• Journal of The Korea Institute of Healthcare Architecture
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• v.22 no.1
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• pp.17-28
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• 2016

Purpose: The purpose of this paper is to analyze the spatial configurations of a sample of Korean regional emergency medical centers (REMCs) to explore its underlying genotypes and thus produce a base line data for the analysis and evaluations of future REMCs designs using space syntax theory. Methods: Space syntax analysis was used as a major tool for the analysis and exploration of Genotype. The measures of Integration(overall integration with exterior and without exterior as well as the integration of individual clinical spaces for each center), base difference factor (DF) and Space link ratio were calculated for a sample of seven Korean REMCs. Results: The result shows a strikingly similar pattern of Syntactic measures across the sample, the mean integration of sample ranges from 0.82-0.99 with exterior (while considering the exterior space as a root) and 0.81-1.01 without exterior (considering the connections of interior spaces only with no outside connection). The base difference factor (DF) of the sample varies from 0.60-0.81 with exterior and from 0.59-0.82 without exterior. Case number-1 was identified as non-genotype with differing order of Syntactic values. Although the genotype had different forms, layouts and even sizes, these results cannot be explained by Phenotypical comparisons. Implications: This study will contribute to the configurational analysis and evaluation of existing and future Korean REMCs design and practice of emergency healthcare delivery system in Korea.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.337-340
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• 1999

The most salient and discussed features of speech production in agrammatic aphasia are the omission and substitution of grammatical morphemes. Cross-linguistic studies have shown that the pattern of omission/substitution is not random but occurs in a systematic and highly constrained way. Although these descriptions are important, they do not explain why all grammatical morphemes are not equally impaired. Friedmann and Grodzinsky (1997) proposed the Tree-Pruning Hypothesis (TPH) to account for these patterns of sparing and loss. The TPH claims that in an agrammatic representation, an impaired functional node is underspecified, thus allowing inappropriate affixation to occur. Additionally, whenever a node is impaired, all nodes above it will also be impaired. Using four types of narratives collected from two Korean agrammatic patients, We test the claim that the impairment in agrammatism is based on such hierarchical representation. It was found that these patients consistently produced appropriate grammatical morphemes that are higher in a syntactic tree than the impaired morphemes. The finding that an intact node exists higher than an impaired node refutes the TPH.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.7-10
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• 2000

Studies of prosody and sentence processing have demonstrated that prosodic phrasing can exhibit strong effects on processing decisions in English. In this paper, we tested Korean sentence fragments containing syntactically ambiguous Adj-N1-N2 strings in a cross-modal naming task. Four accentual phrasing patterns were tested: (a) the default phrasing pattern, in which each word forms an accentual phrase; (b) a phrasing biased toward N1 modification; (c) a phrasing biased toward complex-NP modification; and (d) a phrasing used with adjective focus. Patterns (b) and (c) are disambiguating phrasings; the other two are commonly found with both interpretations and are thus ambiguous. The results showed that the naming time of items produced in the prosody contradicting the semantic grouping is significantly longer than that produced in either default or supporting prosody, We claim that, as in English, prosodic information in Korean is parsed into a well-formed prosodic representation during the early stages of processing. The partially constructed prosodic representation produces incremental effects on syntactic and semantic processing decisions and is retained in memory to influence reanalysis decisions.

• MALSORI
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• no.46
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• pp.51-64
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• 2003

In order to produce high quality synthesized speech, it is very important to get an accurate grapheme-to-phoneme conversion and prosody model from texts using natural language processing. Robust preprocessing for non-Korean characters should also be required. In this paper, we analyzed Korean texts using a morphological analyzer, part-of-speech tagger and syntactic chunker. We present a new grapheme-to-phoneme conversion method for Korean using a hybrid method with a phonetic pattern dictionary and CCV (consonant vowel) LTS (letter to sound) rules, for unlimited vocabulary Korean TTS. We constructed a prosody model using a probabilistic method and decision tree-based method. The probabilistic method atone usually suffers from performance degradation due to inherent data sparseness problems. So we adopted tree-based error correction to overcome these training data limitations.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.4
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• pp.433-441
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• 1992

This paper describes an algorithm that can efficiently analyze the ECG signal using frame knowledge representation technique. Input to the analysis process is a set of significant points which have been extracted from an original sampled signal(lead II) by the syntactic peak recognition algorithm. The hierarchical property of ECG signal is represented by hierarchical AND/OR graph. The semantic information and constraints of the ECG signal are desctibed by frame. As the control mechanism for labeling points, the search mechanism with the mixed paradigms of data-driven and model driven hypothesis formation, scoring function, hypothesis modification network and instance inheritance are used. We used the CSE database in order to evaluate the performance of the proposed algorithm.

