• Korean Journal of Environmental Agriculture
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• v.40 no.4
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• pp.366-372
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• 2021

BACKGROUND: Ammonia is known as a precursor to fine particulate matter, and according to CAPSS, annual ammonia emissions in the agricultural sector were 249,777 tons as of 2018, accounting for about 79.0% of Korea's total ammonia emissions. In particular, ammonia emissions from agricultural land increased by 19,566 tons (10.2%) compared to the previous year. The Ministry of Environment is setting emission statistics using the ammonia emission coefficient developed in Korea in 2008, but researchers in the agricultural field regard it as a coefficient that does not reflect the reality of Korea's agricultural environment. Accordingly, in order to develop ammonia emission coefficients from the cultivation of apples and pears, Korea's representative fruit type, test agricultural land was set in Iksan, Jeollabuk-do. METHODS AND RESULTS: This study attempted to obtain the ammonia emission coefficient by the treatment of the composite fertilizer (N-P₂O₅-K₂O=12-7-9), and the flux was measured using a dynamic flow-through chamber method. As for the chamber, a total of 12 chambers were installed repeatedly in 4 zones and used to develop emission coefficients. Using compound fertilizers during fruit tree cultivation, the ammonia emission coefficient was evaluated as 10.4 kg NH3/ton for pears and 15.3 kg NH₃/ton for apples. The reason why the ammonia emission coefficient according to the use of composite fertilizers was calculated higher for apple cultivation is believed to be due to the relatively high pH concentration of apple orchard soil. CONCLUSION(S): This study may provide basic data for upgrading the ammonia emission coefficient when using composite fertilizers in agricultural land. In the future, it might be necessary to upgrade the calculation of emissions through the development of ammonia and fine particulate matter emission coefficients considering the agricultural environment of Korea.

• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.861-872
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• 2022

The purpose of this study was to establish a complex disaster scenario that can comprehensively consider various disaster situations that may occur in the utility tunnel. Method: In order to comprehensively consider the correlation between disasters, a composite disaster scenario was derived from a combination of damage factors, respectively. A risk assessment was performed in order to derive the priorities of the scenarios. And based on the results, the priorities of complex disaster scenarios were set. Result: Based on the disaster cases in the utility tunnel, a plan was prepared for complex disaster scenarios centered on damage. A complex disaster scenario was specified using a semi-quantitative evaluation method for single and multiple disaster factors such as fire, flooding, and earthquake. Conclusion: The composite disaster scenario derived from this study can be used for the prevention and preparation of damage when the precursor symptoms of a disaster are detected. In addition, the results of this study are expected to be used as basic data for preparing strategic plans and preparing complex disaster response technologies to induce rapid response and recovery in case of emergency disasters.

• The Mathematical Education
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• v.62 no.3
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• pp.363-380
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• 2023

This study analyzed the difficulties and mathematical modeling knowledge improvement that an elementary school teacher experienced in modifying a mathematics textbook task to a mathematical modeling task. To this end, an elementary school teacher with 10 years of experience participated in teacher-researcher community's repeated discussions and modified the average task in the data and pattern domain of the 5th grade. The results are as followings. First, in the process of task modification, the teacher had difficulties in reflecting reality, setting the appropriate cognitive level of mathematical modeling tasks, and presenting detailed tasks according to the mathematical modeling process. Second, through repeated task modifications, the teacher was able to develop realistic tasks considering the mathematical content knowledge and students' cognitive level, set the cognitive level of the task by adjusting the complexity and openness of the task, and present detailed tasks through thought experiments on students' task-solving process, which shows that teachers' mathematical modeling knowledge, including the concept of mathematical modeling and the characteristics of the mathematical modeling task, has improved. The findings of this study suggest that, in terms of the mathematical modeling teacher education, it is necessary to provide teachers with opportunities to improve their mathematical modeling task development competency through textbook task modification rather than direct provision of mathematical modeling tasks, experience mathematical modeling theory and practice together, and participate in teacher-researcher communities.

