• Journal of Korean Neurosurgical Society
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• v.62 no.4
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• pp.442-449
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• 2019

Objective : Bone mineral density (BMD) is an important consideration during fusion surgery. Although dual X-ray absorptiometry is considered as the gold standard for assessing BMD, quantitative computed tomography (QCT) provides more accurate data in spine osteoporosis. However, QCT has the disadvantage of additional radiation hazard and cost. The present study was to demonstrate the utility of artificial intelligence and machine learning algorithm for assessing osteoporosis using Hounsfield units (HU) of preoperative lumbar CT coupling with data of QCT. Methods : We reviewed 70 patients undergoing both QCT and conventional lumbar CT for spine surgery. The T-scores of 198 lumbar vertebra was assessed in QCT and the HU of vertebral body at the same level were measured in conventional CT by the picture archiving and communication system (PACS) system. A multiple regression algorithm was applied to predict the T-score using three independent variables (age, sex, and HU of vertebral body on conventional CT) coupling with T-score of QCT. Next, a logistic regression algorithm was applied to predict osteoporotic or non-osteoporotic vertebra. The Tensor flow and Python were used as the machine learning tools. The Tensor flow user interface developed in our institute was used for easy code generation. Results : The predictive model with multiple regression algorithm estimated similar T-scores with data of QCT. HU demonstrates the similar results as QCT without the discordance in only one non-osteoporotic vertebra that indicated osteoporosis. From the training set, the predictive model classified the lumbar vertebra into two groups (osteoporotic vs. non-osteoporotic spine) with 88.0% accuracy. In a test set of 40 vertebrae, classification accuracy was 92.5% when the learning rate was 0.0001 (precision, 0.939; recall, 0.969; F1 score, 0.954; area under the curve, 0.900). Conclusion : This study is a simple machine learning model applicable in the spine research field. The machine learning model can predict the T-score and osteoporotic vertebrae solely by measuring the HU of conventional CT, and this would help spine surgeons not to under-estimate the osteoporotic spine preoperatively. If applied to a bigger data set, we believe the predictive accuracy of our model will further increase. We propose that machine learning is an important modality of the medical research field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.520-527
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• 2019

In this study, the technical level and competence of Chungbuk region manufactures were diagnosed and implications for efficiency improvement of cooperation with local universities were derived. The results are as follow. First, in Chungbuk area, 75% of the skilled workers are medium-skilled and high skilled workers. And the life cycle of production products was found to have entered middle/old age. In addition, the industries were overestimating its technology capabilities, including marketing and sales technology, and management technology. Therefore, local universities should develop differentiated program such as technology transfer and commercialization support so that companies can nurture new industries and it is necessary to improve understanding of reality and future prediction ability through various education and seminars. Second, universities in Chungbuk province have failed to meet the practical demands of industry by providing general educational programs such as lifelong education curriculum, rather than the practical training required by industry. First of all, industries needed the practical training programs such as human resource empowerment, technical education and workers' retraining for local industry development. In addition, industries were expected to provide relevant knowledge and infrastructure such as testing, analysis, participation in technology development such as commissioning and joint research. Therefore, universities should prepare customized Industry-Academia Cooperation Programs through industry demand survey in planning. Also, it is necessary to establish various connection points with industry to ensure that industry-academia cooperation will continue and achieve results. Third, the technology of the industries in Chungbuk province was found to be very unrelated to the next generation regional strategic industries. This is not shared vision between industry and local government, Industry-Academia Cooperation Programs will serve as a platform to organize various community entities. Universities will be able to play a key role in between industries and local governments.

