• Korean Journal of Child Education & Care
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• v.18 no.4
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• pp.123-143
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• 2018

Objective: The purpose of this study was to investigate daycare center director's awareness of male teacher recruitment and need for effective male teacher recruitment. Methods: To this end, eight directors of child care centers with male teachers were selected as subjects of study. The data collection method was applied to the Focus Group Interview method, and a four interviews were conducted for two to two and a half hours. Results: After the interview data was analyzed, the contents were categorized into two major themes and six sub themes in awareness of male teacher recruitment by director of daycare center. The two major themes were (1) A vague fear of upcoming difficulties (2) The light and darkness of male teachers in the organization culture of childcare. Looking at the results, in a vague fear of upcoming difficulties theme includes administrative disadvantages, gender-related social atmosphere, and uncertainty about their role performance. Second, in the light and darkness theme includes women-centered organizational culture and adaptation, the vision of child care sites, and the role of male teachers at childcare sites. Next the contents were categorized into one major theme and four sub themes in need for effective male teacher recruitment by director of daycare center. The major theme was a male teacher's way into the daycare site, and sub five themes were expanding opportunities for child care experience and practices, a shift in the perception that it's not a man, it's an individual problem, maximizing the strengths of men, and improving the system. Conclusion/Implications: Based on these results, several specific implications of need for effective male teacher recruitment were suggested.

• Journal of IKEEE
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• v.23 no.3
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• pp.1088-1091
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• 2019

In this paper, a real-time monitoring system for environmental safety by living area is proposed. The proposed system is designed to measure radiation, fine dust and basic living information (temperature) using fixed and mobile measuring equipment, and constitutes a web database that stores data received from the equipment. It also develops web programs for displaying received data on PCs and mobile phones. The results of testing the performance of the system by an authorized testing agency showed that the radiation measurement range was measured in the range of $10{\mu}Sv/h$ to 10mSv/h, which is comparable to the world's highest level, and that the accuracy was measured between ${\pm}6.7$ and ${\pm}8.7$ percent of the measurement uncertainty was measured and normal operation at or below the international standard of ${\pm}15$ percent. In addition, the temperature test was conducted on a section of $-20^{\circ}C$ to $50^{\circ}C$ and normal operation was confirmed in response to the temperature change. Stability of radiated electromagnetic waves was ensured by a suitable judgment. The product's testing in general and high and low temperature environments for about four months after the prototype was made confirmed to be more than five years of durability. The measurement range and accuracy of fine dust sensors are compared with those of companies that measure the air environment, and the performance level is similar through the air quality measurement register.

• Journal of Convergence for Information Technology
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• v.9 no.4
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• pp.59-67
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• 2019

Most of the prior researches in brand extension evaluation have utilized purchase intention as a n effective variable to assess the effectiveness of brand extensions. In contrast, the author proposes that trial intention is to better predict consumers' behavioral response in the newly launched brand extension markets where relate to high risk and uncertainty. Furthermore, the study explores the effects of attitude toward parent brand and consumers' characteristics (perceived similarity and consumption experience) on trial intention of brand extensions. In order to achieve the purpose of the study, the data collection was conducted for actual consumers who had experience using parent brand products. This study employed experiment and questionnaire survey and collected data of 186 was analyzed using clustering analysis and regression analysis. The main results are as follows. First, attitude toward parent brand has a positive effect on trial intention of the extensions. Second, perceived similarity and consumption experience of parent brand have moderating effects on the relation of attitude toward parent brand and trial intention of brand extensions. The results provide that both industry and academic researchers with a guide to process trial intention of brand extension from a comprehensive perspective.

• Journal of the Korean Society of Earth Science Education
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• v.13 no.3
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• pp.238-252
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• 2020

In this study, we analyzed the types of rebuttals in the argument structure of learning contents in lesson plans constructed by Earth science preservice teachers, and then we explored examples of how they responded to resolving the rebuttal. As a result of analyzing preservice teachers' assignments, discussions, and interviews collected during a total of 20 hours of classes and group discussions for 5 weeks, all 5 types of rebuttals suggested by Verheij (2005) were identified. Through the data analysis, a total of 18 rebuttal cases derived, and these cases were classified into 3 types according to how preservice teachers solve the rebuttals in class. The conclusions and implications based on the results are as follows: First, this study provided empirical data that the thinking process of validating core elements of argumentation and processes of argumentation is actively taking place in preservice teachers' lesson planning using the argument structure, and expanded the scope of application of argumentation in science education research. Second, the argument structure of learning contents should be used to help teachers to come up with strategies to induce students' curiosity and devotion to learn science contents. Third, preservice teachers should have the opportunity to think about the nature of science, including the variability and uncertainty of scientific knowledge when they discover rebuttals and develop solutions to them. Based on these conclusions, implications and suggestions for science education and further research were suggested.