• Annual Conference on Human and Language Technology
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• 2001.10d
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• pp.25-32
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• 2001

한국어 자연언어처리에서 부딪치는 첫 번째 어려움은 형태소 분석 대상으로서의 어절(통사적 단어)이 형태론적으로 다양한 유형을 갖는다는 데 있다. 따라서 정확하고 효율적인 형태소 분석기를 설계하고 구현하는 데 있어서 우선적으로 요구되는 것은 다양한 유형의 어절을 형태론적으로 분석하여 체계화하는 것이다. 이러한 문제 인식에 따라 본 연구에서는 형태소 결합 관계를 중심으로 체언 어절과 용언 어절의 구성 양상에 대해 살펴보았다.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.175-177
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• 2000

본 논문에서는 다수의 페이지로 구성된 복잡한 구조의 문서로부터 SGML/XML에 기반한 전자 문서를 생성하기 위한 구문론적인 구조분석 방법을 제안한다. 제안된 방법은 구조분석의 정확성과 처리속도의 향상을 위하여 텍스트 영역의 계층적인 트리를 파싱하여 논리적인 계층 구조를 추출한다. 또한 본 논문은 문서 유형의 논리적인 구조 정보와 기하적인 특성을 효과적으로 기술할 수 있는 문서 모델을 정의한다. 제안된 방법의 성능을 평가하기 위하여 IEEE Transactions on Pattern Analysis and Machine Intelligence로부터 스캐닝한 372개의 논문 영상으로 실험한 결과, 제안된 방법은 기존 연구와 달리 다수의 문서 영상으로 구성된 문서에 대하여 논리적인 구조분석을 효율적으로 지원하였다. 특히 제안된 방법은 논리적인 구조분석의 최종 결과로서 SGML/XML 문서를 생성하기 때문에 문서의 재사용성과 호환성을 높인다.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.282-284
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• 2012

음성 인식 기술의 발전과 더불어 다양한 분야에서 음성 인식 시스템이 활용되고 있다. 본 논문에서는 사용자 음성으로부터 입력된 문장의 의도를 파악하여 모바일 기기를 제어할 수 있는 시스템에 대해서 기술한다. 사용자의 의도를 파악하기 위해, 동일한 의미를 가진 문장 형태들을 LSP(Lexico Semantic/Syntactic Pattern)로 구성하였고, 이를 이용하여 입력된 문장의 의도를 파악할 수 있는 문장-의미 분석 시스템을 구현하였다. 사용자의 음성 인식은 구글 안드로이드 음성 인식 모듈을 이용하였으며, 음성 인식 모듈과 문장-의미 분석 시스템을 통해 얻어진 화자의 의도는 모바일 기기의 동작과 연결된다. 본 논문은 자연적인 음성 명령을 통해 자연스러운 모바일 제어가 가능하다는 것을 보여준다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.667-669
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• 2002

중국어 V＋NP$_1$＋的＋NP$_2$형 패턴은 동사구와 명사구로 분석이 가능하여 중국어 구문분석의 결과에 중요한 영향을 미친다. 본 논문은 중국어 V＋NP$_1$＋的＋NP$_2$형 패턴의 구조적 중의성 문제를 해결하기 위한 방법을 제안한다. 제안하는 방법은 통계정보로 보완된 동사의 결합가 정보, 두 명사간의 결합도 정보 및 휴리스틱으로 구조적 애매성을 해소하고자 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.11
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• pp.2866-2879
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• 2012

Among the various security threats in online games, the use of game bots is the most serious problem. Previous studies on game bot detection have proposed many methods to find out discriminable behaviors of bots from humans based on the fact that a bot's playing pattern is different from that of a human. In this paper, we look at the chatting data that reflects gamers' communication patterns and propose a communication pattern analysis framework for online game bot detection. In massive multi-user online role playing games (MMORPGs), game bots use chatting message in a different way from normal users. We derive four features; a network feature, a descriptive feature, a diversity feature and a text feature. To measure the diversity of communication patterns, we propose lightly summarized indices, which are computationally inexpensive and intuitive. For text features, we derive lexical, syntactic and semantic features from chatting contents using text mining techniques. To build the learning model for game bot detection, we test and compare three classification models: the random forest, logistic regression and lazy learning. We apply the proposed framework to AION operated by NCsoft, a leading online game company in Korea. As a result of our experiments, we found that the random forest outperforms the logistic regression and lazy learning. The model that employs the entire feature sets gives the highest performance with a precision value of 0.893 and a recall value of 0.965.