• The Journal of Bigdata
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• v.7 no.2
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• pp.1-9
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• 2022

In the global era, the importance of imported food safety management is increasing. Address information of overseas food companies is key information for imported food safety management, and must be verified for prompt response and follow-up management in the event of a food risk. However, because each country's address system is different, one verification system cannot verify the addresses of all countries. Also, the purpose of address verification may be different depending on the field used. In this paper, we deal with the problem of classifying a given overseas food business address into the administrative district level of the country. This is because, in the event of harm to imported food, it is necessary to find the administrative district level from the address of the relevant company, and based on this trace the food distribution route or take measures to ban imports. However, in some countries the administrative district level name is omitted from the address, and the same place name is used repeatedly in several administrative district levels, so it is not easy to accurately classify the administrative district level from the address. In this study we propose a deep learning-based administrative district level classification model suitable for this case, and verify the actual address data of overseas food companies. Specifically, a method of training using a label powerset in a multi-label classification model is used. To verify the proposed method, the accuracy was verified for the addresses of overseas manufacturing companies in Ecuador and Vietnam registered with the Ministry of Food and Drug Safety, and the accuracy was improved by 28.1% and 13%, respectively, compared to the existing classification model.

• Issues in Feminism
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• v.10 no.1
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• pp.123-158
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• 2010

For the last several months, abortion debates have sparkled in Korea. The government has escalated the need of active punishment of illegal abortions to solve low fertility problems, while some obstetricians and gynecologist have proclaimed stoppage of illegal abortions suing colleague doctors who has conducted illegal abortions. Women's rights groups and researchers have also responded to the abortion debate claiming that women's decisions over their pregnancy are important in making of abortion policies. To contribute to Korean abortion debates, his paper aims to analyze European experiences of abortion polices in relation to the consequences on women's health. For the analysis of European abortion experiences, three countries - Ireland, U.K, and Netherland -are chosen. These three countries are selected since their legal and social acceptance of abortion and the level of safe abortion system are different. Each country is reviewed by national abortion policy, legal regulation, medical system and the role of civil society. The analysis shows several implications for abortion debates occurring in Korea. Various systematic policy mechanisms - abortion on women' request, abortions without complicated doctor's referrals, transparent and anonymous counseling and information provision regarding abortion, training and education for medical professionals to guarantee high quality abortion, abortions funded publicly for women to improve their access to abortions, steady monitoring and auditing abortion procedures and outcomes for safe abortion and so on - are required in Korean society. Two track procedures - safe abortion on women's request and prevention of unwanted pregnancy - are needed for reproduction of healthy women and society.

• Journal of Practical Agriculture & Fisheries Research
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• v.19 no.1
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• pp.39-49
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• 2017

The present study conducted a comparison on tree growth and productivity of high-density apple orchards by several orchard management systems: making scaffolds by heading-back and thinning out pruning (T-1), maintaining scaffolds upward and bearing shoots downward (T-2), managing branches slightly upward without heading-back (T-3), keeping leaders downward and shoots pending (T-4), maintaining leaders high and branches horizontal with severe pinching (T-5), making leaders with lower branches vigorous and upper shoots pending (T-6), and controlling very high planting density with bending branches (T-7). In conclusion, the orchards of (T-5) and (T-6) management systems showed a superior performance in controlling tree growth, productivity, and quality of fruits. Also, superior management efficiency was obtained in the orchards of (T-5) and (T-6).

• Journal of Wetlands Research
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• v.25 no.4
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• pp.267-273
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• 2023

Algae are an important component of the ecosystem. However, the excessive growth of cyanobacteria has various harmful effects on river environments, and diatoms affect the management of water supply processes. Algal monitoring is essential for sustainable and efficient algae management. In this study, an object detection model was developed that detects and classifies images of four types of harmful cyanobacteria used for the criteria of the algae alert system, and one diatom, Synedra sp.. You Only Look Once(YOLO) v8, the latest version of the YOLO model, was used for the development of the model. The mean average precision (mAP) of the base model was analyzed as 64.4. Five models were created to increase the diversity of the input images used for model training by performing rotation, magnification, and reduction of original images. Changes in model performance were compared according to the composition of the input images. As a result of the analysis, the model that applied rotation, magnification, and reduction showed the best performance with mAP 86.5. The mAP of the model that only used image rotation, combined rotation and magnification, and combined image rotation and reduction were analyzed as 85.3, 82.3, and 83.8, respectively.

