• East Asian mathematical journal
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• 제25권2호
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• pp.215-220
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• 2009

In this paper, we investigate the generating strings and the number of 2-(edge)connected bipartite Steinhaus graphs.

• 정보과학회 논문지
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• 제43권11호
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• pp.1275-1280
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• 2016

유사 문자열 검색을 위해 기존의 기법들은 우선 후보 문자열 집합을 생성한 후에 후보 문자열을 검증하는 방법을 사용한다. 이때, 유사 문자열 검색의 성능을 결정짓는 가장 중요한 요소는 후보 생성 방법이다. 기존의 기법들은 질의 문자열로부터 고정길이 q-그램들을 선택하고, 선택된 q-그램에 해당하는 역리스트를 이용해 후보 문자열을 생성한다. 본 논문에서는 질의 문자열 내의 가변길이 그램들을 사용하여 후보 문자열을 생성할 수 있는 기법과 질의 문자열로부터 최적의 가변길이 그램들의 조합을 선택하는 동적 프로그래밍 알고리즘을 제안한다. 실험을 통해 제안하는 기법이 기존의 기법들 보다 유사 문자열 검색의 성능을 향상시킴을 보인다.

• 로봇학회논문지
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• 제5권4호
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• pp.318-325
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• 2010

This paper proposes a new string controller for puppet which is optimized in terms of the number of motors and its size. To optimize the number of motors needed for generating the essential motions of puppet, the motion of bending a leg is implemented by one string and the walking motion by two legs is implemented by one motor. To minimize the space needed for the controller when generating the essential motions of puppet, cylindrical and articulated joints are used in the controller. The proposed controller is actually implemented to perform various puppet shows and it has been proved that the size of the controller is small enough for two puppets to stand close to shake hands and it is fast enough to simulate fast dance motions.

• Kyungpook Mathematical Journal
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• 제43권4호
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• pp.567-577
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• 2003

In this paper, we classify the Steinhaus graphs with minimum degree two.

• Genomics & Informatics
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• 제10권4호
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• pp.266-270
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• 2012

Grammatical inference methods are expected to find grammatical structures hidden in biological sequences. One hopes that studies of grammar serve as an appropriate tool for theory formation. Thus, we have developed JSequitur for automatically generating the grammatical structure of biological sequences in an inference framework of string compression algorithms. Our original motivation was to find any grammatical traits of several cancer genes that can be detected by string compression algorithms. Through this research, we could not find any meaningful unique traits of the cancer genes yet, but we could observe some interesting traits in regards to the relationship among gene length, similarity of sequences, the patterns of the generated grammar, and compression rate.

• East Asian mathematical journal
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• 제26권3호
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• pp.423-427
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• 2010

In this paper, we give an upper bound for dominations of Steinhaus graphs, and the domination numbers of the bipartite Steinhaus graphs. Also, we give an upper bound for Nordhaus-Gaddum type result for the bipartite Steinhaus graphs.

• Kyungpook Mathematical Journal
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• 제48권2호
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• pp.331-335
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• 2008

In this paper, we investigate the number of ones in rows of Pascal's Rectangle. Using these results, we determine the existence of regular bipartite Steinhaus graphs. Also, we give an upper bound for the minimum degree of bipartite Steinhaus graphs.

• 한국정보처리학회논문지
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• 제3권7호
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• pp.1659-1668
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• 1996

스트링 문법은 그래프 언어와 부분집합인 스트링 언어를 생성하는 반면 그래프 문법은 그래프 언어를 생성한다. 그래프 문법 모델중 가장 성공적인 것중의 하나인 NLC문법은 노드 레이블을 이용하여 하나의 노드를 하나의 그래프로 치환 하므로서 그래프를 생성한다. 그래프를 포함하는 하아피그래프를 생성하는 하이퍼그래프 문법 모델로는 미리 정해놓은 접착점들의 순서를 이용하여 하나의 하이퍼에지를 하나의 하이퍼그래프로 치환하는 CFHG 문법, CFHG 문법의 확장형으로서 복제 및 삭제의 방벙 을 통해 하이페이지와 그것이 포함하고 있는 노드들, 즉 하나의 핸들을 하나의 하아 퍼그래프로 차환하는 HH 문법, 그리고 eNCE방식을 이용하여 하나의 핸들을 하나의 하아퍼그래프로 치환하는 HRNCE 문법 등이 소개되었다. 본 논문에서는 HRNCE 문법이 생성하는 그래프 언어와 위에서 언급된 기타의 그래프 문법들이 생성하는 그래프 언어 들을 비교하므로서 HRNCE 문법과 타 그래프 문법들의 언어 생성력을 비교 검토하고자 한다.

• 음성과학
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• 제15권4호
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• pp.67-81
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• 2008

The accuracy rate of P2G (Phoneme-to-Grapheme) is one of the important factors determining the quality of unlimited voice recognition (VR) systems. Few studies were, however, conducted to reduce ambiguities of a phoneme string which can be segmented into a variety of different linguistic units (i.e. morphemes, words, eo-jeols), thus be transformed into more than one grapheme string. This paper is a preliminary research for building a large knowledge base of those homonymic & heterographic units(HHUs), which will provide unlimited Korean VR systems with more accurate P2G information. This paper analyzes 2 main factors generating HHUs: (1) boundary determination of the prosodic unit; (2) its segmentation into linguistic units. In this paper, linguistic characteristics determining variable boundaries of a prosodic unit are investigated, and the ambiguity types of HHUs are classified in accordance with their morphological and syntactic structures as well as with the phonological rules governing them.

• 대한임베디드공학회논문지
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• 제14권5호
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• pp.277-286
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• 2019

In this paper, we propose an efficient hyperplane generation technique to classify human activity from combination of events and sequence information obtained from multiple-event sensors. By generating hyperplane efficiently, our machine learning algorithm classify with less memory and run time than the LSVM (Linear Support Vector Machine) for embedded system. Because the fact that light weight and high speed algorithm is one of the most critical issue in the IoT, the study can be applied to smart home to predict human activity and provide related services. Our approach is based on reducing numbers of hyperplanes and utilizing robust string comparing algorithm. The proposed method results in reduction of memory consumption compared to the conventional ML (Machine Learning) algorithms; 252 times to LSVM and 34,033 times to LSTM (Long Short-Term Memory), although accuracy is decreased slightly. Thus our method showed outstanding performance on accuracy per hyperplane; 240 times to LSVM and 30,520 times to LSTM. The binarized image is then divided into groups, where each groups are converted to binary number, in order to reduce the number of comparison done in runtime process. The binary numbers are then converted to string. The test data is evaluated by converting to string and measuring similarity between hyperplanes using Levenshtein algorithm, which is a robust dynamic string comparing algorithm. This technique reduces runtime and enables the proposed algorithm to become 27% faster than LSVM, and 90% faster than LSTM.