• Journal of the Korea Society of Computer and Information
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• v.22 no.10
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• pp.109-119
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• 2017

In recent through development of IOT owing to that mass stream data is being generated in variety of application complex event processing technology is being watched with keen interest as a technology to analyze this kind of real-time continuous data. However, the existing study related with complex event processing only comes to an end at simple event processing based on low-level event or comes to an end at service defect discovery with providing limited operator and so on. Accordingly, there would be limitation to provide useful analysis information. In this paper in consideration of complex event along with aspect-oriented programming an extended complex event model is provided, which is possible to provide more valuable and useful information. Specifically, we extend the model to support hierarchical event structures and let the model recognize point-cuts of aspect-oriented programming as events. We provide the event operators designed to specify the events on instances and handle temporal relations of the instances. It is presented that syntax and semantics of constructs in our event processing language including various and progressive event operators, complex event pattern, 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 Information Processing Systems
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• v.15 no.3
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• pp.570-592
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• 2019

The Event-B design pattern is an excellent way to quickly develop a formal model of the system. Researchers have proposed a number of Event-B design patterns, but they all lack formal behavior semantics. This makes the analysis, verification, and simulation of the behavior of the Event-B model very difficult, especially for the control-intensive systems. In this paper, we propose a novel method to transform the Event-B synchronous control flow design pattern into the labeled transition system (LTS) behavior model. Then we map the design pattern instantiation process of Event-B to the instantiation process of LTS model and get the LTS behavior semantic model of Event-B model of a multi-level complex control system. Finally, we verify the linear temporal logic behavior properties of the LTS model. The experimental results show that the analysis and simulation of system behavior become easier and the verification of the behavior properties of the system become convenient after the Event-B model is converted to the LTS model.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.3
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• pp.79-99
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• 1992

The DEVS (Discrete Event system Specification) formal model for discrete event simulation is a hierarchical, modular model. Because the DEVS formal model has a mathematical structure, it provides a theoretic background of discrete event simulation model. However, the DEVS formal model is difficult to understand because of its mathematical structure. Also, since the DEVS formal model is often constructed by heuristic, subjective method of model designer from the model, a systematic model built-in methodology does not exist. In this paper, we propose the model formalization methodology from an informal model to the DEVS formal model. For this formalization methodology, we introduce formal tools for model construction based on the DEVS ( from an informal model : Event Dependency Graph (EDG) for the event analysis and State Representation Graph(SRG) for the system state analysis.

• Journal of KIISE:Information Networking
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• v.37 no.1
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• pp.8-15
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• 2010

In this study, we present an extended complex event model by considering both of the complex event and the aspect-oriented programming. We propose an advanced scheme for the event specification suited for the event correlation based network management systems by merging these two models. Specifically, we extend the model to support hierarchical event structures and let the model recognize point-cuts of aspect-oriented programming as events. We provide the event operators designed to specify the events on instances and handle temporal relations of the instances. Lastly, we compare the proposed model with other event models and present the benefits of it.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.864-867
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• 1995

Presented in the paper is a structured approach to modeling automated manufacturing system (AMS) in the form of an event graph. The proposed two-phase procedure for formal modeling is 1) reference modeling by schematic supervisory control modeling and 2) event graph transformation from supervisory control model. Also described is a formal model for a small-sized FMS in the form of an event graph.

• Journal of Information Processing Systems
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• v.11 no.2
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• pp.248-265
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• 2015

In this paper, we propose a maximum entropy-based model, which can mathematically explain the bio-molecular event extraction problem. The proposed model generates an event table, which can represent the relationship between an event trigger and its arguments. The complex sentences with distinctive event structures can be also represented by the event table. Previous approaches intuitively designed a pipeline system, which sequentially performs trigger detection and arguments recognition, and thus, did not clearly explain the relationship between identified triggers and arguments. On the other hand, the proposed model generates an event table that can represent triggers, their arguments, and their relationships. The desired events can be easily extracted from the event table. Experimental results show that the proposed model can cover 91.36% of events in the training dataset and that it can achieve a 50.44% recall in the test dataset by using the event table.

• Journal of the Korean Society of Safety
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• v.31 no.5
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• pp.187-194
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• 2016

A single fire event within a fire area can cause multiple initiating events considered in internal events probabilistic safety assessment (PSA). For an example, a fire event in turbine building fire area can cause a loss of the main feed-water and loss of off-site power initiating events. This fire initiating event could result in special plant responses beyond the scope of the internal events PSA model. One approach to address a fire initiating event is to develop a specific fire event tree. However, the development of a specific fire event tree is difficult since the number of fire event trees may be several hundreds or more. Thus, internal fire events PSA model has been generally constructed by modifications of the pre-developed internal events PSA model. New accident sequence logics not covered in the internal events PSA model are separately developed to incorporate them into the fire PSA model. Recently, many fire PSA models have fire induced initiating event fault trees not shown in an internal event PSA model. Up to now, there has been no analytical comparative study on the constructions of fire events PSA model using internal events PSA model with and without fault trees of initiating events. In this study, the changing process of internal events PSA model to fire events PSA model is analytically presented and discussed.

• The Journal of Information Technology
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• v.9 no.3
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• pp.77-89
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• 2006

The event study analyzes returns around event date at a time. Event study provides estimation periods and cumulative returns. Stock split announcements are generally associated with positive abnormal returns. It is important to investigate the responses of stocks to new information contained in the announcements of stock splits. So It is important to study the long term performance in the case of Stock Split. This Study forced to two approach method in evaluating the performance, the event time portfolio approach and calendar time portfolio approach. The event time portfolio approach exists the CAR model, BHAR model and WR model. And the calendar time portfolio approach has the 3 factor model, 4 factor model, CTAR model, and RATS model.

• Communications for Statistical Applications and Methods
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• v.15 no.5
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• pp.727-735
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• 2008

Consider a clinical trial in which the main end-point is survival. Suppose after the start of the study an intermediate event occurs which may be influenced by a covariate(or treatment). In many clinical studies the occurrence of an intermediate event may change the survival distribution. This investigation develops two-stage model which, in the first stage, models the effect of covariate on the intermediate event and models the relationship between survival time and covariate as well as the intermediate event. In this paper, the two-stage model is presented in order to model intermediate event and a test based on this model is also provided. A numerical simulations are carried out to evaluate its overall significance level.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.807-825
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• 2020

In recent years, business environments have become more complex; therefore, enterprises must be capable of responding flexibly and agilely. For these purposes, effective enterprise systems service monitoring and early decision making based on the same, emerge as core competency of the enterprise. In addition, enterprise system techniques that filter meaningful data are needed to event processing. 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 study, we present an extended event processing model that enables delivery of more valuable and useful business information through situation detection. Primarily, the event processing architecture in an enterprise system is proposed as a definite approach, and then define an event meta-model suitable for the proposed architecture. Based on the defined model, we propose the syntax and semantics of the elements that make up the event processing language include various and progressive event operators, the rules, complex event pattern, etc. In addition, an event context mechanism is proposed to analyze more delicate events. Finally, the effectiveness and applicability of proposed approach is presented through a case study.