• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3868-3888
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• 2022

A widely used social networking service like Twitter has the ability to disseminate information to large groups of people even during a pandemic. At the same time, it is a convenient medium to share irrelevant and unverified information online and poses a potential threat to society. In this research, conventional machine learning algorithms are analyzed to classify the data as either non-rumor data or rumor data. Machine learning techniques have limited tuning capability and make decisions based on their learning. To tackle this problem the authors propose a deep learning-based Rumor Detection Neural Network model to predict the rumor tweet in real-world events. This model comprises three layers, AttCNN layer is used to extract local and position invariant features from the data, AttBi-LSTM layer to extract important semantic or contextual information and HPOOL to combine the down sampling patches of the input feature maps from the average and maximum pooling layers. A dataset from Kaggle and ground dataset #gaja are used to train the proposed Rumor Detection Neural Network to determine the veracity of the rumor. The experimental results of the RDNN Classifier demonstrate an accuracy of 93.24% and 95.41% in identifying rumor tweets in real-time events.

• Journal of Korea Trade
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• v.25 no.8
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• pp.45-56
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• 2021

Purpose - This study examines the relationship between the global consumer's shopping value and the intent to purchase in many of today's emerging international malls. furthermore, the orientation of shopping will be examined to see if there is a significant mediating effect between the value of shopping and willingness to purchase in international shopping malls. Design/methodology - This study conducted a survey of Chinese travelers who had experience in visiting a shopping mall during their visit to Korea through an online panel research agency and received a total of 230 responses. To confirm the relationship with constructs, the structural equation model (SEM) was used to test hypothesis in this research. Findings - The study was to examine the relationship of the international consumers' shopping value to the purchase intention in shopping mall when they visit to other countries, and to find if there was any effect on the relationship between the shopping value of the shopping orientation and the willingness of the international shopping mall. Originality/value - By confirming the relationship between international consumers' shopping value and shopping orientation, this study proposed the theoretical implications for global consumers' shopping behavior. In addition, this result can affect the development of service programs for foreign consumers.

• Journal of Multimedia Information System
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• v.9 no.3
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• pp.201-208
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• 2022

Customized service is a vital and mandatory element for apps in improving their technical performance and app customer analysis. While apps require users' consent for their data extraction and usage, many of the terms and agreement forms are written intricately, making it harder for users to fully understand the whole concept of users' data collection for customized services. Ever since the Facebook-Cambridge Analytica scandal, personal data privacy has been re-examined, forcing many app companies to reinforce a reliable solution to data privacy issues. However, there has not been a secured solution, which worries many people about the future advanced issues when metaverse platforms are actively used in daily apps. The research aims to collect the reactions and behaviors of everyday app users who utilize apps with customized services to understand the nature of privacy data issues and the users' opinions about the future implementation of metaverse platforms. The method of the research was an online questionnaire that targeted university students. The study revealed many fearful and anxious reactions about personal data and further metaverse issues where most app users were uneducated about how current apps collect and utilize users' private data.

• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.85-91
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• 2023

In order to utilize KOSMOS, the performance evaluation results are presented in this paper with CloudSuite, an application service-based benchmark program in the cloud computing area. CloudSuite offers several distinct applications as cloud services in two parts: offline applications and online applications on containers. In comparison with other microservers which have similar hardware specifications of KOSMOS, it was observed that KOSMOS was superior in all CloudSuite benchmark applications. KOSMOS also showed higher performance than Intel Xeon CPU-based servers in an offline application. KOSMOS reduced completion time during executing Graph Analytics by 30.3% and 72.3% compared to two Intel Xeon CPU-based servers in an experimental configuration of multiple nodes in KOSMOS.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2292-2313
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• 2023

With improving computing performance, various digital platforms are being developed to enable easily utilization of high-performance computing environments. EDISON 1.0 is an online simulation platform widely used in computational science and engineering education. As the research paradigm changes, the demand for developing the EDISON 1.0 platform centered on simulation into the EDISON 2.0 platform centered on data and artificial intelligence is growing. Herein, a data framework, a core module for data-centric research on EDISON 2.0 digital platform, is proposed. The proposed data framework provides the following three functions. First, it provides a data repository suitable for the data lifecycle to increase research reproducibility. Second, it provides a new data model that can integrate, manage, search, and utilize heterogeneous data to support a data-driven interdisciplinary convergence research environment. Finally, it provides an exploratory data analysis (EDA) service and data enrichment using an AI model, both developed to strengthen data reliability and maximize the efficiency and effectiveness of research endeavors. Using the EDISON 2.0 data framework, researchers can conduct interdisciplinary convergence research using heterogeneous data and easily perform data pre-processing through the web-based UI. Further, it presents the opportunity to leverage the derived data obtained through AI technology to gain insights and create new research topics.

