• Earthquakes and Structures
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• v.8 no.5
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• pp.977-994
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• 2015

In this study, earthquake loads are investigated statistically and compared with the nominal earthquake loads calculated according to the Turkish Earthquake Code, namely: "Specifications for Structures to be Built in Earthquake Areas". For this purpose, the "actual" mean load values estimated from statistical methods and the nominal load values computed according the Seismic Code are compared, with respect to some variations in the basic parameters, such as the importance factor, building height, site coefficient, seismic zone and seismic load reduction factor. In addition to the data compiled from different regions of Turkey, the published data and information in the foreign literature are also used in the determination of the earthquake load statistics. Although the dead and live loads acting on a structure are independent of the geographical location of the structure, environmental loads, such as earthquake loads are highly dependent on the location of the structure. Accordingly, for the assessment of statistical parameters associated with earthquake loads, twelve different locations which can represent the different seismic zones of Turkey as accurately as possible are chosen. As a result of the code calibration procedure considered in this study, it is observed that the load values obtained from the Turkish Seismic Code may overestimate or underestimate the actual seismic loads in some of the seismic zones.

• The Korean Journal of Applied Statistics
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• v.31 no.3
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• pp.329-342
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• 2018

Nomogram is a statistical tool that visualizes the risk factors of the disease and then helps to understand the untrained people. This study used risk factors of chronic obstructive pulmonary disease (COPD) and compared with logistic regression model and naïve Bayesian classifier model. Data were analyzed using the Korean National Health and Nutrition Examination Survey 6th (2013-2015). First, we used 6 risk factors about COPD. We constructed nomogram using logistic regression model and naïve Bayesian classifier model. We also compared the nomograms constructed using the two methods to find out which method is more appropriate. The receiver operating characteristic curve and the calibration plot were used to verify each nomograms.

• Journal of Radiation Protection and Research
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• v.32 no.1
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• pp.9-13
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• 2007

From HPGe calibration spectrum of liquid mixed source in cylindrical vial, we developed simulated spectrum for spectrum analysis education. It is the spectrum that combine peaks separated from measured spectrum. After that, spectrum removed statistical variation of channel counts. Statistical fluctuation of the spectrum is made by Box-Muller function. The spectrum contains 18 peaks. The peak's centroid and area were defined exactly. Developed spectra are calibration spectrum, sample spectrum, background spectrum and spectra for efficiency correction for geometry and cascade coincidence.

• 한국전산유체공학회:학술대회논문집
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• 2011.05a
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• pp.286-290
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• 2011

This paper introduces the optimum macro-siting of a potential site for an offshore wind farm around Jeju Island using the RDAPS sea wind model. The statistical model was developed by analyzing the sea wind data from RDAPS model, and the meso-scale digital wind map was prepared. To develop the high resolution spatial calibration model, Artificial Neural Network(ANN) models were used to construct the wind and bathymetric maps. Accuracy and consistency of wind/bathymetric spatial calibration models were obtained using analysis of variance. The optimization problem was defined to maximize the energy density satisfying the criteria of maximum water depth and maximum distance from the coastline. The candidate site was selected through Genetic Algorithm(GA). From the results, it is possible to predict roughly a candidate site location for the installation of the offshore wind jam, and to evaluate the wind resources of the proposed site.

• Communications for Statistical Applications and Methods
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• v.25 no.3
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• pp.297-306
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• 2018

Cardiovascular disease (CVD) is the leading cause of death worldwide and has a high mortality rate after onset; therefore, the CVD management requires the development of treatment plans and the prediction of prevalence rates. In our study, age, income, education level, marriage status, diabetes, and obesity were identified as risk factors for CVD. Using these 6 factors, we proposed a nomogram based on a $na{\ddot{i}}ve$ Bayesian classifier model for CVD. The attributes for each factor were assigned point values between -100 and 100 by Bayes' theorem, and the negative or positive attributes for CVD were represented to the values. Additionally, the prevalence rate can be calculated even in cases with some missing attribute values. A receiver operation characteristic (ROC) curve and calibration plot verified the nomogram. Consequently, when the attribute values for these risk factors are known, the prevalence rate for CVD can be predicted using the proposed nomogram based on a $na{\ddot{i}}ve$ Bayesian classifier model.

