• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.754-758
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• 2005

Optimization of process variables such as arc current, welding voltage and welding speed in terms of the weld characteristics desired is the key step in achieving high quality and improving performance characteristics without increasing the cost. Consequently, incorrect settings of those process variables give rise to deviations in the welding characteristics from the desired bead geometry. Therefore, trainee welders are referred to the tabulated information relating different metal types and thickness as to recommend the desired values of process variables. Basically, the bead geometry plays an important role in determining the mechanical properties of the weld. So that it is very important to select the process variables for obtaining optimal bead geometry. However, it is difficult for the traditional identification methods to provide an accurate model because the optimized welding process is non-linear and time-dependent. In this paper, the possibilities of the Infra-red sensor in sensing and control of the bead geometry in the automated welding process are presented. Infra-red sensor is a well-known method to deal with the problems with a high degree of fuzziness so that the sensor is employed to build the relationship between process variables and the quality characteristic the proposed above respectively. Based on several neural networks, the mathematical models are derived from extensive experiments with different welding parameters and complex geometrical features. The developed system enables to select the optimal welding parameters and control the desired weld dimensions during arc welding process.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.159-168
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• 2021

As the information age enters, the use of biometrics using the body is gradually increasing because it is very important to accurately recognize and authenticate each individual's identity for information protection. Among them, finger vein authentication technology is receiving a lot of attention because it is difficult to forge and demodulate, so it has high security, high precision, and easy user acceptance. However, the accuracy may be degraded depending on the algorithm for identification or the surrounding light environment. In this paper, we designed and manufactured a side-type finger vein recognizer that is highly versatile among finger vein measuring devices, and authenticated using the deep learning model of DenseNet-201 for high accuracy and recognition rate. The performance of finger vein authentication technology according to the influence of the infrared light source used and the surrounding visible light was analyzed through simulation. The simulations used data from MMCBNU_6000 of Jeonbuk National University and finger vein images taken directly were used, and the performance were compared and analyzed using the EER.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.619-627
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• 2021

Recent advance in low cost and light-weight drones has extended their application areas in both military and private sectors. Accordingly surveillance program against unfriendly drones has become an important issue. Drone detection and classification technique has long been emphasized in order to prevent attacks or accidents by commercial drones in urban areas. Most commercial drones have small sizes and low reflection and hence typical sensors that use acoustic, infrared, or radar signals exhibit limited performances. Recently, artificial intelligence algorithm has been actively exploited to enhance radar image identification performance. In this paper, we adopt machined learning algorithm for high resolution radar imaging in drone detection and classification applications. For this purpose, simulation is carried out against commercial drone models and compared with experimental data obtained through high resolution radar field test.

• Economic and Environmental Geology
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• v.44 no.6
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• pp.463-474
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• 2011

The Haenam epithermal mineralized zone is located in the southwestern part of South Korea, and hosts low sulfidation epithermal Au-Ag deposit (Eunsan-Moisan) and clay quarries (Okmaesan, Seongsan, and Chunsan). Epithermal deposits and accompanying hydrothermal alteration related to Cretaceous volcanism caused large zoned assemblages of hydrothermal alteration minerals. Advanced argillic-altered rocks with mineral assemblages of alunite-quartz, alunite-dickite-quartz, and dickite-kaolinite-quartz exposed on the Okmaesan, Seongsan, and Chunsan area. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), with three visible and near infrared bands, six shortwave infrared bands, and five thermal infrared bands, was used to identify advanced argillic-altered rocks within the Haenam epithermal mineralized zone. The distinct spectral features of hydrothermal minerals allow discrimination of advanced argillic-altered rocks from non-altered rocks within the study area. Because alunite, dickite, and kaolinite, consisting of advanced argillic-altered rocks within the study area are characterized by Al-O-H-bearing minerals, these acid hydrothermal minerals have a strong absorption feature at $2.20{\mu}m$. The band combination and band ratio transformation cause increasing differences of DN values between advanced argillic-altered rock and non-altered rock. The alunite and dickite-kaolinite of advanced argillic-altered rocks from the Okmaesan, Seongsan, and Chunsan have average DN values of 1.523 and 1.737, respectively. These values are much higher than those (1.211 and 1.308, respectively) of non-altered area. ASTER images can remotely provide the distribution of hydrothermal minerals on the surface. In this way good relation between ASTER spectra analysis and field data suggests that ASTER spectral analysis can be useful tool in the initial steps of mineral exploration.

