• Journal of Chest Surgery
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• v.57 no.2
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• pp.184-194
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• 2024

Background: Left ventricular assist devices (LVADs) are widely employed as a therapeutic option for end-stage heart failure. We evaluated the outcomes associated with centrifugal-flow LVAD implantation, comparing 2 device models: the Heartmate 3 (HM3) and the Heartware Ventricular Assist Device (HVAD). Methods: Data were collected from patients who underwent LVAD implantation between June 1, 2015 and December 31, 2022. We analyzed overall survival, first rehospitalization, and early, late, and LVAD-related complications. Results: In total, 74 patients underwent LVAD implantation, with 42 receiving the HM3 and 32 the HVAD. A mild Interagency Registry for Mechanically Assisted Circulatory Support score was more common among HM3 than HVAD recipients (p=0.006), and patients receiving the HM3 exhibited lower rates of preoperative ventilator use (p=0.010) and extracorporeal membrane oxygenation (p=0.039). The overall early mortality rate was 5.4% (4 of 74 patients), with no significant difference between groups. Regarding early right ventricular (RV) failure, HM3 implantation was associated with a lower rate (13 of 42 [31.0%]) than HVAD implantation (18 of 32 [56.2%], p=0.051). The median rehospitalization-free period was longer for HM3 recipients (16.9 months) than HVAD recipients (5.3 months, p=0.013). Furthermore, HM3 recipients displayed a lower incidence of late hemorrhagic stroke (p=0.016). In the multivariable analysis, preoperative use of continuous renal replacement therapy (odds ratio, 22.31; p=0.002) was the only significant predictor of postoperative RV failure. Conclusion: The LVAD models (HM3 and HVAD) demonstrated comparable overall survival rates. However, the HM3 was associated with a lower risk of late hemorrhagic stroke.

• Journal of The Korean Society of Integrative Medicine
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• v.12 no.2
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• pp.155-166
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• 2024

Purpose : This study aims to identify key factors for predicting dropout risk at the university level and to provide a foundation for policy development aimed at dropout prevention. This study explores the optimal machine learning algorithm by comparing the performance of various algorithms using data on college students' dropout risks. Methods : We collected data on factors influencing dropout risk and propensity were collected from N University. The collected data were applied to several machine learning algorithms, including random forest, decision tree, artificial neural network, logistic regression, support vector machine (SVM), k-nearest neighbor (k-NN) classification, and Naive Bayes. The performance of these models was compared and evaluated, with a focus on predictive validity and the identification of significant dropout factors through the information gain index of machine learning. Results : The binary logistic regression analysis showed that the year of the program, department, grades, and year of entry had a statistically significant effect on the dropout risk. The performance of each machine learning algorithm showed that random forest performed the best. The results showed that the relative importance of the predictor variables was highest for department, age, grade, and residence, in the order of whether or not they matched the school location. Conclusion : Machine learning-based prediction of dropout risk focuses on the early identification of students at risk. The types and causes of dropout crises vary significantly among students. It is important to identify the types and causes of dropout crises so that appropriate actions and support can be taken to remove risk factors and increase protective factors. The relative importance of the factors affecting dropout risk found in this study will help guide educational prescriptions for preventing college student dropout.

• International Journal of Human Ecology
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• v.13 no.2
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• pp.1-13
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• 2012

This study examined the effects of academic self-concept (internal factor) and maternal parenting behaviors (external factor) on academic delay of gratification (ADOG). Additionally, models predicting ADOG were compared between Korean and Malaysian children. The participants of this study were 100 Korean third graders and their mothers, and 100 Malaysian third graders and their mothers. The children completed the modified versions of the Academic Delay of Gratification Scale for Children, and Academic Self-Concept Questionnaire. The mothers completed the Parenting Attitude Test. Pearson's correlation tests, independent t-tests, and multiple regression analyses were conducted to test the research hypotheses. The results showed that Korean children reported higher ADOG and academic self-concept scores than that of Malaysian children. Moreover, academic self-concept was found to have a significant positive effect on ADOG among both Korean and Malaysian children. There was no significant gender difference in ADOG for both Korean and Malaysian children. However, the effects of maternal parenting behaviors on ADOG were only detected among the Malaysian children, particularly on Achievement Press. That is, only for the Malaysian children, maternal pressure about academic achievement was found to have a significant positive effect on ADOG. In conclusion, only academic self-concept was found to be a significant predictor explaining the variance in ADOG among Korean children. On the other hand, academic self-concept and maternal parenting behaviors were shown as significant predictors explaining the variance in ADOG among Malaysian children.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1419-1436
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• 2020

For an energy harvesting sensor network, when the network lifetime is not the only primary goal, maximizing the network performance under environmental energy harvesting becomes a more critical issue. However, clustering protocols that aim at providing maximum information throughput have not been thoroughly explored in Energy Harvesting Wireless Sensor Networks (EH-WSNs). In this paper, clustering protocols are studied for maximizing the data transmission in the whole network. Based on a long short-term memory (LSTM) energy predictor and node energy consumption and supplement models, an uneven clustering protocol is proposed where the cluster head selection and cluster size control are thoroughly designed for this purpose. Simulations and results verify that the proposed scheme can outperform some classic schemes by having more data packets received by the cluster heads (CHs) and the base station (BS) under these energy constraints. The outcomes of this paper also provide some insights for choosing clustering routing protocols in EH-WSNs, by exploiting the factors such as uneven clustering size, number of clusters, multiple CHs, multihop routing strategy, and energy supplementing period.

