• Journal of the Korean Society of Food Science and Nutrition
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• v.38 no.6
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• pp.801-806
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• 2009

A species producing transglutaminase (EC 2.3.2.13) was isolated from forest soil and identified as Streptomyces platensis YK-2. The transglutaminase was purified from culture broth by 50% methanol precipitation, followed by successive chromatography on DEAE-Sephadex. The yield and purification-fold was 63.4% and 2.2-fold, respectively. The purified microbial transglutaminase (MTG) migrated as a single band of approximately 45 kDa upon sodium dodecyl sulfate polyacrylamide gel eletrophoresis. The isoelectric point determined by multichambered electrofocusing was pH $6.0{\sim}7.0$. The enzyme was strongly inhibited by $Hg^{++}$, but was activated by $Cd^{++}$, $Mg^{++}$, $Mn^{++}$, $Pb^{++}$ and reducing agents such as dithiothreitol and mercaptoethanol.

• The Journal of the Acoustical Society of Korea
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• v.27 no.5
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• pp.256-261
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• 2008

In this paper, we propose a novel approach to improve the performance of minima controlled recursive averaging (MCRA) which is based on the conditional maximum a posteriori criterion. A crucial component of a practical speech enhancement system is the estimation of the noise power spectrum. One state-of-the-art approach is the minima controlled recursive averaging (MCRA) technique. The noise estimate in the MCRA technique is obtained by averaging past spectral power values based on a smoothing parameter that is adjusted by the signal presence probability in frequency subbands. We improve the MCRA using the speech presence probability which is the a posteriori probability conditioned on both the current observation the speech presence or absence of the previous frame. With the performance criteria of the ITU-T P.862 perceptual evaluation of speech quality (PESQ) and subjective evaluation of speech quality, we show that the proposed algorithm yields better results compared to the conventional MCRA-based scheme.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.2
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• pp.33-41
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• 2001

Currently, the compression is one of the most important technology in multimedia society. Audio files arc rapidly propagated throughout internet Among them, the most famous one is MP-3(MPEC-1 Laver3) which can obtain CD tone from 128Kbps, but tone quality is abruptly down below 64Kbps. MPEC-II AAC(Advanccd Audio Coding) is not compatible with MPEG 1, but it has high compression of 1.4 times than MP 3, has max. 7.1 and 96KHz sampling rate. In this paper, we propose an algorithm that decreased the capacity of AAC encoding computation but increased the processing speed by optimizing psychoacoustic model which has enormous amount of computation in MPEG 2 AAC encoder. The optimized psychoacoustic model algorithm was implemented by C++ language. The experiment shows that the psychoacoustic model carries out FFT(Fast Fourier Transform) computation of 3048 point with 44.1 KHz sampling rate for SMR(Signal to Masking Ratio), and each entropy value is inputted to the subband filters for the control of encoder block. The proposed psychoacoustic model is operated with high speed because of optimization of unpredictable value. Also, when we transform unpredictable value into a tonality index, the speed of operation process is increased by a tonality index optimized in high frequency range.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.5
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• pp.445-453
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• 2016

This paper presents the implementation and design of the 1T-1R wireless HD video streaming systems over 28 GHz mmWave frequency using 3GPP LTE-TDD standard on NI USRP RIO SDR platform. The baseband of the system uses USRP RIO that are stored in Xilinx Kintex-7 chip to implement LTE-TDD transceiver modem, the signal that are transceived from USRP RIO up or down converts to 28 GHz by using self-designed 28 GHz RF transceiver modules and it is finally communicated HD video data through self-designed $4{\times}8$ sub array antennas. It is that communication method between USRP RIO and Host PC use PCI express ${\times}4$ to minimize delay of data to transmit and receive. The implemented system show high error vector magnitude performance above 25.85 dBc and to transceive HD video in experiment environment anywhere.

• Journal of Adhesion and Interface
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• v.21 no.3
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• pp.107-112
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• 2020

Recently, the atomically thin transition-metal dichalcogenide (TMD) semiconductors have attracted much attention owing to their remarkable properties such as tunable bandgap with high carrier mobility, flexibility, transparency, etc. However, because these TMD materials have a significant drawback that they are easily degraded in an ambient environment, various attempts have been made to improve chemical stability. In this research article, I report a method to improve the air stability of WSe₂ one of the TMD materials via surface passivation with an h-BN insulator, and its application to field-effect transistors (FETs). With a modified hot pick-up transfer technique, a vertical heterostructure of h-BN/WSe₂ was successfully made, and then the structure was used to fabricate the top-gate bottom-contact FETs. The fabricated WSe₂-based FET exhibited not only excellent air stability, but also high hole mobility of 150 ㎠/Vs at room temperature, on/off current ratios up to 3×10⁶, and 192 mV/decade of subthreshold swing.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.4
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• pp.22-30
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• 2001

