• Molecules and Cells
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• v.37 no.6
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• pp.457-466
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• 2014

Proteomic analysis is helpful in identifying cancerassociated proteins that are differentially expressed and fragmented that can be annotated as dysregulated networks and pathways during metastasis. To examine metastatic process in lung cancer, we performed a proteomics study by label-free quantitative analysis and N-terminal analysis in 2 human non-small-cell lung cancer cell lines with disparate metastatic potentials - NCI-H1703 (primary cell, stage I) and NCI-H1755 (metastatic cell, stage IV). We identified 2130 proteins, 1355 of which were common to both cell lines. In the label-free quantitative analysis, we used the NSAF normalization method, resulting in 242 differential expressed proteins. For the N-terminal proteome analysis, 325 N-terminal peptides, including 45 novel fragments, were identified in the 2 cell lines. Based on two proteomic analysis, 11 quantitatively expressed proteins and 8 N-terminal peptides were enriched for the focal adhesion pathway. Most proteins from the quantitative analysis were upregulated in metastatic cancer cells, whereas novel fragment of CRKL was detected only in primary cancer cells. This study increases our understanding of the NSCLC metastasis proteome.

• The Journal of the Korea Contents Association
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• v.12 no.6
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• pp.346-352
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• 2012

Radiation dose estimation on the newborn and infants during radiation examinations, unlike for the adults, is not actively being progressed. Therefore, as an index to present exposure dose during radiation examinations on newborn and infants, entrance skin dose was measured, and the result was compared with results of monte carlo simulation to raise reproducibility of entrance skin dose measurement, and it was proved that various geometry implementation was possible. The resulting values through monte carlo simulation was estimated using normalization factors for entrance skin dose to calibrate radiation dose and then normalized to a unit X ray radiation field size. Average entrance skin dose per one time exposure was $78.41{\mu}Gy$ and the percentage error between measurement by dosimeter and by monte carlo simulation was found to be -4.77%. Entrance skin dose assessment by monte carlo simulation provides possible alternative method in difficult entrance skin dose estimation for the newborn and infants who visit hospital for actual diagnosis.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.65-74
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• 2009

In optimizing the neural network structure, there are two methods of the pruning scheme and the constructive scheme. In this paper we use the pruning scheme to optimize neural network structure, and the genetic algorithm to find out its optimum node pruning. In the conventional researches, the input and hidden layers were optimized separately. On the contrary we attempted to optimize the two layers simultaneously by encoding two layers in a chromosome. The offspring networks inherit the weights from the parent. For teaming, we used the existing error back-propagation algorithm. In our experiment with various databases from UCI Machine Learning Repository, we could get the optimal performance when the network size was reduced by about $8{\sim}25%$. As a result of t-test the proposed method was shown better performance, compared with other pruning and construction methods through the cross-validation.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.1
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• pp.1-8
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• 2011

The accuracy of MR sensor-based electronic compass is influenced by the temperature drift and DC offset of the MR sensor and the OP-amp, the magnetic distortion of nearby magnetic materials, and the compass tilt We design the 3-axis MR sensor and accelerometers-based electronic compass which is compensated by the set/reset pulse switching method on the temperature drift and DC offset, by the execution of hard-iron calibration routine on the magnetic distortion, and by the execution of the Euler rotational equation on the compass tilt. We qualitatively analyze the measured azimuth error on the execution of sensitivity calibration routine which is the normalization process on the different sensitivity of each MR sensor and the different gain of each op-amps. This compensation and analytic result make us design the one degree accuracy electronic compass.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.26-35
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• 2009

In this paper, we present morphology-based step region extraction and regularized iterative point-spread-function (PSF) estimation methods. The proposed PSF estimation method uses canny edge detector to extract the edge of the input image. We extract feasible vertical and horizontal edges using morphology analysis, such as the hit-or-miss transform. Given extracted edges we estimate the optimal step-response using flattening and normalization processes. The PSF is finally characterized by solving the equation which relates the optimal step response and the 2D isotropic PSF. We shows the restored image by the estimated PSF. The proposed algorithm can be applied a fully digital auto-focusing system without using mechanical focusing parts.

• Journal of Digital Contents Society
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• v.19 no.2
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• pp.363-370
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• 2018

Ransomware detection has become a hot topic in computer security for protecting digital contents. Unfortunately, current signature-based and static detection models are often easily evadable by compress, and encryption. For overcoming the lack of these detection approach, we have proposed the dynamic ransomware detection system using data mining techniques such as RF, SVM, SL and NB algorithms. We monitor the actual behaviors of software to generate API calls flow graphs. Thereafter, data normalization and feature selection were applied to select informative features. We improved this analysis process. Finally, the data mining algorithms were used for building the detection model for judging whether the software is benign software or ransomware. We conduct our experiment using more suitable real ransomware samples. and it's results show that our proposed system can be more effective to improve the performance for ransomware detection.

