• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.77-82
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• 2023

The Ministry of Agriculture, Food and Rural Affairs established the FarmMap, an digital map of agricultural land. In this study, using deep learning, we suggest the application of farm map reading to farmland such as paddy fields, fields, ginseng, fruit trees, facilities, and uncultivated land. The farm map is used as spatial information for planting status and drone operation by digitizing agricultural land in the real world using aerial and satellite images. A reading manual has been prepared and updated every year by demarcating the boundaries of agricultural land and reading the attributes. Human reading of agricultural land differs depending on reading ability and experience, and reading errors are difficult to verify in reality because of budget limitations. The farmmap has location information and class information of the corresponding object in the image of 5 types of farmland properties, so the suitable AI technique was tested with ResNet50, an instance segmentation model. The results of attribute reading of agricultural land using deep learning and attribute reading by humans were compared. If technology is developed by focusing on attribute reading that shows different results in the future, it is expected that it will play a big role in reducing attribute errors and improving the accuracy of digital map of agricultural land.

• Journal of Korean Library and Information Science Society
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• v.53 no.4
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• pp.123-142
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• 2022

In 2000, North Korea developed and published a two-volume, <Classification-Search Term Dictionary> and is currently used throughout North Korea. The purpose of this study is to examine the development process of the classification schemes of the North Korea after liberation and to understand the contents, composition, and principles of the <Classification-Search Term Dictionary> published in 2000 and revised in 2014. Until now, all the studies of the North Korean classification schemes were studies on the <Book Classification Scheme> published in North Korea in 1964, and there has been no discussion on North Korea's classification schemes since then. The first volume of the <Classification-Search Term Dictionary> consists of 'classification symbols - search terms', and the second volume consists of 'search terms - classification symbols'. Volume 1 is based on the <Books and Bibliography Classification Scheme (1996)>, and there are a total of 41 main classes in five categories. Volume 1 allocates 1 main class (11/19) to 'revolutionary ideas and theories', 8 main classes (20~27) to 'natural sciences', 19 main classes (30~69) to 'engineering technology and applied sciences', 12 main classes (70~85) to 'social sciences', and 1 main class (90) to 'total sciences'. Volume 2 is similar to subject-headings. North Korea's <Classification-Search Term Dictionary> is the first classification scheme introduced in South Korea and is expected to be the starting point for future studies on the establishment of the standard unification classification schemes.

• Journal of radiological science and technology
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• v.46 no.1
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• pp.23-28
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• 2023

The purpose of this study is to see the radiation protection effect of the oral injected Dendranthema zawadskii var. latilobum (Maxim.) Kitam. extracts on the small intestine and uterus of female SD Rat as a natural radiation protection agent. The experimental group was divided into four groups: Normal Control group (NC group), Injected Dendranthema zawadskii var. latilobum (Maxim.) Kitam. extracts group (DZ group), irradiated group after injecting Dendranthema zawadskii var. latilobum (Maxim.) Kitam. extracts (DZ+IR group). The whole body of SD Rat was irradiated with gamma-ray 10Gy, and the administration of oral Dendranthema zawadskii var. latilobum (Maxim.) Kitam. Extract was 2 cc (71.56 mg/day/kg) once a day for 2 weeks. For this study, chages in blood cell levels, SOD assay, small intestine and uterus were observed. In the 21st white blood cell level, the DZ+IR group recovered to a normal level, and the IR group didn't. The IR group villus length was lower than other groups on Day 1. IR group was partially recovered, and DZ+IR group was recovered like the NC group on Day 21. In the case of the first-day endometrium, the IR group was thin and the boundary was cloudy, and the DZ+IR group was thicker and the boundary was clearer than the IR group. Day 21 IR group still did not recover, and DZ+IR group recovered like NC group. This is believed to have radiation protection effects in the blood cells and small intestine and uterus of the irradiated female SD Rat, and is expected to be useful for the study of natural radiation protection materials.

