• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.453-462
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• 2022

In this paper, the artificial intelligence (AI) technology used in the medical image analysis field was analyzed through a literature review. Literature searches were conducted on PubMed, ResearchGate, Google and Cochrane Review using the key word. Through literature search, 114 abstracts were searched, and 98 abstracts were reviewed, excluding 16 duplicates. In the reviewed literature, AI is applied in classification, localization, disease detection, disease segmentation, and fit degree of registration images. In machine learning (ML), prior feature extraction and inputting the extracted feature values into the neural network have disappeared. Instead, it appears that the neural network is changing to a deep learning (DL) method with multiple hidden layers. The reason is thought to be that feature extraction is processed in the DL process due to the increase in the amount of memory of the computer, the improvement of the calculation speed, and the construction of big data. In order to apply the analysis of medical images using AI to medical care, the role of physicians is important. Physicians must be able to interpret and analyze the predictions of AI algorithms. Additional medical education and professional development for existing physicians is needed to understand AI. Also, it seems that a revised curriculum for learners in medical school is needed.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.167-180
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• 2021

The purpose of this study is to present a framework of the MyData business ecosystem that shows a different pattern from the previous one by the MyData concept and to define the characteristics of actors participating in the ecosystem. Because MyData is an individual exercising sovereignty over his or her data, there is a characteristic that the individual participates as a key actor in the business. In other words, MyData Operators participate in the MyData business ecosystem to help individuals who own MyData, MyData creating business and MyData using business, among them, manage their own data. Therefore, this study conducts a case study of domestic and foreign MyData businesses to revitalize the domestic MyData industry. In particular, the business model of 45 cases of overseas MyData operators was analyzed and classified into 7 types of 4 groups. And through this, the importance of the role of MyData Operator in the MyData industry ecosystem is confirmed and a developmental ecosystem model is proposed.

• Korean Journal of Culture and Social Issue
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• v.27 no.4
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• pp.475-503
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• 2021

The purpose of this study is to clarify the constructs of emotion suppression and help understanding on the multidimensional nature of emotion suppression by classifying constructs for suppression according to the KMW model. Also, this study examined the gender differences of emotion suppression. For this purpose, 657 adult male and female subjects were evaluated for attitude toward emotions, and difficulty in emotional regulation, as well as depression, state anger and daily stress scale. As a result of the exploratory factor analysis on the scales related to the emotion suppression factors, the emotion suppression factors corresponding to each stage of the KMW model were found to be 'distraction against emotional information, 'difficulty in understanding and interpretation of emotions', 'emotion control beliefs', 'vulnerability on emotional expression beliefs'. Next, the study participants were classified by performing a cluster analysis based on each emotion suppression factor. As a result, four clusters were extracted and named 'emotional control belief cluster', 'emotional expression cluster', 'emotional attention failure cluster', and 'general emotional suppression cluster'. As a result of examining the average difference of male depression, depression, state anger, and daily stress for each group, significant differences were found in all dependent variables. As a result of examining whether there is a difference in the frequency of emotional suppression clusters according to gender, the frequency of emotional suppression clusters was high in men, and the ratio of emotional expression clusters was high in women. Finally, it was analyzed whether there was a gender difference in the effect of the emotional suppression cluster on psychosocial adaptation, and the implications were discussed based on the results of this study.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.30 no.4
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• pp.436-441
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• 1985

The study was conducted to provide basic information to breeders and agronomists working with sesame. The grain weight and germinability were investigated for eight plant types classified by branching habit, capsules per axil, and carpels and loculi of a capsule. Two typical cultivars were chosen for each plant type among 527 gene pools. Dry weight of one thousand grains was increased rapidly from 25th to 35th day after flowering, and reached peak on 40th day after flowering in upper part capsules and 45th day after flowering in lower and middle part capsules, so that this period was considered to be of physiological maturity in each capsule bearing part. Side capsules on main stem and branch capsules were lighter than central ones of main stem, and upper capsules of four carpels eight loculi type decreased more seriously. BTB type demonstrated relatively better growth compared to the growth of BTQ type in one thousand grain weight. The maximum grain filling duration for germination percentage increased rapidly up to 40th day after flowering. Above 70% germinability was obtained from 40th day after flowering. Harvesting time of physiological maturity was considered to be 45th day after flowering with peaks of 2.14g of one thousand grain weight, 26% of grain water content and 90% of germinability.

• Korean Journal of Clinical Laboratory Science
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• v.55 no.1
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• pp.16-28
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• 2023

Lung adenocarcinoma accounts for about 40% of all lung cancers. With the recent development of gene profiling technology, studies on mutations in oncogenes and tumor suppressor genes, which are important for the development and growth of tumors, have been actively conducted. Companion diagnosis using next-generation sequencing helps improve survival with targeted therapy. In this study, formalin-fixed paraffin-embedded tissues of non-small cell lung cancer patients were subjected to hematoxylin and eosin staining for detecting genetic mutations that induce lung adenocarcinoma in Koreans. Immunohistochemical staining was also performed to accurately classify lung adenocarcinoma tissues. Based on the results, next-generation sequencing was applied to analyze the types and patterns of genetic mutations, and the association with smoking was established as the most representative cause of lung cancer. Results of next-generation sequencing analysis confirmed the single nucleotide variations, copy number variations, and gene rearrangements. In order to validate the reliability of next-generation sequencing, we additionally performed the existing genetic testing methods (polymerase chain reaction-epidermal growth factor receptor, immunohistochemistry-anaplastic lymphoma kinase (D5F3), and fluorescence in situ hybridiation-receptor tyrosine kinase 1 tests) to confirm the concordance rates with the next-generation sequencing test results. This study demonstrates that next-generation sequencing of lung adenocarcinoma patients simultaneously identifies mutation.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.397-412
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• 2023

