• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.10
• /
• pp.4143-4145
• /
• 2014

Background: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) Ewing sarcoma (ES) outcome data. The aim of this study was to identify and optimize ES-specific survival prediction models and sources of survival disparities. Materials and Methods: This study analyzed socio-economic, staging and treatment factors available in the SEER database for ES. 1844 patients diagnosed between 1973-2009 were used for this study. For the risk modeling, each factor was fitted by a Generalized Linear Model to predict the outcome (bone and joint specific death, yes/no). The area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. Results: The mean follow up time (S.D.) was 74.48 (89.66) months. 36% of the patients were female. The mean (S.D.) age was 18.7 (12) years. The SEER staging has the highest ROC (S.D.) area of 0.616 (0.032) among the factors tested. We simplified the 4-layered risk levels (local, regional, distant, un-staged) to a simpler non-metastatic (I and II) versus metastatic (III) versus un-staged model. The ROC area (S.D.) of the 3-tiered model was 0.612 (0.008). Several other biologic factors were also predictive of ES-specific survival, but not the socio-economic factors tested here. Conclusions: ROC analysis measured and optimized the performance of ES survival prediction models. Optimized models will provide a more efficient way to stratify patients for clinical trials.

• Journal of the Korea Society of Computer and Information
• /
• v.12 no.6
• /
• pp.105-113
• /
• 2007

A gene regulatory network is a network of genes representing how genes influence the activities of other genes. Nowadays from microarray experiments, a large number of measurements on the expression levels of genes are available. One of typical data is the so-called "steady-state model" data measuring the expression levels of other genes after knocking out a particular gene. This paper shows how to reverse engineer a parsimonious gene regulatory network, using these measurement data. Our model considers auto-regulation, which forms a cycle in a genetic network. We also model repressor and enhancer roles of genes. which are not considered in previous known methods.

• Journal of Information Technology Applications and Management
• /
• v.12 no.4
• /
• pp.105-121
• /
• 2005

Ubiquitous computing(UC) is an emerging paradigm. Its arrival as a mainstream is expected to trigger innovative UC-driven business models (UCBMs). Currently, there is no Parsimonious methodology to analyze and provide diagnostics for UCBMs. With this research, we propose a analytical architecture that enables the assessment of an UCBM in its structural strengths and weaknesses. With value logic as the cornerstone, the architecture is composed of value actors, value assets, value context, business value Propositions, customer value propositions, value creation logics, and value assumptions. Dimensional variables are initially Identified based on the review of business model literature. Then, their significance is empirically examined through 14 UCBM scenarios, and variables that are expected to Play an important role in the UCBM assessment are decided. Finally, by analyzing the scenarios in terms of the dimensional variables, we attempted to summarize general characteristics of emerging UCBMs.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.28 no.2
• /
• pp.18-27
• /
• 2000

The importance of constraints has been one of major issues in recreation for prediction of choice behavior; however, traditional conjoint choice model did not consider the effects of these variables or fail to integrate them into choice model adequately. The purposes of this research are (a) to estimate the effects of constraints in theme park choice behavior by the constraints-induced conjoint choice model, and (b) to test additional explanatory power of the additional constraints in this suggested model against the more parsimonious traditional model. A leading polling agency was employed to select respondents. Both alternative generating and choice set generating fractional factorial design were conducted to meet the necessary and sufficient conditions for calibration of the constraints-induced conjoint choice model. Th alternative-specific model was calibrated. The log-likelihood ratio test revealed that suggested model was accepted in the favor of the traditional model, and the goodness-of-fit($\rho$$^2$) of suggested and traditional model was 0.48427 and 0.47950, respectively. There was no difference between traditional and suggested model in estimates of attribute levels of car and shuttle bus because alternatives were created to estimate the effects of constraints independently from mode related variables. Most parameters values of constraints had the expected sign and magnitude: the results reflected the characteristics of the theme parks, such as abundance of natural attractions and poor accessibility in Everland, location of major fun rides indoor in Lotte World, city park like characteristics of Dream Land, and traffic jams in Seoul. Instead of the multinomial logit model, the nested logit model is recommended for future researches because this model more reasonably reflects the real decision-making process in park choice. Development of new methodology too integrate this hierarchical decision-making into choice model is anticipated.