• The Journal of Korean Association of Computer Education
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• v.12 no.2
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• pp.47-59
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• 2009

Informatics textbooks for elementary school students have been developed by cities, provinces, and private publishers respectively, and instructional objectives differ depending on the textbook selected by each school. Therefore, discussion on the analysis of instructional objectives is highly needed. The purpose of this study is to develop standards of instructional objectives for Informatics textbooks in elementary school based on the analysis of instructional objectives. To do so, first, an analysis frame was made based on preceding studies for instructional objectives. Second, instructional objectives of current Informatics textbooks were analyzed. Finally, standards of instructional objectives were developed applying Delphi method. It is expected that the standards of instructional objectives suggested here will be referred to as a guideline for developing the curricula and textbooks for Informatics subject in elementary school and to contribute to the normalization of production for qualified textbooks and education in Informatics subject in the future.

• Molecules and Cells
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• v.22 no.3
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• pp.336-342
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• 2006

Real time reverse transcription (RT)-PCR was used to quantify the expression of the botulinum neurotoxin type A (BoNT/A) gene (cntA) by normalization with the expression of 16S rRNA. The method were confirmed by monitoring the mRNA levels of cntA during growth in five type A strains. In all but one of the strains the expression of cntA mRNA was maximal in the late exponential phase, and approximately 35-fold greater than in the early exponential phase. The concentration of the extracellular BoNT/A complex detected by ELISA was highest in stationary phase. Sodium nitrite and sorbic acid completely inhibited growth at 20 ppm and $4mg\;ml^{-1}$, respectively. CntA expression became lower in proportion to the concentration of sorbic acid, and this reduction was confirmed by mouse bioassay. Our results show that real time RT-PCR can be used to quantify levels of C. botulinum type A neurotoxin transcripts and to assess the effects of food additives on botulinal risk.

• Preventive Nutrition and Food Science
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• v.8 no.1
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• pp.40-45
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• 2003

Acanthopanax senticosus was grown by a novel, proprietary method, of culturing isolated cells in a bioreactor. An extract from the cells was evaluated for its effect on lipid metabolism in rats fed a high fat diet. Male Sprague-Dawley rats (n＝6) were fed either an AIN-76 diet (control, NDCon), control diet plus Acanthopanax senticosus extract (ND＋Ex), a modified AIN-76 diet supplemented with 20% beef tallow (high fat, HFCon), or a high fat diet plus Acanthopanax senticosus extract (HF＋Ex), for 5weeks. Body weight gain was significantly higher in the HFCon group than the NDCon group. Feed consumption was significantly lower, but energy intake higher, in the groups fed high fat diets compared with the groups fed control diets. Serum HDL-cholesterol concentrations were significantly increased but serum LDL-cholesterol concentrations were decreased in the groups fed the Acanthopanax senticosus extract. Abdominal fat accumulation and serum leptin levels were significantly higher in the HFCon group than the other groups. Carnitine palmitoyltransferase-I (CPT-I) mRNA levels were increased in the groups fed Acanthopanx senticosus extract. These results suggest that supplementation of cell cultured Acanthopanax senticosus extract regulates CPT-I mRNA levels in liver and has an effect on the normalization of lipids in rats fed a high fat diet.

• Journal of Biosystems Engineering
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• v.38 no.1
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• pp.48-54
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• 2013

Purpose: This study evaluated the feasibility of using a discrete wavelet transform (DWT) method as a preprocessing tool for visible/near-infrared spectroscopy (VIS/NIRS) with a spectroscopic transmittance dataset for predicting the internal quality of cherry tomatoes. Methods: VIS/NIRS was used to acquire transmittance spectrum data, to which a DWT was applied to generate new variables in the wavelet domain, which replaced the original spectral signal for subsequent partial least squares (PLS) regression analysis and prediction modeling. The DWT concept and its importance are described with emphasis on the properties that make the DWT a suitable transform for analyzing spectroscopic data. Results: The $R^2$ values and root mean squared errors (RMSEs) of calibration and prediction models for the firmness, sugar content, and titratable acidity of cherry tomatoes obtained by applying the DWT to a PLS regression with a set of spectra showed more enhanced results than those of each model obtained from raw data and mean normalization preprocessing through PLS regression. Conclusions: The developed DWT-incorporated PLS models using the db5 wavelet base and selected approximation coefficients indicate their feasibility as good preprocessing tools by improving the prediction of firmness and titratable acidity for cherry tomatoes with respect to $R^2$ values and RMSEs.