• Journal of Ginseng Research
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• v.45 no.2
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• pp.246-253
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• 2021

Background: Ginseng is one of the most valuable herbal supplements. It is challenging to perform quality control of ginseng products due to the diversity of bioactive saponins in their composition. Acid or alkaline hydrolysis is often used for the structural elucidation of these saponins and sugars in their side chains. Complete transformation of the original ginsenosides into their aglycones during the hydrolysis is one of the ways to determine a total saponin group content. The main hurdle of this approach is the formation of various by-products that was reported by many authors. Methods: Separate HPLC assessment of the total protopanaxadiol, protopanaxatriol and ocotillol ginsenoside contents is a viable alternative to the determination of characteristic biomarkers of these saponin groups, such as ginsenoside Rf and pseudoginsenoside F₁₁, which are commonly used for authentication of P. ginseng Meyer and P. quinquefolius L. samples respectively. Moreover, total ginsenoside content is an ideal aggregated parameter for standardization and quality control of ginseng-based medicines, because it can be directly applied for saponin dosage calculation. Results: Different hydrolysis conditions were tested to develop accurate quantification method for the elucidation of total ginsenoside contents in herbal products. Linearity, limits of quantification, limits of detection, accuracy and precision were evaluated for the developed HPLC-MS method. Conclusion: Alkaline hydrolysis results in fewer by-products than sugar elimination in acidic conditions. An equimolar response, as a key parameter for quantification, was established for several major ginsenosides. The developed approach has shown acceptable results in the analysis of several different herbal products.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.143-151
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• 2021

The enormous prevalence of transferring official confidential digital documents via the Internet shows the urgent need to deliver confidential messages to the recipient without letting any unauthorized person to know contents of the secret messages or detect there existence . Several Steganography techniques such as the least significant Bit (LSB), Secure Cover Selection (SCS), Discrete Cosine Transform (DCT) and Palette Based (PB) were applied to prevent any intruder from analyzing and getting the secret transferred message. The utilized steganography methods should defiance the challenges of Steganalysis techniques in term of analysis and detection. This paper presents a novel and robust framework for color image steganography that combines Linear Congruential Generator (LCG), simulated annealing (SA), Cesar cryptography and LSB substitution method in one system in order to reduce the objection of Steganalysis and deliver data securely to their destination. SA with the support of LCG finds out the optimal minimum sniffing path inside a cover color image (RGB) then the confidential message will be encrypt and embedded within the RGB image path as a host medium by using Cesar and LSB procedures. Embedding and extraction processes of secret message require a common knowledge between sender and receiver; that knowledge are represented by SA initialization parameters, LCG seed, Cesar key agreement and secret message length. Steganalysis intruder will not understand or detect the secret message inside the host image without the correct knowledge about the manipulation process. The constructed system satisfies the main requirements of image steganography in term of robustness against confidential message extraction, high quality visual appearance, little mean square error (MSE) and high peak signal noise ratio (PSNR).

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.29-35
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• 2021

License plate recognition plays a key role in intelligent transportation systems. Therefore, it is a very important process to efficiently detect the number and character areas. In this paper, we propose a method to effectively detect license plate number area by applying deep learning and semantic image segmentation algorithm. The proposed method is an algorithm that detects number and text areas directly from the license plate without preprocessing such as pixel projection. The license plate image was acquired from a fixed camera installed on the road, and was used in various real situations taking into account both weather and lighting changes. The input images was normalized to reduce the color change, and the deep learning neural networks used in the experiment were Vgg16, Vgg19, ResNet18, and ResNet50. To examine the performance of the proposed method, we experimented with 500 license plate images. 300 sheets were used for learning and 200 sheets were used for testing. As a result of computer simulation, it was the best when using ResNet50, and 95.77% accuracy was obtained.

• Structural Engineering and Mechanics
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• v.83 no.3
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• pp.293-304
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• 2022

In this work, a novel reliability approach for combined high and low cycle fatigue (CCF) estimation is developed by combining active learning strategy with least squares support vector machines (LS-SVM) (named as ALS-SVM) surrogate model to address the multi-resources uncertainties, including working loads, material properties and model itself. Initially, a new active learner function combining LS-SVM approach with Monte Carlo simulation (MCS) is presented to improve computational efficiency with fewer calls to the performance function. To consider the uncertainty of surrogate model at candidate sample points, the learning function employs k-fold cross validation method and introduces the predicted variance to sequentially select sampling. Following that, low cycle fatigue (LCF) loads and high cycle fatigue (HCF) loads are firstly estimated based on the training samples extracted from finite element (FE) simulations, and their simulated responses together with the sample points of model parameters in Coffin-Manson formula are selected as the MC samples to establish ALS-SVM model. In this analysis, the MC samples are substituted to predict the CCF reliability of turbine blades by using the built ALS-SVM model. Through the comparison of the two approaches, it is indicated that the reliability model by linear cumulative damage rule provides a non-conservative result compared with that by the proposed one. In addition, the results demonstrate that ALS-SVM is an effective analysis method holding high computational efficiency with small training samples to gain accurate fatigue reliability.

