• Journal of the Korean Geographical Society
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• v.49 no.4
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• pp.601-614
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• 2014

The purpose of this study is to investigate high school students' geographic misconceptions and their mechanisms of formation. Three main theories explaining why students develop misconceptions exist: 1) framework theory, 2) p-prim(phenomenological primitive) theory, and 3) categorization theory. This study chose three target geographic concepts, or, 1st and 2nd mountain ranges, secondary central business district and satellite city, and the Nopsae wind and the F$\ddot{o}$hn phenomenon. Then, this research explored students' typical misconceptions regarding these concepts and attempted to examine which theory explains the misconception forming processes most well. As a result, the following misconceptions were found. First, students understood that the numbers 1 and 2 denote the order of the formation of mountain ranges. Second, despite differences in their main functions, students tended to subsume the secondary central business district and satellite city under one functional category. Third, students believed that the Nopsae wind and the F$\ddot{o}$hn phenomenon are identical in hierarchy. This study explained students' creation of these misconceptions by applying the categorization theory in which students located a concept in an inappropriate location of an ontology tree.

• Journal of Advanced Navigation Technology
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• v.18 no.3
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• pp.209-214
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• 2014

Current black boxes have a problem of storing unnecessary imagery data recordings without data classification. For this reason, users have to erase videos every time. This method is inadequate for black boxes with limited memory capacity. In this paper, we design and implement a system that recognizes traffic accident situations and saves these recordings by classifying them according to weighted values. The system was made to save video recorded at a 30-sec interval of every event to black box folders by changing names based on weighted value data under the external environment in a 1:10 scale model car. Based on this, when the tests were performed as a major car accident while driving, the videos were created in w2 folder, and when the tests were performed as a minor car accident while stopped, the videos were created in w1 folder.

• Journal of Ginseng Research
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• v.45 no.1
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• pp.58-65
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• 2021

Background: Panax ginseng, as one of the most widely used herbal medicines worldwide, has been studied comprehensively in terms of the chemical components and pharmacology. The proteins from ginseng are also of great importance for both nutrition value and the mechanism of secondary metabolites. However, the proteomic studies are less reported in the absence of the genome information. With the completion of ginseng genome sequencing, the proteome profiling has become available for the functional study of ginseng protein components. Methods: We optimized the protein extraction process systematically by using SDS-PAGE and one-dimensional liquid chromatography mass spectrometry. The extracted proteins were then analyzed by two-dimensional chromatography separation and cutting-edge mass spectrometry technique. Results: A total of 2,732 and 3,608 proteins were identified from ginseng root and cauline leaf, respectively, which was the largest data set reported so far. Only around 50% protein overlapped between the cauline leaf and root tissue parts because of the function assignment for plant growing. Further gene ontology and KEGG pathway revealed the distinguish difference between ginseng root and leaf, which accounts for the photosynthesis and metabolic process. With in-deep analysis of functional proteins related to ginsenoside synthesis, we interestingly found the cytochrome P450 and UDP-glycosyltransferase expression extensively in cauline leaf but not in the root, indicating that the post glucoside synthesis of ginsenosides might be carried out when growing and then transported to the root at withering. Conclusion: The systematically proteome analysis of Panax ginseng will provide us comprehensive understanding of ginsenoside synthesis and guidance for artificial cultivation.

• The Mathematical Education
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• v.61 no.4
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• pp.581-595
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• 2022

The purpose of this study is to specify the procedure for making item models based on ontology models using automatic item generation in the mathematics subject through the CAFA system, and to explore the generated item instances. As an illustration for this, an item model was designed as a part of formative assessment based on the content characteristics, including concepts and calculations, and process characteristics, including application, using the representative values and the measures of dispersion in Mathematics of the 9th grade based on the evaluation criteria achievement standards. The item types generated in one item model were a best answer type, a correct answer type, a combined-response type, an incomplete statement type, a negative type, a true-false type, and a matching type. It was found that HTML, Google Charts, TTS, figures, videos and so on can be used as media. The implications of the use of digital evaluation based on automatic item generation were suggested in the aspects of students, pre-service teachers, general teachers, and special education, and the limitations of this study and future research directions were presented.

