• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.364-364
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• 2000

Timed Petri Net(TPN) is one of methods to model and to analyze Discrete Event Dynamic Systems(DEDSs) with real time values. It has two time values, earliest firing time ($\alpha$$_{i}$) and latest firing time ($\beta$$_{I}$) for the each transition. A transition of TPN is fired at arbitrary time of time interval ($\alpha$$_{I}$, $\beta$$_{i}$). Uncertainty of firing time gives difficulty to analyze and estimate a modeled system. In this paper, we proposed the Fuzzy Transition Timed Petri Net(FTTPN) with fuzzy theory to determine the optimal transition time (${\gamma}$$_{i}$). The transition firing time (${\gamma}$$_{i}$) of FTTPN is determined from fuzzy controller which is modeled with information of state transition. Each of the traffic signal controllers are modeled using the proposed method and timed petri net. And its Performance is evaluated by simulation of traffic signal controller. controller.

• Journal of Korean Society of Transportation
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• v.12 no.3
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• pp.49-64
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• 1994

The development of a mathematical modular framework based on Petri Network theory to model a traffic network is the subject of this paper. Traffic intersections are the primitive elements of a transportation network and are characterized as event driven and asynchronous systems. Petri network have been utilized to model these discrete event systems; further analysis of their structure can reveal information relevant to the concurrency, parallelism, synchronization, and deadlock avoidance issuse. The Petri-net based model of a generic traffic junction is presented. These modular networks are effective in synchronizing their components and can be used for modeling purposes of an asynchronous large scale transportation system. The derived model is suitable for simulations on a multiprocessor computer since its program execution safety is secured. The software pseudocode for simulating a transportation network model on a multiprocessor system is presented.

• Electronics and Telecommunications Trends
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• v.36 no.6
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• pp.55-66
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• 2021

The air traffic industry, one of Korea's major industries, has recently experienced increased demand from overseas air passengers, launched a low-cost airline, and increased special freight transportation capacity. These initiatives have had a positive impact on air traffic (for example, profitability); however, air traffic management has become more complex, which has increased the incidence of aviation accidents and created safety hazards. There is an increasing need to collect and analyze aviation data that can proactively respond to aviation accidents. Concatenation of collected aviation data as big data and the development of artificial intelligence technology are gradually expanding aviation safety event analysis from conventional statistical analysis to machine learning-based analysis. This paper surveys the trends of flight safety event analysis to derive aviation safety risk factors by looking at the types and characteristics of aviation data that can be used to predict accidents related to safety in aviation operations.

• The Korean Journal of Applied Statistics
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• v.23 no.4
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• pp.715-724
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• 2010

Recurrent event data occurs when a subject experience the event of interest several times and has been found in biomedical studies, sociology and engineering. Several diverse approaches have been applied to analyze the recurrent events (Cook and Lawless, 2007). In this study, we analyzed the YTOP(Young Traffic Offenders Program) dataset which consists of 192 drivers with conviction dates by speeding violation and traffic rule violation. We consider a subject-specific effect, frailty, to reflect the individual's driving behavior and extend to time-varying frailty effect. Another feature of this study is about the redefinition of risk set. During the study, subject may be under suspension and this period is regarded as non-risk period. Thus the risk variables are reformatted according to suspension and termination time.

• The Korean Journal of Applied Statistics
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• v.25 no.4
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• pp.621-632
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• 2012

Recurrent event data can be easily found in longitudinal studies such as clinical trials, reliability fields, and the social sciences; however, there are a few observations that disappear temporarily in sight during the follow-up and then suddenly reappear without notice like the Young Traffic Offenders Program(YTOP) data collected by Farmer et al. (2000). In this article we focused on inference for a cumulative mean function of the recurrent event data with these incomplete observation gaps. Defining a corresponding risk set would be easily accomplished if we know the exact intervals where the observation gaps occur. However, when they are incomplete (if their starting times are known but their terminating times are unknown) we need to estimate a distribution function for the terminating times of the observation gaps. To accomplish this, we treated them as interval-censored and then estimated their distribution using the EM algorithm proposed by Turnbull (1976). We proposed a nonparametric estimator for the cumulative mean function and also a nonparametric test to compare the cumulative mean functions of two groups. Through simulation we investigated the finite-sample performance of the proposed estimator and proposed test. Finally, we applied the proposed methods to YTOP data.

