• Journal of Power System Engineering
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• v.20 no.3
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• pp.29-35
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• 2016

Because of the severe service environment of the large marine vessel, the fatigue strength and its evaluation play an important role in design and maintenance of marine crankshaft. The aim of this work is to investigate the probability distribution of fatigue lives in crank throw forged steel and to develop the methodology for estimation of the probabilistic design fatigue strength. Detailed studies were performed on the constant amplitude axial loading fatigue test. The experiments were controlled by stress ratio of -1 and 15Hz frequency for each stress level. The considerable variability of fatigue life was observed in each stress level under rigidly controlled constant fatigue testing conditions. The fatigue life of crank throw forged steel was well followed the log-normal and Weibull distribution. In addition, it can be used for the estimation of probabilistic design fatigue strength by using the proposed methodology.

• Journal of Radiation Protection and Research
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• v.38 no.4
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• pp.185-188
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• 2013

Heating method using electric heater was used to reduce water content in fingernail clippings. Authors found that low water content is helpful to measure EPR signal of fingernail sample with enhanced variability. Generally, natural dehydration happens in normal room condition at least one month and needs much time for using in experiment. So, artificial heating method is applied in this study for time savings. Fingernail samples were tested to find effect of water content to the EPR signal on microwave power levels for dosimetry. Low water content in fingernail reduced variability of EPR signal and makes it possible to measure accurate EPR signal. It also made it possible to measure constant movement of EPR signals on several microwave power levels. Although this method was difficult to apply directly in fingernail/EPR dosimetry, we, authors, believe that this heating method would be useful to differentiate MIS2 and RIS which are generally located at the same g-factor and almost impossible to be identified with each other.

• Journal of the Korea Society of Computer and Information
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• v.22 no.5
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• pp.65-72
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• 2017

Premature Ventricular Contraction(PVC) arrhythmia is most common abnormal-heart rhythm that may increase mortal risk of a cardiac patient. Thus, it is very important issue to identify the specular portraits of PVC pattern especially from the patient. In this paper, we propose a new method to extract the characteristics of PVC pattern by applying K-means machine learning algorithm on Heart Rate Variability depicted in Poinecare plot. For the quantitative analysis to distinguish the trend of cluster patterns between normal sinus rhythm and PVC beat, the Euclidean distance measure was sought between the clusters. Experimental simulations on MIT-BIH arrhythmia database draw the fact that the distance measure on the cluster is valid for differentiating the pattern-traits of PVC beats. Therefore, we proposed a method that can offer the simple remedy to identify the attributes of PVC beats in terms of K-means clusters especially in the long-period Electrocardiogram(ECG).

• Journal of the Ergonomics Society of Korea
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• v.12 no.2
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• pp.63-83
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• 1993

The primary objective of the research is to develop a mathematical method to incorporate the variability of anthropometric body dimensions and joint strengths of individuals in a biomechanical analysis. A multivariate normal simulation model estimated anthropometric body dimensions and joint strengths of the random link-person, based on the assumptions that the vari- ables of body dimensions and joint strengths are correlated and follow normal distributions. Statistical comparative analysis demonstrated that the random link-person represented a more realistic human-like form in an anthropometric sense than the proportional link-person whose body dimensions were estimated proportionally. Estimated joint strengths for the random link-person, however, did not match the measured joint strengths as closely as the estimated body dimensions. The random link-person will allow biomechanical analysis of manual materials handling tasks to be individualized with respect to the anthropometry and a static strength.

• Korean Management Science Review
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• v.29 no.1
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• pp.101-114
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• 2012

The demand for naval spare parts is intermittent and erratic. This feature, referred to as non-normal demand, makes forecasting difficult. Hierarchical forecasting using an aggregated time series can be more reliable to predict non-normal demand than direct forecasting. In practice the performance of hierarchical forecasting is not always superior to direct forecasting. The relative performance of the alternative forecasting methods depends on the demand features. This paper analyses the influence of the demand features on the performance of the alternative forecasting methods that use hierarchical and direct forecasting. Among various demand features variability, kurtosis, skewness and equipment groups are shown to significantly influence on the performance of the alternative forecasting methods.

• Proceedings of the KOSOMBE Conference
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• v.1990 no.11
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• pp.25-28
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• 1990

We tested the ability of two-dimensional echocardiograms of complete heart cycle in closed-chest human to discriminate between normal and infarcted myocardium using fixed window, Inter- and Intra-frame analysis. The results show that statistical parameter, MEAN, second order gray level statistics parameter, ASM and proposed parameter, HGE, I.T, can quantitatively distinguish between normal and Infarcted regions. The manner in which these parameters vary over the cardiac cycle is also a good indicator of the state of myocardium. The infarcted areas yield regions of higher Intensity throughout the cardiac cycle. Whereas, normal tissue demonstrates greater variability throughout the cardiac cycle.

• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.271-280
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• 2011

Heart Rate Variability (HRV) analysis is a convenient tool to assess Myocardial Ischemia (MI). The analysis methods of HRV can be divided into time domain and frequency domain analysis. This paper uses wavelet transform as frequency domain analysis in contrast to time domain analysis in short term HRV analysis. ST-T and normal episodes are collected from the European ST-T database and the MIT-BIH Normal Sinus Rhythm database, respectively. An episode can be divided into several segments, each of which is formed by 32 successive RR intervals. Eighteen HRV features are extracted from each segment by the time and frequency domain analysis. To diagnose MI, the Neural Network with Weighted Fuzzy Membership functions (NEWFM) is used with the extracted 18 features. The results show that the average accuracy from time and frequency domain features is 75.29% and 80.93%, respectively.

• The Korean Journal of Pain
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• v.22 no.1
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• pp.39-46
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• 2009

Background: Ketamine has an indirect sympathetic stimulation effect. We investigated heart rate variability (HRV) as a marker of cardiac autonomic function after a target controlled infusion (TCI) of ketamine with a plasma concentration of 30 or 60 ng/ml. Methods: In 20 adult volunteers, the mean of the R wave to the adjacent R wave interval (RRI), the range of RRI, the root mean square successive difference of intervals (RMSSD), the total power, the low frequency (LF, 0.04-0.15 Hz) power, the high frequency (HF, 0.15-0.4 Hz) power, the normal unit HF (nuHF), the normal unit LF (nuLF), the LF/HF ratio and the SD1 and the SD2 in the Poincare plot were measured before and after a TCI of ketamine. We observed for any psychedelic symptoms or sedation. Results: There were no differences in the mean and range of the RRI, RMSSD, total power, LF power, HF power, nuHF, nuLF, LF/HF ratio, SD1 and SD2 between before and after ketamine administration. The OAA/S score was higher and there were more psychedelic symptoms with a 60 ng/ml plasma concentration than with a 30 ng/ml plasma concentration. Conclusions: This study did not show any effect of a low plasma concentration of ketamine on the autonomic nervous system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3B
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• pp.285-293
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• 2010

Soil moisture is a key factor to control the exchange of water and energy between the surface and the atmosphere. In recent, many researches for spatial and temporal variability analyses of soil moisture have been conducted. In this study, we analyzed the spatio-temporal variability of soil moisture in Walnut Gulch Experimental Watershed, Arizona, U.S. during the Soil Moisture Experiment 2004 (SMEX04). The spatio-temporal variability analyses were performed to understand sensitivity of five observation sites with precipitation and relationship between mean soil moisture, and its standard deviation and coefficient of variation at the sites, respectively. It was identified that log-normal distribution was superior to replicate soil moisture spatial patterns. In addition, precipitation was identified as a key physical factor to understand spatio-temporal variability of soil moisure based on the temporal stability analysis. Based on current results, higher spatial variability was also observed which was agreed with the results of previous studies. The results from this study should be essential for improvement of the remotely sensed soil moisture retrieval algorithm.

• Journal of Oriental Neuropsychiatry
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• v.20 no.3
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• pp.133-147
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• 2009

Objectives : This study has the object to evaluate the effect of meditation at the clinical field and to classify the profer meditation by the emotional states of patients. Methods : Thirty volunteers have been recruited using local advertisement. They devided into two groups(patient group, normal group). Emotional states and stressors (STAI, STAXI, BDI, SCL-90-R, Stress Response inventory, Life event stress) have been evaluated. After that test HRV(Heart Rate Variability) has been tested and subjects took a 5-minute rest. After that, one of meditation has been chosed and has been demonstrated for 10 minutes by practiced trainer(Autogenic Training, Fruit Imaginary Meditation, Random assignment). After 5 minutes resting time, HRV has been measured again with meditation that had been administered. Results : 1. The higher the scale of emotional index, the more sensitively react has been occured according to the meditation. 2. The rate of HRV index that means stable state is higher in Fruit Imaginary Meditation group who thought to be administered meditation well. 3. The Fruit Imaginary Meditation is more effective immediately than Autogenic Training assessed by HRV scale and VAS scale of well-administered meditation especially in patients group. 4. Subjects of Highly suffered emotional problem have more effect in Fruit Imaginary Meditation Group compared to Autogenic Training Group. Conclusions : Suitable beginner meditation course considered patient's emotional problem needs to be programmed.