• 한국시스템다이내믹스연구
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• 제10권1호
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• pp.33-60
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• 2009

This study explores the limitation in making a causal model through an existing case and proposes an alternative plan to improve a theoretical system of causation modeling. To make a dynamic and actual model, several principles are needed such as reality based analysis of system structures and dynamics, consistent expression of causations, conversion of numerical formulas to causal relations, classification and arrangement of variables by size of concept, etc. However, it is hard to find cases to apply these considerations from existing models in System Dynamics. Therefore, this study verifies errors of derived models from literatures and proposes principles and guides that should be considered to make a sound dynamic model on a causal map. It contributes to making an opportunity for exciting public opinion to improve theory about causal maps, yet it has limitation that the study does not advance forward to the experimental step. For future study, it plans to make up by classifying and leveling causal variables, developing a dynamic BSC model.

• Journal of Preventive Medicine and Public Health
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• 제55권2호
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• pp.116-124
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• 2022

Epidemiological studies typically examine the causal effect of exposure on a health outcome. Standardization is one of the most straightforward methods for estimating causal estimands. However, compared to inverse probability weighting, there is a lack of user-centric explanations for implementing standardization to estimate causal estimands. This paper explains the standardization method using basic R functions only and how it is linked to the R package stdReg, which can be used to implement the same procedure. We provide a step-by-step tutorial for estimating causal risk differences, causal risk ratios, and causal odds ratios based on standardization. We also discuss how to carry out subgroup analysis in detail.

• 대한수학회지
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• 제34권2호
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• pp.257-264
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• 1997

We shall introduce the concept of almost causality condition. By defining the almost causality condition we would like to examine the relationship between Woodhouse's causality principle and other known causality conditions. We show that a series of causality conditions can be characterized by using the almost causality condition.

• 한국시스템다이내믹스연구
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• 제12권1호
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• pp.131-153
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• 2011

The purpose of this study is to explore the applicability of the causal maps for estimating creativity. This study assumes that fluency, flexibility, originality and elaboration are elements of creativity; and there are common characteristics between systems and creative thinking. For this study, 30 students from the 5th grade create causal maps which are consisted of the contents of 'the water cycle in the earth'. The causal maps are analyzed and evaluated by focusing on the characteristics of creativity. In way of the marking causal maps based on creativity, each word is scored as 1 point on the basis of 30 points for fluency. Each word which is linked more than one word is scored 3 points for flexibility, but the maximum points are limited as 35 points. In originality, if it is approved each word is worthy as well as originality, it is scored as 10 points on the basis of 40 points. Lastly, each number of cycle loops is scored as 15 points for elaboration, and the maximum scores are limited as 45 points. As is stated above, the limiting of the maximum scores are designed based on corresponded to 10% students of participators. In the result of this study, the students' scores of evaluating creativity applied causal maps show similar patterns from relative point of view to the other results which were evaluated the creativity by credible organ. Consequently, it is recognized that the causal maps have the possibility of being able to estimate quantitatively the creativity.

• 디지털산업정보학회논문지
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• 제19권4호
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• pp.45-52
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• 2023

With the advent of deep learning, Artificial Intelligence (AI) technology has experienced rapid advancements, extending its application across various industrial sectors. However, the focus has shifted from the independent use of AI technology to its dispersion and proliferation through the open AI ecosystem. This shift signifies the transition from a phase of research and development to an era where AI technology is becoming widely accessible to the general public. However, as this dispersion continues, there is an increasing demand for the verification of outcomes derived from AI technologies. Causal AI applies the traditional concept of causal inference to AI, allowing not only the analysis of data correlations but also the derivation of the causes of the results, thereby obtaining the optimal output values. Causal AI technology addresses these limitations by applying the theory of causal inference to machine learning and deep learning to derive the basis of the analysis results. This paper analyzes recent cases of causal AI technology and presents the major tasks and directions of causal AI, extracting patterns between data using the correlation between them and presenting the results of the analysis.

