• 대한치과기공학회지
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• 제40권3호
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• pp.115-123
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• 2018

Purpose: The purpose of this study was establishing process of manufacturing dental prosthesis by using eZIS system(DDS Inc.,Korea). Methods: To evaluate accuracy verification, the test was practiced two ways. First, Comparison of 3D printing models and stone models was practiced by using 3D superimposing software. #36 prepared master model was scanned by eZIS system and three 'Veltz3D' 3D printing models and three 'Bio3D' 3D printing models were manufactured. three stone models were manufactured by conventional impression technique. Second, Fitness test was practiced. the 3D printing models and the stone models was compared by manufacturing same resin crown. #36 prepared master model was scanned 9 times and manufactured (milled) 9 resin crowns by eZIS system. These crowns were cemented three 'Veltz3D' 3D printing models, three 'Bio3D' 3D printing models and three stone models. These crowns were sliced mesiodistal axis and gaps were measured by digital microscope. Results: The average accuracy of Bio3D models were 65.75%. Veltz3D(Hebsiba) models were 60.11% Stone models were 41.00%. Conclusion : This study results showed 3D printing model is similar with stone model. So it was under clinical allow, didn't affect final dental prothesis. There were no significant differences in the appearance of the three types of milling crowns.

• 대한간호학회지
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• 제29권6호
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• pp.1192-1207
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• 1999

The purpose of this study was to clarify the dynamic relationships among risk factors of arteriosclerosis and to develop and examine a model which could explain this relationship clearly. Data were collected from medical records of 400 male clients who visited a university hospital located in Inchon for physical examinations, from May 1996 to December 1996. Data were analyzed using the LISREL (Linear Structural Relationship) 8 program. To test the fitness of the hypothesized model, chi-square, RMSR (root mean square residual), GFI (goodness of fit index), CN (critical number) and Q-plot were used. Most of the fitness measurements, except the chi-square showed that the hypothesized model complimented the real data. According to the results, there were trends that obesity and hyperlipidemia were prevalent in heavier smokers, higher alcohol intakers, and groups who excercised less. Also, hypertension was more prevalent in older age, higher alcohol intaker, and higher serum lipid level groups. In contrast to the hypothesis, alcohol intake did not significantly affect serum lipid levels. This might be due to the serum lipid measurements (total cholesterol and trigryceride) used in this study to estimate hyperlipidemia. The direct effect of smoking on hypertension was not significant. However, the total effect of smoking on the hypertension was significant since indirect effects of smoking on hypertension, such as obesity and hyperlipidemia, were significant. The total effect of obesity on hypertension was significant since the indirect effect of obesity on hypertension via hyperlipidemia was significant, although the direct effect of smoking on hypertension was not significant. The degree of explaining hyperlipidemia with smoking, exercise, and obesity was high (60%), however, the degree of explaining obesity with age, smoking, alcohol intake, and exercise was very low (7%). On the basis of these results, high risk factors of arteriosclerosis such as hypertension, hyperlipidemia, or obesity are either directly or indirectly correlated each other. Therefore, it is difficult to predict outcomes for increasing or decreasing the risk factors by simply modulating a factor. Smoking, alcohol, and exercise both directly and indirectly affected major risk factors of arteriosclerosis. Therefore, correcting these variables is required to decrease risk factors. Finally, the relationship among other risk factors which have been known to be related with arteriosclerosis (diet, stress or hereditary) should be clarified in further studies.

• 인터넷정보학회논문지
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• 제20권1호
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• pp.1-10
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• 2019

빅 데이터에서 텍스트 마이닝은 많은 수의 데이터로부터 많은 특징 추출하기 때문에, 클러스터링 및 분류 과정의 계산 복잡도가 높고 분석결과의 신뢰성이 낮아질 수 있다. 특히 텍스트마이닝 과정을 통해 얻는 Term document matrix는 term과 문서간의 특징들을 표현하고 있지만, 희소행렬 형태를 보이게 된다. 본 논문에서는 탐지모델을 위해 텍스트마이닝에서 개선된 GA(Genetic Algorithm)을 이용한 특징 추출 방법을 설계하였다. TF-IDF는 특징 추출에서 문서와 용어간의 관계를 반영하는데 사용된다. 반복과정을 통해 사전에 미리 결정된 만큼의 특징을 선택한다. 또한 탐지모델의 성능 향상을 위해 sparsity score(희소성 점수)를 사용하였다. 스팸메일 세트의 희소성이 높으면 탐지모델의 성능이 낮아져 최적화된 탐지 모델을 찾기가 어렵다. 우리는 fitness function에서 s(F)를 사용하여 희소성이 낮고 TF-IDF 점수가 높은 탐지모델을 찾았다. 또한 제안된 알고리즘을 텍스트 분류 실험에 적용하여 성능을 검증하였다. 결과적으로, 제안한 알고리즘은 공격 메일 분류에서 좋은 성능(속도와 정확도)을 보여주었다.

