• Title/Summary/Keyword: Reliability Measures

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The Effects of Satisfaction with Culinary-Related Majors at Local Junior Colleges on Learning Immersion and Self-Efficacy

  • Pyoung-Sim Park
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.9
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    • pp.137-148
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    • 2023
  • This study investigated the influence of major satisfaction on learning flow and self-efficacy of students majoring in culinary arts at local junior colleges. In the 2022-2 semester, 260 freshmen and sophomore college students majoring in culinary from five junior colleges in the Gwangju and Jeonnam regions were analyzed. For data processing, SPSS Ver. 25.0 was used. The data is used to measure reliability by Cronbach's α, t-test, ANOVA, Pearson's correlation coefficient, and multiple regression analysis. The results of this study are as follows : First, there was a difference in satisfaction between freshmen and sophomores in major satisfaction with cooking related departments at local junior colleges. Second, there was a significant effect of satisfaction with cooking-related majors at local junior colleges on learning immersion. Third, there was a significant effect of satisfaction with cooking-related majors at local junior colleges on self-efficacy. In conclusion, it was found that major satisfaction affects learning immersion and self-efficacy for both students enrolled in cooking-related departments at local junior colleges. In the future, we suggest follow-up research on educational measures to increase learning immersion and self-efficacy for students who are not majoring in cooking in the high school curriculum and students who are insufficient in major classes due to part-time jobs during the semester.

The Effect of Happiness Sharing Kumdo Class Participating Adolescents' Achievement Goal Orientation on Ego-Resiliency and Quality of Life (행복나눔검도교실에 참여하는 청소년의 성취목표성향이 자아탄력성과 삶의 질에 미치는 영향)

  • Kim, Hyung-Ryong
    • Journal of Korea Entertainment Industry Association
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    • v.13 no.7
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    • pp.295-306
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    • 2019
  • The purpose of this study was to Happiness Sharing Kumdo Class Participating Adolescents' achievement goal orientation on ego-resiliency and quality of life and to provide guidance measures for the correct growth of vulnerable participants through the happiness sharing Kumdo class, which will be activated as a sports support program. To achieve the purpose of this research, 236 Adolescent participating in the Happiness Sharing Kumdo Class was selected and surveyed in Seoul, Gyeonggi Province and Incheon. Based on the data collected, the following results were derived by conducting frequency analysis, exploratory factor analysis, reliability analysis, correlation analysis, and multiple regression analysis. First, verification of the effect of achievement goal orientation of Adolescent participating in Happiness Sharing Kumdo Class on ego-resiliency showed that task-orientation has significant influence on diversity, future-orientation, and emotion control, and ego-orientation has significant influence on diversity and emotion control. Second, verification of the effect of achievement goal orientation of Adolescent participating in Happiness Sharing Kumdo Class on quality of life showed that task-orientation has significant influence on quality of physical, psychological, social, environmental and educational quality, and ego-orientation has a significant influence on quality of physical and environmental quality. Third, verification of the effect of ego-resiliency on quality of life by Adolescent participating in Happiness Sharing Kumdo Class showed that diversity has not significant influence all factors of quality of life, but future-orientation has significant influence on quality of psychological and environmental quality, and emotion control has a significant influence on quality of physical, psychological, social and educational quality.

Predicting Future ESG Performance using Past Corporate Financial Information: Application of Deep Neural Networks (심층신경망을 활용한 데이터 기반 ESG 성과 예측에 관한 연구: 기업 재무 정보를 중심으로)

  • Min-Seung Kim;Seung-Hwan Moon;Sungwon Choi
    • Journal of Intelligence and Information Systems
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    • v.29 no.2
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    • pp.85-100
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    • 2023
  • Corporate ESG performance (environmental, social, and corporate governance) reflecting a company's strategic sustainability has emerged as one of the main factors in today's investment decisions. The traditional ESG performance rating process is largely performed in a qualitative and subjective manner based on the institution-specific criteria, entailing limitations in reliability, predictability, and timeliness when making investment decisions. This study attempted to predict the corporate ESG rating through automated machine learning based on quantitative and disclosed corporate financial information. Using 12 types (21,360 cases) of market-disclosed financial information and 1,780 ESG measures available through the Korea Institute of Corporate Governance and Sustainability during 2019 to 2021, we suggested a deep neural network prediction model. Our model yielded about 86% of accurate classification performance in predicting ESG rating, showing better performance than other comparative models. This study contributed the literature in a way that the model achieved relatively accurate ESG rating predictions through an automated process using quantitative and publicly available corporate financial information. In terms of practical implications, the general investors can benefit from the prediction accuracy and time efficiency of our proposed model with nominal cost. In addition, this study can be expanded by accumulating more Korean and international data and by developing a more robust and complex model in the future.

