• Phonetics and Speech Sciences
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• v.3 no.1
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• pp.145-151
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• 2011

In view of the hypothesis that the effects of Parkinson's disease on voice production can be detected before pharmacological intervention, the prosodic features of patients with idiopathic Parkinson's disease (IPD) and a healthy aging group were diagnostically analyzed with the long term object of establishing, for clinical purposes, early disease-progression biomarkers. Twenty patients (male 8; female 12) with IPD (prior to pharmacological intervention) and a healthy control group of 22 (male 10; female 12) were selected. Ten sentences were recorded with a head-worn microphone. One sentence was chosen for the analysis of this paper. Relevant parameters, i.e. 3-dimensional model (F0, intensity, duration) and pitch and intensity related slopes (maxEnergy, maxF0, meanAbS, semiT, meanEnergy, meanF0), were analyzed by two-group discriminant analysis. The stepwise estimation method of discriminant analysis was performed by gender. The discriminant functions predicted 83.9% of the male test data correctly while the prediction rate was 93.1% for the female group. The results showed that meanF0_slope and semiT_slope were more important parameters than the others for the male group. For the female group, the meanEnergy_slope and maxEnergy_slope were the important ones. These findings indicate that significant parameters are different for the male and female group. Gender lifestyle may be responsible for this difference. Dysprosodic features of IPD show not simultaneously but progressively in terms of F0, intensity and duration.

• Journal of Korea Water Resources Association
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• v.49 no.10
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• pp.823-833
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• 2016

This study developed a trivariate Copula function based drought frequency analysis model to better evaluate the recent 2014~2015 drought event. The bivariate frequency analysis has been routinely used for the drought variables of interest (e.g. drought duration and severity). However, the recent drought patterns showed that the intensity can be regarded as an important factor which is being characterized by short duration and severe intensity. Thus, we used the trivariate Copula function approach to incorporate the trivariate drought characteristics into the drought frequency analysis. It was found that the return periods based on the trivariate frequency analysis are, in general, higher than the existing bivariate frequency analysis. In addition, this study concludes that the increase in drought frequency claimed by the Gumbel copula function has been overestimated compared to the Student t Copula function. In other words, the selection of copula functions is rather sensitive to the estimation of trivariate drought return periods at a given duration, magnitude and intensity.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.16-16
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• 2011

Statistics of extreme rainfall play a vital role in engineering practice from the perspective of mitigation and protection of infrastructure and human life from flooding. While flood frequency assessments, based on river flood flow data are preferred, the analysis of rainfall data is often more convenient due to the finer spatial nature of rainfall recording networks, often with longer records, and potentially more easily transferable from site to site. The rainfall frequency analysis as a design tool has developed over the years in New Zealand from Seelye's daily rainfall frequency maps in 1947 to Thompson's web based tool in 2010. This paper will present a history of the development of New Zealand rainfall frequency analysis methods, and the details of the latest method, so that comparisons may in future be made with the development of Korean methods. One of the main findings in the development of methods was new knowledge on the distribution of New Zealand rainfall extremes. The High Intensity Rainfall Design System (HIRDS.V3) method (Thompson, 2011) is based upon a regional rainfall frequency analysis with the following assumptions: $\bullet$ An "index flood" rainfall regional frequency method, using the median annual maximum rainfall as the indexing variable. $\bullet$ A regional dimensionless growth curve based on the Generalised Extreme Value (GEV), and using goodness of fit test for the GEV, Gumbel (EV1), and Generalised Logistic (GLO) distributions. $\bullet$ Mapping of median annual maximum rainfall and parameters of the regional growth curves, using thin-plate smoothing splines, a $2km\times2km$ grid, L moments statistics, 10 durations from 10 minutes to 72 hours, and a maximum Average Recurrence Interval of 100 years.

• Journal of Korean Medical Science
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• v.33 no.49
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• pp.314.1-314.15
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• 2018

Background: Despite its growing significance, studies on the burden of disease associated with natural disasters from the perspective of public health were few. This study aimed at estimating the national burden of disease associated with typhoons and torrential rains in Korea. Methods: During the period of 2002-2012, 11 typhoons and five torrential rains were selected. Mortality and morbidities were defined as accentual death, injury and injury-related infection, and mental health. Their incidences were estimated from National Health Insurance Service. Case-crossover design was used to define the disaster-related excess mortality and morbidity. Disability-adjusted life years (DALYs) were directly assessed from excess mortality and morbidity. Results: The burden of disease from typhoons increased with the intensity, with 107.7, 30.6, and 36.6 DALYs per 100,000 per event for strong, moderate, and weak typhoons, respectively. Burden of disease from torrential rains were 56.9, 52.8, and 26.4 DALYs per 100,000 per event for strong, moderate, and weak episodes, respectively. Mental disorders contributed more years lived with disability (YLDs) than did injuries in most cases, but the injury-induced YLDs associated with strong typhoon and torrential rain were higher than those of lower-intensity. The elderly was the most vulnerable to most types of disaster and storm intensities, and males younger than 65 years were more vulnerable to a strong torrential rain event. Conclusion: The intensity of torrential rain or typhoon was the strongest determinant of the burden of disease from natural disasters in Korea. Population vulnerable may vary depending on the nature and strength of the disasters.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.127-132
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• 2011

In this study, calculation results of sediments yield prediction models were compared with the amount of dredging data for the Inje, Gangwon mountain region of Korea. MSDPM and LADMP were used as a sediments prediction model which was calibrated and modified to calculate the sediments yield of Korean mountain region. Both sediments yield prediction models were modified by using Threshold Maximum Rainfall Intensity and Total Minimum Rainfall Intensity and correction coefficient. After comparing with the amount of dredging, it was found that results of MSDPM is more accurate than the results of LADMP. Difference of results of MSDPM and the amount of dredging is 27.6% and difference of results of LADMP and the amount of dredging is 50.6%. Both sediments yield prediction models which were calibrated in this study can be used to calculate the sediments yield for the Korean mountain region.

