• The Mathematical Education
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• v.63 no.1
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• pp.1-18
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• 2024

This study aims to analyze low-performing high school students' difficulties in constructed response (CR) mathematics assessments and explore ways to use writing activities to support student learning. The participants took CR assessments, engaged in guided writing activities across 15 lessons, and provided responses to our interviews. The study identified 20 types of student difficulties, which were sorted into two main categories: "mathematical difficulties" and "CR difficulties." The difficult nature of mathematics as a school subject included a lack of understanding of mathematical concepts, students' difficulty with mathematical symbols and notations, and struggles with word problems. Challenges specific to CR assessments included students' difficulties arising from the testing conditions unlike those of multiple-choice items, and included issues related to constructing appropriate responses and psychological barriers. To address these challenges in CR assessments, the study conducted guided writing activities as an intervention, through which six themes were identified: (1) internalization of mathematical concepts, (2) mathematical thinking through relational understanding, (3) diverse problem-solving methods, (4) use of mathematical symbols, (5) reflective thinking, and (6) strategies to overcome psychological barriers.

• Korean Journal of Environmental Biology
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• v.41 no.4
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• pp.627-636
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• 2023

Bemisia tabaci Gennadius, one of the most invasive insect pests, has spread quickly nationwide since it was introduced to South Korea in 2008. The use of insecticides is the main management strategy for this pest, but the control efficiency has been decreased due to insecticide resistance. We collected 12 local B. tabaci populations to investigate the regional differences in efficiency and observed the mortality from 14 commercial insecticides applied at recommended concentrations (RC) and dilutions (0.1 RC and 0.01 RC) using the leaf dipping bioassay. Except for etofenprox (46-64%), thiamethoxam (37-60%), pyriproxyfen (21-61%), and pyridaben (61-65%), the other insecticides showed excellent insecticidal efficacy of 70% to 100% at their RC. In particular, flupyradifurone, emamectin benzoate, and cyantraniliprole showed high insecticidal efficacy of over 90% in all of the tested populations. Some insecticides that rapidly decreased in activity (less than 30%) at diluted concentrations or showed high resistance levels in nearby regions were classified for cautious use due to the possibility or potential to develop resistance. The results provide selected insecticides for B. tabaci control by region and could contribute to reducing insecticide abuse and increasing insecticidal efficiency in farming fields.

• Journal of Advanced Technology Convergence
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• v.3 no.3
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• pp.17-27
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• 2024

This study focuses on the development and evaluation of a chatbot system based on the International Classification of Functioning, Disability, and Health (ICF) framework to enhance community participation among elderly individuals with mild dementia in South Korea. The study involved 12 elderly participants who were living alone and had been diagnosed with mild dementia, along with 15 caregivers who were actively involved in their daily care. The development process included a comprehensive needs assessment, system design, content creation, natural language processing using Transformer Attention Algorithm, and usability testing. The chatbot is designed to offer personalized activity recommendations, reminders, and information that support physical, social, and cognitive engagement. Usability testing revealed high levels of user satisfaction and perceived usefulness, with significant improvements in community activities and social interactions. Quantitative analysis showed a 92% increase in weekly community activities and an 84% increase in social interactions. Qualitative feedback highlighted the chatbot's user-friendly interface, relevance of suggested activities, and its role in reducing caregiver burden. The study demonstrates that an ICF-based chatbot system can effectively promote community participation and improve the quality of life for elderly individuals with mild dementia. Future research should focus on refining the system and evaluating its long-term impact.

• Korean Chemical Engineering Research
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• v.62 no.3
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• pp.274-280
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• 2024

Machine learning techniques utilizing neural networks have been employed in various fields such as disease gene discovery and diagnosis, drug development, and prediction of drug-induced liver injury. Disease features can be investigated by molecular information of DNA. In this study, we developed a neural network to predict the length of DNA and the number of DNA species in mixture solution which are representative molecular information of DNA. In order to address the time-consuming limitations of gel electrophoresis as conventional analysis, we analyzed the dynamic data of a microfluidic concentrating device. The dynamic data were reconstructed into a spatiotemporal map, which reduced the computational cost required for training and prediction. We employed a convolutional neural network to enhance the accuracy to analyze the spatiotemporal map. As a result, we successfully performed single DNA length prediction as single-variable regression, simultaneous prediction of multiple DNA lengths as multivariable regression, and prediction of the number of DNA species in mixture as binary classification. Additionally, based on the composition of training data, we proposed a solution to resolve the problem of prediction bias. By utilizing this study, it would be effectively performed that medical diagnosis using optical measurement such as liquid biopsy of cell-free DNA, cancer diagnosis, etc.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.125-132
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• 2024

Recently, with immersive virtual reality(IVR) technologies, various services such as education, training, entertainment, industry, healthcare and remote collaboration have been applied. In particular, researches are actively being studied to visualize and interact with virtual humans, research on virtual pets in IVR is also emerging. For interaction with the virtual pet, similar to real-world interaction scenarios, the most important thing is to provide physical contact such as haptic and non-verbal interaction(e.g., gesture). This paper investigates the effects on factors (e.g., shape and texture) of passive haptic feedbacks using mapping physical props corresponding to the virtual pet. Experimental results show significant differences in terms of immersion, co-presence, realism, and friendliness depending on the levels of texture elements when interacting with virtual pets by passive haptic feedback. Additionally, as the main findings of this study by statistical interaction between two variables, we found that there was Uncanny valley effect in terms of friendliness. With our results, we will expect to be able to provide guidelines for creating interactive contents with the virtual pet in immersive VR environments.

