• Korean Public Health Research
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• v.44 no.4
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• pp.99-109
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• 2018

Objective : Health literacy (HL) is, defined as "the degree to which individuals have the capacity to obtain, process, and understand basic health information and services needed to make appropriate health decisions." Being old is one of the main risk factors with limited health literacy. This study aims to adapt Chew's health literacy scale into the Korean language and validate the scale for the use of the elderly. Methods : Data were drawn from the '2016 Seoul Survey on Elderly Health and Functional Assessment, which includes a total of 725 people aged 60 to 79. The sample was randomly divided into two groups for reliability and validity tests of the modified Chew's scale of 8 items. The Korean version of the questionnaire was developed by group translation, expert reviews, and forward-backward translation. Exploratory and confirmatory factor analyses were conducted to assess and validate the factor structure of the scale. Results : Results suggest the two-factor structure ("Understanding" and "Applying" of HL) with 8 items. Exploratory factor analyses of the first sample (n=400) revealed that the internal reliability of the scale was high (Cronbach's ${\alpha}=.904$). Principal axis factoring extracted two factors ("Understanding" and "Applying" of HL) and explained 78.3% of total variance (KMO=.872, Bartlett's ${\chi}^2=2431.3$, df=28, p<.001). Confirmatory factor analysis of the second sample (n=325) was performed and the two-factor model was supported (GFI=.960, CFI=.979, TLI=.969, RMSEA=0.075). Conclusions : This study provides evidence for adequate criterion and validity of the health literacy scale for the community dwelling elderly in Korea.

• International Area Studies Review
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• v.22 no.4
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• pp.123-143
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• 2018

Many studies on the acceptance of multi-national products have made academic contributions by offering various implications. However, there have been relatively few studies on the attitudes and behaviors of multi-national products depending on the purchasing tendency of consumers. The purpose of this study is to investigate how acceptance process of multi-national product, which is high involvement, appears by sorting consumers' purchasing tendency into rational consumption tendency, brand pursuit tendency, and consciousness of other people. Also, in order to supplement the measurement method of existing research, this study sought to analyze the acceptance behavior of consumers more precisely by classifying the situation before and after exposures of multi-national origin information on products. For this, 266 consumers were surveyed and statistical analysis was conducted through structural equation modeling. As a result of the research model, it was found that consciousness of other people has a significant effect on susceptibility and antipathy of multi-national product. In addition, antipathy against multi-national products has more powerful effect than susceptibility.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.1
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• pp.1-15
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• 2019

The purpose of this study is to analyze the relationship between entrepreneurship and entrepreneurial intention. This relationship has been conceptually addressed in many previous studies and has been empirically tested. However, this study is different from the previous studies in the following four points. First, we measured entrepreneurial intention by manipulating launching a start-up as a relative concept for employment, which is consistent with the conceptual definition of entrepreneurial intention (i.e. entrepreneurial decision making in the process of career choice). Second, it is distinguished from previous researches in that it uses the question of preference for "action" with regard to job choice. Third, we expanded the opportunity for discussion using the youth panel data of the Korea Employment Information Service. Fourth, the altruistic purpose is included in the category of entrepreneurship. Empirical results showed that intentions of entrepreneurship were stronger when the need for achievement was intense, internal control tendency was intended, risk-taking propensity was sturdy, and autonomous tendency was high. However, innovation and aggressiveness are not statistically related to entrepreneurial intention. On the other hand, the altruistic tendency was found to have a negative correlation with entrepreneurial intention. The results of this study can provide meaningful implications for both private sector investors and government policy makers.

