• English Language & Literature Teaching
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• v.10 no.2
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• pp.43-65
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• 2004

In the comprehension of English texts, Korean students generally try to translate English into Korean in accordance with the word order of Korean language. As a result, the comprehension of English texts is made in a regressive way, which results in slower reading. In order to enhance the reading speed, it is necessary for students to practice progressive reading. Also, while reading English texts, most readers' eyes tend to look at one word at a time, which actually cuts down on the reading speed. Reading by the sense group of as many words as possible at a glance, however, can help a reader more efficiently in less time. This research aims at developing the Powerpoint program for progressive reading by the sense group according to the student's level. In this program, as for methodology, the technique of rooking it fade-away is introduced to force a reader's eyes to move fast. Through this technique, it is possible to make a line of the texts disappear on the screen and make another line appear, which enables a reader to sweep the words across each and every line of the reading material smoothly without regression.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.32-41
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• 2000

In this paper, we proposed a method which predict the verb by using the neural network in order to enhance communication rate in augmentative communication system for Korean language disorders. Each word is represented by an information vector according to syntax and semantics, and is positioned at the state space by being partitioned into various regions different from a dictionary-like lexicon. Conceptual similarity is realized through position in state space. When a symbol was pressed, we could find the word for the symbol at the position in the state space. In order to prevent verb prediction's redundancy according to input units, we predicted the verb after separating class using the neural network. In the result we can enhance $20\% communication rate in the restricted space

• English Language & Literature Teaching
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• v.13 no.2
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• pp.47-61
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• 2007

The purpose of this paper is to survey the major elements that have changed English from a synthetic language to an analytic one. Therefore, this paper has looked at the differences between synthetic languages and analytic ones. In synthetic languages, the relation of words in a sentence is synthetically determined by means of inflections, while in analytic languages, the functions of words in a sentence are analytically determined by means of word order and function words. Thus, Old English with full inflectional systems shows the synthetic nature. However, in the course of time, Old English inflections came to be lost by phonetic changes and operation, which made English dependent on word order and function words to signal the relation of words in a sentence. The major phonetic changes that have shifted English are the change of final /m/ to /n/, the leveling of unstressed vowels, the loss of final /n/, and the decay of schwa in final syllables. These changes led to reduction of inflections of English as well as the loss of grammatical gender. The operation of analogy, the tendency of language to follow certain patterns and to adapt a less common form to a more familiar one, has also played an important role in changing English.

• Speech Sciences
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• v.10 no.4
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• pp.241-254
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• 2003

The purpose of the present study was to investigate the sentence comprehension strategies used by Korean/English bilingual children when they listened to sentences of their first language, i.e., Korean. The framework of competition model was employed to analyze the influence of the second language, i.e., English, during comprehension of Korean sentences. The participants included 10 bilingual children (ages 7;4-13;0) and 20 Korean-speaking monolingual children(ages 5;7-6;10) with similar levels of development in Korean language as bilingual children. In an act-out procedure, the children were asked to determine the agent in sentences composed of two nouns and a verb with varying conditions of three cues (case-marker, animacy, and word-order). The results revealed that both groups of children used the case marker cues as the strongest cue among the three. The bilingual children relied on case-marker cues even more than the monolingual children. However, the bilingual children used animacy cues significantly less than the monolingual children. There were no significant differences between the groups in the use of word-order cues. The bilingual children appeared less effective in utilizing animacy cues in Korean sentence comprehension due to the backward transfer from English where the cue strength of animacy is very weak. The influence of the second language on the development of the first language in bilingual children was discussed.

• Journal of Internet Computing and Services
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• v.10 no.6
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• pp.113-121
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• 2009

In order to retrieve images with different emotions in regions of the images, this paper proposes the image retrieval system using emotion sketch. The proposed retrieval system divides an image into $17{\times}17$ sub-regions and extracts emotion features in each sub-region. In order to extract the emotion features, this paper uses emotion colors on 160 emotion words from H. Nagumo's color scheme imaging chart. We calculate a histogram of each sub-region and consider one emotion word having the maximal value as a representative emotion word of the sub-region. The system demonstrates the effectiveness of the proposed emotion sketch and our experimental results show that the system successfully retrieves on the Corel image database.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.5
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• pp.1027-1037
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• 2019

