• Journal of the Korean Society of Earth Science Education
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• v.14 no.3
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• pp.277-291
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• 2021

This study is to implicate for analyzing the expertise of Education for Sustainable Development (ESD) dealing with science-related social issues by reorganizing educational materials on climate crisis topics and analyzing in-depth class performance preparation and actual class by pre-service science teachers. As a result of the study, it was found that pre-service science teachers have the expertise to analyze the curriculum horizontally and extract subject-integrated elements, but it is difficult to perform convergent science classes by incorporating them into the social problem-solving process in actual classes. In addition, it was analyzed that through this study, pre-service science teachers came to think about the importance of having their own specialized expertise when they become school teachers through preparation for their classes integrating science-related social issues. Through the application of the reciprocal peer teaching applied in this study, giving pre-service science teachers of various expertise an opportunity to experience the process of designing and implementing integrated science classes while sharing their expertise will greatly help them improve their convergence education.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.307-332
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• 2022

One of the most intensively conducted research areas in business application study is a bankruptcy prediction model, a representative classification problem related to loan lending, investment decision making, and profitability to financial institutions. Many research demonstrated outstanding performance for bankruptcy prediction models using artificial intelligence techniques. However, since most machine learning algorithms are "black-box," AI has been identified as a prominent research topic for providing users with an explanation. Although there are many different approaches for explanations, this study focuses on explaining a bankruptcy prediction model using a counterfactual example. Users can obtain desired output from the model by using a counterfactual-based explanation, which provides an alternative case. This study introduces a counterfactual generation technique based on a genetic algorithm (GA) that leverages both domain knowledge (i.e., causal feasibility) and feature importance from a black-box model along with other critical counterfactual variables, including proximity, distribution, and sparsity. The proposed method was evaluated quantitatively and qualitatively to measure the quality and the validity.

• Journal of agricultural medicine and community health
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• v.47 no.1
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• pp.14-26
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• 2022

Objectives: Handwashing is one of the most effective methods to prevent the spread of infectious diseases. This study assessed the related factors and reasons for not practicing handwashing at school among adolescents. Methods: We analyzed data collected from 57,303 adolescents who participated in the 15th Korea Youth Risk Behavior Survey 2019. Results: The proportions of not washing hands "before meals at school" and "after using the toilet at school" were 15.9% and 4.4%, respectively. The adjusted odds ratio for not washing hands before meals at school was significantly higher in girls (Odds Ratio [OR]=1.52, 95% Confidence Intervals [CI]=1.42-1.63), metropolitan city (OR=1.32, 95% CI=1.11-1.56), city (OR=1.29, 95% CI=1.08-1.54), higher grade, higher academic performance, lower economic status, not handwashing at home (OR=14.36, 95% CI=13.37-15.42), and without annual personal hygiene education (OR=1.41, 95% CI=1.33-1.49). Reasons for not washing hands at school among adolescents who do not wash their hands before meals at school included 'it is bothersome (52.3%)', 'there is no soap or hand sanitizer (13.8%)', and 'I do not feel the need (9.5%)'. Conclusions: Improving handwashing before meals at school among adolescents requires raising awareness of the importance of handwashing before meals and establishing a suitable environment and handwashing-encouraging culture.

• Journal of Korea Port Economic Association
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• v.37 no.3
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• pp.35-53
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• 2021

Over the past 20 years, Korea's number of international passengers and freight transportation records has increased by 8.6% per year, respectively. However, despite the development of sea lanes and increased voyages, there have been constant calls for improving the inefficient management of international passenger ports. Hence, this paper presents improvements and further directions for international passenger port management. Focusing on the Incheon International passenger port as a representative case study, the main results show that the most important, urgent, possible measures for improving the port management include (i) the expansion of customs personnel and implementation of a 24-hours customs clearance system in operation, (ii) installation of buffer facilities between the ferry and ferry cargo and establishment of hinterland specialized in car ferry freight in a facility, and (iii) clear standards for cost-bearing subjects and limitation of high cost related to terminal use in institution. These results imply the need for government policy access and investment reflecting stakeholder opinions at various levels, such as operation, facilities, institution, and so forth, for efficient management of international passenger ports.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.485-496
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• 2022

This study is for the software implementation to generate atmospheric and surface reflectance products from RapidEye satellite imagery. The software is an extension based on Orfeo Toolbox (OTB) and an open-source remote sensing software including calibration modules which use an absolute atmospheric correction algorithm. In order to verify the performance of the program, the accuracy of the product was validated by a test image on the Radiometric Calibration Network (RadCalNet) site. In addition, the accuracy of the surface reflectance product generated from the KOMPSAT-3A image, the surface reflectance of Landsat Analysis Ready Data (ARD) of the same site, and near acquisition date were compared with RapidEye-based one. At the same time, a comparative study was carried out with the processing results using QUick Atmospheric Correction (QUAC) and Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) tool supported by a commercial tool for the same image. Similar to the KOMPSAT-3A-based surface reflectance product, the results obtained from RapidEye Extension showed accuracy of agreement level within 5%, compared with RadCalNet data. They also showed better accuracy in all band images than the results using QUAC or FLAASH tool. As the importance of the Red-Edge band in agriculture, forests, and the environment applications is being emphasized, it is expected that the utilization of the surface reflectance products of RapidEye images produced using this program will also increase.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.429-440
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• 2021

