• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.3
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• pp.59-65
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• 2009

To investigate a posttraumatic stress, social support and work burden and to identify high risk group and related factors which were exerted influence on posttraumatic stress of firefighters. Data were gathered from total 264 firefighters consisting of 85 fire distinguishers & rescue workers, 96 emergency medical personnel and 83 in ambulance & fire truck drivers in C province and were analyzed 22 items by IES-R, 20 work burden items by Choi(2000), 8 social support items by Oh(2006) using SPSSWIN 14.0 program. Posttraumatic stress of general characteristics by work was showed significant difference in age, marriage status, education, position, office duration, mobilization frequency and experience of traumatic events. Posttraumatic stress were showed significant difference in 3 groups and fire distinguishers & rescue workers is the highest group. Posttraumatic stress was correlated with work burden(r=.317, p<0.01) for fire distinguishers & rescue workers, social support(r=-.331, p<0.01) and work burden(r=.522 p<0.001) for emergency medical personnel and work burden(r=.454, p<0.01) for ambulance & fire truck drivers. The high risk groups are fire distinguishers & rescue workers(60%), emergency medical personnel(55.2%)and ambulance & fire truck drivers(45.8%). Related factors are the experience seeing victim's danger for fire distinguishers & rescue workers(odds ratio=1.216, 95% confidence interval:1.068-1.383), and are work burden(odds ratio=1.100, 95% confidence interval:1.043-1.159) and office duration(odds ratio=1.010, 95% confidence interval 1.001-1.018) for emergency medical personnel, and are the experience seeing victim's danger(odds ratio=1.178, 95% confidence interval:1.010-1.373), age(odds ratio=1.129, 95%confidence interval:1.020-1.249), work burden(odds ratio=1.103, 95% confidence interval:1.034-1.177) for ambulance & fire truck drivers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.143-146
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• 2008

For tracing tag locations, a trajectories should be modeled and indexed in radio frequency identification (RFID) systems. The trajectory of a tag can be represented as a line that connects two spatiotemporal locations captured when the tag enters and leaves the vicinity of a reader. If a tag enters but does not leave a reader, its trajectory is represented only as a point captured at entry and we should extend the region of a query to find the tag that remains in a reader. In this paper, we propose an interval data model of tag's trajectory in order to solve the problem. For the interval data model. we propose a new index scheme called the IR-tree(Interval R-tree) and algorithms of insert and split for processing query efficiently. We also evaluate the performance of the proposed index scheme and compare it with the previous indexes.

• Journal of Embryo Transfer
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• v.22 no.2
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• pp.111-114
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• 2007

This study was carried out to investigate the reproductive performance of average (less than 10,000 liters milk in 305 days) and high yielding (more than 10,000 liters milk in 305 days) Holstein cattle at commercial dairy herds (n=22). Data on milk progesterone (10 to 60 days postpartum), days to post-partum estrous, days to post-partum conception, service per conception and calving interval were recorded for two consecutive years. Post-partum milk progesterone concentration and days to reach peak milk progesterone concentration were similar in high and average yielding cows. High yielding cows took more days to show signs of first postpartum estrous than average yielding cows. Post-partum conception was 20 days earlier in average yielding cows than high yielding cows. Artificial insemination per conception was similar between average and high yielding cows. Calving interval was 26.9 days longer in high yielding cows compared to average yielding cows. In conclusion, better reproductive and feeding management may help improve the reproductive performance of high yielding dairy cattle in commercial dairy farms.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.3 s.303
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• pp.47-52
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• 2005

Obstructive Sleep Apnea (OSA) is a representative symptom of sleep disorder caused by the obstruction of upper airway. Because OSA causes not only excessive daytime sleepiness and fatigue, hypertension and arrhythmia but also cardiac arrest and sudden death during sleep in the severe case, it is very important to detect the occurrence and the frequency of OSA. OSA is usually diagnosed through the laboratory-based Polysomnography (PSG) which is uncomfortable and expensive. Therefore researches to improve the disadvantages of PSG are needed and studies for the detection of OSA using only one or two parameters are being made as alternatives to PSG. In this paper, we developed an algorithm for the detection of OSA based on Heart Rate Variability (HRV). The proposed method is applied to the ECG data sets provided from PhysioNet which consist of learning set and training set. We extracted features for the detection of OSA such as average and standard deviation of 1 minute R-R interval, power spectrum of R-R interval and S-peak amplitude from data sets. These features are applied to the input of neural network. As a result, we obtained sensitivity of $89.66\%$ and specificity of $95.25\%$. It shows that the features suggested in this study are useful to detect OSA.

