• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.427-434
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• 2009

With the rapid evolution of the Internet and mobile environments, text including spelling errors such as newly-coined words and abbreviated words are widely used. These spelling errors make it difficult to develop NLP (natural language processing) applications because they decrease the readability of texts. To resolve this problem, we propose a spelling error correction model using a spelling error correction dictionary and a newspaper corpus. The proposed model has the advantage that the cost of data construction are not high because it uses a newspaper corpus, which we can easily obtain, as a training corpus. In addition, the proposed model has an advantage that additional external modules such as a morphological analyzer and a word-spacing error correction system are not required because it uses a simple string matching method based on a correction dictionary. In the experiments with a newspaper corpus and a short message corpus collected from real mobile phones, the proposed model has been shown good performances (a miss-correction rate of 7.3%, a F1-measure of 97.3%, and a false positive rate of 1.1%) in the various evaluation measures.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.34 no.4
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• pp.286-292
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• 2012

The lateral upper arm flap (LUAF) was initially described by in 1982 by Song et al. as a simple skin flap, addressing the availability of cutaneous nerves for anastomoses. Katsaros et al., reported the use of a lateral upper arm skin flap, but also considered using it as a composite graft. The LUAF for the oral and maxillofacial reconstruction has several advantages over other flaps, such as constant anatomy, good color match and texture, thin design and plasticity. There is no functional limitation in the donor arm, such as strength and extension, and donor defects can be closed primarily with a linear scar, even when a flap of up to 8 cm in width is taken. For a better understanding of LUAF as a routine reconstructive option in moderate defect of maxillofacial region, the constant anatomical findings must be learned and memorized by young doctors during the specialized training course for the Korean national board of oral and maxillofacial surgery. This article review the anatomical basis of LUAF with Korean language.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.164-170
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• 2012

A Virtual Reality Modeling Language (VRML) database access in remote virtual reality control platform for dyeing enterprise $MiWi^{TM}$ thermal sensor network is presented in this paper. The VRML-ASP framework is introduced for 3D real-time data plotting in this application. The activities of thermal sensor nodes and sensor area are analyzed. The database access framework is optimized for $MiWi^{TM}$ wireless sensor networks. The experimental results show that VRML-ASP database access framework could be a reliable and competitive data-manage candidate for targeted virtual reality remote industrial visualization application.

• Child Health Nursing Research
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• v.7 no.2
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• pp.161-178
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• 2001

The purpose of this study was to identify nursing interventions performed by neonatal nursing unit nurses. For data collection this study used the taxonomy of Nursing Intervention Classification(NIC : 486 nursing intervention) which was modified by McCloskey & Bulecheck(2000). The new 58 nursing interventions was translated into Korean, and then modified by pannel group, which consist of clinical experts and nursing scholars and finally the 419 nursing interventions was selected. The data were collected from 112 nurses. 168 nursing interventions were performed at least monthly by 50％ or more of the nurses. The high frequency of performed nursing interventions were Family domain. 37 nursing interventions were performed at least once a day. The nursing interventions receiving the highest item mean score were neonatal care, neonatal monitoring, photo-therapy; neonate, bottle feeding and temperature regulation. 56 nursing interventions were rarely performed by 90％ or more of the nurses. Most of them were in the behavioral domain. The rarely used interventions were urinary bladder training, art therapy, religious addiction prevention, religious ritual enhancement and bladder irrigation. Therefore, neonatal nursing units nurses used interventions in the Physiological: basic domain most often on a daily basis and the interventions in the behavioral domain least often. These findings will help in building of a standardized language for the neonatal nursing units and enhance the quality of nursing care. Further study will be needed to classify each intervention class and nursing activity and validate NIC in pediatric care unit.

• The Journal of the Korea Contents Association
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• v.11 no.1
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• pp.379-386
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• 2011

The article is to investigate selection of Korean cuisine restaurants and levels of acculturation for foreigner living in Korea and to suggest some guidelines for drawing them and enlargement in consuming market. Out of 250 questionnaires, 220 questionnaires were used for data analysis. The findings are showed visiting for taking experience other culture and learning technology & training, not knowing well much about Korean culture, and eating experience Korean food on 30.5%, less than 2 years length in Korea. And the most difficult points are showed unclear communication, rude behavior, attitude, and language in living Korea. Second, the purpose of visiting restaurant is to spend good time with friends and to eat out special food, then foreigners usually have lunch & dinner Korean food, their own food on weekend. Third, 'service' and 'sanitation & cleanness' factors were ranked highly for foreigners living less than 2 years, but 'location' factor was ranked highly for residents living more than 4 years in the Korea. Last, foreigners living less than 2 years recognized highly on 'identification and Korea culture' in the Korea.

