• 제목/요약/키워드: Spectral modeling

검색결과 233건 처리시간 0.023초

Mastitis Detection by Near-infrared Spectra of Cows Milk and SIMCA Classification Method

  • Tsenkova, R.;Atanassova, S.
    • 한국근적외분광분석학회:학술대회논문집
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    • 한국근적외분광분석학회 2001년도 NIR-2001
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    • pp.1248-1248
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    • 2001
  • Mastitis is a major problem for the global dairy industry and causes substantial economic losses from decreasing milk production and considerable compositional changes in milk, reducing milk quality. The potential of near infrared (NIR) spectroscopy in the region from 1100 to 2500nm and chemometric method for classification to detect milk from mastitic cows was investigated. A total of 189 milk samples from 7 Holstein cows were collected for 27 days, consecutively, and analyzed for somatic cells (SCC). Three of the cows were healthy, and the rest had mastitis periods during the experiment. NIR transflectance milk spectra were obtained by the InfraAlyzer 500 spectrophotometer in the spectral range from 1100 to 2500nm. All samples were divided into calibration set and test set. Class variable was assigned for each sample as follow: healthy (class 1) and mastitic (class 2), based on milk SCC content. The classification of the samples was performed using soft independent modeling of class analogy (SIMCA) and different spectral data pretreatment. Two concentration of SCC - 200 000 cells/ml and 300 000 cells/ml, respectively, were used as thresholds fer separation of healthy and mastitis cows. The best detection accuracy was found for models, obtained using 200 000 cells/ml as threshold and smoothed absorbance data - 98.41% from samples in the calibration set and 87.30% from the samples in the independent test set were correctly classified. SIMCA results for classes, based on 300 000 cells/ml threshold, showed a little lower accuracy of classification. The analysis of changes in the loading of first PC factor for group of healthy milk and group of mastitic milk showed, that separation between classes was indirect and based on influence of mastitis on the milk components. The accuracy of mastitis detection by SIMCA method, based on NIR spectra of milk would allow health screening of cows and differentiation between healthy and mastitic milk samples. Having SIMCA models, mastitis detection would be possible by using only DIR spectra of milk, without any other analyses.

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생물공정 모니터링 및 모델링을 위한 2차원 형광스펙트럼의 다변량 분석 (Chemometric Analysis of 2D Fluorescence Spectra for Monitoring and Modeling of Fermentation Processes)

  • 강태형;손옥재;김춘광;정상욱;이종일
    • KSBB Journal
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    • 제21권1호
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    • pp.59-67
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    • 2006
  • 본 연구에서는 2차원 형광스펙트럼의 PCA 분석을 통하여 발효 공정을 모니터링하고 PCR과 PLS과 같은 다변량 분석기법을 이용하여 공정을 모델링하였다. 재조합 대장균 E. coli 와 효모 S.cerevisiae의 발효 공정 중에 얻어진 많은 양의 2차원 형광스펙트럼 자료는 우선 PCA를 통해 축소된다. 그리고 PCA에서 주성분점수와 적재 산점도는 발효 공정의 정성적 경향을 묘사하기 위해 사용되었다. 또한, PCR과 PLS는 2차원 형광스펙트럼의 분석을 위해 사용되었으며 PLS모델이 보정과 예측 능력에서 PCR모델보다 조금 더 우수한 성능을 나타냈다. 따라서 2차원 형광스펙트럼 자료를 이용하여 생물공정을 모델링 하고자 할 때는 PCR 방법보다는 PLS 방법을 사용하는 것이 유리할 것이다.

On Mathematical Representation and Integration Theory for GIS Application of Remote Sensing and Geological Data

  • Moon, Woo-Il M.
    • 대한원격탐사학회지
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    • 제10권2호
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    • pp.37-48
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    • 1994
  • In spatial information processing, particularly in non-renewable resource exploration, the spatial data sets, including remote sensing, geophysical and geochemical data, have to be geocoded onto a reference map and integrated for the final analysis and interpretation. Application of a computer based GIS(Geographical Information System of Geological Information System) at some point of the spatial data integration/fusion processing is now a logical and essential step. It should, however, be pointed out that the basic concepts of the GIS based spatial data fusion were developed with insufficient mathematical understanding of spatial characteristics or quantitative modeling framwork of the data. Furthermore many remote sensing and geological data sets, available for many exploration projects, are spatially incomplete in coverage and interduce spatially uneven information distribution. In addition, spectral information of many spatial data sets is often imprecise due to digital rescaling. Direct applications of GIS systems to spatial data fusion can therefore result in seriously erroneous final results. To resolve this problem, some of the important mathematical information representation techniques are briefly reviewed and discussed in this paper with condideration of spatial and spectral characteristics of the common remote sensing and exploration data. They include the basic probabilistic approach, the evidential belief function approach (Dempster-Shafer method) and the fuzzy logic approach. Even though the basic concepts of these three approaches are different, proper application of the techniques and careful interpretation of the final results are expected to yield acceptable conclusions in cach case. Actual tests with real data (Moon, 1990a; An etal., 1991, 1992, 1993) have shown that implementation and application of the methods discussed in this paper consistently provide more accurate final results than most direct applications of GIS techniques.

