• Annual Conference on Human and Language Technology
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• 2007.10a
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• pp.99-106
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• 2007

본 연구는 국어의 모든 언어적 특성을 기술하고 이를 실제 형태소 분석에 적용할 수 있도록 다차원 해석 사전을 이용하는 형태소 분석 시스템인 moHANA(Morphological Hangul Analyzer)에 관한 연구이다. moHANA의 해석 사전은 태그정보 사전, 어휘 사전 그리고 문법 사전으로 구성된다. 태그정보 사전은 기존 형태소 해석기의 일차원적인 품사 정보와 달리 어류 태그정보, 형태적 정보, 통사적 정보, 의미적 정보 및 화용 정보의 5 차원 벡터 정보로 작성된다. 어휘 사전은 어휘와 그 어휘가 가질 수 있는 태그정보를 우선 순위에 기반하여 순서열로 가지며, 문법 사전은 특수 문법 연산자를 이용하여 태그정보 사전에 정의된 각각의 태그가 연결 가능한지 여부를 규정하는 문법이 구축되어 있다. 형태소가 가지는 태그정보를 다차원으로 정의하고 이에 따른 문법 규칙의 표현을 통해 보다 자세한 형태소 분석 및 새로운 형태소 태그의 삽입과 삭제의 용이함을 얻을 수 있다.

• Journal of Korean Academy of Nursing
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• v.29 no.1
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• pp.21-33
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• 1999

This study was designed to develop a basic plan for computerization of nursing records. The subjects were 7 nursing record forms, 58 charts, 23 nurses, 2 nurse managers, a nurse and computer specialist, 16 master course students and 3 professors. Data collection was conducted through questionnaire, observation and interview. The collected data were analyzed for problems, plan of improvement and needs for computerization. Based upon these results, it is recommended that nursing record computerization was needed a basic plan to integrate needs of nursing record computerization. The basic plan as fellows : 1. To illustrate a data flow path of nursing record and data dictionary that show nurse's work and record process. 2. To establish a system in order to use multi -tasking and graphic user interface. 3. To establish hardware and software in order to embody integrated management of computer based system through structured walkthrough. 4. To choose effective database management system and to achieve Log as record unit.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.787-789
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• 2004

People frequently feel the need of a general searching tool that frees from language barrier when they find information through the internet. Therefore, it is necessary to have a multilingual parallel corpus to search with a word that includes a search keyword and has a corresponding word in another language, Multilingual parallel corpus can be built and reused effectively through the several processes which are judgment of the web documents, sentence alignment and word alignment. To build a multilingual parallel corpus, multi-lingual dictionary should be constructed in each language and HTML should be simplified. And by understanding the meaning and the statistics of document structure, judgment on translated web documents will be made and the searched web pages will be aligned in sentence unit.

• Journal of Integrative Natural Science
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• v.14 no.2
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• pp.35-40
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• 2021

In this paper, we proposed a multi-subject-level sentiment analysis model for user reviews using the Latent Dirichlet Allocation (LDA) method targeting user-generated content (UGC). Data were collected from users' online reviews of hotels in major tourist cities in the world, and 30 hotel-related topics were extracted using the entire user reviews through the LDA technique. Six major hotel-related themes (Cleanliness, Location, Rooms, Service, Sleep Quality, and Value) were selected from the extracted themes, and emotions were evaluated for sentences corresponding to six themes in each user review in the proposed sentiment analysis model. Sentiment was analyzed using a dictionary. In addition, the performance of the proposed sentiment analysis model was evaluated by comparing the emotional values for each subject in the user reviews and the detailed scores evaluated by the user directly for each hotel attribute. As a result of analyzing the values of accuracy and recall of the proposed sentiment analysis model, it was analyzed that the efficiency was high.

• The KIPS Transactions:PartB
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• v.17B no.4
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• pp.295-302
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• 2010

Example-based super resolution(EBSR) is a method to reconstruct high-resolution images by learning patch-wise correspondence between high-resolution and low-resolution images. It can reconstruct a high-resolution from just a single low-resolution image. However, when it is applied to a text image whose font type and size are different from those of training images, it often produces lots of noise. The primary reason is that, in the patch matching step of the reconstruction process, input patches can be inappropriately matched to the high-resolution patches in the patch dictionary. In this paper, we propose a new patch matching method to overcome this problem. Using an image observation model, it preserves the correlation between the input and the output images. Therefore, it effectively suppresses spurious noise caused by inappropriately matched patches. This does not only improve the quality of the output image but also allows the system to use a huge dictionary containing a variety of font types and sizes, which significantly improves the adaptability to variation in font type and size. In experiments, the proposed method outperformed conventional methods in reconstruction of multi-font and multi-size images. Moreover, it improved recognition performance from 88.58% to 93.54%, which confirms the practical effect of the proposed method on recognition performance.

