• Korean Journal of Optics and Photonics
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• v.16 no.6
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• pp.535-541
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• 2005

We report on the development of a passively mode-locked near-infrared femtosecond laser with Cr:YAG crystal that operates near room temperature. The laser wavelength could easily be tuned by using only the internal prism pair over 110 nm from 1400 nm to 1510 nm in cw and over about 30 nm in mode-locked operation, respectively Maximum cw output powers of 810 mW were obtained with $1.5 \%$ output coupler for absorbed pump powers of 7.6 W. For compensation of the internal group velocity dispersion, an IR graded prism pair was used. The Cr:YAG laser delivered nearly Fourier-transform limited pulses with a pulse duration as short as 64 fs at 100 MHz repetition rate. In the mode-locked regime, the laser was operating at 1510 nm with a spectral bandwidth of 44 nm. In order to avoid unstable mode-locking and power instabilities, self-built tubes were inserted into the beam path in the resonator and purged with N2 gas. Finally, output powers of the Cr:YAG laser were optimized to 250 mW fer long time stable mode-locked operation.

• Korean Journal of Food Science and Technology
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• v.26 no.5
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• pp.579-584
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• 1994

Near infrared reflectance(NIR) spectroscopy was used to determine the degree of retrogradation of cooked rice. Cooked rice samples were stored at $4^{\circ}C$ for 120 hours, and the degree of retrogradation was measured at every 6 hour during the storage time. Stored cooked rices were freeze-dried, milled and passed through a 100 mesh sieve. Enzymatic method using glucoamylase was used as reference method for the determination of the degree of retrogradation. Spectral differences due to retrogradation of cooked rice were observed at 1434, 1700, 1928, 2100, 2284 and 2320 nm. 32 samples of which moisture content were below 5% were used for calibration set, and 16 samples were used for validation set. High correlations were achieved between degree of retrogradation determined by conventional enzymatic method and by NIR with multiple correlation coefficient of 0.9753, and a standard error of calibration(SEC) of 3.64%. Comparable results were obtained with 3.91% of standard error of prediction(SEP), when the calibration equation was applied to independent group of samples of which moisture contents were in the range of calibration set. But when the calibration equation was applied to samples of which moisture contents were outer range of calibration set, SEP and bias were increased and correlation coefficient was decreased. The determination of degree of retrogradation was affected by sample moisture content. To determine degree of retrogradation of cooked rice by NIR using this calibration equation, it was suggested that sample moisture content should be controlled to below 5%.

• Korean Journal of Food Science and Technology
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• v.24 no.5
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• pp.408-413
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• 1992

This study was conducted to determine the effect of the homogenizing grade of sample on absorbance of near infrared reflectance spectrophotometer with which chemical compositions of food were rapidly and effectively analyzed. By the mathematical treatment of absorbance values standard error of prediction was reduced as follows. 1. The absorbance values of various samples ground for the same periods of time were calibrated before or after treatment with first or second derivative in an attempt to accurately predict the components of samples ground for the different periods of time. The standard error of prediction for moisture content were 1.478%, 0.658% and 0.580%, respectively, those for fat content 0.949%, 0.637% and 0.527%, respectively, and those for protein content 0.514%, 0.493% and 0.394%, respectively. Calibration of absorbance values after second derivative treatment showed the highest accuracy in predicting sample components. 2. The absorbance values of various samples ground for the different periods of time were calibrated before or after treatment with first or second derivative in order to accurately predict the components of samples ground for the different periods of time. The standard error of prediction for moisture content were 1.026%, 0.589% and 0.568%, respectively, and those for protein content 0.860%, 0.557% and 0.399%, respectively. The standard error of prediction were lower in the order of calibrations before and after first and second derivative treatments. As a result, calibration of absorbance values after second derivative treatment showed higher accuracy regardless of grinding time of samples.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.3
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• pp.113-127
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• 2015