• Journal of Service Research and Studies
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• v.13 no.4
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• pp.191-205
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• 2023

Artificial Intelligence (AI), especially in the domain of text-generative services, has witnessed a significant surge, with forecasts indicating the AI-as-a-Service (AIaaS) market reaching a valuation of $55.0 Billion by 2028. This research set out to explore the quality dimensions characterizing synthetic text media software, with a focus on four key players in the industry: ChatGPT, Writesonic, Jasper, and Anyword. Drawing from a comprehensive dataset of over 4,000 reviews sourced from a software evaluation platform, the study employed the Latent Dirichlet Allocation (LDA) topic modeling technique using the Gensim library. This process resulted the data into 11 distinct topics. Subsequent analysis involved comparing these topics against established AI service quality dimensions, specifically AICSQ and AISAQUAL. Notably, the reviews predominantly emphasized dimensions like availability and efficiency, while others, such as anthropomorphism, which have been underscored in prior literature, were absent. This observation is attributed to the inherent nature of the reviews of AI services examined, which lean more towards semantic understanding rather than direct user interaction. The study acknowledges inherent limitations, mainly potential biases stemming from the singular review source and the specific nature of the reviewer demographic. Possible future research includes gauging the real-world implications of these quality dimensions on user satisfaction and to discuss deeper into how individual dimensions might impact overall ratings.

• Journal of The Korean Association For Science Education
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• v.44 no.1
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• pp.39-55
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• 2024

This study aimed to examine research trends related to Natural Language Processing (NLP) in science education by analyzing 37 domestic and international documents that utilized NLP techniques in the field of science education from 2011 to September 2023. In particular, the study systematically analyzed the content, focusing on the main application areas of NLP techniques in science education, the role of teachers when utilizing NLP techniques, and a comparison of domestic and international perspectives. The analysis results are as follows: Firstly, it was confirmed that NLP techniques are significantly utilized in formative assessment, automatic scoring, literature review and classification, and pattern extraction in science education. Utilizing NLP in formative assessment allows for real-time analysis of students' learning processes and comprehension, reducing the burden on teachers' lessons and providing accurate, effective feedback to students. In automatic scoring, it contributes to the rapid and precise evaluation of students' responses. In literature review and classification using NLP, it helps to effectively analyze the topics and trends of research related to science education and student reports. It also helps to set future research directions. Utilizing NLP techniques in pattern extraction allows for effective analysis of commonalities or patterns in students' thoughts and responses. Secondly, the introduction of NLP techniques in science education has expanded the role of teachers from mere transmitters of knowledge to leaders who support and facilitate students' learning, requiring teachers to continuously develop their expertise. Thirdly, as domestic research on NLP is focused on literature review and classification, it is necessary to create an environment conducive to the easy collection of text data to diversify NLP research in Korea. Based on these analysis results, the study discussed ways to utilize NLP techniques in science education.

• Journal of Dental Rehabilitation and Applied Science
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• v.40 no.3
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• pp.135-141
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• 2024

Purpose: The purpose of this study was to investigate the accuracy of image merging of an intraoral scan of an edentulous arch to a facial scan using wax rim and markers. Materials and Methods: For registration of oral scan to face scan, a wax rim with markers was made. The markers were cuboid and divided into four groups according to size (5, 10 mm) and attachment location (midline, canine region). The evaluation of registration accuracy was compared with a standard created using cone-beam computed tomography data. Anterior linear variation of the edentulous arch and the 3D variation of the overall arch were measured. Kruskal-Wallis test and Mann-Whitney U test were used for statistics, and the significance level was set at 0.05 and evaluated under Bonferroni correction (0.05/6 = 0.083). Results: In the anterior deviation and global deviation results, there was no statistically significant difference in the oral scan position displacement values between the 5 mm and 10 mm groups. When the midline marker was used, the intraoral scan position displacement value was significantly lower than when only the canine marker was used. Conclusion: Marker attached wax rim can be used for image matching between facial and intraoral scans of the edentulous arch. Marker location at the middle area increases the accuracy of image matching.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.2
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• pp.231-238
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• 2023

