• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.149-155
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• 2021

In this study, we intend to develop a defective road surface object recognition model that automatically detects road surface defects that restrict the movement of the transportation handicapped using electric mobile devices with deep learning. For this purpose, road surface information was collected from the pedestrian and running routes where the electric mobility aid device is expected to move in five areas within the city of Busan. For data, images were collected by dividing the road surface and surroundings into objects constituting the surroundings. A series of recognition items such as the detection of breakage levels of sidewalk blocks were defined by classifying according to the degree of impeding the movement of the transportation handicapped in traffic from the collected data. A road surface object recognition deep learning model was implemented. In the final stage of the study, the performance verification process of a deep learning model that automatically detects defective road surface objects through model learning and validation after processing, refining, and annotation of image data separated and collected in units of objects through actual driving. proceeded.

• Molecules and Cells
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• v.47 no.3
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• pp.100033.1-100033.13
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• 2024

Considering the recent increase in the number of colorectal cancer (CRC) cases in South Korea, we aimed to clarify the molecular characteristics of CRC unique to the Korean population. To gain insights into the complexities of CRC and promote the exchange of critical data, RNA-sequencing analysis was performed to reveal the molecular mechanisms that drive the development and progression of CRC; this analysis is critical for developing effective treatment strategies. We performed RNA-sequencing analysis of CRC and adjacent normal tissue samples from 214 Korean participants (comprising a total of 381 including 169 normal and 212 tumor samples) to investigate differential gene expression between the groups. We identified 19,575 genes expressed in CRC and normal tissues, with 3,830 differentially expressed genes (DEGs) between the groups. Functional annotation analysis revealed that the upregulated DEGs were significantly enriched in pathways related to the cell cycle, DNA replication, and IL-17, whereas the downregulated DEGs were enriched in metabolic pathways. We also analyzed the relationship between clinical information and subtypes using the Consensus Molecular Subtype (CMS) classification. Furthermore, we compared groups clustered within our dataset to CMS groups and performed additional analysis of the methylation data between DEGs and CMS groups to provide comprehensive biological insights from various perspectives. Our study provides valuable insights into the molecular mechanisms underlying CRC in Korean patients and serves as a platform for identifying potential target genes for this disease. The raw data and processed results have been deposited in a public repository for further analysis and exploration.

• Journal of Life Science
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• v.21 no.5
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• pp.631-646
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• 2011

Mesenchymal stem cells (MSC) are multipotent and can be isolated from diverse human tissues including bone marrow, fat, placenta, dental pulp, synovium, tonsil, and the thymus. They function as regulators of tissue homeostasis. Because of their various advantages such as plasticity, easy isolation and manipulation, chemotaxis to cancer, and immune regulatory function, MSCs have been considered to be a potent cell source for regenerative medicine, cancer treatment and other cell based therapy such as GVHD. However, relating to its supportive feature for surrounding cell and tissue, it has been frequently reported that MSCs accelerate tumor growth by modulating cancer microenvironment through promoting angiogenesis, secreting growth factors, and suppressing anti-tumorigenic immune reaction. Thus, clinical application of MSCs has been limited. To understand the underlying mechanism which modulates MSCs to function as tumor supportive cells, we co-cultured human adipose tissue derived mesenchymal stem cells (ASC) with cancer cell lines H460 and U87MG. Then, expression data of ASCs co-cultured with cancer cells and cultured alone were obtained via microarray. Comparative expression analysis was carried out using DAVID (Database for Annotation, Visualization and Integrated Discovery) and PANTHER (Protein ANalysis THrough Evolutionary Relationships) in divers aspects including biological process, molecular function, cellular component, protein class, disease, tissue expression, and signal pathway. We found that cancer cells alter the expression profile of MSCs to cancer associated fibroblast like cells by modulating its energy metabolism, stemness, cell structure components, and paracrine effect in a variety of levels. These findings will improve the clinical efficacy and safety of MSCs based cell therapy.

