• Journal of Applied Biological Chemistry
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• 제58권3호
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• pp.237-240
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• 2015

이팝나무(Chionanthus retusus Lindl. & Paxton) 꽃은 실온에서 80% MeOH 수용액으로 추출하고 이 추출물을 EtOAC 분획, n-BuOH 분획, $H_2O$ 분획으로 나누었다. EtOAc 분획에 대하여 silica gel 및 ODS column chromatography를 반복 실시하여 4종의 화합물을 분리 및 정제하였다. nuclear magnetic resonance, infrared, 및 Electronic ionization mass spectrometer 등을 해석하여, ursolic acid (1), corosolic acid (2), ${\beta}$-sitosterol (3), 그리고 daucosterol (4)로 구조동정 하였다. 분리한 4종의 화합물은 이팝나무 꽃으로부터 이번 실험에서 처음 분리 되었다.

• 천문학회보
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• 제37권2호
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• pp.141.1-141.1
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• 2012

CIBER (Cosmic Infrared Background ExpeRiment) is a sounding-rocket borne experiment which is designed to find the evidence of the First stars (Pop.III stars) in the universe. They are expected to be formed between the recombination era at z ~ 1100 and the most distant quasar (z ~ 8). They have never been directly detected due to its faintness so far, but can be observed as a background radiation at around $1{\mu}m$ which is called the Cosmic Near-Infrared Background (CNB). The CIBER is successfully launched on July 10, 2010 at White Sands Missile Range, New Mexico, USA. It consists of three kinds of instruments. One of them is a LRS (Low Resolution Spectrometer) which is a refractive telescope of 5.5 cm aperture with spectral resolution of 20 ~ 30 and wavelength coverage of 0.7 to $2.0{\mu}m$ to measure the spectrum of the CNB. Since LRS detects not only CNB but also stellar components, we can study their spectral features with the broad band advantage especially at around $1{\mu}m$ which is difficult at ground observations because of the atmospheric absorption by water vapor. I identified around 300 stars from observed six fields. If we can classify their spectral types with SED fitting, we can study their physical conditions of the stellar atmosphere as well as making a stellar catalogue of continuous stellar spectrum.

• 한국환경복원기술학회지
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• 제25권5호
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• pp.43-57
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• 2022

This study aims to classify forest fire-affected areas, identify forest types by the intensity of forest fire damage using multi-time Landsat-satellite images before and after forest fires and to analyze the effects of artificial restoration sites and natural restoration sites. The difference in the values of the Normalized Burned Ratio(NBR) before and after forest fire damage not only maximized the identification of forest fire affected and unaffected areas, but also quantified the intensity of forest fire damage. The index was also used to confirm that the higher the intensity of forest fire damage in all forest fire-affected areas, the higher the proportion of coniferous forests, relatively. Monitoring was conducted after forest fires through Normalized Difference Vegetation Index(NDVI), an index suitable for the analysis of effects by restoration type and the NDVI values for artificial restoration sites were found to no longer be higher after recovering the average NDVI prior to the forest fire. On the other hand, the natural restoration site witnessed that the average NDVI value gradually became higher than before the forest fires. The study result confirms the natural resilience of forests and these results can serve as a basis for decision-making for future restoration plans for the forest fire affected areas. Further analysis with various conditions is required to improve accuracy and utilization for the policies, in particular, spatial analysis through forest maps as well as review through site checks before and immediately after forest fires. More precise analysis on the effects of restoration will be available based on a long term monitoring.

• 농업과학연구
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• 제50권4호
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• pp.675-696
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• 2023

Terpenoids, also referred to as terpenes, are a large family of naturally occurring chemical compounds present in the essential oils extracted from medicinal plants. In this study, a nondestructive methodology was created by combining ATR-FT-IR (attenuated total reflectance-Fourier transform infrared), and Raman spectroscopy for the terpenoids assessment in medicinal plants essential oils from ten different geographical locations. Partial least squares regression (PLSR) and support vector regression (SVR) were used as machine learning methodologies. However, a deep learning based model called as one-dimensional convolutional neural network (1D CNN) were also developed for models comparison. With a correlation coefficient (R²) of 0.999 and a lowest RMSEP (root mean squared error of prediction) of 0.006% for the prediction datasets, the SVR model created for FT-IR spectral data outperformed both the PLSR and 1 D CNN models. On the other hand, for the classification of essential oils derived from plants collected from various geographical regions, the created SVM (support vector machine) classification model for Raman spectroscopic data obtained an overall classification accuracy of 0.997% which was superior than the FT-IR (0.986%) data. Based on the results we propose that FT-IR spectroscopy, when coupled with the SVR model, has a significant potential for the non-destructive identification of terpenoids in essential oils compared with destructive chemical analysis methods.

