• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.58-58
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• 1993

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.23-23
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• 1996

• Journal of Information Technology Applications and Management
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• v.22 no.3
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• pp.105-114
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• 2015

This paper presents a fast Time Difference of Arrival (TDOA) estimation for sound source localization. TDOA is the time difference between the arrival times of a signal at two sensors. We propose a partial cross correlation method to increase the speed of TDOA estimation for sound source localization. We do this by predicting which part of the cross correlation function contains the required TDOA value with the help of the signal energies, and then we compute the cross correlation function in that direction only. Experiments show approximately 50% reduction in the cross correlation computation time thereby increasing the speed of TDOA computation. This makes it very relevant for real world surveillance.

• Journal of Physiology & Pathology in Korean Medicine
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• v.16 no.5
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• pp.1075-1078
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• 2002

Objective: The management for the stroke should ,given as soon as possible to be effect. But Patients with stroke symptoms commonly delay many hours before seeking medical attention. We evaluated the factors which are related to the time of hospital arrival after acute stroke. Method: Data were obtained from 317 patients admitted to our hospital within 72 hours of stroke onset. We assessed demographic variables, stoke subtype. referral routes. history of previous stroke, level of consciousness, distance from the place where stroke occurred to hospital, and the time interval between onset of stroke and arrival at the hospital. Results: Mean patient age was 65.99±9.57 years. The mean time interval between onset of stroke and hospital arrival was 17.26±18.69 hours and 128 (40.38%) patients arrived within 6 hours. The patients whoes stoke subtype was infarction, who arrived our hospital by way of other hospital, who had no suffered from previous stroke and who showed no impairement of consciousness was arrived at the hospital late(p<0.05). Conclusion: The majority of patients arrive at the hospital after prolonged delays for multiple reasons, and patients with milder symptoms, for whom treatment might be more effective, were less likely to arrive in time for therapy. Our study suggest that effective education about stroke to the patients and public would be highly necessary.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.3
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• pp.28-34
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• 2015

An analysis method of trajectory prediction has been suggested and the developed trajectory prediction module, which is an important functional component of the Arrival Manager (AMAN) of Jeju airport, has been tested by applying the suggested method. The objective of this method is to improve prediction performance of the trajectory prediction module. The trajectory prediction module predicts the trajectories based on the real-time track data and flight plans. Therefore, the suggested analysis method includes the simulation framework which is based on real-time playback, recording, and graphic display systems for testing. Besides, the definition of time error, which is a important index for the time based scheduling system, such as AMAN, is included in the suggested analysis method. An example of arrival time prediction accuracy improvement through the suggested analysis method has also been presented.

• Journal of Platform Technology
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• v.9 no.4
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• pp.51-59
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• 2021

In this paper, we propose a location-based service that the user's location is known by connection history to WI-FI AP installed in a facility known its location previously. The location-based service proposed in this paper manages job processing states of technicians who inspect and maintain the facility like elevator by using worker's location and arrival time information. The job scheduling management method proposed in this paper is based on previously scheduled arrival time and actual arrival time to a target facility. And we experimentally implemented the inspection and maintenance system of an elevator to show the feasibility of job schedule management based on location and arrival time information acquired from Wi-Fi AP connection history. Our experimental implementation shows that our proposed method is usefulness in the field of the inspection and maintenance of a facility.

• Journal of Platform Technology
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• v.10 no.1
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• pp.11-19
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• 2022

In this paper, we propose a location-based service that the user's location is known by connection history to WI-FI AP installed in a facility known its location previously. The location-based service proposed in this paper manages job processing states of technicians who inspect and maintain the facility like elevator by using worker's location and arrival time information. The job scheduling management method proposed in this paper is based on previously scheduled arrival time and actual arrival time to a target facility. And we experimentally implemented the inspection and maintenance system of an elevator to show the feasibility of job schedule management based on location and arrival time information acquired from Wi-Fi AP connection history. Our experimental implementation shows that our proposed method is usefulness in the field of the inspection and maintenance of a facility.

• Management Science and Financial Engineering
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• v.15 no.2
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• pp.1-21
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• 2009

We consider an $M^x/G/1$ queueing system with a random setup time under Bernoulli vacation schedule, where the service of the first unit at the completion of each busy period or a vacation period is preceded by a random setup time, on completion of which service starts. However, after each service completion, the server may take a vacation with probability p or remain in the system to provide next service, if any, with probability (1-p). This generalizes both the $M^x/G/1$ queueing system with a random setup time as well as the Bernoulli vacation model. We carryout an extensive analysis for the queue size distributions at various epochs. Further, attempts have been made to unify the results of related batch arrival vacation models.

• Health Policy and Management
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• v.30 no.3
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• pp.399-408
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• 2020

Background: The purpose of this study was to examine the impact of the regional characteristics on the accessibility of emergency care and the impact of emergency medical accessibility on the patients' prognosis and the emergency medical expenditure. Methods: This study used the 13th beta version 1.6 annual data of Korea Health Panel and the statistics from the Korean Statistical Information Service. The sample included 8,119 patients who visited the emergency centers between year 2013 and 2017. The arrival time, which indicated medical access, was used as dependent variable for multi-level analysis. For ordinal logistic regression and multiple regression, the arrival time was used as independent variable while patients' prognosis and emergency medical expenditure were used as dependent variables. Results: The results for the multi-level analysis in both the individual and regional variables showed that as the number of emergency medical institutions per 100 km² area increased, the time required to reach emergency centers significantly decreased. Ordinal logistic regression and multiple regression results showed that as the arrival time increased, the patients' prognosis significantly worsened and the emergency medical expenses significantly increased. Conclusion: In conclusion, the access to emergency care was affected by regional characteristics and affected patient outcomes and emergency medical expenditure.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.36-43
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• 2002

We analyze bulk service $M/G^{b}/1$ queues using the arrival time approach of Chae et al. (2001). As a result, the decomposition property of the M/G/1 queue with generalized vacations is extended to the $M/G^{b}/1$ queue in which the batch size is exactly a constant b. We also demonstrate that the arrival time approach is useful for relating the time-average queue length PGF to that of the departure time, both for the $M/G^{b}/1$queue in which the batch size is as big as possible but up to the maximum of constant b. The case that the batch size is a random variable is also briefly mentioned.