• 한국화재소방학회논문지
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• 제33권5호
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• pp.109-117
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• 2019

화재발생의 직접적인 원인 제공자들이 그 화재로 인한 피해자들에게 손해배상을 할 능력이 없으면 피해자들은 소방기관에 국가배상책임을 물어 피해구제를 받으려는 경향이 있다. 2가지 국가배상 사례 분석에서 화재로 인한 손해와 소방공무원의 화재예방 또는 소방특별조사 활동과 관련된 과실 사이에 인과관계가 있으면, 법원은 소방기관에서 피해자에게 손해를 배상하도록 판결함을 알 수 있었다. 2017년 12월 26일 「소방기본법」이 개정되어 '소방활동에 대한 면책' 조항이 마련되었지만 면책을 받으려면 그 활동의 불가피성이 입증되어야 하는데, 화재예방이나 소방검사 활동은 구조·구급활동과 달리 그 활동의 불가피성을 입증하기가 쉽지 않으므로 화재와 관련된 국가배상 청구 소송은 줄어들지 않을 것으로 예측된다.

• Journal of Microbiology and Biotechnology
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• 제20권12호
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• pp.1653-1663
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• 2010

The first gene (${\alpha}$-gal1) encoding an extracellular ${\alpha}$-Dgalactosidase from the thermophilic fungus Talaromyces emersonii was cloned and characterized. The ${\alpha}$-gal1 gene consisted of an open reading frame of 1,792 base pairs interrupted by six introns that encoded a mature protein of 452 amino acids, including a 24 amino acid secretory signal sequence. The translated protein had highest identity with other fungal ${\alpha}$-galactosidases belonging to glycosyl hydrolase family 27. The ${\alpha}$-gal1 gene was overexpressed as a secretory protein with an N-terminal histidine tag in the methylotrophic yeast Pichia pastoris. Recombinant ${\alpha}$-Gal1 was secreted into the culture medium as a monomeric glycoprotein with a maximal yield of 10.75 mg/l and purified to homogeneity using Hisbinding nickel-agarose affinity chromatography. The purified enzyme was maximally active at $70^{\circ}C$, pH 4.5, and lost no activity over 10 days at $50^{\circ}C$. ${\alpha}$-Gal1 followed Michaelis-Menten kinetics ($V_{max}\;of\;240.3{\mu}M/min/mg,\;K_m\;of\;0.294 mM$) and was inhibited competitively by galactose ($K_m{^{obs}}$ of 0.57 mM, $K_i$ of 2.77 mM). The recombinant T. emersonii ${\alpha}$-galactosidase displayed broad substrate preference, being active on both oligo- and polymeric substrates, yet had strict specificity for the ${\alpha}$-galactosidic linkage. Owing to its substrate preference and noteworthy stability, ${\alpha}$-Gal1 is of particular interest for possible biotechnological applications involving the processing of plant materials.

• 산업경영시스템학회지
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• 제40권4호
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• pp.96-104
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• 2017

A one-shot system (device) refers to a system that is stored for a long period of time and is then disposed of after a single mission because it is accompanied by a chemical reaction or physical destruction when it operates, such as shells, munitions in a defense weapon system and automobile airbags. Because these systems are primarily related with safety and life, it is required to maintain a high level of storage reliability. Storage reliability is the probability that the system will operate at a particular point in time after storage. Since the stored one-shot system can be confirmed only through inspection, periodic inspection and maintenance should be performed to maintain a high level of storage reliability. Since the one-shot system is characterized by a large loss in the event of a failure, it is necessary to determine an appropriate inspection period to maintain the storage reliability above the reliability goal. In this study, we propose an optimal inspection policy that minimizes the total cost while exceeding the reliability goal that the storage reliability is set in advance for the one-shot system in which periodic inspections are performed. We assume that the failure time is the Weibull distribution. And the cost model is presented considering the existing storage reliability model by Martinez and Kim et al. The cost components to be included in the cost model are the cost of inspection $c_1$, the cost of loss per unit time between failure and detection $c_2$, the cost of minimum repair of the detected breakdown of units $c_3$, and the overhaul cost $c_4$ of $R_s{\leq}R_g$. And in this paper, we will determine the optimal inspection policy to find the inspection period and number of tests that minimize the expected cost per unit time from the finite lifetime to the overhaul. Compare them through numerical examples.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2008년도 춘계 학술발표회 제20권1호
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• pp.189-192
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• 2008

