• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1195-1204
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• 2021

Recently, local torrential rain have become more frequent and severe due to abnormal climate conditions, causing a surge in human and properties damage including infrastructures along the river. In this study, water surface elevation prediction algorithm was developed using the LSTM (Long Short-term Memory) technique specialized for time series data among Machine Learning to estimate and prevent flooding of the facilities. The study area is Jamsu Bridge, the study period is 6 years (2015~2020) of June, July and August and the water surface elevation of the Jamsu Bridge after 3 hours was predicted. Input data set is composed of the water surface elevation of Jamsu Bridge (EL.m), the amount of discharge from Paldang Dam (m³/s), the tide level of Ganghwa Bridge (cm) and the number of tweets in Seoul. Complementary data were constructed by using not only structured data mainly used in precedent research but also unstructured data constructed through wordcloud, and the role of unstructured data was presented through comparison and analysis of whether or not unstructured data was used. When predicting the water surface elevation of the Jamsu Bridge, the accuracy of prediction was improved and realized that complementary data could be conservative alerts to reduce casualties. In this study, it was concluded that the use of complementary data was relatively effective in providing the user's safety and convenience of riverside infrastructure. In the future, more accurate water surface elevation prediction would be expected through the addition of types of unstructured data or detailed pre-processing of input data.

• Applied Chemistry for Engineering
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• v.33 no.3
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• pp.235-241
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• 2022

According to the World Water Development Report 2015 released by the United Nations, drinking water is expected to decrease by 40% by 2030. This does not mean that the amount of water decreases, but rather that the water source is contaminated due to environmental pollution. Because microbes are deeply related to water quality, the analysis of microbe is very important for water quality management. While the most common method currently used for microbial analysis is microscopic examination of the shape and feature after cell culture, as the gene analysis technology advances, quantitative polymerase chain reaction (qPCR) can be applied to the microscopic microbiological analysis, and the application method has been studied. Among them, a reverse transcription (RT) step enables the analysis of RNA by RT-PCR. Integrated cell culture (ICC)-qPCR shortens the test time by using it with microbial culture analysis, and viability qPCR can reduce the false positive errors of samples collected from natural water source. Multiplex qPCR for improved throughput, and microfluidic qPCR for analysis with limited amount of sample has been developed In this paper, we introduce the case, principle and development direction of the qPCR method applied to the analysis of microorganisms.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.913-924
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• 2022

In this paper, we presented a database construction of undersea images for the Habitats of Ecklonia cava and Sargassum and conducted an experiment for semantic segmentation using state-of-the-art (SOTA) models such as High Resolution Network-Object Contextual Representation (HRNet-OCR) and Shifted Windows-L (Swin-L). The result showed that our segmentation models were superior to the existing experiments in terms of the 29% increased mean intersection over union (mIOU). Swin-L model produced better performance for every class. In particular, the information of the Ecklonia cava class that had small data were also appropriately extracted by Swin-L model. Target objects and the backgrounds were well distinguished owing to the Transformer backbone better than the legacy models. A bigger database under construction will ensure more accuracy improvement and can be utilized as deep learning database for undersea images.

• 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 the Korean Applied Science and Technology
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• v.38 no.2
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• pp.423-433
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• 2021

The purpose of this study was to establish the concept of self-management in beauty service experts through two integrated research methods of open-ended questionnaires and focus group interview. For data collection, an open-ended questionnaire was conducted for 151 beauty service experts located in Seoul·Gyeonggi-do, and a focus group interview was conducted with 8 experts in beauty experts to collect data. Accordingly, the results derived through a series of research procedures are as follows. First, as a result of the inductive content analysis of the open questionnaire, the self-management of beauty service experts was derived into four types of intellectual management: health management, interpersonal management, appearance management, and technology management. Second, in the results of the focus group interview, the inductive content analysis was more validly supported, and the beauty service field-centered interview cases were dealt with in-depth, resulting in two additional attributes of contactless management and knowledge management. The results of this study can be used as basic data for establishing strategies for life as a successful professional of beauty service workers and developing self-management measurement tools for beauty service experts.

• Journal of the Korean Chemical Society
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• v.65 no.4
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• pp.268-278
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• 2021

The purpose of this study is to subdivide responsive teaching types proposed in the previous study in order to observe the change in the responsive teaching types in teacher educational programs, and to identify factors that impede changes in responsive teaching types. To this end, an educational program including introduction of responsive teaching, case analysis of responsive teaching, individual assignments and group discussions on facilitator type educational scenarios is provided for chemistry teachers who participated in a chemistry education course established in a graduate school of education. Based on previous research, when the teacher's teaching method was analyzed as evaluator, transfer, guide and facilitatore, a type that could not be classified was observed. In this study, responsive teaching types were added by adding two types: explorer and interpreter. In addition, through individual assignments and group discussion data, we could observe the factors that hinder teachers' responsive teaching changes. The obstacles that impede the change to responsive teaching were classified into teacher factors, student factors, and environmental factors. Among the obstacles, teacher factors include a belief in teacher-led instruction, a belief in the role of a teacher as a transfer of knowledge, a belief that the curriculum should be followed, a lack of understanding of the teacher about students, and a lack of the teacher's ability to lead student-led expansion. The student factor was distrust of the student's competence. Also, as an environmental factor, there was an educational environment such as multi-students class. Effective teacher education on responsive teaching can be achieved only when the perception related to these obstacles can be removed.