• Communications for Statistical Applications and Methods
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• v.16 no.6
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• pp.891-901
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• 2009

In this paper, we investigate the approach to estimate VaR under the transformed GARCH model. The time series are transformed to approximate to the underlying distribution of error terms and then the parameters and the one-sided prediction interval are estimated with the transformed data. The back-transformation is applied to compute the VaR in the original data scale. The analyses on the asset returns of KOSPI and KOSDAQ are presented to verify the accuracy of the coverage probabilities of the proposed VaR.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.149-158
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• 2019

The scheduling of planned maintenance problem of a system consisting of a number of components was studied. The purpose of maintenance scheduling is to minimize the cost of maintaining long-term operations. On the system side, the cost of a system shutdown can be minimized by grouping and inspecting a number of components. In addition, proper inspection cycles can be selected for each component to identify the failure sufficiently early to minimize the cost of the failure. To reduce the complexity of the calculations, the 'base interval approach' used in previous studies was applied and, in addition, the inspection cost savings from simultaneous inspections of multiple components were considered. To compare the effectiveness of inspection cost savings, this paper presents the results of simulation analysis performed by referring to the cases in the existing studies.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.931-940
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• 2013

For analysis of clustered survival data, the inferences of parameters in semi-parametric frailty models have been widely studied. It is also important to investigate the potential heterogeneity in event times among clusters (e.g. centers, patients). For purpose of this analysis, the interval estimation of frailty is useful. In this paper we propose a visualizing method to present confidence intervals of individual frailties across clusters using the frailtyHL R-package, which is implemented from h-likelihood methods for frailty models. The proposed method is demonstrated using two practical examples.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.249-255
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• 2000

HRIV(Hybrid Rule-Interval Variation) method is presented to stabilize a class of nonlinear systems, where SMC(Sliding Mode Control) and ADC (ADaptive Control) schemes are incorporated to overcome the unstable characteristics of a conventional FLC(Fuzzy Logic Control). HRIV method consists of two modes: I-mode (Integral Sliding Mode PLC) and R-mode(RIV method). In I-mode, SMC is used to compensate for MAE(Minimum Approximation Error) caused by the heuristic characteristics of FLC. In R-mode, RIV method reduces interval lengths of rules as states converge to an equilibrium point, which makes the defined Lyapunov function candidate negative semi-definite without considering MAE, and the new uncertain parameters generated in R-mode are compensated by SMC. In RIV method, the overcontraction problem that the states are out of a rule-table can happen by the excessive reduction of rule intervals, which is solved with a dynamic modification of rule-intervals and a transition to I-mode. Especially, HRIV method has advantages to use the analytic upper bound of MAE and to reduce Its effect in the control input, compared with the previous researches. Finally, the proposed method is applied to stabilize a simple nonlinear system and a modified inverted pendulum system in simulation experiments.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.633-636
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• 1986

We have developed an automated ECG interpretation technique by micro-computer for rapid analysis of ECG data in the clinical hospital. This system is consisted of 16 bit microcomputer including bandpass-filter, comparator, A/D converter in order to obtain the QRS width, R-R interval.

• Honam Mathematical Journal
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• v.24 no.1
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• pp.25-33
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• 2002

In this paper we have shown conditions of R for the existence of the solution to the problem of the type $-u''=ue^{{\varepsilon}u}$ on the interval (0, R) with boundary and other conditions as in $(1-{\varepsilon})-(4)$ for various ${\varepsilon}$.