• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.1
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• pp.9-22
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• 2009

This paper is an explanation of a design and an implementation of Web 2.0 online travel agency system for frequent decision-making. On the Web 2.0 travel agency system, optimized information is obtained by applying data mining technology such as association rules, decision trees, and neural networks, and this system is a unified system that consists of the block systems of hotels, ground traffic, and flights in tour packages of a travel agency system. Furthermore, it is implemented to manage the system that is not for the administrator of a travel agency system, but for users or communities that use the system need their own information. The expected effect of this system is to maximize the investment company's efficiency through a new-concept interest model created by B2C customers, and also B2B small and medium-sized travel agencies adopting the system. As a result, it is a system that stimulates dormant customer activity and prevents good customers from leaving by maximizing the merit and capacity of the existed web site for marketing. Moreover, this system is also a model for people who plan customized travel agency business, and will show a way for the domestic and international travel agency industry's globalization.

• Journal of Distribution Science
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• v.21 no.7
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• pp.117-129
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• 2023

Purpose: With the number of COVID-19 cases declining and generational differences among how people use mobile apps, including health service apps, the goal of this research is to identify and analyze the factors that affect people's attitudes when using the Halodoc health service app during the third year of the pandemic. Research design, data, and methodology: This study proposes a quantitative analysis method based on PLS-SEM modeling. This study has used a questionnaire survey to collect randomized data from 268 Halodoc users from generations Y and Z in Jakarta. Results: Both the Y and Z generations believe there is a significant usefulness factor in the attitude toward using the application. The start of the pandemic period demonstrates that the urgency of using health service applications is no longer determined by performance expectations, effort, or social panic, but rather by these applications' usability. Conclusions: Even though a health service application is no longer considered an urgent service or a priority need, attitudes, and behaviors in using it emphasize the aspect of long-term benefits. These findings supplement other considerations and understandings in application of the Unified Theory of Acceptance and Use of Technology (UTAUT) model in explaining attitudes and intention behaviors.

• Journal of Korea Artificial Intelligence Association
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• v.1 no.1
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• pp.11-16
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• 2023

Accurate hospital case modeling and prediction are crucial for efficient healthcare. In this study, we demonstrate the implementation of regression analysis methods in machine learning systems utilizing mathematical statics and machine learning techniques. The developed machine learning model includes Bayesian linear, artificial neural network, decision tree, decision forest, and linear regression analysis models. Through the application of these algorithms, corresponding regression models were constructed and analyzed. The results suggest the potential of leveraging machine learning systems for medical research. The experiment aimed to create an Azure Machine Learning Studio tool for the speedy evaluation of multiple regression models. The tool faciliates the comparision of 5 types of regression models in a unified experiment and presents assessment results with performance metrics. Evaluation of regression machine learning models highlighted the advantages of boosted decision tree regression, and decision forest regression in hospital case prediction. These findings could lay the groundwork for the deliberate development of new directions in medical data processing and decision making. Furthermore, potential avenues for future research may include exploring methods such as clustering, classification, and anomaly detection in healthcare systems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.73-82
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• 2019

In order to build a smart factory, building a CPPS (Cyber Physical Product System) is an important system that must be accompanied. Through the CPPS, it is the reality of smart factories to move physical factories to a digital-based cyber world and to intelligently and autonomously monitor and control them. But The existing CPPS architectures present only an abstract modeling architecture, and the research that applied the OPC UA Framework (Open Platform Communication Unified Architecture), an international standard for data exchange in the smart factory, as the basic system of CPPS It was insufficient. Therefore, it is possible to implement CPPS that can include both cloud and IoT by collecting field data distributed by CPPS architecture applicable to actual factories and concentrating data processing in a centralized In this study, we implemented CPPS architecture through central OPC UA Server based on OPC UA conforming to central processing OPC UA Framework, and how CPPS logical process and data processing process are automatically generated through OPC UA modeling processing We have proposed the CPPS architecture including the model factory and implemented the model factory to study its performance and usability.

• Journal of the Korea Society for Simulation
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• v.29 no.2
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• pp.73-81
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• 2020

HCCL stands for Heterogenous Container Class Library. HCCL is a library that allows heterogeneous types of data to be stored in a container as a single record and to be constructed as a list of the records to be stored in database. With HCCL, encryption/decryption can be done based on the unified data type. Recently, IoT sensor which is embedded in smartphone enables developers to provide various convenient services to users. However, it is also true that infringement of personal information may occur in the process of transmitting sensor information to API and users need to be prepared for this situation in some sense. In this study, we developed a data model that enhances existing security using SEED cryptographic algorithms while managing information of sensors based on HCCL. Due to the fact that the Android environment does not provide permission management function for sensors, this study decided whether or not to encrypt sensor information based on the user's choice so that the user can determine the creation and storage of safe data. For verification of this work, we have presented the performance evaluation by comparing with the situation of storing the sensor data in plaintext.