• Journal of Plant Biotechnology
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• v.43 no.2
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• pp.213-222
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• 2016

This study aims to establish a system for the rapid discrimination of Zoysia species using metabolite fingerprinting of FT-IR spectroscopy combined with multivariate analysis. Whole cell extracts from leaves of 19 identified Zoysia japonica, 6 identified Zoysia sinica, and 38 different unidentified Zoysia species were subjected to Fourier transform infrared spectroscopy (FT-IR). PCA (principle component analysis) and PLS-DA (partial least square discriminant analysis) from FT-IR spectral data successfully divided the 25 identified turf grasses into two groups, representing good agreement with species identification using molecular markers. PC (principal component) loading values show that the $1,100{\sim}950cm^{-1}$ region of the FT-IR spectra are important for the discrimination of Zoysia species. A dendrogram based on hierarchical clustering analysis (HCA) from the PCA and PLS-DA data of turf grasses showed that turf grass samples were divided into Zoysia japonica and Zoysia sinica in a species-dependent manner. PCA and PLS-DA from FT-IR spectral data of Zoysia species identified and unidentified by molecular markers successfully divided the 49 turf grasses into Z. japonica and Z. sinica. In particular, PLS-DA and the HCA dendrogram could mostly discriminate the 47 Z. japonica grasses into two groups depending on their origins (mountainous areas and island area). Considering these results, we suggest that FT-IR fingerprinting combined with multivariate analysis could be applied to discriminate between Zoysia species as well as their geographical origins of various Zoysia species.

• Korean Journal of Heritage: History & Science
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• v.56 no.3
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• pp.158-171
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• 2023

Pottery filled with organic materials was excavated from the G-2 building site of Yongjangseong Fortress, Jingo, a relic of the Goryeo Dynasty. In this study, the characteristics of organic material were confirmed by a scientific analysis of organic material in pottery found at the palace in Yongjangseong, Jindo. In addition, it was intended to review the analysis method to identify the natural resin and to secure characteristic components(biomarkers) for each natural resin and use them as basic data in the future. The organic materials in the pottery were analyzed using attenuated total reflectance Fourier-transformed infrared spectroscopy(ATR-FTIR) and gas chromatography mass spectrometry(GC-MS). The infrared spectral characteristics were estimated to be natural resin, and biomarkers of organic materials were identified as sesquiterpene-based compounds(C₁₅H₂₄, MW 204) and derivatives. The lacquer(T.vemicifluum) is composed mainly of alkenes, alkanes, and catechol. Pine resin(P.densiflora), on the other hand, is primarily composed of diterpenoid(abietic acid, pimaric acid) and Whangchil(yellow lacquer) is identified to have sesquiterpenes(such as selinene, muurolene, calamenene) as its main components. So, the organic material in the pottery can be identified as Whangchil by comparing their compounds with modern resin materials from Dendropanax. morbifera that correspond with the results. Whangchil, which is exuded from the Dendropanax. morbifera, has been used as a natural coating materials since ancient times, and it has been confirmed that the characteristic components are well preserved even 700 years later. It can be assumed that the interior Whangchil was stored not for use as a coating, but rather for ritual purposes when the building was constructed, because the pottery was found near the cornerstone. Furthermore, based on simplified sample preparation using pyrolysis-gas chromatography mass spectrometry(Py-GC-MS), the thermal decomposition products were found to be similar to the characteristic components, suggesting that this method can be applied to the identification of natural resins used in historic artifacts.

• Journal of Applied Biological Chemistry
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• v.57 no.4
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• pp.321-324
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• 2014

Fresh and chopped aerial parts of Oryza sativa were extracted in 80% aqueous mehthanol, and the concentrated extract was successively partitioned in n-hexane, ethyl acetate (EtOAc), n-butanol (n-BuOH), and $H_2O$ fractions. From the n-BuOH fraction, two compounds were isolated through repeated silica gel and ODS column chromatography (c.c.). Based on nuclear magnetic resonance (NMR), mass spectrometry and infrared spectroscopy spectroscopic data, the compounds were identified to be adenosine (1) and phlomuroside (2). Especially, the configuration of both the anomer hydroxyl groups was determined as ${\beta}$ from the coupling constants of the anomer protons (J =6.0 and 7.6 Hz) in the $^1H-NMR$ spectra. This is the first report for the isolation of these compounds from Oryza sativa L.

• 한국생물공학회:학술대회논문집
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• 2003.04a
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• pp.40-44
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• 2003