• 한국산업정보학회논문지
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• 제22권6호
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• pp.71-84
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• 2017

Over the past decade, we have witnessed Serious Debates in MISQ and Other Journals Between Two Camps that have Differing Views on the use of Causal Indicators to Measure Constructs. There is the Camp that advocates Causal Indicators (ADVOCATE) and the Camp that opposes Their Usage (OPPONENT). The Debates have been primarily centered on the OPPONENT's Argument that the Meaning of a Latent Variable is determined by its Outcome Variables. However, Little Effort has been made to Validate the ADVOCATE's Dispute (Against the OPPONENT's Arguments) that the Meaning of a Latent Variable is decided by its Causal Indicators if there is no Misspecification. Our Study precisely examines the Integrity of the Argument. For this, we empirically examine how the two Primary Psychometric Properties-Comprehensiveness and Interrelationship-of Causal Indicators Influence Theory Testing between Latent Variables through Three Different Tests (i.e., Comprehensive Test, Interrelationship Test, and Mixed Test). Conducted on Two Different Datasets, Our Analysis Consistently Reveals that Structural Path Coefficients are Hardly Sensitive to the Changes (i.e., Misspecification) in the Properties of Causal Indicators. The Discovery offers Important Evidence that the Sound Theoretical Logic of a Causal Model is not in Sync with the Empirical Mechanism of Parameter Estimation. This Underscores that a Latent Variable Formed by Causal Indicators is empirically an elusive notion that is Difficult to Operationalize. As Our Results have Significant Implications on the Integrity of Numerous IS studies which have conducted Theory or Hypothesis Testing Using Causal Indicators, we strongly advocate Open Discussions among Methodologists regarding Our Findings and Their Implications for Both Published IS Research and Future Practices.

• 근관절건강학회지
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• 제9권2호
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• pp.187-202
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• 2002

This study was aim to provide rheumatoid arthritis patients the basic data of development of nursing intervention to help psychosocial adaptation of rheumatoid arthritis patients as exploring the relationship among causal perception, coping pattern, psychosocial adaptation of rheumatoid arthritis. As the results of this study the mean score of causal perception of the subjects was 3.37. The score of the internal-unstable was the highest. which was followed by extra-stable, internal factor, internal-stable, external factor and external-unstable in order among the factor of causal perception. The mean score of coping pattern was 2.64. The type of coping patterns the score of the receptive coping was the highest, which was followed by wishful coping active coping and negative coping in order among the type of coping pattern. The mean score of psychosocial adaptation was 3.28. The subconcept of psychosocial adaptation the score for personal relationship was the highest, which was followed by role function and mental state in order among the psychosocial adaptation. The analysis of the relation among causal perception, coping pattern and psychosocial adaptation showed significant negative correlation between causal perception and psychosocial adaptation(r=-0.3219, P=0.002). The analysis of the relation between the type of coping pattern and psychosocial adaptation showed significant negative correlation between psychosocial adaptation and active coping(r=-0.3210, P=0.002), negative coping(r=-0.2296, P=0.032). Only causal perception(-.36) and period of illness(-.26) effected on the psychosocial adaptation were shown to the negative direction significantly. The psychosocial adaptation was explained the 17% by these two variables. Based on this study results the factor of causal perception and the type of coping pattern of rheumatoid arthritis were shown significant relations between psychosocial adaptation. We suggests that nurses in practice apply to assessing the factor of causal perception of individuals illness and the type of coping patterns when nursing interventions in rheumatoid arthritis patients.

