A study on the classification of research topics based on COVID-19 academic research using Topic modeling (토픽모델링을 활용한 COVID-19 학술 연구 기반 연구 주제 분류에 관한 연구)
- Yoo, So-yeon;Lim, Gyoo-gun
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- Journal of Intelligence and Information Systems
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- v.28 no.1
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- pp.155-174
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- 2022
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From January 2020 to October 2021, more than 500,000 academic studies related to COVID-19 (Coronavirus-2, a fatal respiratory syndrome) have been published. The rapid increase in the number of papers related to COVID-19 is putting time and technical constraints on healthcare professionals and policy makers to quickly find important research. Therefore, in this study, we propose a method of extracting useful information from text data of extensive literature using LDA and Word2vec algorithm. Papers related to keywords to be searched were extracted from papers related to COVID-19, and detailed topics were identified. The data used the CORD-19 data set on Kaggle, a free academic resource prepared by major research groups and the White House to respond to the COVID-19 pandemic, updated weekly. The research methods are divided into two main categories. First, 41,062 articles were collected through data filtering and pre-processing of the abstracts of 47,110 academic papers including full text. For this purpose, the number of publications related to COVID-19 by year was analyzed through exploratory data analysis using a Python program, and the top 10 journals under active research were identified. LDA and Word2vec algorithm were used to derive research topics related to COVID-19, and after analyzing related words, similarity was measured. Second, papers containing 'vaccine' and 'treatment' were extracted from among the topics derived from all papers, and a total of 4,555 papers related to 'vaccine' and 5,971 papers related to 'treatment' were extracted. did For each collected paper, detailed topics were analyzed using LDA and Word2vec algorithms, and a clustering method through PCA dimension reduction was applied to visualize groups of papers with similar themes using the t-SNE algorithm. A noteworthy point from the results of this study is that the topics that were not derived from the topics derived for all papers being researched in relation to COVID-19 (
) were the topic modeling results for each research topic (
) was found to be derived from For example, as a result of topic modeling for papers related to 'vaccine', a new topic titled Topic 05 'neutralizing antibodies' was extracted. A neutralizing antibody is an antibody that protects cells from infection when a virus enters the body, and is said to play an important role in the production of therapeutic agents and vaccine development. In addition, as a result of extracting topics from papers related to 'treatment', a new topic called Topic 05 'cytokine' was discovered. A cytokine storm is when the immune cells of our body do not defend against attacks, but attack normal cells. Hidden topics that could not be found for the entire thesis were classified according to keywords, and topic modeling was performed to find detailed topics. In this study, we proposed a method of extracting topics from a large amount of literature using the LDA algorithm and extracting similar words using the Skip-gram method that predicts the similar words as the central word among the Word2vec models. The combination of the LDA model and the Word2vec model tried to show better performance by identifying the relationship between the document and the LDA subject and the relationship between the Word2vec document. In addition, as a clustering method through PCA dimension reduction, a method for intuitively classifying documents by using the t-SNE technique to classify documents with similar themes and forming groups into a structured organization of documents was presented. In a situation where the efforts of many researchers to overcome COVID-19 cannot keep up with the rapid publication of academic papers related to COVID-19, it will reduce the precious time and effort of healthcare professionals and policy makers, and rapidly gain new insights. We hope to help you get It is also expected to be used as basic data for researchers to explore new research directions.
Deriving adoption strategies of deep learning open source framework through case studies (딥러닝 오픈소스 프레임워크의 사례연구를 통한 도입 전략 도출)
- Choi, Eunjoo;Lee, Junyeong;Han, Ingoo
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- Journal of Intelligence and Information Systems
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- v.26 no.4
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- pp.27-65
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- 2020
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Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.
