• KIPS Transactions on Software and Data Engineering
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• v.6 no.10
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• pp.493-498
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• 2017

Capsule endoscopy is specialized for the observation of small intestine that is difficult to access by general endoscopy. The diagnostic procedure through capsule endoscopy consists of three stages: examination of indicant, endoscopy, and diagnosis. At this time, key information needed for diagnosis includes indicant, lesions, and suspected disease information. In this paper, these information are defined as semantic features and the extracting process is defined as semantic-based analysis. It is performed in whole capsule endoscopy. First, several symptoms of patient are checked before capsule endoscopy to get some information on suspected disease. Next, capsule endoscopy is performed by checking the suspected diseases. Finally, diagnosis is concluded by using supporting information. At this time, some association are used to conclude diagnosis. For example, there are the disease association between the symptom and the disease to identify the expected disease, and the anatomical association between the location of the lesion and supporting information. However, existing knowledge models such as MST and CEST only lists the simple term related to endoscopy and cannot consider such semantic associations. Therefore, in this paper, we propose association-based knowledge model for supporting diagnosis of capsule endoscopy. The proposed model is divided into two; a disease model and anatomical model of small intestine, interesting area(organs) of capsule endoscopy. It can effectively support diagnosis by providing key information for capsule endoscopy.

• 한국노년학
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• v.38 no.1
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• pp.225-241
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• 2018

Self-driving is meaningful activity for older persons because it enlarges the range of activity and provides opportunities for social participation. Driving is a complex activity that requires integration of physical, cognitive and sensory functions and is influenced by human and psychological factors. Age related functional deterioration affects the driving ability of older drivers. The purpose of this study is to investigate the factors affecting the risk of accidents and driving cessation of elderly drivers through systematic literature review. MEDLINE, EMBASE, Cochrane Library, KoreaMed, Pubmed were used for searching articles published from 2007 to 2017. 'aged', 'aging', 'automobile driving', 'age factors' were used as search terms and 18 articles were finally selected for analysis among 1,458 articles. In result of the study, the most significant effect showed in the physical domain, the driving habit and the performance function. The most frequent used tools evaluated driving habit and the cognitive function. In demographic characteristics, there was a correlation with the driving discontinue according to sex and age. This study emphasizes the necessity of preparing measures for safety driving with elderly. In addition, it suggests the necessity of systematically services such as individual education programs based on various driving cessation related factors of the elderly.

• Smart Media Journal
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• v.8 no.2
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• pp.58-65
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• 2019

Automatic text summarization is a process of shortening a text document by either extraction or abstraction. The abstraction approach inspired by deep learning methods scaling to a large amount of document is applied in recent work. Abstractive text summarization involves utilizing pre-generated word embedding information. Low-frequent but salient words such as terminologies are seldom included to dictionaries, that are so called, out-of-vocabulary(OOV) problems. OOV deteriorates the performance of Encoder-Decoder model in neural network. In order to address OOV words in abstractive text summarization, we propose a copy mechanism to facilitate copying new words in the target document and generating summary sentences. Different from the previous studies, the proposed approach combines accurate pointing information and selective copy mechanism based on bidirectional RNN and bidirectional LSTM. In addition, neural network gate model to estimate the generation probability and the loss function to optimize the entire abstraction model has been applied. The dataset has been constructed from the collection of abstractions and titles of journal articles. Experimental results demonstrate that both ROUGE-1 (based on word recall) and ROUGE-L (employed longest common subsequence) of the proposed Encoding-Decoding model have been improved to 47.01 and 29.55, respectively.

• Journal of Industrial Convergence
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• v.20 no.6
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• pp.27-35
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• 2022

The purpose of this study is to analyze the metaverse-related issues in the news big data from an educational perspective, explore their characteristics, and provide implications for the educational applicability of the metaverse and future education. To this end, 41,366 cases of metaverse-related data searched on portal sites were collected, and weight values of all extracted keywords were calculated and ranked using TF-IDF, a representative term weight model, and then word cloud visualization analysis was performed. In addition, major topics were analyzed using topic modeling(LDA), a sophisticated probability-based text mining technique. As a result of the study, topics such as platform industry, future talent, and extension in technology were derived as core issues of the metaverse from an educational perspective. In addition, as a result of performing secondary data analysis under three key themes of technology, job, and education, it was found that metaverse has issues related to education platform innovation, future job innovation, and future competency innovation in future education. This study is meaningful in that it analyzes a vast amount of news big data in stages to draw issues from an education perspective and provide implications for future education.

• Journal of Platform Technology
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• v.11 no.4
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• pp.19-34
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• 2023

In order to identify the trends and insights of 'startups' in the global era, we conducted an in-depth trend analysis of the global startup ecosystem using Google Trends, a big data analysis platform. For the validity of the analysis, we verified the correlation between the keywords 'startup' and 'global' through BIGKinds. We also conducted a network analysis based on the data extracted using Google Trends to determine the frequency of searches for the keyword or term 'startup'. The results showed a strong positive linear relationship between the keywords, indicating a statistically significant correlation (correlation coefficient: +0.8906). When exploring global startup trends using Google Trends, we found a terribly similar linear pattern of increasing and decreasing interest in each country over time, as shown in Figure 4. In particular, startup interest was low in the range of 35 to 76 from mid-2020 due to the COVID-19 pandemic, but there was a noticeable upward trend in startup interest after March 2022. In addition, we found that the interest in startups in each country except South Korea is very similar, and the related topics are startup company, technology, investment, funding, and keyword search terms such as best startup, tech, business, invest, health, and fintech are highly correlated.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.1
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• pp.29-41
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• 2023