• Korean Journal of Clinical Laboratory Science
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• v.54 no.4
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• pp.293-297
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• 2022

In 2022, Korea reported a total of 224 perfusionists, employing nurses or clinical laboratory technologists (also known as medical technologists) to provide hospital self-education or reliable education. In 2021, the total number of perfusionists in Japan was 2,100, mainly supported by clinical engineering technologists. During the same period, the number of perfusionists reported in the United States was 4,212, who had received training in the master's program, post-bachelor certificate program, and bachelor's program. Most personnel in the USA were graduates of healthcare sciences or life sciences. Perfusionists must be knowledgeable in heart anatomy, physiology, pharmacology, pathology, hemodynamics, laboratory analysis, and quality assurance, as well as techniques to operate the cardiopulmonary bypass machine (heart-lung bypass machine). These are jobs similarly handled by clinical laboratory technologists. The importance of perfusionists became more prominent during two major crises: the MERS-CoV and COVID-19 pandemic. Currently, perfusionists play a significant role in the rapidly expanding field of extracorporeal membrane oxygenation (ECMO) and extracorporeal circulation during cardiac surgery. Results of the current study indicate that hospitals offering cardiac surgery and infectious disease hospitalization need to be institutionalized to secure a certain number of qualified perfusionists. In the future, we look forward to establishing a perfusion technology association under the Korean Society for Clinical Laboratory Physiology to provide academic exchanges.

• Journal of Adhesion and Interface
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• v.23 no.4
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• pp.122-129
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• 2022

In this study, the hydrophilicity of the metal fiber is improved by introducing an oxygen-containing functional group to the fiber surface after treatment of the metal fiber using the oxygen plasma treatment time as an experimental variable. For the surface modification of metal fibers, changes in surface properties before and after plasma treatment were observed using SEM and x-ray photoelectron spectroscopy (XPS). In order to observe the effect of the plasma treatment time on the surface of the metal fiber, the change in contact angle of the metal fiber with respect to a polar solvent and a non-polar solvent was measured. After calculating the change in surface free energy using the measured contact angle, the contact angle and the surface free energy for metal fibers before and after oxygen plasma treatment were compared, and the correlation with the adhesion work was also considered. The microdroplet specimens were prepared to investigate the effect of surface changes of these metal fibers on the improvement of shear strength at the interface when combined with other materials and the interfacial shear strength was measured, and the correlation with the adhesion work was also identified. Therefore, the oxygen plasma treatment of the metal fiber results in an increase in the physical surface area on the fiber surface and a change in contact angle and surface energy according to the introduction of the oxygen-containing functional group on the surface. This surface hydrophilization resulted in improving the interfacial shear strength with the polymer resin.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.33 no.4
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• pp.145-152
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• 2023

The average Nusselt numbers in the source and crystal region for the variation of thermal Grashof number (Gr_t) in the range of 2.31 × 10⁴ ≤ Gr_t ≤ 4.68 × 10⁴ are obtained through numerical simulations. It is shown the average Nusselt number in the crystal region is more than twice as large as the average Nusselt number in the source region. The average Nusselt number in the source region shows an increasing tendency with increasing the thermal Grashof number, Gr_t, while the average Nusselt number in the crystal region shows a decreasing tendency with increasing thermal Grashof number, Gr_t. For the variation of the solutal Grashof number (Gr_s) in the ran ge of 3.28 × 10⁵ ≤ Gr_s ≤ 4.43 × 10⁵, the average Sherwood number in the source region and crystal region tends to decrease as the solutal Grashof number, Gr_s increases. The average Sherwood number in the crystal region is about four times greater than the average Sherwood number in the source region.

• The Korean Journal of Coaching Psychology
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• v.7 no.2
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• pp.21-46
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• 2023

The current study aimed to develop and evaluate the effectiveness of a group coaching program to improve college students' career exploration behaviors based on the self-affirmation theory. Participants were undergraduate students at a University in Seoul and volunteered in the program during the break. The group coaching program was conducted twice a week during three weeks, a total of six times, and each session lasted 2 to 2.5 hours. In this study, the effect of self-affirmation embedded in the group coaching program on various psychological variables and college students' career exploration behaviors were examined. A mixed-randomized analysis was conducted to compare the pre, post, and follow-up tests of the experimental, comparison, and no-treatment control groups, each consisting of 18 participants. The results showed that participants in the experimental group coaching condition showed more significant improvements in psychological resources, career self-efficacy, openness, problem-focused coping, and career exploration behaviors compared to the comparison and control groups, and these results were maintained even after the program ended. The implications of this study for coaching theory and practice, as well as limitations and future research directions, were discussed.

