• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5669-5673
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• 2015

Background: Breast cancer is the most prevalent kind of cancer among women in Iran. Regarding the importance of cancer prevention and considerable variation of breast cancer incidence in different parts of the country, it is necessary to recognize regions with high incidence of breast cancer and evaluate the role of potential risk factors by use of advanced statistical models. The present study focussed on incidence of breast cancer in Iran at the province level and also explored the impact of some prominent covariates using Bayesian models. Materials and Methods: All patients diagnosed with breast cancer in Iran from 2005 to 2008 were included in the study. Smoking, fruit and vegetable intake, physical activity, obesity and the Human Development Index (HDI), measured at the province level, were considered as potential modulating factors. Gamma-Poisson, log normal and BYM models were used to estimate the relative risk of breast cancer in this ecological investigation with and without adjustment for the covariates. Results: The unadjusted BYM model had the best fit among applied models. Without adjustment, Isfahan, Yazd, and Tehran had the highest incidences and Sistan- Baluchestan and Chaharmahal-Bakhtiari had the lowest. With the adjusted model, Khorasan-Razavi, Lorestan and Hamedan had the highest and Ardebil and Kohgiluyeh-Boyerahmad the lowest incidences. A significantly direct association was found between breast cancer incidence and HDI. Conclusions: BYM model has better fit, because it contains parameters that allow including effects from neighbors. Since HDI is a significant variable, it is also recommended that HDI should be considered in future investigations. This study showed that Yazd, Isfahan and Tehran provinces feature the highest crude incidences of breast cancer.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.1
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• pp.13-20
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• 2012

In this study, the change pattern of hydrological response function as development has been observed. The target watershed was selected Tanbu sub-Basin in the Bocheong Basin. The applied channel networks are composed of 10 cases that are channel networks by strahler's ordering scheme and cases of all grids channel or the hillslope in basin. To each case of grid in basin, channel and hillslope drainage path lengths to outlet of basin are calculated, and hydrological response function was calculated by Nash Model. As results of this analysis, the peak discharge of hydrological response function is increased and peak time is shortened as development of channel networks. And based on statistical characteristics of hydrological response function, mean (lag time) and variance of travel time are reduced exponentially.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.4
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• pp.139-144
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• 2011

This study proposed a classification method of LIDAR data by using simultaneously the color information (R, G, B) and reflection intensity information (I) obtained from terrestrial LIDAR and by analyzing the association between these data through the use of statistical classification methods. To this end, first, the factors that maximize variance were calculated using the variables, R, G, B, and I, whereby the factor matrix between the principal factor and each variable was calculated. However, although the factor matrix shows basic data by reducing them, it is difficult to know clearly which variables become highly associated by which factors; therefore, Varimax method from orthogonal rotation was used to obtain the factor matrix and then the factor scores were calculated. And, by using a non-hierarchical clustering method, K-mean method, a cluster analysis was performed on the factor scores obtained via K-mean method as factor analysis, and afterwards the classification accuracy of the terrestrial LiDAR data was evaluated.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.5
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• pp.467-475
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• 2007

This study compared the sea surface wind pattern between model results from KMA operational model (RDAPS) and observational results from QuikSCAT in the 2005-2006 year. The mean spatial distributions of sea surface wind show the prominent seasonal patterns of summer and winter season adjacent to Korean Peninsular. The statistical analysis also shows well seasonal variation of sea surface wind patterns between model and observation results. The BIAS value represents less than -0.5 m/s and -1 m/s in summer and winter seasons, respectively. The spatially averaged correlation coefficient shows larger than 0.7 and 0.8 in summer and winter seasons, respectively. The correlation coefficient of winter season shows higher value than that of summer season in the comparison between model and observation. This results show that the RDAPS model simulate well strong sea surface wind in winter season rather than weak sea surface wind in summer season.

• Journal of radiological science and technology
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• v.42 no.6
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• pp.477-482
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• 2019

Recently, due to the increased use of medical radiation, the radiation exposure of radiation workers should be considered as well as medical exposure of patients. And it is recommended to close the door during radiography. however, In this study, when the door was inevitably opened for radiography, the proposed method was to install the shield as a method of reducing the exposure dose. And its efficiency was analyzed. In simple chest radiography, the measurement point was changed according to the measurement location. Dose rate were measured 10 times for each condition using a dosimeter. And the average value was derived. Using this, the change of dose according to the opening and closing of the door and the installation of the shield was analyzed. Using this, we compared and analyzed the dose change according to the door opening and closing and the installation of the shield, and significance was verified through the SPSS ver. 24. Depending on whether the door was opened or closed, 11,215.35%, 159.0%, 101.9% increased in front of the door in the consol room, behind the wall and behind the lead glass. Depending on the installing of the shield, the 49.2%, 29.6%, 19.9%, 30.6% decrease in front of the door in the examination and consol room, behind the wall and lead glass. In addition, statistical analysis was showed that there were significant differences in both the results according to whether the door was opened or closed and shielding(p<.05). Close the door during radiography. However, when the door should be opened, it was confirmed that the dose rate were reduced by installing the shield. Therefore, to optimize radiation protection, it is recommended to install shields when opening the door.