Recently, there has been a growing interest in UAS(Unmanned Aerial System), and it is required to develop techniques to effectively detect water body from the recorded images in order to implement flood monitoring using UAS. This study used a UAS with RGB and NIR+RG bands to achieve images, and applied supervised classification method to evaluate the accuracy of water body detection. Firstly, the result for accuracy in water body image classification by RGB images showed high Kappa coefficients of 0.791 and 0.783 for the artificial neural network and minimum distance method respectively, and the maximum likelihood method showed the lowest, 0.561. Moreover, in the evaluation of accuracy in water body image classification by NIR+RG images, the magalanobis and minimum distance method showed high values of 0.869 and 0.830 respectively, and in the artificial neural network method, it was very low as 0.779. Especially, RGB band revealed errors to classify trees or grasslands of Songsan amusement park as water body, but NIR+RG presented noticeable improvement in this matter. Therefore, it was concluded that images with NIR+RG band, compared those with RGB band, are more effective for detection of water body when the mahalanobis and minimum distance method were applied.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1407-1412
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• 2014

In order to improve spectrum sensitivity of photodiode for detection of the laser at 850 nm ~ 1000 nm of near-infrared wavelength band, this study has produced silicon-based fast film PIN photodiode and analyzed electrical and optical properties. The manufactured device is packaged in TO-18 type. The electrical properties of the dark currents both Anode 1 and Anode 2 have valued of approximately 0.055 nA for 5 V reverse bias, while the capacitance showed 19.5 pF at frequency range of 1 kHz and about 19.8 pF at the range of 200 kHz for 0 V. In addition, the rising time of output signal was verified to have fast response time of about 30 ns for 10 V. For the optical properties, the best spectrum sensitivity was 0.66 A/W for 880 nm, while it was relatively excellent value of 0.45 A/W for 1,000 nm.

• Korean Journal of Optics and Photonics
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• v.26 no.1
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• pp.23-29
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• 2015

In this paper, we propose a microscope system for detecting both a tumor and blood vessels in brain tumor surgery as fluorescence images by using multiple light sources and a beam-splitter module. The proposed method displays fluorescent images of the tumor and blood vessels on the same display device and also provides accurate information about them to the operator. To acquire a fluorescence image, we utilized 5-ALA (5-aminolevulinic acid) for the tumor and ICG (Indocyanine green) for blood vessels, and we used a beam-splitter module combined with a microscope for simultaneous detection of both. The beam-splitter module showed the best performance at 600 nm for 5-ALA and above 800 nm for ICG. The beam-splitter is flexible to enable diverse objective setups and designed to mount a filter easily, so beam-splitter and filter can be changed as needed, and other fluorescent dyes besides 5-ALA and ICG are available. The fluorescent images of the tumor and the blood vessels can be displayed on the same monitor through the beam-splitter module with a CCD camera. For ICG, a CCD that can detect the near-infrared region is needed. This system provides the acquired fluorescent image to an operator in real time, matching it to the original image through a similarity transform.

• Journal of the Mineralogical Society of Korea
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• v.30 no.1
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• pp.31-43
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• 2017

This study investigated mineralogy, spectral characteristics and heavy metal contamination including Cd, Ni, Al, Fe, Mn and S for white precipitation in Miin falls based on XRF, XRD, and spectrometer. As a result, Al concentration was abnormally high at all samples, and most of the samples showed high contamination level in Cd and Ni. XRD results detected quartz, kaolinite, rhomboclase, aluminocoquimbite, and gibbsite which infers that heavy metal elements are distributed by adsorption with clay minerals. Spectral characteristics of white precipitation can be described by increasing pattern of reflectance in visible spectrum and decreasing pattern of reflectance in longer wave length including near infrared and shortwave infrared spectrum. The absorption features reveals that spectral characteristics of white precipitation is mainly controlled by kaolinite, rhomboclase, aluminocoquimbite, and gibbsite. The relationship between heavy metal concentration and absorption depth showed high positive correlation for Al concentration and absorption feature at 2202 nm of Al-OH absorption. This spectral characteristics indicates that absorption depth could be effectively used for estimation of heavy metal concentration.

