• Journal of Digital Convergence
• /
• v.13 no.2
• /
• pp.35-42
• /
• 2015

As the value of Bigdata has been recognized importantly, public agencies including the government, private sector, etc. began to have an interest in Big Data. As there are sources of various data, and a variety of planning and analysis methods based on these sources has emerged, It is true that Bigdata will become a tool for creation of the new high qualitied information and decision making based on new insights. The purpose of this study is to find an alternative to the subway congestion problem that is not improved even though the various measures. In this study, we tried to explore approaches for ways to improve the congestion of the Seoul Subway using Seoul Metropolitan public data. Lastly, this study derived a policy alternative to establish new bus route that runs around the metro station that have a high level of congestion.

• Asia-Pacific Journal of Business
• /
• v.14 no.4
• /
• pp.289-303
• /
• 2023

Purpose - The purpose of this study is to investigate the types and forms of various marketing activities actually used in pharmaceutical companies and to empirically analyze the impact of these marketing activities on sales. Design/methodology/approach - This study categorize five years' worth of marketing activity data from a foreign pharmaceutical company 'A' which operates in South Korea into five categories. Multiple regression analysis and interaction effects are employed for data analysis. Findings - First, CRM calls, Detail calls, GP, and Web events have a positive impact on sales, but SoV does not show significant differences. Second, in the comparison between HQ1 and HQ2 based on patent ownership, Detail calls and Web events had a stronger impact on sales in HQ2, where the patent period is still in effect, compared to HQ1. However, SoV showed no difference between HQ1 and HQ2. Research implications or Originality - First, Detail Calls are more effective for drugs with active patents, while CRM Calls work better for drugs with expired patents. This emphasizes the need to customize call strategies based on patent status. Second, the significant impact of Web Events on sales in HQ2 compared to HQ1 suggests that online information access is crucial, indicating that customer receptivity varies based on product nature. Third, these insights, derived from data analysis, call for a shift in pharmaceutical marketing analysis methods away from traditional approaches. Finally, this study holds significance as one of the first empirical analyses using actual marketing data from pharmaceutical companies in South Korea.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.6
• /
• pp.764-770
• /
• 2004

This paper presents a hybrid data mining mechanism to extract expert knowledge from historical data and extend expert systems' reasoning capabilities by using fuzzy neural network (FNN)-based learning & rule extraction algorithm. Our hybrid data mining mechanism is based on association rule extraction mechanism, FNN learning and fuzzy rule extraction algorithm. Most of traditional data mining mechanisms are depended ()n association rule extraction algorithm. However, the basic association rule-based data mining systems has not the learning ability. Therefore, there is a problem to extend the knowledge base adaptively. In addition, sequential patterns of association rules can`t represent the complicate fuzzy logic in real-world. To resolve these problems, we suggest the hybrid data mining mechanism based on association rule-based data mining, FNN learning and fuzzy rule extraction algorithm. Our hybrid data mining mechanism is consisted of four phases. First, we use general association rule mining mechanism to develop an initial rule base. Then, in the second phase, we adopt the FNN learning algorithm to extract the hidden relationships or patterns embedded in the historical data. Third, after the learning of FNN, the fuzzy rule extraction algorithm will be used to extract the implicit knowledge from the FNN. Fourth, we will combine the association rules (initial rule base) and fuzzy rules. Implementation results show that the hybrid data mining mechanism can reflect both association rule-based knowledge extraction and FNN-based knowledge extension.

• Journal of Korea Multimedia Society
• /
• v.11 no.3
• /
• pp.386-397
• /
• 2008

This study proposes the actualization of a standard data model for activities through the development of clinical document architecture for medication administration using the health level 7 development frameworks(HDF) process based on object oriented analysis and development method of health level 7 V 3. Medication administration is the most common activity performed by clinical professionals at healthcare settings. A standardized information model and structured hospital information system are necessary to achieve evidence-based clinical activities. We had used HDF and various tools(Rose tree, RMIM designer, V3 generator) to create the clinical document architecture(CDA). This allowed us to illustrate each step of the HDF in the administration of medication. This study generated a information model of the medication administration process, which is one clinical activity. It should become a fundamental conceptual model for understanding international standard methodology by information technology(IT) developers with the objective of modeling healthcare information systems.

