• International Journal of Control, Automation, and Systems
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• 제3권4호
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• pp.571-579
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• 2005

In this paper, we proposed an algorithm for arrhythmia classification, which is associated with the reduction of feature dimensions by linear discriminant analysis (LDA) and a support vector machine (SVM) based classifier. Seventeen original input features were extracted from preprocessed signals by wavelet transform, and attempts were then made to reduce these to 4 features, the linear combination of original features, by LDA. The performance of the SVM classifier with reduced features by LDA showed higher than with that by principal component analysis (PCA) and even with original features. For a cross-validation procedure, this SVM classifier was compared with Multilayer Perceptrons (MLP) and Fuzzy Inference System (FIS) classifiers. When all classifiers used the same reduced features, the overall performance of the SVM classifier was comprehensively superior to all others. Especially, the accuracy of discrimination of normal sinus rhythm (NSR), arterial premature contraction (APC), supraventricular tachycardia (SVT), premature ventricular contraction (PVC), ventricular tachycardia (VT) and ventricular fibrillation (VF) were $99.307\%,\;99.274\%,\;99.854\%,\;98.344\%,\;99.441\%\;and\;99.883\%$, respectively. And, even with smaller learning data, the SVM classifier offered better performance than the MLP classifier.

• 대한의용생체공학회:의공학회지
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• 제31권5호
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• pp.365-374
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• 2010

This paper is about the personal identification algorithm using an ECG that has been studied by a few researchers recently. Previously published algorithm can be classified as two methods. One is the method that analyzes ECG features and the other is the morphological analysis of ECG. The main characteristic of proposed algorithm uses together two methods. The algorithm consists of training and testing procedures. In training procedure, the features of all recognition objects' ECG were extracted and the PCA was performed for morphological analysis of ECG. In testing procedure, 6 candidate ECG's were chosen by morphological analysis and then the analysis of features among candidate ECG's was performed for final recognition. We choose 18 ECG files from MIT-BIH Normal Sinus Rhythm Database for estimating algorithm performance. The algorithm extracts 100 heartbeats from each ECG file, and use 40 heartbeats for training and 60 heartbeats for testing. The proposed algorithm shows clearly superior performance in all ECG data, amounting to 90.96% heartbeat recognition rate and 100% ECG recognition rate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권8호
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• pp.4076-4092
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• 2019

Nowadays, most users access internet through mobile applications. The common way to authenticate users through websites forms is using passwords; while they are efficient procedures, they are subject to guessed or forgotten and many other problems. Additional multi modal authentication procedures are needed to improve the security. Behavioral authentication is a way to authenticate people based on their typing behavior. It is used as a second factor authentication technique beside the passwords that will strength the authentication effectively. Keystroke dynamic rhythm is one of these behavioral authentication methods. Keystroke dynamics relies on a combination of features that are extracted and processed from typing behavior of users on the touched screen and smart mobile users. This Research presents a novel analysis in the keystroke dynamic authentication field using two features categories: timing and no timing combined features. The proposed model achieved lower error rate of false acceptance rate with 0.1%, false rejection rate with 0.8%, and equal error rate with 0.45%. A comparison in the performance measures is also given for multiple datasets collected in purpose to this research.

• 전자공학회논문지SC
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• 제42권5호
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• pp.27-34
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• 2005