Baum-Welch 학습법을 이용한 HMM 기반 대역폭 확장법 (HMM-Based Bandwidth Extension Using Baum-Welch Re-Estimation Algorithm)

  • 송근배;김석호
    • 한국음향학회지
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    • 제26권6호
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    • pp.259-268
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    • 2007
  • 본 논문에서는 HMM 기반 통계적인 대역폭 확장(Bandwidth Extension, BWE) 방법의 개선에 대해 다룬다. 이를 위해 우선, HMM 모델 학습을 위한 기존의 Jax의 학습법과 일반적인 Baum-Welch 학습법의 관계를 비교 검토하고, Jax의 학습법의 한계점 및 문제점을 검토한다. 그리고 이를 바탕으로 Baum-Welch학습법을 이용한 새로운 HMM 기반 BWE 방법을 제시한다. 결론적으로, Baum-Welch 학습법은 Jax의 학습법의 일반화된 형태로 볼 수 있으며, 보다 유연하고 적응적인 학습능력을 가진 알고리즘임을 알 수 있다. 따라서 학습 데이터에 대한 보다 정확한 HMM 모델링이 가능하며 아울러, 이와 같이 개선된 HMM 모델을 활용함으로써 BWE 시스템의 성능향상을 가져 올 수 있었다. 실험결과에 의하면, 제시된 새로운 방법이 기존의 Jax의 방법에 비해 실험의 모든 경우에서 우수한 성능을 보임을 알 수 있다. 주어진 실험조건하에서 근제곱평균(root-mean-square, RMS) 로그 스펙트럴 왜곡(Log Spectral Distortion, LSD) 값이 전체적으로 평균 0.52dB 그리고, 최소 0.31dB에서 최대 0.8dB까지 개선되었다.

국내 유도분극 탐사의 연구동향 (Research Trends in Induced Polarization Exploration in Korea)

  • 박삼규
    • 지구물리와물리탐사
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    • 제24권4호
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    • pp.202-208
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    • 2021
  • 유도분극(Induced Polarization, IP)탐사가 1973년에 국내 학술지에 처음 소개되었으며, 그 이후 석탄 및 금속광상탐사에 응용되기 시작하면서 대학 및 연구기관에서 유한요소법에 의한 IP 모델링 연구와 인공모형 시료의 유도분극반응 측정 기술이 개발되었다. 1980년 중반에 광대역유도분극(SIP) 탐사기가 국내에 도입되면서 실내 측정 및 해석 기술이 개발되었으나 자원산업의 쇠퇴와 더불어 광상탐사 현장에서 널리 활용되지는 못했다. 1990년대에는 IP탐사가 황화광물의 열수광상 및 벤토나이트 광화대 조사와 해수 침입에 의한 지하수 오염지역에 적용된 사례가 있다. 2000년대 들어서면서 IP탐사의 3차원 역해석 기술이 개발되고, 국내외 광물자원확보를 위한 정밀물리탐사 기술이 요구되면서 암석 시료의 SIP 측정 및 현장 탐사 기술이 확보되었으며, 해남지역 금은광상의 광화대 탐사에 적용한 결과 SIP탐사 기술이 황화광물을 포함하고 있는 금속광상탐사에 유용함이 입증되었다. 이러한 IP 탐사는 리튬, 코발트, 니켈과 같은 첨단 산업의 핵심광물 탐사에서 효과적일 것으로 여겨지고, 또한 환경오염과 지반조사 분야에서도 유용할 것으로 기대된다.

