• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.113-117
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• 1997

In this paper we detected the thrombosis formation by spectral analysis and neural network. Using microphone and amplifier, we measured the sound from the mechanical valve which is attached to the pneumatic ventricular assist device. The sound was sampled by A/D converter and the periodogram is the main algorithm or obtaining spectrum. We made the valvular thrombosis models using pellethane and silicon and they are thrombosis model on the disk, around the sewing ring and fibrous tissue growth across the orifice of valve. The spectrum of normal and 5 kinds of thrombotic valve were obtained and primary and secondary peak appeared in each spectrum waveform. So to distinguish the secondary peak of normal and thrombotic valve quantatively, 3 layer back propagation neural network.

• Korean Journal of Agricultural Science
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• v.39 no.1
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• pp.117-123
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• 2012

Pathogenic fungi and bacteria such as Pectobacterium atrosepticum, Clavibacter michiganensis subsp. sepedonicus, Verticillium albo-atrum, and Rhizoctonia solani were the major microorganism which causes diseases in seed potato during postharvest process. Current detection method for disease-infected seed potato relies on human inspection, which is subjective, inaccurate and labor-intensive method. In this study, a reflectance spectroscopy was used to classify sound and disease-infected seed potatoes with the spectral range from 400 to 1100 nm. Partial least square discriminant analysis (PLS-DA) with various preprocessing methods was used to investigate the feasibility of classification between sound and disease-infected seed potatoes. The classification accuracy was above 97 % for discriminating disease seed potatoes from sound ones. The results show that Vis/NIR reflectance method has good potential for non-destructive sorting for disease-infected seed potatoes.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.8 s.173
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• pp.143-150
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• 2005

To verify applicability of multi-dimensional spectral analysis (MDSA) fur noise source identification two different approaches which are frequency response and coherent function have been investigated. The coherence function approach appears able to separate the correlated system when the noise sources were coherent. In this study, we identify contribution of structure-borne-noise of vehicle HVAC system using MDSA method. Firstly, to identify the applicability of MDSA method, 4-inputs of vehicle HVAC system were the signals measured by accelerometers attached on the selected noise sources which were composed of blower, evaporator, heater and duct. While 1-output which was driver's position sound was the SPL signals measured by a remote microphone, when the blower motor was operating. We identify efficiency of systems modeled with four Inputs/single output through ordinary coherence function (OCF) and partial coherence function (PCF). As a result of experiment, the blower accounted for $62-88\%$ of the overall level of sound energy density. Also, according to the analysis of acoustic signal and vibration signals measurement, an investigation of the noise source identification in the vehicle HVAC is presented. With the sound intensity method, the major sources of the vehicle HVAC radiation are verified. Also the method of improving the noise reduction is proposed by attaching damping patch access to blower motor and noise reduction is verified.

• The Journal of the Acoustical Society of Korea
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• v.29 no.4
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• pp.243-250
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• 2010

This paper proposes a spectral modeling of Korean traditional instrument, Haegeum, using cepstral analysis to naturally describe Haegeum sounds varying with time. To get a precise result of cepstral analysis, we set the frame size to 3 periods of input signal and more cepstral coefficients are used to extract formants. The performance is enhanced by flexibly controlling the cutoff frequency of bandpass filter depending on the resonances in the synthesis process of sinusoidal components and the deleting peaks remained in the residual signal. To detect the change of pitch, we divide the input frames into silence, attack, and sustain region and determine which region the current frame is involved in. Then, the proposed method readjusts the frame size according to the fundamental frequency in the case of the current frame is in attack region and corrects the extraction errors of the fundamental frequency for the frames in sustain region. With these processes, the synthesized sounds are much more similar to the originals. The evaluation result through the listening test by a Haegeum player says that the synthesized sounds are almost similar to originals (96~100 % similar to the original sounds).

• Phonetics and Speech Sciences
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• v.16 no.1
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• pp.33-40
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• 2024

This study investigated acoustic features in spectral moment analysis, comparing accurate articulations with distortions of alveolar fricatives such as dentalization, palatalization, and lateralization. A retrospective analysis was conducted on speech samples from 61 children (mean age: 5.6±1.5 years, 19 females, 42 males) using the Assessment of Phonology & Articulation for Children (APAC) and Urimal-test of Articulation and Phonology I (U-TAP I). Spectral moment analysis was applied to 169 speech samples. The results revealed that the center of gravity of accurate articulations was higher than that of palatalization, while palatalization was lower than dentalization. The variance of dentalization was higher than that of both accurate articulations and palatalization. The skewness of dentalization was higher than that of accurate articulations, and the skewness of palatalization was higher than that of accurate articulations. The kurtosis of palatalization was higher than that of both accurate articulations and dentalization. No significant differences were observed for the position of fricatives (initial, medial) and tense type (plain, tense) across all variables of spectral moment analysis for each distortion type. This study confirmed distinct patterns in center of gravity, variance, skewness, and kurtosis depending on the type of alveolar fricative distortion. The objective values provided in this study will serve as foundational data for diagnosing alveolar fricative distortions in children with speech sound disorders.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.152-155
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• 2002