심실세동은 심장의 무질서한 전기적 활동으로 인해 심근 수축이 동시에 이뤄지지 않게 되어 급성심장사에 이르게 하는 부정맥이다. 본 연구에서는 이러한 심실세동 검출을 위해 적은 양의 학습 데이터만으로 좋은 분류 성능을 보이는 SVM(Support Vector Machine) 분류기 기반의 심실세동 검출 알고리즘을 제안하였다. 심전도 신호로부터 SVM 분류기에 입력할 입력 특징을 추출하기 위하여 웨이브렛 변환기반의 대역통과 필터링, R점 검출, 입력 특징 추출구간 설정의 전처리 과정을 수행하였으며 입력 특징으로는 리듬 기반의 정보 및 웨이브렛 변환 계수를 선택하였다. SVM 다원분류기는 정상리듬(NSR) 분류기, 심실 세동과 유사한 심실빈맥(VT) 분류기, 심실세동(VF) 분류기 그리고 그 외 부정맥 분류기로 구성하였다. SVM 분류기의 파라미터 C값과 ${\alpha}$값은 실험을 통하여 최고 성능을 나타내는 C=10, ${\alpha}=1$을 선택하였다. SVM 다원 분류기를 통한 정상리듬, 심실빈맥 심실세동의 검출 평균값은 98.39%, 96.92%, 99.88%의 우수한 검출 성능을 나타냈다. 본 연구에서 제안된 동일 입력특징을 사용하여 SVM 분류기의 심실세동 검출 결과와 다층퍼셉트론 신경망 및 퍼지추론 방법에 의한 결과를 비교하였으며 SVM 분류기가 비슷하거나 우수한 결과를 보였다. 또한 기존 다른 알고리즘에 비하여도 우수한 결과를 보임으로써 제안된 입력 특징을 통한 SVM 분류기 기반의 심실세동 검출이 유용함을 확인할 수 있었다.

• Journal of Chest Surgery
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• 제16권1호
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• pp.97-101
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• 1983

The steadily increasing number of operations performed on the heart has given rise to occasional complications involving the nervous system, and this has been interested to cardiac surgeons and neurologists. This survey has been carried out on all Gases submitted to open heart surgery at Seoul National University Hospital during 1982 to determine which operative features were associated with the occurrence of neurological damage. 514 subjects were studied and neurological damage was noted in twenty-five patients [4.9%]. Eight of these 25 patients died in the postoperative period, but neurological damage contributed to the fatal outcome in six cases. Remaining seventeen patients were discharged without problems except one Cortical blindness and one hemiplegic patients who were survived without other problems . A number of features were found to be related to the development of neurological damage, which were age, duration of perfusion, nature of operation, cardiac rhythm and presence of the thrombi or calcification and hypothermic arrest. But many unknown etiological factors are remained out of our sight. A significant increase in the incidence of neurological damage was shown in older age group [13.3% in over 40 year of age], and also the duration of the bypass was associated with subsequent neurological injury especially more than 120 minutes [11.6%]. The presence of atrial fibrillation with intracardiac thrombi or calcification was also a contributing factor to developing neurological complication [16.7%]. These factors were regarded to influence the postoperative neurological complications and more effective method for prevention of these neurologic complication should be studied.

• 말소리와 음성과학
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• 제3권3호
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• pp.77-88
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• 2011

Foreign accent in second language production depends heavily on the transfer of features from the first language. This study examines acoustic variations in segments and suprasegments by native and nonnative speakers of English, searching for patterns of the transfer and plausible indexes of foreign accent in English. The acoustic variations are analyzed with recorded read speech by 20 native English speakers and 50 Korean learners of English, in terms of vowel formants, vowel duration, and syllabic variation induced by stress. The results show that the acoustic measurements of vowel formants and vowel and syllable durations display difference between native speakers and nonnative speakers. The difference is robust in the production of lax vowels, diphthongs, and stressed syllables, namely the English-specific features. L1 transfer on L2 specification is found both at the segmental levels and at the suprasegmental levels. The transfer levels measured as groups and individuals further show a continuum of divergence from the native-like target. Overall, the eldest group, students who are in the graduate schools, shows more native-like patterns, suggesting weaker foreign accent in English, whereas the high school students tend to involve larger deviation from the native speakers' patterns. Individual results show interdependence between segmental transfer and prosodic transfer, and correlation with self-reported proficiency levels. Additionally, experience factors in English such as length of English study and length of residence in English speaking countries are further discussed as factors to explain the acoustic variation.