• Journal of Korea Water Resources Association
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• v.56 no.10
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• pp.641-653
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• 2023

As climate change and urbanization are causing unprecedented natural disasters in urban areas, it is crucial to have urban flood predictions with high fidelity and accuracy. However, conventional physically- and deep learning-based urban flood modeling methods have limitations that require a lot of computer resources or data for high-resolution flooding analysis. In this study, we propose and implement a method for improving the spatial resolution of urban flood analysis using a deep learning based super-resolution technique. The proposed approach converts low-resolution flood maps by physically based modeling into the high-resolution using a super-resolution deep learning model trained by high-resolution modeling data. When applied to two cases of retrospective flood analysis at part of City of Portland, Oregon, U.S., the results of the 4-m resolution physical simulation were successfully converted into 1-m resolution flood maps through super-resolution. High structural similarity between the super-solution image and the high-resolution original was found. The results show promising image quality loss within an acceptable limit of 22.80 dB (PSNR) and 0.73 (SSIM). The proposed super-resolution method can provide efficient model training with a limited number of flood scenarios, significantly reducing data acquisition efforts and computational costs.

• Korean Journal of Radiology
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• v.24 no.4
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• pp.294-304
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• 2023

Objective: We aimed to investigate whether image standardization using deep learning-based computed tomography (CT) image conversion would improve the performance of deep learning-based automated hepatic segmentation across various reconstruction methods. Materials and Methods: We collected contrast-enhanced dual-energy CT of the abdomen that was obtained using various reconstruction methods, including filtered back projection, iterative reconstruction, optimum contrast, and monoenergetic images with 40, 60, and 80 keV. A deep learning based image conversion algorithm was developed to standardize the CT images using 142 CT examinations (128 for training and 14 for tuning). A separate set of 43 CT examinations from 42 patients (mean age, 10.1 years) was used as the test data. A commercial software program (MEDIP PRO v2.0.0.0, MEDICALIP Co. Ltd.) based on 2D U-NET was used to create liver segmentation masks with liver volume. The original 80 keV images were used as the ground truth. We used the paired t-test to compare the segmentation performance in the Dice similarity coefficient (DSC) and difference ratio of the liver volume relative to the ground truth volume before and after image standardization. The concordance correlation coefficient (CCC) was used to assess the agreement between the segmented liver volume and ground-truth volume. Results: The original CT images showed variable and poor segmentation performances. The standardized images achieved significantly higher DSCs for liver segmentation than the original images (DSC [original, 5.40%-91.27%] vs. [standardized, 93.16%-96.74%], all P < 0.001). The difference ratio of liver volume also decreased significantly after image conversion (original, 9.84%-91.37% vs. standardized, 1.99%-4.41%). In all protocols, CCCs improved after image conversion (original, -0.006-0.964 vs. standardized, 0.990-0.998). Conclusion: Deep learning-based CT image standardization can improve the performance of automated hepatic segmentation using CT images reconstructed using various methods. Deep learning-based CT image conversion may have the potential to improve the generalizability of the segmentation network.

• Archives of Plastic Surgery
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• v.51 no.2
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• pp.251-257
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• 2024

Background Plastic surgery has developed to benefit in a variety of challenging areas formerly handled by other disciplines. Medical students do not have a clear picture of plastic surgery as a career due to lacking scope, clinical practice, and understanding of plastic surgery as a clinical area of expertise, including general practitioners, nursing staff, medical trainees, and the general public, and misconceptions about the extent of reconstructive and plastic surgery. Methods A cross-sectional observational study was conducted on Kuwait University Medical students (2nd-7th Years) over a period of 1 month. A questionnaire and a consent form were provided to eligible students. The inclusion criteria were Kuwait University Medical students from 2nd to 7th Years with signed consent form. The response was collected via email sent in coordination with the Vice Dean of Student Affairs in the Faculty of Medicine. Using statistical package for the social sciences, responses were statistically analyzed. Pearson's chi-square test was used to calculate p-values, where p < 0.05 was considered statistically significant. Results A total of 244 eligible medical students, 121 males and 123 females, were included in the study, with a mean age of 21 (±2) years. Similarly, 126 (51.6%) were preclinical students (2nd-4th-year students), while 118 (48.4%) were clinical students (5th-7th-year students). About 79.8% of medical students believed that plastic surgery plays an essential role in trauma management, whereas 9.2% did not consider plastic surgery significant for trauma management. This study found that only 15.5% of medical students were interested in enrolling in plastic surgery residency after graduation, while 47.1% of students did not consider plastic surgery residency after graduation. However, 37.4% were uncertain. The two most driving factors in deciding on plastic surgery residency were expected income (61.8%) and lifestyle (14.3%). Conclusion Improving medical students' education quality can enhance their perception and awareness of plastic surgery. Students should be taught the broader scope of plastic surgery. The inclusion of formal training during undergraduation is the essence of time and should be added to or improved during plastic surgery rotations with more emphasis on reconstructive and hand/peripheral nerve surgery. Student-led interest groups can be a useful tool for educating students about their specialty.

