• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.2
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• pp.130-137
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• 2021

This study evaluated newly introduced, commercial super sweet corn hybrids (Zea mays L.) for their potential as breeding materials. Agronomic traits were measured and variance components were obtained using a linear mixed model to estimate the heritability. The trials were carried out in 2018 at two locations (Haenam and Oksan in South Korea). All traits had low heritability, except for mid tasseling and silking days. These traits with low heritability mostly had low genetic variance component estimate. In case of ear height ratio, significant genotype by location appeared to be responsible for low genetic variance, which in turn led to low heritability. Low heritability estimates from the trials with commercial hybrids were perhaps because those hybrids were highly improved for commercial success. Hence, this does not necessarily point to them having poor potential as breeding materials. To overcome low heritability, significant genotype by environment interaction, and achieve high selection efficiency, intermating among hybrids is recommended to create new recombinants before inbred line development.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.620-631
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• 2022

This paper shows the numerical prediction of the change in oil outflow rate according to the orifice shape of a damaged ship by using the computational fluid dynamics (CFD) analysis method. It also provides discharge coefficients for various orifice shapes to be used in theoretical prediction approaches. The oil outflow from the model ship was analyzed using a multiphase flow method under the condition that the Froude and Reynolds number similitudes were satisfied. The present numerical results were verified by comparing them with the available experimental data. Along with the aspect ratio of the orifice and the wall thickness of the cargo tank, the effects of the orifice shapes defined by mathematical figures on the oil outflow were investigated. To consider more realistic situations, the investigation of the ef ect of the crushed iron plate around the damaged part was also included. The numerical results confirmed the change in oil outflow time for various shapes of the damaged part of the oil tank, and discharge coefficients that quantify the viscous effects of those orifice shapes were extracted. To verify the predicted discharge coefficients, they were applied to an oil spill estimation equation. As a result, a good agreement between the CFD and theoretical results was obtained.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.238-249
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• 2021

This research aims to present effective influencer marketing strategies against a heavy blow in Korean influencer marketing industry because of the paid advertisement controversy and the reinforcement of regulations for online advertisement. By investigating the effects of influencer reputation, which is composed of communication skills, influence, authenticity and professionalism on marketing effect, as well as the mediating effect of parasocial relationship, the study provides some implications for influencer selecting. The effect of economic interests is examined under 4 experimental conditions of paid advertisements, brand collaboration, brand gifts and organic review to figure out how to arrange an appropriate sponsorship plan. According to results of PLS structural equation analysis, it shows that the influence and authenticity of an influencer have a significant positive effect on marketing effect and the mediating effect of parasocial relationship is partially proved. It seems that the effect of influencer reputation on marketing effect is significantly differentiated in different contexts, which confirms the moderating effect of economic interest. Distinguish from previous studies, this study focuses on types of economic interest rather than a simple comparison between sponsorship disclosure versus no disclosure and makes contributions to expanding reputation research. Meanwhile, findings of this study could give some practical implications for marketing practitioners in planning influencer marketing.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.523-533
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• 2022

This paper presents a two-stage spatio-spectral fusion method (2SSFM) based on area-to-point regression kriging (ATPRK) to enhance spatial and spectral resolutions using multi-sensor satellite images with complementary spatial and spectral resolutions. 2SSFM combines ATPRK and random forest regression to predict spectral bands at high spatial resolution from multi-sensor satellite images. In the first stage, ATPRK-based spatial down scaling is performed to reduce the differences in spatial resolution between multi-sensor satellite images. In the second stage, regression modeling using random forest is then applied to quantify the relationship of spectral bands between multi-sensor satellite images. The prediction performance of 2SSFM was evaluated through a case study of the generation of red-edge and short-wave infrared bands. The red-edge and short-wave infrared bands of PlanetScope images were predicted from Sentinel-2 images using 2SSFM. From the case study, 2SSFM could generate red-edge and short-wave infrared bands with improved spatial resolution and similar spectral patterns to the actual spectral bands, which confirms the feasibility of 2SSFM for the generation of spectral bands not provided in high spatial resolution satellite images. Thus, 2SSFM can be applied to generate various spectral indices using the predicted spectral bands that are actually unavailable but effective for environmental monitoring.

• Journal of Practical Engineering Education
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• v.13 no.3
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• pp.515-532
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• 2021

The purpose of this study was to analysis of PBL for Korean Apprenticeship Program in Mechanical Engineering. The details of the study were as follows: First, the perception related to the PBL of Korean apprenticeship program was investigated. Second, the utilization and the operational difficulties of PBL for Korean Apprenticeship Program were investigated. Third, the supporting system for PBL was suggested. Research methods were literature research, questionnaire survey and FGI. The survey was conducted online from July 15 to August 14, 2021. A total of 515 respondents responded. A total of 108 in 515 respondents were in Mechanical Engineering. FGI conducted a total of 25 people who actual use PBL in the field of Korean Apprenticeship Program. Conclusions and suggestions based upon the result of this study are as follows. First, It is necessary to improve the utilization of PBL for Korean Apprenticeship Program in Industry. Second, PBL is necessary to apply optionally according to the job and field situation. Third, it is necessary to support system of evaluation for PBL in Korean Apprenticeship Program. Finally, related operation model and guideline need to be prepared for best practice.

