• Journal of the Korea Society for Simulation
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• v.13 no.2
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• pp.1-12
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• 2004

This paper estimated the arrival angle and electric wave delay time using the space method law and the directions of arrival (DOA) estimation algorithm in case of signal correlation. Space method law is the method used to repress cross correlation before applying the weight value to the receiving signal. The values of the diagonal elements in the correlation matrix were averaged to replace as the diagonal elements value. In the area of wireless communication or mobile communication, there are high correlations in case of low delay time difference in multiple waves. This causes the quality of the communication to drop due to interference with the desired signal elements. This paper estimated the arrival angle and electric wave delay time using the space method law and the MUSIC algorithm. With the arrival angle algorithm, the arrival angle cannot be estimated below 5 in case of signal correlations because the angle resolution capacity decreases accordingly. The super resolution capacity was estimated to determine the arrival angle below 5 in this paper. In addition, the proposed algorithm estimated the short delay time difference to be below 20ns.

• Journal of Korean Academy of Nursing
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• v.33 no.8
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• pp.1153-1160
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• 2003

Purpose. 1) To identify the time taken from symptom onset to the arrival at the hospital (pre-hospital delay time) and time taken from the arrival at the hospital to the initiation of the major treatment (in-hospital delay time) 2) to examine whether rapid treatment results in lower mortality. 3) to examine whether the pre- and in-hospital delay time can independently predict in-hospital mortality. Methods. A retrospective study with 586 consecutive AMI patients was conducted. Results. Pre-hospital delay time was 5.25 (SD=10.36), and in-hospital delay time was 1.10 (SD=1.00) hours for the thrombolytic therapy and 50.24 (SD=121.18) hours for the percutaneous transluminal coronary angio-plasty (PTCA). In-hospital mortality was the highest when the patients were treated between 4 to 48 hours after symptom onset using PTCA (p=.02), and when treated between 30 minutes and one hour after hospital arrival using thrombolytics (p=.01). Using a hierarchical logistic regression model, the pre- and in-hospital delay times did not predict the in-hospital mortality. Conclusion. Pre- and in-hospital delay times need to be decreased to meet the desirable therapeutic time window. Thrombolytics should be given within 30 minutes after arrival at the hospital, and PTCA should be initiated within 4 hours after symptom onset to minimize in-hospital mortality of AMI patients.

• Journal of the Korean Society for Nondestructive Testing
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• v.28 no.6
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• pp.512-518
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• 2008

Guided wave technology is advantageous for fast inspection of pipe wall thinning since the guided wave propagates long distance. In this investigation, the method to evaluate gradual wall thinning in a pipe based on the arrival time delay with magnetostrictive patch transducers is presented. Low frequency A0 Lamb waves were generated and measured by the present transducer and it was applied to arrival time delay measurement experiments on a test pipe having gradual wall thinnings artificially manufactured. From experiments, consistent results that wall thinning increases the arrival time delay of A0 waves were obtained. Consequently, the feasibility of the magnetostrictive patch transducers to evaluate wall thinning was verified.

• Journal of the Korean Society of Industry Convergence
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• v.4 no.1
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• pp.41-49
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• 2001

This study developed signal optimization algorithm by analyzing vehicle arrival patterns. The major principle of signal optimization is dissipate all queueing vehicle in 1cycle and assign delay time uniformly for all approaches. For this, this study used optimal green time and surplus green time. Optimal green time calculated by estimated traffic volume from vehicle arrival model. Surplus green time defined as the gap of optimal green time and queue dissipated time. And alternative cycle has minimum surplus green time was selected as the optimal cycle. Finally, total delay and average delay per vehicle can be calculated by using queueing theory.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.101-111
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• 2017

This study propose a method to predict the bus arrival time by considering the signal delay time which is an element which can not be considered in the current bus arrival prediction information generation algorithm. In order to consider the signal delay time, travel time is divided into three components: service time, cruising travel time, and signal delay time. Signal delay time was estimated using intersection arrival time and TOD. The results show that most of the errors that occurred in predicting the arrival time are within about 30 seconds. Some of the estimates have large errors due to the nature of this methodology that uses the estimated value of the intersection arrival time rather than the observation value. It is also difficult to predict the arrival time of the express buses using this method. Future studies such as improving this through real-time location information will greatly improve the accuracy of the methodology.

• Journal of Korean Society of Transportation
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• v.28 no.1
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• pp.125-134
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• 2010

It is occurred bus arrival time errors when a bus arrives at a bus stop because of a variety of traffic condition such as traffic signal cycle, the time to get on and off a bus, a bus-only lane and so on. In this paper, bus delay time which is occurred as the result of traffic condition was estimated with Markov Chain process and bus arrival time at each bus stop was predicted with it. As the result of the study, it is confirmed to improve accuracy than the method of bus arrival time prediction with existing method (weighed moving average method) in case predicting bus arrival time using 7 by 7 and 9 by 9 matrixes.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.3
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• pp.1-10
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• 2009

Bus delay time is occurred as the result of traffic condition and important factor to predict bus arrival time. In this paper, transition probability matrixes between bus stops are made by using Markov Chain and it is predicted bus delay time with them. As the results of study, it is confirmed a possibility of adapting the assumption which it has same bus transition probability between stops through paired-samples T-test and overcame the limitation of exiting studies in case there is no scheduled bus arrival time for each stops with using bus interval time. Therefore it will be possible to predict bus arrival time with Markov Chain.

• Journal of information and communication convergence engineering
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• v.3 no.3
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• pp.119-121
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• 2005

This paper aims to estimate the delay time of multiple signals in a multi-path environment. It also seeks to carry out a comparative analysis with the existing delay time under the proposed algorithm to develop a new algorithm that applies the space average method in a MUSIC algorithm. Unlike the existing delay time estimation algorithm, the developed algorithm was able to estimate the delay time in 5ns low. Therefore, the algorithm proposed in this paper improved the existing delay time estimated algorithm.

• Journal of the Korea Society for Simulation
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• v.8 no.2
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• pp.101-109
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• 1999

In a commercial facsimile network system, a simulation analysis has been performed using ARENA due to the unavailability of theoretical models. The effect of a priority is compared with that of the current FCFS rule on the arriving call blocking rate and transmission time delay. The result shows that the priority rule reduces more service time delay as the arrival rate increases. A simulation analysis procedure is proposed to select optimal in/out port ratio at various hourly arrival rates with a given multiple-place transmission requests ratio.

• Journal of the Korea Society for Simulation
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• v.3 no.1
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• pp.89-98
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• 1994

In this paper, a criteria for selecting an appropriate load redistribution algorithm is devised so that a fault-tolerance distributed system can operte at its optimal efficience. To present the guideline for selecting redistributing algorithms, simulation models of fault-tolerant system including redistribution algorithms are developed using SLAM II. The job arrival rate, service rate, failure and repair rate of nodes, and communication delay time due to load migration are used as parameters of simulation. The result of simulation shows that the job arrival rate and the failure rate of nodes are not deciding factors in affecting the relative efficiency of algorithms. Algorithm B shows relatively a consistent performance under various environments, although its performance is between those of other algorithms. If the communication delay time is longer than average job processing time, the performance of algorithm B is better than others. If the repair rate is relatively small or communication delay time is longer than service time, algorithm A leads to good performance. But in opposite environments, algorithm C is superior to other algorithms.