The purpose of this study is to develop a perceived elderly stigma scale for intergenerational research and practice. Although negative stereotypes on elderly population have worsened physical and psychological health of older people, there has been a lack of systematic efforts to measure and monitor stigmatic perception and behavior of younger generation on elderly people. We initially constructed a 34-item perceived elderly stigma scale, by integrating the processes of literature review and exploratory item generation. After confirming the face validity of the scale, a 31-item perceived elderly stigma scale was tested with 252 adults recruited from an online research panel. The result of an exploratory factor analysis suggests a 5-factor solution with 28 items: ability, personality, appearance, authoritarian dependancy, and family-obsession. The convergent/discriminant validity was confirmed by examining its relationships with ageism, elderly discrimination, attitude toward elderly, and respect for elderly. After a series of refinement and empirical tests, the perceived elderly stigma scale would contribute to understanding the current state of elderly discrimination in our society and to develop necessary policies and promotion strategies to eliminate intergenerational conflicts.
Journal of the Korea Academia-Industrial cooperation Society
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v.21
no.12
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pp.310-319
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2020
Korea estimates the traffic noise by measuring the total traffic noise when the traffic passes (SPB; Statistical Pass-By). Another method (CPX; Close Proximity) directly measures the tire/road noise by installing a microphone near the tire. The CPX method is not a formal test method in Korea. There has been little research between CPX and SPB. This study proposes a method for estimating SPB, using the CPX, which is easy to measure. This study used the results of a large-scale test conducted by Korea Expressway Corporation (KEC) and a research paper on CPX in this section. The results by the KEC showed that the low noise pavement has a noise reduction of 10.4dB. In CPX research, the noise reduction was 10.7dB and was similar to 10.4dB in SPB. This study shows why the noise reduction is the same regardless of the position, the reason that the amount of noise reduction is similar, the difference of the noise according to the position of the microphone using the concept of noise summation and distance reduction. This study shows that including the CPX as a variable in the traffic noise prediction program is very important to improve noise prediction reliability.
Objectives: The purpose of this study was to identify new variables that can enhance adult oral health behaviors by confirming the degree of adult e-health literacy, oral health knowledge, and oral health behaviors and examining their relevance. Methods: A self-reported questionnaire was filled out by 350 adults from June 22 to August 1, 2021. Data were analyzed using SPSS 23.0. independent t-test, one way ANOVA, the scheffé post-hoc test and the pearson correlation coefficients were reviewed, A hierarchical regression analysis was conducted. Results: Oral health behaviors according to general characteristics showed significant differences in gender, educational background, dental visit within 1 year, subjective oral health status, oral health interest, frequency of oral internet use, and reliability of internet oral health information. Also it was found that e-health literacy affects oral health behavior. Conclusions: In this study, e-health literacy, oral health knowledge, and oral health behavior were correlated and it was confirmed that e-health literacy had an effect on oral health behavior. In the future, it is necessary to develop a tool that can measure e-oral health literacy and to find a way to improve the oral health behavior of adults by using e-oral health literacy.
Journal of the Korean Society for information Management
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v.39
no.2
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pp.233-254
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2022
Link reduction algorithms such as pathfinder network are the widely used methods to overcome problems with the visualization of weighted networks for knowledge domain analysis. This study proposed NetRSQ, an indicator to measure the goodness of fit of a link reduction algorithm for the network visualization. NetRSQ is developed to calculate the fitness of a network based on the rank correlation between the path length and the degree of association between entities. The validity of NetRSQ was investigated with data from previous research which qualitatively evaluated several network generation algorithms. As the primary test result, the higher degree of NetRSQ appeared in the network with better intellectual structures in the quality evaluation of networks built by various methods. The performance of 4 link reduction algorithms was tested in 40 datasets from various domains and compared with NetRSQ. The test shows that there is no specific link reduction algorithm that performs better over others in all cases. Therefore, the NetRSQ can be a useful tool as a basis of reliability to select the most fitting algorithm for the network visualization of intellectual structures.
This study aims to develop the trustworthiness model for public digital records, as an admissibility framework for establishing trust. The trustworthiness model is deemed to used to identify the qualities of the digital records in their lifecycle, including the identity that could be identified at the time of the creation, integrity obtained from the chain-of-custodial management, the evidence of relationship between business activities and records, and the technical or cognitive accessibility. Based on the analysis of the QADEP model, it was decided to develop a model that could measure the trustworthiness of public digital records in the external measurement type, which are authenticity, reliability, and usability. In line with this direction, the model expanded measurement areas and indicators of the QADEP model through the analysis of ISO 16175-1:2020, and measuring metrics was also proposed so that it could be a measuring instrument for public digital records in Korea, after analysing NAK 19-3. It would be useful to expand the model and to test the approach of the trustworthiness model for public digital records.
The size of the cryptocurrency market is growing. For example, market capitalization of bitcoin exceeded 500 trillion won. Accordingly, many studies have been conducted to predict the price of cryptocurrency, and most of them have similar methodology of predicting stock prices. However, unlike stock price predictions, machine learning become best model in cryptocurrency price predictions, conceptually cryptocurrency has no passive income from ownership, and statistically, cryptocurrency has at least three times higher liquidity than stocks. Thats why we argue that a methodology different from stock price prediction should be applied to cryptocurrency price prediction studies. We propose Reverse Walk-forward Validation (RWFV), which modifies Walk-forward Validation (WFV). Unlike WFV, RWFV measures accuracy for Validation by pinning the Validation dataset directly in front of the Test dataset in time series, and gradually increasing the size of the Training dataset in front of it in time series. Train data were cut according to the size of the Train dataset with the highest accuracy among all measured Validation accuracy, and then combined with Validation data to measure the accuracy of the Test data. Logistic regression analysis and Support Vector Machine (SVM) were used as the analysis model, and various algorithms and parameters such as L1, L2, rbf, and poly were applied for the reliability of our proposed RWFV. As a result, it was confirmed that all analysis models showed improved accuracy compared to existing studies, and on average, the accuracy increased by 1.23%p. This is a significant improvement in accuracy, given that most of the accuracy of cryptocurrency price prediction remains between 50% and 60% through previous studies.
