• Journal of Korea Society of Industrial Information Systems
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• v.20 no.4
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• pp.1-9
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• 2015

This paper proposes CAC method that is more efficient for RRM using game theory combined with Multiple Attribute Decision Making(MADM). Because users request services with different Quality of Service(QoS), the network preference values to alternative networks for each service are calculated by MADM methods such as Grey Relational Analysis(GRA), Simple Additive Weighting(SAW) and Technique for Order Preference by Similarity to Ideal Solution(TOPSIS). According to a utility function representing preference value, non-cooperative game is played, and then network provider select the requested service that provide maximum payoff. The appropriate service is selected through Nash Equilibrium that is the solution of game and the game is played repeated. We analyze two overlaid networks among four Wireless LAN(WLAN) systems with different properties. Simulation results show that proposed MADM techniques have same outcomes for every game round.

• The Journal of Korean Society for School & Community Health Education
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• v.12 no.2
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• pp.113-127
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• 2011

Background: University health services have provided comprehensive medical care, counseling, health promotion, and public health services to their students and several other local institutions. To their faculty and staff, university health care centers have served occupational health services and employee assistant program. Purpose: We performed this study to review the health promotion services on two kinds of health care center with different style of university formate. Methods: We tried to collect the data by literature review and interview with executive and provider at health care center in University of California at Berkeley and San Jose State University. Results: Our results were as followed. First, students could use the medical services just as they would their regular doctor's office and urgent care center. Second, the health promotion unit offered programs and services for keeping students healthy and safe, including many opportunities for students to get involved in shaping the public health of the campus. Third, the health promotion recommendation offered from ACHA was useful guideline to improve health status of their member in university campus. Finally, the student satisfaction surveys were used for evaluation and quality improvement. Conclusions: The systematic approach to improve health status of students, faculty and staff can use to maintain a state of optimum health among the diverse student community in support of academic excellence. Coupled with health promotion and public health programs, university health service have to reach all segments of the healthy campus community. To achieve study goals in university, the health care center contributes to promote accountability and responsibility for the health and well being of the members in their campus.

• Journal of Korean Medical Science
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• v.33 no.53
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• pp.343.1-343.8
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• 2018

Background: Linkage of public healthcare data is useful in stroke research because patients may visit different sectors of the health system before, during, and after stroke. Therefore, we aimed to establish high-quality big data on stroke in Korea by linking acute stroke registry and national health claim databases. Methods: Acute stroke patients (n = 65,311) with claim data suitable for linkage were included in the Clinical Research Center for Stroke (CRCS) registry during 2006-2014. We linked the CRCS registry with national health claim databases in the Health Insurance Review and Assessment Service (HIRA). Linkage was performed using 6 common variables: birth date, gender, provider identification, receiving year and number, and statement serial number in the benefit claim statement. For matched records, linkage accuracy was evaluated using differences between hospital visiting date in the CRCS registry and the commencement date for health insurance care in HIRA. Results: Of 65,311 CRCS cases, 64,634 were matched to HIRA cases (match rate, 99.0%). The proportion of true matches was 94.4% (n = 61,017) in the matched data. Among true matches (mean age 66.4 years; men 58.4%), the median National Institutes of Health Stroke Scale score was 3 (interquartile range 1-7). When comparing baseline characteristics between true matches and false matches, no substantial difference was observed for any variable. Conclusion: We could establish big data on stroke by linking CRCS registry and HIRA records, using claims data without personal identifiers. We plan to conduct national stroke research and improve stroke care using the linked big database.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.543-555
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• 2019

The purpose of this study was to define and clarify the concept of Shared decision-making (SDM) in patients with chronic disease. Walker and Avant's concept analysis process was used to analyze interdisciplinary convergence in SDM. SDM in patients with chronic disease can be defined by the following attributes: acknowledgment patients as 'self-care experts', the rights of self-determination, reversible negotiation, and patient-centered care. The antecedents of SMD consisted of situations where there is a need to make a decision from several treatment options of similar efficacy, decisional conflict, patient, family, and health provider's willingness to participate in the decision-making process, enough time and opportunity for SDM. The consequences occurring as a result of SMD were decrease decisional conflict, improvement health outcome, satisfaction, quality of life, enhancement self-management and self-efficacy with long-term, and living acceptably with the illness. Based on these results, a scale measuring SDM in patients with chronic disease is needed.

• Knowledge Management Research
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• v.20 no.2
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• pp.25-42
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• 2019

AI speakers which are wireless speakers with smart features have released from many manufacturers and adopted by many customers. Though smart features including voice recognition, controlling connected devices and providing information are embedded in many mobile phones, AI speakers are sitting in home and has a role of the central en-tertainment and information provider. Many surveys have investigated the important factors to adopt AI speakers and influ-encing factors on satisfaction. Though most surveys on AI speakers are cross sectional, we can track customer attitude toward AI speakers longitudinally by analyzing customer reviews on AI speakers. However, there is not much research on the change of customer attitude toward AI speaker. Therefore, in this study, we try to grasp how the attitude of AI speaker changes with time by applying text mining-based analysis. We collected the customer reviews on Amazon Echo which has the highest share of AI speakers in the global market from Amazon.com. Since Amazon Echo already have two generations, we can analyze the characteristics of reviews and compare the attitude ac-cording to the adoption time. We identified all sub topics of customer reviews and specified the topics for smart features. And we analyzed how the share of topics varied with time and analyzed diverse meta data for comparisons. The proportions of the topics for general satisfaction and satisfaction on music were increasing while the proportions of the topics for music quality, speakers and wireless speakers were decreasing over time. Though the proportions of topics for smart fea-tures were similar according to time, the share of the topics in positive reviews and importance metrics were reduced in the 2nd generation of Amazon Echo. Even though smart features were mentioned similarly in the reviews, the influential effect on satisfac-tion were reduced over time and especially in the 2nd generation of Amazon Echo.

