• The Journal of the Acoustical Society of Korea
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• v.10 no.1
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• pp.52-60
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• 1991

This paper describes the study on isolated word recognition by using DHMM(Dynamic Hidden Markov Model) which has dynamic feature of spectrum as a parameter. This paper discusses speech recognition experiment basedon HMM which can evaluate not only instantaneous spectral features but also dynamic spectral features. LPC cepstrum parameters is used as a static feature and LPC cepstrum's regression coefficient is used as a dynamic feature. These two features are quantized by each VQ codebook. DHMM is modeled by receiving static vector and dynamic vector by input. In the whole experiment, as recognition experiment using DHMM shows 92.7% of recognition rate while the experiment using conventional HMM shows 88.8% of recognition rate, DHMM proved to be a useful model.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.4
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• pp.303-312
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• 2007

There is still a controversy going on about how to model energy dissipation due to breaking over frequency domain. In this study, we unveil the exact structure of energy dissipation using stochastic wave breaking model. It turns out that contrary to our present understanding, energy dissipation is cubically distributed over frequency domain. The verification of proposed model is conducted using the acquired data during SUPERTANK Laboratory Data Collection Project (Krauss et al., 1992). For further verification, we numerically simulate the nonlinear shoaling process of Conoidal wave over a beach of uniform slope, and obtain very promising results from the viewpoint of a skewness and asymmetry of wave field, usually regarded as the most fastidious parameter to satisfy.

• ETRI Journal
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• v.35 no.3
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• pp.542-545
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• 2013

State-of-the-art voice codecs have been developed to extend the input bandwidth to enhance quality while maintaining interoperability with a legacy codec. Most of them employ a modified discrete cosine transform (MDCT) for coding their extended band. We propose a source filter model-based coding algorithm of MDCT spectral coefficients, apply it to the ITU-T G.711.1 super wideband (SWB) extension codec, and subjectively test it to validate the model. A subjective test shows a better quality over the standardized SWB codec.

• Journal of Astronomy and Space Sciences
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• v.23 no.4
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• pp.303-310
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• 2006

We model the aspherical dust envelopes around O-rich AGB stars. We perform the radiative transfer model calculations for axisymmetric dust distributions. We simulate what could be observed from the aspherical dust envelopes around O-rich AGB stars by presenting the model spectral energy distributions and images at various wave-lengths for different optical depths and viewing angles. The model results are very different from the ones with spherically symmetric geometry.

• 한국전산유체공학회:학술대회논문집
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• 2010.05a
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• pp.556-561
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• 2010

This paper proposes a three-dimensional haptotaxis model to simulate the migration of the population of cancer cells. The invasion of the cancer cells relates with the hapto- and the effect of the energy between cells and (ECM). The diffuse interface model is employed, which incorporates haptotaxis mechanism and interface energies. The semi-implicit Fourier spectral scheme is adopted for efficient complications. The simulation results reveal rich dynamics of cancer cells migration.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.3112-3112
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• 2001

Near-Infrared Spectroscopy (NIRS) was investigated aiming at the identification of falsified drugs. The identification is based on comparison of the NIR spectrum of a sample with a typical spectra of an authentic drug using multivariate modelling and classification algorithms (PCA/SIMCA). Two spectrophotometers (Brimrose - Luminar 2000 and 2030), based on acoustic-optical filter (AOTF) technology, sharing the same controlling computer, software (Brimrose - Snap 2.03) and the data acquisition electronics, were employed. The Luminar 2000 scans the range 850 1800 nm and was employed for transmitance/absorbance measurements of liquids with a transflectance optical bundle probe with total optical path of 5 mm and a circular area of 0.5 $\textrm{cm}^2$. Model 2030 scans the rage 1100 2400 nm and was employed for reflectance measurement of solids drugs. 300 spectra, acquired in about 20 s, were averaged for each sample. Chemometric treatment of the spectral data, modelling and classification were performed by using the Unscrambler 7.5 software (CAMO Norway). This package provides the Principal Component Analysis (PCA) and SIMCA algorithms, used for modelling and classification, respectively. Initially, NIRS was evaluated for spectrum acquisition of various drugs, selected in order to accomplish the diversity of physico-chemical characteristics found among commercial products. Parameters which could affect the spectra of a given drug (especially if presented as solid tablets) were investigated and the results showed that the first derivative can minimize spectral changes associated with tablet geometry, physical differences in their faces and position in relation to the probe beam. The effect of ambient humidity and temperature were also investigated. The first factor needs to be controlled for model construction because the ambient humidity can cause spectral alterations that should cause the wrong classification of a real drug if the factor is not considered by the model.

