• Transactions of the Korean Society of Pressure Vessels and Piping
• /
• v.17 no.1
• /
• pp.36-48
• /
• 2021

As the material aging of nuclear power plants has been progressing in domestic and overseas, crack growth becomes one of the most important issues. In this respect, the crack growth assessment has been considered an essential part of structural integrity. The crack growth assessment for nuclear power plants has been generally performed based on ASME B&PV Code, Sec. XI but the idealization of crack shape and the conservative solutions of stress intensity factor (SIF) are used. Although finite element analysis (FEA) based on iterative crack growth analysis is considered as an alternative method to simulate crack growth, there are yet no guidelines to model the crack-tip spider-web mesh for such analysis. In this study, effects of various meshing factors on FE SIF calculation are systematically examined. Based on FEA results, proper criteria for spider-web mesh in crack-tip are suggested. The validation of SIF calculation method through mapping initial stress field is investigated to consider initial residual stress on crack growth. The iterative crack-tip modeling program to simulate crack growth is developed using the proposed criteria for spider-web mesh design. The SIF results from the developed program are validated by comparing with those from technical reports of other institutes.

• Korean Journal of Childcare and Education
• /
• v.16 no.1
• /
• pp.115-143
• /
• 2020

Objective: The purpose of this study was to examine underlying types of developmental trajectories of adaptation to child care among infants and toddlers. This study also aimed to identify latent classes in their child care adaptation types in order to find predictors that account for individual differences. Methods: Participants were 420 mothers of infants and toddlers and 123 teachers. The levels of child care adaptation of participating infants and toddlers were rated monthly from early April to June, 2019. The collected data were analyzed using growth mixture modeling, latent class analysis and multinominal logistic analysis. Results: The results of growth trajectories of child care adaptation showed there were two to four latent groups by dimension of child care adaptation. Also, the groups of individual dimensions of child care adaptation were classified into three latent classes, which were 'complying and positive group', 'negative group', and 'individualized group. Multinominal logistic analysis revealed that children's age, gender, and temperament differentiated the three latent classes of adaptation to child care. Conclusion/Implications: The results show individual characteristics that infants and toddlers possess should be prudently considered in order for successful adaptation to child care.

• The Korean Journal of Franchise Management
• /
• v.13 no.4
• /
• pp.1-12
• /
• 2022

Purpose: In 2020, the franchise industry accomplished a significant growth compared to the previous year, as the number of franchise companies increased by 9.0% while the number of franchise brands increased by 12.5%. Despite growth in size, the Korean franchise industry underwent many negative incidents, such as franchise ownership sales to private equity funds, that led to deterioration of businesses. From this point of view, this study aims to make various proposals to help policy makers develop franchise industry policies by analyzing trends of the current and previous presidential administrations' franchise policies and regulations using newspaper articles. Research design, data and methodology: A total of 7,439 articles registered in Naver API from February 25, 2013 to November 29, 2021 were extracted. Among them, 34 unrelated video articles were deleted, and a total of 7,405 articles from both administrations were used for analysis. The R package was used for word frequency analysis, word clouding, word correlation analysis, and LDA (Latent Dirichlet Allocation) topic modeling. Results: The keyword frequency analysis shows that the most frequently mentioned keywords during the previous administration include 'no-brand', 'major company', 'bill', 'business field', and 'SMEs', and those mentioned during the current administration include 'industry' and 'policy'. As a result of LDA topic modeling, 9 topics such as 'global startups' and 'job creation' from the previous administration, and 10 topics such as 'franchise business' and 'distribution industry' from the current administration were derived. The results of LDAvis showed that the previous administration operated a policy based on mutual growth of large and small businesses rather than hostile regulations in the franchise business, whereas the current administration extended the regulation related to franchise business to the employment sector. Conclusions: The analysis of past two administrations' franchise policy, it can be suggested that franchisors and franchisees may complement each other in developing the Fair Transactions in Franchise Business Act and achieving balanced growth. Moreover, political support is needed for sound development of franchisors. Limitations and future research suggestions are presented at the end of this study.

• Journal of Korea Society of Industrial Information Systems
• /
• v.3 no.1
• /
• pp.67-77
• /
• 1998

Reliability growth testing used to evaluate reliability in the automobile industry have not always been able to correctly address reliability concerns with increased confidence. The demand to confirm to all product performance requirements under various operating environments has added to the complexity of accurately assessin theproduct's reliability in the required development time. In addition, it is often desired to determine the relationship of a product's reliability to cost, development time, design, manufacturability and assembly. This paper presents the methods for reliability growth modeling to evaluate and interpret reliability concerns to support the reliability analysis of automobile assemblies and systems. This reliability growth modeling process is a mechanism to help "build in" reliability during early phases in the vehicle devleopment stage.

• Journal of the Korea Convergence Society
• /
• v.10 no.2
• /
• pp.217-225
• /
• 2019

The Latent Growth Modeling(LGM) is known as the typical analysis method of longitudinal data and it could be classified into unconditional model and conditional model. It is common to assume that the growth trajectory of unconditional model of LGM is linear. In the case of quasi-linear, the methodology for improving the model fitness using Sequential Pattern of Association Rule Mining is suggested. To do this, we divide longitudinal data into quintiles and extract periodic changes of the longitudinal data in each quintiles and make sequential pattern based on this periodic changes. To evaluate the effectiveness, the LGM module in SPSS AMOS was used and the dataset of the Youth Panel from 2001 to 2006 of Korea Employment Information Service. Our methodology was able to increase the fitness of the model compared to the simple linear growth trajectory.