In order for social robots to take root in human life, it is important to consider the technical implementation of social robots and human psychology toward social robots. This study aimed to derive potential social robot clusters based on the emotions consumers feel about social robot appearance design, and to identify and compare important design characteristics and emotional differences of each cluster. In our study, we established a social robot emotion framework to measure and evaluate the emotions consumers feel about social robots, and evaluated the emotions of social robot designs based on the semantic differential method, an kansei engineering approach. We classified 30 social robots into 4 clusters by conducting a multidimensional scaling method and K-means cluster analysis based on the emotion evaluation results, confirmed the characteristics of design elements for each cluster, and conducted a comparative analysis on consumer emotions. We proposed a strategic direction for successful social robot design and development from a human-centered perspective based on the design characteristics and emotional differences derived for each cluster.

• Tunnel and Underground Space
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• v.33 no.4
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• pp.228-243
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• 2023

Bentonite is widely recognized and utilized as a buffer material in high-level radioactive waste repositories, mainly due to its favorable characteristics such as swelling capability and low permeability. Bentonite buffers play an important role in ensuring the safe disposal of radioactive waste by providing a low permeability barrier and effectively preventing the migration of radionuclides into the surrounding rock. However, the long-term performance of bentonite buffers still remains a subject of ongoing research, and one of the main concerns is the erosion of the buffer induced by swelling and groundwater flow. The erosion of the bentonite buffer can significantly impact repository safety by compromising the integrity of buffer and leading to the formation of colloids that may facilitate the transport of radionuclides through groundwater, consequently elevating the risk of radionuclide migration. Therefore, it is very important to numerically quantify the erosion of bentonite buffer to evaluate the long-term performance of bentonite buffer, which is crucial for the safety assessment of high-level radioactive waste disposal. In this technical note, Two-region model is introduced, a proposed model to simulate the erosion behavior of bentonite based on a dynamic bentonite diffusion model, and quantitative evaluation is conducted for the bentonite buffer erosion with this model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.157-164
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• 2023

This paper suggests O(n²) polynomial time heuristic algorithm for corporate tax structure optimization problem that has been classified as NP-complete problem. The proposed algorithm constructs tax tree levels that the target holding company is located at root node of Level 1, and the tax code categories(T_e) 1,4,3,2 are located in each level 2,3,4,5 sequentially. To find the maximum tax-relief path from source(S) to target(T), firstly we connect the minimum witholding tax rate _minr_w(u, v) arc of node u point of view for transfer the profit from u to v node. As a result we construct the spanning tree from all of the source nodes to a target node, and find the initial feasible solution. Nextly, we find the alternate path with minimum foreign tax rate _minr_fi(u, v) of v point of view. Finally we choose the minimum tax-relief path from of this two paths. The proposed heuristic algorithm performs better optimal results than linear programming and Tabu search method that is a kind of metaheuristic method.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.1
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• pp.85-97
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• 2023

Seoul Boramae Park was opened on May 5, 1986, after the Republic of Korea Air Force Academy relocated to Cheongju City in 1985. This study aims to examine the birth and evolution of Seoul Boramae Park and diagnose the park's value being transformed from the former site of the Air Force Academy. Policy reports and newspaper data were analyzed as a research method, focusing on Seoul public records. The study results are as follows. First, Seoul Boramae Park is a large-scale park created before the policy for parks on relocated sites we enacted. Second, Seoul Boramae Park has historical value as an urban park where memories and traces of the Air Force Academy overlap. Third, Seou Boramae Park contributed to regional change by promoting the public value of parks created on the relocated sites with an urban planning method. Seoul Boramae Park has implications for Korean landscape history as a case of securing large green areas in Seoul and presenting its function and roles as a park created on a relocated site.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.179-188
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• 2023

Recently, fake news disguises the form of news content and appears whenever important events occur, causing social confusion. Accordingly, artificial intelligence technology is used as a research to detect fake news. Fake news detection approaches such as automatically recognizing and blocking fake news through natural language processing or detecting social media influencer accounts that spread false information by combining with network causal inference could be implemented through deep learning. However, fake news detection is classified as a difficult problem to solve among many natural language processing fields. Due to the variety of forms and expressions of fake news, the difficulty of feature extraction is high, and there are various limitations, such as that one feature may have different meanings depending on the category to which the news belongs. In this paper, emotional change patterns are presented as an additional identification criterion for detecting fake news. We propose a model with improved performance by applying a convolutional neural network to a fake news data set to perform analysis based on content characteristics and additionally analyze emotional change patterns. Sentimental polarity is calculated for the sentences constituting the news and the result value dependent on the sentence order can be obtained by applying long-term and short-term memory. This is defined as a pattern of emotional change and combined with the content characteristics of news to be used as an independent variable in the proposed model for fake news detection. We train the proposed model and comparison model by deep learning and conduct an experiment using a fake news data set to confirm that emotion change patterns can improve fake news detection performance.