• Communications for Statistical Applications and Methods
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• v.28 no.4
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• pp.339-350
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• 2021

In medical research, the risk factors associated with human diseases need to be identified to predict the incidence rate and determine the treatment plan. Logistic regression analysis is primarily used in order to select risk factors. However, individuals who are unfamiliar with statistics outcomes have trouble using these methods. In this study, we develop a nomogram that graphically represents the numerical association between the disease and risk factors in order to identify the risk factors for delirium and to interpret and use the results more effectively. By using the logistic regression model, we identify risk factors related to delirium, construct a nomogram and predict incidence rates. Additionally, we verify the developed nomogram using a receiver operation characteristics (ROC) curve and calibration plot. Nursing home, stroke/epilepsy, metabolic abnormality, hemodynamic instability, and analgesics were selected as risk factors. The validation results of the nomogram, built with the factors of training set and the test set of the AUC showed a statistically significant determination of 0.893 and 0.717, respectively. As a result of drawing the calibration plot, the coefficient of determination was 0.820. By using the nomogram developed in this paper, health professionals can easily predict the incidence rate of delirium for individual patients. Based on this information, the nomogram could be used as a useful tool to establish an individual's treatment plan.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.178-180
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• 2016

TMDE(Test Measurement and Diagnostic Equipment) which is using in the military weapon system should perform the periodic calibration to maintain a measurement reliability during the life cycle, organizations are faced with increasing pressures to minimize costs while improving the reliability of test equipment. Previous studies suggest that reliability models are determined by considering simple size and characteristics of equipment, however an applying single Model may not be fit well maintenance data of many kinds of TMDEs. This paper presents that recommending an optimal calibration interval through the goodness of fit test with verifying statistical significance level among the several intervals which are computed with using major reliability models. According to the result of applying the actual proposed of calibration interval analysis method for various types of equipment, reliabilities are maintained for the end of calibration intervals.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1335-1338
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• 2002

This paper presents the analysis of the required limit on a multibeam active phased array antenna (APAA) aperture using the statistical simulation for a High Altitude Platform Station (HAPS). The simulation takes into account the random errors caused by the non-identity of the array elements and the inaccuracy of the antenna calibration. The results of our statistical simulation show that the strict requirements on the sidelobe envelope for HAPSs can be met when the amplitude and phase distribution errors are minor, a condition which may be achieved by using digital beam forming.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.501-504
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• 2001

The use of error compensation techniques has been recognized as an effective way in the improvement of the accuracy of a machine tool. The laser measurement method for identifying position errors of machine tool has the disadvantages such as high cost, long calibration time and usage of volumetric error synthesis model. Accordingly, this paper deals with analysis of the position errors of a machine tool using ball bar test without using complicated error synthesis model. Statistical analysis method was adopted in this paper for deriving position errors using hemispherical helix ball bar test.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.10
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• pp.1219-1230
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• 2004

Comparing to the gravimetric and volumetric method, the flowmeter calibration based on the master meter method is relatively economical and convenient, especially for high flowrate. The uncertainty of flow quantity and flowrate using the master meter method was evaluated according to the GUM (Guide to the Expression of Uncertainty in Measurement). In order to apply for the wider flow range, two master meters (electromagnetic flow meter) were employed as reference flowmeters. The uncertainty of the master meter was obtained by combining the statistical variation of the repeated measurements and the variation of fluid density and pipe material due to temperature and pressure changes were scrutinized. for a practical application, the uncertainty of calibrator, whose measuring capacity of 1000 ㎥/h obtained by employing two 500 ㎥/h electromagnetic How meters, was evaluated. The uncertainty budget shows the quantitative contribution of each uncertainty component to the overall uncertainty of the calibrator. As a result, it was found that the dominant uncertainties were from the master meter, which was evaluated statistically, and from the process of least squares fitting. On the contrary, the uncertainties arising from the variation of the fluid density and the pipe volume due to the temperature and pressure were negligible.