콘크리트 교량에서 수행되는 기존 점검방법은 점검자가 현장에서 교량의 외관상태를 기록한 다음 내업을 통해서 수작업으로 외관조사망도를 작성하는 과정으로 진행된다. 하지만, 열악한 현장작업 여건으로 인해 획득되는 데이터는 객관성과 신뢰도가 떨어진다는 문제점이 있다. 본 연구에서는 이러한 문제점을 개선하기 위하여 외관조사결과를 자동으로 추출하는 이미지 처리 프로그램을 개발하였다. 이 프로그램은 교량으로부터 획득한 디지털 이미지를 처리하고 분석하며, 결과의 입출력 및 관리하는 데까지의 모든 관련 프로그램을 통칭한다. 프로그램 개발을 위하여 디지털 이미지의 크기와 카메라 배율간의 관계 분석, 균열 분석 알고리즘 개발, 이미지의 해상도 및 정밀도 분석 등의 연구가 수행되었다. 최초 계획에서는 이미지 처리를 통하여 균열망도를 자동으로 구현하도록 설계하였지만, 데이터의 용량과 이미지 처리의 기술적인 한계 그리고 콘크리트 표면의 여러 가지 조건에 등에 따라 결과의 신뢰도가 많이 차이가 난다는 것을 확인하였다. 따라서 결과를 정확하게 추출하기 위하여 자동판독 프로그램을 근간으로 하면서 사용자에 의해 수정작업이 가능하도록 프로그램을 보완하였다.

• Corrosion Science and Technology
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• 제7권4호
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• pp.208-211
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• 2008

Safety operation of main pipelines is primarily provided by anticorrosive monitoring. Anticorrosive monitoring of oil pipeline transportation objects is based on results of complex corrosion inspections, analysis of basic data including design data, definition of a corrosion residual rate and diagnostic of general equipment's technical condition. All the abovementioned arrangements are regulated by normative documents. For diagnostics of corrosion-technical condition of oil pipeline transportation objects one presently uses different methods such as in-line inspection using devices with ultrasonic, magnetic or another detector, acoustic-emission diagnostics, electrometric survey, general external corrosion diagnostics and cameral processing of obtained data. Results of a complex of diagnostics give a possibility: $\cdot$ to arrange a pipeline's sectors according to a degree of corrosion danger; $\cdot$ to check up true condition of pipeline's metal; $\cdot$ to estimate technical condition and working ability of a system of anticorrosive protection. However such a control of corrosion technical condition of a main pipeline creates the appearance of estimation of a true degree of protection of an object if values of protective potential with resistive component are taken into consideration only. So in addition to corrosive technical diagnostics one must define a true residual corrosion rate taking into account protective action of electrochemical protection and true protection of a pipeline one must at times. Realized anticorrosive monitoring enables to take a reasonable decision about further operation of objects according to objects' residual life, variation of operation parameters, repair and dismantlement of objects.

• 천문학논총
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• 제27권3호
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• pp.39-47
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• 2012

MIRIS, Multi-purpose Infra-Red Imaging System, is the main payload of STSAT-3 (Korea Science & Technology Satellite 3), which will be launched in the end of 2012 (the exact date to be determined) by a Russian Dnepr rocket. MIRIS consists of two camera systems, SOC (Space Observation Camera) and EOC (Earth Observation Camera). During a shock test for the flight model stability in the launching environment, some lenses of SOC EQM (Engineering Qualification Model) were broken. In order to resolve the lens failure, analyses for cause were performed with visual inspections for lenses and opto-mechanical parts. After modifications of SOC opto-mechanical parts, the shock test was performed again and passed. In this paper, we introduce the solution for lens safety and report the test results.

