• Journal of Microbiology and Biotechnology
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• v.16 no.11
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• pp.1778-1783
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• 2006

Event-specific PCR detection methods are the primary trend in genetically modified (GM) plant detection owing to their high specificity based on the flanking sequence of the exogenous integrant. Therefore, this study describes a real-time PCR system for event-specific GM canola GT73, consisting of a set of primers, TaqMan probe, and single target standard plasmid. For the specific detection of GT73 canola, the 3'-integration junction sequence between the host plant DNA and the integrated specific border was targeted. To validate the proposed method, test samples of 0, 1, 3, 5, and 10% GT73 canola were quantified. The method was also assayed with 15 different plants, and no amplification signal was observed in a real-time PCR assay with any of the species tested, other than GT73 canola.

• The Transactions of the Korea Information Processing Society
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• v.5 no.5
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• pp.1204-1215
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• 1998

In this paper, we propose a scenario representing method, a specification language, and a verification technique for OARTS(Object based Approach for Real-Time Systems). As well as the general modeling method(event trace diagram), this study includes a specification language and a verification technique because there was no study about methodological level technique for scenario development as yet. Centering around the synchronization problem of transition of external modules which are the communication interfaces based on the objects, we lay stress on the representation of sequence of external events and internal action transitions. From the results of practical experiences, it has been ascertained that the proposed method reflect well the requirements in the analysis step, and its validity of the representation has been identified by a conceptual verifier. We support that it can serve as an analyzing tool for representing a general real-time scenarios also.

• Journal of KIISE:Software and Applications
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• v.28 no.10
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• pp.706-719
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• 2001

In this paper, we present a new approach to deterministic execution for testing concurrent programs. The proposed approach makes use of the notion of event independence which has been used in the partial-order method in order to resolve the state-explosion problem and constructs and automation which accepts all the sequences semantically equivalent to a given sequence. Consequently, we can allow a program to be executed according to event sequences other then the (possibly infeasible) given sequence if they have the same effects on the program's behavior. One advantage of this method is that it can be applied to situations where a program is not exactly implemented as described in the specification.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1670-1683
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• 2017

Mitotic event recognition is a crucial and challenging task in biomedical applications. In this paper, we introduce the slow feature analysis and propose a fully-automated mitotic event recognition method for cell populations imaged with time-lapse phase contrast microscopy. The method includes three steps. First, a candidate sequence extraction method is utilized to exclude most of the sequences not containing mitosis. Next, slow feature is learned from the candidate sequences using slow feature analysis. Finally, a hidden conditional random field (HCRF) model is applied for the classification of the sequences. We use a supervised SFA learning strategy to learn the slow feature function because the strategy brings image content and discriminative information together to get a better encoding. Besides, the HCRF model is more suitable to describe the temporal structure of image sequences than nonsequential SVM approaches. In our experiment, the proposed recognition method achieved 0.93 area under curve (AUC) and 91% accuracy on a very challenging phase contrast microscopy dataset named C2C12.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.3
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• pp.164-172
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• 2022

A HAZID is a brainstorming workshop to identify hazards in an early phase of a project. It should be flexible to capture all probable accidents allowing experienced participants to exploit their expertise and experiences. A bowtie analysis is a graphical representation of major accident hazards elaborating safety measures i.e. barriers. The result of these workshops should be documented in an organized manner to share as good as possible details of the discussion through the lifetime of the project. Currently results are documented using a three-step representation of an accident; causes, top event and consequences, which cannot capture correctly sequence of events leading to various accidents and roles of barrier between two events. Another problem is that barriers would be shown repeatedly leading to a misunderstanding that there are an enough number of safety measures. A new bowtie analysis method is proposed to describe an accident in multiple steps showing relations among causes or consequences. With causes and consequences shown in a format of a tree, the frequencies of having the top event (Fault tree analysis) and various consequences (Event tree analysis) are evaluated automatically based on the frequency of initiating causes and the probabilities of failure of barriers. It will provide a good description of the accident scenario and help the risk to be assessed transparently.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.313-326
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• 2017

