• Journal of Digestive Cancer Research
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• 제11권3호
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• pp.157-164
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• 2023

Prediction is a significant topic in clinical research. The development and validation of a prediction model has been increasingly published in clinical research. In this review, we investigated analytical methods and validation schemes for a clinical prediction model used in digestive cancer research. Deep learning and logistic regression, with split-sample validation as an internal or external validation, were the most commonly used methods. Furthermore, we briefly introduced and summarized the advantages and disadvantages of each method. Finally, we discussed several points to consider when conducting prediction model studies.

• Journal of Korea Trade
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• 제24권8호
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• pp.171-188
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• 2020

Purpose - This is an exploratory study that aims to apply text mining techniques, which computationally extracts words from the large-scale text data, to legal documents to quantify trade claim contents and enables statistical analysis. Design/methodology - This is designed to verify the validity of the application of text mining techniques as a quantitative methodology for trade claim studies, that have relied mainly on a qualitative approach. The subjects are 81 cases of arbitration and court judgments from China published on the website of the UNCITRAL where the CISG was applied. Validation is performed by comparing the manually analyzed result with the automatically analyzed result. The manual analysis result is the cluster analysis wherein the researcher reads and codes the case. The automatic analysis result is an analysis applying text mining techniques to the result of the cluster analysis. Topic modeling and semantic network analysis are applied for the statistical approach. Findings - Results show that the results of cluster analysis and text mining results are consistent with each other and the internal validity is confirmed. And the degree centrality of words that play a key role in the topic is high as the between centrality of words that are useful for grasping the topic and the eigenvector centrality of the important words in the topic is high. This indicates that text mining techniques can be applied to research on content analysis of trade claims for statistical analysis. Originality/value - Firstly, the validity of the text mining technique in the study of trade claim cases is confirmed. Prior studies on trade claims have relied on traditional approach. Secondly, this study has an originality in that it is an attempt to quantitatively study the trade claim cases, whereas prior trade claim cases were mainly studied via qualitative methods. Lastly, this study shows that the use of the text mining can lower the barrier for acquiring information from a large amount of digitalized text.

• 대한간호학회지
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• 제45권2호
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• pp.240-250
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• 2015

Purpose: The purpose of this study was to validate the Korean version of the Ethical Leadership at Work questionnaire (K-ELW) that measures RNs' perceived ethical leadership of their nurse managers. Methods: The strong validation process suggested by Benson (1998), including translation and cultural adaptation stage, structural stage, and external stage, was used. Participants were 241 RNs who reported their perceived ethical leadership using both the pre-version of K-ELW and a previously known Ethical Leadership Scale, and interactional justice of their managers, as well as their own demographics, organizational commitment and organizational citizenship behavior. Data analyses included descriptive statistics, Pearson correlation coefficients, reliability coefficients, exploratory factor analysis, and confirmatory factor analysis. SPSS 19.0 and Amos 18.0 versions were used. Results: A modified K-ELW was developed from construct validity evidence and included 31 items in 7 domains: People orientation, task responsibility fairness, relationship fairness, power sharing, concern for sustainability, ethical guidance, and integrity. Convergent validity, discriminant validity, and concurrent validity were supported according to the correlation coefficients of the 7 domains with other measures. Conclusion: The results of this study provide preliminary evidence that the modified K-ELW can be adopted in Korean nursing organizations, and reliable and valid ethical leadership scores can be expected.

• Journal of Preventive Medicine and Public Health
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• 제56권1호
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• pp.12-20
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• 2023

Quantitative and qualitative research explore various social phenomena using different methods. However, there has been a tendency to treat quantitative studies using complicated statistical techniques as more scientific and superior, whereas relatively few qualitative studies have been conducted in the medical and healthcare fields. This review aimed to provide a proper understanding of qualitative research. This review examined the characteristics of quantitative and qualitative research to help researchers select the appropriate qualitative research methodology. Qualitative research is applicable in following cases: (1) when an exploratory approach is required on a topic that is not well known, (2) when something cannot be explained fully with quantitative research, (3) when it is necessary to newly present a specific view on a research topic that is difficult to explain with existing views, (4) when it is inappropriate to present the rationale or theoretical proposition for designing hypotheses, as in quantitative research, and (5) when conducting research that requires detailed descriptive writing with literary expressions. Qualitative research is conducted in the following order: (1) selection of a research topic and question, (2) selection of a theoretical framework and methods, (3) literature analysis, (4) selection of the research participants and data collection methods, (5) data analysis and description of findings, and (6) research validation. This review can contribute to the more active use of qualitative research in healthcare, and the findings are expected to instill a proper understanding of qualitative research in researchers who review qualitative research reports and papers.

