• 한국체육학회지인문사회과학편
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• v.54 no.2
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• pp.299-312
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• 2015

The purpose of this study was to find the effects of user experience on flow and satisfaction of electronic hogu system in the taekwondo game. The subjects were players who had experience using electronic hogu system in the taekwondo game for 2014 year 7month~10month. 652 samples out of 750 samples through convenient sampling method were adopted as a final data. We confirmed the goodness of fit test of the model, utilizing SPSS WIN Ver 18.0, and AMOS 7.0, and after which we tested each hypothesis. The results were as follows; First, sentient, emotional, cognitive, behavioral, relational experience of user experience did not have a significant influence on cognition flow. Second, sentient, emotional, relational experience of user experience did not have a significant influence on behavioral flow. Third, cognitive, behavioral experience of user experience had a significant influence on behavioral flow. Fourth, cognition, behavioral flow had a significant influence on satisfaction. Fifth, factor between native and foreigner taekwondo players had significantly different. This paper is a meaningful to figure out user satisfaction of electronic hogu system in taekwondo games and maximize athletic performance.

• Composites Research
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• v.36 no.3
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• pp.211-216
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• 2023

When designing ships and aircraft structures, it is important to design them to satisfy weight reduction and strength. Currently, studies related to topology optimization using 3D printed composite materials are being actively conducted to satisfy the weight reduction and strength of the structure. In this study, structural analysis was performed to analyze the applicability of 3D printed composite materials to the flight control surface, one of the parts of an aircraft or unmanned aerial vehicle. The optimal topology shape of the flight control surface for the bending load was analyzed by considering three types (hexagonal, rectangular, triangular) of the topology shape of the flight control surface. In addition, the bending strength of the flight control surface was analyzed when four types of reinforcing materials (carbon fiber, glass fiber, high-strength high-temperature glass fiber, and kevlar) of the 3D printed composite material were applied. As a result of comparing the three-point bending test results with the finite element method results, it was confirmed that the flight control surface with hexagonal topology shape made of carbon fiber and Kevlar had excellent performance. And it is judged that the 3D printed composite can be sufficiently applied to the flight control surface.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2C
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• pp.71-79
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• 2009

This study is to develope the resilient modulus prediction model, which is the function of mean effective principal stress and axial strain, for three types of railroad trackbed materials such as crushed stone, weathered granite soil, and crushed-rock soil mixture. The model consists of the maximum Young's modulus and nonlinear values for higher strain, analogous to dynamic shear modulus. The maximum value is modeled by model parameters, $A_E$ and the power of mean effective principal stress, $n_E$. The nonlinear portion is represented by modified hyperbolic model, with the model parameters of reference strain, ${\varepsilon}_r$ and curvature coefficient, a. To assess the performance of the prediction models proposed herein, the elastic response of a test trackbed near PyeongTaek, Korea, was evaluated using a 3-D elastic multilayer computer program (GEOTRACK). The results were compared with measured elastic vertical displacement during the passages of freight and passenger trains at two locations, whose sub-ballasts were crushed stone and weathered granite soil, respectively. The calculated vertical displacements of the sub-ballasts are within the order of 0.6mm, and agree well with measured values. The prediction models are thus concluded to work properly in the preliminary investigation.

• The Journal of Bigdata
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• v.7 no.2
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• pp.31-41
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• 2022

Steel is one of the most fundamental components to mechanical industry. However, the quality of products are greatly impacted by the surface defects in the steel. Thus, researchers pay attention to the need for surface defects detector and the deep learning methods are the current trend of object detector. There are still limitations and rooms for improvements, for example, related works focus on developing the models but don't take into account real-time application with practical implication on industrial settings. In this paper, a real-time application of steel surface defects detection based on YOLOv4 is proposed. Firstly, as the aim of this work to deploying model on real-time application, we studied related works on this field, particularly focusing on one-stage detector and YOLO algorithm, which is one of the most famous algorithm for real-time object detectors. Secondly, using pre-trained Yolov4-Darknet platform models and transfer learning, we trained and test on the hot rolled steel defects open-source dataset NEU-DET. In our study, we applied our application with 4 types of typical defects of a steel surface, namely patches, pitted surface, inclusion and scratches. Thirdly, we evaluated YOLOv4 trained model real-time performance to deploying our system with accuracy of 87.1 % mAP@0.5 and over 60 fps with GPU processing.

• The Journal of Bigdata
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• v.8 no.1
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• pp.157-165
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• 2023

Seafood is a major source of protein in many countries and its consumption is increasing. In Korea, consumption of seafood is increasing, but self-sufficiency rate is decreasing, and the importance of safety management is increasing as the amount of imported seafood increases. There are hundreds of species of aquatic products imported into Korea from over 110 countries, and there is a limit to relying only on the experience of inspectors for safety management of imported aquatic products. Based on the data, a model that can predict the customs inspection results of imported aquatic products is developed, and a machine learning classification model that determines the non-conformity of aquatic products when an import declaration is submitted is created. As a result of customs inspection of imported marine products, the nonconformity rate is less than 1%, which is very low imbalanced data. Therefore, a sampling method that can complement these characteristics was comparatively studied, and a preprocessing method that can interpret the classification result was applied. Among various machine learning-based classification models, Random Forest and XGBoost showed good performance. The model that predicts both compliance and non-conformance well as a result of the clearance inspection is the basic random forest model to which ADASYN and one-hot encoding are applied, and has an accuracy of 99.88%, precision of 99.87%, recall of 99.89%, and AUC of 99.88%. XGBoost is the most stable model with all indicators exceeding 90% regardless of oversampling and encoding type.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.67-72
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• 2006

