• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1133-1138
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• 2000

This paper describes a signal recognition method for diagnosing the rotating machinery using wavelet-aided Self-Organizing Feature Map(SOFM). The SOFM specialized from neural network is a new and effective algorithm for interpreting large and complex data sets. It converts high-dimensional data items into simple order relationships with low dimension. Additionally the Learning Vector Quantization(LVQ) is used for reducing the error from SOFM. Multi-resolution and wavelet transform are used to extract salient features from the primary vibration signals. Since it decomposes the raw timebase signal into two respective parts in the time space and frequency domain, it does not lose either information unlike Fourier transform. This paper is focused on the development of advanced signal classifier in order to automatize vibration signal pattern recognition. This method is verified by the experiment and several abnormal vibrations such as unbalance and rubbing are classified with high flexibility and reliability by the proposed methods.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.943-947
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• 2008

Dynamic response characteristics of a beam undergoing impulsive force are investigated using the wavelet transform method in this study. When an impulse is applied to an arbitrary position of a beam, it will generate a structural deformation wave. The characteristics of the wave are changing in the domain of time and space. The maximum amplitude of each natural frequency mode and the time to reach the maximum amplitude are obtained in this study. The effects of the location of impulse on the variations of the dynamic characteristics is also investigated.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.78-83
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• 2003

General algorithm is developed for the prediction of internal flow-induced noise. This algorithm is based on the integral formula derived by using the General Green Function, Lighthills acoustic analogy and Curls extension of Lighthills. Novel approach of this algorithm is that the integral formula is so arranged as to predict frequency-domain acoustic signal at any location in a duct by using unsteady flow data in space and time, which can be provided by the Computational Fluid Dynamics Techniques. This semi-analytic model is applied to the prediction of internal aerodynamic noise from a throttle valve in an automotive engine. The predicted noise levels from the throttle valve are compared with actual measurements. This illustrative computation shows that the current method permits generalized predictions of flow noise generated by bluff bodies and turbulence in flow ducts.

• Fibers and Polymers
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• v.6 no.2
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• pp.156-161
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• 2005

The gray line-profile method is introduced to find fabric density. Some patterned fabrics like stripe design as well as solid fabrics of basic weave structures are used to verify the efficiency and accuracy of the method. The approach is compared with Fourier transform method. Although the gray line-profile method is concise, it shows good results in both solid and patterned fabrics. In addition, it does not require a pre-processing or filtering technique in space or frequency domain to enhance the image suitable for the analysis. However, the approach is slightly influenced by the filter size for finding the local minimums of profile graph.

• Korean Journal of Optics and Photonics
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• v.2 no.1
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• pp.36-49
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• 1991

The coherence properties of electromagnetic fields are reviewed, based on both the classical and quantum theories. The elementary concepts, employed frequently in the discussion of interference phenomena, are summarized. The well-known interference phenomena are described in terms of second-order coherences. The coherence theory in space-frequency domain is introduced and the coherent mode representation is presented. The generation and propagation of coherence of light are analysed and it is shown that the coherence of light is developed as light propagates. The quantum theory goes parallel with the classical theory, via the optical equivalence theorem. There are, however, certain nonclassical characteristics of light, which may not be easily understood in classical therms. These nonclassical phenomena are believed to originate from the particle aspects of light. The quantum effect on the interfernce phenomena is analysed and finally the outlook of the future research is briefly mentioned.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.281-286
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• 2003

Wavelet Transform can effectively represent the local characteristics of a signal in the space-frequency domain. However, the feature vector extracted using wavelet transform is not translation invariant. This paper describes a new feature extraction method using wavelet transform, which is translation-invariant. Based on this translation-invariant feature extraction, the iris recognition method, based on this feature extraction method, is robust to noises. Experimentally, we show that the proposed method produces super performance in iris recognition.

• Computational Structural Engineering
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• v.7 no.4
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• pp.127-136
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• 1994

For two-and three-dimensional problems, the vibration isolation effect of barriers in the travel path of waves has been studied using a boundary element method in the frequency domain. The soil is modelled as a half-space or a layered medium. The results indicate that the effectiveness of a wave barrier is strongly dependent on its location and depth with respect to the vibration source and that the optimum values of these two parameters are sensitive to vibration frequencies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.4
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• pp.912-917
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• 2004

The increase of illegal usage and conflict in digital content market would diminish motivation of creators for their work, furthermore break down digital content market on cyber-space. Watermarking technology support to the legal users by the protection technique based on the digital content copyright protection method(DRM). Most of previous digital watermarking have embeded to the content. In this paper, we propose a wavelet based watermarking method which is used for implementing in the frequency domain.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.3
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• pp.481-492
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• 1997

This paper presents an algorithm for recognizing surface mount device(SMD) IC pattern based on the error back propoagation(EBP) neural network and discrete cosine transform(DCT). In this approach, we chose such parameters as frequency, angle, translation and amplitude for the shape informantion of SMD IC, which are calculated from the coefficient matrix of DCT. These feature parameters are normalized and then used for the input vector of neural network which is capable of adapting the surroundings such as variation of illumination, arrangement of objects and translation. Learning of EBP neural network is carried out until maximum error of the output layer is less then 0.020 and consequently, after the learning of forty thousand times, the maximum error have got to this value. Experimental results show that the rate of recognition is 100% in case of the random pattern taken at a similar circumstance as well as normalized training pattern. It also show that proposed method is not only relatively relatively simple compare with the traditional space domain method in extracting the feature parameter but also able to re recognize the pattern's class, position, and existence.

• 한국벤처창업학회:학술대회논문집
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• 2022.04a
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• pp.157-161
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• 2022

Building on the DC interaction model between a parent company and its spin-offs, we examine that a dyadic relationship can be differentiated within the functions of space, motivation, and time. We investigate that these three factors encompassing the parent-spin-off DC relationship can be applicable to both linear(i.e., geographic proximity and low spin-off CEO's salary is positive) and nonlinear(i.e., too much frequency of new spin-off creation is as harmful as too little) effects on determining the performance of spin-off firms. The direction of causality is underpinned by social capital, human capital, and compensation-activation theory rather than by the normal consequences of previous empirical research. Further, our results suggest the overlap between DC and entrepreneurship; namely, spin-off firms create, learn, and exploit opportunities through a reconfiguration of parent DC so that DC establishes itself as a key concept in the entrepreneurship domain.