• Journal of Science Education
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• v.45 no.1
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• pp.90-104
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• 2021

This study conducted an online survey to understand what elementary school teachers think about the learning contents of elementary science education subjects needed to train elementary science teachers suitable for the era of the 4th Industrial Revolution. The results are as follows: First, there were many elementary school teachers who thought that the current learning content of elementary science education was not suitable for the era of the 4th Industrial Revolution and that it needed to modify the learning content. Many of the teachers said that the learning content of the subject did not include the characteristics of the 4th Industrial Revolution, but also did not reflect the changes of the times and remained in the past. Second, the content that elementary school teachers thought was important in training elementary school teachers suitable for the era of the 4th Industrial Revolution was mainly related to the interests and curiosity of students, and scientific experiments or inquiry. On the contrary, the items that they thought should be deleted or reduced included science learning theory, science teaching/learning model, nature of science, and guidance for gifted children. Third, the contents that elementary school teachers thought needed to be added as learning content of elementary science education subjects were SSI education, science education-related social change and future prediction, advanced science technology, STEAM guidance, and integrated education within the science field. Fourth, in order to train elementary school teachers suitable for the era of the 4th Industrial Revolution, the contents that they thought should be introduced first as learning content of elementary science education subjects were SSI education, integrated education within the science field, STEAM guidance, and core competencies. Other contents that need to be introduced were software education, safety education, and project learning methods.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.135-144
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• 2021

Recently, data-driven decision-making technology has become a key technology leading the data industry, and machine learning technology for this requires high-quality training datasets. However, real-world data contains missing values for various reasons, which degrades the performance of prediction models learned from the poor training data. Therefore, in order to build a high-performance model from real-world datasets, many studies on automatically imputing missing values in initial training data have been actively conducted. Many of conventional machine learning-based imputation techniques for handling missing data involve very time-consuming and cumbersome work because they are applied only to numeric type of columns or create individual predictive models for each columns. Therefore, this paper proposes a new data imputation technique called 'Denoising Self-Attention Network (DSAN)', which can be applied to mixed-type dataset containing both numerical and categorical columns. DSAN can learn robust feature expression vectors by combining self-attention and denoising techniques, and can automatically interpolate multiple missing variables in parallel through multi-task learning. To verify the validity of the proposed technique, data imputation experiments has been performed after arbitrarily generating missing values for several mixed-type training data. Then we show the validity of the proposed technique by comparing the performance of the binary classification models trained on imputed data together with the errors between the original and imputed values.

• The Korean Journal of Emergency Medical Services
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• v.26 no.3
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• pp.161-184
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• 2022

Purpose: This study aimed to develop a cardiopulmonary resuscitation training program for firefighters (FD-CPR) to help improve the survival rate after cardiac arrest on the fireground. Methods: The FD-CPR was developed following 3 steps of the FD-CPR instructional design based on the behaviorism theory. The content of the program was validated by a group of 7 experts using the contents validity index (CVI) and through a pilot-test. Results: A scenario consisting of 7 procedures, and a skill performance evaluation tool consisting of 16 questions were developed. The evaluation tool average score for the difficulty test was 41.16% (even) and that for the discrimination test was 0.32 (high). Subsequently, an 80 min training program was developed. As verified by the 7 experts through the CVI, it was as high as 1.0. Conclusion: The FD-CPR developed domestically for the first time in this study was effective in enhancing the CPR performance skills of the firefighters. If FD-CPR is added to the curriculum at the Fire Service Academy educational course for the new firefighters, the CPR performance skills could be maintained. Furthermore, the program can facilitate a better survival rate for colleagues having cardiac arrest on the field.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.57-69
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• 2023

In a situation where digital transformation using artificial intelligence is active around the world, the growth of domestic AI companies or AI industrial ecosystems is slow. Where a large amount of government funds related to AI are being invested to overcome the difficult economic situation, systematic research on the effect is insufficient. So, this study aimed to examine the policy effectiveness of the government artificial intelligence solution voucher support project for small and medium-sized enterprises (SMEs) using Propensity Score Matching (PSM) and Difference-in-Differences (DID) on the financial performance of beneficiary companies. For empirical analysis, PSM-DID analysis was performed using sales performance since 2019 for 461 companies with a history of voucher support among the AI SMEs data released by the National IT Industry Promotion Agency. As a result of the analysis, the beneficiary companies' asset growth, salary, and R&D expenses increased overall after government support, and no significant contribution could be confirmed in terms of profits. This study suggests that the voucher policy business directly contributed to the company's growth in the short term, but it requires a certain period of time to generate profits.

• Journal of the Korean Geotechnical Society
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• v.38 no.11
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• pp.149-161
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• 2022

This study selected the indexes for evaluating the damage of the railway embankments due to liquefaction from the earthquake damage cases of railway embankments. The study correlated the selected indexes and the settlement of the embankment crest from the dynamic numerical analysis. Further, the correlation was used to develop a method for evaluating the liquefaction damage to the railway embankment. The damage cases and damage types were analyzed, and referring to the liquefaction damage assessment method for other structures, the embankment height (H), the non-liquefiable layer thickness (H₁), and the liquefaction potential index were selected as indexes for evaluating the damage. The study performed dynamic effective stress analyses on the railway embankment, and the PM4-Sand model was applied as the constitutive liquefaction model for the embankment foundation ground. The model's validity was first verified by comparing it with the existing dynamic centrifugal model test results performed on the railway embankment. Nine sites where the foundation ground can be liquefied were selected from the data of 549 embankments of the Honam High-speed Railway in Korea. Further, dynamic numerical analyses using four seismic waves as input earthquake load were performed for the selected site sections. The numerical analysis results confirmed the correlation between the evaluation indexes and the embankment crest settlement. A method for efficiently evaluating the damage to the embankment due to liquefaction was proposed using the chart obtained from this correlation.