• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.1
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• pp.100-108
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• 2021

The purpose of this study is to analyze the reliability index of a design by applying the reduction factor of the recently developed fiber reinforced high strength concrete design guideline(draft). By collecting material and member test data performed for the development of the design guideline(draft), statistical characteristics of material strength and member strength analysis equations are obtained. A simul ation that appl ies the material statistical characteristics and the member anal ysis equation of the design guidel ine(draft) is performed, and the statistical characteristics of the section strength are calculated by combining the statistical characteristics of the analysis equation. Reliability analysis was performed by applying the load combination of the domestic highway bridge design code and concrete structural code, and it was confirmed that the design that applies the reduction factor for materials and members suggested in the design guideline(draft) satisfies the target reliability index.

• Journal of the Korean Geotechnical Society
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• v.38 no.12
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• pp.79-89
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• 2022

Every summer in our country, an accident occurs, in which the retaining wall on a steep slope collapses due to torrential rain. According to the data on the results of steep slope risk assessment in 2019, over 780 retaining walls are below grade C; therefore, preparing for countermeasures is urgent. However, due to the limited budget for the repair and reinforcement of these retaining walls, it is necessary to discuss the investment prioritization. In this study, a prioritization method was proposed at the network and project levels along with the review of the revised criteria of disaster risk assessment in the steep slope retaining wall, and an application research in the network level was conducted for six retaining walls. Moreover, it is proposed that the priority index was determined by using the actual cost for repair and reinforcement in determination of the project level prioritization.

• Composites Research
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• v.29 no.5
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• pp.299-305
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• 2016

This paper presents a method to detect the fiber property variation of laminated CFRP plates using the bivariate Gaussian distribution function. Five unknown parameters are considered to determine the fiber damage distribution, which is a modified form of the bivariate Gaussian distribution function. To solve the inverse problem using the combined computational method, this study uses several natural frequencies and mode shapes in a structure as the measured data. The numerical examples show that the proposed technique is a feasible and practical method which can prove the location of a damaged region as well as inspect the distribution of deteriorated stiffness of CFRP plates for different fiber angles and layup sequences.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2010.05a
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• pp.437-440
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• 2010

This paper represents a simple and effective calculation method to predict the orthotropic engineering constants for C/SiC woven fabric composite. The method, a quasi-analytical method using the modified equivalent laminated model, idealizes the woven fabric structure as a symmetric three-ply laminate to utilize a classical laminated plate theory. The required initial parameters are in-plane modulus from experiments and crimp ratio of the woven fabric. This study shows its feasibility by demonstrating example to calculate the engineering constants to thickness direction needed for three dimensional thermo-mechanical stress calculations.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.5
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• pp.179-186
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• 2006

In this study, Multi-Layer Perceptron(MLP) among models of Artificial Neural Network(ANN) is used for the development of a model that evaluates the bending capacities of reinforced concrete beams strengthened by FRP Rebar. And the data of the existing researches are used for materials of ANN model. As the independent variables of input layer, main components of bending capacities, width, effective depth, compressive strength, reinforcing ratio of FRP, balanced steel ratio of FRP are used. And the moment performance measured in the experiment is used as the dependent variable of output layer. The developed model of ANN could be applied by GFRP, CFRP and AFRP Rebar and the model is verified by using the documents of other previous researchers. As the result of the ANN model presumption, comparatively precise presumption values are achieved to presume its bending capacities at the model of ANN(0.05), while observing remarkable errors in the model of ANN(0.1). From the verification of the ANN model, it is identified that the presumption values comparatively correspond to the given data ones of the experiment. In addition, from the Sensitivity Analysis of evaluation variables of bending performance, effective depth has the highest influence, followed by steel ratio of FRP, balanced steel ratio, compressive strength and width in order.