• Journal of Environmental Science International
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• v.30 no.12
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• pp.1101-1111
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• 2021

In this study, among the W-S-R(Wiper-Signal-Rainfall) relationship methods used to produce sensor-based rain information in real time, we sought to produce actual rainfall information by applying machine learning techniques to account for the effects of wiper operation. To this end, we used the gradient descent and threshold map methods for pre-processing the cumulative value of the difference before and after wiper operation by utilizing four sensitive channels for optical sensors which collected rain sensor data produced by five rain conditions in indoor artificial rainfall experiments. These methods produced rainfall information by calculating the average value of the threshold according to the rainfall conditions and channels, creating a threshold map corresponding to the 4 (channel) × 5 (considering rainfall information) grid and applying Optima Rainfall Intensity among the big data processing techniques. To verify these proposed results, the application was evaluated by comparing rainfall observations.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.558-574
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• 2014

The number of fatty liver patients is sharply growing due to the rapid increase in the incidence of metabolic syndrome, which can lead to diseases such as abdominal obesity, hypertension, diabetes, and hyperlipidemia. Early diagnosis requires examinations using magnetic resonance imaging (MRI), wherein quantitative analyses are implemented through a professional water-fat separation method in many cases, as the intensity values of the areas of interest and non-interest are considerably similar or the same. However, such separation method generates inaccurate results in high magnetic fields, where the inhomogeneity of the fields increases. To overcome the limits of such conventional fat quantification methods, this paper proposes a field map estimation method that is effective in high magnetic fields. This method generates field maps through echo images that are obtained using the existing IDEAL sequences, and considers the wrapping degree of the field maps. Then clustering is performed to separate calibration areas, the least square fits based on the region growing method schema of the separated calibration areas, and the histograms are adjusted to separate the water from the fats. In experiment results, our proposed method had a superior fat detection rate of an average of 86.4%, compared to the ideal method with an average of 61.5% and Yu's method with an average of 62.6%. In addition, it was confirmed that the proposed method had a more accurate water detection rate of 98.4% on the average than the 88.6% average of the fat saturation method.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.3 s.43
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• pp.1-8
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• 2005

This paper describes a new objective methodology of seismic building damage assessment which is called Advanced Component Method(ACM). ACM is a major attempt to replace the conventional loss estimation procedure, which is based on subjective measures and the opinions of experts, with one that objectively measures both earthquake intensity and the response ol buildings. First, response of typical buildings is obtained analytically by nonlinear seismic static analysis, push-over analyses. The spectral displacement Is used as a measure of earthquake intensity in order to use Capacity Spectrum Method and the damage functions for each building component, both structural and non-structural, are developed as a function of component deformation. Examples of components Include columns, beams, floors, partitions, glazing, etc. A repair/replacement cost model is developed that maps the physical damage to monetary damage for each component. Finally, building response, component damage functions, and cost model were combined probabilistically, using Wonte Carlo simulation techniques, to develop the final damage functions for each building type. Uncertainties in building response resulting from variability in material properties and load assumptions were incorporated in the Latin Hypercube sampling technique. The paper also presents and compares ACM and conventional building loss estimation based on historical damage data and reported loss data.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.2
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• pp.78-87
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• 2012

In this paper, we address the tracking problem caused by camera motion and rolling shutter effects associated with CMOS sensors in consumer handheld cameras, such as mobile cameras, digital cameras, and digital camcorders. A modified particle filtering method is proposed for simultaneously tracking objects and compensating for the effects of camera motion. The proposed method uses an elastic registration algorithm (ER) that considers the global affine motion as well as the brightness and contrast between images, assuming that camera motion results in an affine transform of the image between two successive frames. By assuming that the camera motion is modeled globally by an affine transform, only the global affine model instead of the local model was considered. Only the brightness parameter was used in intensity variation. The contrast parameters used in the original ER algorithm were ignored because the change in illumination is small enough between temporally adjacent frames. The proposed particle filtering consists of the following four steps: (i) prediction step, (ii) compensating prediction state error based on camera motion estimation, (iii) update step and (iv) re-sampling step. A larger number of particles are needed when camera motion generates a prediction state error of an object at the prediction step. The proposed method robustly tracks the object of interest by compensating for the prediction state error using the affine motion model estimated from ER. Experimental results show that the proposed method outperforms the conventional particle filter, and can track moving objects robustly in consumer handheld imaging devices.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.1
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• pp.145-152
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• 2001

Thermal deformation of a machine tool structure can be evaluated from the analysis of the whole temperature field. However, it is extremely inefficient and impossible to know the whole temperature field by measuring temperatures at every point. So, the temperature estimator is required, which can predict the whole temperature field from the temperatures of just a few points. In this paper, a 1-dimensional heat transfer problem is modeled with modal analysis and state space equations. And then the state observer is designed to estimate the intensity of heat source and the whole temperature field in real time. The reliability of the estimator is verified by making comparison between solutions obtained from the proposed method and the exact solutions of examples. The proposed method is applied to the estimation of temperature distribution in a ball screw system.