• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2393-2399
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• 2013

In this paper, we proposed a method to screening of Alzheimer's disease (AD) from Raman spectra of platelet with synthesis of basis spectra using singular value decomposition (SVD). Raman spectra of platelet from AD transgenic mice are preprocessed with denoising, removal background and normalization method. The column vectors of each data matrix consist of Raman spectrum of AD and normal (NR). The matrix is factorized using SVD algorithm and then the basis spectra of AD and NR are determined by 12 column vectors of each matrix. The classification process is completed by select the class that minimized the root-mean-square error between the validation spectrum and the linear synthesized spectrum of the basis spectra. According to the experiments involving 278 Raman spectra, the proposed method gave about 97.6% classification rate, which is better performance about 6.1% than multi-layer perceptron (MLP) with extracted features using principle components analysis (PCA). The results show that the basis spectra using SVD is well suited for the diagnosis of AD by Raman spectra from platelet.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.32-39
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• 2018

Raman spectra exhibit differences in intensity depending on the measuring equipment and environmental conditions even for the same material. This restricts the pattern recognition approach of Raman spectroscopy and is an issue that must be solved for the sake of its practical application, so as to enable the reusability of the Raman database and interoperability between Raman devices. To this end, previous studies assumed the existence of a transfer function between the measurement devices to obtain a direct spectral correction. However, this method cannot cope with other conditions that cause various intensity distortions. Therefore, we propose a classification method using linear intensity calibration which can deal with various measurement conditions more flexibly. In order to evaluate the performance of the proposed method, a Raman library containing 14033 chemical substances was used for identification. Ten kinds of chemical Raman spectra measured using three different Raman spectroscopes were used as the experimental data. The experimental results show that the proposed method achieves 100% discrimination performance against the intensity-distorted spectra and shows a high correlation score for the identified material, thus making it a useful tool for the identification of chemical substances.

• Korean Journal of Optics and Photonics
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• v.28 no.3
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• pp.116-121
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• 2017

In this paper, a Raman spectrometer is designed to detect chemicals contaminating the ground. The system is based on Raman spectroscopy, which is spectral analysis of scattered light from chemicals, induced by a laser. The system consists of a transmitting-optics module with a laser to induce Raman-scattered light from the sample, a receiving-optics module to collect the scattered light, and a spectrograph to separate the collected light into a wavelength spectrum. The telescope, a part of the receiving-optics module, is designed to produce a focal spot in the same position for variable measurement distances using the code V simulator, considering the distance change between the system and the road. The Raman spectra of 12 chemicals on a glass surface and on a concrete sample were measured. Intensity differences between the Raman spectra acquired on a glass surface and on a concrete sample were observed, but the characteristics of the spectra according to the chemicals on them were similar. Additionally, the Raman spectrum of PTFE (polytetrafluoroethylene) was measured at various distances. The measured and simulated optical throughputs were similar. In conclusion, it is confirmed that with this system the Raman spectrum can be measured, irrespective of the distance change.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.196-202
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• 2013

Basal cell carcinoma (BCC) is the most common skin cancer and its incidence is increasing rapidly. In this paper, we propose a diagnosis method of basal cell carcinoma by Raman spectra of skin tissue using the NMF(non-negative matrix factorization) algorithm. After preprocessing steps, measured Raman spectra is used classification experiments. The weight and the basis can be obtained in a simple matrix operation and a column vector of the matrix decompsed by the NMF. Linear combination of bases and weights, it is possible to approximate the average of Raman spectra. The classification method is to select the class which to minimize the root mean square of the difference of the linear combination and the objective spectrum. According to the experimental results, the proposed method shows the promising results to diagnosis BCC. In addition, it confirmed that the proposed method compared with the previous research result could be effectively applied in the analysis of the Raman spectra.

• Journal of the Korean Society for Nondestructive Testing
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• v.34 no.4
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• pp.283-289
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• 2014

This study was conducted to develop a non-destructive detection method for adulterated powder products using Raman spectroscopy and partial least squares regression(PLSR). Garlic and ginger powder, which are used as natural seasoning and in health supplement foods, were selected for this experiment. Samples were adulterated with corn starch in concentrations of 5-35%. PLSR models for adulterated garlic and ginger powders were developed and their performances evaluated using cross validation. The $R^2_c$ and SEC of an optimal PLSR model were 0.99 and 2.16 for the garlic powder samples, and 0.99 and 0.84 for the ginger samples, respectively. The variable importance in projection (VIP) score is a useful and simple tool for the evaluation of the importance of each variable in a PLSR model. After the VIP scores were taken pre-selection, the Raman spectrum data was reduced by one third. New PLSR models, based on a reduced number of wavelengths selected by the VIP scores technique, gave good predictions for the adulterated garlic and ginger powder samples.

