• 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.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.168-169
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• 2022

In this study, we investigates the auto-berthing problem for the underactuated surface vessel in the presence of constraints of dynamic uncertainties, finite time, transmission load, and environmental disturbance. A novel control scheme is proposed by fusing the finite time control technology and the event-triggered input algorithm. In the algorithm, differential homeomorphism coordinate the transformation is used to solve the problem of underactuation. Then, we apply the finite time technology and event triggered to save the time of the berthing vessel and relieve transmission burden between the controller and the vessel respectively. Moreover, a radial basis function network is used to approximate unknown nonlinear functions, and minimum learning parameters are introduced to lessen the computational complexity. A sufficient effort has been made to verify the stability of the closed-loop system based on the Lyapunov stability theory. Finally, simulation results display the effectiveness of the proposed scheme.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.1
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• pp.205-214
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• 2008

To transfer large amount of packets fast in sensor network, it is necessary that the delay between successive packet transmissions should be minimized as possible. In Sensor network, since the Operating Systems are worked on the event driven, the Timer Event is used to transfer packets successively. However, since the transferring time of packet completely is varies very much, it is very hard to set appropriate interval. If interval is too long, delay also becomes too long but if interval is too short, the fail of transfer request would increase. In this paper, we propose ESTEO which reduces the delay between successive packet transmissions by using SendDone Event which informs that a packet transmission has been completed. In ESTEO, the delay between successive packet transmissions is shortened very much since the transmission of next Packet starts at the time when the transmission of previous packet has completed, irrespective of the transmission time. Therefore ESTEO could provide high packet transmission rate given large amount of packets.

• Proceedings of the KSR Conference
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• 2009.05b
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• pp.341-347
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• 2009

In high speed railway, event recorder system stores a train speed and the related data for train operation in real time. Using those information, we can analysis the train operation and the reason of train accident. Analysis software gets the stored data from Event Recorder and shows the status of various signals related with train operation. Using it, also we can analysis the train operation before and after the given time. In this paper we propose the analysis software to show and analysis the operation of high speed train. The method of transferring the stored data from Event Recorder into Analysis Software is proposed. We develop the efficient procedure to store the transferred data into analysis system. Also the effective method to show the store data and to analysis them is studied for finding the cause of train accident.

• Journal of the Korea Society for Simulation
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• v.21 no.4
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• pp.35-46
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• 2012

As complexity of real-time systems is being increased ad hoc approaches to analysis of such systems would have limitations in completeness and coverability for states space search. Formal means using a model-based approach would solve such limitations. This paper proposes a model-based formal method for logical analysis, such as safety and liveness, of real-time systems at a discrete event system level. A discrete event model for real-time systems to be analyzed is specified by DEVS(Discrete Event Systems Specification) formalism, which specifies a discrete event system in hierarchical, modular manner. Analysis of such DEVS models is performed by Communicating DEVS (C-DEVS) formalism of a timed global state transition specification and an associated analysis algorithm. The C-DEVS formalism and an associated analysis algorithm guarantees that all possible states for a given system are visited in an analysis phase. A case study of a safety analysis for a rail road crossing system illustrates the effectiveness of the proposed method of the model-based approach.

• Convergence Security Journal
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• v.20 no.5
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• pp.27-32
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• 2020

The Windows Event Log is a Log that defines the overall behavior of the system, and these files contain data that can detect various user behaviors and signs of anomalies. However, since the Event Log is generated for each action, it takes a considerable amount of time to analyze the log. Therefore, in this study, we designed and implemented an XML-based Event Log analysis tool based on the main Event Log list of "Spotting the Adversary with Windows Event Log Monitoring" presented at the NSA.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.9
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• pp.1364-1372
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• 2017

In this paper, a problem of event-triggered model predictive control is investigated for continuous-time Takagi-Sugeno (T-S) fuzzy systems with input quantization. To efficiently utilize network resources, event-trigger is employed, which transmits limited signals satisfying the condition that the measurement of errors is over the ratio of a certain level. Considering sampling and quantization, continuous Takagi-Sugeno (T-S) fuzzy systems are regarded as a sector bounded continuous-time T-S fuzzy systems with input delay. Then, a model predictive controller (MPC) based on parallel distributed compensation (PDC) is designed to optimally stabilize the closed loop systems. The proposed MPC optimize the objective function over infinite horizon, which can be easily calculated and implemented solving linear matrix inequalities (LMIs) for every event-triggered time. The validity and effectiveness are shown that the event triggered MPC can stabilize well the systems with even smaller average sampling rate and limited actuator signal guaranteeing optimal performances through the numerical example.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1385-1402
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• 2019

Quickly picking up some valuable information from massive manufacturing event stream usually faces with the problem of long detection time, high memory consumption and low detection efficiency due to its stream characteristics of large volume, high velocity, many variety and small value. Aiming to solve the problem above for the current complex event processing methods because of not sharing detection during the detecting process for massive manufacturing event streams, an efficient complex event processing method based on multipattern sharing is presented in this paper. The achievement of this paper lies that a multipattern sharing technology is successfully used to realize the quick detection of complex event for massive manufacturing event streams. Specially, in our scheme, we firstly use pattern sharing technology to merge all the same prefix, suffix, or subpattern that existed in single pattern complex event detection models into a multiple pattern complex event detection model, then we use the new detection model to realize the quick detection for complex events from massive manufacturing event streams, as a result, our scheme can effectively solve the problems above by reducing lots of redundant building, storing, searching and calculating operations with pattern sharing technology. At the end of this paper, we use some simulation experiments to prove that our proposed multiple pattern processing scheme outperforms some general processing methods in current as a whole.

• Geophysics and Geophysical Exploration
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• v.12 no.4
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• pp.316-327
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• 2009

A standard for national seismological observatory was proposed on 1999. Since then, Quanterra digitizer has been installed and is operating on almost all of seismic stations which belong to major seismic monitoring organizations. Quanterra digitizer produce and transmit real-time event packet and data packet. Characteristics of event packet and arrival time of each channel's data packet on data center were investigated. Packet selection criteria using signal to noise ratio (hereafter SNR) and signal period from real-time event packet based on 100 samples per second (hereafter sps) velocity data were developed. Estimation of epicenter using time information of the selected event packet were performed and tested. A series of experiment show that event packets were received approximately 3~4 second earlier than data packets and the number of event packet was only 0.3% compare to data packets. Just about 5% against all of event packets were selected as event packet were related P wave of real earthquake. Using the selected event packets we can estimate an epicenter with misfit less than 10 km within 20 sec for local earthquake over magnitude 2.5.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_1
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• pp.549-557
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• 2012

Spatial phenomena such as environment pollution, disease and the risk of spreading information need a rapid initial response to perceive spread event. Moving data perceive spread event through real-time processing and analysis. To process and analysis the event, spatial-temporal complex event processing is used. Previous spatialtemporal complex event processing is possible basis spatial operator but insufficient apply to design spatialtemporal complex event processing to perceive spatial phenomena of high complexity. This study proposed hierarchical spatio-temporal CEP design which will efficiently manage the fast growing incoming sensor data. The implementation of the proposed design is evaluated with GPS location data of moving vehicles which are used as the incoming data stream for identifying spatial events. The spatial component of existing CEP software engine has been extended during the implementation phase to broaden the capabilities of processing spatio-temporal events.