• Journal of Trauma and Injury
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• v.37 no.1
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• pp.28-36
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• 2024

Purpose: Recent advancements in interventional radiology have made angioembolization an invaluable modality in trauma care. Angioembolization is typically performed by interventional radiologists. In this study, we aimed to investigate the safety and efficacy of emergency angioembolization performed by trauma surgeons. Methods: We identified trauma patients who underwent emergency angiography due to significant trauma-related hemorrhage between January 2020 and June 2023 at Jeju Regional Trauma Center. Until May 2022, two dedicated interventional radiologists performed emergency angiography at our center. However, since June 2022, a trauma surgeon with a background and experience in vascular surgery has performed emergency angiography for trauma-related bleeding. The indications for trauma surgeon-performed angiography included significant hemorrhage from liver injury, pelvic injury, splenic injury, or kidney injury. We assessed the angiography results according to the operator of the initial angiographic procedure. The term "failure of the first angioembolization" was defined as rebleeding from any cause, encompassing patients who underwent either re-embolization due to rebleeding or surgery due to rebleeding. Results: No significant differences were found between the interventional radiologists and the trauma surgeon in terms of re-embolization due to rebleeding, surgery due to rebleeding, or the overall failure rate of the first angioembolization. Mortality and morbidity rates were also similar between the two groups. In a multivariable logistic regression analysis evaluating failure after the first angioembolization, pelvic embolization emerged as the sole significant risk factor (adjusted odds ratio, 3.29; 95% confidence interval, 1.05-10.33; P=0.041). Trauma surgeon-performed angioembolization was not deemed a significant risk factor in the multivariable logistic regression model. Conclusions: Trauma surgeons, when equipped with the necessary endovascular skills and experience, can safely perform angioembolization. To further improve quality control, an enhanced training curriculum for trauma surgeons is warranted.

• Journal of the Korean Society of Earth Science Education
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• v.17 no.2
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• pp.181-193
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• 2024

Summative assessment provides information on how well students have achieved learning objectives, making the development of high-quality assessment items essential for accurate evaluation. This is one of the competencies that teachers must possess. This study aims to analyze summative assessment items created by pre-service elementary teachers, examining their intentions and the difficulties encountered in the item development process. The study involved 45 second-year students enrolled in an elementary teacher training university. They were grouped into teams of three and tasked with developing ten items, documenting the purpose of each item, the answer key, and the challenges faced during item creation. The collected summative assessment items were analyzed using a two-dimensional purpose classification table that includes Klopfer's taxonomy of educational objectives. The intentions behind the summative assessments and the difficulties faced during item development were inductively organized and analyzed through qualitative data analysis. The results revealed that pre-service elementary teachers adequately reflected scientific content elements but did not evenly cover assessment domains. The most challenging aspect for them was adjusting the difficulty level. Although they considered most factors that should be taken into account during item development, these considerations were not reflected in the actual items. These findings suggest that knowledge and experience are crucial in developing summative assessment items, and systematic lectures are necessary for pre-service elementary teachers.

• Journal of Plant Biotechnology
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• v.42 no.2
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• pp.71-76
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• 2015

Developed countries have set seed industry as a new growth engine, which demands strong support from the government. Multinational seed companies such as Monsanto and DuPont have made huge financial investment to secure their major roles in the global market. To spur domestic seed industry performance, Korean government laid out the foundation for developing seed industry through policy promotion in the late 2000s. In this paper, I look at the current state of the domestic and international seed market to provide information for improving the efficiency of the propulsion of the Golden Seed Project (GSP) along with its vision. The increasing size of global giant companies has been regarded to monopolize the world seed industry wherein ten renowned companies occupy 73% of the overall global market. In effect, this causes a price hike due to limited seed choices. Domestic seed market has been stuck in a range due to a sustained low agricultural production resulting in decreased seed demand and market size. Though breeding technologies for rice and vegetables are world-class, the technologies for top global crops such as cabbage, paprika, and forage are insufficient therefore professionals in this field are not easily employed. Moreover, there is a lack in appropriate infrastructure set up in the universities which adds to ineffective training of professionals. Being a key-supporting industry for agriculture, seed industry should be granted with strong and sustainable investment support from the government. In view thereof, GSP, which started in 2012, ambitions to spur researches outlined by excellent professionals in universities and seed companies aimed to drive seed export volume and quality and attain domestic seed self-sufficiency through adoption of export- and import-substitution seed types (10 varieties each) development strategies. To develop Korea's seed industry excellent achievement of GSP's goals should be drawn successfully and to do this beside development of high quality seeds, support programs for promotion of seed exports are also needed.