• Korean Journal of Plant Resources
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• v.34 no.5
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• pp.443-450
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• 2021

Peach flesh color is commercially important criteria for classification and has implications for nutritional quality. To breed new yellow-fleshed peach cultivar many cross seedlings and generations should be maintained. Therefore it is necessary to develop early selection molecular markers for screening cross seedlings and germplasm with economically important traits to increase breeding efficiency. For the comparison of transcription profiles in peach varieties with a different flesh color expression, two cDNA libraries were constructed. Differences in gene expression between yellow-fleshed peach cultivar, 'Changhowon Hwangdo' and white-fleshed peach cultivar, 'Mibaekdo' were analyzed by next-generation sequencing (NGS). Expressed sequence tag (EST) of clones from the two varieties was selected for nucleotide sequence determination and homology searches. Putative single nucleotide polymorphisms (SNPs) were screened from peach EST contigs by high resolution melting (HRM) analysis, SNP ID ppa002847m:cds and ppa002540m:cds displayed specific difference between 17 yellow-fleshed and 21 white-fleshed peach varieties. The SNP markers for distinguishing yellow and white fleshed peach varieties by HRM analysis offers the opportunity to use early selection. This SNP markers could be useful for marker assisted breeding and provide a good reference for relevant research on molecular mechanisms of color variation in peach varieties.

• Journal of Adhesion and Interface
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• v.22 no.2
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• pp.57-62
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• 2021

Recently, the atomically thin two-dimensional transition-metal dichalcogenides (TMDs) have received considerable attention for the application to next-generation semiconducting devices, owing to their remarkable properties including high carrier mobility. However, while a technique for growing graphene is well matured enough to achieve a wafer-scale single crystalline monolayer film, the large-area growth of high quality TMD monolayer is still a challenging issue for industrial application. In order to enlarge the size of single crystalline MoS₂ monolayer, here, we systematically investigated the effect of process parameters in molten-salt-assisted chemical vapor deposition method. As a result, with optimized process parameters, we found that single crystalline monolayer MoS₂ can be grown as large as 420 ㎛.

• Geophysics and Geophysical Exploration
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• v.24 no.3
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• pp.89-97
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• 2021

Fault detection in seismic data is well suited to the application of machine learning algorithms. Accordingly, various machine learning techniques are being developed. In recent studies, machine learning models, which utilize synthetic data, are the particular focus when training with deep learning. The use of synthetic training data has many advantages; Securing massive data for training becomes easy and generating exact fault labels is possible with the help of synthetic training data. To interpret real data with the model trained by synthetic data, the synthetic data used for training should be geologically realistic. In this study, we introduce a method to generate realistic synthetic seismic data. Initially, reflectivity models are generated to include realistic fault structures, and then, a one-way wave equation is applied to efficiently generate seismic stack sections. Next, a migration algorithm is used to remove diffraction artifacts and random noise is added to mimic actual field data. A convolutional neural network model based on the U-Net structure is used to verify the generated synthetic data set. From the results of the experiment, we confirm that realistic synthetic data effectively creates a deep learning model that can be applied to field data.

• Animal Bioscience
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• v.34 no.2
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• pp.243-255
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• 2021

Objective: Deoxynivalenol (DON) and zearalenone (ZEN) are mycotoxins that frequently contaminate maize and grain cereals, imposing risks to the health of both humans and animals and leading to economic losses. The gut microbiome has been shown to help combat the effects of such toxins, with certain microorganisms reported to contribute significantly to the detoxification process. Methods: We examined the cecum contents of three different dietary groups of pigs (control, as well as diets contaminated with 8 mg DON/kg feed or 0.8 mg ZEN/kg feed). Bacterial 16S rRNA gene amplicons were acquired from the cecum contents and evaluated by next-generation sequencing. Results: A total of 2,539,288 sequences were generated with ~500 nucleotide read lengths. Firmicutes, Bacteroidetes, and Proteobacteria were the dominant phyla, occupying more than 96% of all three groups. Lactobacillus, Bacteroides, Megasphaera, and Campylobacter showed potential as biomarkers for each group. Particularly, Lactobacillus and Bacteroides were more abundant in the DON and ZEN groups than in the control. Additionally, 52,414 operational taxonomic units were detected in the three groups; those of Bacteroides, Lactobacillus, Campylobacter, and Prevotella were most dominant and significantly varied between groups. Hence, contamination of feed by DON and ZEN affected the cecum microbiota, while Lactobacillus and Bacteroides were highly abundant and positively influenced the host physiology. Conclusion: Lactobacillus and Bacteroides play key roles in the process of detoxification and improving the immune response. We, therefore, believe that these results may be useful for determining whether disturbances in the intestinal microflora, such as the toxic effects of DON and ZEN, can be treated by modulating the intestinal bacterial flora.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.85-99
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• 2021

