• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.1
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• pp.76-83
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• 2016

This study investigated the quality characteristics and antioxidative activity of muffins prepared with coffee ground residue water extracts (CRE) and powder (CRP). CRE-muffins were prepared by addition of CRE (0~2.0%, w/v) to water of a basic formulation, whereas CRP-muffins were prepared by addition of CRP (0~3.0%, w/w) to the flour. The height and volume index of CRE-muffins were higher than those of control. The weight and water contents of CRE-muffins and CRP-muffins were higher than those of the control. The hardness of CRE-muffins decreased compared to the control, whereas hardness of CRP-muffins increased. The total polyphenol contents and antioxidative activity of muffin significantly increased with increasing concentrations of CRE and CRP. Muffins containing 0.5~2.0% CRE and 0.5~3.0% CRP had acceptable sensory properties (flavor, taste, texture, and overall acceptability). Therefore, this study indicated that the optimal concentrations of CRE and CRP into muffin formula are 1.0 % (w/v) and 1.0% (w/w), respectively.

• Journal of the Korean Geotechnical Society
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• v.31 no.8
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• pp.17-28
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• 2015

The purpose of this study is to measure the volumetric water content of unsaturated soils during drying and wetting process by using volumetric pressure plate extractor (VPPE) incorporated with time domain reflectometry (TDR). The VPPE consists of a pressure cell, a pressure regulator, a burette system and a TDR probe. Two samples with different initial void ratios were prepared in the pressure cell, and the air pressure at the range of 0.1 kPa - 50 kPa was applied to adjust the matric suction by the pressure regulator. The burette system was used to measure the volumetric water content change of the sample according to the matric suction. In addition, the TDR probe, installed in the cell, was used to evaluate the dielectric constant from the reflected signal of the electromagnetic wave at the probe. The volumetric water content of specimen was estimated by the empirical equation between the volumetric water content and dielectric constant, which was calibrated with the Jumunjin sand. The test results show that the volumetric water content calculated by TDR probe is strongly correlated to the measured value by burette system. The hysteresis occurs during drying and wetting process. Furthermore, the degree of hysteresis reduces in the repeated process. This study suggests that TDR may be effectively used to evaluate the water content soil for the determination of water characteristic curve of unsaturated soils.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1C
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• pp.102-110
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• 2004

In this paper, we propose a VLSI structure of real-time image compression and reconstruction processor using 2-D discrete wavelet transform and implement into a hardware which use minimal hardware resource using ASIC library. In the implemented hardware, Data path part consists of the DWT kernel for the wavelet transform and inverse transform, quantizer/dequantizer, the huffman encoder/huffman decoder, the adder/buffer for the inverse wavelet transform, and the interface modules for input/output. Control part consists of the programming register, the controller which decodes the instructions and generates the control signals, and the status register for indicating the internal state into the external of circuit. According to the programming condition, the designed circuit has the various selective output formats which are wavelet coefficient, quantization coefficient or index, and Huffman code in image compression mode, and Huffman decoding result, reconstructed quantization coefficient, and reconstructed wavelet coefficient in image reconstructed mode. The programming register has 16 stages and one instruction can be used for a horizontal(or vertical) filtering in a level. Since each register automatically operated in the right order, 4-level discrete wavelet transform can be executed by a programming. We synthesized the designed circuit with synthesis library of Hynix 0.35um CMOS fabrication using the synthesis tool, Synopsys and extracted the gate-level netlist. From the netlist, timing information was extracted using Vela tool. We executed the timing simulation with the extracted netlist and timing information using NC-Verilog tool. Also PNR and layout process was executed using Apollo tool. The Implemented hardware has about 50,000 gate sizes and stably operates in 80MHz clock frequency.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.1
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• pp.13-20
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• 2005

In this paper, I recognized Korean isolated words using CVEM which is suggested by M. Bilginer et al. CVEM is an algorithm which is easy to extract the common properties from training voice signals and also doesn't need complex calculation. In addition CVEM shows high accuracy in recognition results. But, CVEM has couple of problems which are impossible to use for many training voices and no discriminant information among extracted common vectors. To get the optimal common vectors from certain voice classes, various voices should be used for training. But CVEM is impossible to get continuous high accuracy in recognition because CVEM has a limitation to use many training voices and the absence of discriminant information among common vectors can be the source of critical errors. To solve above problems and improve recognition rate, k-clustering subspace method and DCVEM suggested. And did various experiments using voice signal database made by ETRI to prove the validity of suggested methods. The result of experiments shows improvements in performance. And with proposed methods, all the CVEM problems can be solved with out calculation problem.

• The Journal of the Acoustical Society of Korea
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• v.24 no.1
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• pp.29-37
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• 2005

This paper proposes an automatic genre classification system for Korean traditional music. The Proposed system accepts and classifies queried input music as one of the six musical genres such as Royal Shrine Music, Classcal Chamber Music, Folk Song, Folk Music, Buddhist Music, Shamanist Music based on music contents. In general, content-based music genre classification consists of two stages - music feature vector extraction and Pattern classification. For feature extraction. the system extracts 58 dimensional feature vectors including spectral centroid, spectral rolloff and spectral flux based on STFT and also the coefficient domain features such as LPC, MFCC, and then these features are further optimized using SFS method. For Pattern or genre classification, k-NN, Gaussian, GMM and SVM algorithms are considered. In addition, the proposed system adopts MFC method to settle down the uncertainty problem of the system performance due to the different query Patterns (or portions). From the experimental results. we verify the successful genre classification performance over $97{\%}$ for both the k-NN and SVM classifier, however SVM classifier provides almost three times faster classification performance than the k-NN.