• Korean Journal of Applied Biomechanics
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• v.17 no.4
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• pp.1-8
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• 2007

The purpose of this study was to investigate the difference in the stride-to-stride variability between two treadmill conditions; traditional treadmill and special treadmill whose speed can be adjusted automatically by subject's walking speed. Eight male subjects (25.1 years, 172.7 cm, 66.6 kg) were participated in treadmill walking experiment. First, preferred walking speed (PWS) of each subject was determined. Second, each subject performed walking experiment with fixed PWS condition and with free PWS condition for 10 minutes. 3D motion capture system (Motion analysis Corp., USA) with 6 cameras was used to collect motion data with sampling frequency of 120Hz. Temporal and spatial variables for stride-to-stride variability were calculated. Coefficient of variance (CV) which quantifies the amount of variability and Detrended Fluctuation Analysis (DFA) which explains the structure (self-similarity) of the variability were used for analysis. Results showed that the amount of variability during free PWS condition was greater than that of fixed PWS condition. DFA results showed that there was a statistical difference between two treadmill conditions for the variables of step length, stance time, and double support time. From these results, it is possible that traditional treadmill study might give incorrect conclusion about gait variability study. Further study is necessary to clarify these matters by considering the number of subjects, experimental time, and gait variables for the study of stride-to-stride variability.

• Journal of Korean Society on Water Environment
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• v.36 no.5
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• pp.373-384
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• 2020

Hydrological models are based on a combination of parameters that describe the hydrological characteristics and processes within a watershed. For this reason, the model performance and accuracy are highly dependent on the parameters. However, model uncertainties caused by parameters with stochastic characteristics need to be considered. As a follow-up to the study conducted by Choi et al (2020), who developed a relatively simple semi-distributed hydrological model, we propose a tool to estimate the posterior distribution of model parameters using the Metropolis-Hastings algorithm, a type of Markov-Chain Monte Carlo technique, and analyze the uncertainty of model parameters and simulated stream flow. In addition, the uncertainty caused by the parameters of each version is investigated using the lumped and semi-distributed versions of the applied model to the Hapcheon Dam watershed. The results suggest that the uncertainty of the semi-distributed model parameters was relatively higher than that of the lumped model parameters because the spatial variability of input data such as geomorphological and hydrometeorological parameters was inherent to the posterior distribution of the semi-distributed model parameters. Meanwhile, no significant difference existed between the two models in terms of uncertainty of the simulation outputs. The statistical goodness of fit of the simulated stream flows against the observed stream flows showed satisfactory reliability in both the semi-distributed and the lumped models, but the seasonality of the stream flow was reproduced relatively better by the distributed model.

• Journal of Korean Society of Rural Planning
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• v.19 no.1
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• pp.81-90
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• 2013

The aim of the research was to analyze a correlation between rural villages and a space of amenity resources in order to provide objective basic data for rural renewal planning in the future. 15 villages were selected to analyze amenity resources. A Space Syntax Method(SSM) was used to analyze a spacial structure of each village and location characteristics of amenity resources. Finally, Statistical Package for the Social Sciences(SPSS) was used for a cluster analysis. The results of spacial analysis showed that the MeanDepth of rural villages was 4.482 and Global Integration Value(GInteg) was 0.956. Relatively, a depth was lower and GInteg was higher, compared to other villages. Rural villages were easily recognized and accessible by outsiders, compared to mountain and fishing villages. In the case of rural villages, the MeanDepth of amenity resources was low and GInteg was high in the results of cluster analysis using a nonhierachical method. Results indicated that an access was easy and amenity resources were closely located each other. However, the deviation of each village was great in mountain villages. This research suggests that an effective maintenance of road network for improving accessibility would be given priority in an undeveloped farming and fishing villages' renewal. Especially, using a spacial analysis in village renewal planning process can improve accessibility and maximize an utilization of public facilities and amenity resources.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.236-241
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• 1998

The NOAA AVHRR remote sense SST data, collected by the National Fisheries Research and Development Institute (NFRDI), are analyzed in order to understand the spatial and temporal distributions of SST in the seas adjacent to Korea. Our study is based on 10-day SST images during last 7 years (1991-1997). For a time series analysis of multiple 557 images, all of images must be aligned exactly at the same position by adjusting the scales and positions of each SST image. We devised an algorithm which yields automatic detections of cloud pixels from multiple SST images. The cloud detection algorithm is based on a physical constraint that SST anomalies in the ocean do not exceed certain limits (we used $\pm$ 3$^{\circ}C$ as a criterion of SST anomalies). The remote sense SST data are tuned by comparing remote sense data with observed SST at coastal stations. Seasonal variations of SST are studied by harmonic fit of SST normals at each pixel. The SST anomalies are studied by statistical method. We found that the SST anomalies are rather persistent with time scales between 1 and 2 months. Utilizing the persistency of SST anomalies, we devised an algorithm for a prediction of future SST Model fit of SST anomalies to the Markov process model yields that autoregression coefficients of SST anomalies during a time elapse of 10 days are between 0.5 and 0.7. We plan to improve our algorithms of automatic cloud pixel detection and prediction of future SST. Our algorithm is expected to be incorporated to the operational real time service of SST around Korea.

• Journal of Korea Water Resources Association
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• v.33 no.3
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• pp.279-288
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• 2000

The impact of land slope to the degree of flow divergence was considered employing distributional applications of slope exponents in the now directlOn algoriUnns. Lmear, exponential and ]X)wer law of distributional functIons were employed to address the variation of slope exponents m a terrain analysis. Dongok subwatershed at Wichun test watershed was selected as a study area. Digital Elevation Models of 20m, 30m, 40m and 50m grid size were made to perfonn the analysis. Various calcualtion methodologies of topographic index and the impact of grid sizes were investigated in terms of statistical and spatial aspects. DIstributional applications of slope e.xponents made it possible to represent the flow divergence and convergence about the ten-ain characteristics. The Monte~Carlo method was used to simulate six runoff events to check the impact of topographic factor in the runoff simulation.