• The Journal of Engineering Geology
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• v.32 no.2
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• pp.271-280
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• 2022

Landfast sea ice forms near coastlines in polar regions. Continuous monitoring of this sea ice is important, as it plays a key role in the marine ecosystem and affects the operation of nearby research stations. This study detected landfast sea ice around Jang Bogo research station in East Antarctica by stacking interferometric coherence images of Sentinel-1 synthetic aperture radar (SAR) data with 6-, 12- and 18-day temporal baselines. A total of 50 landfast sea ice maps were generated covering July 2017 to June 2018. The time series revealed regional differences in the timing of the maximum extent as well as growth rate of landfast sea ice. Overall, detecting landfast sea ice using interferometric SAR coherence seems promisingly feasible; however, limitations remain owing to low backscattering coefficients from new and smooth sea ice surfaces and subtle movements of sea ice in contact with the Campbell Glacier Tongue.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.4
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• pp.723-736
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• 2022

Steganography is being used as a means of secret communication for crimes that threaten national security such as terrorism and espionage. With the development of computers, steganography technologies develop and criminals produce and use their own programs. However, the research for steganography is not active because detailed information on national security cases is not disclosed. The development of investigation technologies and the responses of criminal law are insufficient. Therefore, in this paper, the detection and decoding process was examined for steganography investigation, and the method was analyzed for 'the spy case of Pastor Kim', who was convicted by the Supreme Court. Multiple security devices were prepared using symmetric steganography using the pre-promised stego key. Furthermore, the three criminal legal issues: (1) the relevance issue, (2) the right to participate, and (3) the public trial issue a countermeasure were considered in national security cases. Through this paper, we hope that the investigative agency will develop analysis techniques for steganography.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1739-1748
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• 2021

Real estate prices affect countries, businesses, and households, and many studies have been conducted on the real estate bubble in recent soaring real estate prices. However, if the real estate bubble prediction simply compares the real estate price, or if it does not reflect key psychological variables in real estate sales, it can be judged that the accuracy of the bubble prediction model is poor. The purpose of this study is to design a predictive model that can explain the real estate bubble situation by region using the autoencoder technique. Existing real estate bubble analysis studies failed to set various types of variables that affect prices, and most of them were conducted based on linear models. Thus, this study suggests the possibility of introducing techniques and variables that have not been used in existing real estate bubble studies.

• The Korean Journal of Nuclear Medicine
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• v.13 no.1_2
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• pp.7-14
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• 1979

Radionuclide cardiac angiography has distinct advantages in safety, patient comfort, cost and ease of performance. This method offers diagnostic accuracy equivalent to that of cardiac catheterization. By this method the qualitative and quantitative diagnosis of the cardiac shunts are available. Also for it is repeatable with ease and more physiologic, it has application in following pre- and post-operative shunt patients. We performed the radionuclide cardiac angiographies in 147 cases of heart diseases and 26 cases of normal group. 1. The detection of left-to-right shunt was possible in 22 of 24 patients, and 2 patients were not diagnosed due to small shunt amount. (Qp/Qs<1.3) In 21 patients of right-to-left shunt, all were diagnosed by radionuclide cardiac angiography. 2. With the pulmonary time-activity curve, $C_2/C_1$ ratio was calculated. In normal control group, a range of $C_2/C_1$ ratios of $21{\sim}38%$ was established with a mean value of $28.6{\pm}4.6%$. In patients with left-to-right shunts determined by catheterization data, the range of $C_2/C_1$ ratio was $33{\sim}90%$, with a mean value of $67.8{\pm}12.2%$. 3. In 8 cases of left-to-right shunt, $Q_p/Q_s$ ratios determined by radionuclide cardiac angiography were compaired with those of cardiac catheterization. The correlation coefficient was 0.907. (P<0.001) 4. Postoperative radionuclide cardiac angiographies were done in 21 cases. 3 of 13 patients with left-to-right shunts were found to have residual shunts. 8 patients with right-to-left shunts were confirmed to have no residual shunt.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.5
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• pp.139-148
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• 2009

In this paper, I propose an automatic analysis method of golf swine from single-camera video sequences. I define necessary swing features for automatic swing analysis in 2-dimensional environment and present efficient swing analysis methods using various image processing techniques including line and edge detection. The proposed method has two characteristics compared with previous swing analysis systems and related studies. First, the proposed method enables an automatic swing analysis in 2-dimension while previous systems require 3-dimensional environment which is relatively complex and expensive to run. Second, swing analysis is done automatically without human intervention while other 2-dimensional systems necessarily need analysis by a golf expert. I tested the method on 20 swing video sequences and found the proposed method works effective for automatic analysis of golf swing.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.37.3-38
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• 2021

One of the key questions on star formation is how the organic molecules are synthesized and delivered to the planets and comets since they are the building blocks of prebiotic molecules such as amino acid, which is thought to contribute to bringing life on Earth. Recent astrochemical models and experiments have explained that complex organic molecules (COMs; molecules composed of six or more atoms) are produced on the dust grain mantles in cold and dense gas in prestellar cores. However, the chemical networks and the roles of physical conditions on chemistry are not still understood well. To address this question, hot (> 100 K) cores in high mass young stellar objects (M > 8 Msun) are great laboratories due to their strong emissions and larger samples than those of low-mass counterparts. In addition, CH₃OH masers, which have been mostly found in high mass star forming regions, can provide constraints due to their very unique emerging mechanisms. We investigate twelve high mass star forming regions in ALMA band 6 observation. They are associated with 44/95 GHz Class I and 6.7 GHz Class II CH3OH masers, implying that the active accretion processes are ongoing. For these previously unresolved regions, 66 continuum peaks are detected. Among them, we found 28 cores emitting COMs and specified 10 cores associated with 6.7 GHz Class II CH3OH masers. The chemical diversity of COMs is found in cores in terms of richness and complexity; we identified up to 19 COMs including oxygen- and nitrogen-bearing molecules and their isotopologues in a core. Oxygen-bearing molecules appear to be abundant and more complex than nitrogen-bearing species. On the other hand, the COMs detection rate steeply grows with the gas column density, which can be attributed to the effective COMs formation in dense cores.