• 지역과문화
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• v.7 no.2
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• pp.113-132
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• 2020

This study explored ways to make tourism resources based on the historical significance and major legacies of Yesan Imjon Fortress and Hongju Juryu Fortress, the center of the war where the core leadership of Baekje Restoration War was located. After the collapse of Baekje, it looked at the process of the restoration war centered on Imjon Fortress, the main characters, Imjon Fortress and Juryu Fortress, and the legends related to the restoration war. The tourism value of Baekje Restoration War is highlighted in terms of location identity and dark tourism. After reviewing cases of similar characteristics to the Baekje Restoration War, the method of tourism resourceization was presented. The elements of resourceization include characters, battles, relics, places, and name legends. Reproduction strategy, experience strategy, hard branding strategy and soft branding strategy were presented. As an example of the reenactment strategy, the Baekgang Battle reenactment event was presented. Experience strategies include walking and Baekje pottery. As for the hard-branding strategy, installation of sculptures of major characters and upgrading of tourist information signs were suggested. Soft branding strategies raised the need for logo marks, catch phrases, character products, video contents, and story maps through the branding of fortresses related to the Baekje Restoration War.

• Journal of Practical Engineering Education
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• v.14 no.1
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• pp.37-48
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• 2022

This study analyzed the effect of internal audit on the performance of the IATF 16949 automotive quality management system to understand the internal audit of companies and propose measures to activate the company's internal audit process. It was identified with the empirical analysis that 'The internal auditor competence, internal audit planning, internal audit implementation, infrastructure, culture/environment, and CEO support' to characterize IATF 16949 internal audit of automotive quality management system affects the internal performance and business performance of the company. In addition, I checked the size of the company and the period of certification period as moderating variables according to the sales based on the presented as factors that can improve the performance of the company, and how the moderating effects are seen in the relationship with the performance of the organization. I did analysis of technical statistics, exploratory factors, reliability, and multi-regression analysis with SPSS program. I summarized the results of the study, as a result of that, it was found that the internal audit planning, internal audit implementation, culture/ environment, and CEO support of independent variables affected the parameter and dependent variables (the internal performance and management performance of companies).

• Journal of The Korean Association For Science Education
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• v.42 no.4
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• pp.429-438
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• 2022

In this study, we propose a way to improve science teacher expertise through infographics creation teacher training program by analyzing the infographics types focusing on the Earth Science subject of the 2015 revised curriculum, and inspecting the teachers' utilization of graphic tools. The data visualization characteristics of Earth Science textbooks were analyzed, the execution results of the infographics creation teacher training program were presented, and a survey on science teachers' change in perception and competency of infographics. As a result of the Earth Science textbook analysis, diagram-type, map-type, and comparative analysis-type infographics were frequently used, and were mainly presented as text-assisted-type infographics. The infographics creation teacher training program was conducted five times for 112 science teachers to create the complete, text-assisted, incomplete, and gradient-type infographics. Incomplete infographics for development of evaluation questions were most needed. Although many science teachers recognize the importance of infographics, they lacked the competency to create high-quality infographics because there were no training opportunities for infographics creation. After completing the training, 74.1% of teachers felt that the quality of developments of supplementary textbooks and evaluation questions had improved, and answered that it was helpful in re-educating knowledge and improving teaching-learning methods. Based on the research results, ways to improve science teacher expertise through infographics creation teacher training program were suggested.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.274-284
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• 2022

