• Journal of the Korean Recycled Construction Resources Institute
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• v.7 no.2
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• pp.158-165
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• 2019

The purpose of this study is to investigate analytically the flexural behavior of beam reinforced by an alkali-activated slag-based fiber-reinforced composite. The materials and mixture proportion were selected to manufacture an alkali-activated slag-based fiber-reinforced composite with high tensile strain capacity over 7% and compressive strength and tension tests were performed. The composite showed a compressive strength of 32.7MPa, a tensile strength of 8.43MPa, and a tensile strain capacity of 7.52%. In order to analyze the flexural behavior of beams reinforced by ultra-high-ductile composite, nonlinear sectional analysis was peformed for four types of beams. Analysis showed that the flexural strength of beam reinforced partially by ultra-high-ductile composite increased by 8.0%, and the flexural strength of beam reinforced fully by ultra-high-ductile composite increased by 24.7%. It was found that the main reason of low improvement in flexural strength is the low tensile strain at the bottom of beam. The tensile strain at bottom corresponding to the flexural strength was 1.38% which was 18.4% of tensile strain capacity of the composite.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.314-321
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• 2019

The Self-Adaptive Vision Correction Algorithm (SAVCA) developed in this study was suggested for improving usability by modifying four parameters (Modulation Transfer Function Rate, Astigmatic Rate, Astigmatic Factor and Compression Factor) except for Division Rate 1 and Division Rate 2 among six parameters in Vision Correction Algorithm (VCA). For verification, SAVCA was applied to two-dimensional mathematical benchmark functions (Six hump camel back / Easton and fenton) and 30-dimensional mathematical benchmark functions (Schwefel / Hyper sphere). It showed superior performance to other algorithms (Harmony Search, Water Cycle Algorithm, VCA, Genetic Algorithms with Floating-point representation, Shuffled Complex Evolution algorithm and Modified Shuffled Complex Evolution). Finally, SAVCA showed the best results in the engineering problem (speed reducer design). SAVCA, which has not been subjected to complicated parameter adjustment procedures, will be applicable in various fields.

• Fire Science and Engineering
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• v.33 no.2
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• pp.63-67
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• 2019

In this study, the pressure loss of a fire hose reel hydrant was examined and the effects of each factor on the pressure loss were analyzed. First, in the pressure loss experiment according to the length of the reel hose, the pressure loss increased with increasing length of the reel hose; it was approximately 38.86% based on a 25 m hose. Second, the pressure loss of the reel hose per unit length was estimated to be $.13{\sim}.15kgf/cm^2$. Third, in the pressure loss experiment according to the change in the flow rate, the result was similar to the relation, flow rate - pressure loss (${\Delta}P{\sim}Q^2$), in the piping flow. These results provide basic data on the evaluation of fire pump pressure and the performance-based fire-protecting design of fire hose reel hydrants used in buildings.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.227-234
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• 2019

The purpose of this study is to present a block type smart classroom model for comprehensive supply of educational contents, classroom environment and ICT technology in African countries where educational infrastructure is weak. It will provide a contextual solution that integrates learning management, power management, and classroom environment management systems, and will be a convergence model that can optimize economic and non-economic conditions for different African countries. It can be expected to enhance utilization as it is a differentiated model from existing classrooms with a single container, as well as independent research and development centered on services, content, and solutions. Through this integrated research process, we can overcome the spatial and functional limitations appearing in single container classrooms and build a flexible space for advanced e-learning technology. The depth and scope of the follow-up study can be carried by investigating the performance and models that are in line with the educational and infrastructure conditions of the various regions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.155-163
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• 2019

The knowledge about drought propagation is very important in accurate estimation of hydrological drought characteristics and efficient development of early warning system. This study investigated a probabilistic relationship of drought propagation based on Bayesian network model for historic period and for future projection under climate change scenario RCP 8.5 over the Han River basin. The results revealed that the propagation rate and lag time have increasing and decreasing trends from the historic period of 1967-2013 to the future periods of 2014-2053 and 2054-2100 under climate change, respectively. The probabilistic results of Bayesian model revealed that the probability of occurrence of lag time varied spatially and decreased when the intensity of meteorological drought changed from moderate to severe and extreme condition during 1967-2013. The values of probability increased in the first future period of 2014-2053 in several sub-basins and slight decreased in the second period of 2054-2100. The proposed probabilistic results will be useful for the decision makers to develop related policies with an appropriate insight toward the future drought status.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.3
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• pp.287-294
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• 2021