• Horticultural Science & Technology
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• v.29 no.6
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• pp.633-640
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• 2011

Brassica rapa is an A genome model species for Brassica crop genetics, genomics, and breeding. With the completion of sequencing the B. rapa genome, functional analysis of the genome is forthcoming issue. The expressed sequence tags are fundamental resources supporting annotation and functional analysis of the genome including identification of tissue-specific genes and promoters. As of July 2011, 147,217 ESTs from 39 cDNA libraries of B. rapa are reported in the public database. However, little information can be retrieved from the sequences due to lack of organized databases. To leverage the sequence information and to maximize the use of publicly-available EST collections, the Brassica rapa tissue-specific EST database (BrTED) is developed. BrTED includes sequence information of 23,962 unigenes assembled by StackPack program. The unigene set is used as a query unit for various analyses such as BLAST against TAIR gene model, functional annotation using MIPS and UniProt, gene ontology analysis, and prediction of tissue-specific unigene sets based on statistics test. The database is composed of two main units, EST sequence processing and information retrieving unit and tissue-specific expression profile analysis unit. Information and data in both units are tightly inter-connected to each other using a web based browsing system. RT-PCR evaluation of 29 selected unigene sets successfully amplified amplicons from the target tissues of B. rapa. BrTED provided here allows the user to identify and analyze the expression of genes of interest and aid efforts to interpret the B. rapa genome through functional genomics. In addition, it can be used as a public resource in providing reference information to study the genus Brassica and other closely related crop crucifer plants.

• Journal of the Korean Society for Library and Information Science
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• v.40 no.3
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• pp.391-413
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• 2006

This study analyzed the procedures and contents of digitalization of sinological resources owned by major sinological resource institutes in Korea. It investigated the united organizations that use such sinological resources It also assessed governmental policies and future Plans for digitalization of sinological resources. Finally, it proposed steps and conditions necessary for successful digitalization of sinological resources. (1) The level of digitalization of library management, searching, and usage system of national library, university library, and research library that has been applied since 1980s has already been highly advanced. The amount of sinological resources collected is significant and its substance value is very high. The digitalized resources are already distributed on internet partially. However, the level of digitalization of sinological resources still lacks some aspects and requires further effort. (2) The data base for digitalized sinological resources already available can be grouped into bibliographic information, contents and annotation, and full text. and it includes both domestic and foreign resources. The quantities of resources are as described in the body (3) The types of digital sinological resources include antient books. archives, micro, and book blocks. (4) The encoding DB methods of digital sinological resources include text. image, PDF. and etc. (5) The united organizations of sinological resources enable us to avoid duplicated investigation and enhance service efficiency. Here are some factors to consider in order to accomplish ideal digitalization of sinological resources. (1) First of all, it is necessary to organize a control center for digitalization procedures of old materials, and allow it a certain degree of authority to develop and Proceed a comprehensive Plan. (2) Both short- and long-term plans need to be developed in order to analyze various aspects of digitalization process. and their steps need to be taken gradually (3) It is necessary to train experts for old materials and let them construct and manage DB.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.12
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• pp.1809-1815
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• 2019

Objective: Copy number variations (CNVs) are a major source of genetic diversity complementary to single nucleotide polymorphism (SNP) in animals. The aim of the study was to perform a comprehensive genomic analysis of CNVs based on high density whole-genome SNP markers in Chinese Dongxiang spotted pigs. Methods: We used customized Affymetrix Axiom Pig1.4M array plates containing 1.4 million SNPs and the PennCNV algorithm to identify porcine CNVs on autosomes in Chinese Dongxiang spotted pigs. Then, the next generation sequence data was used to confirm the detected CNVs. Next, functional analysis was performed for gene contents in copy number variation regions (CNVRs). In addition, we compared the identified CNVRs with those reported ones and quantitative trait loci (QTL) in the pig QTL database. Results: We identified 871 putative CNVs belonging to 2,221 CNVRs on 17 autosomes. We further discarded CNVRs that were detected only in one individual, leaving us 166 CNVRs in total. The 166 CNVRs ranged from 2.89 kb to 617.53 kb with a mean value of 93.65 kb and a genome coverage of 15.55 Mb, corresponding to 0.58% of the pig genome. A total of 119 (71.69%) of the identified CNVRs were confirmed by next generation sequence data. Moreover, functional annotation showed that these CNVRs are involved in a variety of molecular functions. More than half (56.63%) of the CNVRs (n = 94) have been reported in previous studies, while 72 CNVRs are reported for the first time. In addition, 162 (97.59%) CNVRs were found to overlap with 2,765 previously reported QTLs affecting 378 phenotypic traits. Conclusion: The findings improve the catalog of pig CNVs and provide insights and novel molecular markers for further genetic analyses of Chinese indigenous pigs.

