• Publications of The Korean Astronomical Society
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• v.34 no.3
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• pp.41-48
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• 2019

We compared and analyzed the astronomy terms currently used by astronomers in the two Koreas to promote inter-Korean astronomy cooperation. We analyzed a total of 2716 pairs of terms common in both Koreas glossaries, using the astronomical terminology contained in the South Korean source, the 'Terminology of Astronomy', and the North Korean source, 'Mirror 2.0'. For each pair of terms, their morphological features and meanings were compared. We categorized into 11 groups for comparison of astronomical terms. We found that most of the terms are used similarly in the two Koreas. About 47% of the total is similar in form. Although terms are different, meanings communicate about 37% of the total. As a result, similar terms used by the two Koreas correspond to about 85% of the total. However, 15% of terms are difficult to understand because they have different forms or meanings such as diffraction (회절/에돌이), flare (플레어/요반) etc. Further research on terms that are used differently by the two Koreas, and the conversion of appropriate terms through mutual understanding should be made in the future.

• Database Research
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• v.34 no.3
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• pp.3-13
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• 2018

Text classification is one of the text mining technologies that classifies a given textual document into its appropriate categories and is used in various fields such as spam email detection, news classification, question answering, emotional analysis, and chat bot. In general, the text classification system utilizes machine learning algorithms, and among a number of algorithms, naïve Bayes and support vector machine, which are suitable for text data, are known to have reasonable performance. Recently, with the development of deep learning technology, several researches on applying deep neural networks such as recurrent neural networks (RNN) and convolutional neural networks (CNN) have been introduced to improve the performance of text classification system. However, the current text classification techniques have not yet reached the perfect level of text classification. This paper focuses on the fact that the text data is expressed as a vector only with the word dimensions, which impairs the semantic information inherent in the text, and proposes a neural network architecture based upon the semantic tensor space model.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.1
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• pp.32-42
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• 2024

In this study, 1,474 effective patents were derived for quantitative analysis of five major countries, including Korea, China, Japan, the United States and Europe, for marine space policy simulator technology used as a support for integrated marine space management means, and domestic technology competitiveness and domestic and foreign technology trends were identified through annual and national patent application trends and word cloud analysis. This diagnosed the need for active policy support for research and development of marine space policy simulator technology at the government level and preparation through linkage strategies such as patent application consideration and standardization preoccupation for surrounding technologies to prepare for China-led market monopoly and preoccupation.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.12 no.1
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• pp.51-70
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• 2001

Characteristics of handwriting were investigated and compared between the patients with writing disabilities and normal elementary school pupils. Generally, the heights of the letters of the patients were significantly larger than those of normal children, and letters of the patients were more sparsely distributed than those of controls. The distance between the words were significantly reduced in the patients’ writings, which indicated that patients had much more problems of space-leaving than normal pupils. Letter heights differences were significant across all grades in the patients and normal controls. The heights of the letters decreased as they grew older, and the slope of the decrements were more steeper in normal girls(r=-0.45) than girls with writing disabilities(r=-0.16). Sex differences were found in the letter spacings in low grades(grades 1, 2), that is, the distances between the letters were significantly narrower in the male patients than normal boys in these grades, and the differences were almost indiscriminating in grades 3 through 5, and finally, in sixth grade, letter spacings were signifycantly broader in normal boys than male dysgraphics. In girls, letter spacings were significantly broader in the patients across all grades. These findings supports the hypothesis that male and female writings were qualitatively different and that distinct mechanisms served in boys and girls dysgraphics. Across all grades and sexes, spaces between the words of the patients were significantly broader than normal pupils, which suggested that space-leaving between the words was important in Korean writings. There was trend that letter spacings and word spacings decreased across grades, but in girls, no correlations between the letter spacings and grades were found. Correlation analyses revealed that letter heights and letter spacings had mild correlation(r=0.11-0.15), and that letter spacings and word spacings had robust correlation(r=0.99). Phonological errors were mostly found in last phoneme(Jong-seong), especially double-phoneme(ㄳ, ㄵ, ㄶ, ㄺ, ㄻ, ㄼ, ㄾ, ㄿ, ㅀ, ㅄ), and in the case the sound values changed due to assimilations of phonemes. Semantic errors were rare in both groups. Space-leaving errors were correlated with phonological errors, and more frequent in boys than girls. In conclusion, significant differences existed in the letter heights, letter spacings, word spacings, and frequencies of phonological errors and spaceleaving errors between the patients with writing disabilities and normal pupils. The characteristics of writings changed across grades and the developmental profiles were somewhat quantitatively different between the groups. The differences became obvious from the second-third grades.

