• Journal of the Korean Recycled Construction Resources Institute
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• v.4 no.1
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• pp.76-81
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• 2016

Recycled aggregate is a valuable resource in Korea in lack of natural aggregate. Government recognizes the importance and suggests various policies enhancing its use for higher value-added application. Most of recycled aggregate produced currently in Korea, however, is applied for low value-added uses such as embankment, reclamation, etc. Its higher valued application such as for structural concrete is very limited. Although domestic manufacturing technology of recycled aggregate is at the world level, recycled aggregate is not applied for structural concrete. Primary reasons for the limited use of the recycled aggregate include bonded mortar and cracks occurred during crushing and hence it is very difficult to predict and control the quality of recycled aggregate concrete. This research intended to grasp combined characteristics of recycled aggregate, high early strength cement, maximum temperature and time duration of steam curing and then, analyze the effects of factors. Also, it suggested the method to improve field applicability of recycled aggregate concrete.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.4
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• pp.10-17
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• 2015

In this paper, to evaluate and verify safety and performance of new-concept lining board, the experiments and analyses were performed. From the flexural tests, it was noted that the failure occurred at the load of 664kN. At structural analyses based on test results, when the loadings are the unit load 100kN and failure load 664kN, the maximum displacements at the middle part of lining board were 2.58mm and 27.01mm, respectively. In addition, at the elastic range and the plastic range, their load carrying capacities were evaluated as DB-34 and DB-41, respectively. Accordingly, it can be concluded that, since the lining board developed in this study satisfy the design load and structural safety, it supplemented its disadvantages and can apply to construction site.

• Journal of the Korean Geographical Society
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• v.48 no.3
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• pp.348-365
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• 2013

This paper aims to examine the complexities of the state-nature relations in Korea by emphasizing the complex processes of interactions between the state and nature. In doing so, it relies on the literature of "political ecology of state-nature" which problematizes the conventional modernist views on nature assuming the dualistic separation between the state and nature. First, we critically review the existing Korean literature on the state-nature relation (e.g., the ecologism, the metabolic rift theory, the social construction of the nature, the green state thesis, etc.) and argue that these studies significantly lack the recognition of the interactions between the state and nature. Second, we discuss the possibilities of seeing the state-nature relations from the perspective of political ecology as an alternative approach to the state-nature relation. Last, we conclude that the political ecology approach to the state-nature can deepen our understandings of the Korean capitalist development.

• Journal of Korean Society of Steel Construction
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• v.18 no.2
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• pp.137-146
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• 2006

In this paper, a numerical study on the evaluation of the redundancy according to the dimension and spacing of cross beams in the composite twin steel plate girder bridges that are generally recognized as a non-redundant load path structures, has been performed. Specifically, a two-lane three-span continuous (40+50+40m) bridge with I-section cross beams which serve as cross bracing, and without a lateral bracing were considered. The material and geometric nonlinear analyses were conducted to evaluate the ultimate loading capacity of the intact and damaged bridge in which one of the two girders is seriously fractured. Through the numerical analyses, it was recognized that there is little difference in redundancy according to the variation of the dimension and spacing of the cross beams for both intact and damaged bridges.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.2
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• pp.1-8
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• 2011

Concrete filled steel tubes(CFST) is considered as a column having better structural stability and better performance of fire resistance than that made with H-section and hollow section in itself. To get the fire resistance of the CFST, two kinds of concrete strength were used, 21 MPa, 40 MPa and 4 sorts of the applied loads were calculated and used to the specimens such as 3.5 m long, round and rectangular section. After various fire tests under 4 sorts of load ratios, the fire resistance of the CFST is not possible to get over 1 hour because of the rapid decrease of concrete strength. The below 50% of the applied load is recommended to obtain over 1 hour fire resistance of the CFST.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.3
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• pp.55-65
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• 2019

Although crack on concrete exists from its early formation, crack requires attention as it affects stiffness of structure and can lead demolition of structure as it grows. Detecting cracks on concrete is needed to take action prior to performance degradation of structure, and deep learning can be utilized for it. In this study, transfer learning, one of the deep learning techniques, was used to detect the crack, as the amount of crack's image data was limited. Pre-trained Inception-v3 was applied as a base model for the transfer learning. Web scrapping was utilized to fetch images of concrete wall with or without crack from web. In the recognition of crack, image post-process including changing size or removing color were applied. In the visualization of crack, source images divided into 30px, 50px or 100px size were used as input data, and different numbers of input data per category were applied for each case. With the results of visualized crack image, false positive and false negative errors were examined. Highest accuracy for the recognizing crack was achieved when the source images were adjusted into 224px size under gray-scale. In visualization, the result using 50 data per category under 100px interval size showed the smallest error. With regard to the false positive error, the best result was obtained using 400 data per category, and regarding to the false negative error, the case using 50 data per category showed the best result.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.535-545
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• 2022

The purpose of this study is to classify the various problems in surface road according to their severity and to propose a priority decision making process for road policy makers. For this purpose, the road problems reported by Cheok-cheok app were classified, and the EPDO was adopted and calculated as an index of their severity. To test applicability of the proposed process, some images of road problems reported by the app were classified and annotated, and the Deep Learning was used for machine learning of the curated images, and then the other images of road problems were used for verification. The detecting success rate of the road problems with high severity such as road kills, obstacles in a lane, road surface cracks was over 90%, which shows the applicability of the proposed process. It is expected that the proposed process will make the app possible to be used in the filed to make a priority decision making by classifying the level of severity of the reported road problems automatically.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.985-993
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• 2006

The use of prefabricated concrete piles have been gradually increased in many construction sites. One of main works for building a concrete pile foundation is to crush a part of pile head which is compressed with more than $800kg/cm^2$. A pile cutting work is usually performed by a crusher and three to four skilled workers. Recent reports on the pile cutting work reveal that a lot of cracks which significantly reduce the strength of the pile and are frequently made during pile cutting operations and it is very repetitive and labor intensive work. To improve productivity, safety, and quality of the conventional concrete pile cutting work, the research on developing an automated concrete pile cutter has been performed. In this paper, sensing methods for detecting a pile cutting line are suggested with operation process algorithms. The suggested methods are very important to develop the automated pile cutter. A pilot-type of the automated pile cutter that adopt one of the suggested sensing methods, is developed and tested in a construction site.

• Korean journal of communication and information
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• v.72
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• pp.7-51
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• 2015

Job seeking for young adults after college in South Korea is much fierce and highly competitive. Many job seekers tend to experience despair, frustration, and insecurity in such a dire social situation. This study focuses on the job seeking experiences of younger generation people by closely examining the self-introduction letters. This work pays keen attention to the narrative strategies and portrayal of the applicants' self-described activities in these forms of letters through a detailed textual and cultural analysis. In doing so, this analysis attempts to contextualize the complex structures of feeling for the part of young job seekers as well as various social factors and pressures that influence on them.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.451-457
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• 2018

We propose an automatic detection and classification system of sewer damage database based on artificial intelligence and deep learning. In order to optimize the performance, we implemented a robust system against various environmental variations such as illumination and shadow changes. In our proposed system, a crack detection and damage classification method using a deep learning based Convolutional Neural Network (CNN) is implemented. For optimal results, 9,941 CCTV images with $256{\times}256$ pixel resolution were used for machine learning on the damaged area based on the CNN model. As a result, the recognition rate of 98.76% was obtained. Total of 646 images of $720{\times}480$ pixel resolution were extracted from various sewage DB for performance evaluation. Proposed system presents the optimal recognition rate for the automatic detection and classification of damage in the sewer DB constructed in various environments.