To use kenaf (Hibiscus cannabinus L.) as a fiber and livestock feed, a high-yielding variety needs to be identified. For this, accurate phenotyping of plant height is required for this breeding purpose due to the strong relationship between plant height and yield. Plant height can be estimated using RGB images from unmanned aerial vehicles (UAV-RGB) and photogrammetry based on Structure from Motion (SfM) algorithms. In kenaf, accurate measurement of height is limited because kenaf stems have high flexibility and its height is easily affected by wind, growing up to 3 ~ 4 m. Therefore, we aimed to identify a method suitable for the accurate estimation of plant height of kenaf and investigate the feasibility of using the UAV-RGB-derived plant height map. Height estimation derived from UAV-RGB was improved using multi-point calibration against the five different wooden structures with known heights (30, 60, 90, 120, and 150 cm). Using the proposed method, we analyzed the variation in temporal height of 23 kenaf cultivars. Our results demontrated that the actual and estimated heights were reliably comparable with the coefficient of determination (R²) of 0.80 and a slope of 0.94. This method enabled the effective identification of cultivars with significantly different heights at each growth stages.

• Microbiology and Biotechnology Letters
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• v.50 no.3
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• pp.414-421
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• 2022

In this study, we isolated Weizmannia ginsengihumi LGHNH (KCTC 14462BP) from 30-year-old wild Panax ginseng C.A. Meyer and elucidated the characteristics of the isolated bacterium and its industrial potential as an anti-aging material. W. ginsengihumi LGHNH was investigated to produce indole-3-acetic acid (IAA), a plant growth-promoting hormone (1.38 ㎍/ml to 2.22 ㎍/ml). We also confirmed the existence of bioconversion activity via the comparison of the ginsenoside content before and after fermentation. As for the converted minor ginsenoside, Rg2(R), Rg4, Rg6, Rg3(S), Rg3(R), Rk1, Rg5, Rh1(R), Rk3 and Rh4 are known to have high bioavailability and various skin effects. We measured mitochondrial membrane potential and ATP biosynthesis to elucidate W. ginsengihumi LGHNH cultured product (WCP) as an anti-aging material. As a result, the mitochondrial membrane potential in HaCaT cells with UVB decreased to 39.3% compared to the unirradiated group, but was recovered to 57.3% and 58.1% by 0.001% (v/v) and 0.01% (v/v) WCP, respectively. In addition, we measured mitochondrial ATP biosynthesis. It decreased to 94.3% compared to the unirradiated group with UVB, but was recovered to 105.3% and 105.7% by 0.001% (v/v) and 0.01% (v/v) WCP.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.57-69
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• 2023

Early morning delivery possesses distinct characteristics that differentiate it from standard delivery services. This service typically involves delivering products to customers during the early morning hours, primarily before 7 AM. While online early morning delivery offers various advantages from a customer perspective, it also presents challenges that sellers and online shopping companies need to overcome. The early morning delivery market is experiencing significant growth in the online food retail sector, incorporating both PC-based online shopping and mobile shopping. The objective of this research is to identify the factors influencing customer satisfaction and the intention to reuse in the context of early morning delivery for online shopping. To model the online shopping environment with early morning delivery, independent factors were categorized into three types: System Properties, Product Characteristics, and Delivery Characteristics. This study examined the relationships among these three independent factors, the mediating factor of customer satisfaction, and the dependent variable of the intention to reuse. To conduct this research, empirical validation of the research hypotheses was carried out using the final dataset for analysis. Within this study, the previously explored System Properties, Product Characteristics, and Delivery Characteristics were established. Summarizing the findings of the analysis, it was discovered that System Properties and Product Characteristics played a significant role in determining the quality of early morning delivery services for online shopping. While product diversity and convenience had a positive impact, it is noteworthy that Delivery Characteristics did not influence customer satisfaction. Consequently, it can be concluded that there is no effect on the intention to reuse.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.387-398
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• 2023

