• Smart Structures and Systems
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• v.30 no.1
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• pp.17-34
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• 2022

For steel structures, fatigue cracks are critical damage induced by long-term cycle loading and distortion effects. Vision-based crack detection can be a solution to ensure structural integrity and performance by continuous monitoring and non-destructive assessment. A critical issue is to distinguish cracks from other features in captured images which possibly consist of complex backgrounds such as handwritings and marks, which were made to record crack patterns and lengths during periodic visual inspections. This study presents a parametric study on image-based crack identification for orthotropic steel bridge decks using captured images with complicated backgrounds. Firstly, a framework for vision-based crack segmentation using the atrous convolution-based Deeplapv3+ network (ACDN) is designed. Secondly, features on crack images are labeled to build three databanks by consideration of objects in the backgrounds. Thirdly, evaluation metrics computed from the trained ACDN models are utilized to evaluate the effects of obstacles on crack detection results. Finally, various training parameters, including image sizes, hyper-parameters, and the number of training images, are optimized for the ACDN model of crack detection. The result demonstrated that fatigue cracks could be identified by the trained ACDN models, and the accuracy of the crack-detection result was improved by optimizing the training parameters. It enables the applicability of the vision-based technique for early detecting tiny fatigue cracks in steel structures.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.532-548
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• 2021

Nuclear power plants contain several monitoring systems that can identify the in-vessel phenomena of a severe accident (SA). Though a lot of analysis and research is carried out on SA, right from the development of the nuclear industry, not all the possible circumstances are taken into consideration. Therefore, to improve the efficacy of the safety of nuclear power plants, additional analytical studies are needed that can directly monitor severe accident phenomena. This paper presents an interacting multiple model (IMM) based fault detection and diagnosis (FDD) approach for the identification of in-vessel phenomena to provide the accident propagation information using reactor vessel (RV) out-wall temperature distribution during severe accidents in a nuclear power plant. The estimation of wall temperature is treated as a state estimation problem where the time-varying wall temperature is estimated using IMM employing three multiple models for temperature evolution. From the estimated RV out-wall temperature and rate of temperature, the in-vessel phenomena are identified such as core meltdown, corium relocation, reactor vessel damage, reflooding, etc. We tested the proposed method with five different types of SA scenarios and the results show that the proposed method has estimated the outer wall temperature with good accuracy.

• Mass Spectrometry Letters
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• v.13 no.4
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• pp.95-105
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• 2022

Amatoxin-induced mushroom poisoning starts with nonspecific symptoms of toxicity but hepatic damage may follow, resulting in the rapid development of liver insufficiency and, ultimately, coma and death. Accurate detection of amatoxins, such as α-, β-, and γ-amanitin, within the first few hours after presentation is necessary to improve the therapeutic outcomes of patients. Therefore, analytical methods for the identification and quantification of α-, β-, and γ-amanitin in biological samples are necessary for clinical and forensic toxicology. This study presents a literature review of the analytical techniques available for amatoxin detection in biological matrices, and established an inventory of liquid chromatography (LC) techniques with mass spectrometry (MS), ultraviolet (UV) detection, and electrochemical detection (ECD). LC-MS methods using quadrupole tandem mass spectrometry, time-of-flight mass spectrometry, and orbitrap MS are powerful analytical techniques for the identification and determination of amatoxins in plasma, urine, serum, and tissue samples, with high sensitivity, specificity, and reproducibility compared to LC with UV and ECD, enzyme-linked immunoassay, and capillary electrophoresis methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.353-362
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• 2023

Messenger phishing, communications frauds crime, exploits remote control of smartphones and non-face-to-face financial transactions, causing property damage due to money transfers, as well as account opening and loans in the name of victims. Such financial accidents may be careless of victims, but the current messenger phishing criminal method is intelligent and can be seen as digging into loopholes in the non-face-to-face user verification process. In this paper we analyze how messenger phishing uses loopholes in user identification procedures in non-face-to-face financial transactions. Through experiments, it is suggested to improve the non-face-to-face verification process for safer financial transactions.

• Steel and Composite Structures
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• v.53 no.1
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• pp.45-59
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• 2024

This paper aims to investigate the impact of interfacial debonding on modal dynamic properties such as frequencies and vibration mode shapes. Furthermore, it seeks to identify the specific locations of debonding in rectangular concrete-filled steel tubular (CFST) columns during the subsequent stage of the study. In this study, debonding is defined as a reduction in the elasticity modulus of concrete by a depth of 3 mm at the connection point with the steel tube. Debonding leads to a lack of correlation between primary and secondary shapes of vibration modes and causes a reduction in the natural frequency in all modes. However, directly comparing changes in vibration responses does not allow for the identification of debonding locations. In this study, a novel irregularity detection index (IDI) is proposed based on modal signal processing via the 2D wavelet transform. The suggested index effectively reveals relative irregularity peaks in the form of elevations at the debonding locations. As the severity of damage increases at a specific debonding location, the relative irregularity peaks would increase only at that specific point; in other words, the detection or non-detection of a debonding location using IDI has minimal effects on the identification of other debonding locations.

