• Journal of the Korean Society for Library and Information Science
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• v.57 no.1
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• pp.213-231
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• 2023

The purpose of this study is to develop and present a model that can evaluate the data maturity of library. To achieve this goal, library data maturity model can be applied to library was designed by analyzing previous studies related to data maturity. As a result of this study, proposed data maturity model consisting of 19 evaluation factors in 5 areas was designed, and the maturity level was set to 5 levels. In the future, it will be possible to measure the data maturity of libraries participating in the library big data project using the data maturity evaluation model, and it can be expected that in the long term, it will be possible to present a direction for data-based library operation and data utilization development.

• ETRI Journal
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• v.28 no.2
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• pp.191-204
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• 2006

Many previous studies of data quality have focused on the realization and evaluation of both data value quality and data service quality. These studies revealed that poor data value quality and poor data service quality were caused by poor data structure. In this study we focus on metadata management, namely, data structure quality and introduce the data quality management maturity model as a preferred maturity model. We empirically show that data quality improves as data management matures.

• Informatization Policy
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• v.28 no.1
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• pp.43-63
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• 2021

The purpose of this research is to examine the relationships among data literacy, organizational culture, and data analytics maturity and the moderating effects of organizational culture. Analysis of the relationship between data literacy and data analytics maturity shows that the higher the data literacy competency of employees, the higher the organization's data analytics maturity. In examining the relationship between organizational culture and data analytics maturity, it is found that relationship culture and innovation culture are positively related to data analytics maturity. In addition, relationship culture and hierarchy culture show significant moderating effects. Relationship culture shows a synergistic effect, whereas hierarchy culture has a buffer effect between data literacy and data analytics maturity.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.98-107
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• 2018

In this paper, we propose a method to classify the skeletal maturity with a small amount of hand wrist X-ray image using deep learning-based meta-learning. General deep-learning techniques require large amounts of data, but in many cases, these data sets are not available for practical application. Lack of learning data is usually solved through transfer learning using pre-trained models with large data sets. However, transfer learning performance may be degraded due to over fitting for unknown new task with small data, which results in poor generalization capability. In addition, medical images require high cost resources such as a professional manpower and mcuh time to obtain labeled data. Therefore, in this paper, we use meta-learning that can classify using only a small amount of new data by pre-trained models trained with various learning tasks. First, we train the meta-model by using a separate data set composed of various learning tasks. The network learns to classify the bone maturity using the bone maturity data composed of the radiographs of the wrist. Then, we compare the results of the classification using the conventional learning algorithm with the results of the meta learning by the same number of learning data sets.

• Journal of Information Technology Applications and Management
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• v.14 no.1
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• pp.1-20
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• 2007

IT outsourcing becomes one of the important shills for managing diverse and complex information systems, SIA is considered as an one of the success factors for the successful outsourcing management. Since it helps to establish common goal and provides better visibility of trends and performance, the SLA process must go beyond mere measurement to include a methodology for the ongoing management of service levels, and for the continuous improvement of service activities, functions and processes. Despite SLA is one of the most important skills for the successful outsourcing, few studies have been conducted for academic as well as practical purpose. For this reason, The objective of this study is to develop an SLA's maturity model and empirically demonstrate how SLA's maturity level affects its Performance through SLA's maturity model. The major contributions of this study are in two areas. This study contributes to academicians as well as practitioners. First, from the academic perspectives this study tries investigating the maturity level of the SLA based on empirical data. Second, practitioners can self-test their firms' maturity level using the proposed model. The results of this study show that the SLA's maturity level affected positively SLA's performance. It is founded that the SLA's maturity level had a significant impact on SLA's performance.