• 대한간호학회지
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• 제52권4호
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• pp.407-420
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• 2022

Purpose: This structural model study was constructed and verified a hypothetical model to examine the effects of parenting stress, social resources, family resources, and positive coping on resilience among mothers of children with developmental disabilities. Methods: Data were collected using self-report structured questionnaires, from October 19 to October 30, 2018, with 214 mothers caring for children with developmental disabilities under the age of 20 years. Results: In the fitness test results of the hypothesis model, with the fit index 𝛘² (p) = 69.27 (< .001), and the normed fit indices (𝛘² = 1.87, GFI = .94, CFI = .97, NFI = .93, and TLI = .95, RMSEA = .06, SRMR = .06), this study satisfies the good fitness in standards. There are seven statistically significant paths among the 10 paths set in the hypothetical model. The explanatory power of parenting stress and social resources, which affects the family resources was 41.4%, the explanatory power of parenting stress, social resources, and family resources affecting the positive coping was 58.9%, and the explanatory power of parenting stress, social resources, family resources, and positive coping affecting resilience was 55.5%. Conclusion: Positive coping, family resources, and social resources of mothers of children with developmental disabilities directly affect their resilience, and parenting stress indirectly affects it. Therefore, to improve the resilience of mothers of children with developmental disabilities, it is necessary to develop a systematic nursing intervention that considers parenting stress, social resources, family resources, and positive coping.

• 한국환경보건학회지
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• 제27권3호
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• pp.35-42
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• 2001

The characteristics of water quality variation were predicted by stochastic model in Chungju dam, north Chungcheong province of south Korea, Monthly time series data of water quality from 1989 to 2001;temperature, BOD, COD and SS, were obtained from environmental yearbook and internet homepage of ministry of environment. Development of model was carried out with Box-Jenkins method, which includes model identification, estimation and diagnostic checking. ACF and PACF were used to model identification. AIC and BIC were used to model estimation. Seosonal multiplicative ARIMA(1, 0, 1)(1, 1, 0)$_{12}$ model was appropriate to explain stochastic characteristics of temperature. BOD model was ARMa(2, 2, 1), COD was seasonal multiplicative ARIMA(2. 0. 1)(1. 0, 1)$_{12}$, and SS was ARIMA(1, 0, 2) respectively. The simulated water quality data showed a good fitness to the observed data, as a result of model verification.ion.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제13권6호
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• pp.378-387
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• 2007

운동 효과를 극대화하기 위하여 개인의 신체 상태를 측정한 후, 운동 처방을 통하여 적합한 운동 프로그램을 생성해 주는 운동 관리 시스템이 도입되어 활용되고 있다. 하지만, 2주$\sim$3개월 주기로 신체 상태를 파악하여 생성되는 운동 프로그램은 다양하게 변화하는 개개인의 운동 습관이나 운동 주기를 실시간으로 반영하지 못하기 때문에, 운동 기간이 길어질수록 사용자의 현재상태에 적절치 않은 운동을 유도할 수 있다. 본 논문에서는 사용자의 상황을 고려한 운동 프로그램을 제공하기 위한 문맥 인지 운동 모델(Context Aware Exercise Model : CAEM)을 제안하며, 이를 지능형 운동 가이드(Intelligent Fitness Guide : IFG) 시스템으로 구현한다. IFG 시스템은 사용자의 상황에 따라 필요한 측정치를 선택적으로 입력 받고, 운동 종류 및 운동 횟수, 운동 강도의 변경 시 운동 최적화 알고리즘 및 운동 지식베이스를 통해 운동 프로그램을 생성한다. IFG는 사용자 상황에 알맞은 운동 프로그램을 실시간으로 제공함으로써, 사용자 상황에 알맞은 효율적인 운동 관리를 할 수 있다.