The COVID-19 outbreak has significantly impacted human lifestyles and patterns. It was recommended to avoid face-to-face contact and over-crowded indoor places as much as possible as COVID-19 spreads through air, as well as through droplets or aerosols. Therefore, if a person who has contacted a COVID-19 patient or was at the place where the COVID-19 patient occurred is concerned that he/she may have been infected with COVID-19, it can be fully expected that he/she will search for COVID-19 symptoms on Google. In this study, an exploratory data analysis using deep learning models(DNN & LSTM) was conducted to see if we could predict the number of confirmed COVID-19 cases by summoning Google Trends, which played a major role in surveillance and management of influenza, again and combining it with data on the number of confirmed COVID-19 cases. In particular, search term frequency data used in this study are available publicly and do not invade privacy. When the deep neural network model was applied, Seoul (9.6 million) with the largest population in South Korea and Busan (3.4 million) with the second largest population recorded lower error rates when forecasting including search term frequency data. These analysis results demonstrate that search term frequency data plays an important role in cities with a population above a certain size. We also hope that these predictions can be used as evidentiary materials to decide policies, such as the deregulation or implementation of stronger preventive measures.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.153-173
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• 2022

This study analyzes yelp's online restaurant reviews written in 2019 and explores the factors influencing the decision of the usefulness for online reviews in the restaurant consumption decision process. Specifically, factors expected to affect review usefulness are classified according to the Elaboration Likelihood model. Also, it is assumed that the price range of the restaurant would have a moderating role. For the analysis, datasets provided by yelp.com in February 2020 are used. Among the datasets, online reviews of businesses located in Nevada in the US and belonging to the Food and Restaurant categories are targeted. As a result of the negative binomial regression analysis, it is confirmed that the central cues including review depth and readability and the peripheral cues including review consistency, reviewer popularity, and reviewer exposure positively affect the review usefulness. It is also confirmed that the influences of antecedents that affect the review restaurant prices moderate the effect of the central and peripheral cues on the review usefulness. It also provides implications for the need for price-differentiated review management strategies by review platforms and restaurant businesses.

• Journal of Science Education
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• v.47 no.1
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• pp.52-62
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• 2023

This study examines how prospective earth science teachers perceive the concept of "equilibrium" and "interaction between Earth's spheres" in understanding Earth's radiative equilibrium and tries to identify their misconceptions. For this purpose, a questionnaire was designed and put to them to look into their thought flow based on the items that appeared in the national level evaluation. As a result of analyzing their answers, even though all the prospective teachers correctly described the concept of radiative equilibrium, about 90% of them did not apply the concept of radiative equilibrium to the new environment of the Earth without atmosphere. They do not seem to be able to smoothly derive the concept of a new 'interaction' between the changed regions and a new 'equilibrium' that will be reached over a long period of time. In this respect, it is likely that the textbooks had some influence on the formation of their concepts. In particular, high school Earth Science textbooks describe the Earth's radiation equilibrium in a quantitative manner, focusing on the heat budget of the equilibrium state rather than the process of reaching radiation equilibrium. Such an approach of textbooks might be an obstacle to fostering students into creative convergence-type talents pursued in the 2015 revised curriculum. Meanwhile, in order to eliminate the misconceptions of students often found in the understanding of Earth's radiation equilibrium, this study suggests that the core concepts need to be dealt with more attention even in college courses for training prospective teachers.

• Journal of The Korean Association For Science Education
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• v.43 no.3
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• pp.237-251
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• 2023

This study explores the possibility of automated scoring for scientific graph answers by designing an automated scoring model using convolutional neural networks and applying it to students' kinematics graph answers. The researchers prepared 2,200 answers, which were divided into 2,000 training data and 200 validation data. Additionally, 202 student answers were divided into 100 training data and 102 test data. First, in the process of designing an automated scoring model and validating its performance, the automated scoring model was optimized for graph image classification using the answer dataset prepared by the researchers. Next, the automated scoring model was trained using various types of training datasets, and it was used to score the student test dataset. The performance of the automated scoring model has been improved as the amount of training data increased in amount and diversity. Finally, compared to human scoring, the accuracy was 97.06%, the kappa coefficient was 0.957, and the weighted kappa coefficient was 0.968. On the other hand, in the case of answer types that were not included in the training data, the s coring was almos t identical among human s corers however, the automated scoring model performed inaccurately.