• 한국정보과학회논문지:정보통신
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• 제37권5호
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• pp.396-402
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• 2010

지능형 주택의 상황인지 서비스를 위해서는 거주자의 현재 위치를 파악하는 것이 필수적이다. 이를 위해 본 논문에서는 사용자에게 별도의 장치 소지를 요구하지 않으며 특정 운에 대한 출/입 행동과 같은 위치 이동과 그 사람이 누구인지를 식별하는 센서 네트워크 시스템을 제안한다. 새롭게 개발된 센서 노드는 선행 연구 결과[1]의 짧은 동작 수명 문제를 해결한 것으로 2개의 초전형(PIR) 센서와 초음파 센서, 그리고 2.4 GHz 문선 통신 모듈로 구성된다. 제안된 구성원의 식별 방법은 초음파 센서를 이용한 구성원의 키 차이를 이용한다. 거주자의 위치 이동의 감지는 출/입 행동의 감지에 기초하며 이와 같은 출/입 행동 감지는 2개의 PIR 센서의 감지 순서에 기초하여 이루어진다. 전체 센서 네트워크의 구성은 각 센서 노드가 수신 노드와 과 1대 1로 연결되는 별 형태로 이루어져 있다. 제안된 시스템은 본보기주택에 설치되어 3명의 사용자를 대상으로 실험되었고 그 결과 완벽한 출/입 행동 감지와 평균 81.3%의 구성원 식별 성능을 얻었다.

• Asian Pacific Journal of Cancer Prevention
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• 제16권18호
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• pp.8619-8623
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• 2016

Background: Breast cancer is a common disorder in women, constituting one of the main causes of death all over the world. The purpose of this study was to determine the diagnostic value of the breast tissue diseases by the help of thermography. Materials and Methods: In this paper, we applied non-contact infrared camera, INFREC R500 for evaluating the capabilities of thermography. The study was conducted on 60 patients suspected of breast disease, who were referred to Imam Khomeini Imaging Center. Information obtained from the questionnaires and clinical examinations along with the obtained diagnostic results from ultrasound images, biopsies and thermography, were analyzed. The results indicated that the use of thermography as well as the asymmetry technique is useful in identifying hypoechoic as well as cystic masses. It should be noted that the patient should not suffer from breast discharge. Results: The accuracy of asymmetry technique identification is respectively 91/89% and 92/30%. Also the accuracy of the exact location of identification is on the 61/53% and 75%. The approach also proved effective in identifying heterogeneous lesions, fibroadenomas, and intraductal masses, but not ISO-echoes and calcified masses. Conclusions: According to the results of the investigation, thermography may be useful in the initial screening and supplementation of diagnostic procedures due to its safety (its non-radiation properties), low cost and the good recognition of breast tissue disease.

• 한국산학기술학회논문지
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• 제18권5호
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• pp.557-564
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• 2017

대한민국 군의 K 계열 전차에 장착되어 있는 열영상장비의 목적은 시계가 제한된 환경에서 외부의 적외선 영역의 정보를 인간이 인지할 수 있는 시각 정보로 변환하는 것이다. 열영상장비의 시계, 배율, 분해능, 변조전달함수, 잡음등가온도차, 최소분해가능온도차 등의 지표 중에서 최소 분해 가능 온도차(MRTD)는 공간주파수와 온도분해능을 복합적으로 표현할 수 있기 때문에, 열영상장비의 성능 표현에 있어 가장 중요한 파라메터이다. 그러나 NATO의 MRTD 표준 측정 방법은 많은 주관적인 요소를 포함하고 있다. 즉, 측정자의 정신 상태, 시력 등의 차이와 측정환경에 따라 측정 결과의 오차가 발생하므로 MRTD의 측정결과는 안정적이지 못하다. 따라서 본 논문에서는 정성적인 MRTD 측정 방법을 gary scale을 바탕으로 이미지 연산을 통한 정량적인 지표로 변환하였다. 흑상과 백상의 Gray scale 차이의 평균을 최소분해가능온도로 변환하여, 국방규격서에서 요구하는 성능요구조건의 충족여부를 판단할 수 있다. 또한 gray scale은 MRTD의 탐지/인지/식별의 판별기준으로 활용할 수 있다. 전차에 열영상장비가 탑재되어 작전을 수행할 때의 탐지 가능 거리를 안개, 폭우, 맑은 날씨 등의 다양한 환경조건에 따라 분석하였다.