• Journal of Biosystems Engineering
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• v.27 no.2
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• pp.117-124
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• 2002

This research was conducted to develop a method to remove the effect of surface temperature of Shingo pears for sugar content measurement. Sugar content was measured by a near-infrared spectrum analysis technique. Reflected spectrum and sugar content of a pear were used for developing regression models. For the model development, reflected spectrums having wavelengths in the range of 654 to 1,052nm were used. To remove the effect of surface temperature, special sample preparation techniques and partial least square (PLS) regression models were proposed and tested. 71 Shingo pears stored in a cold storage, which had 2$^{\circ}C$ inside temperature, were taken out and left in a room temperature for a while. Temperature and reflected spectrum of each pear was measured. To increase the temperature distribution of samples, temperature and reflected spectrum of each pear was measured four times with one hour twenty minutes interval. During the experiment, temperature of pears increased up to 17 $^{\circ}C$. The total number of measured spectrum was 284. Three groups of spectrum data were formed according to temperature distribution. First group had surface temperature of 14$^{\circ}C$ and total number of 51. Second group consisted of the first and the fourth experiment data which contained the minimum and the maximum temperatures. Third group consisted of 155 data with normal temperature-distribution. The rest data set were used for model evaluation. Results shelved that PLS model I, which was developed by using the first data group, was inadequate for measuring sugar content of pears which had different surface temperatures from 14$^{\circ}C$. After temperature compensation, sugar content predictions became close to the measured values. Since using many data which had wide range of surface temperatures, PLS model II and III were able to predict sugar content of pears without additional temperature compensation. PLS model IV, which included the surface temperatures as an independent variable. showed slightly improved performance(R$^2$=0.73). Performance of the model could be enhanced by using samples with more wide range of temperatures and sugar contents.

• Resources Recycling
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• v.26 no.1
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• pp.69-77
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• 2017

Used small household appliances(small e-waste) consists of a variety of complex materials and components. The small e-waste is mainly composed of plastics and an important potential source of waste plastic. The black plastics, particularly are very difficult to separate by resin type and therefore these are mainly recycled in the form of a mixtures. In the present study, the sorting technologies such as gravity and electro static separation, near-infrared ray(NIR) and IR/Raman optical sorting separation on mixture of black plastics were analyzed and their limitations on sorting process were also investigated. The Laser Induced Breakdown Spectroscopy(LIBS) spectrum of each black plastics was used for identification of black plastics by resin type, and after analyzing the normalization operation, Principal Component Analysis(PCA) was carried out. The spectrum data was optimized through PCA process. In order to improve the identification accuracy and sorting efficiency of black plastics, it is necessary to design a classifier with high efficiency and to improve the performance and reliability of the classifier by applying the field of intelligent algorithms.

• Journal of Food Hygiene and Safety
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• v.21 no.4
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• pp.204-212
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• 2006

This study was conducted to investigate the possibility of rapid and non-des tructive evalution of AV (Acid Value), IV (Iodine Value) and fatty acids in sesame oils. The samples were scanned over the range $400\sim2500nm$ using transmittance spectrum of NIRS(Near-infrared spectroscopy). A calibration equation calculated by MPLS regression technique was developed and correlation coefficient of determination for AV, IV, palmitic acid, stearic acid, linoleic acid and linolenic acid content were 0.9907, 0.9677, 0.9527, 0.9210, 0.9829, 0.9736 and 0.9709 respectively. The validation model for measuring the AV content had R of 0.989, SEP of 0.058 and IV content had R of 0.944, SEP of 0.562 and palmitic acid content had R of 0.924, SEP of 0.194 and stearic acid content had R of 0.717, SEP of 0.168 and oleic acid content had R of 0.989, SEP of 0.221 and linoleic acid content had R of 0.967, SEP of 0.297 and linolenic acid content had R of 0.853, SEP of 0.480 by MPLS. The obtained results indicate that the NIRS procedure can potentially be used as a non-destructive analysis method for the purpose of rapid and simple measurement of AV, IV and fatty acids in sesame oils.