• Computers and Concrete
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• v.15 no.5
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• pp.771-794
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• 2015

This paper proposes an innovative method for selection of measurement sets in static parameter identification of concrete or steel bridges. This method is proved as a systematic tool to address the first steps of Structural System Identification procedures by observability techniques: the selection of adequate measurement sets. The observability trees show graphically how the unknown estimates are successively calculated throughout the recursive process of the observability analysis. The observability trees can be proved as an intuitive and powerful tool for measurement selection in beam bridges that can also be applied in complex structures, such as cable-stayed bridges. Nevertheless, in these structures, the strong link among structural parameters advises to assume a set of simplifications to increase the tree intuitiveness. In addition, a set of guidelines are provided to facilitate the representation of the observability trees in this kind of structures. These guidelines are applied in bridges of growing complexity to explain how the characteristics of the geometry of the structure (e.g. deck inclination, type of pylon-deck connection, or the existence of stay cables) affect the observability trees. The importance of the observability trees is justified by a statistical analysis of measurement sets randomly selected. This study shows that, in the analyzed structure, the probability of selecting an adequate measurement set with a minimum number of measurements at random is practically negligible. Furthermore, even bigger measurement sets might not provide adequate SSI of the unknown parameters. Finally, to show the potential of the observability trees, a large-scale concrete cable-stayed bridge is also analyzed. The comparison with the number of measurements required in the literature shows again the advantages of using the proposed method.

• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.201-208
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• 2009

As the ubiquitous environment is created, the latest ports introduce U-Port services in managing ports generally and embody container's location identification system, port terminal management system, and advanced information exchange system etc. In particular, the location identification system for freight cars and containers provide in real time the information on the location and condition for them, and enables them to cope with an efficient vehicle operation management and its related problems immediately. However, such a system is insufficient in effectively handling with the troubles in a large-scale port including freight car's disorderly driving, parking, stop, theft, damage, accident, trespassing and controlling. In order to solve these problems, this study structures the vehicle positioning system and the image verification system unsing high resolution image compression and AVE/H.264 store and transmission technology, able to mark and identify the vehicle location on the digital map while a freight car has stayed in a port since the entry of an automatic gate, or able to identify the place of accident through image remotely.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.3
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• pp.193-199
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• 2020

This study examines a method for identifying stiffness reductions in structures subjected to seismic loads and retrofitting effects using a combination of the finite element method and an advanced genetic algorithm. The novelty of this study is the application of seismic loading and its response to anomalies in the tested structure. The technique described in this study may enable not only detection of damaged elements but also the identification of their locations and the extent of damage due to seismic loading. To demonstrate the feasibility of the method, the advanced genetic algorithm is applied to frame and truss bridge structures subjected to El Centro and Pohang seismic loads. The results reveal the excellent computational efficiency of the method and its ability to prevent severe damage from earthquakes.

• Microbiology and Biotechnology Letters
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• v.41 no.2
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• pp.249-252
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• 2013

The Bacillus KU801 strain, due to its potential in the field of probiotics for animal use, was isolated from chicken feces. Strain KU801 was identified as Bacillus amyloliquefaciens KU801 based on the results of 16S rRNA sequencing. Vegetative and spore cells of B. amyloliquefaciens KU801 were resistant to artificial gastric juice and artificial bile acid. B. amyloliquefaciens KU801 was found to inhibit the production of nitric oxide (NO) and increase the production of Interleukin-1 alpha (IL-1${\alpha}$). DNA damage induced by N-methyl-Ntion of ninitroso-guanidine (MNNG) was significantly inhibited, in a dose dependent manner, by preincubating MNNG together with B. amyloliquefaciens KU801. These results demonstrate the potential use of B. amyloliquefaciens KU801 as a feed additive.

• Smart Structures and Systems
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• v.16 no.3
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• pp.415-433
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• 2015

Tendon failures in bonded post-tensioned bridges over the last two decades have motivated ongoing investigations on various aspects of unbonded tendons and their monitoring methods. Recent research shows that change of strain distribution in anchor heads can be useful in detecting wire breakage in unbonded construction. Based on this strain variation, this paper develops a damage detection model that enables an automated tendon monitoring system to identify and locate wire breaks. The first part of this paper presents an experimental program conducted to study the strain variation in anchor heads by generating wire breaks using a mechanical device. The program comprised three sets of tests with fully populated 19-strand anchor head and evaluated the levels of strain variation with number of wire breaks in different strands. The sensitivity of strain variation with wire breaks in circumferential and radial directions of anchor head in addition to the axial direction (parallel to the strand) were investigated and the measured axial strains were found to be the most sensitive. The second part of the paper focuses on formulating the wire breakage detection framework. A finite element model of the anchorage assembly was created to demonstrate the algorithm as well as to investigate the asymmetric strain distribution observed in experimental results. In addition, as almost inevitably encountered during tendon stressing, the effects of differential wedge seating on the proposed model have been analyzed. A sensitivity analysis has been performed at the end to assess the robustness of the model with random measurement errors.