• Journal of the Korean BIBLIA Society for library and Information Science
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• v.22 no.3
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• pp.189-206
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• 2011

This paper proposes a conceptual framework to explore the ways in which people work with in accessing, sharing, and navigating Web resources. In order to provide a better frame of a user's interaction with a folksonomy, an information foraging approach was adapted that denotes adaptive information seeking behaviors of users within human information interaction. A conceptual framework that consists of three different components from users' points of view was proposed: tagging, navigation, and knowledge sharing. This understanding will help us to motivate possible future directions of research in folksonomy and lay the groundwork for empirical research which focuses on qualitative analysis of a folksonomic and users' tagging behaviors.

• Korean Medical Education Review
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• v.18 no.2
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• pp.51-57
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• 2016

This literature review explores artificial intelligence (AI) technology trends and IBM Watson health and medical references. This study explains how healthcare will be changed by the evolution of AI technology, and also summarizes key technologies in AI, specifically the technology of IBM Watson. We look at this issue from the perspective of 'information overload,' in that medical literature doubles every three years, with approximately 700,000 new scientific articles being published every year, in addition to the explosion of patient data. Estimates are also forecasting a shortage of oncologists, with the demand expected to grow by 42%. Due to this projected shortage, physicians won't likely be able to explore the best treatment options for patients in clinical trials. This issue can be addressed by the AI Watson motivation to solve healthcare industry issues. In addition, the Watson Oncology solution is reviewed from the end user interface point of view. This study also investigates global company platform business to explain how AI and machine learning technology are expanding in the market with use cases. It emphasizes ecosystem partner business models that can support startup and venture businesses including healthcare models. Finally, we identify a need for healthcare company partnerships to be reviewed from the aspect of solution transformation. AI and Watson will change a lot in the healthcare business. This study addresses what we need to prepare for AI, Cognitive Era those are understanding of AI innovation, Cloud Platform business, the importance of data sets, and needs for further enhancement in our knowledge base.

• Journal of Korean Society for Quality Management
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• v.49 no.3
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• pp.421-431
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• 2021

Purpose: For improving outgoing quality, this study presents a novel sampling framework based on predictive analytics. Methods: The proposed framework is composed of three steps. The first step is the variable selection. The knowledge-based and data-driven approaches are employed to select important variables. The second step is the model learning. In this step, we consider the supervised classification methods, the anomaly detection methods, and the rule-based methods. The applying model is the third step. This step includes the all processes to be enabled on real-time prediction. Each prediction model classifies a product as a target sample or random sample. Thereafter intensive quality inspections are executed on the specified target samples. Results: The inspection data of three Samsung products (mobile, TV, refrigerator) are used to check functional defects in the product by utilizing the proposed method. The results demonstrate that using target sampling is more effective and efficient than random sampling. Conclusion: The results of this paper show that the proposed method can efficiently detect products that have the possibilities of user's defect in the lot. Additionally our study can guide practitioners on how to easily detect defective products using stratified sampling

• Smart Media Journal
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• v.8 no.2
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• pp.66-73
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• 2019

Recently, object recognition technology using computer vision has attracted attention as a technology to replace sensor-based object recognition technology. It is often difficult to commercialize sensor-based object recognition technology because such approach requires an expensive sensor. On the other hand, object recognition technology using computer vision may replace sensors with inexpensive cameras. Moreover, Real-time recognition is viable due to the growth of CNN, which is actively introduced into other fields such as IoT and autonomous vehicles. Because object recognition model applications demand expert knowledge on deep learning to select and learn the model, such method, however, is challenging for non-experts to use it. Therefore, in this paper, we analyze the structure of deep - learning - based object recognition models, and propose a platform that can automatically select a deep - running object recognition model based on a user 's desired condition. We also present the reason we need to select statistics-based object recognition model through conducted experiments on different models.

