• Journal of the Korean Society of Safety
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• v.26 no.4
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• pp.87-95
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• 2011

The urgent VAI(Vital Area Identification) method development is required since 'The Act of Physical Protection and Radiological Emergency' that is established in 2003 requires an evaluation of physical threats in nuclear facilities and an establishment of physical protection in Korea. The KAERI(Korea Atomic Energy Research Institute) has developed the VAI methodology and VAI software called as VIPEX(Vital area Identification Package EXpert) for identifying the vital areas. This study is to demonstrate the applicability of KAERI's VAI methodology to a hypothetical facility, and to identify the importance of information of cable and piping runs when identifying the vital areas. It is necessarily needed to consider cable and piping runs to determine the accurate and realistic TEPS(Top Event Prevention Set). If the information of cable and piping runs of a nuclear power plant is not considered when determining the TEPSs, it is absolutely impossible to acquire the complete TEPSs, and the results could be distorted by missing it. The VIPEX and FTREX(Fault Tree Reliability Evaluation eXpert) properly calculate MCSs and TEPSs using the fault tree model, and provide the most cost-effective method to save the VAI and physical protection costs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.654-662
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• 2016

As the number of gates and basic events in fault trees increases, it becomes difficult to calculate the exact probability of the top event. In order to overcome this difficulty the BDD methodology can be used to calculate the exact top event probability for small and medium size fault trees in short time. Fault trees are converted to BDD by using CUDD library functions and a failure path search algorithm is proposed to calculate the exact top event probability. The backward search algorithm is more efficient than the forward one in finding failure paths and in the calculation of the top event probability. This backward search algorithm can reduce searching time in the identification of disjoint failure paths from BDD and can be considered as an effective tool to find the cut sets and the minimal cut sets for the given fault trees.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.125-130
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• 2017

Since field control equipment such as PLC has no function to log key event information in the log, it is difficult to analyze the accident. Therefore, it is necessary to secure information that can analyze when a cyber accident occurs by logging the main event information of the field control equipment such as PLC and IED. The protocol analyzer is required to analyze the field control device (the embedded device) communication protocol for event logging. However, the conventional analyzer, such as Wireshark is difficult to process the data identification and extraction of the large variety of protocols for event logging is difficult analysis of the payload data based and classification. In this paper, we developed a system for Big Data based on field control device communication protocol payload data extraction for event logging of large studies.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10c
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• pp.392-395
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• 2006

RFID(Radio Frequency IDentification)는 라디오 신호에 따라 반응하는 태그(Tag)를 이용하여 해당 사물을 인식하는 기술이다. RFID 이벤트의 특징은 짧은 시간 내에 빠르게 생성되며 생성된 각각의 RFID 이벤트 정보는 단순하지만 대량의 이벤트들을 처리할 수 있으며 추가적인 정보를 태그에 담을 수 있다. 이러한 장점으로 물류나 재고관리 유통분야 등에서 RFID를 이용하여 시스템을 자동화하고 있다. RFID를 시스템에 적용하기 위해서는 RFID이벤트의 특성을 고려하여 시스템이 개발되어야 한다. 그러나 여전히 기존의 RFID 시스템은 해당 어플리케이션의 비즈니스 이벤트를 처리하기 위해 RFID에 대한 다양한 지식과 통신 방법 등을 이해해야 하는 복잡함을 가지고 있다. 뿐만 아니라 이기종의 플랫폼에서 개발, 동작하는 어플리케이션 개발을 지원하는 측면에서도 어려움이 있다. 본 논문에서는 다양한 이기종의 RFID 어플리케이션과 ALE를 지원하기 위한 비즈니스 이벤트 프레임워크(Business Event Framework, BEF)를 제시하였다. 또한 실제 이기종의 플랫폼에서 개발된 어플리케이션을 지원하기 위해 어플리케이션 매니저(AppManager)를 정의하였다. 마지막으로 RFID 관련 기술을 개발자가 모두 이해해야함을 최소화 하기위해 비즈니스 이벤트 스펙(Business Event Spec, BESpec)을 정의하였다.

• Journal of the Korean Society of Safety
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• v.15 no.2
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• pp.126-135
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• 2000

Probabilistic Safety Assessment (PSA) is an engineering analysis method to identify possible contributors to the risk from a nuclear power plant and now it has become a standard tool in safety evaluation of nuclear power plants. PSA consists of three phases named as Level 1, 2 and 3. Level 2 PSA, mainly focused in this paper, uses a step-wise approach. At first, plant damage states (PDSs) are defined from the Level 1 PSA results and they are quantified. Containment event tree (CET) is then constructed considering the physico-chemical phenomena in the containment. The quantification of CET can be assisted by a decomposition event tree (DET). Finally, source terms are quantitatively characterized by the containment failure mode. As the main benefit of PSA is to provide insights into plant design, performance and environmental impacts, including the identification of the dominant risk contributors and the comparison of options for reducing risk, this technique is expected to be applied to the industrial safety area.