• Journal of Digital Convergence
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• v.13 no.4
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• pp.81-87
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• 2015

This study will show the digital forensic model which fights against cyber-crimes to prepare various cyber-crimes. The digital forensic model will be more useful about the investigation of cyber-crimes and arresting criminals after researching the uses of the digital forensic model and cyber-crime rates in South Korea. This model conduct the standardized data with various languages by the language support system through the digital forensic analyzer. This model will send the data to law enforcement reviewing whether or not we ought to prove criminal charges. Moreover, law enforcement can access the file system to find out admissibility of evidence. And this model simplifies lawful investigation about additional investigation. The data, which is conducted and saved by the digital forensic system, will be helpful to protect against the future crimes because of the data.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.5-28
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• 2022

In this study, LD construction cases of overseas libraries were analyzed with focus on published datasets, reused vocabulary, and interlinked external datasets, and based on the analysis results, basic data on LD construction plans of domestic libraries were obtained. As a result of the analysis of 21 library cases, overseas libraries have established a faithful authority LD and conducted new services using published LDs. To this end, overseas libraries collaborated with other libraries and cultural institutions within the region, within the country, and nationally under the leadership of the library, and based on this cooperation, a specialized dataset was published. Overseas libraries used Schema.org to increase the visibility of published LDs, and used BIBFRAME for subdivision of description to define various entities and build LDs based on the defined entities. Overseas libraries have utilized various defined entities to link related information, display results, browse, and download in bulk. Overseas libraries were interested in the continuous up-to-date of interlinked external datasets, and directly utilized external data to reinforce catalog information. In this study, based on the derived implications, points to be considered when issuing LDs by domestic libraries were proposed. The research results can be used as basic data when future domestic libraries plan LD services or upgrade existing services.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.3
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• pp.253-263
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• 2008

Extension of IFC data model for steel bridge members is proposed to represent detailed design information. First of all, the design data items and their representation method are classified by analyzing primary references such as design specification, structural calculation documents and shop drawings. Some of the classified items are enough to be represented by the existing IFC model. However, the need of additional model is noted to systematically represent the design information for other items such as stiffener, diaphragm, joint system, and shear connector. An inheritance relations and properties for added model are also defined. The application program based on the proposed data model is developed. In the end, by loading the application program on the AutoCAD 2002 program, end-users can input the design information of steel bridge members. The applicability and efficiency of the proposed data model and the program are verified by checking the section area, intervals, and interferences.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.1-9
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• 2021

Deep learning in computer vision has made accelerated improvement over a short period but large-scale learning data and computing power are still essential that required time-consuming trial and error tasks are involved to derive an optimal network model. In this study, we propose a similar image classification performance improvement method based on CR (Confusion Rate) that considers only the characteristics of the data itself regardless of network optimization or data reinforcement. The proposed method is a technique that improves the performance of the deep learning model by calculating the CRs for images in a dataset with similar characteristics and reflecting it in the weight of the Loss Function. Also, the CR-based recognition method is advantageous for image identification with high similarity because it enables image recognition in consideration of similarity between classes. As a result of applying the proposed method to the Resnet18 model, it showed a performance improvement of 0.22% in HanDB and 3.38% in Animal-10N. The proposed method is expected to be the basis for artificial intelligence research using noisy labeled data accompanying large-scale learning data.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.6
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• pp.601-605
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• 2020

In large ships with complex structures, it is difficult to locate workers. In particular, it is not easy to detect when a worker falls down, making it difficult to respond quickly. Thus, research is being conducted to detect fallen workers using a camera or by attaching a device to the body. Existing image-based fall detection systems have been designed to detect a person's body parts; hence, it is difficult to detect them in various ships and postures. In this study, the entire fall area was extracted and deep learning was used to detect the fallen shipworker based on the image. The data necessary for learning were obtained by recording falling states at the shipyard. The amount of learning data was augmented by flipping, resizing, and rotating the image. Performance evaluation was conducted with precision, reproducibility, accuracy, and a low error rate. The larger the amount of data, the better the precision. In the future, reinforcing various data is expected to improve the effectiveness of camera-based fall detection models, and thus improve safety.