• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.656-657
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• 2012

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.5 no.2
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• pp.193-199
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• 1995

This study was designed to investigate the difference of time weighted average(TWA) of noise levels and noise doses by the different operating parameter settings such as exchange rate, threshold level and criterion level for noise dosimeter in the field measurements of noise at industrial working environments. The time weighted averages of noise level and noise doses for noise working environments were determined by noise dosimeter on 80 workers employed at 20 industrial establishments of 8 industries. The results obtained were as follows: 1. The mean time weighted average(TWA) of the noise working environments by the operating parameter settings showed 93.4 dB(A) in 3 dB of exchange rate, 80 dB of threshold level and 90dB of criterion level 92.0 dB(A) in 3 dB-exchange rate, 90 dB-threshold level and 90 dB-criterion level, in 90.8 dB(A) in 5 dB of exchange rate, 80 dB of threshold level and 90 dB of criterion level, and 86.7 dB(A) in 5 dB of exchange rate, 90 dB of threshold level and 90dB of criterion level. 2. ln group of noise level less than 90 dB(A), mean TWAs of 80 dB of threshold level were significantly higher than that of 90 dB of threshold level in 3 dB and 5 dB of exchange rate. 3. The case exceeded threshold limit value of noise was 49(61.3 %) in 3dB, 80dB and 90 dB setting, 44(55.0 %) in 3 dB, 90 dB, 90 dB setting, 33(41.3 %) in 5 dB, 80dB, 90 dB setting and 26(32.5%) in 5 dB, 90 dB, 90 dB setting. Above considerations in mind, it is suggested that exchange rate and threshold level be specified in related laws and regulations in the evaluation of working environments noise.

• Journal of Korea Multimedia Society
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• v.13 no.9
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• pp.1329-1336
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• 2010

Cellular Automata is a discrete dynamical system which natural phenomena may be specified completely in terms of local relation, can increase and decrease the difference of luminance locally according to transition rule by keeping the characteristic of target image. In this paper, we propose a noise reduction method by keeping the characteristic using transition rule of Cellular Automata, also we propose methods of effective transition rule, the selection of parameters, the selection of number of neighborhood pixels. For uniform distribution noise, Gaussian noise, impulse noise, we do an experiment on adaptive state using different mathematical operations and compare its results. It was confirmed that the proposed transition rule is based on fast convergence speed and has stabile results.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1220-1225
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• 2010

This paper proposes a novel active noise control (ANC) approach that uses an IIR filter and neural network techniques to effectively reduce interior noise. We construct a multiple-channel IIR filter module which is a linearly augmented framework with a generic IIR model to generate a primary control signal. A three-layer perceptron neural network is employed for establishing a secondary-path model to represent air channels among noise fields. Since the IIR module and neural network are connected in series, the output of an IIR filter is transferred forward to the neural model to generate a final ANC signal. A gradient descent optimization based learning algorithm is analytically derived for the optimal selection of the ANC parameter vectors. Moreover, re-estimation of partial parameter vectors in the ANC system is proposed for online learning. Lastly, we present the results of a numerical study to test our ANC methodology with realistic interior noise measurement obtained from Korean railway trains.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.12
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• pp.1920-1925
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• 2012

In this paper, we propose a novel method to improve the performance of the improved minima controlled recursive averaging (IMCRA) in non-stationary noisy environment. The conventional IMCRA algorithm efficiently estimate the noise power by averaging past spectral power values based on a smoothing parameter that is adjusted by the signal presence probability in frequency subbands. Since the minimum of smoothing parameter is defined as 0.85, it is difficult to obtain the robust estimates of the noise power in non-stationary noisy environments that is rapidly changed the spectral characteristics such as babble noise. For this reason, we proposed the modified IMCRA, which adaptively estimate and updata the noise power according to the noise type classified by the Gaussian mixture model (GMM). The performances of the proposed method are evaluated by perceptual evaluation of speech quality (PESQ) and composite measure under various environments and better results compared with the conventional method are obtained.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.04a
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• pp.615-620
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• 1997

The flow rate and the noise level of 18 cross flow fans were measured to analyze the effect of design variables on these and to finally find the optimal design value. These data were analyzed by the Taguchi method and the neural network. The optimal values obtained by the neural network showed good agreements with that by the Taguchi method. The effects of eight design variables on the fan performance and the noise were evaluated and discussed.

• Journal of Korea Multimedia Society
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• v.6 no.3
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• pp.419-428
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• 2003

Several methods have been studied to prune the parasitic branches that cause unfortunately from thinning a shape to get its skeleton. We found that the symmetric path finding method was most efficient because it followed the boundary pixels of the shape just once. In this paper, its extended method is proposed to apply to removing the noise branches that protrude out of the boundary of a segmented or extracted shape in a given image. The proposed method can remove a noise branch with one-pixel width and also remove the noise branch that includes a round shape called a noise blob. The method uses a 4-8-directional boundary-following technique to determine symmetric paths and finds noise branches with noise blobs by detecting quasi-symmetric paths. Its time complexity is a linear function of the number of boundary pixels. Interactively selectable parameters are used to define various types of noise branches flexibly, which are the branch - size parameter and the blob-size parameter. Experimental results for a practical shape and various artificial shapes showed that the proposed method was very useful for simplifying the shapes.

• 한국데이터정보과학회:학술대회논문집
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• 2004.04a
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• pp.131-139
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• 2004

Robust parameter design is to identify appropriate settings of control factors that make the system's performance robust to changes in the noise factors that represent the source of variation. In this paper, we introduce a factor analysis approach to simultaneously optimize multiple quality characteristics in the robust parameter design. An example is illustrated to compare it with already proposed method.

• Journal of Integrative Natural Science
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• v.12 no.3
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• pp.69-73
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• 2019

Taguchi has used the signal-to-noise ratio (SN) to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. Taguchi has dealt with having constraints on both the mean and variability of a characteristic (the dual response problem) by combining information on both mean and variability into an SN. Many Statisticians criticize the Taguchi techniques of analysis, particularly those based on the SN. In this paper we propose a substantially simpler optimization procedure for parameter design to solve the dual response problems without resorting to SN.

• Smart Structures and Systems
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• v.14 no.5
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• pp.831-845
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• 2014

This paper proposed a discrete wavelet transform based method for time-varying physical parameter identification of shear type structures. The time-varying physical parameters are dispersed and expanded at multi-scale as profile and detail signal using discrete wavelet basis. To reduce the number of unknown quantity, the wavelet coefficients that reflect the detail signal are ignored by setting as zero value. Consequently, the time-varying parameter can be approximately estimated only using the scale coefficients that reflect the profile signal, and the identification task is transformed to an equivalent time-invariant scale coefficient estimation. The time-invariant scale coefficients can be simply estimated using regular least-squares methods, and then the original time-varying physical parameters can be reconstructed by using the identified time-invariant scale coefficients. To reduce the influence of the ill-posed problem of equation resolving caused by noise, the Tikhonov regularization method instead of regular least-squares method is used in the paper to estimate the scale coefficients. A two-story shear type frame structure with time-varying stiffness and damping are simulated to validate the effectiveness and accuracy of the proposed method. It is demonstrated that the identified time-varying stiffness is with a good accuracy, while the identified damping is sensitive to noise.