• Journal of Korean Academy of Nursing
• /
• v.28 no.2
• /
• pp.344-357
• /
• 1998

This study was designed to construct a model that predicts the quality of life of family caregivers with a chronically ill patient. The hypothetical model was developed based on the findings from past studies on quality of life and on the family with a chronically ill patient. Data were collected by self-reported questionnaires from 200 family caregivers in Seoul & Kyung Gi-Do, from May 1 to July 21, 1997. Data were analyzed using descriptive statistics and correlation analysis. The Linear Structural Relationship(LISREL) modeling process was used to find the best fit model which predicts causal relationships among variables. The results are as follows : 1. The overall fit of the hypothetical model to the data was moderate [X$^2$=31.54(df=23, p=.11), GFI=.96, AGFI=.91, RMR=.04]. 2. Paths of the model were modified by considering both its theoretical implication and the statistical significance of the parameter estimates. Compared to the hypothetical model, the revised model has become parsimonious and had a better fit to the data expect chi-square value(GFI=.95, AGFI=.91, RMR=.04). 3. Some of predictive factors, especially economic status, physical ability to perform daily-life activity, period after disease-onset, social support and fatigue revealed indirect effects on the quality of life of family caregivers with a chronically ill patient. 4. The factors, burden and role satisfaction revealed significant direct effects on the quality of life of family caregivers with a chronically ill patient. 5. All predictive variables of quality of life of family caregivers with a chronically ill patient, especially economic status, physical ability to perform daily-life activity, period after disease-onset, social support, fatigue, burden and role satisfaction explained 38.0% of the total variance in the model. In conclusion, the derived model in this study is considered appropriate in explaining and predicting quality of life of family caregivers with a chronically ill patient. Therefore it can effectively be used as a reference model for further studies and suggests direction in nursing practice.

• Journal of Korean Academy of Nursing
• /
• v.26 no.2
• /
• pp.320-336
• /
• 1996

Health promoting behaviors of an individual are affected by various variables. Recently, there has been a growing concern over important health problems of the middle aged women. Physiological changes in the middle aged women and their responsibility for family care can result in physical and psychological burden experienced by middle aged women. This study was designed to test Pender's model and thus purpose a model that explains health promoting behaviors among middle-aged women in Korea. The hypothetical model was developed based on the Pender's health promoting model and the findings from past studies on women's health. Data were collected by self-reported questionnaires from 863 women living in Seoul, between 20th, April and 15th, July 1995. Data were analyzed using descriptive statistics and correlation analysis. The Linear Structural Relationship(LISREL) modeling process was used to find the best fit model which assumes causal relationships among variables. The results are as follows : 1. The Overall fit of the hypothetical model to the data was good expect chi-square value（GFI＝.96, AGFI＝.91, RMR＝.04）. 2. Paths of the model were modified by considering both its theoretical implication and statistical significance of the parameter estimates. Compared to the hypothetical model, the revised model has become parsimonious and had a better fit to the data expect chi-square value（GFI＝.95, AFGI＝ .92. RMR＝.04）. 3. Some of modifying factors, especially age, occupation, educational levels and body mass index (BMI) are revealed significant effects on health promoting behaviors. 4. Some of cognitive-perceptual factors, especially internal health locus of control, self-efficacy and perceptive health status are revealed significant effects on health promoting behaviors. 5. All predictive variables of health promoting behaviors, especially age, occupation, educational levels, body mass index(BMI), internal health locus of control, self-efficacy ＆ perceptive health status are explained 20.0％ of the total variance in the model.

• Journal of Korean Society on Water Environment
• /
• v.35 no.4
• /
• pp.316-331
• /
• 2019