Studies of Molecular Breeding Technique Using Genome Information on Edible Mushrooms
- Kong, Won-Sik;Woo, Sung-I;Jang, Kab-Yeul;Shin, Pyung-Gyun;Oh, Youn-Lee;Kim, Eun-sun;Oh, Min-Jee;Park, Young-Jin;Lee, Chang-Soo;Kim, Jong-Guk
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- 한국균학회소식:학술대회논문집
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- 2015.05a
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- pp.53-53
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- 2015
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Agrobacterium tumefaciens-mediated transformation(ATMT) of Flammulina velutipes was used to produce a diverse number of transformants to discover the functions of gene that is vital for its variation color, spore pattern and cellulolytic activity. Futhermore, the transformant pool will be used as a good genetic resource for studying gene functions. Agrobacterium-mediated transformation was conducted in order to generate intentional mutants of F. velutipes strain KACC42777. Then Agrobacterium tumefaciens AGL-1 harboring pBGgHg was transformed into F. velutipes. This method is use to determine the functional gene of F. velutipes. Inverse PCR was used to insert T-DNA into the tagged chromosomal DNA segments and conducting sequence analysis of the F. velutipes. But this experiment had trouble in diverse morphological mutants because of dikaryotic nature of mushroom. It needed to make monokaryotic fruiting varients which introduced genes of compatible mating types. In this study, next generation sequencing data was generated from 28 strains of Flammulina velutipes with different phenotypes using Illumina Hiseq platform. Filtered short reads were initially aligned to the reference genome (KACC42780) to construct a SNP matrix. And then we built a phylogenetic tree based on the validated SNPs. The inferred tree represented that white- and brown- fruitbody forming strains were generally separated although three brown strains, 4103, 4028, and 4195, were grouped with white ones. This topological relationship was consistently reappeared even when we used randomly selected SNPs. Group I containing 4062, 4148, and 4195 strains and group II containing 4188, 4190, and 4194 strains formed early-divergent lineages with robust nodal supports, suggesting that they are independent groups from the members in main clades. To elucidate the distinction between white-fruitbody forming strains isolated from Korea and Japan, phylogenetic analysis was performed using their SNP data with group I members as outgroup. However, no significant genetic variation was noticed in this study. A total of 28 strains of Flammulina velutipes were analyzed to identify the genomic regions responsible for producing white-fruiting body. NGS data was yielded by using Illumina Hiseq platform. Short reads were filtered by quality score and read length were mapped on the reference genome (KACC42780). Between the white- and brown fruitbody forming strains. There is a high possibility that SNPs can be detected among the white strains as homozygous because white phenotype is recessive in F. velutipes. Thus, we constructed SNP matrix within 8 white strains. SNPs discovered between mono3 and mono19, the parental monokaryotic strains of 4210 strain (white), were excluded from the candidate. If the genotypes of SNPs detected between white and brown strains were identical with those in mono3 and mono19 strains, they were included in candidate as a priority. As a result, if more than 5 candidates SNPs were localized in single gene, we regarded as they are possibly related to the white color. In F. velutipes genome, chr01, chr04, chr07,chr11 regions were identified to be associated with white fruitbody forming. White and Brown Fruitbody strains can be used as an identification marker for F. veluipes. We can develop some molecular markers to identify colored strains and discriminate national white varieties against Japanese ones.
Aquatic and Riparian Flora of the Nakdonggang River Tributary (Sangju: Byeongseong-cheon, Buk-cheon, Oeseo-cheon) (낙동강 지류의 수생 및 수변 식물상(상주: 병성천, 북천, 외서천))
- Hwang, Yong;Hong, Jeong-Ki
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- Korean Journal of Plant Resources
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- v.33 no.5
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- pp.516-535
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- 2020
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This study was conducted to provide information on local resource plants by identifying aquatic and Riparian flora. We investigated the aquatic and riparian floras in 3 streams(Byeongseong-cheon, Buk-cheon, Oeseo-cheon) from February to October 2019. 321 taxa (i.e. 300 species, 5 subspecies, 15 varieties 1 Cultivars from 203 genera of 78 families) of the vascular plants were found in the survey area. Byeongseong-cheon is 133 taxa, Buk-cheon is 233 taxa and Oeseo-cheon is 132 taxa. Among 321 taxa, we found 5 endemic species, 3 red list plants, and However, endangered plants were not found in 3 streams. Aquatic and Riparian plant 138 taxa(i.e. Aquatic plant 20 taxa, Riparian plant 118 taxa). Life forms is annual plant 43 taxa, biennial plant 24 taxa, perennial plant 71 taxa. Aquatic plant growth forms emergent hydrophyte 13 taxa, floating leaved hydrophyte 1 taxa, submerged hydrophyte 6 taxa. The number of floristic regional indicator plants was 15 (i.e. 1 species of IV degree, 3 taxa of III degree, 5 taxa of II degree, and 6 taxa of I degree). Approved foreign export plants 31 taxa. In addition, 52 naturalized plants were identified, and the percentage of Naturalized Index (NI) and Urbanization Index (UI) were 16.1%, and 16.2%, respectively. Vascular plant usability and reclassification result is Edible 213 species (66%), Medicinal 244 species (76%), Flavor 10 species (3%), Industrial 136 species (42%), Ornamental 137 species (36%), Restoration 117 species (36%), Compost 155 species (48%), Unknown 7 species (5%). We hope that our results provide reference data to set up strategy of resources plants, conservation of biodiversity in the 3 streams and Sangju-si areas.
