• Korean Journal of Radiology
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• v.24 no.3
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• pp.235-246
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• 2023

Objective: It is difficult to predict the treatment response of tissue after stereotactic radiosurgery (SRS) because radiation necrosis (RN) and tumor recurrence can coexist. Our study aimed to predict tumor recurrence, including the recurrence site, after SRS of brain metastasis by performing a longitudinal tumor habitat analysis. Materials and Methods: Two consecutive multiparametric MRI examinations were performed for 83 adults (mean age, 59.0 years; range, 27-82 years; 44 male and 39 female) with 103 SRS-treated brain metastases. Tumor habitats based on contrast-enhanced T1- and T2-weighted images (structural habitats) and those based on the apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) images (physiological habitats) were defined using k-means voxel-wise clustering. The reference standard was based on the pathology or Response Assessment in Neuro-Oncologycriteria for brain metastases (RANO-BM). The association between parameters of single-time or longitudinal tumor habitat and the time to recurrence and the site of recurrence were evaluated using the Cox proportional hazards regression analysis and Dice similarity coefficient, respectively. Results: The mean interval between the two MRI examinations was 99 days. The longitudinal analysis showed that an increase in the hypovascular cellular habitat (low ADC and low CBV) was associated with the risk of recurrence (hazard ratio [HR], 2.68; 95% confidence interval [CI], 1.46-4.91; P = 0.001). During the single-time analysis, a solid low-enhancing habitat (low T2 and low contrast-enhanced T1 signal) was associated with the risk of recurrence (HR, 1.54; 95% CI, 1.01-2.35; P = 0.045). A hypovascular cellular habitat was indicative of the future recurrence site (Dice similarity coefficient = 0.423). Conclusion: After SRS of brain metastases, an increased hypovascular cellular habitat observed using a longitudinal MRI analysis was associated with the risk of recurrence (i.e., treatment resistance) and was indicative of recurrence site. A tumor habitat analysis may help guide future treatments for patients with brain metastases.

• Journal of Distribution Science
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• v.14 no.10
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• pp.109-116
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• 2016

Purpose - This study investigates the purchase pattern relating to soybean products in Korea. Specifically, the effect of branding based on a regional name was analyzed in terms of consumer purchase frequencies. The primary purpose of this study is to understand why family characteristics affect product selection for a regional brand in the soybean food category. Research design, data, and methodology - We used data collected by the Rural Development Administration (RDA) of Korea. The RDA has monitored agricultural food consumers for years in order to obtain purchase records. Panel participants live in regions near the capital city of Seoul, Korea. Examining data from January 2010 to May 2016, 667 families were selected for analysis. The final data set was 1,335,402. Each purchase item by each individual family was aggregated to a countable weekly observation. To analyze the data set quantitatively, zero-inflation regression was adopted, which was appropriate to avoid biases from overly dispersed observations. Results - We hypothesized the effects of regional branding from the viewpoint of the family characteristics. The first hypothesis was that the number of children would be positively associated with the purchase of a regional brand of soybean products. The result strongly supported this hypothesis. The second hypothesis was that the number of family members would be negatively associated with the purchase of the soybean products of a regional brand. Based on empirical analysis, we concluded that this hypothesis was partially supported. The third hypothesis was the presence of an interaction effect between the number of children and the family size, which was supported by the results. As a supplementary analysis, we also tested mean-variance differences in terms of categories and regional branding with corporate branding. Conclusion - The results of this study provide insights for regional branding strategies in agricultural food management. This study appears to be one of the seminal studies trying to analyze purchase patterns from longitudinal observations. In addition, this study adopted variables characterizing family lifestyle. This study confirmed that children and family size should be considered when soybean product brands are introduced.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.5
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• pp.96-104
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• 2000

This paper represents to develop a computer software system which is capable to analyze the phase transformation of high strength steel(BV-AH32) and to predict heat transfer and welding residual stress due to phase transformation during Gas Metal Arc(GMA) welding. The developed model was considered temperature dependent properties such as young's modules, coefficient of thermal expansion and yield stress as well as the double ellipsoidal heat distribution by the moving arc. From the results, it was found that the longitudinal and transverse residual stresses calculated by the coupled analysis of heat transfer, residual stress and phase transformation showed good agreement with the experimental data. In addition, the temperature distribution as well as longitudinal and transverse residual stresses of weldment by the 1-pass and 2-pass of welding were also determined.

• Proceedings of the KWS Conference
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• 1999.10a
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• pp.310-313
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• 1999

This paper represents to develop a computer software system which is capable to analyze the phase transformation of high strength steel(BV-AH32) and to predict heat transfer, residual stress due to phase transformation during Gas Metal Arc(GMA) welding. The developed model was taken into account temperature dependent of young's modules, coefficient of thermal expansion and yield stress as well as the double ellipsoidal heat distribution by the moving arc. The results showed that the longitudinal and transverse residual stresses calculated by the coupled analysis of heat transfer, residual stress and phase transformation are in good agreement with the experimental data. In addition, the temperature distribution as well as longitudinal and transverse residual stresses of weldment were determined at the 1-pass and 2-pass of welding.