• The Korean Journal of Archival Studies
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• no.34
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• pp.57-105
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• 2012

The CAMS(Central Archives Management System) of NAK(National Archives of Korea) is an important system which receives and manages large amount of electronic records annually from 2015. From the point of view in database design, this paper analyzes the database schema of CAMS and discusses the direction of overall improvement of the CAMS. Firstly this research analyzes the tables for records and folders in the CAMS database which are core tables for the electronic records management. As a result, researchers notice that it is difficult to trust the quality of the records in the CAMS, because two core tables are entirely not normalized and have many columns whose roles are unknown. Secondly, this study suggests directions of normalization for the tables for records and folders in the CAMS database like followings: First, redistributing the columns into proper tables to reduce the duplication. Second, separating the columns about the classification scheme into separate tables. Third, separating the columns about the records types and sorts into separate tables. Lastly, separating metadata information related to the acquisition, takeover and preservation into separate tables. Thirdly, this paper suggests considerations to design and manage the database schema in each phase of archival management. In the ingest phase, the system should be able to process large amount of records as batch jobs in time annually. In the preservation phase, the system should be able to keep the management histories in the CAMS as audit trails including the reclassification, revaluation, and preservation activities related to the records. In the access phase, the descriptive metadata sets for the access should be selected and confirmed in various ways. Lastly, this research also shows the prototype of conceptual database schema for the CAMS which fulfills the metadata standards for records.

• Journal of Internet Computing and Services
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• v.20 no.2
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• pp.109-118
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• 2019

The purpose of this study is to deliver both market-practical and civil-centric political implication for sharing economy by investigating the nature of consumer-adoption for car-sharing service. With the global interest and market proliferation of the sharing economy, various service models for sharing idle resources have also been released in Korea. Particularly, in case of car sharing service, public - private partnership projects are spreading rapidly in various local governments including Seoul, along with the growing demand for alternative transportation system centering on the urban area. This study conducted an empirical study on the process of accepting the car sharing service by analyzing the data collected from users of the car sharing service "Sharing Car(Nanum Car)" of Seoul Metropolitan Government. A survey was conducted on 281 users in their twenties who are in the age of main use among the experienced users of the "Sharing Car(NaNum)" residing in Seoul. The result of analysis on the relationship between these users' perceived value and intention to use the vehicle sharing service would provide implications for establishing consumer(citizen)-centeric policies as well as market implications.

• Korean Journal of Anesthesiology
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• v.71 no.6
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• pp.467-475
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• 2018

Background: The Quality of Recovery-40 (QoR-40) is a widely-used, self-rated, and self-completed questionnaire for postoperative patients. The questionnaire is intended to elicit information from each patient regarding the quality of recovery during the postoperative period. It is noteworthy, however, that an official Korean version of the QoR-40 (QoR-40K) has not been established. The purpose of this study was to develop the QoR-40K by translation and cultural adaptation process and to evaluate the validity and reliability of the QoR-40K. Methods: After pre-authorization from the original author of the QoR-40, the translation procedure was established and carried out based upon Beaton's recommendation to create a QoR-40K model comparable to the original English QoR-40. Two hundred surgical patients were enrolled, and each completed the questionnaire during the preoperative period, on the third day, and 1 month after surgery. The QoR-40K was compared with the visual analogue scale (VAS) and another health-related questionnaire, the Short-form Health Survery-36 (SF-36). The method of validation for QoR-40K included test-retest reliability, internal consistency, and level of responsiveness. Results: Spearman's correlation coefficient for test-retest reliability was 0.895 (P < 0.001), and Cronbach's alpha of the global QoR-40K on the third day after surgery was 0.956. A positive correlation was obtained between the QoR-40K and the mental component summary of SF-36 (${\rho}=0.474$, P < 0.001), and a negative correlation was observed between QoR-40K and VAS (${\rho}=-0.341$, P < 0.001). The standardized responsive mean of the total QoR-40K was 0.71. Conclusions: The QoR-40K was found to be as acceptable and reliable as the original English QoR-40 for Korean patients after surgery, despite the apparent differences in the respective patients' cultural backgrounds.

• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.23-30
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• 2021

This paper proposes a noise-tolerant image classification system using multiple autoencoders. The development of deep learning technology has dramatically improved the performance of image classifiers. However, if the images are contaminated by noise, the performance degrades rapidly. Noise added to the image is inevitably generated in the process of obtaining and transmitting the image. Therefore, in order to use the classifier in a real environment, we have to deal with the noise. On the other hand, the autoencoder is an artificial neural network model that is trained to have similar input and output values. If the input data is similar to the training data, the error between the input data and output data of the autoencoder will be small. However, if the input data is not similar to the training data, the error will be large. The proposed system uses the relationship between the input data and the output data of the autoencoder, and it has two phases to classify the images. In the first phase, the classes with the highest likelihood of classification are selected and subject to the procedure again in the second phase. For the performance analysis of the proposed system, classification accuracy was tested on a Gaussian noise-contaminated MNIST dataset. As a result of the experiment, it was confirmed that the proposed system in the noisy environment has higher accuracy than the CNN-based classification technique.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.12
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• pp.569-578
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• 2021

Thanks to web development today, we can easily access online news via various media. As much as it is easy to access online news, we often face fake news pretending to be true. As fake news items have become a global problem, fact-checking services are provided domestically, too. However, these are based on expert-based manual detection, and research to provide technologies that automate the detection of fake news is being actively conducted. As for the existing research, detection is made available based on contextual characteristics of an article and the comparison of a title and the main article. However, there is a limit to such an attempt making detection difficult when manipulation precision has become high. Therefore, this study suggests using a verifying article to decide whether a news item is genuine or not to be affected by article manipulation. Also, to improve the precision of fake news detection, the study added a process to summarize a subject article and a verifying article through the summarization model. In order to verify the suggested algorithm, this study conducted verification for summarization method of documents, verification for search method of verification articles, and verification for the precision of fake news detection in the finally suggested algorithm. The algorithm suggested in this study can be helpful to identify the truth of an article before it is applied to media sources and made available online via various media sources.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.349-357
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• 2021

Recently, drones are rapidly becoming common and expanding. There is a great need for diversity in whether drone flight data can be used as entertainment technology analysis data. In particular, it is necessary to check whether it is possible to analyze and utilize the flight and operation process of entertainment drones, which are developing through autonomous and intelligent methods, through data analysis and machine learning. In this paper, it was confirmed whether it can be used as a machine learning technology by using FC data in the evaluation of drones for entertainment. As a result, FC data from DJI and Parrot such as Mavic2 and Anafi were unable to analyze machine learning for entertainment. It is because data is collected at intervals of 0.1 second or more, so that it is impossible to find correlation with other data with GCS. On the other hand, it was found that machine learning technologies can be applied in the case of Fixhawk, which used an ARM processor and operates with the Nuttx OS. In the future, it is necessary to develop technologies capable of analyzing the characteristics of entertainment by dividing fixed-wing and rotary-wing flight information. For this, a model shoud be developed, and systematic big data collection and research should be conducted.

• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.33-40
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• 2021

Currently, the shipping and port industries are implementing strategies to improve port processing capabilities through the expansion and efficient operation of port logistics resources to survive fierce competition with rapidly changing trends. The calculation of the port's processing capacity is determined by the loading and unloading equipment installed at the dock, and the port's processing capacity can be improved through various methods, such as additional deployment of logistics resources or efficient operation of resources in use. However, it is difficult to expect an improvement effect in a short period of time because the additional deployment of logistics resources is clearly limited in time is clear. Therefore, it is a feasible way to find an efficient operation method for resources being used to improve processing capacity. Domestic ports are also actively promoting informatization and digitalization with the development of the 4th industrial revolution technology. However, the calculation of the number of Y/T (Yard Tractor) assignments in the current unloading process depends on expert experience, and related previous studies also focus on the allocations of Y/T or Calculation of the total number of Y/T required. Therefore, this study analyzed the factors affecting the number of Y/T allocations using the loading and unloading information of incoming ships, and based on this, cluster analysis, regression analysis, and deep neural network(DNN) model were used.