• Animal Bioscience
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• v.35 no.11
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• pp.1808-1816
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• 2022

Objective: The study of Hanwoo (Korean native cattle) has mainly been focused on meat quality and productivity. Recently the field of microbiome research has increased dramatically. However, the information on the microbiome in Hanwoo is still insufficient, especially relationship between vagina and feces. Therefore, the purpose of this study is to examine the microbial community characteristics by analyzing the 16S rRNA sequencing data of Hanwoo vagina and feces, as well as to confirm the difference and correlation between vaginal and fecal microorganisms. As a result, the goal is to investigate if fecal microbiome can be used to predict vaginal microbiome. Methods: A total of 31 clinically healthy Hanwoo that delivered healthy calves more than once in Cheongju, South Korea were enrolled in this study. During the breeding season, we collected vaginal and fecal samples and sequenced the microbial 16S rRNA genes V3-V4 hypervariable regions from microbial DNA of samples. Results: The results revealed that the phylum-level microorganisms with the largest relative distribution were Firmicutes, Actinobacteria, Bacteroidetes, and Proteobacteria in the vagina, and Firmicutes, Bacteroidetes, and Spirochaetes in the feces, respectively. In the analysis of alpha, beta diversity, and effect size measurements (LefSe), the results showed significant differences between the vaginal and fecal samples. We also identified the function of these differentially abundant microorganisms by functional annotation analyses. But there is no significant correlation between vaginal and fecal microbiome. Conclusion: There is a significant difference between vaginal and fecal microbiome, but no significant correlation. Therefore, it is difficult to interrelate vaginal microbiome as fecal microbiome in Hanwoo. In a further study, it will be necessary to identify the genetic relationship of the entire microorganism between vagina and feces through the whole metagenome sequencing analysis and meta-transcriptome analysis to figure out their relationship.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.159-172
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• 2023

In general, social problem-solving research aims to create important social value by offering meaningful answers to various social pending issues using scientific technologies. Not surprisingly, however, although numerous and extensive research attempts have been made to alleviate the social problems and issues in nation-wide, we still have many important social challenges and works to be done. In order to facilitate the entire process of the social problem-solving research and maximize its efficacy, it is vital to clearly identify and grasp the important and pressing problems to be focused upon. It is understandable for the problem discovery step to be drastically improved if current social issues can be automatically identified from existing R&D resources such as technical reports and articles. This paper introduces a comprehensive dataset which is essential to build a machine learning model for automatically detecting the social problems and solutions in various national research reports. Initially, we collected a total of 700 research reports regarding social problems and issues. Through intensive annotation process, we built totally 24,022 sentences each of which possesses its own category or label closely related to social problem-solving such as problems, purposes, solutions, effects and so on. Furthermore, we implemented four sentence classification models based on various neural language models and conducted a series of performance experiments using our dataset. As a result of the experiment, the model fine-tuned to the KLUE-BERT pre-trained language model showed the best performance with an accuracy of 75.853% and an F1 score of 63.503%.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.114-123
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• 2023

With the development of computer vision technology, video sensors such as CCTV are detecting incident. However, most of the current incident have been detected based on existing fixed imaging equipment. Accordingly, there has been a limit to the detection of incident in shaded areas where the image range of fixed equipment is not reached. With the recent development of edge-computing technology, real-time analysis of mobile image information has become possible. The purpose of this study is to evaluate the possibility of detecting expressway emergencies by introducing computer vision technology to dash cam. To this end, annotation data was constructed based on 4,388 dash cam still frame data collected by the Korea Expressway Corporation and analyzed using the YOLO algorithm. As a result of the analysis, the prediction accuracy of all objects was over 70%, and the precision of traffic accidents was about 85%. In addition, in the case of mAP(mean Average Precision), it was 0.769, and when looking at AP(Average Precision) for each object, traffic accidents were the highest at 0.904, and debris were the lowest at 0.629.

• Journal of Animal Science and Technology
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• v.51 no.1
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• pp.1-8
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• 2009

We generated 57,598 expressed sequence tags (ESTs) from 3 cDNA libraries of Hanwooo (Korean Cattle), fat, loin, liver. Liver, intermuscular fat and longissimus dorsi tissues were obtained from a 24-month-old Hanwoo steer immediately after slaughter. cDNA library was constructed according to the oligocapped method. The EST data were clustered and assembled into unique sequences, 4,759 contigs and 7,587 singletons. To carry out functional analysis, Gene Ontology annotation and identification of significant leaf nodes were performed that were detected by searching significant p-values from $2^{nd}$ level GO terms to leaf nodes using Bonferroni correction. We found that 13, 26 and 8 significant leaf nodes are unique in the transcripts according to 3 GO categories, molecular function, biological process and cellular component. Also digital gene expression profiling using the Audic's test was performed and tissue specific genes were detected in the above 3 libraries.