• Health Policy and Management
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• v.29 no.2
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• pp.138-145
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• 2019

Background: The purpose of this study is supposed to figure out the keyword network from 2009 to 2018 with social network analysis and provide the research data that can help the Korea government's policy making on smoking cessation. Methods: First, frequency analysis on the keyword was performed. After, in this study, I applied three classic centrality measures (degree centrality, betweenness centrality, and eigenvector centrality) with R 3.5.1. Moreover, I visualized the results as the word cloud and keyword network. Results: As a result of network analysis, 'smoking' and 'smoking cessation' were key words with high frequency, high degree centrality, and betweenness centrality. As a result of looking at trends in keyword, many study had been done on the keyword 'secondhand smoke' and 'adolescent' from 2009 to 2013, and 'cigarette graphic warning' and 'electronic cigarette' from 2014 to 2018. Conclusion: This study contributes to understand trends on smoking cessation study and seek further study with the keyword network analysis.

• Proceedings of the KSPS conference
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• 2005.04a
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• pp.77-80
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• 2005

The aim of this paper was to analyze the lexical effects on spoken word recognition of Korean monosyllabic word. The lexical factors chosen in this paper was frequency, density and lexical familiarity of words. Result of the analysis was as follows; frequency was the significant factor to predict spoken word recognition score of monosyllabic word. The other factors were not significant. This result suggest that word frequency should be considered in speech perception test.

• MALSORI
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• no.62
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• pp.51-68
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• 2007

Two experiments were conducted to determine the exact locus of the frequency effect in speech production. Experiment 1 addressed the question as to whether the word frequency effect arise from the stage of lemma selection. A picture-word interference task was performed to test the significance of interactions between the effects of target frequency, distractor frequency and semantic relatedness. There was a significant interaction between the distractor frequency and the semantic relatedness and between the target and the distractor frequency. Experiment 2 examined whether the word frequency effect is attributed to the lexeme level which represent phonological information of words. A methodological logic applied to Experiment 2 was the same as that of Experiment 1. There was no significant interaction between the distractor frequency and the phonological relatedness. These results demonstrate that word frequency has influence on the processes involved in selecting a correct lemma corresponding to an activated lexical concept in speech production.

• Journal of Korean Elementary Science Education
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• v.33 no.4
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• pp.674-682
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• 2014

This study aims to analyze STEAM-related articles and to look into the trend of research to present implications for research directions in the future. To achieve the research purpose, the researcher searched by key words, 'STEAM' and 'Convergence Education' through the RISS. Subjects of analysis were titles of 181 articles in journal articles and conference papers published from 2011 through 2013. Through an analysis of the frequency of the texts that appeared in the titles of the papers, key words were selected, the co-occurrence matrix of the key words was established, and using network maps, degree centrality and betweenness centrality, and structural equivalence, a network text analysis was carried out. For the analysis, KrKwic, KrTitle, UCINET and NetMiner Program were used, and the results were as follows: in the result of the text frequency analysis, the key words appeared in order of 'program', 'development', 'base' and 'application'. Through the network among the texts, a network built up with core hubs such as 'program', 'development', 'elementary' and 'application' was found, and in the degree centrality analysis, 'program', 'elementary', 'development' and 'science' comprised key issues at a relatively high value, which constituted the pivot of the network. As a result of the structural equivalence analysis, regarding the types of their respective relations, it was analyzed that there was a similarity in four clusters such as the development of a program (1), analysis of effects (2) and the establishment of a theoretical base (1).

• The Journal of the Acoustical Society of Korea
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• v.30 no.5
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• pp.295-302
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• 2011

The purpose of this study was to develop Korean Consonant Perception Test (KCPT), that is a phonemic level including elementary data to evaluate speech and consonant perception ability of the normal and the hearing impaired qualitatively and quantitatively. KCPT was completed with meaningful monosyllabic words out of possible all Korean monosyllabic words, considering articulation characteristics, the degree of difficulty, and the frequency of the phonemic appearance, after assembling a tentative initial and final consonants testing items using four multiple-choice method which were applied to the seven final consonant regulation and controlled with the familiarity of the target words. Conclusively, the final three hundred items were developed including two- and one-hundred items for initial and final testing items, respectively, with the evaluation of the 20 normal hearing adults. Through this process, the final KCPT was composed upon the colloquial frequency following identification of no speakers' variances statistically and elimination of the highly difficult items. The 30 hearing impaired were tested with KCPT and found that the half lists, A and B, were not different statistically and the initial and final testing items were appropriate for evaluating initial and final consonants, respectively.