• Proceedings of the IEEK Conference
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• summer
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• pp.237-243
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• 2004

A multichannel smart sound sensor capable to detect and identify sound events in noisy conditions is presented in this paper. Sound information extraction is a complex task and the main difficulty consists is the extraction of high­level information from an one-dimensional signal. The input of smart sound sensor is composed of data collected by 5 microphones and its output data is sent through a network. For a real time working purpose, the sound analysis is divided in three steps: sound event detection for each sound channel, fusion between simultaneously events and sound identification. The event detection module find impulsive signals in the noise and extracts them from the signal flow. Our smart sensor must be capable to identify impulsive signals but also speech presence too, in a noisy environment. The classification module is launched in a parallel task on the channel chosen by data fusion process. It looks to identify the event sound between seven predefined sound classes and uses a Gaussian Mixture Model (GMM) method. Mel Frequency Cepstral Coefficients are used in combination with new ones like zero crossing rate, centroid and roll-off point. This smart sound sensor is a part of a medical telemonitoring project with the aim of detecting serious accidents.

• Journal of information and communication convergence engineering
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• v.5 no.3
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• pp.233-238
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• 2007

An approach to identify Chinese event types is proposed in this paper which combines a good feature selection policy and a Maximum Entropy (ME) model. The approach not only effectively alleviates the problem that classifier performs poorly on the small and difficult types, but improve overall performance. Experiments on the ACE2005 corpus show that performance is satisfying with the 83.5% macro - average F measure. The main characters and ideas of the approach are: (1) Optimal feature set is built for each type according to local feature selection, which fully ensures the performance of each type. (2) Positive and negative features are explicitly discriminated and combined by using one - sided metrics, which makes use of both features' advantages. (3) Wrapper methods are used to search new features and evaluate the various feature subsets to obtain the optimal feature subset.

• Smart Structures and Systems
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• v.31 no.2
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• pp.101-111
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• 2023

Structural health monitoring (SHM) covers a range of damage detection strategies for buildings. In real-time, SHM provides a basis for rapid decision making to optimise the speed and economic efficiency of post-event response. Previous work introduced an SHM method based on identifying structural nonlinear hysteretic parameters and their evolution from structural force-deformation hysteresis loops in real-time. This research extends and generalises this method to investigate the impact of a wide range of flag-shaped or pinching shape nonlinear hysteretic response and its impact on the SHM accuracy. A particular focus is plastic stiffness (K_p), where accurate identification of this parameter enables accurate identification of net and total plastic deformation and plastic energy dissipated, all of which are directly related to damage and infrequently assessed in SHM. A sensitivity study using a realistic seismic case study with known ground truth values investigates the impact of hysteresis loop shape, as well as added noise, on SHM accuracy using a suite of 20 ground motions from the PEER database. Monte Carlo analysis over 22,000 simulations with different hysteresis loops and added noise resulted in absolute percentage identification error (median, (IQR)) in K_p of 1.88% (0.79, 4.94)%. Errors were larger where five events (Earthquakes #1, 6, 9, 14) have very large errors over 100% for resulted K_p as an almost entirely linear response yielded only negligible plastic response, increasing identification error. The sensitivity analysis shows accuracy is reduces to within 3% when plastic drift is induced. This method shows clear potential to provide accurate, real-time metrics of non-linear stiffness and deformation to assist rapid damage assessment and decision making, utilising algorithms significantly simpler than previous non-linear structural model-based parameter identification SHM methods.

• Journal of Satellite, Information and Communications
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• v.10 no.3
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• pp.16-21
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• 2015

In this paper, we presented Under Vehicle Inspection System by comparing two image signals. Two signals are generated by license plate number and under-vehicle pattern recognition. The test shows reliable precision within real-time of 2.8sec, which can be applicable commercially. In the future, more research will be conducted to enhance the precision by automatic image balance in many challenging situations.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.76.2-76.2
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• 2019

Recent observation of the neutron star merger event, GW170817, through both gravitational wave (GW) and electromagnetic wave (EM) observations opened a new way of exploring the universe, namely, multi-messenger astronomy (MMA). One of the keys to the success of MMA is a rapid identification of EM counterpart. We will introduce the strategy for prioritization of GW source host galaxy candidates. Our method relies on recent simulation results regarding plausible properties of GW source host galaxies and the low latency localization map from LIGO/Virgo. We will show the test results for both NS merger and BH merger events using previous events and describe observing strategy with our facilities for GW events during the ongoing LIGO/Virgo O3 run. Finally, we report the result of follow-up observation on, the first neutron star merger event, S190425z, during LIGO/VIrgo O3 run.