• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.113-117
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• 2016

Quantile regression is an efficient method for predicting and estimating the relationship between explanatory variables and percentile points of the response distribution, particularly for extreme percentiles of the distribution. To study the relationship between urbanization and cancer morbidity, we here applied quantile regression. This cross-sectional study was conducted for 9 cancers in 345 cities in 2007 in Iran. Data were obtained from the Ministry of Health and Medical Education and the relationship between urbanization and cancer morbidity was investigated using quantile regression and least square regression. Fitting models were compared using AIC criteria. R (3.0.1) software and the Quantreg package were used for statistical analysis. With the quantile regression model all percentiles for breast, colorectal, prostate, lung and pancreas cancers demonstrated increasing incidence rate with urbanization. The maximum increase for breast cancer was in the 90th percentile (${\beta}$=0.13, p-value<0.001), for colorectal cancer was in the 75th percentile (${\beta}$=0.048, p-value<0.001), for prostate cancer the 95th percentile (${\beta}$=0.55, p-value<0.001), for lung cancer was in 95th percentile (${\beta}$=0.52, p-value=0.006), for pancreas cancer was in 10th percentile (${\beta}$=0.011, p-value<0.001). For gastric, esophageal and skin cancers, with increasing urbanization, the incidence rate was decreased. The maximum decrease for gastric cancer was in the 90th percentile(${\beta}$=0.003, p-value<0.001), for esophageal cancer the 95th (${\beta}$=0.04, p-value=0.4) and for skin cancer also the 95th (${\beta}$=0.145, p-value=0.071). The AIC showed that for upper percentiles, the fitting of quantile regression was better than least square regression. According to the results of this study, the significant impact of urbanization on cancer morbidity requirs more effort and planning by policymakers and administrators in order to reduce risk factors such as pollution in urban areas and ensure proper nutrition recommendations are made.

• Smart Media Journal
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• v.3 no.1
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• pp.9-15
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• 2014

In these days, along with the extreme popularity of online social network services, it becomes an important problem understanding the role of social network in the research of message dissemination. Past studies of message dissemination over online social network services mostly consider the coverage of message dissemination and the methods to maximize it. But, these works lack of the consideration of the impact of multi channel social network, which has multiple communication channel with distinct properties of message transfer and various users with distinct channel preferences. In this paper, the new message dissemination model over multi-modal multi-channel social network, the Delay Weighted Independent Cascade Model, is proposed. The proposed model considers various channels including online social network service, email, SMS messaging, phone and mouth-to-mouth and their distinct message transfer properties. In order to consider the various user properties, the different value of probability of forwarding a message and the different preference of communication channel is considered. Moreover, the proposed model considers the distribution of user location and allows to analyze the properties of message dissemination under various scenarios. Based on the proposed model, a message dissemination simulator is generated and the message disseminations on various scenarios are analyzed.

• Journal of Biosystems Engineering
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• v.42 no.3
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• pp.136-146
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• 2017

Purpose: This paper presents an appropriate wrapping method by analyzing the pressure distribution applied to a bale surface, along with the change in pressure according to an increase in the number of film layers in rice straw bales, which account for 74% of the total bulky feed supply in Korea. Methods: A model with the shape of an actual bale was fabricated to analyze the distribution of surface pressure in bale wrapping, and the pressure was measured. Experiments were conducted to analyze the pressure using eight different layer numbers (2, 4, 6, 8 10, 12, 14, and 16 layers) at five wrapping speeds (27, 29, 31, 33, and 35 rpm). Results: The maximum pressure applied to a circular bale by the film occurred at the center of the end of the bale, whereas the minimum pressure occurred at the center of the bale side. An extreme value ratio between the minimum and maximum pressures was distributed as 8.5-56.6%, which was improved with an increase in rotation speed. The an uneven pressure distribution occurred because the number of film overlaps was 8.24-times greater at the center of the bale's end than at the center of the ba le side. At a level 5 rotation speed, the minimum pressure was $P_{LV5-M1}=0.0625{\sigma}^2+36.173{\sigma}-36.753$ ($R^2=0.9845$) at $M_1$, and the maximum pressure was $P_{LV5-M6}=5.5552{\sigma}^2+41.05{\sigma}-39.071$ at $M_2$, revealing a correlation of $R^2=0.9983$. Conclusions: To replace four layers with six layers, 2-4 layers were added only to the side of the bale, and the minimum pressure at $M_1$ was then improved from that at four layers to that at six layers, and the amount of film consumed for 4-6 layers was reduced by 84.6%.