• Journal of the Korean Electrochemical Society
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• v.26 no.3
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• pp.35-41
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• 2023

The carbon-coated silicon monoxide (c-SiO_x), which is a negative electrode active material for lithium-ion batteries (LIBs), has a limited cycle performance due to severe volume changes during cycles, despite its high specific capacity. In particular, the significant volume change of the active material can deform the electrode structure and easily damage the electron transfer pathway. To improve performance and mitigate electrode damage caused by volume changes, we replaced parts of the carbon black conducting agent with carbon nanotubes (CNTs) having a linear shape. The content of the entire conductive material in the electrode was fixed at 10% by mass, and the relative content of CNTs ranged from 0% to 25% by mass to prepare electrodes and evaluate electrochemical performance. As the CNT content in the electrode increased, both cycle life and rate capability improved. Even a small amount of CNT can significantly improve the electrochemical performance of a c-SiO_x negative electrode with large volume changes. Furthermore, dispersing CNTs effectively can lead to achieving the equivalent performance with a reduced quantity of CNTs.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.19-36
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• 2023

As advances in information and communication technology have made it easier for anyone to produce and disseminate information, a new problem has emerged: fake news, which is false information intentionally shared to mislead people. Initially spread mainly through text, fake news has gradually evolved and is now distributed in multimedia formats. Since its founding in 2005, YouTube has become the world's leading video platform and is used by most people worldwide. However, it has also become a primary source of fake news, causing social problems. Various researchers have been working on detecting fake news on YouTube. There are content-based and background information-based approaches to fake news detection. Still, content-based approaches are dominant when looking at conventional fake news research and YouTube fake news detection research. This study proposes a fake news detection method based on background information rather than content-based fake news detection. In detail, we suggest detecting fake news by utilizing related video information from YouTube. Specifically, the method detects fake news through CNN, a deep learning network, from the vectorized information obtained from related videos and the original video using Doc2vec, an embedding technique. The empirical analysis shows that the proposed method has better prediction performance than the existing content-based approach to detecting fake news on YouTube. The proposed method in this study contributes to making our society safer and more reliable by preventing the spread of fake news on YouTube, which is highly contagious.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.8
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• pp.355-364
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• 2023

As advanced cyber threats continue to increase in recent years, it is difficult to detect new types of cyber attacks with existing pattern or signature-based intrusion detection method. Therefore, research on anomaly detection methods using data learning-based artificial intelligence technology is increasing. In addition, supervised learning-based anomaly detection methods are difficult to use in real environments because they require sufficient labeled data for learning. Research on an unsupervised learning-based method that learns from normal data and detects an anomaly by finding a pattern in the data itself has been actively conducted. Therefore, this study aims to extract a latent vector that preserves useful sequence information from sequence log data and develop an anomaly detection learning model using the extracted latent vector. Word2Vec was used to create a dense vector representation corresponding to the characteristics of each sequence, and an unsupervised autoencoder was developed to extract latent vectors from sequence data expressed as dense vectors. The developed autoencoder model is a recurrent neural network GRU (Gated Recurrent Unit) based denoising autoencoder suitable for sequence data, a one-dimensional convolutional neural network-based autoencoder to solve the limited short-term memory problem that GRU can have, and an autoencoder combining GRU and one-dimensional convolution was used. The data used in the experiment is time-series-based NGIDS (Next Generation IDS Dataset) data, and as a result of the experiment, an autoencoder that combines GRU and one-dimensional convolution is better than a model using a GRU-based autoencoder or a one-dimensional convolution-based autoencoder. It was efficient in terms of learning time for extracting useful latent patterns from training data, and showed stable performance with smaller fluctuations in anomaly detection performance.