• 인터넷정보학회논문지
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• 제10권2호
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• pp.179-186
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• 2009

본 논문은 가중 퍼지소속함수 기반 신경망(Neural Network with Weighted Fuzzy Membership Functions, NEWFM)을 이용하여 Creighton University Ventricular Tachyarrhythmia DataBase(CUDB)의 심전도(ECG) 신호로부터 정상리듬(Normal Sinus Rhythm, NSR)과 심실빈맥/심실세동(Ventricular Tachycardia/Ventricular Fibrillation, VT/VF)을 분류하는 방안을 제시하고 있다. NEWFM에서 사용할 특징입력을 추출하기 위해서 첫 번째 단계에서는 웨이블릿 변환(wavelet transform, WT)을 이용하였다. 두 번째 단계에서는 첫 번째 단계에서 생성된 웨이블릿 계수들을 위상공간 재구성(Phase Space Reconstruction, PSR)과 첨단(Peak) 추출 기법의 입력 값으로 이용하여 2개의 특징입력을 추출하였다. NEWFM은 이들 2개의 특징입력을 이용하여 정상리듬과 심실빈맥/심실세동을 분류하였고 그 결과로 90.13%의 분류성능을 나타내었다.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2004년도 춘계 학술대회 발표논문집
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• pp.245-249
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• 2004

The aim of this paper is to show the possibilities of the proficiency -based and integrated teaching of High School English reading and listening based on sense group and utterance restructuring. The proficiency -based and integrated listening and reading activities in stages are as follows. Step1, students fill in the blanks with strong or weak sounding words according to their abilities. Step2, speak along (track) based on restructuring and post-lexical phenomena while listening to the sentence. Step3, read and understand directly the passage, which have been marked the differentiated places where a native speaker of English would beat all likely to pause. Students need to listen to spoken English, so they recognize words in written and spoken form. They must be familiar with suprasegmental features, stress and rhythm, and post-lexical phenomena during reading activities.

• 대한후두음성언어의학회지
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• 제22권2호
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• pp.111-114
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• 2011

All singers can often develop voice trouble secondary to vocal abuse and overuse, but it is well known that traditional Korean singer (pansori) develop voice disorders more frequently than western style sunger. While laryngological concern for voice disorders arising in professional singers has received some attention, empirically motivated investigations of the underlying acoustic features of the singing voice have been relatively limited. Since all singers have a good knowledge of the voice and voice training, they would hardly give consent for treatment to a doctor unless he understood their desire to maximize their voice quality. The components of this report are composed of breathing, basic ekement, and vocalization, essencial fact, for getting a perfect voice for pansori. The breathing is based on hypogastric breathing. The main functions of breathing are energy and power of utterence, tempo of rhythm and seperating paragraph and controlling feelings according to dramatic situation. Vocalization is based on general vocalization. Main uses of it are maintaining singer's tone and harmony of cosmetic dual force.

• 한국산학기술학회논문지
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• 제17권10호
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• pp.104-108
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• 2016

흑인음악은 미국 내에서 소박한 민요에서부터 '재즈','알앤비','소울','펑크' 음악을 포함하는 매우 포괄적인 개념이다. 5음 음계의 싱코페이션을 사용하는 독특한 아프리카적 특성과 가스펠의 영향을 받으면서 발전하게 된다. 흑인 음악 장르의 다양성은 인종차별에 대한 역사적 흐름과 지역적 특색과 더불어 백인들과의 음악적 퓨전에서 찾을 수 있다. 미국 흑인음악의 거장 '스티비원더'. 흑인음악의 아버지라는 타이틀과 함께 그에게는 신체적 특징이 있다. 그것은 장애를 극복하면서, 수많은 음반과 히트곡 그리고 수 없이 많은 상을 차지하며, 미국을 넘어 전 세계적인 인기를 구가하는 뮤지션이 됐다는 점이다. 실용 음악사에 놓칠 수 없는 '스티비원더' 의 삶과 음악 그리고, 정신을 계승, 발전시켜 나아가야 함은 이 시대와 앞으로의 우리들의 음악을 폭넓게 밝혀주는 주요한 요소 중의 하나일 것 이다. 스티비원더의 모험 정신과 천재성은 앞으로도 우리나라 대중음악 및 뮤지션에게 큰 영향을 주게 될 것이다. 본 논문에서는 흑인 음악의 거장 '스티비원더'의 작품을 분석하고 악기 구성과 리듬의 독특함이 우리나라의 대중음악 뮤지션에게 어떠한 영향을 주었는지 연구 한다.