• 센서학회지
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• 제22권1호
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• pp.38-43
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• 2013

In this study, the artery's compliance model and the pulsation waveform model was proposed to estimate blood pressure without applying HPF (High Pass Filter) on signal measured by the oscillometric method. The method proposed in the study considered two ways of estimating blood pressure. The first method of estimating blood pressure is by comparing and analyzing changes in pulsation waveform's dicrotic notch region during each cardiac period. The second method is by comparing and analyzing morphological changes in the pulsation waveform during each cardiac period, which occur in response to the change in pressure applied on the cuff. To implement these methods, we proposed the compliance model and the pulsation waveform model of the artery based on hemodynamic theory, and then conducted various simulations. The artery model presented in this study only took artery's compliance into account. Then, a pulsation waveform model was suggested, which uses characteristic changes in the pulsation waveform to estimate blood pressure. In addition, characteristic changes were observed in arterial volume by applying artery's pulsation waveform to the compliance model. The pulsation waveform model was suggested to estimate blood pressure using characteristic changes of the pulsation waveform in the arteries. This model was composed of the sum of sine waves and a Fourier's series in combination form up to 10th harmonics components of the sinusoidal waveform. Then characteristic of arterial volume change was observed by inputting pulsation waveform into the compliance model. The characteristic changes were also observed in the pulsation waveform by mapping the arterial volume change in accordance with applied cuff's pressure change to the pulsation waveform's change according to applied pressure changes by cuff. The systolic and diastolic blood pressures were estimated by applying positional change of pulsation waveform's dicrotic notch region.

• Journal of Multimedia Information System
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• 제5권3호
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• pp.147-154
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• 2018

Natural language processing (NLP) is an emerging research area in which we study how machines can be used to perceive and alter the text written in natural languages. We can perform different tasks on natural languages by analyzing them through various annotational tasks like parsing, chunking, part-of-speech tagging and lexical analysis etc. These annotational tasks depend on morphological structure of a particular natural language. The focus of this work is part-of-speech tagging (POS tagging) on Hindi language. Part-of-speech tagging also known as grammatical tagging is a process of assigning different grammatical categories to each word of a given text. These grammatical categories can be noun, verb, time, date, number etc. Hindi is the most widely used and official language of India. It is also among the top five most spoken languages of the world. For English and other languages, a diverse range of POS taggers are available, but these POS taggers can not be applied on the Hindi language as Hindi is one of the most morphologically rich language. Furthermore there is a significant difference between the morphological structures of these languages. Thus in this work, a POS tagger system is presented for the Hindi language. For Hindi POS tagging a hybrid approach is presented in this paper which combines "Probability-based and Rule-based" approaches. For known word tagging a Unigram model of probability class is used, whereas for tagging unknown words various lexical and contextual features are used. Various finite state machine automata are constructed for demonstrating different rules and then regular expressions are used to implement these rules. A tagset is also prepared for this task, which contains 29 standard part-of-speech tags. The tagset also includes two unique tags, i.e., date tag and time tag. These date and time tags support all possible formats. Regular expressions are used to implement all pattern based tags like time, date, number and special symbols. The aim of the presented approach is to increase the correctness of an automatic Hindi POS tagging while bounding the requirement of a large human-made corpus. This hybrid approach uses a probability-based model to increase automatic tagging and a rule-based model to bound the requirement of an already trained corpus. This approach is based on very small labeled training set (around 9,000 words) and yields 96.54% of best precision and 95.08% of average precision. The approach also yields best accuracy of 91.39% and an average accuracy of 88.15%.

• 한국빅데이터학회지
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• 제4권2호
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• pp.23-34
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• 2019

최근 디지털 플랫폼을 활용한 민생 위협 범죄는 '15년 약 14만여 건, '16년 약 15만여 건 등 사이버범죄 지속 증가 추이이며 전통적인 수사기법을 통한 온라인 범죄 대응에 한계가 있다고 판단되고 있다. 현행 수기 온라인 검색 및 인지 수사 방식만으로는 빠르게 변화하는 민생 위협 범죄에 능동적으로 대처 할 수 없으며, 소셜 미디어 특성상 불특정 다수에게 게시되는 콘텐츠로 이루어 졌다는 점에서 더욱 어려움을 겪고 있다. 본 연구는 민생 침해 범죄가 발생하는 온라인 미디어의 특성을 고려한 콘텐츠 웹 수집 방식 중 사이트 중심의 수집과 Open API를 통한 방식을 제시한다. 또한 불법콘텐츠의 특성상 신속히 게시되고 삭제되며 신조어, 변조어 등이 다양하고 빠르게 생성되기 때문에 수작업 등록을 통한 사전 기반 형태소 분석으로는 빠른 인지가 어려운 상황이다. 이를 해소 하고자 온라인에서 벌어지는 민생 침해 범죄를 게시하는 불법 콘텐츠를 빠르게 인지하고 대응하기 위한 데이터 전처리인 WPM(Word Piece Model)을 통하여 기존의 사전 기반의 형태소 분석에서 토크나이징 방식을 제시한다. 데이터의 분석은 불법 콘텐츠의 수사를 위한 지도학습 기반의 분류 알고리즘 모델을 활용, 투표 기반(Voting) 앙상블 메소드를 통하여 최적의 정확도를 검증하고 있다. 본 연구에서는 민생경제를 침해하는 범죄를 사전에 인지하기 위하여 불법 다단계에 대한 사례를 중심으로 분류 알고리즘 모델을 활용하고, 소셜 데이터의 수집과 콘텐츠 수사에 대하여 효과적으로 대응하기 위한 실증 연구를 제시하고 있다.

