• 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.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.1
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• pp.5-24
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• 2022

As a new academic publication model is attempted to improve the transparency, efficiency, and speed of scientific knowledge production and distribution, the open peer review platform for verification and openness of peer review history is also activated. Publons is a global platform for tracking, validating, disclosing, and recognizing the peer-reviewed histories of more than 3 million researchers worldwide. This study analyzed the review activities of 579 researchers from domestic universities who are actively reviewing international journals through Publons. As a result of the analysis, first, researchers from domestic universities who actively review international academic journals were found to be in the fields of medicine and electrical and electronics, and in most fields, assistant professors or higher with high WOS indexed research papers are participating. Second, there was a long-tail phenomenon in which a small number of reviewers with extremely high number of review papers existed in all academic fields, and there was no significant difference in the number of review papers and review report length depending on the nationality, academic status, and age of the reviewers. Lastly, although there was a weak correlation between the amount of papers reviewed by reviewers and the number of published papers, it was found that researchers with an extremely large number of reviews do not necessarily produce as many research papers.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.391-398
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• 2022

The aim of this study was to identify the factors affecting the mental health of high school students. The participants comprised 216 students in general high school. Data collection was conducted from May 1, 2020 to May 20, 2020. The data were analyzed using descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient and a multiple regression analysis. The average score for self-esteem was 3.75±0.64(1-5), perceived stress was 2.86±0.58(1-5), emotional regulation ability was 3.43±0.65(1-5) and mental health was 1.91±0.71(1-5). Mental health had a statistically significant relationship with self-esteem(r=-.64, p<.001), emotional regulation ability(r=-.61, p<.001) and perceived stress(r=.54, p<.001). The factors affecting mental health were self-esteem(β=.46, p<.001), emotional regulation ability(β=-.37, p<.001), negative perceived stress(β=.17, p=.001) ; the explanatory power of the model was 60.0%. Therefore, it will be necessary to develop a program that can help high school students improve their self-esteem and control their negative emotions in order to promote their mental health.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.97-109
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• 2022

This study analyzed successful cases of using metaverse in a reality where interest in metaverse is increasing. The use of Metaverse is mainly used in companies to explore its industrial potential or government agencies strive for policy support, but the possibility of application in educational institutions has another meaning. We tried to find the success factors and future implications by analyzing actual cases of using metaverse at university entrance ceremonies. As a result of analyzing the case of S University in Asan, Chungcheongnam-do's metaverse entrance ceremony, it was determined that the university's first metaverse entrance ceremony could be counted as a very meaningful success story. Specifically, on the technical level, it stood out that the existing metaverse technology and the new technology for the event were properly harmonized. At the organizational level, it is meaningful that the internal organization's resources were efficiently utilized based on previous experiences. On the environmental level, the COVID19 environment and the MZ generation. It was analyzed that the social change of going to college contributed to the planning and success of the metaverse entrance ceremony. As a result, it is judged that the successful use of the resources possessed by a clear goal is the success factor of the metaverse entrance ceremony.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.189-200
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• 2022

Ground subsidence on urban roads is a social issue that can lead to human and property damages. Therefore, it is crucial to detect underground cavities in advance and repair them. Underground cavity detection is mainly performed using ground penetrating radar (GPR) surveys. This process is time-consuming, as a massive amount of GPR data needs to be interpreted, and the results vary depending on the skills and subjectivity of experts. To address these problems, researchers have studied automation and quantification techniques for GPR data interpretation, and recent studies have focused on deep learning-based interpretation techniques. In this study, we described a hyperbolic event detection process based on deep learning for GPR data interpretation. To demonstrate this process, we implemented a series of algorithms introduced in the preexisting research step by step. First, a deep learning-based YOLOv3 object detection model was applied to automatically detect hyperbolic signals. Subsequently, only hyperbolic signals were extracted using the column-connection clustering (C3) algorithm. Finally, the horizontal locations of the underground cavities were determined using regression analysis. The hyperbolic event detection using the YOLOv3 object detection technique achieved 84% precision and a recall score of 92% based on AP50. The predicted horizontal locations of the four underground cavities were approximately 0.12 ~ 0.36 m away from their actual locations. Thus, we confirmed that the existing deep learning-based interpretation technique is reliable with regard to detecting the hyperbolic patterns indicating underground cavities.

• The Journal of the Acoustical Society of Korea
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• v.42 no.3
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• pp.189-202
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• 2023

In this study, the acoustic performance was analyzed by architectural shapes of the hall. There are four architectural shapes of halls. They are rectangular, horseshoe, surround, and fan-shape. Eight acoustic parameters were used to determine the acoustic performance. These are RT₆₀, EDT, C₈₀, BQI, LF, G_mid, G₁₂₅ and ITDG. First, measurement data of famous concert halls around the world were analyzed. The correlation coefficient R was obtained by regression analysis of the relationship between the subjective ranking of the halls and the acoustic parameters. It was found that BQI, G, and ITDG have higher correlation coefficients R. Also the average of acoustic parameters for each architectural shape were obtained. The total acoustic performance for each shape was calculated by using the correlation coefficient R as a weight for each acoustic parameters. As a result, rectangular halls and horseshoe halls showed good acoustical performances. Second, 3D models of each architectural shape were created and acoustic simulation had been performed. The simulation was performed by creating 3D models of each four shapes of concert halls with the same volume and sound absorption coefficient. Listening test was carried out using the sound source which is created from impulse responses of 3D model. As a result, rectangular hall and horseshoe hall showed the best performance however surround hall and fan-shaped hall showed relatively poor performance.