Conventional cyber-attack detection solutions are generally based on signature-based or malicious behavior analysis so that have had difficulty in detecting unknown method-based attacks. Since the various information occurring all the time reflects the state of the system, by modeling it in a steady state and detecting an abnormal state, an unknown attack can be detected. Since a variety of system information occurs in a string form, word embedding, ie, techniques for converting strings into vectors preserving their order and semantics, can be used for modeling and detection. Novelty Detection, which is a technique for detecting a small number of abnormal data in a plurality of normal data, can be performed in order to detect an abnormal condition. This paper proposes a method to detect system anomaly by cyber attack using embedding and novelty detection.

• The Journal of Industrial Distribution & Business
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• v.12 no.2
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• pp.19-27
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• 2021

Purpose: This study investigated the impact of key factors such as service quality, perceived benefit and brand familiarity on a consumer's intention to order online food delivery (OFD). In addition, mediating effect of electronic word of mouth (e-WOM) between relationships among selected key variables and OFD purchase intention is also assessed. Research design, data and methodology: This explanatory, quantitative study employed convenience sampling and collected data through online structured questionnaire from 304 respondents who are users of OFD apps based in greater Klang valley region of Malaysia. The data was then subjected to normality and reliability assessment followed by confirmatory factor analysis, validity assessment and structural equation modelling using IBM SPSS AMOS 24.0. Results: Findings revealed that service quality, perceived benefits and brand familiarity affects purchase intention positively and significantly. Perceived benefits demonstrated highest impact on purchase intention followed by brand familiarity and service quality. Findings also suggest that e-WOM fully mediates relationship between brand familiarity and purchase intention, however, the same was not observed for remaining two variables. Conclusions: The study has enriched OFD literature by investigating impact of selected key factors on purchase intention in the context of OFD. Implications, limitations and future research avenues are then discussed.

• Journal of The Korean Association of Information Education
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• v.7 no.1
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• pp.37-47
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• 2003

A grading system of practical word processor skills is designed and implemented by using HWPML(Hangul Word Processor Markup Language) which is a product of Hangul and Computer Co Ltd. By using HWPML, which is a markup tag structure of Hangul file, Hangul files can be edited in other application programs. Authorized users can make questions. However, only the manager is allowed to register answers to the questions in order to maintain the correctness of grading. The result of test is stored in the database and the statistics on pass or failure can be shown interactively. The number of taking test and scores for each user are stored in the database and they can be accessed to whenever the user wants them. Comments on the test results are provided by the manager so that learners can intensity their weak points.

• Journal of Digital Convergence
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• v.11 no.5
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• pp.225-235
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• 2013

Recently, in order to promote their marketing promotion, the entrepeneurs attach importance to many SNS services and execute it. The representative elements of the SNS service are interactivity, information offering. This study analyzes empirical effects on the SNS service depending on the Relationship Commitment and shows the strategies to enlarge the use frequency and the On-line Word-of-Mouth. The conclusion of this study shows that the Interactivity has a higher positive effects on Affective Commitment than those on information offering and Information offering has stronger positive effects on calculative commitment than interactivity. Also, these effects enlarge the high use frequency more than the low use frequency. This study also shows that the information offering affect the On-line Word-of-Mouth more positively than the Interactivity. And this study shows that SNS service affects the positive effects on the relationship commitment rather than the On-line Word-of-Mouth. Based on the results, the practical implications are offered.

• Journal of KIISE
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• v.44 no.5
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• pp.522-536
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• 2017

Keyword extraction can be utilized in text mining of massive documents for efficient extraction of subject or related words from the document. In this study, we proposed a hierarchical graph model based on the co-occurrence relationship, the intrinsic dependency relationship between words, and common sub-word in a single document. In addition, the enhanced TextRank algorithm that can reflect the influences of outgoing edges as well as those of incoming edges is proposed. Subsequently a novel keyword extraction scheme using the proposed hierarchical graph model and the enhanced TextRank algorithm is proposed to extract representative keywords from a single document. In the experiments, various evaluation methods were applied to the various subject documents in order to verify the accuracy and adaptability of the proposed scheme. As the results, the proposed scheme showed better performance than the previous schemes.