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

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.3
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• pp.16-23
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• 2001

In this paper, we propose the pseudo n-gram language models for speech recognition with middle size vocabulary compared to large vocabulary speech recognition using the statistical n-gram language models. The proposed method is that it is very simple method, which has the standard structure of ARPA and set the word probability arbitrary. The first, the 1-gram sets the word occurrence probability 1 (log likelihood is 0.0). The second, the 2-gram also sets the word occurrence probability 1, which can only connect the word start symbol and WORD, WORD and the word end symbol . Finally, the 3-gram also sets the ward occurrence probability 1, which can only connect the word start symbol , WORD and the word end symbol . To verify the effectiveness of the proposed method, the word recognition experiments are carried out. The preliminary experimental results (off-line) show that the word accuracy has average 97.7% for 452 words uttered by 3 male speakers. The on-line word recognition results show that the word accuracy has average 92.5% for 20 words uttered by 20 male speakers about stock name of 1,500 words. Through experiments, we have verified the effectiveness of the pseudo n-gram language modes for speech recognition.

• Journal of KIISE
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• v.43 no.6
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• pp.678-685
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• 2016

Named Entity Recognition and Classification (NERC) is a task for recognition and classification of named entities such as a person's name, location, and organization. There have been various studies carried out on Korean NERC, but they have some problems, for example lacking some features as compared with English NERC. In this paper, we propose a method that uses word embedding as features for Korean NERC. We generate a word vector using a Continuous-Bag-of-Word (CBOW) model from POS-tagged corpus, and a word cluster symbol using a K-means algorithm from a word vector. We use the word vector and word cluster symbol as word embedding features in Conditional Random Fields (CRFs). From the result of the experiment, performance improved 1.17%, 0.61% and 1.19% respectively for TV domain, Sports domain and IT domain over the baseline system. Showing better performance than other NERC systems, we demonstrate the effectiveness and efficiency of the proposed method.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.14 no.1
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• pp.81-94
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• 2003

Objectives：Developmental reading disorder is a condition which manifests significant developmenttal delay in reading ability or persistent errors. About 3-7% of school-age children have this condition. The purpose of the present study was to validate the diagnostic values of Word/Nonword Reading Test and Letter-Symbol Discrimination Task for the purpose of overcoming the caveats of Basic Learning Skills Test. Methods：Sixty-three reading-disordered patients(mean age 10.48 years old) and sex, age-matched 77 normal children(mean age 10.33 years old) were selected by clinical evaluation and DSM-IV criteria. Reading I and II of Basic Learning Skills Test, Word/Nonword Reading Test, and Letter-Symbol Discrimination Task were carried out to them. Word/Nonword Reading Test：One hundred usual highfrequency words and one hundred meaningless nonwords were presented to the subjects within 1.2 and 2.4 seconds, respectively. Through these results, automatized phonological processing ability and conscious letter-sound matching ability were estimated. Letter-Symbol Discrimination Task：mirror image letters which reading-disordered patients are apt to confuse were used. Reliability, concurrent validity, construct validity, and discriminant validity tests were conducted. Results：Word/Nonword Reading Test：the reliability(alpha) was 0.96, and concurrent validity with Basic Learning Skills test was 0.94. The patients with developmental reading disorders differed significantly from normal children in Word/Nonword Reading Test performances. Through discriminant analysis, 83.0% of original cases were correctly classified by this test. Letter-Symbol Discrimination Task：the reliability(alpha) was 0.86, and concurrent validity with Basic Learning Skills test was 0.86. There were significant differences in scores between the patients and normal children. Factor analysis revealed that this test were composed of saccadic mirror image processing, global accuracy, mirror image processing deficit, static image processing, global vigilance deficit, and inattention-impulsivity factors. By discriminant analysis, 87.3% of the patients and normal children were correctly classified. Conclusion：The patients with developmental reading disorders had deficits in automatized visuallexical route, morpheme-phoneme conversion mechanism, and visual information processing. These deficits were reliably and validly evaluated by Word/Nonword Reading Test and Letter-Symbol Discrimination Task.

• Journal of the Korean Society of Costume
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• v.22
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• pp.297-312
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• 1994

Today though the word ginyoe(gisaeng) was remained as a historic relic but they were firmly existed about 40 years ago and ginyoe's number was about three million in Chosun it's almost near 0.5% of the total population of Chosun. To think that point the ginyoe's so-ciety was considered a special one in the his-tory of Korean woman. The ginyoe as a special social class were specialize in technical art such as dancing and prostitute. Although they were low class they were luxurious slaves whoses clothing was almost equal to that of royal family. They were the leaders of fashion in woman clothing that's because their role was entertainer, This study can be summarized as follows. First ginyoe and public woman's clothing codes were nearly same in koryo but tatally separated in chosun. I could find that was came from those day's moral sprit. Second ginyoe's clothing was not only have luxuriance like royal family but also have unique clothing codes for them. Though they are low class ginyoe could use upper class's clothing codes. But upper class women could'nt use ginyoe's clothing codes are vary various and have their own clothing codes. Third I analyzed ginyoe's clothing codes and then derived 6 ginyoe's clothing messages. They were symbol of wealth symbol of power symbol of occupational function symbol of sexual attraction symbol of social position symbol of freedom.