• Journal of Korean Home Economics Education Association
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• v.36 no.2
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• pp.15-31
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• 2024

This study employs photovoice research methodology to investigate adolescents' experiences in sibling relationships and to analyze the impact of sibling interactions on their development and growth. The participants comprised eight high school students with one sibling (four males and four females) residing in the Incheon region. The research process encompassed several stages: participant recruitment, orientation, photovoice activity (focus group interviews), data analysis, and conclusion derivation. During the photovoice activity, participants engaged in a narrative process of photographing, interpreting, and discussing their experiences. The narratives were categorized into four primary themes: structure and environment, emotional interactions, roles, and parental subsystems. The conclusions drawn from the study are as follows: First, the similarity formed in sibling relationships during adolescence contributes to psychological stability. Second, roles and expectations based on birth order can cause stress for adolescents, indicating the need for equitable role adjustments within the family. Third, conflict in sibling relationships is crucial for enhancing problem-solving and social relationship skills. Lastly, consistent parenting attitudes significantly affect the emotional well-being of siblings. This study emphasizes the significance of fostering a deeper understanding of human development and family relationships through an exploration of adolescent sibling dynamics within home economics education.

• The Transactions of the Korea Information Processing Society
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• v.13 no.8
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• pp.374-381
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• 2024

Documentation repositories on GitHub are used to share information that is helpful in performing various tasks. Popular documentation repositories have an advantage in attracting contributors who can help manage and extend documentation repository. Therefore, it is important to understand the characteristic of documentation repositories helpful to obtain popularity for developing strategies attracting attention of users. This paper presents a study on GitHub documentation repositories. To conduct the study, we collected 566 documentation repositories from GitHub and manually categorized their topic into 30 topics. Based on the stargazer score of the collected documentation repositories, we divided the collected documentation repositories into popular and unpopular documentation repository groups and investigated the topics in the popular documentation group. Then we statistically examined the differences in README characteristics of the popular and unpopular documentation repository groups. As a result, we found that the studied documentation repositories have 23 popular topics. We also found that the popular and unpopular documentation repository groups have differences in 5 README characteristics. The result of our study indicates that what documentation repository become popular in GitHub.

• Journal of the Korean Society of Radiology
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• v.85 no.5
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• pp.883-901
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• 2024

Various diseases can affect the esophagus. Endoscopic ultrasound (EUS), which provides precise information about the layers of the esophageal wall, is the primary approach used to investigate esophageal diseases. However, CT is one of the most important imaging modalities for diagnosing esophageal diseases as it can elucidate mediastinal involvement, adjacent lymphadenopathy, and distant disease spread. These two modalities complement each other in the diagnosis of esophageal diseases. Although radiologists may be unfamiliar with EUS procedures and their interpretation, understanding them aids in the differential diagnosis of esophageal conditions. This pictorial essay illustrates the EUS and CT findings of various esophageal diseases originating in the esophageal wall.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.5
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• pp.973-980
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• 2024

Fuzzing is an automated testing technique that generates a lot of testcases and monitors for exceptions to test a program. Recently, fuzzing research using machine learning has been actively proposed to solve various problems in the fuzzing process, but a comprehensive evaluation of fuzzing research using machine learning is lacking. In this paper, we analyze recent research that applies machine learning to scheduling techniques for fuzzing, categorizing them into reinforcement learning-based and supervised learning-based fuzzers. We evaluated the coverage performance of the analyzed machine learning-based fuzzers against real-world programs with four different file formats and bug detection performance against the LAVA-M dataset. The results showed that AFL-HIER, which applied seed clustering and seed scheduling with reinforcement learning outperformed in coverage and bug detection. In the case of supervised learning, it showed high coverage on tcpdumps with high code complexity, and its superior bug detection performance when applied to hybrid fuzzing. This research shows that performance of machine learning-based fuzzer is better when both machine learning and additional fuzzing techniques are used to optimize the fuzzing process. Future research is needed on practical and robust machine learning-based fuzzing techniques that can be effectively applied to programs that handle various input formats.

• Advances in pediatric surgery
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• v.5 no.1
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• pp.75-81
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• 1999

A survey on the intestinal atresias was made among 34 members of Korean Association of Pediatric Surgeons. The response rate was 82.4 %. Two hundred and fifteen patients from the January 1, 1994 to December 31, 1996 were analyzed. The lesions were 73 cases of duodenum(DA), 72 cases of jejunum(JA), 71 cases ileum(IA) and 2 cases cecum and sigmoid colon respectively. There were 2 cases of combined anomalies (DA + JA + IA and DA + JA). Male to female ratio was 1:1 in DA, and 1.8:1 in JA. Seventy four cases(34.3 %) were premature babies(DA 35.2 %, JA:48.6 %, IA:19.2 %), and 62 cases(28.7 %) had low birth weight (DA:39.4 %, JA 33.0 %, IA:13.7 %). Antenatal diagnosis was made in 92 cases(43.6 %). However 22 cases (23.9 %) of them were transferred to pediatric surgeon after delivery. Maternal polyhydramnios was observed in 63 cases(28.9 %). Seventy· five cases(34.4 %) were taken only simple abdominal film for diagnostic studies. The associated malformations were observed in 54 aresia and were observed more frequently in DA(35 cases, 47.9 %). Meconium peritonitis due to intrauterine bowel perforation was more frequently associated with IA compared to DA and JA. The overall mortality rate was 30 %. (Abbreuations: $P_{T}$;p-value in total, $P_{DJ,DI,JI}$;p value between two groups among duodenal, jejunal and ileal groups).