• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11a
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• pp.366.2-366
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• 2002

Unsteady flow characteristics and associated blade tonal noise of a cross-flow fan are predicted by a computational method. The incompressible Wavier-Stokes equations are time-accurately solved for obtaining the pressure fluctuations between the rotating blades and the stabilizer, and sound pressure is predicted using Curie's equation. The computed fan performance is favorably compared with experimental data, and also indicates that the performance is not significantly altered by the random pitch effect at ø〉0.4. (omitted)

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.5
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• pp.437-443
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• 2012

In this paper, the hybrid method to identify the exciting forces and radiated noise generated from the reciprocating compressor was presented. In order to identify the exciting force, both the acceleration data measured at the compressor shell and numerical finite element model for the full set of compressor were used simultaneously. Applying the identified exciting forces to the numerical model, the velocity responses of all nodes at the shell were predicted. Finally the radiated noises from the vibrating shell were predicted by using the direct boundary element acoustic analysis. For precise numerical modeling, the stiffness of rubber mounts and body springs were identified experimentally from the natural frequencies measured by impact testing. The error of over-all sound pressure level between predicted noise and measured noise was about 2.9 dB.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.5
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• pp.454-461
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• 2009

Internal aeroacoustics of an axial fan used for circulating cold air in refrigerators are computed by using the hybrid method where CFD, acoustic analogy and BEM techniques are utilized. The unsteady flow field around the axial fan is predicted by solving the incompressible RANS equations with the conventional CFD techniques. Then, main noise sources are extracted from this unsteady flow field predictions using Acoustic Analogy. Lastly, BPF noise generated from an axial fan are predicted using these modeled sources combined with the tailed Green function techniques, which are numerically solved by the BEM technique. This hybrid model is validated by comparing the prediction with the experiment. Then, parameter studies are carried out, which suggest a capability of the current method as a design tool for the low-noise of the current axial fan system in a refrigerator.

• The Korean Journal of Applied Statistics
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• v.25 no.4
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• pp.669-680
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• 2012

Noise removal of document images is a necessary step during preprocessing to recognize characters effectively because it has influences greatly on processing speed and performance for character recognition. We have considered using the spatial filters such as traditional mean filters and Gaussian filters, and wavelet transformed based methods for noise deduction in natural images. However, these methods are not effective for the noise removal of document images. In this paper, we present noise removal of document images using support vector regression. The proposed approach consists of two steps which are SVR training step and SVR test step. We construct an optimal prediction model using grid search with cross-validation in SVR training step, and then apply it to noisy images to remove noises in test step. We evaluate our SVR based method both quantitatively and qualitatively for noise removal in Korean, English and Chinese character documents, and compare it to some existing methods. Experimental results indicate that the proposed method is more effective and can get satisfactory removal results.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.682-693
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• 2019

The traditional classification methods mostly assume that the data for class distribution is balanced, while imbalanced data is widely found in the real world. So it is important to solve the problem of classification with imbalanced data. In Mahalanobis-Taguchi system (MTS) algorithm, data classification model is constructed with the reference space and measurement reference scale which is come from a single normal group, and thus it is suitable to handle the imbalanced data problem. In this paper, an improved method of MTS-CBPSO is constructed by introducing the chaotic mapping and binary particle swarm optimization algorithm instead of orthogonal array and signal-to-noise ratio (SNR) to select the valid variables, in which G-means, F-measure, dimensionality reduction are regarded as the classification optimization target. This proposed method is also applied to the financial distress prediction of Chinese listed companies. Compared with the traditional MTS and the common classification methods such as SVM, C4.5, k-NN, it is showed that the MTS-CBPSO method has better result of prediction accuracy and dimensionality reduction.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.630-635
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• 2012

Nearfield acoustic holography method predicts an unmeasured sound field, therefore it depends on its prediction methods. In particular, if one has radiators or scatters, which cannot be expressed by simple geometry, then inverse boundary element method (BEM) is normally employed to reconstruct the sound field induced by sound sources with irregular profiles. The characteristics of boundary element, including the element shape, characteristic length, order of shape function and others, affect the reconstruction error. Investigating the errors by means of changing these factors will provide a guide line for selecting appropriate factors, associated with the elements of BEM. These factors are investigated by numerical simulations, and the accuracies with respect to the variant factors are compared. Novel suggestions for selecting appropriate boundary element factors are described based on the simulation results.

• Proceedings of the IEEK Conference
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• 2003.11c
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• pp.251-254
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• 2003

In this paper, we develop an effective method for estimating and predicting interference power strength using the IMM(Interacting Multiple Model) algorithm. Based on the proposed interference prediction algorithm, we adjust transmission power of mobile terminals to maintain a certain level of target signal - to - interference- plus -noise- ratio ( SINR ) at the base station. Results of numerical experiments are presented to show a performance profile of the proposed algorithm.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.9
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• pp.823-830
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• 2013

The purpose of this study is to develop a noise reduction device installed at the top of noise barrier for further decreasing of noise level of 400 km/h class high-speed railroad. For this, the frequency spectrum of 400 km/h class high-speed railroad was analyzed through the field noise test, and the tuning frequency was determined to design a noise reduction device. The noise reduction device was designed to have noise reduction performance of at least 3 dB(A) using the prediction method(2D BEM) and through the laboratory test with the prototype. Finally, the outdoor test showed that this device could decrease noise level of 400 km/h class high-speed railroad even more than 3 dB(A).

• Journal of Broadcast Engineering
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• v.12 no.6
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• pp.565-573
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• 2007

In this paper, we propose a method to select motion vector predictor by considering prediction structure of a multi view content for coding efficiency of multi view coding which is being standardized in JVT. Motion vector of a different tendency is happened while carrying out temporal and view reference prediction of multi-view video coding. Also, due to the phenomena of motion vectors being searched in both temporal and view order, the motion vectors do not agree with each other resulting a decline in coding efficiency. This paper is about how the motion vector predictor are selected with information of prediction structure. By using the proposed method, a compression ratio of the proposed method in multi-view video coding is increased, and finally $0.03{\sim}0.1$ dB PSNR(Peak Signal-to-Noise Ratio) improvement was obtained compared with the case of JMVM 3.6 method.

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.5
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• pp.484-491
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• 2017

Recent research has shown that quadrupole noise has a significant influence on the overall characteristics of flow-induced noise and on the performance of underwater appendages such as sonar domes. However, advanced research generally uses the Ffowcs Williams-Hawkings analogy without considering the quadrupole source to reduce computational cost. In this study, flow-induced noise is predicted by using an LES turbulence model and a developed formulation, called the formulation Q1As method to properly take into account the quadrupole source. The noise around a circular cylinder in an underwater environment is examined for two cases with different velocities. The results from the method are compared to those obtained from the experiments and the permeable FW-H method. The results are in good agreement with the experimental data, with a difference of less than 1 dB, which indicates that the formulation Q1As method is suitable for use in predicting quadrupole noise around underwater appendages.