Temperature prediction in asphalt pavements is the one of most important factors for estimating the pavement response and predicting the pavement performance in the mechanistic-empirical pavement design. A study on temperature prediction procedure with variation of time and depth in asphalt pavements was conducted using field monitoring data. After selecting the temperature monitoring sections, the temperature sensors have been installed in different depths and the temperature data have been collected in every one hour. The developed pavement temperature prediction model was calibrated using field monitoring temperature data. The predicted temperatures were compared with measured temperatures at different seasons in selected sections. The results showed that the solar absorptivity and emissivity values in the fall is different from the values in other seasons. The predicted temperatures agree well with the measured temperatures at a wide range of temperatures. The temperature differences between each other fall in the range of ${\pm}3^{\circ}C$. It is also found that the regional characteristics did not affect the temperature prediction procedure.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6D
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• pp.719-726
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• 2009

In this study, a series of push-off tests for lean concrete, aggregate, asphalt subbases mainly used in Korea were performed to investigate the friction characteristics between the slab and subbase layers. Use of separation membrane and wet condition of subbase were other parameters in the tests. Horizontal displacements of the slabs and friction coefficients were measured at 1st loading, stable condition (2nd and 3rd loadings), and wet condition (4th loading) by applying 40mm/hour horizontal loadings. Larger maximum friction coefficients were measured in order of the lean concrete, asphalt, aggregate, and subbases using the separation membrane at 1st loading, and in order of the asphalt, aggregate, lean concrete, and subbases using the separation membrane at stable and wet conditions. The friction coefficients of the aggregate and asphalt subbases which did not used the separation membrane decreased by the wet condition while the subbases using the separation membrane were not affected. Additional push-off tests for effects of slab thickness and temperature sensitivity of asphalt will be performed. And, effects of the friction characteristics between the slab and subbase layers on behavior and performance of concrete pavements will be investigated by structural analyses using the test results.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2A
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• pp.169-176
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• 2010

Generally, poly-urea is widely used as waterproof coating material due to its superior adhesiveness, elongation capacity, and permeability resistance. In addition, it can be quickly and easily applied on structure surfaces using spray application. Since it hardens in about 30 seconds after application, its construction efficiency is very high and its usage as a special functional material is also excellent. However, currently, poly-urea is mostly used as waterproof coating material and the researches on its usage as a retrofitting material is lacking at best. Therefore, basic studies on the use of poly-urea as a general structural retrofitting material are needed urgently. The objective of this study is to develop most optimum poly-urea composition for structure retrofitting purpose. Moreover, the structural strengthening capacity of the developed poly-urea is evaluated through flexural capacity experiments on RC beams and RC slabs. From the results of the flexural test of poly-urea strengthened RC beam and slab specimens, the poly-urea and concrete specimen showed monolithic behavior where ductility and ultimate strength of the poly-urea strengthened specimen showed slight increase. However, the doubly reinforced specimens with FRP sheet and poly-urea showed lower capacity than that of the specimen reinforced only with FRP sheet.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.687-693
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• 2006

Image co-registration is the process of overlaying two images of the same scene, one of which represents a reference image, while the other is geometrically transformed to the one. In order to improve efficiency and effectiveness of the co-registration approach, the author proposed a pre-qualified area matching algorithm which is composed of feature extraction with canny operator and area matching algorithm with cross correlation coefficient. For refining matching points, outlier detection using studentized residual was used and iteratively removes outliers at the level of three standard deviation. Throughout the pre-qualification and the refining processes, the computation time was significantly improved and the registration accuracy is enhanced. A prototype of the proposed algorithm was implemented and the performance test of 3 Landsat images of Korea. showed: (1) average RMSE error of the approach was 0.435 pixel; (2) the average number of matching points was over 25,573; (3) the average processing time was 4.2 min per image with a regular workstation equipped with a 3 GHz Intel Pentium 4 CPU and 1 Gbytes Ram. The proposed approach achieved robustness, full automation, and time efficiency.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5A
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• pp.543-550
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• 2009

This study was performed to prove the possibility of utilizing short plastic fibers made for recycled polyethylene terephthalate (RPET) as a structural material. In order to verify the capacity of RPET fiber, it was compared with polypropylene (PP) fiber, most widely used short synthetic fiber, for fiber volume fraction of 0%, 0.5%, 0.75%, and 1.0%. To measure material properties such as compressive strength, split tensile strength, appropriate tests were performed. Also, to measure the strength and ductility capacities of reinforced concrete (RC) member casted with RPET fiber added concrete, flexural test was performed on RC beams. The results showed that compressive strength decreased, as fiber volume fraction increased. These trends are similarly observed in the tests of PP fiber added concrete specimens. Split cylinder tensile strength of RPET fiber reinforced concrete increased slightly as fiber volume fraction increased. For structural member performance, ultimate strength, relative ductility and energy absorption of RPET added RC beam are significantly larger than OPC specimen. Also, the results showed that ultimate flexural strength and ductility both increased, as fiber volume fraction increased. These trends are similarly observed in the tests of PP fiber added concrete specimens. The study results indicate that RPET fiber can be used as an effective additional reinforcing material in concrete members.