• Molecules and Cells
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• 제24권3호
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• pp.441-444
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• 2007

Despite the importance of cell fate decisions regulated by epigenetic programming, no experimental model has been available to study transdifferentiation from myoblasts to smooth muscle cells. In the present study, we show that myoblast cells can be induced to transdifferentiate into smooth muscle cells by modulating their epigenetic programming. The DNA methylation inhibitor, zubularine, induced the morphological transformation of C2C12 myoblasts into smooth muscle cells accompanied by de novo synthesis of smooth muscle markers such as smooth muscle ${\alpha}$-actin and transgelin. Furthermore, an increase of p21 and decrease of cyclinD1 mRNA were observed following zebularine treatment, pointing to inhibition of cell cycle progression. This system may provide a useful model for studying the early stages of smooth muscle cell differentiation.

• 대한음성학회지:말소리
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• 제46호
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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.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 추계학술대회논문집B
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• pp.381-384
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• 2000

Relationships between biochemical phenomena and hemodynamics on human endothelial cells are very important to study the mechanism of atherosclerotic formation and development. The objective of this study is to investigate the flow phenomena around the endothelial cell model by the PIV experiment. The microscopic images of endothelial cells were acquired by a CCD camera to fabricate the shape of endothelial cell. The cell models were fabricated by using a photoforming process. Two consecutive particle images were captured by the CCD camera for the image processing. Conifer powder as the tracing particles was added to water to visualize the flow field. The cross-correlation method was applied fer the image processing of the flow visualization. Pressure and wall shear stress variations on the surfaces of the endothelial cells were calculated to investigate the effects of hemodynamic forces on the morphological changes.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 춘계학술대회
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• pp.2043-2047
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• 2003

The distributions of blood pressure, blood flow, and blow volume in the left common artery (LCCA) were determined using the lumping parameter method. In order to develop a mathematical model for microcirculation in LCCA, the present study adopted preexisted set of measured morphological data on anatomy, mechanical properties of the coronary vessels, viscosity of blood, the basic laws of physics, and the appropriate boundary condition. Pressures and volumes of blood and flow resistance were expressed in terms of electrical voltages, current, and resistances, respectively, in the electrical analog model. The results of two mathematical models, symmetrical and asymmetrical models, were compared with other investigator's data. The present results were in good agreement with previous studies. It was found that the mean pressure profiles were similar in both models.

• Journal of Mechanical Science and Technology
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• 제15권12호
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• pp.1762-1767
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• 2001

The Posuk-Chung Pavilion if a defunct irregular stone water channel in Kyongju, Korea, once used for the meandering stream feast'by kings of Silla Dynasty during the first millennium. The poets were seated around this stone water channel who composed the Chinese poems, overlooking the streams. They load to take the punishment drinks unless they finished the poem before the drifting cup filled with the rice wine arrived at their seats on the meandering stream. In this paper, we have made computer simulation as well as well as model experiment on the ancient meandering stream of the Posuk-Chung Pavilion. The computational results are compared with the experiment and the channel flow characteristics are delineated here. It is discussed how the present Posuk-Chung channel is morphologically distinguished from the Chinese and Japanese meandering streams.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 1994년도 제6회 한글 및 한국어정보처리 학술대회
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• pp.140-145
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• 1994

형태소 분석은 단위 형태소를 분리한 후에 변형이 일어난 형태소의 원형을 복원하고, 분리된 단위 형태소들로부터 단어 형성 규칙에 맞는 연속된 형태소들을 구하는 과정이다. 이러한 일련의 분석 과정은 독립적인 특성이 강하면서 각 모듈이 서로 밀접하게 연관되어 있으므로 Two-level 모델에서는 형태론적 변형뿐만 아니라 형태소 분리 문제를 통합 규칙으로 처리하고 있다. 그러나 한국어에 Two-level 모델을 적응해 보면 형태소 분리와 형태론적 변형이 복합되어 있어서 교착어의 특성과 관계되는 단어 유형을 분석할 때 비효율적인 요소가 발견된다. 따라서 본 논문에서는 교착어인 한국어의 형태소 분석시에 발생하는 문제점들을 해결하는데 적합한 방법론으로 다층 형태론(multi-level morphology)과 다단계 모델(multi-level model)을 제안한다.

• 천문학회보
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• 제35권2호
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• pp.39.2-39.2
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• 2010

We have investigated the evolution of the galaxy morphology in the hierarchical universe taking advantage of Semi-Analytic Model (SAM). It is well known that the galaxy morphology is related to the dynamical and the chemical evolution. This implies that we need to understand overall physical processes in the galaxy to reproduce its morphology. Thus we implemented gradual hot gas stripping of satellite galaxies in a galaxy cluster and recycling of stellar mass losses into our model in order to describe star formation rate of galaxies accurately. To morphologically classify galaxies, the evolution of disc and bulge components is traced carefully. We compute our models based on the dark matter halo merger trees generated by N-body simulations as well as the Extended Press-Schechter (EPS) formalism. We present morphological differences caused by the use of different merger trees.