• Korean Association of Arts Management
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• no.58
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• pp.153-177
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• 2021

This study attempted to analyze language networks based on the theory of art policy in the New Normal era triggered by COVID-19 and domestic and foreign policy trends. For analysis, data containing key words of "Corona" and "Art" were collected from Google News and Web documents from March to September 2020 to extract 227 refined subject words, and the extracted subject words were analyzed as indicators of frequency and centrality of subject words through the Netminor program. In addition, visualization analysis of semantic networks has been attempted for the analysis of relationships between each topic languages. As a result of the semantic network analysis, the most frequent topic was "Corona," and "Culture and Art," "Art," "Performance," "Online" and "Support" were included in the group with the most frequencies. In the centrality analysis, "Corona" was the most popular, followed by "the era," "after," "post," "art," and "cultural arts," with high frequency, "Corona," "art," and "cultural arts" also dominated most centrality. In particular, the top-level key words in the analysis of frequency and centrality of the topic are 'online' and 'support' and 'policy'. This can be seen as indicating that the rapid rise of non-face-to-face and online content and support policies for the artistic communities are needed due to the dailyization of social distance due to COVID-19.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.91-98
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• 2019

The present study was performed to investigate the general research trends of dyslexia and learning disability to explore the centrality of related variables though analysis of keyword networks. Data were collected from ten years articles research information sharing service(RISS) which is provided by korea education and research information service(KERIS). The research subjects selected for the analysis were keyword cleansing work, extraction major keyword using KrKwic program and using NodeXL program to Visualize the center of connection between keyword. The results of this were as follows. First, totally 72 of keyword were extracted from keyword cleansing process and among those keyword. major keywords included learning disability, dyslexia, RTI. Second, analysis of the betweenness centrality of dyslexia and learing disabilities shows that learning disabilities are a key word that has been addressed in the study of dyslexia and learning disabilities in korea. The results of these studies suggest a method of analyzing trends in qualitative and qualitative analysis in relation to dyslexia and learning disorder.

• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.54-60
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• 2020

Online cybercrime has various causes. The criminal guilty language, Criminal lingo is active in the shaded area with the bilateral aspect of the word on cyber. It has been continuously producing massive risk factors in cyberspace. Criminals are shared and disseminated online. It has been linked with fake news and aids to suicide that has recently become an issue. Thus the criminal lingo has become a real danger factor on cyber interface. Recently, Criminal lingo is shared and distributed as cyber hazard information. It is transformed that damaging to the youth and ordinary people through the internet and social networks. In order to take action, it is necessary to construct an expert system based on AI to implement a smart management architecture with block-chain technology. In this paper, we study technically a new smart management architecture which uses artificial intelligence based decision algorithm and block-chain tracking technology to prevent the spread of criminal lingo factors in the evolving cyber world. In addition, through the off-line regular patrol program of police units, we proposed the conversion of online regular patrol program for "cyber harem area".

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.1B
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• pp.25-37
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• 2008

Network streaming technology is a service method which can support several application software via streaming in networks. Although multimedia streaming technology has been developed and widely used, research on the software streaming technology is not yet being progressed actively. In this paper, we design and implement a software streaming technology based on Java language with enhanced performance, compare the existing related systems with it and analyze several characteristics, and perform the performance evaluation. The implemented system has a platform to be used in multiple operating systems in addition to Windows system. It can also be used without installing a software at the client's computer, and has a novel feature that the user's convenience is maximized.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.241-248
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• 2021

The article reviews the social media as an Internet phenomenon, determines their place and level of popularity in the society, as a result of which the social networks are a resource with perspective pedagogical potential. The analysis of social media from the point of view of studying a foreign language and the possibility of their usage as a learning medium has been carried out. The most widespread and popular platforms have been considered and, based on their capabilities in teaching all types of speech activities, the "Instagram", "Twitter", and "Facebook" Internet resources have been selected as the subject of the research. The system of tasks of teaching all types of speech activities and showing the advantages of the "Instagram", "Twitter", and "Facebook" platforms has been proposed and briefly reviewed.

• Journal of the Korea Computer Industry Society
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• v.3 no.8
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• pp.963-980
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• 2002

Software reengineering is making various research for solutions against problem of maintain existing systems. Reengineering has a meaning of development of software on exizting systems through the reverse engineering auf forward engineering. Most of the important concepts used in reengineering is composition that is restructuring of the existing objects. Is there a compiler that can compile a program written in a traditional procedural language (like C or Pascal) and generate a Java bytecode, rather than an executable code that runs oかy on the machine it was compiled (such as an a.out file on a Unix machine)\ulcorner This type of compiler may be very handy for today's computing environment of heterogeneous networks. In this paper we present a software system that does this job at the binary-to-binary level. It takes the compiled binary code of a procedural language and translates it into Java bytecode. To do this, we first translate into an assembler code called Jasmin [7] that is a human-readable representation of Java bytecode. Then the Jasmin assembler converts it into real Java bytecode. The system is not a compiler because it does not start at the source level. We believe this kind of translator is even more useful than a compiler because most of the executable code that is available for sharing does not come with source programs. Of course, it works only if the format of the executable binary code is known. This translation process consists of three major stages: (1) analysis stage that identifies the language constructs in the given binary code, (2) initialization stage where variables and objects are located, classified, and initialized, and (3) mapping stage that maps the given binary code into a Jasmin assembler code that is then converted to Java bytecode.