DISEASE DIAGNOSED AND DESCRIBED BY NIRS

  • Tsenkova, Roumiana N.
    • 한국근적외분광분석학회:학술대회논문집
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    • 한국근적외분광분석학회 2001년도 NIR-2001
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    • pp.1031-1031
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    • 2001
  • The mammary gland is made up of remarkably sensitive tissue, which has the capability of producing a large volume of secretion, milk, under normal or healthy conditions. When bacteria enter the gland and establish an infection (mastitis), inflammation is initiated accompanied by an influx of white cells from the blood stream, by altered secretory function, and changes in the volume and composition of secretion. Cell numbers in milk are closely associated with inflammation and udder health. These somatic cell counts (SCC) are accepted as the international standard measurement of milk quality in dairy and for mastitis diagnosis. NIR Spectra of unhomogenized composite milk samples from 14 cows (healthy and mastitic), 7days after parturition and during the next 30 days of lactation were measured. Different multivariate analysis techniques were used to diagnose the disease at very early stage and determine how the spectral properties of milk vary with its composition and animal health. PLS model for prediction of somatic cell count (SCC) based on NIR milk spectra was made. The best accuracy of determination for the 1100-2500nm range was found using smoothed absorbance data and 10 PLS factors. The standard error of prediction for independent validation set of samples was 0.382, correlation coefficient 0.854 and the variation coefficient 7.63%. It has been found that SCC determination by NIR milk spectra was indirect and based on the related changes in milk composition. From the spectral changes, we learned that when mastitis occurred, the most significant factors that simultaneously influenced milk spectra were alteration of milk proteins and changes in ionic concentration of milk. It was consistent with the results we obtained further when applied 2DCOS. Two-dimensional correlation analysis of NIR milk spectra was done to assess the changes in milk composition, which occur when somatic cell count (SCC) levels vary. The synchronous correlation map revealed that when SCC increases, protein levels increase while water and lactose levels decrease. Results from the analysis of the asynchronous plot indicated that changes in water and fat absorptions occur before other milk components. In addition, the technique was used to assess the changes in milk during a period when SCC levels do not vary appreciably. Results indicated that milk components are in equilibrium and no appreciable change in a given component was seen with respect to another. This was found in both healthy and mastitic animals. However, milk components were found to vary with SCC content regardless of the range considered. This important finding demonstrates that 2-D correlation analysis may be used to track even subtle changes in milk composition in individual cows. To find out the right threshold for SCC when used for mastitis diagnosis at cow level, classification of milk samples was performed using soft independent modeling of class analogy (SIMCA) and different spectral data pretreatment. Two levels of SCC - 200 000 cells/$m\ell$ and 300 000 cells/$m\ell$, respectively, were set up and compared as thresholds to discriminate between healthy and mastitic cows. The best detection accuracy was found with 200 000 cells/$m\ell$ as threshold for mastitis and smoothed absorbance data: - 98% of the milk samples in the calibration set and 87% of the samples in the independent test set were correctly classified. When the spectral information was studied it was found that the successful mastitis diagnosis was based on reviling the spectral changes related to the corresponding changes in milk composition. NIRS combined with different ways of spectral data ruining can provide faster and nondestructive alternative to current methods for mastitis diagnosis and a new inside into disease understanding at molecular level.

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Protein molecular structure, degradation and availability of canola, rapeseed and soybean meals in dairy cattle diets

  • Tian, Yujia;Zhang, Xuewei;Huang, Rongcai;Yu, Peiqiang
    • Asian-Australasian Journal of Animal Sciences
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    • 제32권9호
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    • pp.1381-1388
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    • 2019
  • Objective: The aims of this study were to reveal the magnitude of the differences in protein structures at a cellular level as well as protein utilization and availability among soybean meal (SBM), canola meal (CM), and rapeseed meal (RSM) as feedstocks in China. Methods: Experiments were designed to compare the three different types of feedstocks in terms of: i) protein chemical profiles; ii) protein fractions partitioned according to Cornell Net Carbohydrate and Protein System; iii) protein molecular structures and protein second structures; iv) special protein compounds-amino acid (AA); v) total digestible protein and energy values; vi) in situ rumen protein degradability and intestinal digestibility. The protein second structures were measured using FT/IR molecular spectroscopy technique. A summary chemical approach in National Research Council (NRC) model was applied to analyze truly digestible protein. Results: The results showed significant differences in both protein nutritional profiles and protein structure parameters in terms of ${\alpha}-helix$, ${\beta}-sheet$ spectral intensity and their ratio, and amide I, amide II spectral intensity and their ratio among SBM, CM, and RSM. SBM had higher crude protein (CP) and AA content than CM and RSM. For dry matter (DM), SBM, and CM had a higher DM content compared with RSM (p<0.05), whereas no statistical significance was found between SBM and CM (p = 0.28). Effective degradability of CP and DM did not demonstrate significant differences among the three groups (p>0.05). Intestinal digestibility of rumen undegradable protein measured by three-step in vitro method showed that there was significant difference (p = 0.05) among SBM, CM, and RSM, which SBM was the highest and RSM was the lowest with CM in between. NRC modeling results showed that digestible CP content in SBM was significantly higher than that of CM and RSM (p<0.05). Conclusion: This study suggested that SBM and CM contained similar protein value and availability for dairy cattle, while RSM had the lowest protein quality and utilization.