Carbon dioxide($CO_2$) emission from rivers to the atmosphere is a key component in the global carbon cycle. Most of the rivers are supersaturated with $CO_2$. At a global scale, the amount of $CO_2$ emission from rivers is reported to be five-fold greater than that from lakes and reservoirs, but relevant data are rare in Korea. The objectives of this study is to estimate the $CO_2$ net atmospheric flux(NAF) from the upstream of Gangjeong-Goryeong Weir(GGW), Dalseong Weir(DSW), Hapcheon-Changnyeong Weir(HCW), and Changnyeong-Haman Weir(CHW) located in Nakdong River South Korea) using field and laboratory experiments and to apply data mining techniques to develop parsimonious prediction models that can be used to estimate $CO_2$ NAF with physical and water quality variables that can be collected easily. As a result, the study sites were all heterotrophic systems that often released $CO_2$ to the atmosphere, except when the algal photosynthesis was active.The median $CO_2$ NAF was minimum $391.5mg-CO_2/m^2$ day at GGW and maximum $1472.7mg-CO_2/m^2$ day at DSW. The $CO_2$ NAF showed a negative correlation with pH and Chl-a since the overgrowth of the algae consumed $CO_2$ in the water and increased the pH. As the parsimonious multiple regression model and random forest model developed, this study showed an excellent performance with the $Adj.R^2$ value higher than 0.77 in all weirs. Thus, these methods can be used to estimate $CO_2$ NAF in the river even if there is no $pCO_2$ measurement data.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.3
• /
• pp.138-147
• /
• 2021

The purpose of this study was to develop a measuring tool for the health promotion behavior of Korean nurses. This would address the lack of a proven tool that reflects the nature of the nurses' nursing environment. This study was conducted on 530 nurses from January to December 2019. A literature review and focus group interview were conducted, data analysis was carried out to measure validity and reliability, and the conceptual framework was constructed by applying the IMB model. Five factors namely self-concept (2 questions), hospital life management (4 questions), knowledge and information regarding health (5 questions), physical and mental stress management (3 questions), and work adaptation (2 questions) were framed into 16 questions. The model fit was 346.23 (��<.001), Parsimonious Normed Fit Index (PNFI) was 0.60, and Parsimonious Comparative Fit Index (PCFI) was 0.63, which met the acceptance criteria, and the Root Mean Square Error of Approximation (RMSEA) was 0.10. Goodness of Fit Index (GFI) was 0.88, Comparative Fit Index (CFI) was 0.85, and Incremental Fit Index (IFI) was 0.85 which were found to be acceptable as per the applicable standards. All items had a Cronbach's �� score of .85, which ensured stable reliability. The nurse's health promotion behavior measurement tool developed in this study will be used to measure the nurse's health promotion behavior in terms of nursing practice which will help in understanding the broad contours of this behavior.

• Journal of Physiology & Pathology in Korean Medicine
• /
• v.34 no.4
• /
• pp.209-214
• /
• 2020

The association of cold-heat (CH) pattern and anthropometry/body composition has been suggested in that they are related to thermoregulation. We aimed to study the association of CH pattern and anthropometry/body composition. A total of 1479 individuals aged 50-80 years were included in the study, and their CH pattern were evaluated by a self-administered questionnaire. After adjustment for age and sex, the CH score were significantly correlated with weight, BMI (body mass index), body surface area, waist-hip ratio, fat free mass, body fat mass, body cell mass, intracellular water, extracellular water, and basal metabolic rate; however, the correlation coefficients were mostly low (0.15-0.24). The selected variables for predicting CH score were various according to the methods used for variable selection; however, the adjusted R-squared of the final models were all around 0.12. Thus the most parsimonious model could be the one that includes sex and BMI. In conclusion, various anthropometry and body composition indices were associated with CH pattern. Future studies are necessary to improve the performance of the prediction model.

• The Journal of Korean Medicine
• /
• v.42 no.4
• /
• pp.185-196
• /
• 2021

Objectives: Many symptoms of cold and heat patterns are related to the thermoregulation of the body. Thus, we aimed to study the association of cold and heat patterns with anthropometry/body composition. Methods: The cold and heat patterns of 2000 individuals aged 30-55 years were evaluated using a self-administered questionnaire. Results: Among the anthropometric and body composition variables, body mass index (-0.37, 0.39) and fat mass index (-0.35, 0.38) had the highest correlation coefficients with the cold and heat pattern scores after adjustment for age and sex in the cold-heat group, while the correlation coefficients were relatively lower in the non-cold-heat group. In the cold-heat group, the most parsimonious model for the cold pattern with the variables selected by the best subset method and Lasso included sex, body mass index, waist-hip ratio, and extracellular water/total body water (adjusted R² = 0.324), and the model for heat pattern additionally included age (adjusted R² = 0.292). Conclusions: The variables related to obesity and water balance were the most useful for predicting cold and heat patterns. Further studies are required to improve the performance of prediction models.