• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.89-100
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• 2011

The MAGLEV (Magnetically Levitated Vehicle) system, which is under commercialization as a new transportation system in Korea, is operated by means of unmanned automatic control system. Therefore the plan of train operation should be carefully established and validated in advance. In general, when making the train operation plan, the statistically predicted traffic data is used. However, traffic wave can occur when real train service is operated, and the demand-driven simulation technology is required to review train operation plans and service qualities considering traffic wave. This paper presents a method and model to simulate the MAGLEV's operation considering continuous demand changes. For this purpose, we employed the discrete event model which is suitable for modeling the behavior of railway passenger transportation, and modeled the system hierarchically using DEVS (Discrete Event System Specification) formalism. In addition, through the implementation and experiment using DEVSim++ simulation environment, we tested the feasibility of the proposed model and it is also verified that our demand-driven simulation technology could be used for the prior review of the train operation plans and strategies.

• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3620-3630
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• 2022

The diagnosis of abnormalities in a nuclear power plant is essential to maintain power plant safety. When an abnormal event occurs, the operator diagnoses the event and selects the appropriate abnormal operating procedures and sub-procedures to implement the necessary measures. To support this, abnormality diagnosis systems using data-driven methods such as artificial neural networks and convolutional neural networks have been developed. However, data-driven models cannot always guarantee an accurate diagnosis because they cannot simulate all possible abnormal events. Therefore, abnormality diagnosis systems should be able to detect their own potential misdiagnosis. This paper proposes a rulebased diagnostic validation algorithm using a previously developed two-stage diagnosis model in abnormal situations. We analyzed the diagnostic results of the sub-procedure stage when the first diagnostic results were inaccurate and derived a rule to filter the inconsistent sub-procedure diagnostic results, which may be inaccurate diagnoses. In a case study, two abnormality diagnosis models were built using gated recurrent units and long short-term memory cells, and consistency checks on the diagnostic results from both models were performed to detect any inconsistencies. Based on this, a re-diagnosis was performed to select the label of the second-best value in the first diagnosis, after which the diagnosis accuracy increased. That is, the model proposed in this study made it possible to detect diagnostic failures by the developed consistency check of the sub-procedure diagnostic results. The consistency check process has the advantage that the operator can review the results and increase the diagnosis success rate by performing additional re-diagnoses. The developed model is expected to have increased applicability as an operator support system in terms of selecting the appropriate AOPs and sub-procedures with re-diagnosis, thereby further increasing abnormal event diagnostic accuracy.

• Korean Journal of Computational Design and Engineering
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• v.18 no.4
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• pp.250-257
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• 2013

This paper introduces a failure analysis procedure that underpins real-time fault prognosis. In the previous study, we developed a systematic eventization procedure which makes it possible to reduce the original data size into a manageable one in the form of event logs and eventually to extract failure patterns efficiently from the reduced data. Failure patterns are then extracted in the form of event sequences by sequence-mining algorithms, (e.g. FP-Tree algorithm). Extracted patterns are stored in a failure pattern library, and eventually, we use the stored failure pattern information to predict potential failures. The two practical case studies (marine diesel engine and SIRIUS-II car engine) provide empirical support for the performance of the proposed failure analysis procedure. This procedure can be easily extended for wide application fields of failure analysis such as vehicle and machine diagnostics. Furthermore, it can be applied to human health monitoring & prognosis, so that human body signals could be efficiently analyzed.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.2
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• pp.87-96
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• 2019

Low power issue is one of the most critical problems in the Internet of Things (IoT), which are powered by battery. To solve this problem, various approaches have been presented so far. In this paper, we propose a method to reduce the power consumption by reducing the numbers of accesses into the flash memory consuming a large amount of power for on-chip software execution. Our approach is based on using cooperative logging structure to distribute the sampling overhead in single sensor node to adjacent nodes in case of rare-event applications. The proposed algorithm to identify event occurrence is newly introduced with negative feedback method by observing difference between past data and recent data coming from the sensor. When an event with need of flash access is determined, the proposed approach only allows access to write the sampled data in flash memory. The proposed event detection algorithm (EDA) result in 30% reduction of power consumption compared to the conventional flash write scheme for all cases of event. The sampled data from the sensor is first traced into the random access memory (RAM), and write access to the flash memory is delayed until the page buffer of the on-chip flash memory controller in the micro controller unit (MCU) is full of the numbers of the traced data, thereby reducing the frequency of accessing flash memory. This technique additionally reduces power consumption by 40% compared to flash-write all data. By sharing the sampling information via LoRa channel, the overhead in sampling data is distributed, to reduce the sampling load on each node, so that the 66% reduction of total power consumption is achieved in several IoT edge nodes by removing the sampling operation of duplicated data.