Journal of the Korea Society of Computer and Information
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v.28
no.3
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pp.91-100
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2023
This study is a case study comparing and examining the effects of non-face-to-face(NFTF) classes in the 2021-2 semester and face-to-face(FTF) classes in the 2022-2 semester on learning immersion, learning stress, and learning satisfaction. The learning immersion and learning satisfaction of 240 students were analyzed in NFTF and FTF classes of department S of C junior college where the same textbook, same subject, and same professor were taught. For data processing, SPSS Ver. 23.0 was used. The data is used to measure reliability by Cronbach's α, t-test, Pearson's correlation coefficient, and multiple regression analysis. The results of this study are as follows. First, learners' learning immersion was higher in FTF than NFTF classes among engineering major subjects. Second, it was found that there was a difference in learning stress according to the types of FTF and NFTF classes in engineering major subjects. Third, it was found that there were differences in practice content, communication, and task performance of sub-factors of learning satisfaction according to FTF and NFTF class types in engineering major subjects. In conclusion, it was found that FTF classes had a more positive effect on learning immersion and satisfaction, and NFTF classes had a more negative effect on learning stress.
The Journal of the Korea institute of electronic communication sciences
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v.17
no.6
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pp.1013-1024
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2022
In addition to the assessment measure of electric quality levels, load loss are also a factor in hindering the financial profits of electrical sales companies. Therefore, accurate analysis of load losses generated from distributed power networks is very important. The accurate calculation of load losses in the distribution line has been carried out for a long time in many research institutes as well as power utilities around the world. But it is increasingly difficult to calculate the exact amount of loss due to the increase in the congestion of distribution power network due to the linkage of distributed energy resources(DER). In this paper, we develop smart grid big data infrastructure in order to accurately analyze the load loss of the distribution power network due to the connection of DERs. Through the preprocess of data selected from the smart grid big data, we develop a load loss analysis model that eliminated 'veracity' which is one of the characteristics of smart grid big data. Our analysis results can be used for facility investment plans or network operation plans to maintain stable supply reliability and power quality.
Purpose: How to build the attitude on brand is very important, because it affects the positive word of mouth and revisit intention. Brand attachment, brand name, and image congruence play important role on consumer behavior in terms of reinforcing consumers' perception of food service companies and differentiating them from competing brands. Following the planned behavior theory, this paper examines the effect of linking brand attitude to word-of-mouth and revisit intentions in the restaurant sector. Research design, data, and methodology: This paper examines the structural relationship among brand attachment, brand name, image congruence, brand attitude, WOM, and revisit intention. In order to test the purposes of this study, research model and hypotheses were developed. The questionnaire items were modified and used according to the content of this study based on previous studies. All constructs were measured by multiple items tested and developed in the previous research. The study is based on the quantitative method and considered 519 questionnaires fulfilled by customers of restaurants. The data were explored employing the partial least square-structural equation modelling (PLS-SEM). Frequency analysis was conducted to identify the general characteristics of the survey subjects. To measure the reliability and validity of the measurement tools, confirmatory factor analysis was conducted. Structural model analysis was conducted to verify the research model. Result: The findings demonstrate that brand attachment and brand name had positive effects on attitude while image congruence did not have. Also, attitude had positive effect on WOM and revisit intention. Conclusions: This study expands the literature about WOM and revisit intentions. This study expands prior research in a similar field to which the theory of planned behavior (TPB) is applied, and reveals that brand attachment, brand name, and brand image congruence play an important role in developing brand attitude that affect revisit intention and WOM. And provide guidelines on how to enhance competitiveness in the restaurant sector based on understanding of linking brand attitude to customer loyalty and repeat business. By putting into practice these suggestions in the restaurant industry, brands can easily build up their attitude and boost a positive WOM and the intention to revisit.
Journal of Korea Entertainment Industry Association
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v.15
no.7
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pp.87-96
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2021
The purpose of this study is to analyze the problems of the Physical Activity Promotion System(PAPS) implemented in elementary, middle, and high schools in Korea and to prepare improvement measures. The data of the study was obtained through in-depth interviews, related papers, and press releases. The research participants of this study were 5 incumbent physical education teachers who directly instruct and measure PAPS at school and 5 college students who directly experienced PAPS. The results of the study are as follows. First, the problems that occurred in the educational environment of PAPS were students' indifference, teachers' passive guidance, and decreased physical education hours replaced by PAPS measurement days. Second, the problems occurring in the measurement environment of PAPS were errors due to measurement equipment, deviations due to different measurement locations, and differences in grades according to measurement items. Third, the problems that occur in the measurement process of PAPS are the lack of measurement personnel, the expedient physical fitness measurement, and the non-standardized measurement method. In order to improve these problems and successfully apply PAPS, the following improvement measures should be attempted. Details on this are as follows. First, teachers should inspire students' interest and interest in PAPS. Second, it is necessary to secure the reliability of the measurement result value of PAPS. Third, it is necessary to systematically supplement the school education system for PAPS measurement.
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