• 대한간호학회지
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• 제50권6호
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• pp.848-862
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• 2020

Purpose: The purpose of this study was to develop an instrument to evaluate the needs satisfaction of nurses and examine its validity and reliability. Methods: The initial items for the instrument were developed through a literature review and interviews, using the conceptual framework of Maslow's hierarchy of needs theory. The initial items were evaluated for content validity by 14 experts. Four hundred and eighty-six clinical nurses participated in this study through offline and online surveys to test the reliability and validity of the instrument. The first evaluation (n = 256) was used for item analysis and exploratory factor analysis, and the second evaluation (n = 230) was used to conduct a confirmatory factor analysis and to assess the criterion-related validity and internal consistency of the instrument. Test-retest reliability was analyzed using data from 30 nurses. Results: The final instrument consisted of 30 items with two sub-factors for five needs that were identified through the confirmatory factor analysis. The criterion-related validity was established using the five need satisfaction measures (r = .56). Cronbach's α for total items was .90, and test-retest reliability was .89. Conclusion: The findings from this study indicate that this instrument has sufficient validity and reliability. This instrument can be used for the development of nursing interventions to improve the needs satisfaction of clinical nurses.

• 임상간호연구
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• 제27권3호
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• pp.279-293
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• 2021

Purpose: The purpose of this study was to develop a Korean nursing work environment scale for critical care nurses (KNWES-CCN) and verify its validity and reliability. Methods: A total of 46 preliminary items were selected using content validity analysis of experts on 64 candidate items derived through literature reviews and in-depth interviews with critical care nurses. 535 critical care nurses from 21 hospitals responded to the preliminary questionnaire from February to March 2021. The collected data were analysed using construct, convergent and discriminant validities, and internal consistency and test-retest reliability. Results: The 23 items in 4 factors accounted for 55.6% of the total variance were identified through item analysis and exploratory factor analysis (EFA). EFA was performed with maximum likelihood method including direct oblimin method. In the confirmatory factor analysis, KNWES-CCN consisted of 21 items in 4 factors by deleting the items that were not meet the condition that the factor loading over .50 or the squared multiple correlation over .30. This model was considered to be suitable because it satisfied the fit index and acceptable criteria of the model [𝒳²=440.47 (p<.001), CMIN/DF=2.41, GFI=.86, SRMR=.06, RMSEA=.07, TLI=.90, CFI=.91]. The item total correlation values ranged form .32 to .73 and its internal consistency was Cronbach's α=.92. The reliability of the test-retest correlation coefficient was .72 and the intra-class correlation coefficient was .83. Conclusion: The KNWES-CCN showed good validity and reliability. Therefore, it is expected that the use of this scale would measure and improve nursing work environment for critical care nurses in Korea.

• 디지털융복합연구
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• 제11권3호
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• pp.101-113
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• 2013

기존의 방법론 관련 문헌에서는 반영적 지표를 기반으로 다측정 지표들의 개발과 타당성 검정에 관한 다양한 문헌적 고찰을 수행하였음에도 불구하고 형성적 지표에 대한 관심은 부족하였다. 본 연구의 목적은 형성적 지표를 사용함에 있어서 필요한 접근법에 대한 연구자들의 이해를 돕기 위함이다. 또한 연구자들이 자신의 모델을 위해 필요한 적합한 지표의 선택에 도움을 제공하기 위해 형성적 지표의 본질에 대해서도 살펴보고자 한다. 이를 위해 형성적 지표에 대한 기반이론을 살펴보고 다음으로 실증 분석에서 사용된 사례를 통해 형성적 지표의 접근법과 연구수행 절차에 대해 살펴본다. 마지막으로 실증 연구에서 지표의 사용에 관한 제언을 하고자 한다.

• International Journal of Quality Innovation
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• 제7권1호
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• pp.128-160
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• 2006

With the globalization of economy, industries are facing increasingly greater challenges. Business integration, both internally and externally, is undoubtedly an important topic. However, how does an enterprise create its own value will be the key to an enterprise's success in the future. Therefore, this study bases on the evaluation of company value to assess the key factors and competitive strategies of an enterprise. Yet, only with stable enterprise performance can the company value be correctly evaluated. This will be an important issue for enterprise performance and business strategy. Subject of this study are mainly small and medium-sized (enterprises (SMEs). Model construction for SME value assessment is established through the system dynamics approach. Scholars' opinions on literature validation and application of Delphi Method are explored through literature review on local and foreign studies, in order to compile the relevant perspectives and indices for enterprise value creation. Hence model construction of the value creation system is established, and the correlation between the perspectives and related factors is explored to understand the overall dynamics model of SMEs' value creation system. Consequently, a research method based on the system dynamics perspective is provided for the study of enterprise value creation is provided, as policy reference for improvement of decision-making and value creation.