• 한국병원경영학회지
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• 제21권4호
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• pp.1-12
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• 2016

The purpose of this study are suggest to performance measurement model of Electronic Medical Record(EMR) and Key Performance Index(KPI). For data collection, 665 questionnaires were distributed to medical record administrators and insurance reviewers at 31 hospitals, and 580 questionnaires were collected(collection rate: 87.2%). Regarding methodology, Critical Success Factor(CSF) and index of the information system were derived based on previous studies, and these were set as performance measurement factors of EMR system. The performance measurement factors were constructed by perspective using BSC, and analysis on causal relationship between factors was conducted. A model of causal relationship was established, and performance measurement model of EMR system was proposed through model validation. Analysis on causal relationship between performance management factors revealed that utility cognition of the learning & growth perspective factor had causal relationship with job efficiency(${\beta}=0.20$) and decision support(${\beta}=0.66$) of the internal process perspective factors, and security had causal relationship with system satisfaction(${\beta}=0.31$) of the customer perspective factor. System quality had causal relationship with job efficiency(${\beta}=0.66$) and decision support(${\beta}=0.76$) of the internal process perspective factors, all of which were statistically significant(P<0.01). Job efficiency of the internal process perspective had causal relationship with system satisfaction(${\beta}=0.43$), and decision support had causal relationship with decision support satisfaction(${\beta}=0.91$) and job satisfaction (${\beta}=0.74$), all of which were statistically significant(P<0.01). System satisfaction of the customer perspective had causal relationship with job satisfaction(${\beta}=0.12$), job satisfaction had causal relationship with cost reduction(${\beta}=0.53$) of the financial perspective, and decision support satisfaction had causal relationship with productivity improvement(${\beta}=0.40$)of the financial perspective(P<0.01). Also, cost reduction of the financial perspective had causal relationship with productivity improvement(${\beta}=0.37$), all which were statistically significant(P<0.05). Suitability index verification of the performance measurement model whose causal relationship was found to be statistically significant revealed that $X^2/df=2.875$, RMR=0.036, GFI=0.831, AGFI=0.810, CFI=0.887, NFI=0.838, IFI=0.888, RMSEA=0.057, PNFI=0.781, and PCFI=0.827, all of which were in suitable levels. In conclusion, the performance measurement indices of EMR system include utility cognition, security, and system quality of the learning & growth perspective, decision support and job efficiency of the internal process perspective, system satisfaction, decision support satisfaction, and job satisfaction of the customer perspective, and productivity improvement and cost reduction of the financial perspective. In this study, it is expected that the performance measurement indices and model of EMR system which are suggested by the author, will be a measurement tool available for system performance measurement of EMR system in medical institutions.

• 대한가정학회지
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• 제38권5호
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• pp.15-24
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• 2000

The purpose of the study was to explore the causal relationships between delinquency and self-esteem among adolescents. The subjects of this study were 497 adolescents attending middle schools in Pusan. The data was collected by longitudinal research design of 9 month interval In first, second wave, the participants completed the delinquency scale and the multidimensional self-esteem inventory that includes home self, peer-related self, teacher-related self, academic-general serif, physical appearance self, physical competence self, and personality self, respectively The major findings of this study were as follows: these causal relationships differed among subdimensions of self-esteem, 1)the causal relationship between delinquency and home self was bidirectional, 2)the causal relationship between delinquency and peer-related self, teacher-related self, academic-general self, and personality self was unidirectional, 3)the causal relationship between delinquency and physical appearance self, physical competence self was not statistically significant.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.1039-1042
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• 1995

In real time application such as motion control, it is hard to find the application of non-causal filtering due to its need for future position data, even though it shows wide usage in off-line digital signal processing. Recently, some of motion control areas such as learning and repetitive control use non-causal filtering technique in their application. these kinds of zero-lag non-causal filter application are very usful not only to reduce the machine vibration, but also to increase control accuracy with comparatively less work. In this paper, genuine method to implement zero-lag non-causal filter in a CNC is introduced. Also the variation of this implementation for the learning operation is suggested to give the NC better control performance for a specific job. By adopting the new NC architecture call Soft-NC, all these implementions are made possible here, and especially large memory requirement which hinders their usage for many years is no longer barrier in their real world application.