• Journal of the military operations research society of Korea
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• v.32 no.2
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• pp.143-164
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• 2006

This paper considers the technology spillover effects on industries by analyzing patents. Registered patents in the United States from Korea in 1990 and 1995 are compared by quantity of registrations as well as patent analysis indices, namely, cites per patent, technology cycle time and science linkage. Several regression models between these indices as predictor variables and the value added of an industry as a dependent variable were investigated. The results show that the value added of an industry positively correlates to the number of patent registrations and cites per patent.

• Journal of Families and Better Life
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• v.23 no.1 s.73
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• pp.187-195
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• 2005

The purpose of this study is to examine the influence of parent-to-child financial transfers and economic resources on financial transfers, caregiving, and time donated from middle-aged adult children to their elderly parents. Analyzing data from the Wisconsin Longitudinal Study, which provides long-term observations of financial reciprocity and recent reports about elder care, the current study finds strong positive effects of prior parent-to-child financial transfers in the models of caregiving and time; which indicates the importance of reciprocity. In terms of determinants of resource transfers, the findings of logistic regression analyses suggest that the economic resources of parents and adult children are strong determinants of child-to-parent financial resource transfers. Sociodemographic characteristics of parents and respondents were observed as strong determinants of caregiving or time. In addition, caregiving responds more to the health and income levels of parents whereas donated time is responsive to the net worth of parents and parents' status. For adult children, gender is a strong determinant of both caregiving and time donation. The long-term health problem of adult children is a statistically significant predictor of caregiving, while the employment status of adult children and the number of siblings have statistically a significant association with time donated to care for the parents.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.4
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• pp.1563-1566
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• 2014

Background: Esophageal squamous cell carcinoma (ESCC) accounts for most esophageal cancer in Asia, and is the sixth common cause of cancer-related deaths worldwide. Previous studies indicated HOXB7 is overexpressed in ESCC tissues, but data on prognostic value are limited. Methods: A total of 76 advanced ESCC cases were investigated. Immunohistochemistry (IHC) was used to detect the expression levels of HOXB7 and Kaplan-Meier curves and Cox regression models to determine prognostic significance. Stratified analysis was also performed according to lymph node (LN) status. Results: Kaplan-Meier curve analysis indicated that HOXB7 positive patients had significantly shorter overall survival (OS) than HOXB7 negative patients. Multivariate analysis using the Cox proportional hazards model indicated only TNM stage and HOXB7 expression to be independent predictors of overall survival of advanced ESCC patients. HOXB7 indicated poor OS in both lymph node negative (LN-) and lymph node positive (LN+) patients. Conclusion: HOXB7 predicts poor prognosis of advanced ESCC patients and can be applied as an independent prognostic predictor.

• The Korean Journal of Applied Statistics
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• v.27 no.2
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• pp.227-237
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• 2014

We use the regression model with the indicator variables in the case that we use qualitative variables as some predictor variables in regression analysis. We use the ANCOVA(Analysis of Covariance) model when comparing the response variable among groups while statistically controlling for variation in the response variable caused by a variation in the covariate. DD-plot can be used as a graphical exploratory data analysis tool before the confirmatory data analysis. With the DD-plot, we can discriminate the difference of groups in the regression model with the indicator variables or the ANCOVA model at a glance. Making DD-plot does not demand the statistical model assumption about error terms in regression model. Several examples show the usefulness of DD-plots as a graphical exploratory data analysis tool for the regression analysis.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.7
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• pp.974-982
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• 2004

The purpose of this study was to examine the influence of belief in body control on appearance satisfaction using structural equation modeling. In the structural equation model, self-esteem was included as a common predictor variable of belief in body control and appearance satisfaction, and the ideal body type and perceived body type were included as mediator variables. The data was collected from 96 female college students in the State of Washington, United States, Using AMOS 4, confirmatory factor analyses were conducted to fit the measurement models, and then the fit of the structural model was examined. The results of this study are as follows: The indirect effect of belief in body control on appearance satisfaction through its negative effect on ideal body type was significant. Yet, the direct path of belief in body control to appearance satisfaction and the indirect path through their common relationships with self-esteem were found not significant. These results indicate that higher body control belief may lead to lower appearance satisfaction due to the decreased size of ideal body type.

• Journal of the Korea Concrete Institute
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• v.11 no.4
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• pp.43-54
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• 1999

Shear tests are performed on four full-scale 12.5 m proto-type models, "least depth double tee," which are resulted from the optimization process. Domestic superimposed live load regulation, domestic material properties which is available to product. Korean building code requirements, construction environments and economy are considered as the main factors to establish the process. All of the specimens tested fully comply with the shear strength requirements as specified by ACI 318-95. The research has shown following results. 1) The development length requirement of ACI 318-95 does not seem a good predictor for the estimation of bond failure in a beam with the strands below the supports. 2) The load required for the first initial coner cracking in the dap end and first web shear cracking does not seem to have any relation with the dimension and shear strength of the section in the test beams. 3) The strand slip has a direct relationship with the web shear cracking. However, the coner cracking in the dap end does not give any help for the slip in anchorage. 4) Use of whole area for bearing steel at the bottom of dap end is desired for safe bearing pressure design in the precast prestressed double tee beams. 5) The deflection of beam influences directly on the amount of strand slip at the anchorage after initiation of it, and relationship between them are very linear.