Study on Characteristics of Community and Ecology of Fishes in the Newly Constructed Gunwi Dam Reservoir (신규로 건설된 군위댐 호내 어류 군집 및 생태적 특성에 관한 연구)
- Lee, Jin-Woong;Yoon, Ju-Duk;Kim, Jeong-Hui;Park, Sang-Hyeon;Baek, Seung-Ho;Chang, Kwang-Hyeon;Jang, Min-Ho
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- Korean Journal of Ecology and Environment
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- v.48 no.4
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- pp.219-228
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- 2015
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To secure water resources, dams are normally constructed on the upper - middle part of streams, and it generates physical disturbances such as habitat alteration and stream fragmentation. Such construction can restrict movement of aquatic organisms, especially for freshwater fish which is one of top predator in aquatic ecosystem, and cause genetic fragmentation and community change. In this study, to investigate impact of habitat alteration after dam construction on freshwater fish, we monitored fish community changes, and compared fish fauna between dam reservoir and inflows. Additionally, movement characteristics and habitat boundaries of four species were identified by radio telemetry method. The study was conducted in the Gunwi Dam which was constructed in December 2010. Radio telemetry was applied to Pungtungia herzi, Zacco platypus (living lotic and lentic), Silurus asotus (lentic preferred species) and Zacco koreanus (lotic preferred species). The number of species was remarkably decreased (4 family, 10 species) comparing with before the dam construction (7 family, 15 species). Specifically, Coreoleuciscus splendidus, Niwaella multifasciata, Liobagrus mediadiposalis, Coreoperca herzi and Odontobutis platycephala that inhabit in the lotic environment were not collected in the study area. A total of 8 species were caught in both the dam reservoir and tributaries except 2 species (C. auratus and S. asotus). Sorenson's similarity between the reservoir and its tributaries was high (0.842). All of the radio tagged species stayed in the reservoir except S. asotus which moved to the tributary. These species mainly utilized the shallow littoral zone as a habitat. These results could be useful as a baseline data for efficient management of fishes in lakes.
Distribution and Frequency of SSR Motifs in the Chrysanthemum SSR-enriched Library through 454 Pyrosequencing Technology (국화 SSR-enriched library에서 SSR 반복염기의 분포 및 빈도)
- Moe, Kyaw Thu;Ra, Sang-Bog;Lee, Gi-An;Lee, Myung-Chul;Park, Ha-Seung;Kim, Dong-Chan;Lee, Cheol-Hwi;Choi, Hyun-Gu;Jeon, Nak-Beom;Choi, Byung-Jun;Jung, Ji-Youn;Lee, Kyu-Min;Park, Yong-Jin
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- Journal of the Korean Society of International Agriculture
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- v.23 no.5
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- pp.546-551
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- 2011
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Chrysanthemums, often called mums or chrysanths, belong to the genus Chrysanthemum, which includes about 30 species of perennial flowering plants in the family Asteraceae. We extracted DNA from Dendranthema grandiflorum ('Smileball') to construct a simple sequence repeat (SSR)-enriched library, using a modified biotin-streptavidin capture method. GS FLX (Genome Sequencer FLX System which provides the flexibility to perform the broad range of applications) sequencing (at the 1/8 run specification) resulted in 18.83 mega base pairs (Mbp) with an average read length of 280.06 bp. Sequence analyses of all SSR-containing clones revealed a predominance of di-nucleotide motifs (16,375, 61.5%) followed by tri-nucleotide motifs (6,616, 24.8%), tetra-nucleotide motifs (1,674, 6.3%), penta-nucleotide motifs (1,283, 4.8%), and hexa-nucleotide motifs (693, 2.6%). Among the di-nucleotide motifs, the AC/CA class was the most frequently identified (93.5% of all di-nucleotide types), followed by the GA/AG class (6.1%), the AT/TA class (0.4%), and the CG/GC class (0.03%). When we analyzed the distribution of different repeat motifs and their respective numbers of repeats, regardless of the motif class, of 100 SSR markers, we found a higher number of di-nucleotide motifs with 70 to 80 repeats; we also found two di-nucleotide motifs with 83 and 89 repeats, respectively, but their product lengths were within optimum size (297 and 300 bp). In future work, we will screen for polymorphisms of possible primer pairs. The results will provide a useful tool for assessing molecular diversity and investigating the population structure among and within Chrysanthemum species.
