• 한국의학물리학회:학술대회논문집
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• 한국의학물리학회 1999년도 Japanese Journal of Medical Physics
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• pp.253-254
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• 1999

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1071-1071
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• 2001

Near-infrared spectroscopy (NIRS) is potentially a powerful and revolutionary technology for environmental analysis. It is supported by a large body of scientific and experiential knowledge. The instrumentation is well-developed, with easy-to-use, highly dependable instruments, but at the same time it is still developing, particularly with the production of more portable and rapid instruments, and more powerful software. NIRS is used globally in numerous industries for commodity analysis. Yet NIRS is largely unknown in the field of environmental chemistry and monitoring, and is not even routinely used in soil analysis, where the research literature on NIRS extends over four decades. Part of the explanation for the poor visibility of NIRS is the fact that NIRS is not routinely taught in Chemistry programs in universities, where most environmental chemists and environmental technicians are trained. This presentation examines the unique capabilities of NIRS, such as rapid, real-time analysis; analysis of whole samples; simultaneous analysis of multiple constituents; cost-effectiveness, and portability, as they match needs for analysis in several environmental areas. Examples of NIRS usage and published and unpublished results will be described for such areas as soil and sediment analysis; water quality monitoring; and nutrient loading in application of manures and sewage sludge (biosolids) to land. Present barriers to the use of NIRS in environmental analysis will be discussed. It is argued that emerging environmental problems and increasing attention to some traditional problems will enhance the application of NIRS in the future.

• 한국의학물리학회:학술대회논문집
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• 한국의학물리학회 1999년도 Japanese Journal of Medical Physics
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• pp.207-209
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• 1999

• 한국초지조사료학회지
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• 제9권3호
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• pp.163-167
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• 1989

Near infrared reflectance spectroscopy(NIRS)로 포장를 평가하기 위하여 일건 알파파 건초 5점의 조단백질, NDF, ADF 함량을 측정하였으며 NIRS와 전통적인 문화저방법에 의한 분석치를 비교하였다. 조단백질과 ADF의 량은 NIRS와 화학분석 식간간에 차이가 없었으나 NDF의 함량은 시료번호 2, 4.5에서 유의착(P<0.05)가 있었다.)가 있었다.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2004년도 추계학술발표회 발표논문집
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• pp.669-670
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• 2004

• 한국의학물리학회:학술대회논문집
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• 한국의학물리학회 1999년도 Japanese Journal of Medical Physics
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• pp.228-229
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• 1999

• 한국작물학회지
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• 제46권3호
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• pp.248-252
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• 2001

비파괴분석을 통한 종실 성분 함량 측정의 가능성을 알아보고자 근적외분광분석기(NIRS)를 사용하여 강낭콩 종실 및 분말상태로 조단백 및 조지방 함량을 측정하였다. 1. 강낭콩의 100립중은 12.8-45.5g, 조단백 12.2-16.5%, 조지방 1.68-2.08%의 분포를 나타냈다. 2. 시험계통별 조단백 함량은 13.1-14.0% 13개(32.5%), 조지방 함량은 1.8-l.9% 18개(45%)로 가장 많은 비율을 나타냈다. 3. 검량선 작성시 종래의 화학적 방법에 의한 분석치와 NIRS 분석치 와의 상관계수는 조단백의 경우 비파괴의 종실이 0.90,분말 0.97이고 조지방의 경우 종실 0.40, 분말 0.92로 종실보다는 분말시료가 검량식의 작성에 유리함을 알 수 있었고, 화학성분으로 볼 때 조지방 검량식 보다는 조단백의 검량식이 유용성이 더 큰 것으로 판단되었다. 4. 작성된 검량식들의 정확도를 알아보기 위해 미지의 시료로 측정된 NIRS 분석치와 Validation과의 상관계수는 조단백의 경우 종실 0.86, 분말 0.84이었고 조지방은 종실 0.62, 분말 0.92를 나타내어 조단백의 이용은 가능할 것으로 판단되었다.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2021년도 제64차 하계학술대회논문집 29권2호
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• pp.305-307
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• 2021

Alzheimer's Disease (AD) is a cognitive disorder characterized by memory impairment that can be assessed at early stages based on administering clinical tests. However, the AD pathophysiological mechanism is still poorly understood due to the difficulty of distinguishing different levels of AD severity, even using a variety of brain modalities. Therefore, in this study, we present a hybrid EEG-fNIRS modalities to compensate for each other's weaknesses with the help of Machine Learning (ML) techniques for classifying four subject groups, including healthy controls (HC) and three distinguishable groups of AD levels. A concurrent EEF-fNIRS setup was used to record the data from 41 subjects during Oddball and 1-back tasks. We employed both a traditional neural network (NN) and a CNN-LSTM hybrid model for fNIRS and EEG, respectively. The final prediction was then obtained by using majority voting of those models. Classification results indicated that the hybrid EEG-fNIRS feature set achieved a higher accuracy (71.4%) by combining their complementary properties, compared to using EEG (67.9%) or fNIRS alone (68.9%). These findings demonstrate the potential of an EEG-fNIRS hybridization technique coupled with ML-based approaches for further AD studies.

• 한국작물학회지
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• 제46권2호
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• pp.106-111
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• 2001

The applicability of near infrared reflectance spectroscopy(NIRS) was tested to determine the protein and oil contents in ground soybean [Glycine max (L.) Merr.] seeds. A total of 189 soybean calibration samples and 103 validation samples were used for NIRS equation development and validation, respectively. In the NIRS equation of protein, the most accurate equation was obtained at 2, 8, 6, 1(2nd derivative, 8 nm gap, 6 points smoothing and 1 point second smoothing) math treatment condition with SNV-D (Standard Normal Variate and Detrend) scatter correction method and entire spectrum by using MPLS (Modified Partial Least Squares) regression. In the case of oil, the best equation was obtained at 1, 4, 4, 1 condition with SNV-D scatter correction method and near infrared (1100-2500nm) region by using MPLS regression. Validation of these NIRS equations showed very low bias (protein:-0.016%, oil : -0.011 %) and standard error of prediction (SEP, protein: 0.437%, oil: 0.377%) and very high coefficient of determination ($R^2$, protein: 0.985, oil : 0.965). Therefore, these NIRS equation seems reliable for determining the protein and oil content, and NIRS method could be used as a mass screening method of soybean seed.

• 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.