• Journal of KIISE:Software and Applications
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• v.31 no.9
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• pp.1121-1130
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• 2004

This paper proposes a method for line and word segmentation for machine-printed text blocks. To separate a text region into the unit of lines, it analyses the horizontal projection profile and performs a recursive projection profile cut method. In the word segmentation, between-word gaps are identified by a hierarchical clustering method after finding gaps in the text line by using a connected component analysis. In addition, a special symbol detection technique is applied to find two types of special symbols tying between words using their morphologic features. An experiment with 84 text regions from English and Korean documents shows that the proposed method achieves 99.92% accuracy of word segmentation, while a commercial OCR software named Armi 6.0 Pro$^{TM}$ has 97.58% accuracy.y.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.37 no.9
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• pp.1-10
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• 2000

This paper proposes symbol decoding schemes combined with channel estimation techniques for coded orthogonal frequency division multiplexing (COFDM) systems in fading channels. sThe proposed symbol decoding schemes are consisted of a symbol decoding technique and channel estimation techniques. The symbol decoding based on Viterbi algorithm is achieved by matching the length of branch word from encoder trellis to the codeword length of symbol candidate on decoder trellis. Three combination schemes are described and their error performances are compared. The first scheme is to combine a symbol decoding technique with a training channel estimation technique. The second scheme joins a decision directed channel estimation technique to the first scheme. The time varying channel transfer functions are tracked by the decision directed channel estimation technique and the channel transfer functions used in the symbol decoder are updated every COFDM symbol. Finally, In order to reduce the effect of additive white Gaussian noise (AWGN) between adjacent subchannels, deinterleaved average channel estimation technique is combined. The error performances of the three schemes are significantly improved being compared with that of zero forcing equalizing schemes.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.3
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• pp.200-207
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• 2001

In this paper, we propose an HMM(Hidden Markov modeJ)-MLP(Multi-layer perceptron) hybrid model for recognizing legal words on the English bank check. We adopt an explicit segmentation-based word level architecture to implement an HMM engine with nonscaled and non-normalized symbol vectors. We also introduce an MLP for implicit segmentation-based word recognition. The final recognition model consists of a hybrid combination of the HMM and MLP with a new hybrid probability measure. The main contributions of this model are a novel design of the segmentation-based variable length HMMs and an efficient method of combining two heterogeneous recognition engines. ExperimenLs have been conducted using the legal word database of CENPARMI with encouraging results.

• KIISE Transactions on Computing Practices
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• v.23 no.4
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• pp.226-231
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• 2017

Word representation, an important area in natural language processing(NLP) used machine learning, is a method that represents a word not by text but by distinguishable symbol. Existing word embedding employed a large number of corpora to ensure that words are positioned nearby within text. However corpus-based word embedding needs several corpora because of the frequency of word occurrence and increased number of words. In this paper word embedding is done using dictionary definitions and semantic relationship information(hypernyms and antonyms). Words are trained using the feature mirror model(FMM), a modified Skip-Gram(Word2Vec). Sense similar words have similar vector. Furthermore, it was possible to distinguish vectors of antonym words.

• Journal of Fashion Business
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• v.15 no.5
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• pp.55-68
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• 2011

The purpose of this research is to study the visual characteristics of domestic national men's wear brand logos. For this purpose, 80 of national men's wear brands were selected from '2010/2011 Korea fashion brand Annual' For analysis, they were classified into three categories: logo types composed only with logomark or symbol and logomark together. Types of symbol were classified into word symbol, descriptive symbol, and abstractive symbol. And the used typefaces were classified into serif and san serif and acromatic and cromatic The results are as follows: The visual characteristics of domestic national men's wear brand logos, there were more brands that used logomark with symbol together than logomark only. And the type of symbols were appeared descriptive symbol(32% ) that meaned the men's power, nobleness and royalty. In domestic national men's wear brands, color of logos were more frequently used acromatic color as black and grey than cromatic color. Among the cromatic colors were more appeared to a kind of blue and green. And the used typefaces were the more frequently used to serif typeface of capital. As a result, the visual characteristics of domestic national men's wear brand logo were that they used the brand logos composed of descriptive logomark with symbol together, black serif typeface the most. From this results, we could find that visual stragety of domestic national men's wear brand logos had the tendency to emphasize the function of conveying information, brand concept that men's wear. The specific and continuous following research in which psychological factor of consumer reflected was requested as a measure to seek brand logo that aid to establish brand power and reinforce brand image.