• Clinical and Experimental Pediatrics
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• 제63권9호
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• pp.361-367
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• 2020

Background: Length of stay is a significant indicator of care effectiveness and hospital performance. Owing to the limited number of healthcare centers and facilities, it is important to optimize length of stay and associated factors. Purpose: The present study aimed to investigate factors associated with neonatal length of stay in the neonatal intensive care unit (NICU) using parametric and semiparametric models and compare model fitness according to Akaike information criterion (AIC) between 2016 and 2018. Methods: This retrospective cohort study reviewed 600 medical records of infants admitted to the NICU of Bandar Abbas Hospital. Samples were identified using census sampling. Factors associated with NICU length of stay were investigated based on semiparametric Cox model and 4 parametric models including Weibull, exponential, log-logistic, and log-normal to determine the best fitted model. The data analysis was conducted using R software. The significance level was set at 0.05. Results: The study findings suggest that breastfeeding, phototherapy, acute renal failure, presence of mechanical ventilation, and availability of central venous catheter were commonly identified as factors associated with NICU length of stay in all 5 models (P<0.05). Parametric models showed better fitness than the Cox model in this study. Conclusion: Breastfeeding and availability of central venous catheter had protective effects against length of stay, whereas phototherapy, acute renal failure, and mechanical ventilation increased length of stay in NICU. Therefore, the identification of factors associated with NICU length of stay can help establish effective interventions aimed at decreasing the length of stay among infants.

• 산업경영시스템학회지
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• 제38권4호
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• pp.45-55
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• 2015

In this paper, we consider curriculum mining as an application of process mining in the domain of education. The basic objective of the curriculum mining is to construct a registration pattern model by using logs of registration data. However, subject registration patterns of students are very unstructured and complicated, called a spaghetti model, because it has a lot of different cases and high diversity of behaviors. In general, it is typically difficult to develop and analyze registration patterns. In the literature, there was an effort to handle this issue by using clustering based on the features of students and behaviors. However, it is not easy to obtain them in general since they are private and qualitative. Therefore, in this paper, we propose a new framework of curriculum mining applying K-means clustering based on subject attributes to solve the problems caused by unstructured process model obtained. Specifically, we divide subject's attribute data into two parts : categorical and numerical data. Categorical attribute has subject name, class classification, and research field, while numerical attribute has ABEEK goal and semester information. In case of categorical attribute, we suggest a method to quantify them by using binarization. The number of clusters used for K-means clustering, we applied Elbow method using R-squared value representing the variance ratio that can be explained by the number of clusters. The performance of the suggested method was verified by using a log of student registration data from an 'A university' in terms of the simplicity and fitness, which are the typical performance measure of obtained process model in process mining.

• 한국응용과학기술학회지
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• 제38권3호
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• pp.860-869
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• 2021

본 연구는 모바일 홈트레이닝과 운동몰입, 지속의도에 대한 기술수용 이론을 적용한 인과관계모형에 대한 구조분석 방법(SEM)을 적용하여 소비자을 예측하기 위한 기초자료를 제공하고자 하였다. 현재 코로나-19 팬데믹 사태로 인한 전략적 도구를 파악하기 위해 2021년 2월 1일부터 5월 21일까지 표본계획에 의해 모바일 프로그램인 "서베이 몽키"를 사용하여 유효표본 총 287명의 소비자를 최종 분석에 사용하여 다음과 같은 결과를 도출하였다. 첫째, 수용모델이 운동몰입에 유의미한 영향(+)을 미치는 것으로 나타났으며, 둘째, 수용모델이 운동지속의도에 유의미한 영향(+)을 미치는 것으로 나타났다. 셋째, 운동몰입이 운동지속의도에 유의미한 영향(+)을 미치는 것으로 나타났다.

• 지식경영연구
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• 제9권4호
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• pp.35-49
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• 2008

The purpose of the study is to develop and validate an instructional design model from the perspective of the knowledge creation. To serve the purpose, the researcher conducted 1) literature review to find causal relationship model among knowledge creation factors and to propose a hypothetical instructional design model, 2) data analysis with 50 senior level e-Learning instructional designers, and 3) testing the fitness of the proposed model and relevant causal-relational hypotheses. Results indicate; 1) the proposed model fit to the empirical evidence, 2) 6 hypotheses among 11 were validated. A typical instructional designer's personal competency was evidenced as the most powerful independent variable that predicted knowledge acquisition, knowledge sharing, and the application of the instructional models. However, the expected effect of instructional design models toward other dependent variable was not be found. In addition, further suggestions for the future research are addressed.