• Convergence Security Journal
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• v.18 no.1
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• pp.33-42
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• 2018

CFD analysis is an analytical technique that applies a computer to the design and development of products across the entire industry for heat or fluid flow. This technology is used to shorten the development period and reduce costs through computerized simulation. However, the software used for CFD analysis is now required to use expensive foreign software. The Opensource CFD analysis software used in the proposed system has reliability of commercial CFD analysis software and has various user groups. However, for users who have expert knowledge, Opensource CFD software which supports only text interface environment, We have developed an environment that enables the construction of a CFD analysis environment for beginners as well as professionals. In addition, the proposed system supports the pre-processing (design and meshing) environment for CFD analysis and the environment for post-processing (result analysis & visualization), enabling the integrated CFD analysis process in one platform.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.5
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• pp.59-67
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• 2010

In the paper, we proposed an IM-ACM(Insider Misuse-Access Control Model) for preventing illegal information leakage by insider who exploits his legal rights in the ubiquitous computing environment. The IM-ACM can monitor whether insider uses data rightly using misuse monitor add to CA-TRBAC(Context Aware-Task Role Based Access Control) which permits access authorization according to user role, context role, task and entity's security attributes. It is difficult to prevent information leakage by insider because of access to legal rights, a wealth of knowledge about the system. The IM-ACM can prevent the information flow between objects which have the different security levels using context role and security attributes and prevent an insider misuse by misuse monitor which comparing an insider actual processing behavior to an insider possible work process pattern drawing on the current defined profile of insider's process.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.261-274
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• 2020

Research on the development and effectiveness of internet-based cognitive-behavioral therapy with a trauma focus (iCBT-T) has been actively conducted in Western societies, but these studies have just begun in Korea. The purpose of this study was to suggest practical considerations to developing and managing the iCBT-T program. After reviewing previous studies on iCBT-T, this author suggested a model of convergence and collaboration between mental health knowledge and information and communication technologies (ICT) to develop the iCBT-T program. This article outlines practical considerations, including focus and target groups of iCBT-T, intervention types of iCBT-T (open access vs. guided), number of sessions, ethical issues, professional support, and degree of user involvement. Methods to complement the limitations of internet as a medium are also proposed in the iCBT-T program. The convergence model of CBT-T and ICT is expected to promote the development of programs that can contribute to improving the mental health of users who experience traumatic events.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.100-111
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• 2021

This study aims to lead the new discussion by looking at variables affecting the number of subscription channels and subscription satisfaction in the absence of academic discussion of users' YouTube subscriptions. To this end, we conducted an online survey and analyzed the factors affecting the number of subscription channels and subscription satisfaction of YouTube users. We conducted hierarchical regression to examine their subscription motivation with exploratory factor analysis and to examine the impact of subscription motivations and the intentionality of Youtubers and the usefulness of YouTube knowledge on the number of subscription channels and subscription satisfaction. The analysis results are as follows: First, YouTube's usage and convenience motivation have had a static impact on the number of subscription channels. Second, factors affecting subscription satisfaction have been shown to be convenience subscription motivation, communication with Youtubers motivation, and perceived usefulness of YouTube. The practical significance of this work is that it can be beneficial to platform and channel operators in the changing new media environment. Furthermore, it aims to expand the interaction research extensions between YouTuber and users in the new media environment.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.139-147
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• 2022

The goal of this study is to develop a mobile application so that a person who is new to chemistry can easily acquire the knowledge necessary for chemical structure learning using image tracking technology. The point of this study is to provide a new chemical structure learning experience by recognizing a two-dimensional picture, augmenting the chemical structure into a three-dimensional object, showing it on the user's screen, and using a service that simultaneously provides related information in multiple fields. characteristic. Login API and real-time database technology were used for safe and real-time data management, and an application was developed using image tracking technology for image recognition and 3D object augmentation service. In the future, we plan to use the chemical structure data library to efficiently load and output data.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.53-62
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• 2021

Distance learning (DL) has become a major issue in the educational field with the spread of COVID-19. In order to enhance the satisfaction of DL learners, efforts to cultivate learners' competencies, as well as investment to build IT infrastructure, and activities to support high-quality content provision should be comprehensively considered. Based on a survey of 221 college students, this study verified that digital literacy (knowledge, skill, and mind) and information systems success factors (system, information, and service quality) all positively affect DL satisfaction, in turn, which positively influences on DL continuance. This study is meaningful in that it comprehensively considered learner's ability and IT infrastructure and analyzed the effect on the satisfaction and intention of continuous use of DL. In the future, it is necessary to expand the target of not only college students but also elementary and secondary students and instructors, and to further consider interaction, which is a major factor in the distance learning process.