In this paper we propose three classification algorithms to classify breast tumors that occur in duct into Benign, DCIS(ductal carcinoma in situ) NOS(invasive ductal carcinoma) The general approach for a creating classifier is composed of 2 steps: feature extraction and classification Above all feature extraction for a good classifier is very significance, because the classification performance depends on the extracted features, Therefore in the feature extraction step, we extracted morphology features describing the size of nuclei and texture features The internal structures of the tumor are reflected from wavelet transformed images with 10$\times$ and 40$\times$ magnification. Pariticulary to find the correlation between correct classification rates and wavelet depths we applied 1, 2, 3 and 4-level wavelet transforms to the images and extracted texture feature from the transformed images The morphology features used are area, perimeter, width of X axis width of Y axis and circularity The texture features used are entropy energy contrast and homogeneity. In the classification step, we created three classifiers from each of extracted features using discriminant analysis The first classifier was made by morphology features. The second and the third classifiers were made by texture features of wavelet transformed images with 10$\times$ and 40$\times$ magnification. Finally we analyzed and compared the correct classification rate of the three classifiers. In this study, we found that the best classifier was made by texture features of 3-level wavelet transformed images.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.2 s.302
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• pp.11-18
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• 2005

To detect vehicles in image, first the image is transformed with the steerable pyramid which has independent directions and levels. Feature vectors are the collection of filter responses at different scales of a steerable image pyramid. For the detection of vehicles in image, feature vectors in feature points of the vehicle image is used. First the feature points are selected with the grid points in vehicle image that are evenly spaced, and second, the feature points are comer points which m selected by human, and last the feature points are corner Points which are selected in grid points. Next the feature vectors of the model vehicle image we compared the patch of the test images, and if the distance of the model and the patch of the test images is lower than the predefined threshold, the input patch is decided to a vehicle. In experiment, the total 11,191 vehicle images are captured at day(10,576) and night(624) in the two local roads. And the $92.0\%$ at day and $87.3\%$ at night detection rate is achieved.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.579-588
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• 2013

This paper proposes an effective watermarking approach for copyright protection of fire video images. The proposed watermarking approach efficiently utilizes the inherent characteristics of fire data with respect to color and texture by using a gray level co-occurrence matrix (GLCM) and fuzzy c-means (FCM) clustering. GLCM is used to generate a texture feature dataset by computing energy and homogeneity properties for each candidate fire image block. FCM is used to segment color of the fire image and to select fire texture blocks for embedding watermarks. Each selected block is then decomposed into a one-level wavelet structure with four subbands [LL, LH, HL, HH] using a discrete wavelet transform (DWT), and LH subband coefficients with a gain factor are selected for embedding watermark, where the visibility of the image does not affect. Experimental results show that the proposed watermarking approach achieves about 48 dB of high peak-signal-to-noise ratio (PSNR) and 1.6 to 2.0 of low M-singular value decomposition (M-SVD) values. In addition, the proposed approach outperforms conventional image watermarking approach in terms of normalized correlation (NC) values against several image processing attacks including noise addition, filtering, cropping, and JPEG compression.

• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.93-101
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• 2009

This paper suggests a new algorithm automatically searching for Region-of-Interest(ROI) with high speed, using the edge information of high frequency subband transformed with wavelet. The proposed method executes a searching algorithm of 4-direction object boundary by the unit of block using the edge information, and detects ROIs. The whole image is splitted by $64{\times}64$ or $32{\times}32$ sized blocks and the blocks can be ROI block or background block according to taking the edges or not. The 4-directions searche the image from the outside to the center and the algorithm uses a feature that the low-DOF image has some edges as one goes to center. After searching all the edges, the method regards the inner blocks of the edges as ROI, and makes the ROI masks and sends them to server. This is one of the dynamic ROI method. The existing methods have had some problems of complicated filtering and region merge, but this method improved considerably the problems. Also, it was possible to apply to an application requiring real-time processing caused by the process of the unit of block.

• Research in Plant Disease
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• v.12 no.3
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• pp.298-302
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• 2006

An isolate of Cucumber mosaic virus(CMV), called as Can-CMV, was originally isolated from Canna generalis showing typical streak mosaic foliar symptoms, and its properties were investigated in this study. Whereas all known isolates of CMV could induce symptoms on their systemic hosts(four kinds of Nicotiana spp and a zucchini squash), Can-CMV induced no symptoms on its systemic hosts tested. Replication and movement of the virus on upper leaves as well as inoculated leaves-were confirmed by RT-PCR suggesting that Can-CMV could only infect systemically on N. benthamiana and N. glutinosa. Size of local lesions on the Can-CMV-inoculated leaves of Chenopodium amaranticolor was much smaller than that of Fny-CMV. Whereas Fny-CMV and LS-CMV could induce distinct necrotic local lesions on Vigna unguiculata 2 to 3 days postinoculation(dpi), chlorotic spots symptom was expressed by Can-CMV 4 to 5 dpi. Virus-specific 4 kinds of dsRNAs were isolated from leaves of N. benthamiana infected with Can-CMV, and these dsRNAs corresponded to the viral genomic RNAs and subgenomic RNAs and their patterns were indistinguishable to those of Fny-CMV and LS-CMV. By restriction mapping analysis of 950 bp of RT-PCR amplified products of coat protein gene of the virus as well as by serological analysis of gel diffusion test, Can-CMV belongs to a typical member of CMV subgroup IA. These results suggest that the Can-CMV isolated from C. generalis possesses unique pathological properties to understand further insight into the various interactions between virus and host.