• 한국화재소방학회:학술대회논문집
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• 한국화재소방학회 2009년도 춘계학술논문발표회 논문집
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• pp.255-263
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• 2009

건축물 실내에서의 화재발생 시 초기 소화설비로 시설하고 있는 옥내소화전은 초기화재 진압용으로 큰 역할을 담당하고 있다. 현재 시설되어 있는 옥내소화전 시설이 국가화재안전기준(NFSC)에서 규정하고 있는 일정 방수압을 유지하여야 화재발생 시 소화설비로서 그 기능을 발휘할 수 있다. 대부분의 건축물에 설치되어 있는 옥내소화전의 방수압을 실측하여 본 결과 건물내에 설치된 소화전의 방수압이 국가화재안전기준에서 제시하는 기준치 보다 높게 나타나고 있었다. 이는 매우 바람직한 현상으로 정기적인 소방검사에 따른 소방시설 유지관리의 결과로 보여진다. 앞으로도 소방시설물에 대한 TAB를 통하여 화재진압시설의 정기적이고, 지속적인 안전관리가 이루어 져야 할 것이다.

• Smart Structures and Systems
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• 제29권1호
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• pp.251-266
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• 2022

Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

• Smart Structures and Systems
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• 제29권1호
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• pp.237-250
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• 2022

Structural health monitoring (SHM) plays an important role in ensuring the safety and functionality of critical civil infrastructure. In recent years, numerous researchers have conducted studies to develop computer vision and machine learning techniques for SHM purposes, offering the potential to reduce the laborious nature and improve the effectiveness of field inspections. However, high-quality vision data from various types of damaged structures is relatively difficult to obtain, because of the rare occurrence of damaged structures. The lack of data is particularly acute for fatigue crack in steel bridge girder. As a result, the lack of data for training purposes is one of the main issues that hinders wider application of these powerful techniques for SHM. To address this problem, the use of synthetic data is proposed in this article to augment real-world datasets used for training neural networks that can identify fatigue cracks in steel structures. First, random textures representing the surface of steel structures with fatigue cracks are created and mapped onto a 3D graphics model. Subsequently, this model is used to generate synthetic images for various lighting conditions and camera angles. A fully convolutional network is then trained for two cases: (1) using only real-word data, and (2) using both synthetic and real-word data. By employing synthetic data augmentation in the training process, the crack identification performance of the neural network for the test dataset is seen to improve from 35% to 40% and 49% to 62% for intersection over union (IoU) and precision, respectively, demonstrating the efficacy of the proposed approach.

• 한국방재안전학회논문집
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• 제15권3호
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• pp.1-14
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• 2022

최근 기후변화와 하천 제방의 노후화로 인해 수재해 위험이 가중되고 있으나 기존의 재래적인 하천 제방의 점검은 많은 인력과 예산 소모로 많은 한계점들이 존재하다. 이에 따라 효과적인 홍수 대응을 위해 새로운 모니터링과 예/경보 시스템 구축이 필요한 상황이다. 본 연구는 인공위성(Sentinel-1)을 이용한 하천 제방 변위 산출, 수문학적 요인과의 관계 분석 항목들을 결합한 하천 제방 건강상태 모니터링 방법을 제안한다. 본 연구에서 산정한 변동성 지수를 계산하여 4등급으로 구분하였고, 토양 수분의 급증한 결과를 토대로 제방 붕괴 구간이 변동성이 급증한 취약지점 상태로 판단하였다. 향후에는 원격 기술과 분석 항목들을 결합한 포렌식 기법을 통해 기존 제방관리 시스템의 고도화가 가능할 것으로 기대한다.