물리적 특성 모델링에 기반한 라이팅 환경의 랜더링 기법 (Rendering Method of Light Environment Based on Modeling of Physical Characteristic)

  • 이명영;이철희;하영호
    • 대한전자공학회논문지SP
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    • 제43권6호
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    • pp.46-56
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    • 2006
  • 본 논문에서는 라이팅 환경을 구성하고 있는 광원과 물체의 광학적인 특성을 모델링하여 특정 위치의 관찰자의 시야에 들어오는 3차원 영상을 추정하는 알고리즘을 제안한다. 이전의 논문에서 제안했던 기법을 개선하고, 실제의 자동차 리어램프를 실험에 적용하여 추정한 빛자극과 측정된 빛자극을 비교하여 검증하였다. 랜더링 알고리즘으로는 컴퓨터 그래픽에서 많이 사용되고 있는 광선추적기법을 이용하고, 정확한 실사영상(realistic image)을 재현하기 위하여 물체의 물리적 특성을 반영하는 분광분포를 고려하였다. 물체의 빛 표면반사 및 투과특성과 광원의 빛방출 기하특성을 모델링하여 시점으로 들어오는 빛에너지 추정의 정확도를 개선하였다. 또한 추정된 빛에너지를 인간시각이 느끼는 동일한 색자극으로 디스플레이에 표시할 수 있도록 모니터특성화기법을 적용하여 실사영상에 근접한 영상을 재현하였다.

Near-Infrared Spectroscopy and Modeling of Luminous Blue Variables

  • 김현정;구본철;박용선
    • 천문학회보
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    • 제36권2호
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    • pp.152.1-152.1
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    • 2011
  • We report preliminary results of long-slit near-infrared (NIR) spectroscopy of Luminous Blue Variables (LBVs) with moderate resolution of R ~ 2400. We obtained Jshort (1.04-1.26 micron) and Ks (2.02-2.31 micron) band spectra of 4 LBVs and 3 LBV candidates in Southern hemisphere using IRIS2, infrared imager and spectrograph, mounted on the 4-m Anglo-Australian Telescope. All targets are fairly bright in NIR so that we can obtain high signal-to-noise ratio for clear line detection and modeling. They are also widely distributed in the HR diagram so that we can compare the spectral properties of LBVs in different temperature and luminosity ranges. Among them, we present the results of two well-known LBVs AG Car and HR Car. Their spectra show similar properties with hydrogen, He I, and metallic lines such as Fe II and Mg II, most of them in emission. We discuss, in particular, the He I 1.083 micron lines formed in stellar wind because these two LBVs show large variation in their He I line intensities, compared to previous studies. Since the He I 1.083 line is known to be anticorrelated with the photometric variation of LBVs, strong line intensities with P-Cygni profiles in both stars indicate that they are now near the visual minimum phase. We model the obtained spectra using non-LTE atmosphere code CMFGEN of Hillier (1998) to derive stellar parameters such as wind velocity and mass loss rate, and discuss the long-term variability of stellar parameters of these LBVs. deduced from our otometric solution.

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복소 전기비저항 및 3차원 지질모델링을 이용한 모이산 포텐셜 지도 구축 (Potential Mapping of Moisan area Using SIP and 3D Geological Modeling)

  • 박계순;박삼규;손정술;김창렬;조성준
    • 지구물리와물리탐사
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    • 제17권4호
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    • pp.209-215
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    • 2014
  • 광물자원탐사 기술 개발의 일환으로 광대역 유도분극 탐사 자료를 활용한 광체의 부존 가능성 평가를 위해 모이산 지역에 대한 3차원 포텐셜 지도 구축 연구가 수행되었다. 현장 탐사 결과를 지질모델링 영역별로 해석하여 광체 영역에서 나타나는 위상 및 전기비저항 값의 분포 특성을 해석하였으며, 이를 바탕으로 모이산 광체에 대한 부존 잠재성 평가를 수행하였다. 잠재성 평가 결과 기존에 확인된 광체 영역에서는 높은 부존 가능성이 확인되었으며, 최근 시추를 통해 확인된 일부 광체 영역에서도 주변부에 비해 잠재성이 높은 것으로 해석되어 신뢰도가 높음을 확인하였다. 광체 분포특성에 따라 효과적으로 측선 설계가 이루어지고 보다 조밀한 광대역 유도분극 탐사 자료를 얻을 경우 이번 연구를 통해 습득한 해석 기술은 광체 평가에 효율적으로 적용될 수 있을 것으로 판단된다.