• Journal of the Korean Society of Systems Engineering
• /
• v.3 no.2
• /
• pp.9-16
• /
• 2007

To Manage the Defense Acquisition Process more efficiently, DAPA has looked over the applying SE process to the Eagle Acquisition Program. Based on comparing 'Requirement' with 'items suggested in the proposal' in RFP and analyzing the result by using Cradle, those items have been discovered with IPT, actualized and corrected. In addition, the computerized data base system makes easier to trace all changed and more efficiency to manage programs. Therefore, this study using SE in other acquisition program.

• Journal of Korean Academy of Nursing Administration
• /
• v.12 no.2
• /
• pp.287-294
• /
• 2006

Purpose: The purpose of this study was to identify the change of critical thinking disposition and problem solving process in students who experienced problem-based learning. Method: This research design was one group pre-post test design. Twenty-five nursing students who participated in ‘'Nursing Process' course with two PBL packages for a semester in 2004 were the subjects of this study. The data were analyzed by repeated measures of ANOVA, and content analysis. Result: The problem defining in problem solving process was improved significantly, but there was no significant difference in the critical thinking disposition. Conclusion: The results of this study suggest that PBL has a positive effect on nursing students' problem solving process, But for a more significant effect on a continuous base for critical thinking of nursing students, faculties should use web based and simulation-based education for self directed learning along with clinical situation-based scenarios.

• Journal of Korea Multimedia Society
• /
• v.20 no.8
• /
• pp.1347-1356
• /
• 2017

Artificial intelligence-based services are expanding into a new industrial revolution. There is artificial intelligence technology applied in real life due to the development of big data and deep learning related technology. And data analysis and intelligent assistant services that integrate information from various fields have also been commercialized. Chatbot with interactive artificial intelligence provide shopping, news or information. Chatbot service, which has begun to be adopted by some public institutions, is now just a first step in the steps. This study summarizes the services and technical analysis of chatbot. and the direction of public administration service chatbot was presented.

• Journal of Korean Academy of Nursing Administration
• /
• v.12 no.3
• /
• pp.397-405
• /
• 2006

Purpose: The purpose of this study was to develop the medical error reporting system and to validate an trait of error in the Operating Room. Methods: Descriptive research design was used. The subjects were 30 nurses with below 5-year-career in a University Hospital. Data was collected from 11, April until 22, April, 2005 using web-based error reporting system. Data was analyzed by mean, standard deviation, $X^{2}-test$ using SPSS WIN 10.0 program. Results: A time of medical error in operating room nursing frequent occurrence was from 12 pm. to 4pm. 'Lack of sterile materials' management' was the best frequent occurrence of medical error in operating room nursing. Conclusion: The findings of this study show that manager of healthcare organization must develop the error reporting system more familiar and ordinary. Afterward, we prevent the repetitive medical errors in nursing care through analyzing of error reporting system.

• Journal of Distribution Science
• /
• v.18 no.7
• /
• pp.27-36
• /
• 2020

Purpose: The study examines how emotional leadership affects employee attitude towards work engagement. Leader legitimacy perception is chosen as the mediating variable to understand the effect of emotional leadership on employee work engagement. Research design, data and methodology: The research model is based on theory and empirical research findings in order to examine the mediating effect of leader legitimacy perception on the relationship between the manager's emotional leadership and employee work engagement. For this purpose, a survey was conducted among 188 employees of domestic retail distributors. Confirmatory factor analysis (CFA) and survey data confirmed the construct, and the hypothesis was tested by using structural equation modeling (SEM). Results: a) Emotional leadership has positive influence on leader legitimacy; b) Leader legitimacy is positively related to work engagement; c) Leader legitimacy mediates a positive relationship between emotional leadership and work engagement. However, there is no direct effect on work engagement (of employees) from emotional leadership standpoint. Conclusion: Based on the empirical results, implications and future research directions are discussed.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2002.05a
• /
• pp.306-311
• /
• 2002

This paper propose a personalized defection detection and prevention procedure based on the observation that potential defectors have tendency to take a couple of months or weeks. For this purpose, possible states of customer behavior are determined from past behavior data using SOM (Self-Organizing Map). For the evaluation of the proposed procedure, a case study has been conducted for a Korean online game site. The result demonstestes that the proposed procedure can assist defection prevention effectively and detect potential defectors without deterioration of prediction accuracy comparison to prediction by MLP. Our procedure can be applied to various service industries that can capture fluent customer behavior data such as telecommunications, internet access services, and content services, too.