An industrial robot noise has various noise sources such as gears, motors, bearings, and controller fans. Among these, gears are the most dominant source for noise. The gear noise, caused by tooth profile, elastic deformation, machining error and wear, is directly correlated with the transmission error of mating gear. Due to the fact that has several axis and many gears, it is difficult to understand the characteristics of the vibration and noise of robots. In this study, some advanced analysis techniques based on digital signal processing such as power spectrum, time spectral map, RPM map, and etc., were applied for locating the dominant frequency components of the robot noises and identifying their sources. In addition, sound quality analysis was performed in order to evaluate the operator's annoyance. The noise and vibration measurements were carried out at several points during the operation of each axis considering the effect of load and posture of the robot. Eased on the results, proper countermeasures to reduce excessive noise level have been suggested considering the characteristics of sources.

• The korean journal of orthodontics
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• v.15 no.1
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• pp.55-66
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• 1985

The study was undertaken to ascertain the speech defect of patients with malocclusion, especially of openbite patients, by means of the spectral analysis method. The experimental group was composed of ten female openbite patients and their mean age was 13.8 yrs. The control group was also composed of ten female girls and their mean age was 13.7 yrs. As for the speech material, eight Korean monophthrongs and two Korean fricatives and two affricatives were used. Speeches were recorded and then analyzed by a Kay 7800 digital sonagraph. Formant frequency level or range was used as a phonemic parameter. The results were as follows: 1. Among Vowels /a:/ : $F_1,\;F_3\;and\;F_1/F_2$ showed abnormality. /o:/ and $/w:/:F_2,\;F_2-F_1\;and\;F_1/F_2$ showed abnormality. 2. Among Consonants /S/ and /h/ : The upper and lower borders of the frequency range showed abnormality. (equation omitted) : The lower border of the frequency range showed abnormality. $/C^{h}/$ : The upper and lower borders of the frequency range and concentration point showed abnormality.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.11
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• pp.1071-1077
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• 2010

The reduction of the vehicle interior noise has been the main interest of noise and vibration harshness(NVH) engineers. A passenger vehicle has various and complicated transmission paths of sound and vibration. In order to identify the mechanism of transfer path, estimation of excitation force and exact modeling of transfer path are required. This paper presents method for estimating the noise source contribution on the road noise of the vehicle in a multiple input system where the input sources may be coherent with each other. And vector synthesis technique is employed to identify the characteristics of road noise and its transmission to vehicle compartment through noise and vibration analysis. Vibration reduction efficiency of each transfer path is evaluated by comparing individual vector components obtained virtual simulation.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.78-83
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• 2019

Sounds based machine fault diagnosis recovers all the studies that aim to detect automatically abnormal sound on machines using the acoustic emission by these machines. Conventional methods that use mathematical models have been found inaccurate because of the complexity of the industry machinery systems and the obvious existence of nonlinear factors such as noises. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We propose here an automatic fault diagnosis method of hand drills using discrete wavelet transform(DWT) and pattern recognition techniques such as artificial neural networks(ANN). We first conduct a filtering analysis based on DWT. The power spectral density(PSD) is performed on the wavelet subband except for the highest and lowest low frequency subband. The PSD of the wavelet coefficients are extracted as our features for classifier based on ANN the pattern recognition part. The results show that the proposed method can be effectively used not only to detect defects but also to various automatic diagnosis system based on sound.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.18 no.1
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• pp.33-38
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• 2007

Background and Objectives: It has been suggested that tonsillectomy possibly causes changes of voice because the morphology of the vocal tract is altered. This may cause serious problems for professional voice users. Materials and Method: Subjects were 26 patients. The oral and nasal sound spectrum of oral vowel /a/, /e/ and /i/ were measured before and after tonsillectomy. The formant frequencies and intensities for oral and nasal spectra were compared. The nasality and fundamental frequencies for oral vowel were measured. Results: The first formant frequencies for oral spectra of all vowels were not changed after surgery, but the second formant frequencies were increased significantly after surgery in the vowel /e/ and /i/. The first and second formant intensities for oral spectra were increased significantly after surgery in the all vowels. The first and second formant frequencies for nasal spectra of all vowels were not changed after surgery, but their intensities for nasal spectra were increased after surgery. The nasalities for oral vowel were not changed after surgery. Conclusion : Tonsillectomy appeared to change the spectral features of oral and nasal components of oral vowel, especially spectral intensities.