• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.6
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• pp.119-126
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• 2015

The wall system has been also tending to shift from existing concrete wall to variable lightweight wall according to increasing use of column structure system in apartment construction. Therefore, wall needs certain amount of strength which also means the standard measurement of resistance against loading of wall attachments is needed. Nevertheless, there currently aren't enough researches of related standards for such measurement. For such reason, the research would be used as baseline data to development for test methods of load resistance about attachments on the lightweight wall, that presented improvements in the apparatus and maximum loads for domestic circumstances by researching current tests.

• Smart Structures and Systems
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• v.31 no.4
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• pp.325-334
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• 2023

Computer vision-based damage detection enables non-contact, efficient and low-cost bridge health monitoring, which reduces the need for labor-intensive manual inspection or that for a large number of on-site sensing instruments. By leveraging recent semantic segmentation approaches, we can detect regions of critical structural components and identify damages at pixel level on images. However, existing methods perform poorly when detecting small and thin damages (e.g., cracks); the problem is exacerbated by imbalanced samples. To this end, we incorporate domain knowledge to introduce a hierarchical semantic segmentation framework that imposes a hierarchical semantic relationship between component categories and damage types. For instance, certain types of concrete cracks are only present on bridge columns, and therefore the noncolumn region may be masked out when detecting such damages. In this way, the damage detection model focuses on extracting features from relevant structural components and avoid those from irrelevant regions. We also utilize multi-scale augmentation to preserve contextual information of each image, without losing the ability to handle small and/or thin damages. In addition, our framework employs an importance sampling, where images with rare components are sampled more often, to address sample imbalance. We evaluated our framework on a public synthetic dataset that consists of 2,000 railway bridges. Our framework achieves a 0.836 mean intersection over union (IoU) for structural component segmentation and a 0.483 mean IoU for damage segmentation. Our results have in total 5% and 18% improvements for the structural component segmentation and damage segmentation tasks, respectively, compared to the best-performing baseline model.

• Smart Structures and Systems
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• v.31 no.4
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• pp.335-349
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• 2023

Bridges constantly undergo deterioration and damage, the most common ones being concrete damage and exposed rebar. Periodic inspection of bridges to identify damages can aid in their quick remediation. Likewise, identifying components can provide context for damage assessment and help gauge a bridge's state of interaction with its surroundings. Current inspection techniques rely on manual site visits, which can be time-consuming and costly. More recently, robotic inspection assisted by autonomous data analytics based on Computer Vision (CV) and Artificial Intelligence (AI) has been viewed as a suitable alternative to manual inspection because of its efficiency and accuracy. To aid research in this avenue, this study performs a comparative assessment of different architectures, loss functions, and ensembling strategies for the autonomous segmentation of bridge components and damages. The experiments lead to several interesting discoveries. Nested Reg-UNet architecture is found to outperform five other state-of-the-art architectures in both damage and component segmentation tasks. The architecture is built by combining a Nested UNet style dense configuration with a pretrained RegNet encoder. In terms of the mean Intersection over Union (mIoU) metric, the Nested Reg-UNet architecture provides an improvement of 2.86% on the damage segmentation task and 1.66% on the component segmentation task compared to the state-of-the-art UNet architecture. Furthermore, it is demonstrated that incorporating the Lovasz-Softmax loss function to counter class imbalance can boost performance by 3.44% in the component segmentation task over the most employed alternative, weighted Cross Entropy (wCE). Finally, weighted softmax ensembling is found to be quite effective when used synchronously with the Nested Reg-UNet architecture by providing mIoU improvement of 0.74% in the component segmentation task and 1.14% in the damage segmentation task over a single-architecture baseline. Overall, the best mIoU of 92.50% for the component segmentation task and 84.19% for the damage segmentation task validate the feasibility of these techniques for autonomous bridge component and damage segmentation using RGB images.