• The Korean Journal of Franchise Management
• /
• v.12 no.4
• /
• pp.13-23
• /
• 2021

Purpose: This study aimed to derive clues for the franchise industry to overcome difficulties such as various legal regulations and social responsibility demands and to continuously develop by analyzing the research trends related to franchises published in Korea. Research design, data and methodology: As a result of searching for 'franchise' in ScienceON, abstracts were collected from papers published in domestic academic journals from 1994 to June 2021. Keywords were extracted from the abstracts of 1,110 valid papers, and after preprocessing, keyword analysis, TF-IDF analysis, and topic modeling using LDA algorithm, along with trend analysis of the top 20 words in TF-IDF by year group was carried out using the R-package. Results: As a result of keyword analysis, it was found that businesses and brands were the subjects of research related to franchises, and interest in service and satisfaction was considerable, and food and coffee were prominently studied as industries. As a result of TF-IDF calculation, it was found that brand, satisfaction, franchisor, and coffee were ranked at the top. As a result of LDA-based topic modeling, a total of 12 topics including "growth strategy" were derived and visualized with LDAvis. On the other hand, the areas of Topic 1 (growth strategy) and Topic 9 (organizational culture), Topic 4 (consumption experience) and Topic 6 (contribution and loyalty), Topic 7 (brand image) and Topic 10 (commercial area) overlap significantly. Finally, the trend analysis results for the top 20 keywords with high TF-IDF showed that 10 keywords such as quality, brand, food, and trust would be more utilized overall. Conclusions: Through the results of this study, the direction of interest in the franchise industry was confirmed, and it was found that it was necessary to find a clue for continuous growth through research in more diverse fields. And it was also considered an important finding to suggest a technique that can supplement the problems of topic trend analysis. Therefore, the results of this study show that researchers will gain significant insights from the perspectives related to the selection of research topics, and practitioners from the perspectives related to future franchise changes.

• Korean Journal of Child Studies
• /
• v.30 no.4
• /
• pp.69-85
• /
• 2009

The purpose of this study was to identify developmental trajectories of externalizing problems in preschoolers and to investigate dimensions of temperament and parental behaviors associated with trajectory groups. Subjects were 180 3- to 5-year-old preschoolers (96 males, 84 females) in the metropolitan area of Seoul. They were assessed three times at 5 month intervals over a one year period. Teachers reported on children's behavior problems, and parents reported on children's temperaments. Latent Growth Curve Modeling Analysis with cohort sequential design revealed externalizing behaviors gradually decreased between 3 and 6. At the 6-year-old level externalizing behaviors were associated with high novelty seeking temperament. The results were discussed in terms of the importance of longitudinal research in developmental psychopathology.

• Korean Journal of Child Studies
• /
• v.31 no.3
• /
• pp.83-97
• /
• 2010

Growth mixture modeling was used to identify types of changes in overt aggression from Grades 4 to 7 among a sample from the Korean Youth Panel Survey. Three discrete patterns were found to adequately explain changes of overt aggression in both boys and girls : Persistent intermediate aggression; Increasing aggression; and Decreasing aggression. Most boys (93%) fell into the Persistent intermediate aggression group and 49% of girls were found to fall into the Increasing aggression group. This suggests that prevention programs should recognize that girls are at risk of increasing aggression in their early adolescence. Multinomial logistic regression analysis shows that self-control, child abuse, peer support, and involvement with deviant peers at Grades 4 were all strongly associated with trajectory class membership. These associations did not differ by gender. These findings suggest that prevention programs should focus on the multiple risk factors of both boys and girls.

• Journal of Digital Convergence
• /
• v.16 no.6
• /
• pp.85-93
• /
• 2018

The Latent Growth Modeling(LGM) is known as the arising analysis method of longitudinal data and it could be classified into unconditional model and conditional model. Unconditional model requires estimated value of intercept and slope to complete a model of fitness. However, the existing LGM is in absence of a structured methodology to estimate slope when longitudinal data is neither simple linear function nor the pre-defined function. This study used Sequential Pattern of Association Rule Mining to calculate slope of unconditional model. The applied dataset is 'the Youth Panel 2001-2006' from Korea Employment Information Service. The proposed methodology was able to identify increasing fitness of the model comparing to the existing simple linear function and visualizing process of slope estimation.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2004.07a
• /
• pp.33-36
• /
• 2004

The process modeling for the growth rate in pulsed laser deposition(PLD)-grown ZnO thin films is investigated using neural networks(NNets) and the process recipes is optimized via genetic algorithms(GAs). D-optimal design is carried out and the growth rate is characterized by NNets based on the back-propagation(BP) algorithm. GAs is then used to search the desired recipes for the desired growth rate. The statistical analysis is used to verify the fitness of the nonlinear process model. This process modeling and optimization algorithms can explain the characteristics of the desired responses varying with process conditions.