Parameter Optimization and Uncertainty Analysis of the NWS-PC Rainfall-Runoff Model Coupled with Bayesian Markov Chain Monte Carlo Inference Scheme (Bayesian Markov Chain Monte Carlo 기법을 통한 NWS-PC 강우-유출 모형 매개변수의 최적화 및 불확실성 분석)

  • Kwon, Hyun-Han;Moon, Young-Il;Kim, Byung-Sik;Yoon, Seok-Young
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.4B
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    • pp.383-392
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    • 2008
  • It is not always easy to estimate the parameters in hydrologic models due to insufficient hydrologic data when hydraulic structures are designed or water resources plan are established. Therefore, uncertainty analysis are inevitably needed to examine reliability for the estimated results. With regard to this point, this study applies a Bayesian Markov Chain Monte Carlo scheme to the NWS-PC rainfall-runoff model that has been widely used, and a case study is performed in Soyang Dam watershed in Korea. The NWS-PC model is calibrated against observed daily runoff, and thirteen parameters in the model are optimized as well as posterior distributions associated with each parameter are derived. The Bayesian Markov Chain Monte Carlo shows a improved result in terms of statistical performance measures and graphical examination. The patterns of runoff can be influenced by various factors and the Bayesian approaches are capable of translating the uncertainties into parameter uncertainties. One could provide against an unexpected runoff event by utilizing information driven by Bayesian methods. Therefore, the rainfall-runoff analysis coupled with the uncertainty analysis can give us an insight in evaluating flood risk and dam size in a reasonable way.

Dynamic Nonlinear Prediction Model of Univariate Hydrologic Time Series Using the Support Vector Machine and State-Space Model (Support Vector Machine과 상태공간모형을 이용한 단변량 수문 시계열의 동역학적 비선형 예측모형)

  • Kwon, Hyun-Han;Moon, Young-Il
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.3B
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    • pp.279-289
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    • 2006
  • The reconstruction of low dimension nonlinear behavior from the hydrologic time series has been an active area of research in the last decade. In this study, we present the applications of a powerful state space reconstruction methodology using the method of Support Vector Machines (SVM) to the Great Salt Lake (GSL) volume. SVMs are machine learning systems that use a hypothesis space of linear functions in a Kernel induced higher dimensional feature space. SVMs are optimized by minimizing a bound on a generalized error (risk) measure, rather than just the mean square error over a training set. The utility of this SVM regression approach is demonstrated through applications to the short term forecasts of the biweekly GSL volume. The SVM based reconstruction is used to develop time series forecasts for multiple lead times ranging from the period of two weeks to several months. The reliability of the algorithm in learning and forecasting the dynamics is tested using split sample sensitivity analyses, with a particular interest in forecasting extreme states. Unlike previously reported methodologies, SVMs are able to extract the dynamics using only a few past observed data points (Support Vectors, SV) out of the training examples. Considering statistical measures, the prediction model based on SVM demonstrated encouraging and promising results in a short-term prediction. Thus, the SVM method presented in this study suggests a competitive methodology for the forecast of hydrologic time series.

A Comparative Study of Smart Manufacturing Innovation Supply Industry in Germany and Korea (독일과 한국의 스마트 제조혁신 전략에 대한 비교분석 및 시사점 - 양국의 공급산업 전략을 중심으로 -)

  • Sang-Jin Lee;Yun-Hyeok Choi;Jae Kyu Myung
    • Journal of Practical Engineering Education
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    • v.14 no.3
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    • pp.601-608
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    • 2022
  • This study examines the current status of smart manufacturing innovation policies in Germany and Korea, compares and analyzes the supply industry strategies of both countries, and suggests the direction for Korea's smart manufacturing innovation supply industry. Germany's supply industry strategy aims to strengthen the market dominance of domestic suppliers through high technology, compatibility, and high reliability based on reference for global demanding companies. On the other hand, the Korea's supply industry strategy remains at the level improvement of the demanding companies by stage, so it is time to take a long-term and consistent response with the goal of implementing smartization at the advanced level. By referring to Germany's supply industry strategy for the advancement of smart factories, it was intended to help in establishing government support policies and supplier strategies. In addition, based on the analysis results of the supply industry strategies of both countries, improvement measures for the advancement of Korea's smart factories were presented. Ultimately, the contents of this study can be used as basic data for policy establishment to strengthen the industrial competitiveness of Korea's small and medium-sized suppliers.

A Study on the Calculation of Load Resistance Factor of over Tension Anchors by Optimization Design (최적화 설계를 통한 과긴장 앵커의 하중-저항계수 산정 연구)

  • Soung-Kyu Lee;Yeong-Jin Lee;Yong-Jae Song;Tae-Jun Cho;Kang-Il Lee
    • Journal of the Korean Geosynthetics Society
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    • v.22 no.4
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    • pp.17-26
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    • 2023
  • To consider the risk of damage and fracture of P.C strands, the existing post-maintenance system alone has the limitations, hence it is necessary to quantitatively evaluate and predict the deterioration, durability and safety of facilities and establish a reasonable maintenance system considering the asset value of facilities. Therefore, it is worth considering a preventive maintenance plan that allows proactive measures to be taken before a major defect occurs in the temporary anchor. This study devised a preventive over tension method, reviewed its effectiveness through design and field tests, by calculating the resistance factors by performing a reliability-based optimization design. At this time, the over tension anchor method was evaluated using the ratio of the residual tension force after the fracture of P.C strands to the effective tension force before the fracture of P.C strand, followed by the resistance factor calculated by the optimal solution for each random variables using Excel solver and applying it to the limit state equations. As a result of the study, if the over tension ratio is 125% to 130%, the remaining strands showed a high resistance effect even after the fracture of P.C strand. As a result of the optimization design, it was found that it is appropriate to apply the load factor (γ) of 1.25, and the resistance factors of Φ1, Φ2, Φ3 as 0.7, 0.5, 0.6.