Graphene, called the "dream material" is drawing attention as a groundbreaking new material that will lead the era of the 4th Industrial Revolution. Graphene has high strength, excellent electrical and thermal conductivity, excellent optical permeability, and excellent gas barrier properties. In this paper, as the South Korean government recently announced Green New Deal and Digital New Deal policy, we analyze graphene technology, which is also attracting attention for its application to Corona 19 biosensor, to understand its national R&D trend and knowledge structure, and to explore the possibility of its application. Firstly, 4,054 cases of national R&D project information for the last 10 years are collected from the National Science & Technology Information Service(NTIS) to analyze the trend of graphene-related R&D. Besides, projects classified as green technology are analyzed concerning the government's Green New Deal policy. Secondly, text mining analysis is conducted by collecting 500 recent graphene-related articles from e-newspapers. According to the analysis, the field with the largest number of projects was found to be high-efficiency secondary battery technology, and the proportion of total research funds was also the highest. It is expected that South Korea will lead the development of graphene technology in the future to become a world leader in diverse industries including electric vehicles, cellular phone batteries, next-generation semiconductors, 5G, and biosensors.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.223-233
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• 2021

This study is was conducted for 37 first-year students (including 27 males and 10 females) enrolled in the engineering product design class opened as a regular class in the second semester of 2018 at 'A' University in Seoul to examine creative problem solving experiences in class using design_thinking. In this study, creative problem-solving ability was divided into creative personality and problem-solving ability and in the results of examining the difference in pre- and post-creative problem solving abilities through Hotelling's T-square test and t-test, among the creative personality, the tolerance & passion, humor, curiosity, and progressive attitude were found to significantly increase after class. Next, in the results of examining the process of creative problem solving through the reflection journal, in the empathy and prototyping and testing stages of design thinking, more activities for problem solving appeared, and at the stage of problem definition and idea generation, it can be seen that more activities expressing creative personality appear. The results of this study show that creative problem-solving abilities can be improved through design thinking, suggesting that instructional support for effective design thinking should be designed.

• Journal of Korean Library and Information Science Society
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• v.52 no.2
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• pp.401-428
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• 2021

Recently, libraries are trying to communicate with users using various social media. Among them, Instagram is the most used SNS by users recently. Therefore, in this study, in order to effectively operate the library Instagram, we looked at how Instagram in the library is operated, what posts and contents people are interested in, and how the library can utilize it. By analyzing the Instagram operation status of Instagram, we tried to suggest improvement plans and activation plans. For this purpose, theoretical background research on SNS and Instagram, analysis of prior research, and related data were collected and analyzed. Next, for 82 domestic library accounts opened on Instagram, the library type, region, and Instagram account number of posts, 'followers', 'follows', images, etc. were collected, and the Text, hashtags, upload date, number of 'likes' and comments were analyzed. As a result of the study, it was found that increasing followers, uploading user-customized posts, formalizing account profiles, using library-specific hashtags, and communication with users are necessary to activate library Instagram.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.2
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• pp.13-29
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• 2003

Web-mail system is worthy of note as a next generation e-mail system for its mobility and easiness. But many web-mail system does not have any kind of security mechanism. Even if web-mail system provides security services, its degree of strength is too low. Using these web-mail systems, the e-mail is tabbed, modified or forged by attacker easily. To solve these problems, we design and implement secure web-mail system based on the international e-mail security standard S/MIME in this thesis. This secure web-mail system is composed of server system and client system The server system performs basic mail functions - sending/receiving the mails, storing the mails, and management of user information, etc. And the client system performs cryptographic functions - encryption/decryption of the mails, digital signing and validation, etc. Because client system performs cryptographic functions this secure web-mail system gives its reliability and safety, and provides end-to-end security between mail users. Also, this secure web-mail system increase system efficiency by minimize server load.