• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.37-55
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• 2023

With the development of electronic journals and the emergence of various interdisciplinary studies, the selection of journals for publication has become a new challenge for researchers. Even if a paper is of high quality, it may face rejection due to a mismatch between the paper's topic and the scope of the journal. While research on assisting researchers in journal selection has been actively conducted in English, the same cannot be said for Korean journals. In this study, we propose a system that recommends Korean journals for submission. Firstly, we utilize SBERT (Sentence BERT) to embed abstracts of previously published papers at the document level, compare the similarity between new documents and published papers, and recommend journals accordingly. Next, the order of recommended journals is determined by considering the similarity of abstracts, keywords, and title. Subsequently, journals that are similar to the top recommended journal from previous stage are added by using a dictionary of words constructed for each journal, thereby enhancing recommendation diversity. The recommendation system, built using this approach, achieved a Top-10 accuracy level of 76.6%, and the validity of the recommendation results was confirmed through user feedback. Furthermore, it was found that each step of the proposed framework contributes to improving recommendation accuracy. This study provides a new approach to recommending academic journals in the Korean language, which has not been actively studied before, and it has also practical implications as the proposed framework can be easily applied to services.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.381-386
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• 2023

Many existing test case generation researchers extract test cases from models. However, research on generating test cases from natural language requirements is required in practice. For this purpose, the combination of natural language analysis and requirements engineering is very necessary. However, Requirements analysis written in Korean is difficult due to the diverse meaning of sentence expressions. We research test case generation through natural language requirement definition analysis, C3Tree model, cause-effect graph, and decision table steps as one of the test case generation methods from Korean natural requirements. As an intermediate step, this paper generates test cases from C3Tree model-based decision tables using meta-modeling. This method has the advantage of being able to easily maintain the model-to-model and model-to-text transformation processes by modifying only the transformation rules. If an existing model is modified or a new model is added, only the model transformation rules can be maintained without changing the program algorithm. As a result of the evaluation, all combinations for the decision table were automatically generated as test cases.

• Journal of Life Science
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• v.33 no.8
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• pp.632-638
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• 2023

A soybean cultivar with a green seed coat and cotyledon contains high levels of lutein, which is beneficial for eye health. Plus, antinutritional components such as lipoxygenase, Kunitz trypsin inhibitor (KTI), lectin and stachyose exist in the mature seed. The genetic elimination of these antinutritional factors is a necessary step in green soybean breeding. This research was conducted to improve a new green soybean line with the green cotyledon and tetra null genotype (lox1lox2lox3tilers2) in terms of lipoxygenase, KTI, lectin and stachyose. We used five germplasms to develop a breeding population. A total of 69 F₂ seeds were obtained from the cross of parent 1 and parent 2, and from those, 21 F₂ seeds were selected that had the green seed coat color, and which were free of lectin protein. Next, four F₂ plants with the green seed coat and tetra null genotype were selected from the breeding population derived from four genotypes. The absence of lipoxygenase, KTI and lectin proteins was confirmed in the F₅ strain. The breeding line has a green seed coat, green cotyledon and white hilum color. The 100-seed weight and stachyose content for the breeding line were 30.7 g and 2.40 g/kg, respectively. The line selected in this study could be used as a cultivar or parent to improve colored soybean cultivars through the removal of antinutritional components such as lip- oxygenase, KTI, lectin and stachyose.