• Korean journal of communication and information
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• v.45
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• pp.220-254
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• 2009

Presidential TV debates serve as an important instrument for the general viewers to evaluate the candidates’ character, to examine their policy, and finally to make an important political decisions to cast ballots. Every words candidates utter in the course of entire election campaign exert influence of a certain significance by delivering their ideas and by creating clashes with their respective opponents. This study focuses on the conceptual venue, coined as ‘stasis’ by ancient rhetoricians, in which the clashes take place, and examines the words selection made by each candidates, the manners in which they form stasis, call for evidence, educate the public, and finally create a legitimate form of political argumentation. The study applied computer based content analysis using KrKwic and UCINET software to analyze semantic networks among the candidates. The results showed three major candidates, namely Lee Myung Bak, Jung Dong Young, and Lee Hoi Chang, displayed separate patterns in their use of language, by selecting the words that are often neglected by their opponents. Apparently, the absence of stasis and the lack of speaking mutual language significantly undermined the effects of debates. Central questions regarding issues of North Korea failed to meet basic requirements, and the respondents failed to engage in effective argumentation process.

• Journal of Navigation and Port Research
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• v.38 no.6
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• pp.607-614
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• 2014

This article aims to explore and discuss research trends in global cruise industry using keyword network analysis. We visualize keyword networks in each of four groups of 1982-1999, 2000-2004, 2005-2009, 2010-2014 based on the top 20 keyword nodes' degree centrality and betweenness centrality which are selected among four centrality measurements, comparing them with frequency order. The article shows that keyword frequency collected from 240 articles published in international journals is subject to Zipf's law and nodes degree distribution also exhibits power law. We try to find out research trends in global cruise industry to change some important keywords diachronically, visualizing several networks focusing on the top two keywords, cruise and tourism, belonging to all the four year groups, with high degree and betweenness centrality values. Interestingly enough, a new node, China, connecting the top most keywords, appears in the most recent period of 2010-2014 when China has emerged as one of the rapid development countries in global cruise industry. Therefore keyword network analysis used in this article will be useful to understand research trends in global cruise industry because of increase and decrease of numbers of network types in different year groups and the visual connection between important nodes in giant components.

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.351-363
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• 2015

Discourse analysis is useful for examining discourse characteristics of dementia patients and differentiating them from normal adults. However, inconsistent tasks, transcription methods and measures have been utilized, thus analyses were inevitably unsystematic. The purpose of this study was to investigate tasks, transcription methods and measures of discourse studies in dementia. Studies on dementia discourses written in English were collected via Scopus database containing abstracts and citations from 2005 to 2014, and were analyzed in detail. From the results, the most frequently used task was 'storytelling-topic'. It was observed that use of consistent transcription conventions rendered more reliable transcription data. Measures could be categorized into coherence, cohesion, productivity, propositional syntactic lexical analysis, and fluency, and each category belonged to discourse processing levels (i.e., processing of conceptual networks, propositions, and natural language units). In conclusion, future research warrants not only utilization of discourse tasks depending on dementia types and features, but also application of consistent transcription conventions. Additionally, measures based on the discourse processing theory would enable us to systematically interpret discourse studies.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.1
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• pp.34-42
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• 2011

In an effort to the practical realization of phonetic typewriter, we concentrate on the classification of consonants in this paper. Since many of consonants do not show periodic behavior in time domain and thus the validity for Fourier analysis of them are not convincing, vector quantization (VQ) via LBG clustering is first performed to check if the feature vectors of MFCC and LPCC are ever meaningful for consonants. Experimental results of VQ showed that it's not easy to draw a clear-cut conclusion as to the validity of Fourier analysis for consonants. For classification purpose, two kinds of neural networks are employed in our study: self organizing map (SOM) and learning vector quantization (LVQ). Results from SOM revealed that some pairs of phonemes are not resolved. Though LVQ is free from this difficulty inherently, the classification accuracy was found to be low. This suggests that, as long as consonant classification by LVQ is concerned, other types of feature vectors than MFCC should be deployed in parallel. However, the combination of MFCC/LVQ was not found to be inferior to the classification of phonemes by language-moded based approach. In all of our work, LPCC worked worse than MFCC.