• Earthquakes and Structures
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• v.5 no.4
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• pp.395-416
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• 2013

The magneto-rheological (MR) damper contributes to the new technology of structural vibration control. Its developments and applications have been paid significant attentions in earthquake engineering in recent years. Due to the shortages, however, inherent in deterministic control schemes where only several observed seismic accelerations are used as the trivial input and in classical stochastic optimal control theory with assumption of white noise process, the derived control policy cannot effectively accommodate the performance of randomly base-excited engineering structures. In this paper, the experimental and analytical studies on stochastic seismic response control of structures with specifically designed MR dampers are carried out. The random ground motion, as the base excitation posing upon the shaking table and the design load used for structural control system, is represented by the physically based stochastic ground motion model. Stochastic response analysis and reliability assessment of the tested structure are performed using the probability density evolution method and the theory of extreme value distribution. It is shown that the seismic response of the controlled structure with MR dampers gain a significant reduction compared with that of the uncontrolled structure, and the structural reliability is obviously strengthened as well.

• Wind and Structures
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• v.35 no.1
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• pp.21-34
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• 2022

Gust factor is an important parameter for the conversion between peak gust wind and mean wind speed used for the structural design and wind-related hazard mitigation. The gust factor of typhoon wind is observed to show a significant dispersion and some differences with large-scale weather systems, e.g., monsoons and extratropical cyclones. In this study, insitu measurement data captured by 13 meteorological towers during a strong typhoon Morakot are collected to investigate the statistical characteristics, height and wind speed dependency of the gust factor. Onshore off-sea and off-land winds are comparatively studied, respectively to characterize the underlying terrain effects on the gust factor. The theoretical method of peak factor based on Gaussian assumption is then introduced to compare the gust factor profiles observed in this study and given in some building codes and standards. The results show that the probability distributions of gust factor for both off-sea winds and off-land winds can be well described using the generalized extreme value (GEV) distribution model. Compared with the off-land winds, the off-sea gust factors are relatively smaller, and the probability distribution is more leptokurtic with longer tails. With the increase of height, especially for off-sea winds, the probability distributions of gust factor are more peaked and right-tailed. The scatters of gust factor decrease with the mean wind speed and height. AS/NZ's suggestions are nearly parallel with the measured gust factor profiles below 80m, while the fitting curve of off-sea data below 120m is more similar to AIJ, ASCE and EU.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.24 no.2
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• pp.120-127
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• 2012

Exploratory data analysis was carried out by using the long-term wave climate data in Sokcho coastal zone. The main features found in this study are as follows. The coefficient of variations on the wave height and period are about 0.11 and 0.02, respectively. It also shows that the annual components of the wave height and period are dominant and their amplitudes are 0.24 m and 0.56 seconds, respectively. The amount of intra-annual variation range is about two times greater than that of the inter-annual variation range. The distribution shapes of the wave data are very similar to the log-normal and GEV(generalized extreme value) functions. However, the goodness-of-fit tests based on the KS test show as "rejected" for all suggested density functions. Then, the structure of the timeseries wave height data is roughly estimated as AR(3) model. Based on the wave duration results, it is clearly shown that the continuous and maximum duration is decreased as a power function shape and the total duration is exponentially decreased. Meanwhile, the environment of the Sokcho coastal zone is classified as a wave-dominated environment.