• Journal of KIISE:Software and Applications
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• v.29 no.9
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• pp.676-683
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• 2002

The success of XML(eXtensible Markup Language) is primarily based on its flexibility : everybody can define the structure of XML documents that represent information in the form he or she desires. XML is so flexible that XML documents cannot be automatically provided with an underlying semantics. Different tag sets, different names for elements or attributes, or different document structures in general mislead the task of classifying and clustering XML documents precisely. In this paper, we design and implement a system that allows checking the semantic-based similarity between XML tags. First, this system extracts the underlying semantics of tags and then expands the synonym set of tags using an WordNet thesaurus and user-defined word library which supports the abbreviation forms and compound words for XML tags. Seconds, considering the relative importance of XML tags in the XML documents, we extend a conventional vector space model which is the most generally used for document model in Information Retrieval field. Using this method, we have been able to check the similarity between XML tags which are represented different tags.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.19-41
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• 2019

According to the rapidly increasing demand for text data analysis, research and investment in text mining are being actively conducted not only in academia but also in various industries. Text mining is generally conducted in two steps. In the first step, the text of the collected document is tokenized and structured to convert the original document into a computer-readable form. In the second step, tasks such as document classification, clustering, and topic modeling are conducted according to the purpose of analysis. Until recently, text mining-related studies have been focused on the application of the second steps, such as document classification, clustering, and topic modeling. However, with the discovery that the text structuring process substantially influences the quality of the analysis results, various embedding methods have actively been studied to improve the quality of analysis results by preserving the meaning of words and documents in the process of representing text data as vectors. Unlike structured data, which can be directly applied to a variety of operations and traditional analysis techniques, Unstructured text should be preceded by a structuring task that transforms the original document into a form that the computer can understand before analysis. It is called "Embedding" that arbitrary objects are mapped to a specific dimension space while maintaining algebraic properties for structuring the text data. Recently, attempts have been made to embed not only words but also sentences, paragraphs, and entire documents in various aspects. Particularly, with the demand for analysis of document embedding increases rapidly, many algorithms have been developed to support it. Among them, doc2Vec which extends word2Vec and embeds each document into one vector is most widely used. However, the traditional document embedding method represented by doc2Vec generates a vector for each document using the whole corpus included in the document. This causes a limit that the document vector is affected by not only core words but also miscellaneous words. Additionally, the traditional document embedding schemes usually map each document into a single corresponding vector. Therefore, it is difficult to represent a complex document with multiple subjects into a single vector accurately using the traditional approach. In this paper, we propose a new multi-vector document embedding method to overcome these limitations of the traditional document embedding methods. This study targets documents that explicitly separate body content and keywords. In the case of a document without keywords, this method can be applied after extract keywords through various analysis methods. However, since this is not the core subject of the proposed method, we introduce the process of applying the proposed method to documents that predefine keywords in the text. The proposed method consists of (1) Parsing, (2) Word Embedding, (3) Keyword Vector Extraction, (4) Keyword Clustering, and (5) Multiple-Vector Generation. The specific process is as follows. all text in a document is tokenized and each token is represented as a vector having N-dimensional real value through word embedding. After that, to overcome the limitations of the traditional document embedding method that is affected by not only the core word but also the miscellaneous words, vectors corresponding to the keywords of each document are extracted and make up sets of keyword vector for each document. Next, clustering is conducted on a set of keywords for each document to identify multiple subjects included in the document. Finally, a Multi-vector is generated from vectors of keywords constituting each cluster. The experiments for 3.147 academic papers revealed that the single vector-based traditional approach cannot properly map complex documents because of interference among subjects in each vector. With the proposed multi-vector based method, we ascertained that complex documents can be vectorized more accurately by eliminating the interference among subjects.

• Archives of design research
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• v.15 no.1
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• pp.163-170
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• 2002

Virtual Reality is the technique which makes the man experience the similar interaction behavior to the experience in the real world through virtual space. The users participating in the 3D virtual space using virtual reality technique can have the various experiences in the space desired without restrictions on time and space and then it has been applied in many application areas such as video industry, entertainment simulator, medical treatment, construction and design. The area of video among them has been highlighted as a high-added value industry. Therefore this study classifies video industry into four including movie, broadcasting, advertisement and internet and is to examine their characteristics, application cases and developmental potential. In the industry using virtual reality technique in video industry, it is implied for special elect in the area of movie and for providing the various graphic virtual word to audiences with the introduction of virtual studio and character in the area of broadcasting. It can give audiences a synergy effect by inserting 3D advertisement into virtual space in the area of advertisement. Also the implementation of 3D virtual reality such as virtual museum, virtual model house, virtual home shopping and entertainment on the web is possible with the emergence of Virtual Reality Modeling Language (VRML) and it plays the roles of more entertainments. Accordingly, this study is to seek the application methods using virtual reality technique in video industry.