• The Journal of Korean Obstetrics and Gynecology
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• v.36 no.3
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• pp.129-153
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• 2023

Objectives: The purpose of this study is to report the clinical effectiveness and safety of herbal medicine treatment for postmenopausal osteoporosis. Methods: Researchers searched papers through 5 online databases including The Cochrane Library Central, Pubmed, China Academic Journal (CAJ), Oriental medicine Advanced Searching Integrated System (OASIS) and Korean studies Information Service System (KISS). Randomized controlled trials (RCTs) that used herbal medicine as treatment were included. Results: Twenty three studies were selected by the selection and exclusion criteria. The treatment group was treated with herbal medicine alone or with herbal medicine and conventional medicine. The control group was treated with conventional medicine. Most common evaluation index was Bone Mineral Density (BMD) followed by total efficacy rate and level of bone metabolism markers, level of sex hormones, etc. Compared with the control group, the treatment group was more effective and safer in all of 23 studies. Conclusions: Herbal treatment alone could be an effective and safe option in treating postmenopausal osteoporosis. Moreover herbal treatment with conventional medicine could improve its therapeutic effect on postmenopausal osteoporosis as well.

• Journal of Information Science Theory and Practice
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• v.11 no.3
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• pp.58-78
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• 2023

This study aimed to discover the notable experiences of Library and Information Science students in a virtual internship program. It employed qualitative descriptive research design by thematically analyzing the monthly internship journal of the interns. Using Colaizzi's method to identify themes from their experiences, the study revealed that interns expected to gain knowledge and skills on operations, services, and new information communication technologies in libraries. Orientation was found helpful in identifying the things interns needed to prepare. The interns faced issues from procrastination and technical difficulties, which they coped with employing avoidance strategies. Overall, the internship was viewed as an opportunity to learn and navigate the online digital system of the library despite the coronavirus disease 2019 pandemic. They realized their capacity and reflected on which competencies need improvement. In conclusion, students still learned the necessary knowledge and skills of a librarian; experienced the challenges faced in an actual library and were provided with various opportunities and realizations regarding the practice of librarianship. This study proposed a three-stage framework that outlines the involvement of the supervising instructors, librarians, and interns in the internship program from the preparation to the process and post-assessment.

• Journal of Information Science Theory and Practice
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• v.11 no.3
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• pp.1-15
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• 2023

The present study examines the impact of value co-creation on satisfaction and intention to adopt of e-resources among users. Four components of the DART model have been adopted to describe value co-creation. These components are dialogue, access, risk-assessment, and transparency. Ph.D. scholars and faculty members from National Capital Region, India, were requested to respond on a five-point Likert scale. A total of 220 responses were collected with the help of a structured questionnaire from respondents of the top 50 business schools according to National Institute Ranking Framework. These responses have been analysed by means of structured equation modelling on Adanco 2.2 software. Findings of the study reported the insignificant impact of access and risk-assessment, and positive impact of dialogue and transparency on satisfaction. Further, satisfaction has been identified, creating significant impact on adoption of e-resources. Such findings reflect the real picture of customer experience with respect to their role in co-creation of e-resources. Respondents have conveyed their dissatisfaction with the co-creation process of e-resources, as companies do not provide all the information and access to their customers beforehand. Consequently, customers fail to make informed decisions and also find themselves unable to show trust in the service providers of e-resources.

• Annual Conference of KIPS
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• 2011.04a
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• pp.40-42
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• 2011

Smart hand-held devices like iPhone, iPad, Andriod and other mobile-OS machines are becoming a well known part of our daily lives. Utilization of these devices has gone beyond the expectations of their inventors. Evolution of Apple's iOS from a mobile phone Operating System to a wholesome platform for Portable Gaming is an adequate proof. Using these smart devices people are downloading applications from numerous online App Stores. Utilizing remote storage facilities and confining themselves to computing power far below than an entry level laptop, netbooks have emerged. Google's idea of Chrome OS coupled with Google's AppEngine is an eye-opener for researchers and developers. Keeping all these industry-proven innovations in mind we are proposing a Context-Driven Cloud-Oriented Application Architecture for smart devices. This architecture enables our smart devices to behave smarter by utilizing very less of local resources.