• Journal of The Korean Association of Information Education
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• v.25 no.2
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• pp.413-421
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• 2021

In line with the social changes due to the Fourth Industrial Revolution, foreign countries are strengthening information education for the future of education. This study analyzed the current status of software (SW) and artificial intelligence (AI) education among different types of information education programs in elementary schools of major foreign countries, and compared them with the education provided in Korea. Compared to major foreign countries, Korea allocated very little time for software education in elementary schools, making it difficult to sufficiently cover all areas of the curriculum achievement standards. In addition, other countries recognized the importance of artificial intelligence, an important technology of the Fourth Industrial Revolution, and were providing artificial intelligence education on the basis of software education at the national level. The Korean government is also planning on providing the education at national level, but it was identified that the information education of elementary schools have many problematic issues. This study emphasized the need to establish an information curriculum for elementary schools as a way to address these issues.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.170-185
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• 2023

The advent of big data has brought about the need for analytics. Natural language processing (NLP), a field of big data, has received a lot of attention. Topic modeling among NLP is widely applied to identify key topics in various academic journals. The Korean Society of Industrial and Systems Engineering (KSIE) has published academic journals since 1978. To enhance its status, it is imperative to recognize the diversity of research domains. We have already discovered eight major research topics for papers published by KSIE from 1978 to 1999. As a follow-up study, we aim to identify major topics of research papers published in KSIE from 2000 to 2022. We performed topic modeling on 1,742 research papers during this period by using LDA and BERTopic which has recently attracted attention. BERTopic outperformed LDA by providing a set of coherent topic keywords that can effectively distinguish 36 topics found out this study. In terms of visualization techniques, pyLDAvis presented better two-dimensional scatter plots for the intertopic distance map than BERTopic. However, BERTopic provided much more diverse visualization methods to explore the relevance of 36 topics. BERTopic was also able to classify hot and cold topics by presenting 'topic over time' graphs that can identify topic trends over time.

• Animal Bioscience
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• v.37 no.6
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• pp.993-1000
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• 2024

Objective: This study was conducted to investigate the differential expression of the major histocompatibility complex (MHC) gene region in Eimeria-infected broiler. Methods: We profiled gene expression of Eimeria-infected and uninfected ceca of broilers sampled at 4, 7, and 21 days post-infection (dpi) using RNA sequencing. Differentially expressed genes (DEGs) between two sample groups were identified at each time point. DEGs located on chicken chromosome 16 were used for further analysis. Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis was conducted for the functional annotation of DEGs. Results: Fourteen significant (false discovery rate <0.1) DEGs were identified at 4 and 7 dpi and categorized into three groups: MHC-Y class I genes, MHC-B region genes, and non-MHC genes. In Eimeria-infected broilers, MHC-Y class I genes were upregulated at 4 dpi but downregulated at 7 dpi. This result implies that MHC-Y class I genes initially activated an immune response, which was then suppressed by Eimeria. Of the MHC-B region genes, the DMB1 gene was upregulated, and TAP-related genes significantly implemented antigen processing for MHC class I at 4 dpi, which was supported by KEGG pathway analysis. Conclusion: This study is the first to investigate MHC gene responses to coccidia infection in chickens using RNA sequencing. MHC-B and MHC-Y genes showed their immune responses in reaction to Eimeria infection. These findings are valuable for understanding chicken MHC gene function.

• Korean Journal of Materials Research
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• v.7 no.2
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• pp.129-135
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• 1997

This study has investigated the effects of aging treatment on thc nlechanical propcrries of blg-iiAl-x%nix - 0.1.2) alloys fabricated by the squeeze castmg process. The microstructurcs of as-squeeze cast were composed of pro eurectic $\alpha$ magnesium solid solution, super saturated $\alpha$ solid solution and $\beta(Mg_{17}AI_{12}$) compund. Agcd at both $200^{\circ}C$ and $240^{\circ}C$, Mg--6AixZn alloys showed the peak hardness due to the formation of $\beta(Mg_{17}AI_{12}$) precipitates. The tiiscontinuous precipitates of the lamella r\.pe are predominant at $200^{\circ}C$ aging tredrment. tvhilc. the finely dispersed continu ous precipitates were major type at $240^{\circ}C$ treatment. Mg-- GAI-xZn a1loi.s fabricated hy the squeeze casting process had the hetter combination of tensile strength and elongation compared to the conventionally cast alloys. As increascci zinc: contents. the tensile strength was increased 11y the soiid solutirin strengthening effect of zinc,.

• The Journal of Bigdata
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• v.5 no.2
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• pp.121-133
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• 2020

This study was carried out to set the direction of the new industry policy of Busan city by analyzing the changing trend of artificial intelligence technology that has recently developed rapidly and predicting the direction of future development. The company wanted to draw up support measures to utilize artificial intelligence technology, which has been rapidly emerging in the market, in the region's specialized industry. Artificial intelligence is a key keyword in the fourth industrial revolution and artificial intelligence-based data utilization technology can be used in various fields from manufacturing processes to services, and is entering an era of super-fusion in which barriers between technologies and industries will be broken down. In this study, the direction of promotion for fostering Busan as an artificial intelligence city was derived based on the comparison and analysis of artificial intelligence-related ecosystems among major local governments. In this study, we wanted to present a plan to create an artificial intelligence industrial ecosystem that can be called a key policy to foster Busan as an 'AI City'. Busan's plan to foster the AI industry ecosystem is aimed at establishing a policy direction to ultimately nurture the artificial intelligence industry as Busan's future food source.