• Journal of Biosystems Engineering
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• v.31 no.1 s.114
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• pp.59-64
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• 2006

Application of herbicide for rice cropping is inevitable but notorious for its side effect of environmental pollution. Precision fanning will be one of important tools for the least input and sustainable fanning and could be achieved by implementation of the variable rating technology. If a device to detect weeds in rice field is available, herbicide could be applied only to the places where it is needed by the manner of the variable rating technology. The study was carried out to develop an algorithm of image processing to detect weeds in rice field using a machine vision system of multi-spectral digital images. A series of multi-spectral rice field picture of 560, 680 and 800 nm of center wavelengths were acquired from the 27th day to the 39th day after transplanting in the ineffective tillering stage of a rice growing period. A discrimination model to distinguish pixels of weeds from those of rice plant and weed image was developed. The model was proved as having accuracies of 83.6% and 58.9% for identifying the rice plant and the weed, respectively. The model was used in the algorithm to differentiate weed images from mingled images of rice plant and weed in a frame of rice field picture. The developed algorithm was tested with the acquired rice field pictures and resulted that 82.7%, 11.9% and 5.4% of weeds in the pictures were noted as the correctly detected, the undetected and the misclassified as rice, respectively, and 81.9% and 18.0% of rice plants in the pictures were marked as the correctly detected and the misclassified as weed, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.1 no.1
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• pp.85-93
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• 1997

In this paper, a novel method for obtaining spectra of short pulses is proposed. This method will be well-applied to perform spectral analyses of ultrashort laser pulses which are known to be difficult to evaluate their exact forms in frequency domain because of their narrow-width characteristics in time domain. It must be noted that the method can be represented by a recursive formula derived from the PRS(partial-response signaling) model, and thus more easily available for numerical solutions than the conventional methods such as consecutive differentiations and convolutions. The pulses whose fundamental frames can be exactly determined or approximately represented by truncated Fourier series have well-behaving conditions for applications of this new method. Moreover, the transversal 9-type PRS model can offer various approximations for spectral analyses of ultrashort pulses currently used in transmission systems.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.155-164
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• 2024

This study proposes an unsupervised learning-based clustering model to estimate the ESG ratings of domestic public institutions. To achieve this, the optimal number of clusters was determined by comparing spectral clustering and k-means clustering. These results are guaranteed by calculating the Davies-Bouldin Index (DBI), a model performance index. The DBI values were 0.734 for spectral clustering and 1.715 for k-means clustering, indicating lower values showed better performance. Thus, the superiority of spectral clustering was confirmed. Furthermore, T-test and ANOVA were used to reveal statistically significant differences between ESG non-financial data, and correlation coefficients were used to confirm the relationships between ESG indicators. Based on these results, this study suggests the possibility of estimating the ESG performance ranking of each public institution without existing ESG ratings. This is achieved by calculating the optimal number of clusters, and then determining the sum of averages of the ESG data within each cluster. Therefore, the proposed model can be employed to evaluate the ESG ratings of various domestic public institutions, and it is expected to be useful in domestic sustainable management practice and performance management.

• Geophysics and Geophysical Exploration
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• v.10 no.1
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• pp.60-68
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• 2007

Conventional analysis of spectral induced polarization (SIP) data consists of measuring impedances over a range of frequencies, followed by spectral analysis to estimate spectral parameters. For the quantitative and accurate estimation of subsurface SIP parameter distribution, however, a sophisticated and stable inversion technique is required. In this study, we have developed a two-step inversion approach to obtain the two-dimensional distribution of SIP parameters. In the first inversion step, all the SIP data measured over a range of frequencies are simultaneously inverted, adopting cross regularisation of model complex resistivities at each frequency. The cross regularisation makes it possible to enhance the noise characteristics of the inversion by imposing a strong assumption, that complex resistivities should show similar characteristics over a range of frequencies. In numerical experiments, we could verify that our inversion approach successfully reduced inversion artefacts. As a second step, we have also developed an inversion algorithm to obtain SIP parameters based on the Cole-Cole model, in which frequency-dependent complex resistivities from the first step are inverted to obtain a two-dimensional distribution of SIP parameters. In numerical tests, the SIP parameter images showed a fairly good match with the exact model, which suggests that SIP imaging can provide a very useful subsurface image to complement resistivity.