• International Journal of Highway Engineering
• /
• v.15 no.2
• /
• pp.121-129
• /
• 2013

PURPOSES : This study deals with the traffic accidents of rotary in Korea. The objective of this study is to develop the accident models by age group based on the various data of rotaries. METHODS : In pursuing the above, this study gives particular attentions to classifying the accident data of 17 rotaries by age, collecting the data of geometric structure, traffic volume and others, and developing the models using SPSS 17.0 and EXCEL. RESULTS : First, 3 multiple linear regression models which were all statistically significant were developed. The value of model of under 30-49 age group were, however, evaluated to be 0.688 and be less than those of other models. Second, the most powerful variables were analyzed to be traffic volume in the model of under 30 age group, circulatory roadway width in the model of 30-49 age group, and the number of approach lane in the model of above 50 age group. Finally, the test results of accident models using RMSE were all evaluated to be fitted to the given data. CONCLUSIONS : This study propose install streetlights, speed humps and widen Circulatory as effective improvements for reduction of accident in rotary.

• BMB Reports
• /
• v.50 no.11
• /
• pp.546-553
• /
• 2017

Aging is a natural and gradual process in human life. It is influenced by heredity, environment, lifestyle, and disease. DNA methylation varies with age, and the ability to predict the age of donor using DNA from evidence materials at a crime scene is of considerable value in forensic investigations. Recently, many studies have reported age prediction models based on DNA methylation from various tissues and body fluids. Those models seem to be very promising because of their high prediction accuracies. In this review, the changes of age-associated DNA methylation and the age prediction models for various tissues and body fluids were examined, and then the applicability of the DNA methylation-based age prediction method to the forensic investigations was discussed. This will improve the understandings about DNA methylation markers and their potential to be used as biomarkers in the forensic field, as well as the clinical field.

• Structural Engineering and Mechanics
• /
• v.52 no.1
• /
• pp.97-113
• /
• 2014

In the present work appropriate concrete material models have been proposed to predict drying shrinkage and specific creep of High-performance concrete (HPC) using Artificial Neural Network (ANN). The ANN models are trained, tested and validated using 106 different experimental measured set of data collected from different literatures. The developed models consist of 12 input parameters which include quantities of ingredients namely ordinary Portland cement, fly ash, silica fume, ground granulated blast-furnace slag, water, and other aggregate to cement ratio, volume to surface area ratio, compressive strength at age of loading, relative humidity, age of drying commencement and age of concrete. The Feed-forward backpropagation networks with Levenberg-Marquardt training function are chosen for proposed ANN models and same implemented on MATLAB platform. The results shows that the proposed ANN models are more rational as well as computationally more efficient to predict time-dependent properties of drying shrinkage and specific creep of HPC with high level accuracy.

• Journal of Forest and Environmental Science
• /
• v.31 no.4
• /
• pp.255-260
• /
• 2015

Height growth models for Pinus thunbergii in Jeju Island were developed in this study using four widely used nonlinear growth models; Exponential, Modified Logistic, Chapman-Richards, and Weibull. All functions were found to be significant at the 1% level. Chapman-Richards model for height-DBH allometry and Weibull model for height-age allometry was chosen as the best model on the all validation. All the model curves showed the similar pattern. Additionally, there was no abnormal pattern when the previous studies were compared. Therefore, these models are highly expected to be used to estimate the tree height using DBH or age for Pinus thunbergii especially in Jeju Island.

• The Journal of the Society of Korean Medicine Diagnostics
• /
• v.15 no.2
• /
• pp.175-190
• /
• 2011