The systematic management of plant risk is crucial for enhancing the safety of nuclear power plants and for designing new nuclear power plants. Accident sequence precursor (ASP) analysis may be able to provide risk significance of operational experience by using probabilistic risk assessment to evaluate an operational event quantitatively in terms of its impact on core damage. In this study, an ASP methodology for two operation mode, full power and low power/shutdown operation, has been developed and applied to significant accident precursors that may occur during the operation of nuclear power plants. Two operational events, loss of feedwater and steam generator tube rupture, are identified as ASPs. Therefore, the ASP methodology developed in this study may contribute to identifying plant risk significance as well as to enhancing the safety of nuclear power plants by applying this methodology systematically.

• Nuclear Engineering and Technology
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• v.28 no.3
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• pp.247-256
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• 1996

This paper presents a new approach for assessing accident management strategies using containment event trees (CETs) developed during an individual plant examination (IPE) for a reference plant (CE type, 950 MWe PWR). Various accident management strategies to reduce risk have been proposed through IPE. Three strategies for the station blackout sequence are used as an example : 1) reactor cavity flooding only, 2) primary system depressurization only, and 3) doing both. These strategies are assumed to be initiated at about the time of core uncovery. The station blackout (SBO) sequence is selected in this paper since it is identified as one of the most threatening sequences to safety of the reference plant. The effectiveness and adverse effects of each accident management strategy are considered synthetically in the CETs. A best estimate assessment for the developed CETs using data obtained from NUREG-1150, other PRA results, and the MAAP code calculations is performed. The strategies are ranked with respect to minimizing the frequencies of Various containment failure modes. The proposed approach is demonstrated to be very flexible in that it can be applied to any kind of accident management strategy for any sequence.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4560-4570
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• 2022

Dynamic fault tree (DFT) and its related research methods have received extensive attention in safety analysis and reliability engineering. DFT can perform reliability modelling for systems with sequential correlation, resource sharing, and cold and hot spare parts. A technical modelling method of DFT is proposed for modelling ship collision accidents and loss-of-coolant accidents (LOCAs). Qualitative and quantitative analyses of DFT were carried out using the cutting sequence (CS)/extended cutting sequence (ECS) method. The results show nine types of dynamic fault failure modes in ship collision accidents, describing the fault propagation process of a dynamic system and reflect the dynamic changes of the entire accident system. The probability of a ship collision accident is 2.378 × 10^-9 by using CS. This failure mode cannot be expressed by a combination of basic events within the same event frame after an LOCA occurs in a marine nuclear reactor because the system contains warm spare parts. Therefore, the probability of losing reactor control was calculated as 8.125 × 10^-6 using the ECS. Compared with CS, ECS is more efficient considering expression and processing capabilities, and has a significant advantage considering cost.

• Korea journal of population studies
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• v.25 no.2
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• pp.107-138
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• 2002

In general, women's labor force participation follows a M-curve pattern because women's state of economic activity usually changes by their life course stage. This research attentions that the effect of sequence of life course as well as the effects of‘marriage bar’, or‘maternity leave’is very important in understanding women's chaning economic activity status. First, this research hypothesizes that women's four patterns of job career such as‘continuous pattern’,‘discontinuous pattern’,‘non-economic activity pattern’,‘marriage leave pattern’result a significant difference in social and demographic variables. Second, this research analyzes the effect of ordering and timing of life events on women's work transition. This research investigates labor market dynamics to conceptualize labor market behaviors using longitudinal data and sequence analysis and event history analysis. We find that four patterns of job career vary by age, educational attainment, having a certificate or not, their parents’human capital and health status. And we find that the ordering and timing of‘participation in labor market’and‘marriage’determine the pattern of women's work transition.