• Journal of the Korea Concrete Institute
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• v.25 no.3
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• pp.321-329
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• 2013

Recently, the medium-low level radioactive waste from nuclear power plant must be transported from temporary storage to the final repository. Medium-low level radioactive waste, which is composed mainly of the liquid ion exchange resin, has been consolidated with cementitious material in the plastic or iron container. Since cementitious material is brittle, it would generate cracks by impact load during transportation, signifying leakage of radioactive ray. In order to design the safety transporting equipment, there is a need to check the compressive strength of the current waste. However, because it is impossible to measure strength by direct method due to leakage of radioactive ray, we will estimate the strength indirectly by the dynamic modulus of elasticity. Therefore, it must be identified the relationship between of strength and dynamic modulus of elasticity. According to the waste acceptance criteria, the compressive strength of cement based solid is defined as more than 3.44 MPa (500 psi). Compressive strength of the present solid is likely to be significantly higher than this baseline because of continuous hydration of cement during long period. On this background, we have tried to produce the specimens of the 28 day's compressive strength of 3 to 30 MPa having the same material composition as the solid product for the medium-low level radioactive waste, and analyze the relationship between the strength and the dynamic modulus of elasticity. By controling the addition rates of AE agent, we made the mixture containing the ion exchange resin and showing the target compressive strength (3~30 MPa). The dynamic modulus of elasticity of this mixtures is 4.1~10.2 GPa, about 20 GPa lower in the equivalent compressive strength level than that of ordinary concrete, and increasing the discrepancy according to increase strength. The compressive strength and the dynamic modulus of elasticity show the liner relationship.

• Journal of the Korean GEO-environmental Society
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• v.13 no.2
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• pp.5-17
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• 2012

The amount of snow due to global warming and climate change has recently increased. The effective management of snow removal materials will be required. First, on the basis of domestic winter temperature, it is not necessary to get a baseline to less than the freezing point of $-52^{\circ}C$ for the calcium chloride($CaCl_2$) of 30%.. In terms of cost comparison between calcium chloride($CaCl_2$) and sodium chloride($NaCl$), the calcium chloride($CaCl_2$) is 2 to 3 times more expensive, and the supply of the calcium chloride($CaCl_2$) is not produced in domestic country and is in the conditions that have to imports all needed. Accordingly, the effective use scheme of snow removal materials should be considered to multifaceted ways. Thus, the objective of this study is to develop effective method and to replace from calcium choride($CaCl_2$) to sodium chloride($NaCl$) solution in the current snow removal operating system that uses a pre-wetted salt spreading method. The effective method that equals to the quality of the existing snow removal materials was developed in this study through performance tests for deicing chemicals, corrosion test of steel and freezing and thawing tests of concrete.

• The Journal of Society for e-Business Studies
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• v.16 no.4
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• pp.33-51
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• 2011

This research derived the influencing factors for employees' compliance with the information security policy in organizations on the basis of Neutralization Theory, Theory of Planned Behavior and Protection Motivation Theory. To empirically analyze the research model and the hypotheses, data were collected by conducting web survey, 194 of 207 questionnaires were available. The test of causal model was conducted by PLS. Reliability, validity and model fit were found to be statistically significant. the results of hypotheses tests showed that seven ones of eight hypotheses could be accepted. The theoretical implications of this study are as follows : 1) this study is expected to play a role of baseline for future research about employee compliance with the information security policy, 2) this study attempted interdisciplinary approach through combining psychology and information system security research, and 3) it suggested concrete operational definitions of influencing factors for information security policy compliance through comprehensive theoretical review. Also, this study has some practical implications. First, it can provide the guideline to support the successful execution of the strategic establishment for implement of information system security policies in organizations. Second, it is proved that the need for conducting education and training program suppressing employees. neutralization psychology to violate information security policy should be emphasized in the organizations.

• Journal of agriculture & life science
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• v.52 no.6
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• pp.163-173
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• 2018

This study was carried out to propose the baseline data for in situ conservation by analyzing environmental and growth characteristics in Pedicularis hallaisanenesis habitats. P. hallaisanensis habitats, according to investigations, were located on the slope of southwest at an elevation of 1,400 m in Mt. Gayasan and on the slope of southeast at an elevation of 1,500 m in Mt. Hallasan. Pedicularishallaisanensis habitats. Also, habitats were found at the grassland with no upper vegetation. In the study sites, soil pH and soil organic matter were 4.9-6.5 and 4.4-8.1%, respectively. A total of 55 vascular plants taxa were identified in ten quadrats in two habitats, of which 25 were inhabited in Mt. Gayasan and 37 in Mt. Hallasan. Current status of P. hallaisanensis habitats were very vulnerable with the pressure of the vegetation constantly threatening the species' survival. Thus, concrete conservation plans including diverse factors as light intensity, temperature and genetic analysis to protect natural habitats should be set up as soon as possible.