• Database Research
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• v.34 no.3
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• pp.69-85
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• 2018

Many researches proposed federated query engines to perform query on several homogeneous or heterogeneous datasets simultaneously that significantly improve the quality of query results. The existing techniques allow querying only over a few heterogeneous datasets considering the static binding using the non-standard query. However, we observe that a simultaneous system considering the integration of heterogeneous metadata standards can offer better opportunity to generalize the query over any homogeneous and heterogeneous datasets. In this paper, we propose a transparent federated engine (DRAZ) to query over multiple data sources using SPARQL. In our system, we first develop the ontology for a non-RDF metadata standard based on the metadata kernel dictionary elements, which are standardized by the metadata provider. For a given SPARQL query, we translate any triple pattern into an API call to access the dataset of corresponding non-RDF metadata standard. We convert the results of every API call to N-triples and summarize the final results considering all triple patterns. We evaluated our proposed DRAZ using modified Fedbench benchmark queries over heterogeneous metadata standards, such as DCAT and DOI. We observed that DRAZ can achieve 70 to 100 percent correctness of the results despite the unavailability of the JOIN operations.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.6
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• pp.237-249
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• 2010

If one analyzes recent cyber incidents including personal information infringement cases, it seems like actual attack is targeting Internet service providers but actually they are targeting Internet service users. For many users, all the services were not provided to them as they have signed for in the contract or personal informations, which users have provided to service providers when signing contracts, were disclosed to public without users' consent causing aftereffect. As a result, importance of S-SLA indexes, which is to be included in the SLA to be signed between a user and a service provider, is ever more increasing. Especially, if there is a S-SLA indexes for anti-virus services, service providers have to provide a high quality of service as they have signed in the SLA. However, there wasn't any researches in the S-SLA area domestically and there are only limited SLA indexes related to system or service maintenances at the moment. Therefore, this paper analyses security functions in anti-virus services and proposes S-SLA indexes for different security level.

• Knowledge Management Research
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• v.21 no.4
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• pp.157-173
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• 2020

In accommodation sharing economy, customers take a risk of uncertainty about product quality, which is an important factor affecting users' satisfaction. This risk can be lowered by the information disclosed by the facility provider. Self-presentation of the hosts can make a positive effect on listing performance by eliminating psychological distance through emotional interaction with users. This paper analyzed the self-presentation text provided by Airbnb hosts and found key aspects in the text. In order to extract the aspects from the text, host descriptions were separated into sentences and applied the Attention-Based Aspect Extraction method, an unsupervised neural attention model. Then, we investigated the relationship between aspects in the host description and the listing performance via linear regression models. In order to compare their impact between the three facility types(Entire home/apt, Private rooms, and Shared rooms), the interaction effects between the facility types and the aspect summaries were included in the model. We found that specific aspects had positive effects on the performance for each facility type, and provided implication on the marketing strategy to maximize the performance of the shared economy.

• Industry Promotion Research
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• v.7 no.2
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• pp.1-13
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• 2022

This study of purpose is to examine the efficiency through the current status and performance of each institution providing the Daegu community service investment project, and to find a direction for the efficient operation of each institution. In order to promote efficient and effective project promotion by checking the management status that meets the purpose of the local community service investment project, to provide systematic services necessary to consumers, improve quality, and improve the environment, the accurate situation and situation through the efficiency analysis of the service provider organization It is necessary to identify problems, develop programs suitable for regional characteristics, and actively manage services. Specifically, it seeks to provide a more stable and sustainable local community service by measuring efficiency based on information from each institution and comparing and analyzing it among local governments. For this purpose, it is meaningful in analyzing the efficiency of each institution by using the DEA (data envelope analysis) method and presenting the goals and policy implications for efficient operation by comparing them by local government.

• Journal of Information Technology Services
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• v.23 no.1
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• pp.97-121
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• 2024

As data usage grows in importance, ensuring individual control over personal information becomes critical. The emergence of the 'MyData' concept addresses this, particularly in financial services. Although the institutional and technological framework for financial MyData services is in place, there's a need to establish consumer understanding and perception of its usefulness and safety for successful activation. This study focuses on investigating the impact of trust on the intention to use the new mobile banking service, financial MyData. This study has three objectives. Firstly, to analyze whether trust in financial MyData services and trust in financial MyData service providers affect the intention to use financial MyData services. Secondly, to analyze the process of forming trust in financial MyData services based on the phenomenon of transferring trust in service providers to trust in services. Thirdly, to identify the process by which trust transfer occurs between service providers and financial MyData services. Ultimately, the goal of this study is to promote the intention to use financial MyData services based on the concept of trust and to activate these services. In summary, this study emphasizes the significance of trust in financial MyData services, exploring its impact on user intention and the transfer of trust from providers to services. By promoting consumer trust, the research aims to contribute to the activation of financial MyData services.