• Nuclear Engineering and Technology
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• v.16 no.2
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• pp.97-105
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• 1984

A method and computer code for the uncertainty analysis in the top event unavailability are developed and tested by combining Monte Carlo Method and Moments method with fault tree reduction technique. Using system fault trees and unavailability data selected in WASH-1400, the efficiency of the proposed method is tested and these results are compared with those obtained by Monte Carlo method. It is shown that the results are sufficiently good in accuracy and computation time is considerably reduced compared with those by Monte Carlo method.

• Korean Journal of Computational Design and Engineering
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• v.17 no.2
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• pp.111-122
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• 2012

Capacity planning plays an important role not only for master production plan but also for facility or layout design in shipbuilding. Product work breakdown structure, attributes of production resources, and production method or process data are associated in order to make the discrete event simulation model of shipyard layout plan. The production amount of each process and the process time is assumed to be stochastic. Based on the stochastic discrete event simulation model, the production capacity of each facility in shipyard is estimated. The stochastic model of product arrival time, process time and transferring time is introduced for each process. Also, the production capacity is estimated for the assumed master production schedule.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.31
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• pp.177-186
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• 1994

Most causes of accidents are due to physical unsafety conditions and human unsafety actions. The design of safety work by ergonomics method is one of the methodes which effectively reduce these unsafety conditions and unsafety actions. This paper presents considerations in design of safety work. And when we try to analyze the accident event by means of probability, there exist some problems because of fuzziness in physical unsafety conditions' components and human unsafety actions' components which are the causes of basic event. For this reason, it is impossible for input probability of basic event to define a crisp value. In consideration of the uncertain probability of components, this paper deals with the Fuzzy set theory by membership value and suggests calculation procedure and analysis of disaster event.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.598-603
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• 1996

When locked rotor event. occurs, instantaneously affected loop and core flow were quickly reduced, which resulted in an increase in coolant temperature and system pressure. Analysis method of this event was that constant core inlet temperature and system pressure as well as change in core flow calculated from COAST code were statically used as an input variable to HERMITE code, because of no tools to simulate NSSS behavior and 1-D core neutronics transient coincidently. With employing TASS code revised with 1-D neutronics model, this event was analyzed in point of DNBR. By doing so, analysis procedure could be simplified and unreasonable conservatism might be removed in DNBR calculation by consideration of pressure increase.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.3
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• pp.85-90
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• 2015

In this paper, anew parallel event-driven logic simulation is proposed. As the proposed prediction-based parallel event-driven simulation method uses both prediction data and actual data for the input and output values of local simulations executed in parallel, the synchronization overhead and the communication overhead, the major bottleneck of the performance improvement, are greatly reduced. Through the experimentation with multiple designs, we have observed the effectiveness of the proposed approach.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.165-170
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• 2017

This paper presents an event-triggered model predictive controller for adaptive cruise control system with sampled and quantized-data. Unlike existing works, a longitudinal continuous-time model is used for the predictive control of the system. To efficiently utilize network resources, event-trigger scheme is employed, which allows limited sensor and actuator signal satisfying the condition that the measurement of errors is over the ratio of a trigger level. The proposed control gain is obtained by solving a convex problem satisfying several linear matrix inequalities at every sampling times. Simulation results are given to show the effectiveness of the proposed design method.

• Journal of Korea Multimedia Society
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• v.11 no.2
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• pp.143-152
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• 2008

Nowadays, many investigators are studying various methodologies concerning event expression for semantic retrieval of video data. However, most of the parts are still using annotation based retrieval that is defined into annotation of each data and content based retrieval using low-level features. So, we propose a method of creation of the motion unit and extracting event through the unit for the more semantic retrieval than existing methods. First, we classify motions by event unit. Second, we define semantic unit about classified motion of object. For using these to event extraction, we create rules that are able to match the low-level features, from which we are able to retrieve semantic event as a unit of video shot. For the evaluation of availability, we execute an experiment of extraction of semantic event in video image and get approximately 80% precision rate.

• The Journal of Society for e-Business Studies
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• v.14 no.4
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• pp.315-332
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• 2009

In logistic environments, a process, in that it manages the flow of materials among partners, involves more than one organization. In this regard, a logistic process, as a combined process consisting of multiple sub processes, needs to be managed with controling interaction among partners. In achieving systematic management of a logistic process, traditional Business Process Management (BPM) cannot be used for the entire flow, since it lacks the ability to manage interactions among partners. Particularly in logistic environments where RFID technologies are used, how to deal with the connection between RFID event and logistic flow has not been properly addressed. To overcome this limitation, this paper proposes a new method of managing multi-organizational logistic processes based on RFID events. We define inter-workflow pattern, and suggest ECA(Event-Condition-Action) rules for auto triggering of logistic processes. To adjust the rules to RFID events, we invent RFID-based ECA rules using complex event. A prototype system has been developed for the purpose of demonstrating the effectiveness of our approach.

• The KIPS Transactions:PartD
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• v.18D no.4
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• pp.215-224
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• 2011

U-Health collects patient information with various kinds of sensor. Stream data can be summarized as an interval event which has aninterval between start-time-point and end-time-point. Most of temporal mining techniques consider only the event occurrence-time-point and ignore stream data change of state. In this paper, we propose the temporal mining technique considering the event change of state in U-Health. Our method overcomes the restrictions of the environment by sending a significant event in U-Health from sensors to a server. We define four event states of stream data and perform the temporal data mining considered the event change of state. Finally, we can remove an ambiguity of discovered rules by describing cause-and-effect relations among events in temporal relation sequences.

• Journal of KIISE
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• v.43 no.11
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• pp.1281-1297
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• 2016

In recent years, personal videos have seen a tremendous growth due to the substantial increase in the use of smart devices and networking services in which users create and share video content easily without many restrictions. However, taking both into account would significantly improve event detection performance because videos generally have multiple modalities and the frame data in video varies at different time points. This paper proposes an event detection method. In this method, high-level features are first extracted from multiple modalities in the videos, and the features are rearranged according to time sequence. Then the association of the modalities is learned by means of DNN to produce a personal video event detector. In our proposed method, audio and image data are first synchronized and then extracted. Then, the result is input into GoogLeNet as well as Multi-Layer Perceptron (MLP) to extract high-level features. The results are then re-arranged in time sequence, and every video is processed to extract one feature each for training by means of DNN.