• Journal of Korea Water Resources Association
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• v.50 no.10
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• pp.661-671
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• 2017

The objective of this study was to analyze the flood stage considering the uncertainty caused by the river roughness coefficients and discharge. The methodology of this study involved the GLUE (Generalized Likelihood Uncertainty Estimation) to quantify the uncertainty bounds applying three different storm events. The uncertainty range of the roughness was 0.025~0.040. In case of discharge, the uncertainty stemmed from parameters in stage-discharge rating curve, if h represents stage for discharge Q, which can be written as $Q=A(h-B)^C$. Parameters in rating curve (A, B and C) were estimated by non-linear regression model and assumed by t distribution. The range of parameters in rating curve was 5.138~18.442 for A, -0.524~0.104 for B and 2.427~2.924 for C. By sampling 10,000 parameter sets, Monte Carlo simulations were performed. The simulated stage value was represented by 95% confidence interval. In storm event 1~3, the average bound was 0.39 m, 0.83 m and 0.96 m, respectively. The peak bound was 0.52 m, 1.36 m and 1.75 m, respectively. The recurrence year of each storm event applying the frequency analysis was 1-year, 10-year and 25-year, respectively.

• Journal of Korea Water Resources Association
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• v.49 no.8
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• pp.645-656
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• 2016

The study performed a regional flood frequency analysis and proposed a regression equation to estimate design floods corresponding to return periods for ungauged basins in Geum-river basin. Five preliminary tests were employed to investigate hydrological independence and homogeneity of streamflow data, i.e. the lag-one autocorrelation test, time homogeneity test, Grubbs-Beck outlier test, discordancy measure test ($D_i$), and regional homogeneity measure (H). The test results showed that streamflow data were time-independent, discordant and homogeneous within the basin. Using five probability distributions (generalized extreme value (GEV), three-parameter log-normal (LN-III), Pearson type 3 (P-III), generalized logistic (GLO), generalized Pareto (GPA)), comparative regional flood frequency analyses were carried out for the region. Based on the L-moment ratio diagram, average weighted distance (AWD) and goodness-of-fit statistics ($Z^{DIST}$), the GLO distribution was selected as the best fit model for Geum-river basin. Using the GLO, a regression equation was developed for estimating regional design floods, and validated by comparing the estimated and observed streamflows at the Ganggyeong station.

• Journal of the Korean earth science society
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• v.43 no.3
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• pp.367-385
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• 2022

This study evaluates the temperature and precipitation results in East Asia simulated from the Hadley Centre Global Environmental Model version 3 regional climate model (HadGEM3-RA) developed by the UK Met Office. The HadGEM3-RA is conducted in the Coordinated Regional climate Downscaling Experiment-East Asia (CORDEX-EA) Phase II domain for 15 year (2000-2014). The spatial distribution of rainbands produced from the HadGEM3-RA by the summer monsoon is in good agreement with the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of water resources (APRODITE) data over the East Asia. But, precipitation amount is overestimated in Southeast Asia and underestimated over the Korean Peninsula. In particular, the simulated summer rainfall and APRODITE data show the least correlation coefficient and the maximum value of root mean square error in South Korea. Prediction of temperature in Southeast Asia shows underestimation with a maximum error during winter season, while it appears the largest underestimation in South Korea during spring season. In order to evaluate local predictability, the time series of temperature and precipitation compared to the ASOS data of the Seoul Meteorological Station is similar to the spatial average verification results in which the summer precipitation and winter temperature underestimate. Especially, the underestimation of the rainfall increases when the amounts of precipitation increase in summer. The winter temperature tends to underestimate at low temperature, while it overestimates at high temperature. The results of the extreme climate index comparison show that heat wave is overestimated and heavy rainfall is underestimated. The HadGEM3-RA simulated with a horizontal resolution of 25 km shows limitations in the prediction of mesoscale convective system and topographic precipitation. This study indicates that improvement of initial data, horizontal resolution, and physical process are necessary to improve predictability of regional climate model.