• 지능정보연구
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• 제20권4호
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• pp.121-139
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• 2014

기업의 부도 예측은 재무 및 회계 분야에서 매우 중요한 연구 주제이다. 기업의 부도로 인해 발생하는 비용이 매우 크기 때문에 부도 예측의 정확성은 금융기관으로서는 매우 중요한 일이다. 최근에는 여러 개의 모형을 결합하는 앙상블 모형을 부도 예측에 적용해 보려는 연구가 큰 관심을 끌고 있다. 앙상블 모형은 개별 모형보다 더 좋은 성과를 내기 위해 여러 개의 분류기를 결합하는 것이다. 이와 같은 앙상블 분류기는 분류기의 일반화 성능을 개선하는 데 매우 유용한 것으로 알려져 있다. 본 논문은 부도 예측 모형의 성과 개선에 관한 연구이다. 이를 위해 사례 선택(Instance Selection)을 활용한 배깅(Bagging) 모형을 제안하였다. 사례 선택은 원 데이터에서 가장 대표성 있고 관련성 높은 데이터를 선택하고 예측 모형에 악영향을 줄 수 있는 불필요한 데이터를 제거하는 것으로 이를 통해 예측 성과 개선도 기대할 수 있다. 배깅은 학습데이터에 변화를 줌으로써 기저 분류기들을 다양화시키는 앙상블 기법으로 단순하면서도 성과가 매우 좋은 것으로 알려져 있다. 사례 선택과 배깅은 각각 모형의 성과를 개선시킬 수 있는 잠재력이 있지만 이들 두 기법의 결합에 관한 연구는 아직까지 없는 것이 현실이다. 본 연구에서는 부도 예측 모형의 성과를 개선하기 위해 사례 선택과 배깅을 연결하는 새로운 모형을 제안하였다. 최적의 사례 선택을 위해 유전자 알고리즘이 사용되었으며, 이를 통해 최적의 사례 선택 조합을 찾고 이 결과를 배깅 앙상블 모형에 전달하여 새로운 형태의 배깅 앙상블 모형을 구성하게 된다. 본 연구에서 제안한 새로운 앙상블 모형의 성과를 검증하기 위해 ROC 커브, AUC, 예측정확도 등과 같은 성과지표를 사용해 다양한 모형과 비교 분석해 보았다. 실제 기업데이터를 사용해 실험한 결과 본 논문에서 제안한 새로운 형태의 모형이 가장 좋은 성과를 보임을 알 수 있었다.

• 지능정보연구
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• 제21권4호
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• pp.93-110
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• 2015

기존의 협업필터링 추천시스템 연구는 상품에 대한 고객의 평점(rating)이나 구매 여부 데이터로부터 하나의 프로파일을 생성하고 이를 기반으로 추천 성능을 향상시킬 수 있는 새로운 알고리즘을 개발하는 위주로 진행되어 왔다. 그러나 빅데이터 환경이 도래하면서 기업이 수집할 수 있는 고객 데이터가 풍부해지고 다양해짐에 따라, 보다 정확하게 고객의 선호도나 행태를 파악하는 것이 가능하게 되었고 이러한 데이터, 즉 퍼스널 빅데이터(personal big data)를 추천시스템에 활용하는 연구의 필요성이 대두되고 있다. 본 연구에서는 마케팅의 시장세분화 이론에 근거하여 퍼스널 빅데이터로부터 고객의 선호도나 행태를 다양한 관점에서 표현할 수 있는 5종의 다중 프로파일(multimodal profile)을 개발하고, 이를 활용하여 협업필터링 추천시스템의 성능을 개선하고자 한다. 제안하는 5종의 다중 프로파일은 프로파일 통합 유사도, 개별 프로파일 유사도 평균, 개별 프로파일 유사도 가중 평균이라는 세 가지 앙상블 기법을 통해 협업필터링의 이웃(neighborhood) 탐색과정에 적용된다. 실제 퍼스널 빅데이터에 본 연구에서 제안하는 방법론을 적용한 결과, 단일 프로파일을 사용하는 협업필터링 알고리즘보다 추천 성능이 상당히 개선되었으며 앙상블 방법 중에서는 개별 프로파일 유사도 가중 평균 기법이 가장 높은 추천 성능을 보여주었다. 본 연구는 빅데이터 환경에서 추천시스템을 개발하고자 할 때, 어떠한 성격의 데이터로부터 고객의 특성을 규명하는 프로파일을 만들고 이를 어떻게 결합하여 사용하는 것이 효과적인 지 처음으로 제안하였다는 점에서 그 의의가 있다.