• Journal of the Korea Society for Simulation
• /
• v.13 no.2
• /
• pp.1-12
• /
• 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 Society of Transportation
• /
• v.10 no.1
• /
• pp.41-54
• /
• 1992

The purpose of this thesis is to construct a model to estimate the delay that vehicles arriving randomly will be experienced at an isolated singalized intersection. To do this the following objectives are set in this study: (i) An what distance a random arrival pattern occurs after a platoon of vehicles are dis-charged from the stop line; (ii) A model which estimates the average delay per through-vehicle with respect to the de-gree of saturation; and (iii) The relation between the stepped delay and average approach delay per vehicle. The following are the findings of this study: (i) A random arrival pattern on the first second and third lanes occur 300,400 and 300m downstream from stop line rdspectively. A random arrival pattern on lane group occurs 500m downstream from the stop line ; (ii) A model for the estimation of approach delay has been developed in such a way that up to x=0.7 the delay increases linearly and beyond 0.7 the delay increases rapidly in a form of second order polynomial due to high degree of saturation : and (iii) Approach delay equals approximately 1.21 times of stopped delay.

• Journal of Korean Academy of Nursing
• /
• v.33 no.8
• /
• pp.1153-1160
• /
• 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
• /
• v.28 no.6
• /
• pp.512-518
• /
• 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.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.38 no.2
• /
• pp.283-294
• /
• 2018

An accurate pedestrian-delay model is essential for the pedestrian-oriented evaluation of signalized intersection (SI). The crossing behaviors of pedestrians at signalized pedestrian crosswalks (SPCs) are various, and their arrival behaviors consist of two types, random and platoon. It is natural, hence, that the behaviors of pedestrian crossing and arrival should be considered in order to estimate accurate pedestrian delay. Despite this necessity, a simple pedestrian-delay model that cannot explain these behaviors of pedestrian movements is still recommended in Highway Capacity Manual (HCM). For these reasons, a pedestrian-delay model, suitable for various SPCs and SIs, is required to make pedestrian-oriented decisions on the design and operation of various SPCs and SIs. This paper proposes a novel pedestrian-delay model that is based on the behaviors of pedestrian crossing and arrival. The proposed model consists of two sub models: the one for SPC and the other for SI. The SPC delay model was developed based on the behaviors of pedestrian crossing during pedestrian green time. The SI delay model was designed based on the behaviors of pedestrian crossing and platoon arrival. The results of a numerical simulation showed that the proposed delay model can successfully overcome the under- and overestimation problems of the HCM model with explaining various behaviors of pedestrian crossing and arrival.

• Journal of the Korean Society of Industry Convergence
• /
• v.4 no.1
• /
• pp.41-49
• /
• 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
• /
• v.16 no.6
• /
• pp.101-111
• /
• 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 the Korean Society for Railway
• /
• v.18 no.4
• /
• pp.374-390
• /
• 2015

This research shows the relationship between the number of trains and the probability of trains with arrival delay and suggests way to estimate the benefits of improved punctuality in a bottleneck section of the Gyeongbu Line. The arrival delays of high-speed and conventional trains were estimated using the train operation data of KORAIL. Linear regression models for the probability of trains with arrival delay by train type are presented in this paper. The probabilities of trains with arrival delay were more affected by the number of conventional trains than by the number of high-speed rail trains. For the empirical analysis, a project for increasing the capacity in the Seoul~Geumcheongu office section was tested. The benefits of the improved punctuality were estimated to be 4.2~4.5 billion Korean won every year. This research has some limitations but it can help evaluate more precisely the feasibility of the project of increasing the capacity in bottleneck sections.

• Journal of KIISE:Information Networking
• /
• v.36 no.3
• /
• pp.251-255
• /
• 2009

Network coding is a promising technology that increases the system throughput via reducing the number of transmission for a packet delivered from the source node to the destination node. Nevertheless, it suffers from the metrics of end-to-end delay. Network Coding scheme takes more processing delay which occurs as coding node encodes (XOR) a certain number of packets that relayed by the coding node, and more queuing delay which occurs as a packet waits for other packets to be encoded with. Therefore, in this paper, we analyze the dependency of the queuing delay to the arrival rate of each packet. In addition, we analyze and compare the delay in DCF without XOR and DCF with XOR under dynamic traffic.

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