• Bulletin of the Korean Mathematical Society
• /
• v.52 no.6
• /
• pp.1797-1803
• /
• 2015

Let ($S_{\alpha}(n))_{n{\geq}1}$ be the lexicographically greatest Sturmian word of slope ${\alpha}$ > 0. For a fixed ${\sigma}$ > 1, we consider Dirichlet series of the form ${\nu}_{\sigma}({\alpha})$ := ${\Sigma}_{n=1}^{\infty}s_{\alpha}(n)n^{-{\sigma}}$. This paper studies the singular properties of the real function ${\nu}_{\sigma}$, and the Lebesgue-Stieltjes measure whose distribution is given by ${\nu}_{\sigma}$.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.2
• /
• pp.292-298
• /
• 1999

An information structure of large size hypermedia application is usually hierarchical, and the sibling nodes in this structure have same or similar tags and contents. a word "개그" that means the common set of sibling nodes in the hierarchical information structure is used in this paper. It proposes a design method that divides form and content from nodes and it proposes HTML page generation algorithm from forms and contents. This method has reusability of form, maintainability of documents and reduction of cost for authoring.

• Proceedings of the Korean Society for Language and Information Conference
• /
• 2002.02a
• /
• pp.177-186
• /
• 2002

Korean predicative verb forms obligatorily denote the three categories speech level, mood and sentence type which are not handled by most of the automatic word form recognition systems for this language. These categories are marked by special endings. This paper examines predicative verb forms concentrating on the lexical description of these endings in the framework of Left-Associative Grammar (LAG). Additionally this paper suggests a system to analyse verb forms in these aspects. The results of this study have been implemented using Malaga$^2$ and integrated into an automatic word form recognition system for Korerin called KMM (Korean Malaya Morphology).

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.6
• /
• pp.1964-1972
• /
• 2000

For the Korean language, on acoustics, it creates a different form of phonetic value not a phoneme by its own peculiar property. Therefore, the construction of extended recognition system for understanding Korean language should be created with a study of the Korean rule-based system, before it can be used as post-processing of the Korean recognition system. In this paper, text-based Korean rule-based system featuring Korean peculiar vocal sound changing rule is constructed. and based on the text-based phonetic value result of the system constructed, a preliminary phonetic value segmentation border points with non-uniform blocks are extracted in Korean isolated word speech. Through the way of merge and recognition of the non-uniform blocks between the extracted border points, recognition possibility of Korean voice as the form of the phonetic vale has been investigated.

• Speech Sciences
• /
• v.14 no.1
• /
• pp.7-19
• /
• 2007

The present study investigates the so-called frequency inheritance effect in word production. According to some earlier studies (e.g. Jescheniak & Levelt, 1994), retrieval of a low-frequency homophone benefits from its high-frequency homophone twin, and more specifically word-retrieval RT is determined by the frequency of the phonological form of the word (sum of homophone frequencies) rather than the frequency of the specific word. This result, however, has been challenged by later studies (e.g. Caramazza et al., 2001) and one possible resolution is that languages differ in the extent to which the inheritance effect occurs. Two experiments are reported to test whether the frequency inheritance effect depends on the target language, namely, if a language such as Korean with relatively many homophones tend not to show frequency inheritance, which is compared with the language with fewer homophones such as Dutch and German (Jescheniak & Levelt, 1994; Jescheniak et al., 2003). Experiment 1 was picture naming, and Experiment 2 used an English-to-Korean translation task. In both experiments, the homophones were actually slower than the low-frequency controls, suggesting that there was no evidence for the inheritance effect. These results imply that the issue of whether specific word or homophone frequency determines production can be properly assessed by taking into account the language-specific nature of the lexicon such as the percentage of the homophone words in that language.