• Bulletin of the Korean Space Science Society
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• 2004.04a
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• pp.30-30
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• 2004

우리는 보현산 1.8미터망원경에 장착된 고분산 에셸분광기 (BOES)를 사용하여 공생별V1016 Cyg의 스펙트럼을 얻었다. H alpha의 중심부가 포화될 정도의 장기 노출 관측 자료에서 H alpha의 날개 부분과 6545$\AA$ 근처의 He II 라만산란선, 4850$\AA$ 근처의 HeII 라만산란선을 확인하였다. 특히, 4850$\AA$ 근처의 라만산란선은 그 중심 위치가 원래 위치에서 0.8$\AA$ 가량 적색쪽으로 치우쳐 있으며, 우리는 이 현상이 라만산란단면적이 He II 972 방출선에 대하여 비대칭적이기 때문에 나타난다고 해석한다. (중략)

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.2
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• pp.80-85
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• 2011

Alzheimer's disease and Parkinson's disease are the most common neurodegenerative disorders. In this paper, we proposed a feature extraction method for classification of AD and PD based on micro-Raman spectra from platelet. The first step of the preprocessing is a simple smoothing followed by background elimination to the original spectra to make it easy to measure the intensity of the peaks. The last step of the preprocessing was peak alignment with the reference peak. After the inspection of the preprocessed spectra, we found that proportion of two peak intensity at 743 and $757cm^{-1}$ and peak intensity at 1248 and $1448cm^{-1}$ are the most discriminative features. Then we apply mapstd method for normalization. The method returned data with means to 0 and deviation to 1. With these three features, the classification result involving 263 spectra showed about 95.8% true classification in case of MAP(maximum a posteriori probability).

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.143-143
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• 2012

일반적인 라만 분광 시스템은 회절 한계로 인해 공간 분해능이 떨어지며, 시료의 양이 적을 경우에 굉장히 미약하게 발생하는 라만 신호의 검출 감도가 떨어지는 단점이 있다. 본 연구에서는 이러한 문제점을 개선하기 위하여 tip-enhanced Raman spectroscopy (TERS)를 구축하였다. 구축한 TERS 시스템은 뾰족한 금속 탐침을 시료 위에 근접시켜 금속 탐침 내에 존재하는 전자와 여기 광 간의 플라즈몬 공명 현상에 의한 광 안테나 효과를 유도하여 라만 분광 시스템의 공간 분해능을 수십 나노미터 정도로 향상시켰으며, 기존의 라만 분광 시스템에서는 검출되지 않는 미약한 라만 신호를 검출할 수 있었다. 구축한 TERS 시스템을 이용하여 탄소나노튜브를 비롯한 다양한 반도체 시료의 라만 스펙트럼 및 라만이미지를 측정하였고, 금속 탐침이 시료위에 근접되지 않은 경우의 측정 결과와 라만 신호의 세기 및 라만 이미지의 공간 분해능을 비교하여 제안하는 TERS 시스템의 효용성을 검증하였다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.4
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• pp.40-46
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• 2010

In this paper, we use the Raman spectra measured from platelet to the diagnosis of Alzheimer's disease(AD). The Raman spectra used in the experiments were preprocessed with the following method and then fed into the classifier. The first step of the preprocessing is a simple smoothing followed by background elimination to the original spectra to make it easy to measure the intensity of the peaks. The last step of the preprocessing was peak alignment with the reference peak. After the inspection of the preprocessed spectra, we found that proportion of two peak intensity at 743 and 757 $cm^{-1}$ and peak intensity at 1658 $cm^{-1}$ are the most discriminative features. Then we apply mapstd method for normalization. The method returned data with means to 0 and deviation to 1. With these two features, the classification result involving 278 spectra showed about 95.5% true classification in case of MLP(multi-layer perceptron). It means that the Raman spectra measured from platelet would be effectively used to the diagnosis of Alzheimer's disease.

• Smart Media Journal
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• v.2 no.2
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• pp.33-38
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• 2013

In this paper, we investigated baseline estimation methods for remove background noise using Raman spectra from acute alcohol liver injury and acute ethanol-induced chronic liver fibrosis. Far the baseline estimation, we applied first derivative, linear programming and rolling ball method. Optimal input parameter of each method were determined by the training rate of MAP (maximum a posteriori probability) classifier. According to the experimental results, classification results baseline estimation with the rolling ball algorithm gave about 89.4%, which is very promising results for classification of acute alcohol liver injury and acute ethanol-induced chronic liver fibrosis. From these results, to determined the appropriate methods and parameters of baseline estimation impact on classification performance was confirmed.