A Study on Perception and Attitudes of Health Workers Towards the Organization and Activities of Urban Health Centers (도시보건소 직원의 보건소 업무에 대한 인식 및 견해)
- Lee, Jae-Mu;Kang, Pock-Soo;Lee, Kyeong-Soo;Kim, Cheon-Tae
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- Journal of Yeungnam Medical Science
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- v.12 no.2
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- pp.347-365
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- 1995
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A survey was conducted to study perception and attitudes of health workers towards health center's activities and organization of health services, from August 15 to September 30, 1994. The study population was 310 health workers engaged in seven urban health centers in Taegu City area. A questionnaire method was used to collect data and response rate was 81.3 percent or 252 respondents. The following are summaries of findings: Profiles of study population: Health workers were predominantly female(62.3%); had college education(60.3%); and held medical and nursing positions(39.6%), technicians(30.6%) and public health/administrative positions(29.8%). Perceptions on health center's resources: Slightly more than a half(51.1%) of respondents expressed that physical facilities of the centers are inadequate; equipments needed are short(39.0%); human resource is inadequate(44.8%); and health budget allocated is insufficient(38.5%) to support the performance of health center's activities. Decentralization and health services: The majority revealed that the decentralization of government system would affect the future activities of health centers(51.9%) which may have to change. However, only one quarter of respondents(25.4%) seemed to view the decentralization positively as they expect that it would help perform health activities more effectively. The majority of the respondents(78.6%) insisted that the function and organization of the urban health centers should be changed. Target workload and job satisfaction: A large proportion (43.3%) of respondents felt that present target setting systems for various health activities are unrealistic in terms of community needs and health center's situation while only 11.1 percent responded it positively; the majority(57.5%) revealed that they need further training in professional fields to perform their job more effectively; more than one third(35.7%) expressed that they enjoy their professional autonomy in their job performance; and a considerable proportion (39.3%) said they are satisfied with their present work. Regarding the personnel management, more worker(47.3%) perceived it negatively than positive(11.5%) as most of workers seemed to think the personnel management practiced at the health centers is not fair or justly done. Health services rendered: Among health services rendered, health workers perceived the following services are most successfully delivered; they are, in order of importance, Tb control, curative services, and maternal and child health care. Such areas as health education, oral health, environmental sanitation, and integrated health services are needed to be strengthening. Regarding the community attitudes towards health workers, 41.3 percent of respondents think they are trusted by the community they serve. New areas of concern identified which must be included in future activities of health centers are, in order of priority, health care of elderly population, home health care, rehabilitation services, and such chronic diseases control programs as diabetes, hypertension, school health and mental health care. In conclusion, the study revealed that health workers seemed to have more negative perceptions and attitudes than positive ones towards organization and management of health services and activities performed by the urban health centers where they are engaged. More specifically, the majority of health workers studied revealed to have the following areas of health center's organization and management inadequate or insufficient to support effective performance of their health activities: Namely, physical facilities and equipments required are inadequate; human and financial resources are insufficient; personnel management is unsatisfactory; setting of service target system is unrealistic in terms of the community needs. However, respondents displayed a number of positive perceptions, particularly to those areas as further training needs and implementation of decentralization of government system which will bring more autonomy of local government as they perceived these change would bring the necessary changes to future activities of the health center. They also displayed positive perceptions in their job autonomy and have job satisfactions.
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