• Korean Journal of Agricultural Science
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• v.49 no.1
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• pp.129-136
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• 2022

In this study, we aimed to develop a maturity classification model for tomatoes using hyperspectral imaging in the range of 400 - 1,000 nm. Fifty-seven tomatoes harvested in August and November of 2021 were used as the sample set, and hyperspectral data was extracted from the surfaces of these tomatoes. A combined method of SNV (standard normal variate) and SG (Savitzky-Golay) methods was used for the pre-processing of the hyperspectral data. In addition, the hyperspectral data were analyzed for all maturity stages and considering bandwidths with different FWHM (full width at half maximum) values of 2, 25, and 50 nm. The PCA (principal component analysis) method was used to analyze the principal components related to maturity stages for the tomatoes. As a result, 500 - 550 nm and 650 - 700 nm bands were found to be related to the maturity stages of tomatoes. In addition, PC1 and PC2 explained approximately 97% of the variance at all FWHM conditions and thus were used as input data for classification model training based on the SVM (support vector machine). The SVM models were able to classify tomato maturity into five stages (Green, Turning, Pink, Light red, and Red) with over 95% accuracy regardless of the FWHM condition. Therefore, it was considered that hyperspectral data with 50 nm FWHM and SVM is feasible for use in the classification of tomato maturity into five stages.

• Child Health Nursing Research
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• v.22 no.2
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• pp.137-144
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• 2016

Purpose: The purpose of this study was to investigate factors that influence maturity fears in elementary school girls. Methods: The participants were 118 3rd and 4th grade students from 3 elementary schools in 3 cities in Korea. Data were collected using questionnaires which included measurement scales for the relative variables and demographic data. Data were analyzed using t-test, ANOVA, Pearson correlation coefficients, and hierarchial regression analysis with SPSS/WIN 21.0. Results: The significant predictors of maturity fears were weight, father-child communication, frequency of maturity communication with father, and close relation with mother. Conclusion: For effective management of maturity fears in elementary school girls, programs including weight control, functional communication with father and supportive nurturance of mother should be developed.

• Journal of the Korean Home Economics Association
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• v.48 no.6
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• pp.71-82
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• 2010

This study examined the effects of parent-, peer-, and teacher-attachment on development of career maturity via the mediating effects of self concept. There were 2844 elementary school students, ages 12 to 13 years old, who participated in the Korean Youth Panel Survey. All data were used for the analyses. Gender differences were found in most of the variables, including attachment, self concept, and career maturity. The Structural Equation Modeling technique applied to the data revealed that there were both concurrent and lagged effects of attachment and self concept on career maturity. It was found that self concept played a mediating role on career maturity.

• Child Health Nursing Research
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• v.25 no.2
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• pp.95-102
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• 2019

Purpose: The purpose of this study was to identify factors associated with career maturity among Korean high school students. Methods: A descriptive cross-sectional design was adopted using secondary data from the 2012 Korean Welfare Panel Study (KoWePS). The participants were 496 high school students who completed the supplemental survey for children, which included items on career maturity, self-esteem, study stress, teacher attachment, relationship with parents, peer attachment, depression and anxiety. Descriptive statistics, the chi-square-test, the t-test, and a decision tree were used for data analysis. Results: The decision tree identified five final nodes predicting career maturity after forcing self-esteem as the first variable. The highest predicted rate of high career maturity was associated with high self-esteem, experience of career counseling, and high teacher attachment. The lowest predicted rate of high career maturity was associated with low self-esteem and low attachment to friends. Conclusion: Factors influencing career maturity were varied by levels of self-esteem in Korean high school students. Thus, it is necessary to develop different approaches to enhance career maturity according to levels of self-esteem.

• The Journal of Bigdata
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• v.6 no.1
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• pp.13-22
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• 2021

The purpose of this study is to develop and demonstrate a framework for evaluating the maturity of big data for effective data strategy establishment and efficient investment of companies. By supplementing the shortcomings of the evaluation developed so far, a framework was developed to evaluate the maturity of a company's big data in an integrated process. As a result, four evaluation areas of 'Vision and Strategy', 'Management', 'Analysis' and 'Utilization', assessment items for each area, detailed content, and criteria for each stage were derived. This was verified through a survey of entrepreneurs, and the maturity level of big data of domestic companies was confirmed. As a future research direction, it is proposed to develop detailed assessment factors according to the characteristics of each industry, to develop a data utilization framework according to the assessment results, and to improve validity and reliability through adjustment of verification targets.