• Journal of Korean Elementary Science Education
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• v.42 no.3
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• pp.409-420
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• 2023

This study aims to investigate the impact of science classes employing creative science drama on elementary school students' academic achievement and attitudes toward science during the final step of elementary science classes. The creative science drama used in this study is a class-closing activity wherein the teacher provides a basic script for the learning topic and then allows students to complete the rest of the story using their assignment. It devised a creative science drama class based on the research of Yoon (2016), and the contents of this study were centered on the use of magnets and the appearance of the Earth in the first semester of third grade. Students in their third year at H Elementary School in Gyeonggi-do were the subject of this study. The results showed that scientific achievement through science drama in the experimental class was improved, with a statistically significant difference. However, ANCOVA analysis revealed no statistically significant differences in attitudes toward science. Moreover, there was no statistically significant difference in scientific drama perception. Interviews with students in the experimental class applying science drama revealed that students found difficulty in writing science drama scripts and that coordinating and reaching a mutually acceptable opinion in group activities required the most discussion and cooperation. However, many of them stated that the experience of scientific drama was enjoyable and informative, and since what they learned was transformed into a scientific drama, they remembered the lessons longer.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.159-172
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• 2023

In general, social problem-solving research aims to create important social value by offering meaningful answers to various social pending issues using scientific technologies. Not surprisingly, however, although numerous and extensive research attempts have been made to alleviate the social problems and issues in nation-wide, we still have many important social challenges and works to be done. In order to facilitate the entire process of the social problem-solving research and maximize its efficacy, it is vital to clearly identify and grasp the important and pressing problems to be focused upon. It is understandable for the problem discovery step to be drastically improved if current social issues can be automatically identified from existing R&D resources such as technical reports and articles. This paper introduces a comprehensive dataset which is essential to build a machine learning model for automatically detecting the social problems and solutions in various national research reports. Initially, we collected a total of 700 research reports regarding social problems and issues. Through intensive annotation process, we built totally 24,022 sentences each of which possesses its own category or label closely related to social problem-solving such as problems, purposes, solutions, effects and so on. Furthermore, we implemented four sentence classification models based on various neural language models and conducted a series of performance experiments using our dataset. As a result of the experiment, the model fine-tuned to the KLUE-BERT pre-trained language model showed the best performance with an accuracy of 75.853% and an F1 score of 63.503%.

• Journal of Korean Elementary Science Education
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• v.42 no.1
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• pp.194-209
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• 2023

This study aims to present implications for the appropriate establishment and development of a science-authorized textbook system through an understanding of the process of selecting science-authorized textbooks and analyzing the perception of teachers. Toward this end, this study conducted interviews with five elementary school teachers who participated in the science textbook selection process, surveys on 32 teachers, and analysis on the authors of the textbooks. The result demonstrated, first, that the "opinion gathering" stage was the most important one, and a council was formed in consideration of career and major. Moreover, the evaluation standard was reorganized and used according to the situation of the school. Second, in the process of opinion gathering, the teachers used a method for reviewing the entire textbook for each teacher. Inquiry activities and textbook composition (readability) were crucially considered as internal factors, and teaching and learning materials, such as videos, were deemed extremely important as external factors. The variable of the author, which is an indicator of the reliability and expertise of textbooks, was also recognized as vital. Third, the deliberation by the School Committee and the report by the principal were recognized as the administrative final step after selection. Finally, selecting the most suitable textbooks for each grade group was recognized as more important than arbitrarily unifying textbooks for the third and fourth grades and for the fifth and sixth grades.

• Journal of the Society of Disaster Information
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• v.19 no.2
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• pp.334-343
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• 2023

Purpose: In this study, the cavity data found through ground cavity exploration was combined with underground facilities to derive a correlation, and the ground subsidence prediction map was verified based on the AI algorithm. Method: The study was conducted in three stages. The stage of data investigation and big data collection related to risk assessment. Data pre-processing steps for AI analysis. And it is the step of verifying the ground subsidence risk prediction map using the AI algorithm. Result: By analyzing the ground subsidence risk prediction map prepared, it was possible to confirm the distribution of risk grades in three stages of emergency, priority, and general for Busanjin-gu and Saha-gu. In addition, by arranging the predicted ground subsidence risk ratings for each section of the road route, it was confirmed that 3 out of 61 sections in Busanjin-gu and 7 out of 68 sections in Sahagu included roads with emergency ratings. Conclusion: Based on the verified ground subsidence risk prediction map, it is possible to provide citizens with a safe road environment by setting the exploration section according to the risk level and conducting investigation.