• Journal of the Korea Fashion and Costume Design Association
• /
• v.6 no.2
• /
• pp.77-87
• /
• 2004

The purpose of this study was to analize the types of symbol concretely, one of a constituent elements of brand, using in Apparel Brands and to examine the meaning of symbol in the internet site of each brand and to evaluate the symbols in the aesthetic dimension and to suggest a basic data of the branding strategy for marketers. For this purpose, 41 Apparel Brands were selected from fashion magazine and the types of symbol used in the Apparel Brands were classified into three types. According to the formative characters of symbol, there were word symbol, descriptive symbol and abstractive symbol. The results of the study were following: the order was the descriptive symbol, word symbol, and abstractive symbol. The percentages of using symbols were descriptive symbol(61%), word symbol(29%), and abstractive symbol(l0%). The Apparel Brands used the most frequently the descriptive symbol that represents or symbolizes a concrete object to represent the image of brand. The abstractive symbol that use a graphic style or geometrical form to deliver the character of brand was used lowest. From this results, we could find that the descriptive symbol was used to deliver/notify the character or image of company's own brand easy and quickly to consumers in symbolic meaning making use of a concrete object such as a animal, plant, specific object or fictitious person, etc than word or abstractive symbol.

• Smart Media Journal
• /
• v.7 no.4
• /
• pp.24-29
• /
• 2018

Text analysis technique for natural language processing in deep learning represents words in vector form through word embedding. In this paper, we propose a method of constructing a document vector and classifying it into spam and normal text message, using word embedding and deep learning method. Automatic spacing applied in the preprocessing process ensures that words with similar context are adjacently represented in vector space. Additionally, the intentional word formation errors with non-alphabetic or extraordinary characters are designed to avoid being blocked by spam message filter. Two embedding algorithms, CBOW and skip grams, are used to produce the sentence vector and the performance and the accuracy of deep learning based spam filter model are measured by comparing to those of SVM Light.

• Proceedings of the Korea Society of Design Studies Conference
• /
• 2001.10a
• /
• pp.55.2-55
• /
• 2001

• Journal of architectural history
• /
• v.26 no.6
• /
• pp.19-28
• /
• 2017

In this paper, I have reviewed some of the Korean traditional architectural vocabularies that have to be reconsidered in terms of the problem of decode, the problem of meaning, the meaning of explain meaning, and the problem of form analysis. Especially, correct decode and interpretation of Uigwe's Korean ancient architecture borrowed character can correct old decode and interpretation. Furthermore, I confirmed that I could correct the Korean ancient architecture vocabulary that was expiscated wrongly. Especially borrowed characters corresponding to 머름[meoreum](paneling) have been known only far away 遠音[meoreum]. In addition, there were also 遠驗[meolheom] 亇乙軒[meolheon] 亇乙險[meolheom] 亇乙音[meoreom], and so on. Furthermore, in the process of decode these notations, it has become possible to assume that the original words of the modern language 머름[meoreum] also came from *멀험[meolheom]. On the other hand, there are many kinds of people like 付叱心[bussim] 夫叱心[bussim] 扶叱心[bussim] 富叱心[bussim] 富心[bussim]과 北叱心 [bussim] 北心[bussim]. You can also check the Korean ancient architecture vocabulary. However, corresponding words are difficult to find in modern Korean languages. However, in Jeju dialect, we can confirm the corresponding word. This word was used in the Joseon Dynasty, and confirmed that it is dead language today. As mentioned above, it is confirmed that there are many misconceptions about the decode and meaning of the architectural vocabulary made of borrowed character in existing architectural dictionaries, Korean dictionaries, and Korean ancient architecture related papers. Also, although the form is being confirmed, it has been confirmed that there are many things that need to be clarified, such as what the decode is, what the meaning is, and the origin I have also confirmed a number of things that need to be properly expomed in the original form, the original word. In the future, those who study Korean ancient architecture vocabulary and traditional architectural vocabulary should also be interested in these things and research it properly.

• Korean Journal of Cognitive Science
• /
• v.15 no.2
• /
• pp.33-42
• /
• 2004

There are many syntactic similarities between Japanese and Korean language. These similarities enable us to build Japanese-Korean translation systems without depending cm sophisticated syntactic analysis and semantic analysis. To further improve translation accuracy, we have been developing a Japanese-Korean translation system using these similarities for several years. However, there still remain some problems with regard to translation of inflected words, processing of multi-translatable words and so on. In this paper, we propose a new method for Japanese-Koran machine translation by using the relationships of two neighboring words. To solve the problems, we investigate the connection rules of auxiliary verb priority. And we design the translation table, which consists of entry tables and connection form tables. for unambiguous words, we can translate a Japanese word to the corresponding Korean word in terms of direct-matching method by consulting the only entry table. Otherwise we have to evaluate the connection value computed from connection form tables and then we can select the most appropriate target word.