the blended learning approach in a TBL setting that effectively applies online/offline platforms according to the learning contents and activities to maximize students' learning satisfaction and achievement.

• Fashion & Textile Research Journal
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• v.12 no.6
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• pp.755-763
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• 2010

This study was intended to identify the persuasion effects according to social proof message type and product type in the context of online cosmetic advertising. For the experiment, 4 stimuli were developed as experimental stimuli for the 2(social proof message type: attitudinal social proof message, behavioral social proof message)${\times}$2(product type: hedonic product, utilitarian product) factorial design. A total of 160 questionnaires allocating forty students to each group were distributed. The results were as follows. First, behavioral social proof message showed more effective than attitudinal social proof message in advertisement attention, click-through intention and purchase intention. Second, utilitarian product showed more effective than hedonic product in advertisement attention, click-through intention and purchase intention. Third, there was interaction effect according to social proof message type and product type on the aspect of click-through intention.

• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.54-60
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• 2020

Online cybercrime has various causes. The criminal guilty language, Criminal lingo is active in the shaded area with the bilateral aspect of the word on cyber. It has been continuously producing massive risk factors in cyberspace. Criminals are shared and disseminated online. It has been linked with fake news and aids to suicide that has recently become an issue. Thus the criminal lingo has become a real danger factor on cyber interface. Recently, Criminal lingo is shared and distributed as cyber hazard information. It is transformed that damaging to the youth and ordinary people through the internet and social networks. In order to take action, it is necessary to construct an expert system based on AI to implement a smart management architecture with block-chain technology. In this paper, we study technically a new smart management architecture which uses artificial intelligence based decision algorithm and block-chain tracking technology to prevent the spread of criminal lingo factors in the evolving cyber world. In addition, through the off-line regular patrol program of police units, we proposed the conversion of online regular patrol program for "cyber harem area".

• Journal of Korea Game Society
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• v.16 no.1
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• pp.83-92
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• 2016

An online game is a huge distributed system comprised of servers and untrusted clients. In such circumstances, cheaters may employ abnormal behaviors through client modification or network packet tampering. Client-side detection methods have the merit of distributing the burden to clients but can easily be breached. In the other hand, server-side detection methods are trustworthy but consume tremendous amount of resources. Therefore, this paper proposes a security reinforcement method which involves both the client and the server. This method is expected to provide meaningful security fortification while minimizing server-side stress.

• Journal of Distribution Science
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• v.21 no.3
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• pp.25-36
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• 2023

Purpose: Brand community in higher education institutions comes up as an important topic to be discussed because the relationships among consumers can support the institutional brand and ultimately give meaning and vitality to the market-oriented strategy. This study aims to investigate how the literature on brand community in higher education have been distributed in research trends, theoretical frameworks, and methods. Research design, data and methodology: A total of 24 articles were organized from four reputable international databases. Content analysis were performed followed by synthesis toward potential directions and suggestions. Results: The researches in this area have increasingly focused on online interaction. Social identity theory and relationship theory were the two most prevalent theories used. Since the internet provides any social relationship with a specific relationship to form the brand community, its contextualization in higher education resulted in new concept implementation. Conclusions: The relationship within online participati on has impacted the market-oriented strategy of higher education in searching for ways toward a long-term and enduring bond among students, alumni, institutions and brands. As there is a plenteous prospect of data availability combined with big data analysis technology, the online participation will pique the interest of scholars to conduct further research on it.

• Journal of Korea Multimedia Society
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• v.6 no.4
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• pp.685-697
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• 2003

The Web based multimedia programmes/courses are becoming widely available in recent years. Most of these courses focus on Behaviorist way of learning, which does not promote deep learning in any way. For Adults this approach further incapacitated, as it does not satisfy Andragogical needs. The search for Constructivist way of learning through the web applied to Indian conditions led to need for developing a curriculum development approach that would promote construction of knowledge through web based collaboration. This paper attempts to reengineer existing curriculum development processes and lays out a framework of‘Problem Based Online Learning (PBOL)’curriculum design. In this context, entire curriculum development life cycle is evolved and explained. This is a part of doctoral work (Ph.D), which is in progress and being undertaken by K.James Mathai, and guided of Dr.D.S.Karaulia.

• International Journal of Advanced Culture Technology
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• v.9 no.1
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• pp.218-223
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• 2021

Pervasive enhancement and required enforcement of the Internet of Things (IoTs) in a distributed massively multiplayer online architecture have effected in massive growth of Big-Data in terms of server over-load. There have been some previous works to overcome the overloading of server works. However, there are lack of considered methods, which is commonly applicable. Therefore, we propose a combing Sparse Auto-Encoder and Load-Balancing, which is ProGReGA for Big-Data of server loads. In the process of Sparse Auto-Encoder, when it comes to selection of the feature-pattern, the less relevant feature-pattern could be eliminated from Big-Data. In relation to Load-Balancing, the alleviated degradation of ProGReGA can take advantage of the less redundant feature-pattern. That means the most relevant of Big-Data representation can work. In the performance evaluation, we can find that the proposed method have become more approachable and stable.

• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.41-51
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• 2022

We forecast the US oil consumption level taking advantage of google trends. The google trends are the search volumes of the specific search terms that people search on google. We focus on whether proper selection of google trend terms leads to an improvement in forecast performance for oil consumption. As the forecast models, we consider the least absolute shrinkage and selection operator (LASSO) regression and the structured regularization method for large vector autoregressive (VAR-L) model of Nicholson et al. (2017), which select automatically the google trend terms and the lags of the predictors. An out-of-sample forecast comparison reveals that reducing the high dimensional google trend data set to a low-dimensional data set by the LASSO and the VAR-L models produces better forecast performance for oil consumption compared to the frequently-used forecast models such as the autoregressive model, the autoregressive distributed lag model and the vector error correction model.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.547-557
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• 2022

Online learning at a medical school was evaluated and improved based on the results of the evaluation and the principles of online learning environments design. The purpose of this study was to compare the results of online learning satisfaction between semesters from medical students and professors. To evaluate online learning, satisfaction surveys for an online learning platform, student participation, learning methods, learning contents, student assessments, and learning supports were developed and distributed to research participants. 223 students and 37 professors participated for the 1st semester, and 218 students and 49 professors participated for the 2nd semester, and paired t-tests were used for the analysis. Student satisfaction for the online learning platform, learning methods, learning contents, and learning supports were positively changed. However, the differences in the satisfaction for the student participation and student assessments were not statistically significant. In particular, students' satisfaction in basic medical sciences and clinical medicine periods decreased, whereas students' satisfaction in preclinical medicine and clinical clerkship periods increased. Based on the results, this study will contribute to the improvement of online learning at medical schools.