Objectives: Even though there has been no consensus on the concept of viscera organ between the oriental and western medicine, we tried to investigate the correlation between clinical biomarkers of five Jang and chronological age and develop the models for predicting five Jang biological ages by statistical analysis. Methods: We obtained data from about 120,000 subjects who visited health promotion centers for health promotion and disease prevention from January 2004 to June 2009. Participants were included if they were over 20 years old, and excluded if reported to have cardiovascular disease or other serious medical illness such as cancer, malignant hypertension, uncontrolled diabetes, cardiopulmonary insufficiency, liver disease, pancreatic disease or renal disease. Among the clinical biomarkers obtained, we selected the biomarkers which were associated with the function of 5 Jang in previous studies, or showed statistically significant correlation with age. Multiple regression models were used for building prediction models of biological age after adjusting for potential confounders for men and women, respectively. Pearson correlation coefficient was calculated to examine the linear relationship between age and various biomarkers, and multiple regression analysis was used for building the prediction models of five Jang biological ages for men and women, respectively. All statistical data analysis was performed by using SPSS Version 12.0 software and statistical significance was obtained if p<0.05. Results: For males, the best models were developed using 12, 2, 8, 3, and 4 biomarkers for predicting biological ages of heart, lung, liver, pancreas, and kidney, respectively (R2 = 0.57, 0.43, 0.11, 0.24, and 0.93, respectively). Similar to males, for the females, 10, 2, 8, 3, and 4 biomarkers were selected as the models respectively (R2 = 0.76, 0.44, 0.14, 0.38, and 0.89, respectively). Conclusions: As we have developed for the first time the models for predicting five Jang biological ages with common clinical biomarkers, it is expected that these models may be used as clinical supplementary tools in the evaluation of aging status and functional decline of five Jang according to age in health promotion centers and private clinics. At the same time, it is considered that the use as objective tools to evaluate aging status and functional decline of each Jang.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.22
• /
• pp.9731-9737
• /
• 2014

Large scale secular registry or surveillance systems have been accumulating vast data that allow mathematical modeling of cancer incidence and mortality rates. Most contemporary models in this regard use time series and APC (age-period-cohort) methods and focus primarily on predicting or analyzing cancer epidemiology with little attention being paid to implications for designing cancer registry, surveillance or evaluation initiatives. This research models age-specific cancer incidence rates using logistic growth equations and explores their performance under different scenarios of data completeness in the hope of deriving clues for reshaping relevant data collection. The study used China Cancer Registry Report 2012 as the data source. It employed 3-parameter logistic growth equations and modeled the age-specific incidence rates of all and the top 10 cancers presented in the registry report. The study performed 3 types of modeling, namely full age-span by fitting, multiple 5-year-segment fitting and single-segment fitting. Measurement of model performance adopted adjusted goodness of fit that combines sum of squred residuals and relative errors. Both model simulation and performance evalation utilized self-developed algorithms programed using C# languade and MS Visual Studio 2008. For models built upon full age-span data, predicted age-specific cancer incidence rates fitted very well with observed values for most (except cervical and breast) cancers with estimated goodness of fit (Rs) being over 0.96. When a given cancer is concerned, the R valuae of the logistic growth model derived using observed data from urban residents was greater than or at least equal to that of the same model built on data from rural people. For models based on multiple-5-year-segment data, the Rs remained fairly high (over 0.89) until 3-fourths of the data segments were excluded. For models using a fixed length single-segment of observed data, the older the age covered by the corresponding data segment, the higher the resulting Rs. Logistic growth models describe age-specific incidence rates perfectly for most cancers and may be used to inform data collection for purposes of monitoring and analyzing cancer epidemic. Helped by appropriate logistic growth equations, the work vomume of contemporary data collection, e.g., cancer registry and surveilance systems, may be reduced substantially.

• The Korean Journal of Pain
• /
• v.33 no.2
• /
• pp.153-165
• /
• 2020

Background: Well-validated risk prediction models help to identify individuals at high risk of diseases and suggest preventive measures. A recent systematic review reported lack of validated prediction models for low back pain (LBP). We aimed to develop prediction models to estimate the 8-year risk of developing LBP and its recurrence. Methods: A population based prospective cohort study using data from 435,968 participants in the National Health Insurance Service-National Sample Cohort enrolled from 2002 to 2010. We used Cox proportional hazards models. Results: During median follow-up period of 8.4 years, there were 143,396 (32.9%) first onset LBP cases. The prediction model of first onset consisted of age, sex, income grade, alcohol consumption, physical exercise, body mass index (BMI), total cholesterol, blood pressure, and medical history of diseases. The model of 5-year recurrence risk was comprised of age, sex, income grade, BMI, length of prescription, and medical history of diseases. The Harrell's C-statistic was 0.812 (95% confidence interval [CI], 0.804-0.820) and 0.916 (95% CI, 0.907-0.924) in validation cohorts of LBP onset and recurrence models, respectively. Age, disc degeneration, and sex conferred the highest risk points for onset, whereas age, spondylolisthesis, and disc degeneration conferred the highest risk for recurrence. Conclusions: LBP risk prediction models and simplified risk scores have been developed and validated using data from general medical practice. This study also offers an opportunity for external validation and updating of the models by incorporating other risk predictors in other settings, especially in this era of precision medicine.

