• STI Policy Review
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• v.5 no.1
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• pp.57-74
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• 2014

This review organises the fragmented management literature on platform business according to a conceptual map and a meta-theoretical scheme. Since the early 2000s, numerous researchers have examined platform business and two-sided networks with platform business and strategy being an important business innovation model for many industries, creating value primarily by enabling direct interactions. Platforms such as Google or Amazon contain a common set of rules and components in most user transactions. Thirty-two core papers and books on Strategic Management Journal, Industrial Economics and Operation Management-related disciplines are reviewed, with further observations on how cumulative research streams on the platform are carried out independently from each academic perspective. The first of the two arguments in this paper is that because interactive relationships bridge the platform and stakeholders such as end-users and developers, it is crucial for platform companies to be aware of their relationship with stakeholders in order to support and sustainably provide content to their platform. The second is that integrative perspectives are essential due to the low number of interdisciplinary investigations conducted thus far. The paper's final section deals with implications for theory and practice, concluding that integrative studies and interactive relationship studies should be the main research streams in future platform research.

• Journal of The Korean Society of Integrative Medicine
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• v.3 no.1
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• pp.41-51
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• 2015

Purpose: The purpose of this study was to investigate the effects of personalized residential environment improvement on occupational performance satisfaction and activities of daily living(ADL) in stroke patients, and desire to use as the basis for presenting an effective method for improving the residential environment of the disabled patients. Method: This study has been carried out with 3 stroke patients undergoing therapy for rehabilitation at the S hospital from August 2014 to January 2015. Residential environment improvement was conducted based on the desired space. Occupational performance, satisfaction and ADL assessed by modified COPM, K-MBI. Intervention has provided grab bar and aids fit to the environment of each person. Result: After residential environment improvement, ADL score was improved, but improved scores for specific items only. In occupational performance and satisfaction, there was a significant difference. Conclusion: The results of this study were to find out that there is a positive effect of personalized residential environment improvement on occupational performance satisfaction and activities of daily living in stroke patients, could be used as a basis for presenting an effective way to residential environment improvement of the disabled patients.

• Journal of The Korean Society of Integrative Medicine
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• v.8 no.3
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• pp.121-131
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• 2020

Purpose : This study was conducted to confirm the correlation between team sharing spirit, team effectiveness, team cohesion, team reliability, and turnover intention of hospital nurses and to identify the influence factors affecting the turnover intention of hospital nurses. Methods : The sample for this study consisted of 200 nurses from four general hospitals of less than 500 beds located in J city. Data were analyzed using frequency, percentage, mean, standard deviation, t-test, ANOVA, Scheffe' test, Pearson Correlation and Hierarchical Multiple Regression. Results : Factors influencing nurse turnover intentions included satisfaction with nursing position (β=.274), team reliability (β=-.250), satisfaction with department (β=-.178), and career (β=.149) in order, and these influence factors accounted for 32.1 % of nurses' turnover intentions. Conclusion : Based on the results of the study, it is necessary to consider ways to reduce the turnover intention of nurses by devising strategies to increase the factors of satisfaction with nursing positions, team reliability, and satisfaction with department by making good use of the resources of the medical institution. It is suggested to conduct repeated studies of nurses working in various clinical sites and further studies applying various outcome variables in the future.

• Journal of The Korean Society of Integrative Medicine
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• v.4 no.2
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• pp.97-107
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• 2016

Purpose : Cardiovascular disease is major factor of mortality in worldwide. Previous studies shown that the socioeconomic factors, nutrition factors, health behavior factors, biological factors and co-morbidity are increasing a prevalence of cardiovascular disease. Method : This study examined the risk factors for cardiovascular disease among adults aged 30 years and older using the data from the 2012 to 2014 Korean National Health and Nutrition Examination Survey (KNHANES). The study participants were 7,555 Cardiovascular disease includes hypertension, stroke, angina pactoris, and myocardial infarction. Descriptive statistic and multivariates logistic regression were calculated. Result : The overall prevalence of cardiovascular disease was 31.16% in the participants. Cardiovascular disease was significantly associated with gender, age, income, education, marital status as socioeconomic factors in unadjusted model. After adjusting socioeconomic status variables, past smoker (OR 1.27, 95% CI 1.05-1.55), obesity (OR 7.14, 95% CI 4.21-12.11), skipping a meal (OR 2.79, 95% CI 2.46-3.16), HDL-C (OR 0.99, 95% CI 0.98-0.99) and WC (OR 1.06, 95% CI 1.05-1.07) were associated with cardiovascular disease. Conclusion : The results marked the importance of finding high risk groups and an early management of cardiovascular disease.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.326-338
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• 2003

The objective of a neural network design and model selection is to construct an optimal network with a good generalization performance. However, training data include noises, and the number of training data is not sufficient, which results in the difference between the true probability distribution and the empirical one. The difference makes the teaming parameters to over-fit only to training data and to deviate from the true distribution of data, which is called the overfitting phenomenon. The overfilled neural network shows good approximations for the training data, but gives bad predictions to untrained new data. As the complexity of the neural network increases, this overfitting phenomenon also becomes more severe. In this paper, by taking statistical viewpoint, we proposed an integrative process for neural network design and model selection method in order to improve generalization performance. At first, by using the natural gradient learning with adaptive regularization, we try to obtain optimal parameters that are not overfilled to training data with fast convergence. By adopting the natural pruning to the obtained optimal parameters, we generate several candidates of network model with different sizes. Finally, we select an optimal model among candidate models based on the Bayesian Information Criteria. Through the computer simulation on benchmark problems, we confirm the generalization and structure optimization performance of the proposed integrative process of teaming and model selection.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.10
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• pp.5761-5767
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• 2013