A Validation Study of the Korean Version of the Workplace Intergenerational Climate Scale(K-WICS) (한국판 세대친화적 조직문화척도(K-WICS) 타당화 연구)

  • Seoyeong Jeong;Hee Woong Park;Young Woo Sohn
    • Korean Journal of Culture and Social Issue
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    • v.29 no.4
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    • pp.429-453
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    • 2023
  • Due to recent demographic changes, employees from diverse generations now work together in organizations. Thus, there is a need for research on intergenerational cooperation. However, the lack of valid and reliable measures to capture intergenerational climate in the workplace is an obstacle to research. Therefore, we translated the Workplace Intergenerational Climate Scale(WICS) into Korean and validated it with a sample of 1,052 Korean full-time employees. Firstly, we conducted an exploratory factor analysis by using sample 1(N = 460) and revealed a five-factor solution. Secondly, the confirmatory factor analysis(sample 2; N = 592) showed a good model fit of the correlated five-factor model. Thirdly, the scale's discriminant and convergent validity was supported by negative correlations with four types of existing ageism scales and by positive correlations with trust, organizational commitment, work engagement, psychological safety, intention to remain, job satisfaction, and communication satisfaction. Moreover, it further demonstrated significant incremental validity in predicting positive outcome variables even when controlling for pre-existing agism scales. Lastly, we confirmed strict measurement invariance of the scale between the age groups(below 40 versus above 40). The findings support the reliability and validity of the Korean version of WICS among Korean employees. The scale will be broadly applied to measure intergenerational climate of organizations and provide practical implications for HR management.

Application of Back Analysis Technique Based on Direct Search Method to Estimate Tension of Suspension Bridge Hanger Cable (현수교 행어케이블의 장력 추정을 위한 직접탐색법 기반의 역해석 기법의 적용 )

  • Jin-Soo Kim;Jae-Bong Park;Kwang-Rim Park;Dong-Uk Park;Sung-Wan Kim
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.27 no.5
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    • pp.120-129
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    • 2023
  • Hanger cable tension is a major response that can determine the integrity and safety of suspension bridges. In general, the vibration method is used to estimate hanger cable tension on operational suspension bridges. It measures natural frequencies from hanger cables and indirectly estimates tension using the geometry conditions of the hanger cables. This study estimated the hanger cable tension of the Palyeong Bridge using a vision-based system. The vision-based system used digital camcorders and tripods considering the convenience and economic efficiency of measurement. Measuring the natural frequencies for high-order modes required for the vibration method is difficult because the hanger cable response measured using the vision-based system is displacement-based. Therefore, this study proposed a back analysis technique for estimating tension using the natural frequencies of low-order modes. Optimization for the back analysis technique was performed by defining the difference between the natural frequencies of hanger cables measured in the field and those calculated using finite element analysis as the objective function. The direct search method that does not require the partial derivatives of the objective function was applied as the optimization method. The reliability and accuracy of the back analysis technique were verified by comparing the tension calculated using the method with that estimated using the vibration method. Tension was accurately estimated using the natural frequencies of low-order modes by applying the back analysis technique.

The Effect of Participation in Survival Swimming Education on Underwater Anxiety and Water Safety Awareness of University Students (생존수영교육 참여가 대학생의 수중불안과 수상안전 의식에 미치는 영향)

  • Myung-Chul Lee;Kyung-Hun Han
    • Journal of the Korean Applied Science and Technology
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    • v.40 no.6
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    • pp.1201-1212
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    • 2023
  • This study aimed to analyze the changes in underwater anxiety and water safety consciousness among college students through participation in survival swimming education and the relationship between these changes and various factors. To achieve this, 200 college students who were participating in survival swimming education from universities located in the Busan-Ulsan-Gyeongnam region were selected as participants using convenience sampling. Among them, a final valid sample of 191 students was utilized. Data analysis was conducted using SPSS 25.0 statistical software, including exploratory factor analysis, reliability analysis, paired sample t-test, repeated measures ANOVA. The results are as follows: Firstly, college students who participated in survival swimming education showed a decrease in post-test underwater anxiety and an increase in water safety consciousness compared to pre-test. Secondly, the interaction between the groups based on the presence or absence of swimming education experience and time showed a significant effect only in the safety education, a sub-factor of water safety consciousness. Based on these results, the effectiveness of survival swimming education for college students could be confirmed, and further directions for expanding survival swimming education in university settings could be considered.