• The Bulletin of The Korean Astronomical Society
• /
• v.37 no.1
• /
• pp.31.2-31.2
• /
• 2012

We present the Yonsei Evolutionary Population Synthesis (YEPS) models for spectroscopic and photometric evolutions of simple and composite stellar populations. The models are based on the most up-to-date Yonsei-Yale stellar evolutionary tracks and BaSel 3.1 flux libraries, and provide integrated spectroscopic quantities of Lick/IDS system including high-order Balmer absorption-lines. Special care has been taken to incorporate the systematic variation of horizontal branch (HB) morphology as functions of metallicity, age, alpha-element mixture, and helium abundance of simple stellar populations. Our models for normal-helium stellar populations indicate that the realistic modeling of HB and alpha-element brings about 5 Gyr and 0.1 dex differences in age and metallicity estimations, respectively, compared to those without these effects. The HB effect does not depend on the specific choice of stellar libraries and alpha-element enhancements, and this effect is non-negligible even in the metal sensitive absorption indices, such as Mg2 and Mg b. Comparison of the models to observations reveals that the HB and alpha-element effects are critical in understanding otherwise inexplicable phenomena found in globular cluster systems in the Milky Way and nearby galaxies, including the observed bimodality of the line strengths of globular clusters in massive galaxies. In addition, we found that helium-enhanced stellar populations, which are the major sources of extreme HB stars, bring about increased FUV, NUV fluxes, and thus the model colors of those filters become extremely blue. Age dating based on the YEPS model with normal-helium stellar populations reveals that the evidence for 'downsizing' of elliptical galaxies is found not only in the local field but also in Coma cluster, and that the mean age of elliptical galaxies in Coma cluster is about 1.4 Gyr younger than the mean age of those in the local field. We also find that our models with helium-enhanced subpopulations can naturally reproduce the strong UV-upturns observed in giant elliptical galaxies assuming an age similar to that of old GCs in the Milky Way.

• Structural Engineering and Mechanics
• /
• v.72 no.6
• /
• pp.737-746
• /
• 2019

Concrete mechanical properties change constantly with age, temperature, humidity and the other environmental factors. This research studies the effects of temperature and age on the development of concrete elastic modulus by a series of prism specimens. Elastic modulus test was conducted at various temperatures and ages in the laboratory to examine the effects of temperature and age on it. The experimental results reveal that the concrete elastic modulus decreases with the rise of temperature but increases with age. Then, a temperature coefficient K is proposed to describe the effects of temperature and validated by existing studies. Finally, on the basis of K, analytical models are proposed to determine the elastic modulus of concrete at a given temperature and age. The proposed models can offer designers an approach to obtain more accurate properties of concrete structures through the elastic modulus modification based on actual age and temperature, rather than using a value merely based on laboratory testing.

• Proceedings of the Korea Concrete Institute Conference
• /
• 1999.10a
• /
• pp.285-288
• /
• 1999

Creep is a major parameter to represent long-term behavior of concrete structures concerning serviceability and durability. The effect of creep is recently taking account into crack resistance analysis of early-age concrete concerning durability evaluation. Since existing creep prediction models were proposed to predict creep for hardened concrete, most of them cannot consider effectively the information on microstructure formation and hydration developed in the early-age concrete. In this study, creep tests for early-age concrete made of the type I cement and the type V cement are carried out respectively and creep prediction models are evaluated for the prediction of creep behavior in early-age concrete. A creep prediction model is modified for the prediction of creep in early-age concrete and also verified by comparing prediction results with results of creep tests on early-age concrete.