• Journal of Animal Science and Technology
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• v.63 no.4
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• pp.934-953
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• 2021

Ciglitazone is a member of the thiazolidinedione family, and specifically binds to peroxisome proliferator-activated receptor-γ (PPARγ), thereby promoting adipocyte differentiation. We hypothesized that ciglitazone as a PPARγ ligand in the absence of an adipocyte differentiation cocktail would increase adiponectin and adipogenic gene expression in bovine satellite cells (BSC). Muscle-derived BSCs were isolated from six, 18-month-old Yanbian Yellow Cattle. The BSC were cultured for 96 h in differentiation medium containing 5 µM ciglitazone (CL), 10 µM ciglitazone (CM), or 20 µM ciglitazone (CH). Control (CON) BSC were cultured only in a differentiation medium (containing 2% horse serum). The presence of myogenin, desmin, and paired box 7 (Pax7) proteins was confirmed in the BSC by immunofluorescence staining. The CL, CM, and CH treatments produced higher concentrations of triacylglycerol and lipid droplet accumulation in myotubes than those of the CON treatment. Ciglitazone treatments significantly increased the relative expression of PPARγ, CCAAT/enhancer-binding protein alpha (C/EBPα), C/EBPβ, fatty acid synthase, stearoyl-CoA desaturase, and perilipin 2. Ciglitazone treatments increased gene expression of Pax3 and Pax7 and decreased expression of myogenic differentiation-1, myogenin, myogenic regulatory factor-5, and myogenin-4 (p < 0.01). Adiponectin concentration caused by ciglitazone treatments was significantly greater than CON (p < 0.01). RNA sequencing showed that 281 differentially expressed genes (DEGs) were found in the treatments of ciglitazone. DEGs gene ontology (GO) analysis showed that the top 10 GO enrichment significantly changed the biological processes such as protein trimerization, negative regulation of cell proliferation, adipocytes differentiation, and cellular response to external stimulus. Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that DEGs were involved in the p53 signaling pathway, PPAR signaling pathway, biosynthesis of amino acids, tumor necrosis factor signaling pathway, non-alcoholic fatty liver disease, PI3K-Akt signaling pathway, and Wnt signaling pathway. These results indicate that ciglitazone acts as PPARγ agonist, effectively increases the adiponectin concentration and adipogenic gene expression, and stimulates the conversion of BSC to adipocyte-like cells in the absence of adipocyte differentiation cocktail.

• Animal Bioscience
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• v.36 no.1
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• pp.144-155
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• 2023

Objective: Adipocyte differentiation is regulated by a variety of functional genes and noncoding RNAs. However, the role of miRNAs in lipid deposition of goat white adipose tissue is still unclear. Therefore, this study revealed the miRNA expression profile in goat subcutaneous adipocytes by sRNA-seq. Methods: The miRNA expressed in goat subcutaneous preadipocytes and the mature adipocytes were sequenced by sRNA-seq. The differentially expressed miRNAs (DEm) were screened and gene ontology (GO) and Kyoto encyclopedia for genes and genomes (KEGG) analyses were performed. Gain-of-function and loss-of-function combined with oil red O staining, Bodipy staining, and quantitative reverse-transcription polymerase chain reaction (qPCR) were utilized to determine the effect of miR-133a-3p on adipocyte differentiation. Results: A total of 218 DEm were screened out. The target genes of these DEm were significantly enriched in GO items such as biological regulation and in KEGG terms such as FAK signaling pathway and MAPK signaling pathway. qPCR verified that the expression trend of miRNA was consistent with miRNA-seq. The gain-of-function or loss-of-function of miR-133a-3p showed that it promoted or inhibited the accumulation of lipid droplets, and CCAAT enhancer binding protein α (C/EBPα) and C/EBPβ were extremely significantly up-regulated or down-regulated respectively (p<0.01), the loss-of-function also led to a significant down-regulation of peroxisome proliferator activated receptor gamma (PPARγ) (p<0.01). Conclusion: This study successfully identified miRNAs expression patterns in goat subcutaneous adipocytes, and functional identification indicates that miR-133a-3p is a positive regulator of the differentiation process of goat subcutaneous adipocytes. Our results lay the foundation for the molecular mechanism of lipid deposition in meat-source goats from the perspective of miRNA.

• Journal of the Korean earth science society
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• v.23 no.4
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• pp.309-323
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• 2002

This qualitative study investigated preservice teachers' understandings of the ontology and epistemology underlying constructivist notions of learning through four in-depth interviews. Of the sixteen participants in a larger study, five significantly changed ontological and epistemological beliefs and eleven did not. This study focused on these eleven teachers who have hardly changed their philosophical beliefs throughout the teacher education program. Ten teachers who consistently maintained the scientific realist beliefs were presented as a composite case (Young's case). Among the eleven teachers, there was one outlier who had consistently maintained an idealist and relativist epistemological position from the beginning of the study and was subjected to another case analysis (Ben's case). These cases corroborated the assertion that each individual's deeply entrenched ontological and epistemological beliefs are very hard to change. For researchers, this study offers insights into the reasons that preservice teachers give for non-changes in their thinking about learning to teach. The study also examines preservice teachers' perceived constraints in implementing their ideal pedagogies and the influence of the teacher education program on their pedagogical beliefs changes. The benefits and influences of the M.Ed. program's theoretical coursework and the field experiences on these teachers' learning-to-teach experiences are addressed with rich data. The implications for teacher educators as well as for the instructional practices of preservice teacher education programs are discussed. This research emphasize necessity of the field-based teacher education program and the need of empowering experienced school teachers as teacher educators in teacher preparation and professional development.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.783-786
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• 2006