• Journal of The Korean Association For Science Education
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• v.43 no.2
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• pp.87-98
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• 2023

In this study, we investigated the change in science core competency perception of high school students and the reason for change when science inquiry classes were conducted using eight 'skills' of the 2015 revised science curriculum. Fifteen first-year high school students in Jeollanam-do participated in the science inquiry class of this study, and the class was conducted for 20 hours (5 hours a day for four days). The inquiry activities used in the class consisted of four activity stages (research problems, research methods, research results, and conclusions) and each stage was constructed to include at least one 'skill (Problem Recognition, Model Development and Use, Inquiry Design and Performance, Data Collection, Analysis and Interpretation, Mathematical Thinking and Computer Application, Conclusion and Evaluation, Evidence-based Discussion and Demonstration, and Communication)'. As a result of the study, students' perception of the five science core competencies increased statistically significantly at the significance level of 0.01 through inquiry classes and more than 93% of students recognized that their science core competencies improved through the classes. However, since the class of this study was conducted for a small number of students, it is difficult to generalize the effect of the class, and so it is necessary to conduct a quantitative study for many students.

• Korean Journal of Animal Reproduction
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• v.24 no.4
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• pp.419-428
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• 2000

Leptin, the product of obese (ob) gene, is an adipocyte-derived satiety factor that plays a major role in the regulation of food intake, energy homeostasis, body weight, reproductive physiology and neuropeptide secretion. The present study was designed to generate transgenic mice expressing antisense mouse ob (mob) gene. Total RNA was extracted from the adipose tissues of mouse, then reverse transcription was performed. The 303 and 635 bp fragments of anti I and II cDNAs were amplified from mob cDNAs by PCR. The two mob cDNAs were reversely ligated into between adipose tissue specific aP2 promote and SV40 poly(A) site. Transgenic mice carrying two different kinds of antisense mob transgenes were generated by DNA microinjection into pronucleus. Total 14 transgenic mice were born, and the 4 and 5 founder lines of the transgenic mice with anti I and II transgenes were respectively established. Antisense mRNA expression was detected in transgenic F$_1$ mice by RT-PCR analysis. This result suggests that the transgenic mice expressing antisense mob mRNA may be useful as an animal disease model to be obesity caused by decreased amount of leptin secretion.

• Journal of Veterinary Science
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• v.23 no.1
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• pp.2.1-2.18
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• 2022

Background: Co-infections of the porcine reproductive and respiratory syndrome virus (PRRSV) and the Haemophilus parasuis (HPS) are severe in Chinese pigs, but the immune response genes against co-infected with 2 pathogens in the lungs have not been reported. Objectives: To understand the effect of PRRSV and/or HPS infection on the genes expression associated with lung immune function. Methods: The expression of the immune-related genes was analyzed using RNA-sequencing and bioinformatics. Differentially expressed genes (DEGs) were detected and identified by quantitative real-time polymerase chain reaction (qRT-PCR), immunohistochemistry (IHC) and western blotting assays. Results: All experimental pigs showed clinical symptoms and lung lesions. RNA-seq analysis showed that 922 DEGs in co-challenged pigs were more than in the HPS group (709 DEGs) and the PRRSV group (676 DEGs). Eleven DEGs validated by qRT-PCR were consistent with the RNA sequencing results. Eleven common Kyoto Encyclopedia of Genes and Genomes pathways related to infection and immune were found in single-infected and co-challenged pigs, including autophagy, cytokine-cytokine receptor interaction, and antigen processing and presentation, involving different DEGs. A model of immune response to infection with PRRSV and HPS was predicted among the DEGs in the co-challenged pigs. Dual oxidase 1 (DUOX1) and interleukin-21 (IL21) were detected by IHC and western blot and showed significant differences between the co-challenged pigs and the controls. Conclusions: These findings elucidated the transcriptome changes in the lungs after PRRSV and/or HPS infections, providing ideas for further study to inhibit ROS production and promote pulmonary fibrosis caused by co-challenging with PRRSV and HPS.

• Korea Trade Review
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• v.43 no.5
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• pp.25-45
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• 2018

This paper estimates the export losses of the Korean domestic automobile industry due to US trade pressure and its economic ripple effects. Using the HS 6 digit tariff and export data from 2010 to 2017, this paper estimates the tariff elasticity of Korea's US automobile exports against a US tariff increase by applying the Poisson Pseudo maximum likelihood estimation method. After estimating Korea's export losses to the US in three trade pressure scenarios, we estimate its impact on Korean domestic production, value-added and job creation by applying the tariff impact accumulation model based on the industry input-output analysis. Empirical results show that the impact of 25% global tariff by the US on the Korean domestic economy is estimated to result in $30.8 billion in export losses for the five years from 2019 to 2023, about 300 thousand job losses, 88.0 trillion in production inducement losses, and 24.0 trillion in value-added inducement losses. The impacts of withdrawal of the automobile tariff concession are estimated at $4.27 billion export losses and 41.7 thousand job losses. A 15% tariff rate on automobile parts for 3 years is estimated to result in $1.93 billion export losses and 18.7 thousand job losses.