Since there is a limit to the physically visible horizon that sensors for autonomous driving can perceive, complementary utilization of digital map data such as a Local Dynamic Map (LDM) along the probable route of an Autonomous Vehicle (AV) is proposed for safe and efficient driving. Although the amount of digital map data may be insignificant compared to the amount of information collected from the sensors of an AV, efficient management of map data is inevitable for the efficient information processing of AVs. The objective of this study is to analyze the efficiency of information use and information processing time of AV according to the expansion of the active section of LDM-based static road and traffic information. To carry out this objective, a microscopic simulator model, VISSIM and VISSIM COM, was employed, and an area of about 9 km × 13 km was selected in the Busan Metropolitan Area, which includes heterogeneous traffic flows (i.e., uninterrupted and interrupted flows) as well as various road geometries. In addition, the LDM information used in AVs refers to the real high-definition map (HDM) built on the basis of ISO 22726-1. As a result of the analysis, as the electronic horizon area increases, while short links are intensively recognized on interrupted urban roads and the sum of link lengths increases as well, the number of recognized links is relatively small on uninterrupted traffic road but the sum of link lengths is large due to a small number of long links. Therefore, this study showed that an efficient range of electronic horizon for HDM data collection, processing, and management are set as 600 m on interrupted urban roads considering the 12 links corresponding to three downstream intersections and 700 m on uninterrupted traffic road associated with the 10 km sum of link lengths, respectively.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.2
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• pp.13-20
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• 2011

Purpose: The limited FOV(Field of View) of CT (Computed Tomography) can cause truncation artifact at external DFOV (Display Field of View) in PET/CT image. In our study, we measured the difference of SUV and compared the influence affecting to the image reconstructed with the extended DFOV. Materials and Methods: NEMA 1994 PET Phantom was filled with $^{18}F$(FDG) of 5.3 kBq/mL and placed at the center of FOV. Phantom images were acquired through emission scan. Shift the phantom's location to the external edge of DFOV and images were acquired with same method. All of acquired data through each experiment were reconstructed with same method, DFOV was applied 50 cm and 70 cm respectively. Then ROI was set up on the emission image, performed the comparative analysis SUV. In the clinical test, patient group shown truncation artifact was selected. ROI was set up at the liver of patient's image and performed the comparative analysis SUV according to the change of DFOV. Results: The pixel size was increase from 3.91 mm to 5.47 mm according to the DFOV increment in the centered location phantom study. When extended DFOV was applied, $_{max}SUV$ of ROI was decreased from 1.49 to 1.35. In case of shifted the center of phantom location study, $_{max}SUV$ was decreased from 1.30 to 1.20. The $_{max}SUV$ was 1.51 at the truncated region in the extended DFOV. The difference of the $_{max}SUV$ was 25.9% higher at the outside of the truncated region than inside. When the extended DFOV was applied, $_{max}SUV$ was decreased from 3.38 to 3.13. Conclusion: When the extended DFOV was applied, $_{max}SUV$ decreasing phenomenon can cause pixel to pixel noise by increasing of pixel size. In this reason, $_{max}SUV$ was underestimated. Therefore, We should consider the underestimation of quantitative result in the whole image plane in case of patient study applied extended DFOV protocol. Consequently, the result of the quantitative analysis may show more higher than inside at the truncated region.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.3
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• pp.39-50
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• 2011

This study furnishes basis data for plan foundation and proper valuation of view by presenting objective and concrete selection standards and ways of Landscape Control Point(LCP) on valuation of development projects. To sum up the results of study, it establishes the prospect, publicity and direction of view as a selection standard LCP on precedent studies. The prospect, which includes visual range, direction of view, geographical features, and visibility, sets up as a valuation basis picking out the available places which have alterations according to direction and distance in practice. In the case of publicity, to select the place as there presentative area where public activities often happen than others, thirteen evaluation indexes including administration facilities, educational facilities, commercial facilities and so on. And variation of landscape is set up as an assessment index to know how much the land has changed from the beginning to the end of development. To apply the selection standards to sample places, the preliminary LCP is founded by analyzing both the prospect and published; a series of courses for selecting the final LCP is founded by analyzing the preliminary LCP and variableness of landscape on a basic of placed which have many alterations of view. At last, in the case of a selection system for LCP, the preliminary LCP is founded by analyzing both the prospect and publicity; a series of courses for selecting the final LCP is found by analyzing the preliminary LCP and variableness of landscape. Applying selection standards and the assessment index to the Sam-deok 3 residence improvement area, in the case of prospect, the southern distant view area has the largest extent. Next, the results of the assessment using the system of publicity show that a five-lane road is taking up the largest area. Hence, a total of 48 preliminary LCPs are set up by analyzing both the prospect and publicity. The results of analyzing landscape variation, one of the valuation indexes, show that Sam-deok dong around the post office has the highest rate of variation at 28.07%. Finally, three LCPs in each part, which are close range, middle range and distance view, are selected; thus, a total of nine LCPs are selected. The selected LCPs that go through a series of practical courses like a GIS program have a lot of professional opinions and are expected to secure objectivity of landscape assessment.