컴퓨터기반 협동학습(CSCL)은 컴퓨터를 기반으로 학습자들이 공동체를 형성하고 상호협력관계를 통하여 학습하는 환경으로 학습자가 자신의 능력에 맞게 학습할 수 있고 다른 이들과 생각과 정보를 표현, 교환, 조언, 수정하는 등의 상호작용을 할 수 있다. 이러한 CSCL환경에서 학습자들이 어떤 학습 주제에 대해 주어진 프로젝트를 수행하기 위해 서로간의 생각과 정보를 효과적으로 교환하기 위해서는 그 주제에 속하는 개념들에 대한 용어들이 표준화되어지고, 개념들간의 관련성 및 제약성에 대한 정보들이 미리 정의되어 알려져 있어야만 한다. 그런데, 그러한 정보들을 학습자들이 일일이 파악하기란 매우 힘든 일이다. 이러한 문제는 온톨로지 기술을 이용하여 기계로 하여금 그러한 정보들을 이해하여 처리할 수 있도록 함으로써 해결할 수 있다. 따라서, 본 연구에서는 CAD 분야에서 학습자들이 어떠한 제품을 설계하기 위한 프로젝트를 수행시 서로간의 정보와 의견을 효과적으로 교환함으로써 프로젝트를 보다 효율적으로 수행할 수 있도록 하기 위해 공동의 학습공간을 지원하고 제품 설계에 대한 온톨로지를 구성하여 이를 이용하는 것을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.23-26
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• 2006

최근 대부분의 이러닝(E-Learning)을 교육하는 사이트는 학습 콘텐츠를 검색하는 방법이 단순한 리스트의 나열과 택스트 매칭(Text matching)방법을 사용하는 단점이 있다. 이를 보완하기 위해 좀 더 컴퓨터가 정보 데이터의 의미를 분석하여 검색이 가능하도록 개념 네트워크인 시맨틱웹(Semantic Web)이 등장하였다. 본 논문에서는 이러한 시맨틱웹의 온톨로지(Ontology) 언어 중에 토픽맵(Topic Maps)을 사용하여 많은 양의 학습 정보 데이터를 쉽고도 정확하게 연결 지어 학습 콘텐츠에 대한 정보를 표현하고, 구조화할 수 있는 방법을 모색해 보고자 한다. 학습자의 관심분야 정보, 학습객체의 학습 권장자의 정보와 함께 학습 경험과 검색 빈도수를 분석한 협력 필터링과 학습 에이전트의 개인화 기법을 동시에 사용하여 선호도를 분석한다. 이 선호도를 가지고 학습자의 메타데이터를 생성하고, 로그 데이터를 따로 데이터베이스에 저장한다. 이러한 학습자의 정보와 학습 콘텐츠간의 정보를 상호 연결하여, 그 토픽맵을 사용하여 연관관계를 정의해 줌으로써 학업성취도를 높이고, 학습자 개개인의 성향에 가장 알맞은 학습 콘텐츠를 탐색해가는 네비게이터(Navigator)를 설계하였다.

• Journal of Information Science Theory and Practice
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• v.6 no.4
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• pp.28-38
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• 2018

Wikipedia is composed of millions of articles, each of which explains a particular entity with various languages in the real world. Since the articles are contributed and edited by a large population of diverse experts with no specific authority, Wikipedia can be seen as a naturally occurring body of human knowledge. In this paper, we propose a method to automatically identify key entities and relations in Wikipedia articles, which can be used for automatic ontology construction. Compared to previous approaches to entity and relation extraction and/or identification from text, our goal is to capture naturally occurring entities and relations from Wikipedia while minimizing artificiality often introduced at the stages of constructing training and testing data. The titles of the articles and anchored phrases in their text are regarded as entities, and their types are automatically classified with minimal training. We attempt to automatically detect and identify possible relations among the entities based on clustering without training data, as opposed to the relation extraction approach that focuses on improvement of accuracy in selecting one of the several target relations for a given pair of entities. While the relation extraction approach with supervised learning requires a significant amount of annotation efforts for a predefined set of relations, our approach attempts to discover relations as they occur naturally. Unlike other unsupervised relation identification work where evaluation of automatically identified relations is done with the correct relations determined a priori by human judges, we attempted to evaluate appropriateness of the naturally occurring clusters of relations involving person-artifact and person-organization entities and their relation names.