• Proceedings of the KSR Conference
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• 2007.11a
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• pp.913-916
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• 2007

In this paper, the possibility of time reversal phenomenon was investigated in damage detection of structure. In conventional lamb wave techniques, damage is identified by comparing the measured data (baseline signals) and the current data. But this method can lead to high false signal in the intact condition of structures due to environmental conditions of the structures. So in this studying, we investigate the possibility of damage detection in the aluminum plate using the time reversal phenomenon of lamb waves.

• Spatial Information Research
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• v.10 no.4
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• pp.493-499
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• 2002

This paper presents the disaster control due to flooding through the case study of Samwhadong, Donghae city, Kangwondo, broken out at 31, August 2002. In order to assess the characteristics of flood damage one must consider social and geological conditions, the factors of flood risk were derived based on GIS. For reduction of flood damage, flood hazard map was prepared for local residents. These information will support refuge activities, it would aid the reduction of flood damage.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.4
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• pp.621-625
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• 2018

This paper proposes a method for bridge damage factor recognition from inspection reports using deep learning. Bridge inspection reports contains inspection results including identified damages and causal analysis results. However, collecting such information from inspection reports manually is limited due to their considerable amount. Therefore, this paper proposes a model for recognizing bridge damage factor from inspection reports applying Named Entity Recognition (NER) using deep learning. Named Entity Recognition, Word Embedding, Recurrent Neural Network, one of deep learning methods, were applied to construct the proposed model. Experimental results showed that the proposed model has abilities to 1) recognize damage and damage factor included in a training data, 2) distinguish a specific word as a damage or a damage factor, depending on its context, and 3) recognize new damage words not included in a training data.

• Journal of Environmental Science International
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• v.29 no.4
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• pp.395-402
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• 2020

This study was conducted to analyze seasonal variations of de-icing salt ions harvested from soils and plants according to salt damage of Pinus densiflora f. multicaulis, a evergreen conifer, on roadsides. Pinus densiflora f. multicaulis was divided into three groups referred to SD, ND, and WD (serious salt damage (SD) = 71-100%, normal salt damage (ND) = 31-70%, and weak salt damage (WD) = 0-30%) based on the degree of visible foliage damage, and measured acidity (pH), electrical conductivity(EC), and de-icing salt ions (K⁺, Ca²⁺, Na⁺, and Mg²⁺) harvested from soils and plants. The results indicated that acidity, electrical conductivity, and de-icing salt ions of soils and plants were significantly affected by seasonal variation and salt damage. In addition, a strong positive liner relationship was observed in plants between the concentration of de-icing salts and salt damage in spring, while the relationship among seasonal variation and salt damage in soil were not significant. The results from this study has important implications for the management of conifer species in relation to salinity and roadsides maintenance.

• Proceedings of the Korean Society of Toxicology Conference
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• 2006.11a
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• pp.55-64
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• 2006

The fetal central nervous system (CNS) is sensitive to diverse environmental factors, such as alcohol, heavy metals, irradiation, mycotoxins, neurotransmitters, and DNA damage, because a large number of processes occur during an extended period of development. Fetal neural damage is an important issue affecting the completion of normal CNS development. As many concepts about the brain development have been recently revealed, it is necessary to compare the mechanism of developmental abnormalities induced by extrinsic factors with the normal brain development. To clarify the mechanism of fetal CNS damage, we used one experimental model in which 5-azacytidine (5AZC), a DNA damaging and demethylating agent, was injected to the dams of rodents to damage the fetal brain. 5AzC induced cell death (apoptosis)and cell cycle arrest in the fetal brain, and it lead to microencephaly in the neonatal brain. We investigated the mechanism of apoptosis and cell cycle arrest in the neural progenitor cells in detail, and demonstrated that various cell cycle regulators were changed in response to DNA damage. p53, the guardian of genome, played a main role in these processes. Further, using DNA microarray analysis, tile signal cascades of cell cycle regulation were clearly shown. Our results indicate that neural progenitor cells have the potential to repair the DNA damages via cell cyclearrest and to exclude highly affected cells through the apoptotic process. If the stimulus and subsequent DNA damage are high, brain development proceeds abnormally and results in malformation in the neonatal brain. Although the mechanisms of fetal brain injury and features of brain malformation afterbirth have been well studied, the process between those stages is largely unknown. We hypothesized that the fetal CNS has the ability to repair itself post-injuring, and investigated the repair process after 5AZC-induced damage. Wefound that the damages were repaired by 60 h after the treatment and developmental processes continued. During the repair process, amoeboid microglial cells infiltrated in the brain tissue, some of which ingested apoptotic cells. The expressions of genes categorized to glial cells, inflammation, extracellular matrix, glycolysis, and neurogenesis were upregulated in the DNA microarray analysis. We show here that the developing brain has a capacity to repair the damage induced by the extrinsic stresses, including changing the expression of numerous genes and the induction of microglia to aid the repair process.

