• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.228-239
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• 2022

Many countries around the world using ICT technologies have various technologies to keep pace with the 4th industrial revolution, and various algorithms and systems have been developed accordingly. Among them, many industries and researchers are investing in unmanned automation systems based on AI. At the time when new technology development and algorithms are developed, decision-making by big data analysis applied to AI systems must be equipped with more sophistication. We apply, Pearson's correlation analysis is applied to six independent variables to find out the job satisfaction that office workers feel according to their job characteristics. First, a correlation coefficient is obtained to find out the degree of correlation for each variable. Second, the presence or absence of correlation for each data is verified through hypothesis testing. Third, after visualization processing using the size of the correlation coefficient, the degree of correlation between data is investigated. Fourth, the degree of correlation between variables will be verified based on the correlation coefficient obtained through the experiment and the results of the hypothesis test

• Korean Journal of Adult Nursing
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• v.26 no.4
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• pp.403-412
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• 2014

Purpose: The purpose of this study was to validate the Korean version of shortened Nursing Decision-Making Instrument developed by Lauri & $Salanter{\ddot{a}}$(2002). Methods: The subjects were 247 nurses working in eight hospitals of Korea. Data were collected by questionnaires from June to July, 2012 and were analyzed by Principal Component Analysis for construct validity and Cronbach's ${\alpha}$ coefficient for reliability. Results: Factor loadings of the four subscales ranged from .32 to .73. The explained variance from the four factors was 48.54% of the total variance. The factors were named 'implementation of plan, monitoring and evaluation', 'plans of action', 'data collection', and 'data processing and identification'. The first factor consisted of 6 items which explained 13.21% of the total variance and the second factor contained 8 items. The Cronbach's ${\alpha}$ coefficients of the four subscales were from .64 to .81. Conclusion: The Korean version of the shortened Nursing Decision-Making Instrument has satisfactory construct validity and reliability. However, that the scores of the analytic items weren't reversed unlike the analysis method of the original tools is the biggest limitation of this study. In addition, based on the fact that there were several discrepancies for item interpretation of Korean comparing to the findings of the instrument development study, repetitive researches would be suggested.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3C
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• pp.250-257
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• 2006

In this paper, we propose an efficient algorithm for the RDO mode decision in H.264/AVC encoder. Based on the properties of DCT coefficients and the RDO mode decision processing, we derive a new condition for detecting an error block having all-zero DCT coefficient (AZCB). (I)DCT, (I)Q, and entropy coding are skipped for AZCBs in the proposed algorithm. It makes the reduction of the computational complexity for the RDO mode decision. Simulation results show that the proposed algorithm achieves computational saving over 40% compared to the conventional method.

• Journal of Korean Academy of Nursing
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• v.42 no.4
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• pp.453-465
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• 2012

Purpose: The study was done to develop a shared decision-making scale for end-of-life patients in Korea. Methods: The process included construction of a conceptual framework, generation of initial items, verification of content validity, selection of secondary items, preliminary study, and extraction of final items. The participants were 388 adults who lived in one of 3 Korean metropolitan cities: Seoul, Daegu, or Busan. Item analysis, factor analysis, criterion related validity, and internal consistency were used to analyze the data. Data collection was done from July to October 2011. Results: Thirty-four items were selected for the final scale, and categorized into 7 factors explaining 61.9% of the total variance. The factors were labeled as sharing information (9 items), constructing system (7 items), explanation as a duty (5 items), autonomy (4 items), capturing time (3 items), participation of family (3 items), and human respect (3 items). The scores for the scale were significantly correlated among shared decision-making scale, terminating life support scale, and dignified dying scale. Cronbach's alpha coefficient for the 34 items was .94. Conclusion: The above findings indicate that the shared decision-making scale has a good validity and reliability when used for end-of-life patients in Korea.

• International Journal of Advanced Culture Technology
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• v.11 no.3
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• pp.310-314
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• 2023

The purpose of this study is to predict the remaining capacity of lithium-ion batteries and evaluate their performance using five artificial intelligence models, including linear regression analysis, decision tree, random forest, neural network, and ensemble model. We is in the study, measured Excel data from the CS2 lithium-ion battery was used, and the prediction accuracy of the model was measured using evaluation indicators such as mean square error, mean absolute error, coefficient of determination, and root mean square error. As a result of this study, the Root Mean Square Error(RMSE) of the linear regression model was 0.045, the decision tree model was 0.038, the random forest model was 0.034, the neural network model was 0.032, and the ensemble model was 0.030. The ensemble model had the best prediction performance, with the neural network model taking second place. The decision tree model and random forest model also performed quite well, and the linear regression model showed poor prediction performance compared to other models. Therefore, through this study, ensemble models and neural network models are most suitable for predicting the remaining capacity of lithium-ion batteries, and decision tree and random forest models also showed good performance. Linear regression models showed relatively poor predictive performance. Therefore, it was concluded that it is appropriate to prioritize ensemble models and neural network models in order to improve the efficiency of battery management and energy systems.