In this study, tests were performed to analyze the feasibility of using the ground stabilizer from recycled resources such as blast furnace slag powder as filling material of prebored piles. For this, specimens were prepared by applying 70% and 83% of the general water/binder ratio of the filling material of prebored piles. And compression test, model test, and shaking table test were performed to determine the compressive strength, skin friction on the surface between prebored pile and filling material, and seismic performance of ground stabilizer. As a result of the tests, the compressive strength exceeded the relevant domestic standards, and the skin friction was equivalent to that of ordinary portland cement. In addition, the amount of vertical and horizontal displacement caused by earthquakes was found to be much smaller than the domestic standard. Therefore, when considering the test results comprehensively, it is judged that the feasibility of using a ground stabilizer from recycled resources as filling material for prebored pile is sufficient.

• Journal of the Korean GEO-environmental Society
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• v.12 no.12
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• pp.55-61
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• 2011

Recently, a concept of the downtown area was progressively extended by improvement of rapid transportation system and development of the most advanced telecommunication industries. And underground has become bigger in addition deeper, Excavation methods which construct a structure were changed according to construction environments. Top Down methods which are continuous with architectural plan differ from existing excavation methods innovatively, pre-founded column is an important factor for construction methods, duration, expenses. Therefore, this study considers application by investigative methods according to comparison, analysis on loading test result of on site inspection and estimated results of bearing capacity for structure pre-founded column. As a result, almost designing eclipse appeared prior value which didn't arrive result of load test. Also, evaluate permanent load for the compressive stress acting on head of cast-in-place after basic structure was installed. Then, applying stress generally is reduced by confining effect with foundation.

• Applied Chemistry for Engineering
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• v.22 no.3
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• pp.291-295
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• 2011

A bake-out process using auto switchgear for five days was performed to evaluate the reduction effect of the concentration of volatile organic compounds (VOCs) and formaldehyde in a newly-built elementary school gymnasium. Reduction rates of VOCs were observed as followings: 38.2, 64.2, 86.3, 80.2, and 71.5% for benzene, toluene, ethylbenzene, xylene, and styrene, respectively, which satisfies the indoor air quality standards of newly-built apartment houses in Korea. The reduction rate of total VOCs and formaldehyde were 67.0 and 24.7%, respectively. Those results proved that the bake-out process using auto switchgear was effective for reducing indoor air pollutants.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.1
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• pp.50-57
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• 2021

In this study, the engineering charateristics of recycled cold asphalt mixtures using waste glass and red mud were examined as part of the development of low carbon road pavement materials using large amounts of waste. It also examined the satisfaction of the performance criteria specified in the standard. As a result of the study, it was found that RCA using waste glass were not met standard of GR since strain resistance reduced. Therefore, it has been shown that improvements in the composition of the mixture are needed. It has also been shown to significantly improve the performance of the mixture when adding red mud. In addition, it was found that the quality standards for stability, flow value, indirect tensile strength and tensile strength ratio as specified by GR are satisfied.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.473-482
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• 2022

Wearing a mask is also necessary to limit the risk of infection in today's era of COVID-19 and wearing a helmet is inevitable for the safety of personnel who works in a dangerous working environment such as construction sites. This paper proposes an effective deep learning model, HelmetMask-Net, to classify both Helmet and Mask. The proposed HelmetMask-Net is based on CNN which consists of data processing, convolution layers, max pooling layers and fully connected layers with four output classifications, and 4 classes for Helmet, Mask, Helmet & Mask, and no Helmet & no Mask are classified. The proposed HelmatMask-Net has been chosen with 2 convolutional layers and AdaGrad optimizer by various simulations for accuracy, optimizer and the number of hyperparameters. Simulation results show the accuracy of 99% and the best performance compared to other models. The results of this paper would enhance the safety of personnel in this era of COVID-19.