• The Journal of the Acoustical Society of Korea
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• v.26 no.6
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• pp.250-258
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• 2007

Current speech recognition technology s achieved high performance with the development of hardware devices, however it is insufficient for some applications where high reliability is required, such as voice control of powered wheelchairs for disabled persons. For the system which aims to operate powered wheelchairs safely by voice in real environment, we need to consider that non-voice commands such as user s coughing, breathing, and spark-like mechanical noise should be rejected and the wheelchair system need to recognize the speech commands affected by disability, which contains specific pronunciation speed and frequency. In this paper, we propose non-voice rejection method to perform voice/non-voice classification using both YIN based fundamental frequency(F0) extraction and reliability in preprocessing. We adopted a multi-template dictionary and acoustic modeling based speaker adaptation to cope with the pronunciation variation of inarticulately uttered speech. From the recognition tests conducted with the data collected in real environment, proposed YIN based fundamental extraction showed recall-precision rate of 95.1% better than that of 62% by cepstrum based method. Recognition test by a new system applied with multi-template dictionary and MAP adaptation also showed much higher accuracy of 99.5% than that of 78.6% by baseline system.

• Journal of Broadcast Engineering
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• v.13 no.2
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• pp.251-260
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• 2008

In this paper, we present two verifier-based multi-party PAKE (password-authenticated key exchange) protocols. The shared key can be used for secure content transmission. The suggested protocols are secure against server compromise attacks. Our first protocol is designed to provide forward secrecy and security against known-key attacks. The second protocol is designed to additionally provide key secrecy against the server which means that even the server can not know the session keys of the users of a group. The suggested protocols have a constant number of rounds are provably secure in the standard model. To the best of our knowledge, the proposed protocols are the first secure multi-party PAKE protocols against server compromise attacks in the literature.

• Journal of Korea Multimedia Society
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• v.8 no.6
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• pp.790-797
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• 2005

It is well-known that there are many similarities between Japanese and Korean language. For example, the order of words and the nature of the grammatical conjugation of both languages are almost the same. Another similarity is the frequent omission of the subject from a sentence. Moreover, both languages have honorific expressions and the identical concept for expressing nouns in terms of Chinese characters. Using these similarities, we have developed a word-to-word translation system which does away with any deep level analysis of syntactic and semantic structures of the two languages. If we use these similarities, the direct translation method is superior to the internal language translation method or transfer-based translation method. Although the MT system based on the direct translation method is more easily developed than the ones based on other methods, it may have a lot of difficulties when it tries to select the appropriate target word from ambiguous source verbs. In this paper, we propose a new algorithm to extract the meaning of substantives and to make use of the order of the extracted meaning. We could select $86.5\%$ appropriate verbs in the sample sentences from IPAL-verb-dictionary. $13.5\%$ indicates the cases in which we could not distinguish the meaning of substantives. We are convinced, however, that the succeeding rate can be increased by getting rid of the meaning of verbs thatare not used so often.

• Speech Sciences
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• v.7 no.2
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• pp.193-208
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• 2000

This paper describes a multi-step method of intonation modeling for corpus-based Korean speech synthesizer. We selected 1833 sentences considering various syntactic structures and built a corresponding speech corpus uttered by a female announcer. We detected the pitch using laryngograph signals and manually marked the prosodic boundaries on recorded speech, and carried out the tagging of part-of-speech and syntactic analysis on the text. The detected pitch was separated into 3 frequency bands of low, mid, high frequency components which correspond to the baseline, the word tone, and the syllable tone. We predicted them using the CART method and the Viterbi search algorithm with a word-tone-dictionary. In the collected spoken sentences, 1500 sentences were trained and 333 sentences were tested. In the layer of word tone modeling, we compared two methods. One is to predict the word tone corresponding to the mid-frequency components directly and the other is to predict it by multiplying the ratio of the word tone to the baseline by the baseline. The former method resulted in a mean error of 12.37 Hz and the latter in one of 12.41 Hz, similar to each other. In the layer of syllable tone modeling, it resulted in a mean error rate less than 8.3% comparing with the mean pitch, 193.56 Hz of the announcer, so its performance was relatively good.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2141-2155
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• 2020

In order to meet the requirements of background change, illumination variation, moving shadow interference and high accuracy in object detection of moving camera, and strive for real-time and high efficiency, this paper presents an object detection algorithm based on sparse approximation recursion and sparse coding migration in subspace. First, low-rank sparse decomposition is used to reduce the dimension of the data. Combining with dictionary sparse representation, the computational model is established by the recursive formula of sparse approximation with the video sequences taken as subspace sets. And the moving object is calculated by the background difference method, which effectively reduces the computational complexity and running time. According to the idea of sparse coding migration, the above operations are carried out in the down-sampling space to further reduce the requirements of computational complexity and memory storage, and this will be adapt to multi-scale target objects and overcome the impact of large anomaly areas. Finally, experiments are carried out on VDAO datasets containing 59 sets of videos. The experimental results show that the algorithm can detect moving object effectively in the moving camera with uniform speed, not only in terms of low computational complexity but also in terms of low storage requirements, so that our proposed algorithm is suitable for detection systems with high real-time requirements.