With the recent development of deep convolutional neural network learning, deep learning techniques applied to single image super-resolution are showing good results. One of the existing deep learning-based super-resolution techniques is RDN(Residual Dense Network), in which the initial feature information is transmitted to the last layer using residual dense blocks, and subsequent layers are restored using input information of previous layers. However, if all hierarchical features are connected and learned and a large number of residual dense blocks are stacked, despite good performance, a large number of parameters and huge computational load are needed, so it takes a lot of time to learn a network and a slow processing speed, and it is not applicable to a mobile system. In this paper, we use the residual dense structure, which is a continuous memory structure that reuses previous information, and the residual dense channel attention block using the channel attention method that determines the importance according to the feature map of the image. We propose a method that can increase the depth to obtain a large receptive field and maintain a concise model at the same time. As a result of the experiment, the proposed network obtained PSNR as low as 0.205dB on average at 4× magnification compared to RDN, but about 1.8 times faster processing speed, about 10 times less number of parameters and about 1.74 times less computation.

• Korean small business review
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• v.43 no.4
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• pp.173-209
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• 2021

Start-up accelerators are a new type of investor that provide mentoring, education and seed capital to start-ups for a fixed duration and receive a certain stake in them in return. They help start-ups achieve successful commercialization. With increase in performance visibility, the number of private and public sector accelerators rose across domestic and international markets. Private sector accelerators are established and operated by private entities while public sector accelerators are established and operated by the government. Both play complementary roles that are becoming increasingly important to start-ups. Therefore, this study aims to examine the differences in major operational goals and investment determinants between private and public sectors and to understand their implications. The results show that the private sector prioritizes profit generation through the investment, while the public sector aims to contribute to the development of high-growth start-ups, and create region-specific and technology-specific start-up ecosystems. Additionally, both groups consider customer needs the most important determinant. Public groups are more conservative in investments and tend to place importance on objective indicators such as patents, partners, mentors, and co-founders. Conversely, private groups value the capabilities of founders and their ease of collaboration with accelerators. These findings can help start-ups get support from public or private accelerators more easily. It will also help public and private accelerators refine the criteria for selecting start-ups.

• Journal of Korea Entertainment Industry Association
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• v.14 no.4
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• pp.133-144
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• 2020

This study is a new proposal for the methods of actor training and role creation in the contemporary theater and an approach to the practical utilization of the performer, regarding the actor's 'presence' as the essence of living arts, a peculiarity of theater. As the method for this, this study sorts out Vakhangov and Mikhail Chekhov's elements of acting techniques and at the same time, allows an easier approach to the theoretical concept based on the performance records found in the developmental process. The magic realism and the technique of acting discussed in priority in this study emphasize the importance of the exploration and realization of artistic inspiration in everyday life, the actor's imagination and image, and unconsciousness as a method for creating new actors and diversifying their roles. When their common views are summed up, the goals to achieve include a study of a creative method in which outer form and inner truth are combined and the implementation of a new system for creating the individual actor's originality. This study would classify the similarities and differences found through this, reveal the limit of practical efficacy and propose it as a universal method for creating the roles, asking for the actor's voluntary training and active attitudes.

• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.439-446
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• 2020

This study aimed at developing a convergence education program about skin care and social welfare with the purpose of operating liberal arts courses to foster the creativity and character building of university students and the development findings are as follows. The name of the developed course is "beauty treatment welfare and community service" and details were developed for the course overview, goals of the course, textbooks, course management, assignments, and assessment. The lesson goals of this course are character building by fostering creative and outstanding individuals demanded by the society and equipped with the basic knowledge of majors like skin care and social welfare as well as the capability to share and consider through service learning related education for the increase in convergence critical thinking skills and the convergence of skin care and social welfare. The details of the course comprised of introduction about the course, understanding the concept of convergence, understanding the concepts of skin care and social welfare, convergent thinking education and practicum, and education about service learning performance sharing meeting. The service learning is targeted on the socially disadvantaged, such as children and elders, and students can engage in service twice a week with 3 hours for each service session. The assessment is evaluated with midterm (30%), final exam (30%), report (20%), and attendance (20%). This study stresses importance on the development of a convergence education program for skin care and social welfare, which are still undeveloped while convergence education is expanding in university, and with this research as the start, it is anticipated for various approaches to be actively implemented about convergence education in the field of beauty treatment.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.139-159
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• 2022

As interest in health functional foods has increased since COVID-19, the importance of imported food safety inspections is growing. However, in contrast to the annual increase in imports of health functional foods, the budget and manpower required for inspections for import and export are reaching their limit. Hence, the purpose of this study is to propose a machine learning model that efficiently detects unsuitable food suitable for the characteristics of data possessed by government offices on imported food. First, the components of food import/export inspections data that affect the judgment of nonconformity were examined and derived variables were newly created. Second, in order to select features for the machine learning, class imbalance and nonlinearity were considered when performing exploratory analysis on imported food-related data. Third, we try to compare the performance and interpretability of each model by applying various machine learning techniques. In particular, the ensemble model was the best, and it was confirmed that the derived variables and models proposed in this study can be helpful to the system used in import/export inspections.