The potential correlation of X-ray repair cross-complementing group 1 (XRCC1) Arg399Gln polymorphism with hepatocellular carcinoma (HCC) susceptibility is ambiguous. Taking account of inconsistent results of previous meta-analyses and new emerging literatures, we conducted a meta-analysis covering 15 case-control datasets to evaluate the relationship. Relevant studies from Medline, Embase and CNKI were retrieved. A fixed-effect model or a random-effect model, depending on between-study heterogeneity, were applied to estimate the association between XRCC1 polymorphism Arg399Gln and HCC risk with the results presented as odds ratios (ORs) and 95% confidence intervals (95% CIs). In accordance with Hardy-Weinberg equilibrium, 15 studies with data for 6,556 individuals were enrolled in this systematic review. For overall HCC,thr XRCC1 polymorphism Arg399Gln was significantly associated with HCC susceptibility in a homozygote model as well as in a dominant model (G/G vs. A/A, OR=1.253, p=0.028; G/G+A/G vs. A/A, OR= 1.281, p=0.047, respectively), but not in a heterozygote model (A/G vs. A/A, OR=1.271, p=0.066) or a recessive model (G/G vs. A/G + A/A, OR= 1.049, p=0.542). Similar results were also observed on stratification analysis by ethnicity (A/G vs. A/A, OR=1.357, p=0.025; G/G vs. A/A, OR=1.310, p=0.011; G/G+A/G vs. A/A, OR= 1.371, p=0.013). However, no potential contribution of XRCC1 Arg399Gln polymorphism to HCC susceptibility in HBV/HCV subgroups was identified. No publication bias was found in this study. In conclusion, the XRCC1 Arg399Gln polymorphism contributes to HCC susceptibility. Due to the lack of studies in Western countries, further large-sample and rigorous studies are needed to validate the findings.

• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.5
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• pp.628-639
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• 2000

The purpose of this study is to propose a model of private brands proneness form-ation considering the six private brands proneness-related variables simultaneously. Since the theoretical framework is based on previous research in various areas, it serves as an integrative one. Data were collected via intercept surveys conducted at nine regional branches of two major department stores situated in Seoul. Participants(n=1,120), who had previously purchased women's private brand apparel, were asked to complete a questionnaire during two weeks from March 15, 1999 to March 28, 1999. LISREL and SPSS PC+ were used to test the model and analyze its variables. The fitness of the model show the reasonable fit between all indices(RMSR=.036, GFI=.99, AGFI=.92, and NFI=.95). The proposed model supports all the hypothesized relationships. Private brands proneness increases as perceived money value of products, familiarity, positive store image of private brands, and satisfaction of individuals' differentiated needs increase. Furthermore, perceived money value of products increase as perceived risk of private brand purchase and perceived quality variation between private brand products and manufacture's products decrease.

• Journal of Information Technology Applications and Management
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• v.21 no.4_spc
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• pp.463-483
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• 2014

Data are dramatically increased and big data technology is spotlighted innovative technology among the latest information technologies. Organizations are interested in adoption of big data system to analyze various data format and to identify new business opportunity. The purpose of this study is to build a unified model for a system adoption through analysis of impact that affects behavioral intention and usage behavior of using big data. This study in addition to Technology-Organization-Environment (TOE), that is used the introduction of organizational studies, and Diffusion of Innovation (DOI) have implemented an extended unified model including the unified theory of acceptance and use of technology (UTAUT) that is usually used in personal level adoption study. The hypothesis was set up after implementing research model, and then got 411 effective survey data to target the member of organizations. As a result, all models (UTAUT, TOE, DOI) are affect to behavioral intention and usage behavior. It is verified that the suggested unified model was appropriate.

• Animal cells and systems
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• v.16 no.2
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• pp.121-126
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• 2012

In this study, a neural network (NN) modeling approach has been used to predict the mechanical and geometrical behaviors of mouse embryo cells. Two NN models have been implemented. In the first NN model dimple depth (w), dimple radius (a) and radius of the semi-circular curved surface of the cell (R) were used as inputs of the model while indentation force (f) was considered as output. In the second NN model, indentation force (f), dimple radius (a) and radius of the semi-circular curved surface of the cell (R) were considered as inputs of the model and dimple depth was predicted as the output of the model. In addition, sensitivity analysis has been carried out to investigate the influence of the significance of input parameters on the mechanical behavior of mouse embryos. Experimental data deduced by Fl$\ddot{u}$ckiger (2004) were collected to obtain training and test data for the NN. The results of these investigations show that the correlation values of the test and training data sets are between 0.9988 and 1.0000, and are in good agreement with the experimental observations.

• Computers and Concrete
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• v.2 no.6
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• pp.439-454
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• 2005

When deterioration of concrete is observed in a structure, it is highly desirable to determine the cause of such deterioration. Only by understanding the cause can an appropriate repair strategy be implemented to address both the cause and the symptom. In colder climates, bridge deck deterioration is often caused by chlorides from de-icing salts, which penetrate the concrete and depassivate the embedded reinforcement, causing corrosion. Bridge decks can also suffer from other deterioration mechanisms, such as alkali-silica reaction, freeze-thaw, and shrinkage. There is a need for a comprehensive and integrative system to help with the inspection and evaluation of concrete bridge deck deterioration before decisions are made on the best way to repair it. The purpose of this research was to develop a model to help with the diagnosis of concrete bridge deck deterioration that integrates the symptoms observed during an inspection, various deterioration mechanisms, and the probability of their occurrence given the available data. The model displays the diagnosis result as the probability that one of four deterioration mechanisms, namely shrinkage, corrosion of reinforcement, freeze-thaw and alkali-silica reaction, is at fault. Sensitivity analysis was performed to determine which probabilities in the model require refinement. Two case studies are included in this investigation.