• Journal of the Korean Geotechnical Society
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• v.37 no.5
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• pp.47-63
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• 2021

Recently, the demand for three-dimensional (3D) underground maps from the perspective of digital twins and the demand for linkage utilization are increasing. However, the vastness of national geotechnical survey data and the uncertainty in applying geostatistical techniques pose challenges in modeling underground regional geotechnical characteristics. In this study, an optimal learning model based on multi-layer perceptron (MLP) was constructed for 3D subsurface lithological and geotechnical classification in Seoul, South Korea. First, the geotechnical layer and 3D spatial coordinates of each borehole dataset in the Seoul area were constructed as a geotechnical database according to a standardized format, and data pre-processing such as correction and normalization of missing values for machine learning was performed. An optimal fitting model was designed through hyperparameter optimization of the MLP model and model performance evaluation, such as precision and accuracy tests. Then, a 3D grid network locally assigning geotechnical layer classification was constructed by applying an MLP-based bet-fitting model for each unit lattice. The constructed 3D geotechnical layer map was evaluated by comparing the results of a geostatistical interpolation technique and the topsoil properties of the geological map.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.1
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• pp.35-47
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• 2022

Expansion of potato production areas can improve the food security in North Korea because the given crop has less requirements for agricultural materials and facilities. The Global Agro-Ecological Zones (GAEZ) model, which was developed to evaluate climate suitability under different cultivation conditions, was used to identify potential areas for the potato production. The spatial estimates of crop suitability under low and high input management conditions were downloaded from the GAEZ data portal. The values of suitability were obtained at the potato occurrence sites retrieved from the Global Biodiversity Information Facility (GBIF) database. The suitable areas for the potato production were identified using a threshold value derived from the suitability estimates at the occurrence sites. It was found that 90% of the occurrence sites had the suitability index value >3,333, which was set to be the threshold value. The suitable areas in North Korea were summarized by province and county. Rice cultivation areas were excluded from the analysis. The reported relative acreage of potato production was better represented by the suitable areas under the low input management options than the high input conditions. The suitable areas also had a similar distribution to the reported acreage of potato production by county. These results indicated that the GAEZ model would be useful to identify the candidate production areas, which would facilitate the increases in potato production especially under future climate conditions. Furthermore, monthly maps of crop suitability can be used to design cropping systems that would improve crop production under the limited use of agricultural materials and facilities.

• Journal of Korea Water Resources Association
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• v.55 no.7
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• pp.545-556
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• 2022

It is recommended to use long-term hydrometeorological data for more than the service life of the hydraulic structures and water resource planning. For the purpose of expanding rainfall data, stochastic simulation models, such as Modified Bartlett-Lewis Rectangular Pulse (BLRP) and Neyman-Scott Rectangular Pulse (NSRP) models, have been widely used. The optimal parameters of the model can be estimated by repeatedly comparing the statistical moments defined through a combination of parameters of the probability distribution in the optimization context. However, parameter estimation using relatively small observed rainfall statistics corresponds to an ill-posed problem, leading to an increase in uncertainty in the parameter estimation process. In addition, as shown in previous studies, extreme values are underestimated because objective functions are typically defined by the first and second statistical moments (i.e., mean and variance). In this regard, this study estimated the parameters of the NSRP model using the objective function with the third moment and compared it with the existing approach based on the first and second moments in terms of estimation of extreme rainfall. It was found that the first and second moments did not show a significant difference depending on whether or not the skewness was considered in the objective function. However, the proposed model showed significantly improved performance in terms of estimation of design rainfalls.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.32 no.6
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• pp.239-245
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• 2022

Reduced graphene oxide (rGO) has attracted many attention and applications due to its excellent electrochemical ability. Therefore, standardization of rGO through structural and thermal analysis facilitates quality improvement and management, enabling users to increase efficiency and reduce relevant costs. For rGO and graphene-related materials, it is very important to determine the number of layers and define the resulting difference in physical properties. In this study, 3~4 layers of rGO-1 and 9~10 layers of rGO-2 were obtained from graphene oxide (GO) through a hydrazine reduction process. For the prepared rGOs, X-ray diffraction (XRD) pattern obtained a diffraction peak at 2θ≈25° related to (002) reflection was used to calculate the layer numbers by determining interlayer distance and FWHM value. To reduce the angular uncertainty, XRD data analysis was performed with angle correction using standard reference materials for X-ray powder diffraction analysis. Precise interlayer distance and number of layers were determined using OriginLab and open-source XRD diffraction analysis programs using the angle-corrected diffraction data. TG-DSC thermal analysis was performed to further standardize the physical properties of rGO samples.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.192-207
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• 2023

Commercialization of level-4 (Lv.4) autonomous driving applications requires the definition of a safe road environment under which autonomous vehicles can operate safely. Thus, a risk assessment model is required to determine whether the operation of autonomous vehicles can provide safety to is sufficiently prepared for future real-life traffic problems. Although the risk factors of autonomous vehicles were selected and graded, the decision-making method was applied as qualitative data using a survey of experts in the field of autonomous driving due to the cause of the accident and difficulty in obtaining autonomous driving data. The fuzzy linguistic representation of decision-makers and the fuzzy analytic hierarchy process (AHP), which converts uncertainty into quantitative figures, were implemented to compensate for the AHP shortcomings of the multi-standard decision-making technique. Through the process of deriving the weights of the upper and lower attributes, the road alignment, which is a physical infrastructure, was analyzed as the most important risk factor in the operation risk of autonomous vehicles. In addition, the operation risk of autonomous vehicles was derived through the example of the risk of operating autonomous vehicles for the 5 areas to be evaluated.

• Journal of the Korean Geotechnical Society
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• v.38 no.3
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.