• Journal of Radiation Protection and Research
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• 제40권1호
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• pp.17-24
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• 2015

To improve accuracy of dose calculation on kilovoltage cone beam computed tomography (kV CBCT) images, a custom-made phantom was fabricated to acquire an accurate CT number to electron density curve by full scatter of cone beam x-ray. To evaluate the dosimetric accuracy, 9 volumetric modulated arc therapy (VMAT) plans for head and neck (HN) cancer and 9 VMAT plans for lung cancer were generated with an anthropomorphic phantom. Both CT and CBCT images of the anthropomorphic phantom were acquired and dose-volumetric parameters on the CT images with CT density curve (CTCT), CBCT images with CT density curve ($CBCT_{CT}$) and CBCT images with CBCT density curve ($CBCT_{CBCT}$) were calculated for each VMAT plan. The differences between $CT_{CT}$ vs. $CBCT_{CT}$ were similar to those between $CT_{CT}$ vs. $CBCT_{CBCT}$ for HN VMAT plans. However, the differences between $CT_{CT}$ vs. $CBCT_{CT}$ were larger than those between $CT_{CT}$ vs. $CBCT_{CBCT}$ for lung VMAT plans. Especially, the differences in $D_{98%}$ and $D_{95%}$ of lung target volume were statistically significant (4.7% vs. 0.8% with p = 0.033 for $D_{98%}$ and 4.8% vs. 0.5% with p = 0.030 for $D_{95%}$). In order to calculate dose distributions accurately on the CBCT images, CBCT density curve generated with full scatter condition should be used especially for dose calculations in the region of large inhomogeneity.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1266-1266
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• 2001

Pasture composition, an important attribute determining sward condition and value, is normally assessed by hand separation, drying and measuring weight contribution of each species in the mixture. This is a tedious, time and labour consuming procedure. NIRS has demonstrated the potential for predicting botanical composition of swards, but most of the work has been carried out on dry samples. The aim of this work was to evaluate the feasibility of developing NIR models for predicting the white clover and ryegrass content in fresh or dry mixtures artificially prepared from pure samples of both species. Mixtures from pure stands of white clover(Trifolium repens) and perennial ryegrass (Lolium perenne) were prepared with different proportions (0 to 100%) of each species (fresh weight). A total of 55 samples were made (11 mixtures,5 cuts). Spectra (400 to 2500 nm) were taken from fresh chopped (rectangular cuvettes, transport sample module) samples, in a NIR Systems 6500 scanning monochromator controlled by the software NIRS 3 (Infrasoft International), which was also utilized for calibration development. Different math treatments (derivative order, subtraction gap and smooth segment) and a scatter correction treatment of the spectra (SNV and Detrend) were tested. Equations were developed by modified partial least squares. Prediction accuracy evaluated by cross-validation, showed that percentage of clover or ryegrass, as contribution in dry weight, can be successfully percentage of clover or ryegrass, as contribution in dry weight, can be successfully predicted either on fresh or dried samples, with equations developed by different math treatments. Best equations for fresh samples were developed including a first, second, or third derivative, whereas for dry samples best equations included a second or third derivative. Standard errors of ross validation were about 6% for fresh and 3.6% for dry samples, Coefficient of determination of cross validation (1-VR) were over 0.95 times the value of SECV for fresh samples and over 8 times the value of SECV for dry samples. Scatter correction (SNV and Detrend) in general improved prediction accuracy. It is concluded more precise on dried and ground samples, it can be used with an acceptable error level and less time and labour, on fresh samples.

• 한국토양비료학회지
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• 제37권4호
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• pp.259-265
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• 2004

사과의 영양진단에서 사과잎 분석을 신속히 하기 위한 방법을 모색하기 위해 생잎과 건조잎을 이용해 근적의 스펙트럼을 측정하고 이를 질소 함량과의 최적의 상관관계를 도출하기 위해 부분소자승(PLS)과 주성분회귀(PCR)과 같은 다변량 분석법을 이용하여 비파괴 검량식을 작성하였다. 또한 검량식 작성에서 비파괴 측정 정확도를 향상시키기 위하여 smoothing, mean normalization, multiplicative scatter correction (MSC). derivative 등의 다양한 데이터 전처리 조작을 수행하여 정확도 향상 가능성을 조사하였다. 사과 건조잎의 비파괴 측정 가능성을 조사한 결과 PLS-1 모델에서 Norris first derivate하였을 태 RMSEP가 $0.6999g\;kg^{-1}$ 로 가장 좋았으며, 생잎은 Savitzky-Golay first derivate하였을 때에 RMSEP 가 $1.202g\;kg^{-1}$으로 가장 좋았다. 건조잎의 PCR 모델은 mean normalization 처리 후 Savitzky-Golay first derivative하였을 때가 RMSEP 가 $0.553g\;kg^{-1}$, 이었으며 생잎에서도 RMSEP는 $1.047g\;kg^{-1}$로 나타났다. 이와 같은 견과로서 사과의 생잎과 건조잎의 분석이 근적외분석기술에 의해 가능할 것으로 판단된다.