• The Journal of the Acoustical Society of Korea
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• v.33 no.4
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• pp.248-254
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• 2014

Among acoustic signal analysis tasks, acoustic context awareness is one of the most formidable tasks in terms of complexity since it requires sophisticated understanding of individual acoustic events. In conventional context awareness methods, individual acoustic event detection or recognition is employed to generate a relevant decision on the impending context. However this approach may produce poorly performing decision results in practical situations due to the possibility of events occurring simultaneously or the acoustically similar events that are difficult to distinguish with each other. Particularly, the babble noise acoustic event occurring at a bus or subway environment may create confusion to context awareness task since babbling is similar in any environment. Therefore in this paper, a frequency-cepstral feature vector is proposed to mitigate the confusion problem during the situation awareness task of binary decisions: bus or metro. By employing the Support Vector Machine (SVM) as the classifier, the proposed feature vector scheme is shown to produce better performance than the conventional scheme.

• Journal of The Korean Society of Integrative Medicine
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• v.9 no.4
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• pp.167-181
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• 2021

Purpose : This study was conducted to investigate whether phonetic complexity affected the type and frequency of articulation errors and the acoustic duration of consonants and words produced by children with functional articulation and phonological disorders. Methods : The participants in this study were 20 children with functional articulation and phonological disorders and 20 children without such disorders who were between 3 years 7 months old and 4 years 11 months old. The participants were asked to name what they saw in pictures and their responses were recorded. The types and frequencies of articulation errors and the acoustic duration of words were analyzed and words were categorized as being of either 'high' or 'low' phonetic complexity. The acoustic duration of initial and final consonants and vowels following initial consonants were compared between the groups according to articulatory complexity. Results : Children with functional articulation and phonological disorders produced articulation errors more frequently when saying high complexity words and had longer word duration when saying low-complexity words than children without such disorders. There was no major difference in initial and final consonant duration between the groups. but the main effect of articulatory complexity on the duration of both consonants was significant. Conclusion : These results suggest that the articulatory-phonic structure of words influences the speech motor control ability of children with functional articulation and phonological disorders. When articulating consonants, children with functional articulation and phonological disorders had speech motor control ability similar to that of children without such disorders.

• Journal of the Korea Computer Industry Society
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• v.2 no.6
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• pp.775-782
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• 2001

Until recently Web retrieval engine has presented a demanded document to users according to the amount and the frequency of inquired key words in each document under the assumption that the more key words a document has, the more accessible it is. This method of searching doesn't matter to a normal document such as HTML Web data in which structural information is not involved. However, Web data realized in XML contains structural information and modeling of graphic forms is also available. Therefore, in the case of XML, this method leads to no less trouble since it depends only on the frequency of key words. We consider that this problem can be resolved by way of inquiry which is similar to SQL. This form of inquiry enables us to snatch an exact data we want in a quick and clear way with a full advantage of structural quality of XML, overcoming the shortcomings of frequency-based engine. In this paper, We aim to design a model of information retrieval system of XML data using XML DOM and consider its algorithm related with it.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.161-169
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• 2015

Realtime search words of typical portal sites appear every few seconds in descending order by search frequency in order to show issues increasing rapidly in interest. However, the characteristics of realtime search words reordering within too short a time cause problems that they go over the key issues of the day. This paper proposes a method for deriving a key issue through association analysis of realtime search words. The proposed method first makes scores of realtime search words depending on the ranking and the relative interest, and derives the top 10 search words through descriptive statistics for groups. Then, it extracts association rules depending on 'support' and 'confidence', and chooses the key issue based on the results as a graph visualizing them. The results of experiments show that the key issue through association rules is more meaningful than the first realtime search word.

• Journal of The Korean Association of Information Education
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• v.21 no.1
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• pp.57-66
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• 2017

Lately, academic interests in big data analysis and social network has been prominently raised. Various academic fields are involved in this social network based research trend, which is, social network has been actively used as the research topic in social science field as well as in natural science field. Accordingly, this paper focuses on the text analysis and the following social network analysis with the Master's and Doctor's dissertations. The result indicates that certain words had a high frequency throughout the entire period and some words had fluctuating frequencies in different period. In detail, the words with a high frequency had a higher betweenness centrality and each period seems to have a distinctive research flow. Therefore, it was found that the subjects of the Master's and Doctor's dissertations were changed sensitively to the development of IT technology and changes in information curriculum of elementary, middle and high school. It is predicted that researches related to smart, mobile, smartphone, SNS, application, storytelling, multicultural, and STEAM, which had an increased frequency in period 4, would be continuously conducted. Moreover, the topics of robots, programming, coding, algorithms, creativity, interaction, and privacy will also be studied steadily.