• International Journal of Advanced Culture Technology
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• v.10 no.3
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• pp.174-183
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• 2022

The abstract should summarize the contents of the paper and written below the author information. Use the word "Abstract" as the title, in 12-point Times New Roman, boldface type, italicized, centered relative to the column, initially capitalized, fixed-spacing at 13 pt., 12 pt. spacing before the text and 6 pt. after. The abstract content is to be in 11-point, italicized, single spaced type. Leave one blank line after the abstract, and then begin the keywords. All manuscripts must be in English. When it comes to the issue of "virtual and real" in traditional Chinese painting, the first impression is to describe the problems of painting strokes and ink, layout of pictures, etc., but it runs through the initial conception of the work, creation in the middle and aesthetic appreciation of the work. It exists in the whole process of artistic creation and appreciation. In essence, it is a problem of aesthetic thinking and philosophical thinking. Because the traditional Chinese painting theory is influenced by Taoism, when the concept of "virtual and real" is implemented in the specific picture of Chinese painting, it is contained in the specific shape of "physics", that is, the painting theory research of "blank space" in the picture. Based on the traditional Taoist philosophy of China, this paper takes the "virtual and real" view in Lao Zhuang's thought as the research object, deeply analyzes and compares its relationship with the "virtual and real" in Chinese landscape painting, and finds out their artistic spirit, essential characteristics and how to present them. This paper mainly discusses the internal relationship between Taoist philosophy and "virtual and real" in Chinese landscape painting from the following aspects. The introduction expounds the origin, purpose, significance, innovation and research methods of the topic. This paper analyzes the philosophical thoughts about landscape in the philosophical thoughts represented by Lao Tzu and Zhuangzi. The development of Chinese traditional aesthetics theory is closely related to Taoist philosophy, which has laid the foundation and pointed out the direction for the development of Chinese painting theory since ancient times. It also discusses the influence of the Taoist philosophy of "the combination of the virtual and real" on the emergence and development of the artistic conception of landscape painting. Firstly, through the analysis of the artistic conception of landscape painting and its constituent factors, it is pointed out that the artistic conception is affected by the personality and the painting artistic conception. Secondly, through the Taoist thought of "the combination of the virtual and real" in landscape painting, so as to reflect that it is the source of the artistic conception of Chinese landscape painting. It is the unique spiritual concept of "Yin and Yang" and "virtual and real" that creates the unique "blank space" aesthetic realm of Chinese painting in the composition of the picture. Finally, it focuses on the "nothingness" in Taoist philosophy and the "blank space" in Chinese landscape painting. The connotation of the "blank space" in Chinese painting exceeds its own expressive significance, which makes the picture form the aesthetic principle of emotional blending, virtual and real combination and dynamic and static integration. Through the "blank space", it deepens the artistic characteristics of the picture and sublimates the expression of "form" in Chinese painting.

• Information Systems Review
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• v.25 no.1
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• pp.93-110
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• 2023

Recently, attempts have been made to convert unstructured text into vectors and to analyze vast amounts of natural language for various purposes. In particular, the demand for analyzing texts in specialized domains is rapidly increasing. Therefore, studies are being conducted to analyze specialized and general-purpose documents simultaneously. To analyze specific terms with general terms, it is necessary to align the embedding space of the specific terms with the embedding space of the general terms. So far, attempts have been made to align the embedding of specific terms into the embedding space of general terms through a transformation matrix or mapping function. However, the linear transformation based on the transformation matrix showed a limitation in that it only works well in a local range. To overcome this limitation, various types of nonlinear vector alignment methods have been recently proposed. We propose a vector alignment model that matches the embedding space of specific terms to the embedding space of general terms through end-to-end learning that simultaneously learns the autoencoder and regression model. As a result of experiments with R&D documents in the "Healthcare" field, we confirmed the proposed methodology showed superior performance in terms of accuracy compared to the traditional model.

• Journal of the Korean Society of Radiology
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• v.83 no.3
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• pp.538-558
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• 2022

The perivascular space (PVS) of the brain, also known as Virchow-Robin space, consists of cerebrospinal fluid and connective tissues bordered by astrocyte endfeet. The PVS, in a word, is the route over the arterioles, capillaries, and venules where the substances can move. Although the PVS was identified and described first in the literature approximately over 150 years ago, its importance has been highlighted recently after the function of the waste clearing system of the interstitial fluid and wastes was revealed. The PVS is known to be a microscopic structure detected using T2-weighted brain MRI as dot-like hyperintensity lesions when enlarged. Although until recently regarded as normal with no clinical consequence and ignored in many circumstances, several studies have argued the association of an enlarged PVS with neurodegenerative or other diseases. Many questions and unknown facts about this structure still exist; we can only assume that the normal PVS functions are crucial in keeping the brain healthy. In this review, we covered the history, anatomy, pathophysiology, and MRI findings of the PVS; finally, we briefly touched upon the recent trials to better visualize the PVS by providing a glimpse of the brain fluid dynamics and clinical importance of the PVS.