• Radiation Oncology Journal
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• 제7권2호
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• pp.279-285
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• 1989

Tatcher식에 의하여 조직최대선량비와 깊이선량을 6MV X-선의 중심축상에서 측정하였다. 쐐기형 조사야에 있어서 깊이, 조사야 및 쐐기의 두께 등이 증가할수록 깊이선량은 개방 조사야에 비하여 크기가 증가하였다. 그러나 쐐기형 조사야에 있어서 조직산란보정 계수는 개방 조사야에 비하여 그 차이가 $1\%$ 미만이었다. 두 조사야에 있어서 중심축상의 깊이선량백분률의 차이가 발생하는 것은 쐐기에 의해서 X-선이 강화됨을 의미한다. 같은 각도의 쇄기에서 깊이선량백분률과 산란보정계수의 명목쐐기형 조사야와 유효쐐기형 조사야사이의 차이는 없었다. 개방조사야에서 조사야 $6cm{\times}6cm$, 깊이 7cm의 깊이선량백분률은 명목 또는 유효쐐기형 조사야 보다 $3.26\%$가 더 컸다. 그러나 조사야 $(10cm{\times}10cm)$가 커질수록 깊이선량백분률의 차이는 명목 또는 유효쐐기형 조사야보다 더 증가하였다-선량계측차이는 깊이 7cm에서 $3.56\%$, 12cm에서는 $5.30\%$였다 그러므로 심부종양치료시 선량의 계산이나 모니터세팅은 각 쐐기의 깊이 백분선량률과 투과율을 사용하여야 오차를 줄일 수 있을 것으로 사료된다.

• 핵의학기술
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• 제16권2호
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• pp.120-125
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• 2012

이 연구의 목적은 Brain SPECT (Single Photon Emission Computed Tomography)의 Non-attenuation correction (AC-non) 영상에 대한 attenuation correction(AC) 방법 중 Chang's method와 CT based attenuation correction(AC-CT) 사이의 count를 비교하기 위함이다. phantom study는 증류수로 채워진 hoffman 3D phantom에 $^{99m}Tc$ 37Mbq을 투여하였고, patient study는 normal volunteer에 $^{99m}Tc$-HMPAO 750Mbq를 정맥주입하고 Siemens사의 Symbia T6로 Brain SPECT 영상을 획득하였고 뇌 정량 분석을 하였다. 각각의 방법들을 적용한 transverse image는 같은 위치에서 재구성 되었으며 각각 10, 20, 30번째 slice에서 6개의 region of interest(ROI)를 그려 AC-non 과 AC-CT 그리고 Chang's method의 count를 비교하였다. phantom study에서 AC-non, AC-CT, Chang's method의 각각 평균 count는 $4606.8{\pm}511.3$, $16794.6{\pm}2429.4$, $8752.6{\pm}896.5$이었으며 patient study에서 $5460.8{\pm}519.6$, $15320{\pm}1171.6$, $12795{\pm}1422.1$이었다. phantom study에서 AC-CT와 AC-non 사이의 비는 3.70이고 Chang's method와 AC-non 사이의 비는 1.92였으며 patient study에서는 각각 2.85, 2.38이었다. 우리는 이 연구를 통하여 AC-CT가 Chang's method보다 더 높은 AC을 해준다는 걸 알 수 있었다. 그리고 Chang's method는 patient study에서의 AC 값이 phantom study에서의 AC값보다 더 높다는 것을 알 수 있었다. brain SPECT/CT를 시행하는 경우 scatter correction을 같이 시행하고 bone에 의한 감쇠 정보를 반영할 수 있는 AC-CT가 chang's method보다 정확하다 할 수 있겠다.