• Journal of Digital Convergence
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• v.18 no.6
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• pp.479-493
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• 2020

Outbreak of COVID-19 originated from China resulted significantly high casualties and social and economic damages. Currently the major countries see importance of accurate prediction of originating trend to prevent the spread of infectious disease and AI is actively utilized when establishing the system. Therefore this study has comprehended the status of utilizing the AI in overseas and made comparison and analysis with domestic status. It derived the necessity to establish national control tower based on One Health to respond to infectious disease to effectively utilize AI and suggested to establish higher organization, Medical Big Data Governance, to respond to the infectious disease. It is necessary to conduct further study to utilize the results and suggestions derived from this study into the policy and if the suggestions are reflected to improve institutional imperfection, it will be positively used for prevention of the spreading infectious disease and utilizing medical Big Data.

• Biomolecules & Therapeutics
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• v.20 no.5
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• pp.477-481
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• 2012

The rhizomes of Acorus gramineus have frequently been used in traditional medicine mainly for sedation as well as enhancing brain function. In this study, the anti-allergic activity of A. gramineus was investigated. The 70% ethanol extract of the rhizomes of A. gramineus was found to inhibit the allergic response against 5-lipoxygenase (5-LOX)-catalyzed leukotriene (LT) production from rat basophilic leukemia (RBL)-1 cells and ${\beta}$-hexosaminidase release from RBL-2H3 cells with $IC_{50}$'s of 48.9 and > $200{\mu}g/ml$, respectively. Among the 9 major constituents isolated, ${\beta}$-asarone, (2R,3R,4S,5S)-2,4-dimethyl-1,3-bis (2',4',5'-trimethoxyphenyl)tetrahydrofuran (AF) and 2,3-dihydro-4,5,7-trimethoxy-1-ethyl-2-methyl-3-(2,4,5-trimethoxyphenyl)indene (AI) strongly inhibited 5-LOX-catalyzed LT production in A23187-treated RBL-1 cells, AI being the most potent ($IC_{50}=6.7{\mu}M$). Against ${\beta}$-hexosaminidase release by antigen-stimulated RBL-2H3 cells, only AI exhibited strong inhibition ($IC_{50}=7.3{\mu}M$) while ${\beta}$-asarone and AF showed 26.0% and 39.9% inhibition at $50{\mu}M$, respectively. In addition, the ethanol extract of A. gramineus showed significant inhibitory action against the hapten-induced delayed hypersensitivity reaction in mice by oral administration at 200 mg/kg. Therefore, it is suggested that A. gramineus possesses anti-allergic activity and the constituents including ${\beta}$-asarone and AI certainly contribute to the anti-allergic activity of the rhizomes of A. gramineus.

• Korean Journal of Veterinary Service
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• v.34 no.2
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• pp.111-116
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• 2011

Artificial insemination (AI) of swine is a very useful reproductive tool and that offers convenience in the Korean swine industry. Since many viruses have been reported to be excreted through boar semen, we investigated the presence of antibodies and antigens against viruses causing reproductive failure in semen of boar in 349 semen samples collected from six Korean AI centers. Viral antigens were detected by polymerase chain reaction (PCR) or reverse transcription-PCR predominantly. The results was as follows. The major reproductive failure causing factor was porcine circovirus type 2 (PCV2), followed by porcine reproductive and respiratory syndrome virus (PRRSV) ($X^2$=166.64, P<0.001). PCV2 and PRRSV, Japanese encephalitis virus (JEV), encephalomyocarditis virus (EMCV) was detected in 73 samples (20.9%), 44 samples (12.6%), 4 samples (1.1%), 3 samples (0.9%), respectively and porcine parvovirus in one sample (0.3%) Classical swine fever virus (CSFV), bovine viral diarrhea virus and Aujeszky's disease virus (ADV) were not detected. Enzyme-linked immunosorbent assay was carried out in 111 serum samples from three AI centers. In most pigs, antibodies response was showed prominently in CSFV (105 sera, 94.6%) ($X^2$=82.580, P<0.001), followed by, in PRRSV (100 sera, 90.1%), PCV2 (92 sera, 90.1%), and PPV (8 sera, 82.9%). ADV antibody was not detected. Thus, the experimental results will be used for the base data, with respect to the state of viral stillbirth in general pig farms, as well as AI centers and breeding farms in Korea.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.3
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• pp.59-73
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• 2021

There are many lives lost due traffic accidents, and which have not decreased despite advances in technology. In order to prevent traffic accidents, it is necessary to accurately forecast how they will change in the future. Until now, traffic accident-frequency forecasting has not been a major research field, but has been analyzed microscopically by traditional methods, mainly based on statistics over a previous period of time. Despite the recent introduction of AI to the traffic accident field, the focus is mainly on forecasting traffic flow. This study converts into time series data the records from 1,339,587 traffic accidents that occurred in Korea from 2014 to 2019, and uses the AI algorithm to forecast the frequency of traffic accidents based on driver's age and time of day. In addition, the forecast values and the actual values were compared and verified based on changes in the traffic environment due to COVID-19. In the future, these research results are expected to lead to improvements in policies that prevent traffic accidents.

• Journal of Convergence for Information Technology
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• v.11 no.7
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• pp.14-20
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• 2021

Most accidents caused by road icing in winter lead to major accidents. Because it is difficult for the driver to detect the road icing in advance. In this work, we study how to accurately detect road traffic emerging risk using AutoML and CNN's ensemble model that use both structured and unstructured data. We train CNN-based road traffic emerging risk classification model using images that are unstructured data and AutoML-based road traffic emerging risk classification model using weather data that is structured data, respectively. After that the ensemble model is designed to complement the CNN-based classification model by inputting probability values derived from of each models. Through this, improves road traffic emerging risk classification performance and alerts drivers more accurately and quickly to enable safe driving.