• Journal of the Korean Geotechnical Society
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• v.24 no.2
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• pp.67-75
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• 2008

It is interesting to note that distinct element method has been used extensively to model the response of micro and discontinuous behavior in geomechanics. Impressive advances related to response of distinct particles have been conducted and there were difficulties in considering fluid effect simultaneously. Current distinct element methods are progressively developed to solve particle-fluid coupling focused on fluid flow through soil, rock or porous medium. In this research, numerical simulations of fluid injection into particulate materials were conducted to observe cavity initiation and propagation using distinct element method. After generation of initial particles and wall elements, confining stress was applied by servo-control method. The fluid scheme solves the continuity and Navior-Stokes equations numerically, then derives pressure and velocity vectors for fixed grid by considering the existence of particles within the fluid cell. Fluid was injected as 7-step into the assembly in the x-direction from the inlet located at the center of the left boundary under confining stress condition, $0.1MP{\alpha}\;and\;0.5MP{\alpha}$, respectively. For each simulation, movement of particles, flow rate, fluid velocity, pressure history, wall stress including cavity initiation and propagation by interaction of flulid-paricles were analyzed.

• Geophysics and Geophysical Exploration
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• v.26 no.2
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• pp.37-51
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• 2023

The ground roll is the most common coherent noise in land seismic data and has an amplitude much larger than the reflection event we usually want to obtain. Therefore, ground roll suppression is a crucial step in seismic data processing. Several techniques, such as f-k filtering and curvelet transform, have been developed to suppress the ground roll. However, the existing methods still require improvements in suppression performance and efficiency. Various studies on the suppression of ground roll in seismic data have recently been conducted using deep learning methods developed for image processing. In this paper, we introduce three models (DnCNN (De-noiseCNN), pix2pix, and CycleGAN), based on convolutional neural network (CNN) or conditional generative adversarial network (cGAN), for ground roll suppression and explain them in detail through numerical examples. Common shot gathers from the same field were divided into training and test datasets to compare the algorithms. We trained the models using the training data and evaluated their performances using the test data. When training these models with field data, ground roll removed data are required; therefore, the ground roll is suppressed by f-k filtering and used as the ground-truth data. To evaluate the performance of the deep learning models and compare the training results, we utilized quantitative indicators such as the correlation coefficient and structural similarity index measure (SSIM) based on the similarity to the ground-truth data. The DnCNN model exhibited the best performance, and we confirmed that other models could also be applied to suppress the ground roll.

• Journal of Science Education
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• v.46 no.2
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• pp.195-211
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• 2022

In this study, we explored the meaning of astronomical observation activities of five earth science teachers through in-depth interviews. Semi-structured interviews were conducted after providing a questionnaire based on Seidman's three-step process of interview. By analyzing the interview transcript, the educational implications inherent in astronomical observation activities were extracted. Teachers have constructed systematic basis of observation and astronomy in the observational astronomy and laboratory class during their course in the teacher education institute. After they became in-service teachers, practical know-hows of astronomical observation activities in schools were developed with the help of colleagues. By designing and executing astronomical observation activities for students, teachers notice positive changes in the cognitive domain, affective domain, and career perception of the students. Hence, teachers consider that astronomical observation activities have great educational effects. In addition, astronomical activities appear to be very rewarding and satisfying experiences to teachers, by providing opportunities for having pride as an earth science teacher. However, teachers tend to find difficulties in operating astronomical observation activities in fields, due to both internal and external obstacles. It is found that the removal of internal obstacles is more important for teachers to attempt or to continue astronomical observation activities. In this sense, it is necessary to support teachers by providing timely training courses with related content, as well as opportunities to share their experiences within a peer group such as teachers' research society.