• 농업과학연구
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• 제39권1호
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• pp.111-116
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• 2012

Nondestructive evaluation of seed viability is one of the highly demanding technologies for seed production industry. Conventional seed sorting technologies, such as tetrazolium and standard germination test are destructive, time consuming, and labor intensive methods. Near infrared spectroscopy technique has shown good potential for nondestructive quality measurements for food and agricultural products. In this study, FT-NIR spectroscopy was used to classify normal and artificially aged lettuce seeds. The spectra with the range of 1100~2500 nm were scanned for lettuce seeds and analyzed using the principal component analysis(PCA) method. To classify viable seeds from nonviable seeds, a calibration modeling set was developed with a partial least square(PLS) method. The calibration model developed from PLS resulted in 98% classification accuracy with the Savitzky-Golay $1^{st}$ derivative preprocessing method. The prediction accuracy for the test data set was 93% with the MSC(Multiplicative Scatter Correction) preprocessing method. The results show that FT-NIR has good potential for discriminating non-viable lettuce seeds from viable ones.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1284-1284
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• 2001

The transesterification of molten ethylene/vinylacetate (EVA) copolymers by octanol as a reagent and sodium methoxide as a catalyst in an extruder has been monitored by on-line near infrared (NIR) spectroscopy. A total of 60 NIR spectra were acquired for 37 minutes with the last spectrum recorded 31 minutes after the addition of octanol and catalyst was stopped. The experimental spectra show strong baseline fluctuations which are corrected for by multiplicative scatter correction (MSC). The chemometric methods of orthogonal projection approach (OPA) and multivariate curve resolution (MCR) were used to resolve the spectra and to derive concentration profiles of the species. The detailed analysis reveals the absence of completely pure variables that leads to small errors in the calculation of pure spectra. The initial estimation of a concentration that is necessary as an input parameter for MCR also presents a non-trivial task. We obtained results that were not ideal but applicable for practical concentration control. They enable a fast monitoring of the process in real-time and resolve the spectra of the EVA copolymer and the ethylene/vinyl alcohol (EVAL) copolymer to be very close to the reference spectra. The chemometric methods used and the decomposed spectra are discussed in detail.

• Food Science and Biotechnology
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• 제18권1호
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• pp.60-65
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• 2009

Near infrared reflectance spectroscopy (NIRS) was used as a rapid and non-destructive method to determine the protein content in intact and ground seeds of pea (Pisum sativum L.) germplasms grown in Korea. A total of 115 samples were scanned in the reflectance mode of a scanning monochromator at intact seed and flour condition, and the reference values for the protein content was measured by auto-Kjeldahl system. In the developed ground and intact NIRS equations for analysis of protein, the most accurate equation were obtained at 2, 8, 6, 1 math treatment conditions with standard normal variate and detrend scatter correction method and entire spectrum (400-2,500 nm) by using modified partial least squares regression (n=78). External validation (n=34) of these NIRS equations showed significant correlation between reference values and NIRS estimated values based on the standard error of prediction (SEP), $R^2$, and the ratio of standard deviation of reference data to SEP. Therefore, these ground and intact NIRS equations can be applicable and reliable for determination of protein content in pea seeds, and non-destructive NIRS method could be used as a mass analysis technique for selection of high protein pea in breeding program and for quality control in food industry.

• Journal of Biosystems Engineering
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• 제35권6호
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• pp.450-457
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• 2010

Although cherry tomato is one of major vegetables consumed in fresh vegetable market, the quality grading method is mostly dependant on size measurement using drum shape sorting machines. Using Visible/Near-infrared spectroscopy, apparatus to be able to acquire transmittance spectrum data was made and used to estimate firmness, sugar content, and acidity of cherry tomatoes grown at hydroponic and soil culture. Partial least square (PLS) models were performed to predict firmness, sugar content, and acidity for the acquired transmittance spectra. To enhance accuracy of the PLS models, several preprocessing methods were carried out, such as normalization, multiplicative scatter correction (MSC), standard normal variate (SNV), and derivatives, etc. The coefficient of determination ($R^2_p$) and standard error of prediction (SEP) for the prediction of firmness, sugar, and acidity of cherry tomatoes from green to red ripening stages were 0.859 and 1.899 kgf, with a preprocessing of normalization, 0.790 and $0.434^{\circ}Brix$ with a preprocessing of the 1st derivative of Savitzky Golay, and 0.518 and 0.229% with a preprocessing normalization, respectively.

• Korean Journal of Geomatics
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• 제4권1호
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• pp.1-8
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• 2004

In the middle-resolution remote sensing, the Ground Sampled Distance (GSD) that the detector senses and samples is generally larger than the actual size of the objects (or materials) of interest, and so several objects are embedded in a single pixel. In this case, as it is impossible to detect these objects by the conventional spatial-based image processing techniques, it has to be carried out at sub-pixel level through spectral properties. In this paper, we explain the sub-pixel analysis algorithm, also known as the Linear Spectral Mixing (LSM) model, which has been experimented using the Hyperion data. To find Endmembers used as the prior knowledge for LSM model, we applied the concept of the convex geometry on the two-dimensional scatter plot. The Atmospheric Correction and Minimum Noise Fraction techniques are presented for the pre-processing of Hyperion data. As LSM model is the simplest approach in sub-pixel analysis, the results of our experiment is not good. But we intend to say that the sub-pixel analysis shows much more information in comparison with the image classification.