• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.157-161
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• 2009

In recent years, there is a remarkable progress in ICTs (Information and Communication Technologies), and then many attempts to apply ICTs to other industries are being made. In the field of disaster managements, ICTs such as RFID (Radio Frequency IDentification) and USN (Ubiquitous Sensor Network) are used to provide safe environments. Actually, various types of early warning systems using USN are now widely used to monitor natural disasters such as floods, landslides and earthquakes, and also to detect human-caused disasters such as fires, explosions and collapses. These early warning systems issue alarms rapidly when a disaster is detected or an event exceeds prescribed thresholds, and furthermore deliver alarm messages to disaster managers and citizens. In general, these systems consist of a number of various sensors and measure real-time stream data, which requires an efficient and rapid data processing technique. In this study, an event-driven architecture (EDA) is presented to collect event effectively and to provide an alert rapidly. A publish/subscribe event processing method to process simple event is introduced. Additionally, a complex event processing (CEP) technique is introduced to process complex data from various sensors and to provide prompt and reasonable decision supports when many disasters happen simultaneously. A basic concept of CEP technique is presented and the advantages of the technique in disaster management are also discussed. Then, how the main processing methods of CEP such as aggregation, correlation, and filtering can be applied to disaster management is considered. Finally, an example of flood forecasting and early alarm system in which CEP is incorporated is presented It is found that the CEP based on the EDA will provide an efficient early warning method when disaster happens.

• Journal of the Korea Safety Management & Science
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• v.12 no.2
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• pp.161-166
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• 2010

EPC Information Services (EPCIS) is an EPCglobal standard designed to enable EPC-related data sharing within and across supply chain. The EPCIS standard defines standard interfaces to enable EPC-related data to be captured and subsequently to be queried using a set of service operations and an associated data model. There are two kinds of EPCIS data: event data and master data. Event data is created in the process of carrying out business processes. Traceability of goods across supply chain is based on event data. Therefore, each company must have an event data. This study compared he difference between MS-SQL(DRDBMS) and ALTIBASE(MMDBMS) for data storage. We compared the difference between two database management in many respects such as insert time and select time. We come to a conclusion that ALTIBASE is more efficient than MS-SQL.

• Journal of Mechanical Science and Technology
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• v.16 no.11
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• pp.1497-1510
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• 2002

The onset of cavitation causes head and efficiency of a main pump to be reduced significantly and generates vibration and noise. In order to avoid these phenomena, the inlet of the pump is fitted with a special rotor called an inducer, which can operate satisfactorily with extensive cavitation. The motivation of this study is to find out cavitation modes from the inducer inlet pressure signals and event characteristics from outlet ones at various operating conditions. The cavitation modes are analyzed by using a cross-spectral density of fluctuating pressures at the inducer inlet. The time-frequency characteristics of wall pressures downstream of the inducer are presented in terms of event frequency, its duration time, and number of events by using the Choi-Williams distribution.

• Journal of KIISE:Software and Applications
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• v.28 no.12
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• pp.921-929
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• 2001

OCL was used in the UML Semantics document to specify the well-formedness rules of the UML metarmodel. UML was extended to apply it to system developments of several fields, for example real-time UML and web applications with UML. In particular the dependability is important in designing and building hard real-time system. Thus OCL is needed to express real-time UML formally and so it must extended. In this paper, we extend OCL to define event-driven real-time OCL to the development of Nrcl simulator.

• Journal of Korea Multimedia Society
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• v.11 no.3
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• pp.301-314
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• 2008

The existing event recognition is accomplished with the limited systematic foundation, and thus much longer learning time is needed for emergency scenario interpretation due to large scale of probability data. In this paper, we propose a method for nile-based event recognition of an independent object(human) which extract a feature vectors from the object and analyze the behavior pattern of each object and interpretation of emergency scenarios using a probability and object's events. The event rule of an independent object is composed of the Primary-event, Move-event, Interaction-event, and 'FALL DOWN' event and is defined through feature vectors of the object and the segmented motion orientated vector (SMOV) in which the dynamic Bayesian network is applied. The emergency scenario is analyzed using current state of an event and its post probability. In this paper, we define diversified events compared to that of pre-existing method and thus make it easy to expand by increasing independence of each events. Accordingly, semantics information, which is impossible to be gained through an.

• IE interfaces
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• v.20 no.3
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• pp.288-297
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• 2007

Success of semiconductor/LCD industry depends on its yield and quality of product. For the purpose, FDC (Fault Detection and Classification) system is used to diagnose fault state in main manufacturing processes by monitoring time series data collected by equipment sensors which represent various conditions of the equipment. The data set is segmented at the start and end of each product lot processing by a trigger event module. However, in practice, segmented sensor data usually have the features of data asynchronization such as different start points, end points, and data lengths. Due to the asynchronization problem, false alarm (type I error) and missed alarm (type II error) occur frequently. In this paper, we propose a robust process fault detection system by integrating a process event detection method and a similarity measuring method based on dynamic time warping algorithm. An experiment shows that the proposed system is able to recognize abnormal condition correctly under the asynchronous data situation.

• 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.

• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.469-480
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• 2017

On April 1, 2004, KTX (Korea Train eXpress), the first HSR (High-Speed Rail) in Korea, was introduced to Gyeongbu Line. The introduction of the KTX service led to a change in the number of passengers for Gyeongbu Line. Previous studies have analyzed the pre and post-event changes of the intervening events by either simple statistics or intervention ARIMA analysis. However, the intervention ARIMA model has a limitation that several assumptions such as the occurrence time and the type of intervention events are necessary. To this end, this study analyzed the effects of intervention event on the number of passengers using the Gyeongbu line based on a time series outlier detection technique which can overcome limitations in the previous studies. The time series outlier detection technique can analyze the time, effect type and size of an intervention event without the assumption of the time and effect type of the intervention event. The data were collected from the Korea Transport Database (KTDB) for twelve years from 2003 to 2014 (144 months). The analysis results showed that the size of the influence type in the same intervention events was different across the major city routes, and the intervention event which could not be found by previous study methods was also found.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.923-929
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• 2002

We discuss scheduling analysis for a discrete event system with time windows of which firing or holding time delays are subject to random variation within some finite range. To do this, we propose a modified p-lime Petri net, named p+-time Petri net. We develop a condition for which a synchronized transition does not have a dead token, that is, the firing epochs do not violate the time window constraints. We propose a method of computing the feasible range of the token sojourn time at each place based on a time difference graph. We also discuss an application for analyzing wafer residency times within the process chambers for a dual-armed cluster tool for chemical vapor deposition.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.264-267
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• 2000

The need for including time variables in various type of modeled Discrete Event Dynamic Systems(DEDSs) is apparent since the modeled systems are real time in nature. In the real world, almost all event is related to time. A Time Petri Net(TPN) is one of methods for model ins and analyzing of DEDSs with real time values. Two time values, ${\alpha}$$\sub$i/ and ${\beta}$$\sub$i/ are defined for each transition. In this paper, Ire present Fuzzy Transition Timed Petri Net(FTTPN) to determine the optimal transition firing time between ${\alpha}$$\sub$i/ and ${\beta}$$\sub$i/ using fuzzy theory. The traffic signal controller in an intersection is modeled and analyzed by FTTPN.