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126 results on '"Seo, Yong-Ho"'

15. Emergency Response System Using a Surveillance Camera with Collaborative Multiple Robots

Author

Seo, Yong-Ho, Yang, Hyun S., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Lee, Geuk, editor, Howard, Daniel, editor, and Ślęzak, Dominik, editor

Published
2011
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16. Affective Dialogue Communication System with Emotional Memories for Humanoid Robots

Author

Ryoo, M. S., Seo, Yong-ho, Jung, Hye-Won, Yang, H. S., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Tao, Jianhua, editor, Tan, Tieniu, editor, and Picard, Rosalind W., editor

Published
2005
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31. Gel-type autologous chondrocyte (Chondron™) implantation for treatment of articular cartilage defects of the knee

Author

Chun Chung-Woo, Cho Jea-Yeong, Seo Yong-Ho, Kim Yoon-Sik, Kim Jin-Soo, Suh Dong-Sam, Kim Haeng-Boo, Yeo Woo-Jin, Kim Byoung-Woo, Choi Nam-Yong, Park Hyun-Shin, Shetty Asode, and Kim Seok-Jung

Subjects
Diseases of the musculoskeletal system, RC925-935
Abstract

Abstract Background Gel-type autologous chondrocyte (Chondron™) implantations have been used for several years without using periosteum or membrane. This study involves evaluations of the clinical results of Chondron™ at many clinical centers at various time points during the postoperative patient follow-up. Methods Data from 98 patients with articular cartilage injury of the knee joint and who underwent Chondron™ implantation at ten Korean hospitals between January 2005 and November 2008, were included and were divided into two groups based on the patient follow-up period, i.e. 13~24-month follow-up and greater than 25-month follow-up. The telephone Knee Society Score obtained during telephone interviews with patients, was used as the evaluation tool. Results On the tKSS-A (telephone Knee Society Score-A), the score improved from 43.52 ± 20.20 to 89.71 ± 13.69 (P < 0.05), and on the tKSS-B (telephone Knee Society Score-B), the score improved from 50.66 ± 20.05 to 89.38 ± 15.76 (P < 0.05). The total improvement was from 94.18 ± 31.43 to 179.10 ± 24.69 (P < 0.05). Conclusion Gel-type autologous chondrocyte implantation for chondral knee defects appears to be a safe and effective method for both decreasing pain and improving knee function.

Published
2010
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32. Line Spectral Frequency-based Noise Suppression for Speech-Centric Interface of Smart Devices

Author

Gj Jang Gil-Jin Jang, Yh Seo Yong-Ho Seo, Js Park Jeong-Sik Park, and Jh Kim Ji-Hwan Kim

Subjects
noise reduction, Noise suppression, lcsh:Computer engineering. Computer hardware, General Computer Science, Noise measurement, Computer science, Noise reduction, Interface (computing), speech recognition, noise measurement, linear predictive coding, lcsh:TK7885-7895, Linear predictive coding, Line (electrical engineering), Speech enhancement, Noise, Electronic engineering, speech enhancement, lcsh:Electrical engineering. Electronics. Nuclear engineering, Electrical and Electronic Engineering, lcsh:TK1-9971
Abstract

This paper proposes a noise suppression technique for speech-centric interface of various smart devices. The proposed method estimates noise spectral magnitudes from line spectral frequencies (LSFs), using the observation that adjacent LSFs correspond to peak frequencies of spectrum, whereas isolated LSFs are close to flattened valley frequencies retaining noise components. Over a course of segmented time frames, the logarithms of spectral magnitudes at respective LSFs are computed, and their distribution is then modeled by the Rayleigh probability density function. The standard deviation from the Rayleigh function approximates the noise spectral magnitude. The model is updated at every frame in an online manner so that it can deal with real-time inputs. Once the noise spectral magnitude is estimated, a time-domain Wiener filter is derived for the suppression of the estimated noise spectral magnitude, and this is then applied to the input noisy speech signals. Our proposed approach operates well on most smart devices owing to its low computational complexity and real-time implementation. Speech recognition experiments, conducted to evaluate the proposed technique, show that our method exhibits superior performance, with less distortion of original speech, when compared to conventional noise suppression techniques.

Published
2011

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