• 한국초지조사료학회지
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• 제40권4호
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• pp.259-264
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• 2020

본 연구는 근적외선분광법을 이용하여 국내에서 재배중인 수수×수단그라스 교잡종 품 판별 가능성을 검토하고자 수행되었다. 근적외선분광기를 이용하여 수수×수단그라스 교잡종 종자를 가시파장 대역대 (680 - 1,099 nm), NIRS 파장 대역대 (1,100 - 2,500 nm) 및 NIRS 전체 파장 대역대 (680 - 2,500 nm)로 구분하여 스펙트라를 얻은 후 1차 미분과 8 nm gap으로 수 처리를 수행하였으며 부분최소자승 (PLS) 회귀분석법을 통해 품종판별 검량식을 개발하고 판별 정확성을 검증하였다. 수수×수단그라스 교잡종품종 판별의 정확성은 NIR파장대역에서 SECV 8.44 그리고 R2CV 0.89로 가장 판별 정확성이 낮았으며 NIRS 전체 파장대역에서 SECV 7.88 그리고 R2CV 0.90로 가장 높은 판별 정확성을 나타내었다. 파장대역별 예측 정확성은 NIR 파장대역 (1,100 - 2,500 nm)이 가장 우수하였으며, 교차검증오차 (SECV) 8.44에서 예측오차 (SEP) 12.03로 높아졌으며 가시영역대 (680 - 1,099)는 SECV 8.23에서 SEP 12.51로 높아졌다. Discrimination equation 분석법에 의한 NIRS 전체 파장대역별 수수×수단그라스 교잡종 종자의 판별 결과는 품종간에 판별 정확성의 차이가 크게 나타났으며 1, 2, 4 그리고 8번 품종 (G-7, BMR Gold II, Honey chew and SX-17)에서는 100 %의 정확성으로 가장 높게 나타났다. 따라서 NIRS를 이용한 수수×수단그라스 교잡종 종자의 판별분석이 가능할 것으로 판단되었다.

• Journal of Microbiology
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• 제45권6호
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• pp.499-504
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• 2007

A new antagonistic strain of actinomycete, designated AP19-2, was isolated from the feces of giant pandas inhabiting the Foping National Nature Reserve in China. Cultural characteristic studies strongly suggested that this strain is a member of the genus Streptomyces. The nucleotide sequence of the 16S rRNA gene of strain AP19-2 evidenced profound similarity (97-99 %) with other Streptomyces strains. Two pure active molecules were isolated from a fermentation broth of Streptomyces sp. strain AP19-2 via extraction, concentration, silica gel G column chromatography, and HPLC. The chemical structures of the two related compounds (referred to as chromomycin $A_2$ and chromomycin $A_3$) were established on the basis of their Infrared spectra (IR), High Resolution Electrospray Ionization Mass Spectrometry (HR-ESI-MS), and Nuclear Magnetic Resonance (NMR) data, and by comparison with published data.

• Advances in environmental research
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• 제9권3호
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• pp.215-232
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• 2020

Crude oils are essential source of energy. It is majorly found in geographical locations beneath the earth's surface and crude oil is the main factor for the economic developments in the world. Natural crude oil contains unrefined petroleum composed of hydrocarbons of various molecular weights and it contains other organic materials like aromatic compounds, sulphur compounds, and many other organic compounds. These hydrocarbons are rapidly getting degraded by biosurfactant producing microorganisms. The present study deals with the isolation, purification, and characterization of biosurfactant producing microorganism from oil-contaminated soil. The ability of the microorganism producing biosurfactant was investigated by well diffusion method, drop collapse test, emulsification test, oil displacement activity, and blue agar plate method. The isolate obtained from the oil contaminated soil was identified as Bacillus subtilis. The identification was done by microscopic examinations and further characterization was done by Biochemical tests and 16SrRNA gene sequencing. Purification of the biosurfactant was performed by simple liquid-liquid extraction, and characterization of extracted biosurfactants was done using Fourier transform infrared spectroscopy (FTIR). The degradation of crude oil upon treatment with the partially purified biosurfactant was analyzed by FTIR spectroscopy and Gas-chromatography mass spectroscopy (GC-MS).