• The KIPS Transactions:PartD
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• v.18D no.4
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• pp.261-274
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• 2011

In recent competitive business environment each enterprise has to be agile and flexible. For these purposes run-time monitoring ofservices provided by an enterprise and early decision making through this becomes core competition of the enterprise. In addition, in order to process various innumerable events which are generated on enterprise systems techniques which make filtering of meaningful data are needed. However, the existing study related with this is nothing but discovering of service faults by monitoring depending upon API of BPEL engine or middleware, or is nothing but processing of simple events based on low-level events. Accordingly, there would be limitations to provide useful business information. In this paper, through situation detection an extended complex event model is presented, which is possible to provide more valuable and useful business information. Concretely, first of all an event processing architecture in an enterprise system is proposed, and event meta-model which is suitable to the proposed architecture is going to be defined. Based on the defined meta-model, It is presented that syntax and semantics of constructs in our event processing language including various and progressive event operators, complex event pattern, key, etc. In addition, an event context mechanism is proposed to analyze more delicate events. Finally, through application studies application possibility of this study would be shown and merits of this event model would be present through comparison with other event model.

• Journal of Industrial Technology
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• v.27 no.B
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• pp.235-243
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• 2007

Sensor network is used to obtain sensing data in various area. The interval to sense the events depends on the type of target application and the amounts of data generated by sensor nodes are not constant. Many applications exploit long sensing interval to enhance the life time of network but there are specific applications that requires very short interval to obtain fine-grained, high-precision sensing data. If the number of nodes in the network is increased and the interval to sense data is shortened, the amounts of generated data are greatly increased and this leads to increased amount of packets to transfer to the network. To transfer large amount of packets fast, 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. The longer the interval, the higher the delay and the shorter the delay, the larger the fail of transfer request. 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 timee. Therefore ESTEO could provide high packet transmission rate given large amount of packets.

• Journal of Internet Computing and Services
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• v.12 no.4
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• pp.181-194
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• 2011

Server push which is technology of sending contents from servers to browsers in real time using long polling requests enables real time bidirectional communications between servers and browsers in HTTP environment. Recently, thanks to the rapid supply of mobile devices having ability of full browsing, server push is being applied to various applications. However, because servers providing services should offer distributed contents to a large number of users simultaneously in various user environments, they have a burden that offers contents quickly distinguishing much more concurrent users than before. The method of message exchange so far achieved in distributed server environment has difficulties in the performance of simultaneous user request process, the identification of users and the contents delivery. In this paper, We proposed message exchange architecture between servers for offering server push in the distributed server environment. The proposed architecture enables message exchange in the method of push between servers based on event driven architecture. In addition, the proposed architecture enables flexible identification of a event agent and event processing under the connected environment of a lot of users. In this paper, we designed and implemented the proposed architecture and compared performance with the previous way through a performance test. In addition, function is confirmed through the case realization. As a result of the performance test, the proposed architecture can lessen the use of server Thread and response time of users and increase simultaneous throughput.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.5
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• pp.492-500
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• 2014

Activity monitoring has been widely recognized as important and critical tools in system monitoring for detection of abnormal behavior. In this research, we propose a data-driven activity monitoring method to measure relative sales performance which is not sensitive to special event which frequently occur in marketing area. Moreover, the proposed method can automatically updates the monitoring threshold that accommodates a drastically changing business environment. The results from simulation and practical case study from sales of electronic devices demonstrate the usefulness and applicability of the proposed activity monitoring method.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.2
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• pp.109-114
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• 2008

In this paper, a dynamic learning controller for robot manipulator is implemented using real-time operating system with capabilities of multitasking, intertask communication and synchronization, event-driven, priority-driven scheduling, real-time clock control, etc. The controller hardware system with VME bus and related devices is developed and applied to implement a dynamic learning control scheme for robot manipulator. Real-time performance of the proposed dynamic learning controller is tested and evaluated for tracking of the desired trajectory and compared with the conventional servo controller.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.256-259
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• 2016

The growth of mobile devices in Internet of Things (IoT) leads to a number of intelligent buildings related IoT applications. For instance, home automation controlling system uses client system such web apps on smartphone or web service to access the home server by sending control commands. The home server receives the command, then controls for instance the light system. The gateway based RESTful technology responsible for handling clients' requests attests an internet latency in case a large number of clients' requests submit toward the gateway increases. In this paper, we propose the design tasks of the IoT gateway for handling concurrency events. In the procedure of designing tasks, concurrency is best understood by employing multiple levels of abstraction. The way that is eminently to accomplish concurrency is to build an object-oriented environment with support for messages passing between concurrent objects. We also investigate the performance of event-driven architecture for building IoT gateway using node.js on one side and communication protocol based message-oriented middleware known as XMPP to handle communications of intelligent building control devices connected to the gateway through a centralized hub. The Node.JS is 40% faster than the traditional web server side features thread-based approach. The use of Node.js server-side handles a large number of clients' requests, then therefore, reduces delay in performing predefined actions automatically in intelligent building IoT environment.