• Korean small business review
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• v.42 no.2
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• pp.117-137
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• 2020

We examine the current status of smart factory deployment and diffusion programs in Korea, and seek to promote manufacturing innovation from the perspective of SMEs. The main conclusions of this paper are as follows. First, without additional market creation and supply chain improvement, smart factories are unlikely to raise profitability leading to overinvestment. Second, new business models need to connect "manufacturing process efficiency" with "R&D" and "marketing" in value chain in smart factories. Third, when introducing smart factories, we need to focus on the areas where process-embedded technology is directly linked to corporate competitiveness. Based on the modularity-maturity matrix (Pisano and Shih, 2012) and the examples of U.S. Manufacturing Innovation Institute (MII), we establish the new smart factory deployment policy measures as follows. First, we shift our smart factory strategy from quantitative expansion to qualitative upgrading. Second, we promote by each sector the formation of industrial commons that help SMEs to jointly develop R&D, exchange standardized data and practices, and facilitate supplier-led procurement system. Third, to implement new technology and business models, we encourage partnerships, collaborations, and M&As between conventional SMEs and start-ups and business ventures. Fourth, the whole deployment process of smart factories is indexed in detail to identify the problems and provide appropriate solutions.

• Journal of the Korean Regional Science Association
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• v.38 no.4
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• pp.45-58
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• 2022

This study intends to compare the factors influencing the location of international schools on apartment sales and monthly rent prices for Songdo International School in Incheon, which has a history of more than 10 years. At the latest point, 10 years after the opening of the school, apartments in areas near international schools are divided into sales and monthly rent markets and analyzed. Songdo International City, designed as a planned city, was set as a spatial scope, and 2018-19, which is a relatively stable real estate period, was set as a temporal analysis period to avoid the overheating period of real estate after COVID-19. Considering the urban image of the "New Special Education Zone," such as the opening of Songdo Campus by private academies formed around international schools and domestic and foreign universities, the multiple regression model was applied based on the traditional Hedonic price model. As a result of the empirical analysis, first, differences in the price determinants of sales and monthly rent were confirmed. Second, the price influence of international schools was much higher than that of the variables. Third, the influence of international schools was more pronounced in the monthly rent market than in the sales market.

• Journal of Korean Elementary Science Education
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• v.41 no.4
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• pp.725-739
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• 2022

This study aims to analyze what elementary school pre-service teachers focused on and what challenges they faced in designing and producing a guided science inquiry program based on augmented reality (AR) and to provide some implications for teachers' professionalism and teacher education. To this end, focusing on the cases of pre-service teachers who designed and created AR-based guided inquiry programs, the researchers extracted and categorized the pre-service teachers' focus and challenges from the program design and production stages. As a result, in the program design stage, the pre-service teachers tried to construct scenarios that could promote students' active inquiry process. At the same time, drawing on the unique affordances of AR, the pre-service teachers focused on creating vivid visual data in a 3D environment and making meaningful connections between virtual and real-world activities. The pre-service teachers faced challenges in making use of the advantages of AR technology and designing an inquiry program due to a lack of background knowledge about CoSpaces, a content creation program. In the program production stage, the pre-service teachers tried to make their program easy to handle to improve students' concentration on inquiry activities. In addition, challenges of programming using CoSpaces were reported. Based on these results, educational implications were discussed in terms of the pedagogical uses of AR and teachers' professionalism in adopting AR in science inquiry.

• Journal of Bio-Environment Control
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• v.31 no.3
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• pp.152-162
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• 2022

This study developed simulation model for predicting the greenhouse interior environment using artificial intelligence machine learning techniques. Various methods have been studied to predict the internal environment of the greenhouse system. But the traditional simulation analysis method has a problem of low precision due to extraneous variables. In order to solve this problem, we developed a model for predicting the temperature inside the greenhouse using machine learning. Machine learning models are developed through data collection, characteristic analysis, and learning, and the accuracy of the model varies greatly depending on parameters and learning methods. Therefore, an optimal model derivation method according to data characteristics is required. As a result of the model development, the model accuracy increased as the parameters of the hidden unit increased. Optimal model was derived from the GRU algorithm and hidden unit 6 (r² = 0.9848 and RMSE = 0.5857℃). Through this study, it was confirmed that it is possible to develop a predictive model for the temperature inside the greenhouse using data outside the greenhouse. In addition, it was confirmed that application and comparative analysis were necessary for various greenhouse data. It is necessary that research for development environmental control system by improving the developed model to the forecasting stage.