• The Korean Journal of Mycology
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• v.31 no.2
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• pp.67-76
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• 2003

This study was performed to screen antimicrobial activities of 198 extracts from 66 Korean mushrooms against 19 human pathogenic microorganisms using paper disc method. Mushrooms were extracted with petroleum ether 80% ethanol and distilled water in that order Among the extracts with antimicrobial activities, 1 water extract of Amanita virgineoides, 8 ethanolic extracts including Amanita and 1 petroleum ether extrac of Psathyrella hydrophila were highly active against fungi, respectively. In addition to, 24 extracts including Amanita pseudoporphyria, Amanita spissacea, 3 extaracts including Paxillus curtisii were highly active against Gram negative and positive bacteria, respectively.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.3
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• pp.21-27
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• 2002

The digital watermarking methods have been proposed as a solution for solving the illegal copying and proof of ownership problems in the context of multimedia data. But it is still difficult to have been overcame the problem of the protection of property to multimedia data, such as digital images, digital video, and digital audio. This paper describes a watermarking algorithm that embeds non-linearly audio logo watermark data which is converted from audio signal of the ownership in the components of pixel intensities in an original image and that insists of ownership by hearing the audio signal transformed from the extracted audio logo through the speaker. Experimental results show that our algorithm using audio logo proposed in this paper is robust against attacks such as particularly lossy JPEG image compression. 

• Journal of Digital Convergence
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• v.12 no.6
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• pp.271-276
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• 2014

In a speech coding system using excitation source of voiced and unvoiced, it would be involved a distortion of speech quality in case coexist with a voiced and unvoiced consonants in a frame. In this paper, I propose a method of 8kbps Multi-Pulse Speech Coding(FBD-MPC: Frequency Band Division MPC) by using TSIUVC(Transition Segment Including Unvoiced Consonant) searching, extraction and approximation-synthesis method in a frequency domain. I evaluate the 8kbps MPC and FBD-MPC. As a result, SNRseg of FBD-MPC was improved 0.5dB for female voice and 0.2dB for male voice respectively. Compared to the MPC, SNRseg of FBD-MPC has been improved that I was able to control the distortion of the speech waveform finally. And so, I expect to be able to this method for cellular phone and smart phone using excitation source of low bit rate.

• Science of Emotion and Sensibility
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• v.16 no.1
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• pp.117-124
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• 2013

This study examined that how precisely MFCC, LPC, energy, and pitch related parameters of the speech data, which have been used mainly for voice recognition system could predict the vocal emotion categories as well as dimensions of vocal emotion. 110 college students participated in this experiment. For more realistic emotional response, we used well defined emotion-inducing stimuli. This study analyzed the relationship between the parameters of MFCC, LPC, energy, and pitch of the speech data and four emotional dimensions (valence, arousal, intensity, and potency). Because dimensional approach is more useful for realistic emotion classification. It results in the best vocal cue parameters for predicting each of dimensions by stepwise multiple regression analysis. Emotion categorizing accuracy analyzed by LDA is 62.7%, and four dimension regression models are statistically significant, p<.001. Consequently, this result showed the possibility that the parameters could also be applied to spontaneous vocal emotion recognition.

• Phonetics and Speech Sciences
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• v.11 no.3
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• pp.39-47
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• 2019

We propose a method to improve the performance of spontaneous speech recognizers by extending their phone set using speech data. In the proposed method, we first extract variable-length phoneme-level segments from broadcast speech signals, and convert them to fixed-length latent vectors using an long short-term memory (LSTM) classifier. We then cluster acoustically similar latent vectors and build a new phone set by choosing the number of clusters with the lowest Davies-Bouldin index. We also update the lexicon of the speech recognizer by choosing the pronunciation sequence of each word with the highest conditional probability. In order to analyze the acoustic characteristics of the new phone set, we visualize its spectral patterns and segment duration. Through speech recognition experiments using a larger training data set than our own previous work, we confirm that the new phone set yields better performance than the conventional phoneme-based and grapheme-based units in both spontaneous speech recognition and read speech recognition.

