• The Journal of the Korea Contents Association
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• v.19 no.10
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• pp.522-534
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• 2019

The purpose of this study is to investigate the interaction factors(learning motivation, concrete feedback, learner's control) and affordance factors (aesthetics, playfulness, stability) that influence flow in e - learning. This study collected 236 survey data from e-learning users. The data was analyzed the statistical relationships among the variables using the SPSS21 and AMOS21. The measurement model was reliable and valid, and the structual model was good. The result shows that interaction factors (concrete feedback, learner's control) and affordance factor (playfulness) influence on flow. Flow has a significant effect on satisfaction. Especially the effect of playfulness on flow is meaningful. Playfulness is one of the most important factors leading to the flow state of humans. The contribution of this study is to find the factors influencing flow in the interaction between learners and computer in e-learning. It can be used to provide an entertainment experience that can enhance the satisfaction of consumers in the Internet environment by finding the antecedents that affect the flow in computer - human interaction.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.583-598
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• 2022

As human-based tunnel inspections are affected by the subjective judgment of the inspector, making continuous history management difficult. There is a lot of deep learning-based automatic crack detection research recently. However, the large public crack datasets used in most studies differ significantly from those in tunnels. Also, additional work is required to build sophisticated crack labels in current tunnel evaluation. Therefore, we present a method to improve crack detection performance by inputting existing datasets into a deep learning model. We evaluate and compare the performance of deep learning models trained by combining existing tunnel datasets, high-quality tunnel datasets, and public crack datasets. As a result, DeepLabv3+ with Cross-Entropy loss function performed best when trained on both public datasets, patchwise classification, and oversampled tunnel datasets. In the future, we expect to contribute to establishing a plan to efficiently utilize the tunnel image acquisition system's data for deep learning model learning.

• Journal of The Korean Association For Science Education
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• v.38 no.6
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• pp.825-838
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• 2018

The purpose of this study is to develop a survey tool of scientific character for elementary student which connects science education and character education effectively by figuring out traits of elementary students' character being presented in teaching and learning context of elementary school science. For this, we adapted the theocratical model from the previous research which defined scientific character as the competencies being able to practice in concrete teaching and learning context of science. Based on this model, we developed the survey tool as 'Scientific Character Inventory for Elementary Student' to assess elementary students' scientific character as the competences to practice the virtues being pursued in the context of elementary school science and verified its reliability and validity. As a result of an exploratory and confirmatory factor analysis, we confirmed all the items could be summarized into 28 items and eight constructs such as scientific problem-solving, self-management, self-reflection, communication, interpersonal skill, community participation, global citizenship, and environmental ethics awareness. We found that minimum reliability coefficient of constructs was over than 0.5 and reliability coefficient of the total items was 0.878. And also, there was modest relationship between each construct and the total score of scientific character. These results show that the developed survey tool can be useful in evaluating the effectiveness of science character education. This study is meaningful in that it systematically reveals constructs of scientific character which can be raised in concrete context of science teaching and learning so as to suggest the survey tool to assess this.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.575-586
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• 2020

In this study, a two-dimensional hydraulic model test was conducted to examine the hydraulic phenomena that occur around the seawall when wave and wind coexist. Based on recent seawall repair and reinforcement examples, the experimental section was constructed under the condition of installing wave dissipation blocks on the safety surface of four different representative seawalls. Water level fluctuation, reflection, overtopping and wave pressure characteristics according to external force change were reviewed. It was confirmed that the top concrete shape of the seawall is the most important factor of the hydraulic characteristics that appear in front of the seawall, and the tendency is more pronounced when wind acts. Even in the case of vertical type seawall, when wind of 3 m/s~5 m/s occurs, the amount of overtopping increases to about 5%~12%. In the case of wave pressure, it was confirmed from the experimental results that the value increased from about 1.5 to 2.2 times in front of the top of concrete block. In addition, it was confirmed that when the shape of the seawall was different, the range of change in the hydraulic characteristics appeared larger. Therefore, when designing a seawall of a new shape, a more detailed review of the hydraulic characteristics should be accompanied based on these experimental results.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.2
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• pp.85-92
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• 2023

Unlike a completed building, a building under construction may be at risk in terms of safety if a load exceeds the value considered in the design stage owing to various factors, such as a load action different from that in the design stage and insufficient concrete strength. In addition, if an earthquake occurs in a building under construction, greater damage may occur. Therefore, this study studied example models with various sizes of 5, 15, 25, and 60 floors for typical building types and analyzed the effects of seismic load on buildings under construction using construction-stage models according to frame completeness. Because the construction period of the building is much shorter than the period of use after completion, applying same earthquake loads as the design stage to buildings under construction may be excessive. Therefore, earthquakes with a return period of 50 to 2,400 years were applied to the construction stage model to review the seismic loads and analyze the structural performances of the members. Thus, we reviewed whether a load exceeding that of the design stage was applied and the return period level of the earthquake that could ensure structural safety. In addition, assuming the construction period of each example model, the earthquake return period according to the construction period was selected, and the design appropriateness with the selected return period was checked.