• The Journal of Korean Academic Society of Nursing Education
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• v.29 no.4
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• pp.371-380
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• 2023

Purpose: The purpose of this study is to determine the relationship between nursing students' biomedical and artificial intelligence (AI) ethical awareness, ethical values, professional self-concept, and ethical decision-making confidence, and to then identify factors that can influence their ethical decision-making confidence. Methods: This study employed a descriptive research method and was conducted from June 8 to 12, 2023, with 204 students from three nursing colleges in Korea. The collected data were analyzed by frequency and percentage, independent t-test, Pearson's correlation coefficient, and multiple regression using IBM SPSS 23.0. Results: The results of the multiple regression analysis showed that the regression model was significant (F=18.88, p<.001) and that professional self-concept (β=.46, p<.001), ethics education (β=.23, p<.001), AI ethical awareness (β=.16, p=.020), and relativistic ethical values (β=.14, p=.035) explained 34.6% of the nursing students' ethical decision-making confidence. Conclusion: It is necessary to include professional self-concept, AI ethical awareness, and ethical values contents when constructing the curriculums of educational programs in order to improve nursing students' ethical decision-making confidence.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.429-434
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• 2023

This is a single-group pre-post study conducted to determine the effect of a calligraphy program on nursing students' career decision-making self-efficacy and self- leadership. The data collected from 231 second-year nursing students were analyzed using SPSS WIN 25.0 to determine descriptive statistics, paired t-test to analyze the effect of calligraphy, and Pearson correlation coefficient to determine the relationship between career decision self-efficacy and self-leadership. After the program, both career decision self-efficacy (t=7.23, p<.001) and self-leadership (t=6.81, p<.001) improved. The analysis of career decision self-efficacy and self-leadership after the program showed a strong correlation (r=.849, p<.001). The results of this study are significant in that they validate the effectiveness of a calligraphy program in promoting self-leadership and career decision-making self-efficacy among nursing students who do not have clear career goals. Students' overall satisfaction with the calligraphy program was 4/5 points, and they most highly evaluated the smooth interaction between fellow students through the program. At a time when the importance of cultural arts education is gradually increasing in social and educational fields around the world, calligraphy has the advantage of laying the foundation for the promotion of basic arts for the revitalization of cultural arts, so educational support is needed not only in terms of improving the quality of life and pursuing self-actualization of individuals with emotional expression and creative problem-solving skills, but also at the social level.

• Journal of Korea Water Resources Association
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• v.43 no.6
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• pp.559-569
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• 2010

This study proposes an empirical method for estimating the concentration time and storage coefficient of a basin using the Nash unit hydrograph. This method is based on the analytically derived concentration time and storage coefficient of the Nash model. More fundamentally, this method recursively searches convergent number of linear reservoirs and storage coefficient of linear reservoir representing the basin given. This method is to overcome the problem of HEC-HMS to use an optimization technique to estimate the basin concentration time and storage coefficient. The proposed method was applied to the Bangrim station of the Pyungchang river basin, also found to estimate physically reasonable values.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.4
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• pp.33-43
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• 2010

In this paper, we propose a floral scent recognition using odor sensors and a odor display using odor distribution system. Proposed odor recognition has method of correlation coefficient between sensors that select optimal sensors in floral scent recognition system of selective multi-sensors. Proposed floral scent recognition system consists of four module such as floral scent acquisition module, optimal sensor decision module, entropy-based floral scent detection module, and floral scent recognition module. Odor distribution system consists of generation module of distribution information, control module of distribution, output module of distribution. We applied to floral scent recognition for performance evaluation of proposed sensors decision method. As a result, application of proposed method with floral scent recognition obtained recognition rate of 95.67% case of using 16 sensors while applied floral scent recognition system of proposed sensor decision method confirmed recognition rate of 96% using only 8 sensors. Also, we applied to odor display of proposed method and obtained 3.18 thorough MOS experimentation.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.177-179
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• 1993

Best generation mix belongs to a multi attribute decision making, because we should consider many uncertain factors and choose the best one of the alternatives. Sugeno's fuzzy integral has been used as the solution of multi attribute decision making, but the exact value of the coefficient $\lambda$ hat not known yet which is needed to calculate fuzzy measure. This paper proposes the new method to calculate fuzzy measure without fixing the value of $\lambda$. The proposed method considers $\lambda$ as a probability distribution function and calculated expectation of fuzzy measure. The method is applied to the test system and the validity of the method is verified.