Soil-borne infectious disease including Pythium aphanidermatum and Rhizoctonia solani causes severe damage to plants, such as cucumber. This soil-borne infectious disease was not controlled effectively by chemical pesticide. Since these diseases spread through the soil, chemical agents are usually ineffective. Instead, biological control, including antagonistic microbe can be used as a preferred control method. An efficient method was developed to select an antagonistic strain to be used as a biological control agent strain. In this new method, surface tension reduction potential of an isolate was included in the ‘decision factor’ in addition to the other factors, such as growth rate, and pathogen inhibition rate. Considering these 3 decision factors by a statistical method, an isolate from soil was selected and was identified as Bacillus sp. GB16. In the pot test, this strain showed the best performance among the isolated strains. The lowest disease incidence rate and fastest seed growth was observed when Bacillus sp. GB16 was used. Therefore this strain was considered as plant growth promoting rhizobacteria (PGPR). The action of surface tension reducing component was deduced as the enhancement of wetting, spreading, and residing of antagonistic strain in the rhizosphere. This result showed that new selection method was significantly effective in selecting the best antagonistic strain for biological control of soil-borne infectious plant pathogen. The antifungal substances against P. aphanidermatum and R. solani were partially purified from the culture filtrates of Bacillus sp. GB16. In this study, lipopeptide possessing antifungal activity was isolated from Bacillus sp. GB16 cultures by various purification procedures and was identified as a surfactin-like lipopeptide based on the Fourier transform infrared spectroscopy (FT-IR), nuclear magnetic resonance (NMR), high performance liquid chromatography mass spectroscopy (HPLC-MS), and quadrupole time-of-flight (Q-TOF) ESI-MS/MS data. The lipopeptide, named GB16-BS, completely inhibited the growth of Pythium aphanidermatum, Rhizoctonia solani, Penicillium sp., and Botrytis cineria at concentrations of 10 and 50 mg/L, respectively. A novel method to prevent the foaming and to provide oxygen was developed. During the production of surface active agent, such as lipopeptide (surfactin), large amount of foam was produced by aeration. This resulted in the carryover of cells to the outside of the fermentor, which leads to the significant loss of cells. Instead of using cell-toxic antifoaming agents, low amount of hydrogen peroxide was added. Catalase produced by cells converted hydrogen peroxide into oxygen and water. Also addition of corn oil as an oxygen vector as well as antifoaming agent was attempted. In addition, Ca-stearate, a metal soap, was added to enhance the antifoam activity of com oil. These methods could prevent the foaming significantly and maintained high dissolved oxygen in spite of lower aeration and agitation. Using these methods, high cell density, could be achieved with increased lipopeptide productivity. In conclusion to produce an effective biological control agent for soil-borne infectious disease, following strategies were attempted i) effective screening of antagonist by including surface tension as an important decision factor ii) identification of antifungal compound produced from the isolated strain iii) novel oxygenation by $H_2O_2-catalase$ with vegetable oil for antifungal lipopeptide production.

• Journal of Applied Biological Chemistry
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• v.54 no.1
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• pp.1-6
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• 2011

${\gamma}$-PGA(poly-${\gamma}$-glutamic acid) is an unusual anionic polypeptide that is made of D- and L-glutamic acid units connected by amide linkages between ${\alpha}$-amino and ${\gamma}$-carboxylic acid groups. ${\gamma}$-PGA has been isolated from many kinds of organisms. Many Bacillus strains produce ${\gamma}$-PGA as a capsular material of an extracellular viscous material. It is safe for eating as a viscosity element of fermented soybean products such as Chungkookjang and Natto. It is biodegradable, edible and nontoxic toward humans and the environment and its molecular weight varies from ten thousand to several hundred thousand depending on the kinds of strains used. Therefore, potential applications of ${\gamma}$-PGA and its derivatives have been of interest in the past few years in a broad range of industrial fields such as food, cosmetics, medicine, water-treatment, etc. In this study, a bacterium, Bacillus subtilis GS-2 isolated from the Korean traditional seasoning food, Chungkookjang could produce a large amount of ${\gamma}$-PGA with high productivity and had a simple nutrient requirement. Based on carbon utilization pattern and partial 16S rRNA sequence analysis, the GS-2 strain was identified as B. subtilis. The determination of purified ${\gamma}$-PGA was confirmed with thin layer chromatography (TLC), high performance liquid chromatography (HPLC), fourier transform infrared (FT-IR) spectra, and $^1H$-nuclear magnetic resonance ($^1H$-NMR) spectroscopy.

• Journal of Ginseng Research
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• v.32 no.4
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• pp.291-299
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• 2008

The fresh ginseng roots were extracted in aqueous methanol (MeOH), and the obtained extracts were partitioned using ethyl acetate (EtOA), n-butanol (n-BuOH), and water, successively. The repeated silica gel column chromatography for n-BuOH fraction afforded a purified ginsenoside $Rg_1$. The physico-chemical, spectroscopic and chromatographic data of ginsenoside $Rg_1$, such as crystallization characteristics, melting point, specific rotation, infrared spectrometry (IR) data, fast atom bombardment/mass spectrometry (FAB/MS) data, nuclear magnetic resonance (NMR) data, retention factor (Rf) in thin layer chromatography (TLC) experiment, and retention time (r.t.) in HPLC analysis, were measured and compared with those reported in literatures. Especially, the previous literatures reported different data for ginsenoside $Rg_1$ in the $^{1}H-$ and $^{13}C$-NMR experiments. This paper gives the exactly assigned NMR data through 2D-NMR experiments, such as $^{1}H-^{1}H$ correlation spectroscopy (COSY), hetero nuclear single quantum correlation (HSQC), and hetero nuclear multiple bond connectivity (HMBC).