• The Journal of the Acoustical Society of Korea
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• v.26 no.5
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• pp.207-213
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• 2007

In this research, we propose an efficient Speech/Music discrimination method that uses spectrum analysis and neural network. The proposed method extracts the duration feature parameter(MSDF) from a spectral peak track by analyzing the spectrum, and it was used as a feature for Speech/Music discriminator combined with the MFSC. The neural network was used as a Speech/Music discriminator, and we have reformed various experiments to evaluate the proposed method according to the training pattern selection, size and neural network architecture. From the results of Speech/Music discrimination, we found performance improvement and stability according to the training pattern selection and model composition in comparison to previous method. The MSDF and MFSC are used as a feature parameter which is over 50 seconds of training pattern, a discrimination rate of 94.97% for speech and 92.38% for music. Finally, we have achieved performance improvement 1.25% for speech and 1.69% for music compares to the use of MFSC.

• Journal of the Korean Society of Food Science and Nutrition
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• v.33 no.3
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• pp.463-468
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• 2004

This study was conducted to determine the antimicrobial effect of leaf, bark and xylem of 6 kinds of Quercus spp. against food borne disease bacteria. All of the samples tested showed the antimicrobial effect against food borne disease bacteria. Bacillus cereus, Listeria monocytogenes, and Staphylococcus aureus was more sensitive than gram negative bacteria such as Salmonella typhimurium and Escerichia coli O157:H7, but no antimicrobial activity was observed against yeast and molds. Based on antimicrobial activity for kinds of Quercus spp., the antimicrobial activities of Quercus aliena Blume, Quercus mongolica Fisch, and Quercus dentata Thunb were stronger than those of Quercus variebilis Blume, Quercus serrata Thunb, and Quercus acutissima Carruth. In the meantime, the ethanol extract of Quercus spp. leaves showed the strongest antimicrobial activity compared to that of bark and xylem. Especially, the ethanol extract of Quercus aliena Blume leaf showed the strongest antimicrobial effect against foodborne disease bacteria among 6 kinds of Quercus spp.

• The Korean Journal of Mycology
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• v.24 no.1 s.76
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• pp.25-37
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• 1996

Antifungal and antibacterial activities of 108 extracts from 36 species of mushrooms in Korea were screened. The powder of fruiting body of each mushroom was extracted with petroleum ether, 80% ethanol and distilled water subsequently. Among these, five extracts including the ethanol extract of Agaricus subrutilescens, seven extracts including the water extract of Amanita virosa, nine extracts including the water extract of Amanita pantherina and twenty five extracts including the water extract of Lycoperdon perlatum showed antibiotic activities against yeasts, fungi, Gram-negative bacteria and Gram-positive bacteria, respectively.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.422-424
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• 1999

본 논문에서는 질감 특징과 신경회로망을 이용한 유방암조직영상의 분할 방법을 제안한다. 신경회로망의 입력 노드에 사용될 질감 특징을 얻기 위해 10개의 영상에 대해 각 영역(양성세포핵, 음성세포핵, 배경)에서 10개씩의 화소를 선택하고, 그 화소를 중심으로 하는 5$\times$5 영역 30개를 획득, 총 300개의 영역에 대해 R, G, B 각각의 밴드에서 18개의 질감특징을 추출한다. 54개의 입력노드, 28개의 은닉노드, 3개의 출력노드의 구조를 가진 신경회로망을 구성하고, 역전파 학습 알고리즘을 사용하여 신경회로망을 최대오차율이 10-3보다 작을 때까지 학습시킨다. 학습에 의해 획득되어진 분류기를 이용하여 유방암 조직 세포영상을 양성세포핵, 음성세포핵, 배경부분으로 자동 분할한다.

• Proceedings of the Acoustical Society of Korea Conference
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• 1985.10a
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• pp.75-78
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• 1985

본 연구는 시간 영역의 parament를 이용하여 한국어 숫자음(영, 일, 이, 삼, 사, 오, 육, 칠, 팔, 구)을 인식했다. 입력 음성 신호 X(n)의 Beginning Point와 Ending point를 ZCR(Zero-crossing Rate), Magnitude, Energy, Autocorrelation을 이용 Beginning point와 Ending point를 구하고 자음부의 인식은 위 계수들을 이용하여 행했다. 또, 유성음 부분에서는 PARCOR(Partial Autocorrelation), LPC(Linear Predictive Coding)를 이용 모음부와 유성자음을 인식하여 모음을 6개 부류(ㅏ, ㅑ, ㅗ, ㅜ, ㅠ, ㅣ)로 구분 인식했다. 이 방법에 의하면 입력 음성 신호 X(n)의 B.P(Beginning Point)와 E.P(Ending Point)를 쉽게 추출 가능하며 또한 각 Parameter를 이용하여 94.4%의 인식율을 얻었다.