• Journal of the Korea Concrete Institute
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• v.19 no.4
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• pp.515-525
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• 2007

In this investigation, results of laboratory tests on four reinforced concrete flat plate interior connections with elongated rectangular column support which has been used widely in tall residential buildings are presented. The purpose of this study is to evaluate an effect of column aspect ratio (${\beta}_c={c_1}/{c_2}$=side length ratio of column section in the direction of lateral loading $(c_1)$ to the direction of perpendicular to $c_1$) on the hysteretic behavior under earthquake type loading. The aspect ratio of column section was taken as $0.5{\sim}3\;(c_1/c_2=1/2,\;1/1,\;2/1,\;3/1)$ and the column perimeter was held constant at 1200mm in order to achieve nominal vertical shear strength $(V_c)$ uniformly. Other design parameters such as flexural reinforcement ratio $(\rho)$ of the slab and concrete strength$(f_{ck})$ was kept constant as ${\rho}=1.0%$ and $f_{ck}=40MPa$, respectively. Gravity shear load $(V_g)$ was applied by 30 percent of nominal vertical shear strength $(0.3V_o)$ of the specimen. Experimental observations on punching failure pattern, peak lateral-load and story drift ratio at punching failure, stiffness degradation and energy dissipation in the hysteresis loop, and steel and concrete strain distributions near the column support were examined and discussed in accordance with different column aspect ratio. Eccentric shear stress model of ACI 318-05 was evaluated with experimental results. A fraction of transferring moment by shear and flexure in the design code was analyzed based on the test results.

• Journal of the Korean association of regional geographers
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• v.11 no.4
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• pp.523-535
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• 2005

This study is aimed at researching the applicability of teaching-learning models in highschool geography class by designing the models on the basis of geographical experience the learners go through everyday life. The procedures and results of the application of the models are as followed. First, the systematization of the teaching concepts should be preceded to internalize the learners cognitive development, that is, to systemize cognitive structure. The concrete learning points of geographical concepts from the units about Migration and Population Changes are systemized with 'migration' as a higher concept, 'moving type' as basic concept, 'moving factors' as the lower concept. Everyday geographical experiences the students can go through are surveyed. Second, as preparation for the geography class, hand-outs about family-moving history and the change of the family number were used as basic material for real class teaching activity, showing the learners' general concepts are very effective as basic units which can be easily understood and accessed to. Third, with the experimental class, the geography class should secure the flexibility on the teaching-learning process. The result of applying the newly developed teaching-learning model to actual geography classes was that experimental group had higher achievement rate than the compared group with general teaching-learning model applied to. The result of analyzing students' response of the new teaching-learning model was that the students were interested and satisfied emphatically and they showed positive response in regard to practical use of the contents. Here, it is noticeable that the new teaching-learning model causes the students to be interested. But it's also found that there's no big difference in improving the students' inquisitive mind.

• Journal of the Earthquake Engineering Society of Korea
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• v.15 no.2
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• pp.53-60
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• 2011

When designing building structures, dynamic serviceability is one of the most important items. Much research is being carried out on machine vibrations that affect inside residents and expensive equipment in the building structure. The vibration effect generally depends on the mass ratio, and an adequate mass ratio is determined by comparison with the serviceability limit according to the criteria. This study investigates the evaluation of vibration serviceability by using ISO 2631 to confirm the propriety of adequate mass ratios and it is verified that the application of a complicated FE model to model the real large shaking table facility with the mathematical model simulated as a SDOF system. The weighted RMS value is then compared with the comfort limit given by ISO 2631. As a result, the analysis of the numerical model is consistent with analysis of the FE model. Moreover, it is found that the adequate mass ratio of the concrete foundation and shake table, considering the self-weight of the real facility, should be less than 0.013. It is also confirm that the sample facility is satisfies the requirement of an adequate mass ratio.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.2
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• pp.133-144
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• 2006

In order to catch out such Bond Strength, the preceding researchers had ever examined the Bond Strength of FRP Plate through their experimentations by setting up of various fluent. However, since the experiment for research on such Bond Strength takes much of expenditure for equipment structure and time-consuming, also difficult to carry out, it is conducting limitedly. This Study purposes to develop the most suitable Artificial Neural Network Model by application of various Neural Network Model and Algorithm to the adhering experiment data of the preceding researchers. Output Layer of Artificial Neural Network Model, and Input Layer of Bond Strength were performed the learning by selection as the variable of the thickness, width, adhered length, the modulus of elasticity, tensile strength, and the compressive strength of concrete, tensile strength, width, respectively. The developed Artificial Neural Network Model has applied Back-Propagation, and its error was learnt to be converged within the range of 0.001. Besides, the process for generalization has dissolved the problem of Over-Fitting in the way of more generalized method by introduction of Bayesian Technique. The verification on the developed Model was executed by comparison with the resulted value of Bond Strength made by the other preceding researchers which was never been utilized to the learning as yet.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.4
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• pp.65-74
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• 2021

In order to efficiently inspect rapidly increasing old tunnels in many well-developed countries, many inspection methodologies have been proposed using imaging equipment and image processing. However, most of the existing methodologies evaluated their performance on a clean concrete surface with a limited area where other objects do not exist. Therefore, this paper proposes a 6-step framework for tunnel crack detection deep learning model development. The proposed method is mainly based on negative sample (non-crack object) training and Cascade Mask R-CNN. The proposed framework consists of six steps: searching for cracks in images captured from real tunnels, labeling cracks in pixel level, training a deep learning model, collecting non-crack objects, retraining the deep learning model with the collected non-crack objects, and constructing final training dataset. To implement the proposed framework, Cascade Mask R-CNN, an instance segmentation model, was trained with 1561 general crack images and 206 non-crack images. In order to examine the applicability of the trained model to the real-world tunnel crack detection, field testing is conducted on tunnel spans with a length of about 200m where electric wires and lights are prevalent. In the experimental result, the trained model showed 99% precision and 92% recall, which shows the excellent field applicability of the proposed framework.