• Journal of Korean Biological Nursing Science
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• v.26 no.3
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• pp.206-217
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• 2024

Purpose: The study aimed to determine the key factors influencing health-promoting behavior and the behavioral intentions of eHealth consumers based on the health promotion model and technology acceptance model. Methods: This research involved a longitudinal path analysis. The study was conducted with 360 eHealth consumers aged over 18 years, employed in the top five categories of the Korean standard classification of occupations, and living in the five largest cities in South Korea. The data were analyzed using SPSS 22.0 and AMOS 25.0. Results: Health-promoting behaviors were directly supported by prior health-related behavior and behavioral intention, and indirectly supported by perceived ease of use, perceived usefulness, perceived benefit, self-efficacy, and behavioral intention. These variables accounted for 36.3% of the variance in health-promoting behavior. Conclusion: The findings serve as a framework that can help health professionals and health information providers understand how to encourage consumers using eHealth to engage in health-promoting behaviors.

• Korean Journal of Environmental Biology
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• v.34 no.4
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• pp.365-373
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• 2016

Much of the data used in the analysis of environmental ecological data is being obtained over time. If the number of time points is small, the data will not be given enough information, so repeated measurements or multiple survey points data should be used to perform a comprehensive analysis. The method used for that case is longitudinal data analysis or mixed model analysis. However, if the amount of information is sufficient due to the large number of time points, repetitive data are not needed and these data are analyzed using time series analysis technique. In particular, with a large number of data points in the current situation, when we want to predict how each variable affects each other, or what trends will be expected in the future, we should analyze the data using time series analysis techniques. In this study, we introduce univariate time series analysis, intervention time series model, transfer function model, and multivariate time series model and review research papers studied in Korea. We also introduce an error correction model, which can be used to analyze environmental ecological data.

• Korean Journal of Social Welfare
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• v.29
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• pp.158-170
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• 1996

• Journal of Fashion Business
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• v.16 no.1
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• pp.26-40
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• 2012

The purpose of this study is to examine the fashion lifestyle variable of global consumers and to compare among US, Chinese and EU consumers. The data were collected in US(n=749), China(n=702) and EU(n=1083) from 2008 to 2010. For analysis, factor analysis, reliability analysis, K-means cluster analysis and chi-square analysis of SPSS 18.0 are used. The research results are as follow: First, it is shown that significant lifestyle factors of global fashion consumers are "adventure seeking", "fashion-oriented", "conspicuous consumption", "leadership", "brand-oriented", and "DIY". As a result of the cluster analysis of lifestyle types, four cross-national market segments are identified. These segments can be labeled as follows: "conservative fashion-oriented group", "passive consumer group", "neutral consumer group", "active fashion-oriented group". Second, findings also reveal that fashion lifestyle segments had meaningful differences between nationality and by year. Third, the US consumers tended to have conservative fashion-oriented lifestyle in 2008, however global consumers were changed to have active fashion lifestyle in 2010. This research will be useful to global brands in planning marketing strategies by offering specific information for global consumer fashion lifestyle.

• Computers and Concrete
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• v.25 no.4
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• pp.369-382
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• 2020

This paper presents a discussion of the Finite Element Analysis (FEA) when applied for the analysis of concrete elements reinforced with glass fibre reinforced polymer (GFRP) bars. The purpose of such nonlinear FEA model development is to create a tool that can be used for numerical parametric studies which can be used to extend the existing (and limited) experiment database. The presented research focuses on the numerical analyses of concrete beams reinforced with GFRP longitudinal and shear reinforcements. FEA of concrete members reinforced with linear elastic brittle reinforcements (like GFRP) presents unique challenges when compared to the analysis of members reinforced with plastic (steel) reinforcements, which are discussed in the paper. Specifically, the behaviour and failure of GFRP reinforced members are strongly influenced by the compressive response of concrete and thus modelling of concrete behaviour is essential for proper analysis. FEA was performed using the commercial software ABAQUS. A damaged-plasticity model was utilized to simulate the concrete behaviour. The influence of tension, compression, dilatancy, mesh, and reinforcement modelling was studied to replicate experimental test data of beams previously tested at the University of Waterloo, Canada. Recommendations for the finite element modelling of beams reinforced with GFRP longitudinal and shear reinforcements are offered. The knowledge gained from this research allows for the development of a rational methodology for modelling GFRP reinforced concrete beams, which subsequently can be used for extensive parametric studies and the formation of informed recommendations to design standards.

• Journal of the Korean Geographical Society
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• v.48 no.2
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• pp.272-287
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• 2013

This paper describes the importance of selecting explanatory variables(e.g. land price determinants) in hedonic pricing models employed in predicting real estate price, and explores dynamics of the land price determinants over time. The City of Junju was chosen as the study area, and repeated measured price data of standard lots over 17 years were analyzed. We applied a three-level modeling approach to this data in consideration of its nested data structure and longitudinal characteristics. Main land price determinants we focused on are primarily based on items included in the standard comparison table of land price, which is an official hedonic pricing model used by Government to estimate land price for tax levy. Our result shows that the land price fluctuation over 17 years was not uniform over the whole study area with each neighborhood revealing different price trend, and as such warrants longitudinal model components. In addition, some of determinants previously recognized as important were proved insignificant. It was also found that significant determinants at a particular time point lost its power gradually over time and vice versa. It is expected that more accurate prediction of price would be possible when taken account for this dynamics of price determinants over time in applying hedonic pricing model method.