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.2
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• pp.319-324
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• 2009

Qigong is one energy-healing intervention used to prevent and cure ailments and to improve health through regular practice. Although qigong -neither itself nor its postulated mechanism of action- are within the paradigm of modern Western medical science, effects on the human body could be possible. This study aims to review the bibliography, biological responses and therapeutic effects of Qigong. In the process, this review will grasp trends in this field of studies and will direct further researches into the right direction. The computerized Korean databases were searched from their respective inceptions up to January 2008. The search terms used were 'qi', 'qigong', 'doin', 'training', 'bioenergy', 'life nurturing' and random or Korean language terms related to qigong. Several specialized journals were also manually searched for relevant articles. Since the 1990s, Qigong papers in the Korean Literature is increased. Clinical research studies are among the most control design study. Research subjects are less patient than the general public. The most common treatment disease was hypertension. The depth study for the each Qigong is needed. Specifically, I think it should be a clinical studies and qualitative research methods for evaluation are needed.

• Computers and Concrete
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• v.19 no.3
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• pp.275-282
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• 2017

The aim of this study is to build Machine Learning models to evaluate the effect of blast furnace slag (BFS) and waste tire rubber powder (WTRP) on the compressive strength of cement mortars. In order to develop these models, 12 different mixes with 288 specimens of the 2, 7, 28, and 90 days compressive strength experimental results of cement mortars containing BFS, WTRP and BFS+WTRP were used in training and testing by Random Forest, Ada Boost, SVM and Bayes classifier machine learning models, which implement standard cement tests. The machine learning models were trained with 288 data that acquired from experimental results. The models had four input parameters that cover the amount of Portland cement, BFS, WTRP and sample ages. Furthermore, it had one output parameter which is compressive strength of cement mortars. Experimental observations from compressive strength tests were compared with predictions of machine learning methods. In order to do predictive experimentation, we exploit R programming language and corresponding packages. During experimentation on the dataset, Random Forest, Ada Boost and SVM models have produced notable good outputs with higher coefficients of determination of R2, RMS and MAPE. Among the machine learning algorithms, Ada Boost presented the best R2, RMS and MAPE values, which are 0.9831, 5.2425 and 0.1105, respectively. As a result, in the model, the testing results indicated that experimental data can be estimated to a notable close extent by the model.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.45-53
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• 2018

Recently, studies about bilingual word embedding have been gaining much attention. However, bilingual word embedding with Korean is not actively pursued due to the difficulty in obtaining a sizable, high quality corpus. Local embeddings that can be applied to specific domains are relatively rare. Additionally, multi-word vocabulary is problematic due to the lack of one-to-one word-level correspondence in translation pairs. In this paper, we crawl 868,163 paragraphs from a Korean-English law corpus and propose three mapping strategies for word embedding. These strategies address the aforementioned issues including multi-word translation and improve translation pair quality on paragraph-aligned data. We demonstrate a twofold increase in translation pair quality compared to the global bilingual word embedding baseline.

• Journal of KIISE:Software and Applications
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• v.35 no.5
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• pp.306-312
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• 2008

In a goal-oriented dialogue, speaker's intention can be approximated by a semantic structure that consists of a pair of a speech act and a concept sequence. Therefore, it is very important to correctly identify the semantic structure of an utterance for implementing an intelligent dialogue system. In this paper, we propose a model to efficiently analyze the semantic structures based on an active teaming method. To reduce the burdens of high-level linguistic analysis, the proposed model only uses morphological features and previous semantic structures as input features. To improve the precisions of semantic structure analysis, the proposed model adopts CRFs(Conditional Random Fields), which show high performances in natural language processing, as an underlying statistical model. In the experiments in a schedule arrangement domain, we found that the proposed model shows similar performances(92.4% in speech act analysis and 89.8% in concept sequence analysis) to the previous models although it uses about a third of training data.

• The Journal of the Acoustical Society of Korea
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• v.13 no.1
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• pp.24-31
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• 1994

In this paper, we report on the development of a speaker independent continuous speech recognition system using continuous hidden Markov models. The continuous hidden Markov model consists of mean and covariance matrices and directly models speech signal parameters, therefore does not have quantization error. Filter bank coefficients with their 1st and 2nd-order derivatives are used as feature vectors to represent the dynamic features of speech signal. We use the segmental K-means algorithm as a training algorithm and triphone as a recognition unit to alleviate performance degradation due to coarticulation problems critical in continuous speech recognition. Also, we use the one-pass search algorithm that Is advantageous in speeding-up the recognition time. Experimental results show that the system attains the recognition accuracy of $83\%$ without grammar and $94\%$ with finite state networks in speaker-indepdent speech recognition.