In landscape studies, the concept of naturalness was vast in its categories from physical space to cognitive systems, making it difficult to define terms at once. Therefore, this study summarized the concept and evaluation attributes of 'naturalness' used in the literature through systematic review (SR), and identified the scope of individual attributes that constitute the meaning of naturalness. In addition, the individual attributes classified in previous studies were identified as the meaning chain, one of the cognitive linguistic research methods, and applied to papers targeting naturalness among domestic landscape studies to organize a polysemous meaning system. Meaning chain is a suitable method for grasping words whose meaning expands in a chain due to family resemblance around prototypical meaning, and the dimension is classified according to the classification of naturalness evaluation items and a multi-semantic chain system of naturalness concepts discussed in domestic academia. The results of the study are as follows. First, the attributes of naturalness extracted through foreign landscape literature were classified into four areas: nature perceived as wilderness, nature as non-artificiality, nature as visual landscape, and nature as experience, and 13 detailed attributes. Second, these detailed attributes are generally consistent with domestic landscape studies, but their specific cases were different, and a Korean context was presented in perception of time accumulation, also they suggested that there may be a mutual conflict between naturalness attributes.

• Journal of Korean Elementary Science Education
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• v.42 no.1
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• pp.178-193
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• 2023

The aim of this study was to investigate differences in the achievement standards from the 2015 to the 2022 revised national science curriculum and to present the implications for science teaching under the revised curriculum. Achievement standards relevant to primary science education were therefore extracted from the national curriculum documents; conceptual domains in the two curricula were analyzed for differences; various kinds of centrality were computed; and the Louvain algorithm was used to identify clusters. These methods revealed that, in the revised compared with the preceding curriculum, the total number of nodes and links had increased, while the number of achievement standards had decreased by 10 percent. In the revised curriculum, keywords relevant to procedural skills and behavior received more emphasis and were connected to collaborative learning and digital literacy. Observation, survey, and explanation remained important, but varied in application across the fields of science. Clustering revealed that the number of categories in each field of science remained mostly unchanged in the revised compared with the previous curriculum, but that each category highlighted different skills or behaviors. Based on those findings, some implications for science instruction in the classroom are discussed.

• The Mathematical Education
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• v.62 no.1
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• pp.79-93
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• 2023

This study used metaphors as a analysis tool to investigate elementary school students' formation and development of angle concepts. For this purpose, the students were asked to write words associated with angle, right angle, acute angle and obtuse angle and to explain why. In case of angle and right angle, responses of 268 students from 3rd to 6th graders were analyzed and for acute angle and obtuse angle, those of 192 students from 4th to 6th graders were examined. As the results of categorizing the metaphors, they can be classified into categories such as; (1) qualitative aspects: 'things metaphor', 'personality metaphor', 'emotions metaphor' etc., (2) quantitative aspects: 'motions metaphor', 'changes metaphor', 'emotions metaphor' etc., and (3) relational aspects: 'shape relations metaphor.' The metaphoric expressions were prominent in 'qualitative aspects' associated with shapes. As for the other aspects, 'quantitative aspect'- the size of angles and the amount of spread and 'relational aspects' - elements of angle and relationship with another shapes, the frequency increses were shown to as grade levels were up. In case of right angle and acute angle, 'qualitative aspects' associated with shapes were outstanding and the frequency of the metaphoric expressions of obtuse angle was distributed similarly in three aspects. As the figure strand and the measurement strand are integrated to an strand in the 2022 revised curriculum, we need more discussion of multifaced aspects of angle and the learning sequences in the 'figure and measurement' strand.

• Journal of The Korean Association For Science Education
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• v.43 no.6
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• pp.509-520
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• 2023

Scientific explanation is the main goal of scientists' scientific practice, and the science curriculum also includes developing students' abilities to construct scientific explanations as a major goal. Thus, clarifying its meaning is an important issue in the science education community. In this paper, the researchers identified three perspectives on 'scientific explanation' based on the scoping review method (Deductive-Nomological, Probabilistic, and Pragmatic explanation models). We argued that it is important to clarify and distinguish the meanings of 'scientific explanation' from other concepts used in science education, such as 'description', 'prediction', 'hypothesis', and 'argument' based on a review of the literature. It is also pointed out that there is a difference between 'scientific explanation' as a product and 'explaining scientifically' as communication, and several ways to revise achievement standard statements in the science curriculum are suggested, to guide students to construct scientific explanations and to help students to explain scientifically. By adopting the three scientific explanation models, the important factors to be considered were classified and organized, and examples of science learning activities for scientific explanation considering such factors were suggested. It is hoped that the discussion in this study will help establish clearer learning goals in science learning related to scientific explanation and aid the design of more appropriate learning activities accordingly.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.4
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• pp.29-54
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• 2023

This study aimed to analyze the research trends of journal articles published by medical schools representing Korean modern. A total of 682 were selected from two journals published by Medical College in Keijo and Keijo Imperial University Medical Faculty. In results, the affiliations of authors who participated in Acta Medicinalia in Keijo included various schools and hospitals, and the authors' major was found to be similar in basic medicine and clinical medicine. In The Keijo Journal of Medicine, only school-affiliated authors participated, and 96.33% of the authors were majors in basic medicine. Co-occurrence network analysis was conducted on MeSH terms from the title of the article using MeSH on Demand, and the keyword that derived in both journals was 'erythrocytes', which analyzed the condition of red blood cells according to organs and diseases. In frequency analysis, a common area of research in both journals was the study focusing on blood and blood cells, and the study of anemia and tuberculosis, which were prevalent diseases at the time. As for comparing each journal, Acta Medicinalia in Keijo has focused on inflammatory diseases and clinical pathological studies in humans, and The Keijo Journal of Medicine has focused on anatomical studies on animals and pharmacological studies on medicines. Through this study, it was possible to identify the research topics and major keywords in two medical schools with different founding goals.