• Journal of Environmental Science International
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• v.23 no.8
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• pp.1455-1462
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• 2014

The purpose of this study is to examine green consumer behavior (green product purchasing behavior and green consumption life) affected by demographical characteristics, and cognition degree of green life (cognition of a green indicator, a green life catalyst system, and environmental problems). It's also to promote strategy and suggest effective activation plans for the vitalization of green consumer behavior. To carry out the task, verification of credibility, multiple regression analysis, two-step cluster analysis, and multinomial logistic analysis were used. The results are as follows: First, the factors that effect green product purchasing behavior were gender, age, cognitive of a green indicator, carbon points system, electricity peak hour system, and seriousness of environmental damage due to lifestyle. Second, the factors that effect green lifestyle were gender, age, carbon grade indicator system, cognition of a green system, and the seriousness of environmental damage due to lifestyle. Third, the comparative group characteristic analysis showed low rates for careless green consumer behavior groups compared to the passive green consumer behavior groups in cognition of a green indicator, green system, and environmental problems. For active green consumer behavior groups, the analysis showed high rates in cognition of carbon grades, eco-labeling, electricity peak hour system, and environmental damage due to lifestyle. In order to encourage green consumer behavior, it's evident that cognition of a green indicator, a green life catalyst system, and environmental problems need to be improved through strategic education and continuous encouragement.

• Structural Monitoring and Maintenance
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• v.4 no.2
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• pp.133-151
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• 2017

The paper describes the results of an experimental and numerical investigation into the structural and damage response of sandwich composites to low-velocity impact. Sandwich panels consisting of laminated composite skins with three different layups bonded to a PVC foam core were subjected to impact at various energy levels corresponding to barely visible impact damage (BVID) in the impacted skins. Damage assessment analyses were performed on the impacted panels to characterise the extent and the nature of the major failure mechanisms occurring in the skins. The data collected during the experimental analyses were finally used to assess the predictive capabilities of an FE tool recently developed by the authors for detailed simulation of impact damage in composite sandwich panels. Good agreement was observed between experimental results and model predictions in terms of structural response to impact, global extent of damage and typical features of individual damage mechanisms.

• Structural Engineering and Mechanics
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• v.54 no.2
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• pp.221-237
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• 2015

An integrated method is proposed for structural nonlinear damage detection based on time series analysis and the higher statistical moments of structural responses in this study. It combines the time series analysis, the higher statistical moments of AR model residual errors and the fuzzy c-means (FCM) clustering techniques. A few comprehensive damage indexes are developed in the arithmetic and geometric mean of the higher statistical moments, and are classified by using the FCM clustering method to achieve nonlinear damage detection. A series of the measured response data, downloaded from the web site of the Los Alamos National Laboratory (LANL) USA, from a three-storey building structure considering the environmental variety as well as different nonlinear damage cases, are analyzed and used to assess the performance of the new nonlinear damage detection method. The effectiveness and robustness of the new proposed method are finally analyzed and concluded.

• BMB Reports
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• v.34 no.6
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• pp.489-495
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• 2001

DNA damage by UV and environmental agents are the major cause of genomic instability that needs to be repaired, otherwise it give rise to cancer. Accordingly, mammalian cells operate several DNA repair pathways that are not only responsible for identifying various types of DNA damage but also involved in removing DNA damage. In mammals, nucleotide excision repair (NER) machinery is responsible for most, if not all, of the bulky adducts caused by UV and chemical agents. Although most of the proteins involved in NER pathway have been identified, only recently have we begun to gain some insight into the mechanism by which proteins recognize damaged DNA. Binding of Xeroderma pigmentosum group C protein (XPC)-hHR23B complex to damaged DNA is the initial damage recognition step in NER, which leads to the recruitment of XPA and RPA to form a damage recognition complex. Formation of damage recognition complex not only stabilizes low affinity binding of XPA to the damaged DNA, but also induces structural distortion, both of which are likely necessary for the recruitment of TFIIH and two structure-specific endonucleases for dual incision.

• Structural Engineering and Mechanics
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• v.8 no.3
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• pp.285-297
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• 1999

A method is presented to find the location and magnitude of damage in a structure using data from dynamic tests. The test data include a combination of natural frequency measurements, taken before and after the occurrence of damage, and response measurements taken after damage. An algorithm is developed to identify localized increases in the flexibility of the structural members. Increases in flexibility are attributed to damage. The algorithm uses the sensitivity of the flexibility matrix to changes in the natural frequencies of the structure to identify the damage. A set of under determined equations is solved using an objective function which is derived from measurements of the system moments. Damage ranging from 10 to 60% increase in the flexibility of a member was successfully identified in a 50 d.o.f. structure, using a small number of natural frequency and velocity measurements.