• Journal of the Korea Society for Simulation
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• v.18 no.1
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• pp.27-34
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• 2009

Currently network users, especially the number of internet users, increase rapidly. Also, high quality of service is required and this requirement results a sudden network traffic increment. As a result, an efficient management system for huge network traffic becomes an important issue. Ontology/data engineering based context awareness using the System Entity Structure (SES) concepts enables network administrators to access traffic data easily and efficiently. The network traffic analysis system, which is studied in this paper, is designed and implemented based on a model and simulation using data engineering methodology to be avaiable in evaluating large network traffic data. Extensible Markup Language (XML) is used for metadata language in this system. The information which is extracted from the network traffic analysis system could be modeled and simulated in Discrete Event Simulation (DEVS) methodology for further works such as post simulation evaluation, web services, and etc.

• International journal of advanced smart convergence
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• v.8 no.4
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• pp.161-168
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• 2019

Traffic accidents in tunnel can lead to large traffic accidents due to narrow and dark road characteristics. Therefore, special care of the driver is required when is driving in a tunnel. However, accidents can happen at any time. In the event of an accident, a narrow road structure may lead to a second accident. Therefore, all facilities installed inside the tunnel should be allowed to minimize damage in the event of an accident. We confirmed the safety of the collision target through the action of the sedan, Sport Utility Vehicle (SUV) and truck when the vehicle crashed into a stairway installed on the tunnel emergency escape route, and when a concrete barrier or guard rail was installed in front of the stairway. The behavior of the vehicle has resulted in a total of three results: rollover or rollover, change of speed and angle of the vehicle after collision. The sedan and SUV were the most secure when colliding with the guardrail, but considering the truck as a whole, concrete barriers were judged to be the most suitable for minimizing damage from the first accident and reducing the risk of the second accident.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.2
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• pp.355-362
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• 1999

Traffic monitoring, a part of the system management, is a vital function lot the proper operation of a system in use. Currently OMG has been trying to standardize CORBA system management. Besides, many companies and research laboratories have been developing and studying CORBA system management. In this paper, we have designed the proxy to monitor the CORBA traffic using the OSI management technology. To manage CORBA traffic resources, 6 parameters have been made into managed objects. The monitoring system consists of a CORBA server, a proxy object and an MIB. The CORBA server is made up of a service provider, a proxy server, and a event sewer. The proxy object acts as a process of a CORBA object, and is made up of a proxy client, a event client, and an IPC server.

• Journal of Korea Multimedia Society
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• v.9 no.7
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• pp.827-834
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• 2006

In distributed virtual environment, system response time to users' interactions is an importance factor to determine the degree of contentment with the system. Generally, response time is affected by the efficiency of event message processing algorithm, and most of previous systems use FCFS algorithm, which processes message traffic sequentially based only on the event occurrence time. Since this method totally depends on the order of occurrence without considering the priorities of events, it has a problem that might drop the degree of system response time by causing to delay processing message traffic when a bottleneck phenomenon happens in the server side. To overcome this limitation of FCFS algorithm, this paper proposes a concurrent event scheduling algorithm, which is able to process event messages concurrently by assigning the priorities to the events. It is also able to satisfy the two goals of system together, consistency and responsiveness through the combination of occurrence time with priority concept of events.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.12B
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• pp.1996-2002
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• 2000

This paper investigates a priority scheme for IEEE 802.11 Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) protocol in order to provide short access times for priority frames (e.g. time-deadline traffic) even when the overall traffic on the wireless channel is heavy. Under the compatibility constraint for the IEEE 802.11 wireless LANs, two priority systems are simulated: no priority (current IEEE 802.11 standard) for time-deadline traffics and dynamic time-deadline priority. We evaluate algorithms to improve the time-deadline traffic performance using discrete event simulation (DES)