• Korea Journal of Hospital Management
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• v.11 no.3
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• pp.19-41
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• 2006

The Objective of this study was to design the model which predict the future cash flow of hospitals and on the basis of designed model to support sound hospital management by the prediction of future cash flow. The five cash flow measurement variables discussed in financial accrual part were used as variables and these variables were defined as NI, NIDPR, CFO, CFAI, CC. To measure the cash flow B/S related variables, P/L related variables and financial ratio related variables were utilized in this study. To measure cash flow models were designed and to estimate the prediction ability of five cash flow models, the martingale model and the market model were utilized. To estimate relative prediction outcome of cash flow prediction model and simple market model, MAE and MER were used to compare and analyze relative prediction ability of the cash flow model and the market model and to prove superiority of the model of the cash flow prediction model, 32 Regional Public Hospital's cross-section data and 4 year time series data were combined and pooled cross-sectional time series regression model was used for GLS-analysis. To analyze this data, Firstly, each cash flow prediction model, martingale model and market model were made and MAE and MER were estimated. Secondly difference-test was conducted to find the difference between MAE and MER of cash flow prediction model. Thirdly after ranking by size the prediction of cash flow model, martingale model and market model, Friedman-test was evaluated to find prediction ability. The results of this study were as follows: when t-test was conducted to find prediction ability among each model, the error of prediction of cash flow model was smaller than that of martingale and market model, and the difference of prediction error cash flow was significant, so cash flow model was analyzed as excellent compare with other models. This research results can be considered conductive in that present the suitable prediction model of future cash flow to the hospital. This research can provide valuable information in policy-making of hospital's policy decision. This research provide effects as follows; (1) the research is useful to estimate the benefit of hospital, solvency and capital supply ability for substitution of fixed equipment. (2) the research is useful to estimate hospital's liqudity, solvency and financial ability. (3) the research is useful to estimate evaluation ability in hospital management. Furthermore, the research should be continued by sampling all hospitals and constructed advanced cash flow model in dimension, established type and continued by studying unified model which is related each cash flow model.

• Journal of the Korean Society for Library and Information Science
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• v.48 no.3
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• pp.71-111
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• 2014

Metadata schemas are well recognized as one of the important technological components for archiving and preservation of digital resources. However, a single standard is not enough to cover the whole lifecycle for archiving and preserving digital resources. This means that we need to appropriately select metadata standards and combine them to develop metadata schemas to cover the whole lifecycle of resources (or records). Creating a unified framework to understand the features of metadata standards is necessary in order to improve metadata interoperability that covers the whole resource lifecycle. In this study, the author approached this issue from the task-centric view of metadata, proposing a Task model as a framework and analyzing the feature of archival metadata standards. The proposed model provides a new scheme to create metadata element mappings and to make metadata interoperable. From this study, the author found out that no single metadata standard can cover the whole lifecycle and also that an in-depth analysis of mappings between metadata standards in accordance with the lifecycle stages is required. The author also discovered that most metadata standards are primarily resource-centric and the different tasks in the resource lifecycle are not reflected in the design of metadata standard data models.

• Journal of Information Technology Services
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• v.11 no.3
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• pp.17-38
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• 2012

Social network service(SNS), provided by social network sites such as Facebook, Twitter and Cyworld is rapidly growing in online business. Furthermore, many companies have growing interests in finding effective ways to use SNSs for their innovations, marketing and advertisement. In fact, firms have recognized the utility value of the SNS for their business. In this aspect, this study attempts to identify key factors influencing the intention to continuous use of SNSs. Based on the UTAUT(the Unified Theory of Acceptance and Usage of Technology)model, this study proposes the research model, including the effects of social network service characteristics(social relationship support, information sharing, image expression) and individual characteristics(self-disclosure, extroversion, familiarity) on performance expectancy as well as the moderating effect of perceived information security among UTAUT variables. The 412T sets of data collected in a survey were tested against the modeling using SEM using SmartPLS. Results indicated that social network service and individual characteristics had significant effect on performance expectancy with exception of self-disclosure. In addition, the moderating effect of perceived information security had significant effect. The results had important implications for firms providing SNSs hoping to develop a successful business model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.11
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• pp.1027-1035
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• 2012

Recently, the smart phone including web and mobile service based on the reliability and extendability of cloud computing is receiving huge attention. However, most of current cloud services provide just an application service for synchronizing data between mobile entity and server. Business model developed by communication companies have problems with interoperability. This paper proposes a new service security authentication model to efficiently manage smart phone users using different business models between smartphones and to keep the reliability and extendability of cloud computing. Proposed model authenticates for smart phone users to stay with in the unified communication with smart phone user's identity and access control to effectively use the current cloud computing system.

• Journal of Information Technology Applications and Management
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• v.21 no.2
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• pp.49-79
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• 2014

The adoption of technology has always been of interest to academicians and practitioners of the field of Management Information System. This is so because without proper and adequate adoption, technology-no matter how beneficial or advanced it may be-will be of little value to users. Numerous researches, such as the researches of the Technology Acceptance Model (TAM) or the Unified Theory of Acceptance and Use of Technology (UTAUT), had been conducted to understand the human nature in association with the adoption or rejection of technologies that have bombarded the users. The coming of smart technologies (i.e., smart phones and devices), however, seems to have fundamentally changed the environment for adoption. The ubiquity combined with mobility of technology, especially when it comes to mobile apps, seem to make the old PC era of two-stage-pre and post-adoption models obsolete. A new model of adoption that identifies the determinants of technology acceptance and continuance is needed for the smart age. To this end, this paper undertakes an empirical study, by analyzing 229 users of Social Networking Service (SNS) mobile apps, to identify the role of user experience on the multi-stage adoption of technology, and provides results that User Experience (UX) plays the crucial role of bridging the separate stages of pre and post adoption of technologies. The paper concludes by providing practical implications of the new model as it relates to mobile apps and technologies, and recommendations for further studies to get a better understanding of technology adoption in the smart age.