• Analytical Science and Technology
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• v.11 no.3
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• pp.161-166
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• 1998

Analytical method of haloperidol (HAL) in serum which has been widely used in therapy of schizophrenic disorders is developed. Gas chromatography/nitrogen-phosphorus detection (GC/NPD) was used for this study. Bromoperidol was used as an internal standard and diethylether as a solvent of three-step extraction. The extraction yield in this procedure was $67.5{\pm}1.9%$ at 15 ng/mL. A good linear response in the range of 1~40 ng/mL was obtained with correlation coefficient of $r^2=0.999$. Detection limit was 0.5 ng/mL when 2 mL of serum was used. This method was applied for the analysis of HAL in serum of schizophrenic patients. After HAL decanoate (HD) was intaken as intramuscular route, HAL levels were determined at second week and forth week. From the result, the concentration of HAL at forth week appeared to 29.6% lower than those at second week. The present method showed low detection limit and high selectivity. Therefore it can be applied for the trace analysis of HAL in serum and the monitoring.

• Microbiology and Biotechnology Letters
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• v.33 no.2
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• pp.123-129
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• 2005

Isolation and identification of pathogens from slaughter and meat processing plant were investigated. Antimicrobial activity of Amaranthus lividus against isolated pathogens such as Aeromonas sobria, Escherichia coli, Escherichia coli O157, Listeria monocytogenes, Salmonella spp., and Staphylococcus aureus was investigated. Among the chloroform, ethyl acetate and buthanol fraction of amaranthus lividus showed inhibitory effect against Aeromonas sobria CLFM1 and Escherichia coli CLFM2. Antimicrobial substance in chloroform fraction was isolated by silica gel adsorption column chromatography, sephadex LH-20 column chromatography and silica gel partition column chromatography. The antimicrobial compound of amaranthus lividus was identified as diethyl phtalate by HPLC, GC-MS, H-NMR and C-NMR.

• Analytical Science and Technology
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• v.29 no.5
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• pp.219-224
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• 2016

불산 중 극미량 음이온의 고상추출과 이온크로마토그래프를 이용한 고감도 분석법이 개발되었다. 불산 중 불소이온이 고상에 의해 제거하였고 이어서 음이온 (F⁻, CH₃COO⁻, Cl⁻, Br⁻, NO₃⁻, PO₄³⁻, SO₄²⁻)들이 이온크로마토그래프를 이용하여 연속적으로 분리하였다. 고상 추출법에 영향을 주는 각 인자들 (흡착제의 선택, 시료의 부피 및 pH, 용출 용액과 용출용액의 부피)을 결정하였으며 그 결과 흡착제로서 Oasis WAX 컬럼이 가장 우수하였고 1.0 mL의 시료부피, 용출용액으로 50 mM 초산암모늄염 5 mL가 분리능에서 가장 우수하였다. 개발한 방법에 의한 음이온 (Cl⁻, Br⁻, NO₃⁻, PO₄³⁻, SO₄²⁻)들의 방법검출한계는 25 % 불산용액 (w/w) 중에 0.04~0.30 µg/L의 범위를 보였고 정밀도는 20.0와 40.0 µg/L의 농도에서 5 % 이내를 보였다. 한 제조회사에 의한 25 % 불산 중 음이온의 4.2에서 47.5 µg/L의 범위로 모두 검출되었다. 이 방법은 시험절차가 간단하고, 재현성 및 감도가 좋아서 반도체회사에서 불산 중 음이온 불순물을 정도 관리하는데 매우 유용한 방법이 될 것으로 판단된다.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.461-467
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• 2020

In noisy and multi-speaker environments, the performance of speech recognition is unavoidably lower than in a clean environment. To improve speech recognition, in this paper, the signal of the speaker of interest is extracted from the mixed speech signals with multiple speakers. The VoiceFilter model is used to effectively separate overlapped speech signals. In this work, clustering by Probabilistic Linear Discriminant Analysis (PLDA) similarity score was employed to detect the speech signal of the interested speaker, which is used as the reference speaker to VoiceFilter-based separation. Therefore, by utilizing the speaker feature extracted from the detected speech by the proposed clustering method, this paper propose a speaker diarization system using only the mixed speech without an explicit reference speaker signal. We use phone-dataset consisting of two speakers to evaluate the performance of the speaker diarization system. Source to Distortion Ratio (SDR) of the operator (Rx) speech and customer speech (Tx) are 5.22 dB and -5.22 dB respectively before separation, and the results of the proposed separation system show 11.26 dB and 8.53 dB respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.90-95
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• 2014

The researchs using brain-computer interface, the new interface system which connect human to macine, have been maded to implement the user-assistance devices for control of wheelchairs or input the characters. In recent researches, there are several trials to implement the speech recognitions system based on the brain wave and attempt to silent communication. In this paper, we studied how to extract features of vowel based on international phonetic alphabet (IPA), as a foundation step for implementing of speech recognition system based on electroencephalogram (EEG). We conducted the 2 step experiments with three healthy male subjects, and first step was speaking imagery with single vowel and second step was imagery with successive two vowels. We selected 32 channels, which include frontal lobe related to thinking and temporal lobe related to speech function, among acquired 64 channels. Eigen value of the signal was used for feature vector and support vector machine (SVM) was used for classification. As a result of first step, we should use over than 10th order of feature vector to analyze the EEG signal of speech and if we used 11th order feature vector, the highest average classification rate was 95.63 % in classification between /a/ and /o/, the lowest average classification rate was 86.85 % with /a/ and /u/. In the second step of the experiments, we studied the difference of speech imaginary signals between single and successive two vowels.