• Title/Summary/Keyword: 2nd Derivative

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Near infrared spectroscopy for classification of apples using K-mean neural network algorism

  • Muramatsu, Masahiro;Takefuji, Yoshiyasu;Kawano, Sumio
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1131-1131
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    • 2001
  • To develop a nondestructive quality evaluation technique of fruits, a K-mean algorism is applied to near infrared (NIR) spectroscopy of apples. The K-mean algorism is one of neural network partition methods and the goal is to partition the set of objects O into K disjoint clusters, where K is assumed to be known a priori. The algorism introduced by Macqueen draws an initial partition of the objects at random. It then computes the cluster centroids, assigns objects to the closest of them and iterates until a local minimum is obtained. The advantage of using neural network is that the spectra at the wavelengths having absorptions against chemical bonds including C-H and O-H types can be selected directly as input data. In conventional multiple regression approaches, the first wavelength is selected manually around the absorbance wavelengths as showing a high correlation coefficient between the NIR $2^{nd}$ derivative spectrum and Brix value with a single regression. After that, the second and following wavelengths are selected statistically as the calibration equation shows a high correlation. Therefore, the second and following wavelengths are selected not in a NIR spectroscopic way but in a statistical way. In this research, the spectra at the six wavelengths including 900, 904, 914, 990, 1000 and 1016nm are selected as input data for K-mean analysis. 904nm is selected because the wavelength shows the highest correlation coefficients and is regarded as the absorbance wavelength. The others are selected because they show relatively high correlation coefficients and are revealed as the absorbance wavelengths against the chemical structures by B. G. Osborne. The experiment was performed with two phases. In first phase, a reflectance was acquired using fiber optics. The reflectance was calculated by comparing near infrared energy reflected from a Teflon sphere as a standard reference, and the $2^{nd}$ derivative spectra were used for K-mean analysis. Samples are intact 67 apples which are called Fuji and cultivated in Aomori prefecture in Japan. In second phase, the Brix values were measured with a commercially available refractometer in order to estimate the result of K-mean approach. The result shows a partition of the spectral data sets of 67 samples into eight clusters, and the apples are classified into samples having high Brix value and low Brix value. Consequently, the K-mean analysis realized the classification of apples on the basis of the Brix values.

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Interpretation of Airborne Magnetic and Radioactive Data for the Uranium Deposit in Geumsan Area (금산 함우라늄광상 분포지역의 항공자력/방사능 탐사자료 해석)

  • Shin, Eun-Ju;Ko, Kwangbeom;An, Dongkuk;Han, Kyeongsoo
    • Geophysics and Geophysical Exploration
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    • v.16 no.1
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    • pp.36-44
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    • 2013
  • We conducted the airborne magnetic and radiometric survey for the characterization of the black shale related and pyrometamorphic uranium deposits distributed in Geumsan area. For the successful characterization of the uranium deposits, the general geological and structural geological features were investigated based on the lithological and linear feature analysis to individual magnetic and radiometric data as the first step. Lithological analysis from the magnetic reduction to the pole and downward continuation map revealed that prominent positive anomalies caused by black and dark gray slate member were clearly recognized as magnetic sources. These results indicate that magnetic survey, even though it is not a direct method for the detection of uranium, can be a useful tool in uranium detection. By the linear feature analysis based on 2nd vertical derivative and curvature map, two linearments corresponded the gray hornfels and black slate member were extracted and in succession, the additional uranium potential zone was inferred. Final discrimination whether uranium-rich or not was confirmed by radiometric and uranium anomaly map. From these analysis, we finally concluded that uranium deposit originated by pyrometamorphic process was confined near the intrusive area only. On the contrary, it was found that black shale related uranium deposit is distributed and extended through out the entire survey area with south-west to north-east direction. In addition, from the linear feature analysis based on radiometric total anomaly map, the typical discontinuous characteristics were recognized in areas where uranium-contained linearments cross the faults. From the above discussion, we concluded that airborne magnetic and radiometric survey are complementary to each other. So it is preferable to carry out simultaneously for the efficient data processing and fruitful interpretation.

Determination of Protein and Oil Contents in Soybean Seed by Near Infrared Reflectance Spectroscopy

  • Choung, Myoung-Gun;Baek, In-Youl;Kang, Sung-Taeg;Han, Won-Young;Shin, Doo-Chull;Moon, Huhn-Pal;Kang, Kwang-Hee
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.46 no.2
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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.

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Numerical Investigation of Effect of Opening Pattern of Flow Control Valve on Underwater Discharge System using Linear Pump (유량제어밸브 개방형태가 선형펌프 방식 수중사출 시스템에 미치는 영향에 관한 수치적 연구)

  • Lee, Sunjoo
    • Journal of the Korea Institute of Military Science and Technology
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    • v.22 no.2
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    • pp.255-265
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    • 2019
  • In the present study, the effect of opening patterns of a flow control valve on underwater discharge systems using a linear pump was investigated numerically. For that, a improved mathematical model was developed. The improvement is to separate a middle tank from a water cylinder because the cross-section area of the inlet of the middle tank is an important parameter. To validate the improved model, calculation results were compared with a previous study. The results showed that $2^{nd}$ order or more polynomial opening patterns had an advantage over ramp opening patterns. Higher an order of polynomial resulted in wider operating limits. An escape velocity and a maximum acceleration of underwater vehicle were affected by time derivative of the cross-section area of the flow control valve. Besides, as a velocity profile of the vehicle got closer to linearity, the escape velocity got faster and the maximum acceleration got smaller. And velocities of the vehicle and piston had similar variation trend.

Identification of Pharmaceuticals for process control using Near Infrared Spectroscopy and Soft Independence modeling of Class Analogy (SIMCA)

  • Cho, Chang-Hee;Kim, Hyo-Jin;Maeng, Dae-Young;Seo, Sang-Hun;Cho, Jung-Hwan
    • Near Infrared Analysis
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    • v.1 no.2
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    • pp.29-33
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    • 2000
  • The identification step of raw drug materials is an indispensible procedure in the GMP manufacturing process within the pharmaceutical industry. However, wet chemistry methods for identification of drug materials, used by the various Pharmacopeia are time-consuming and expensive steps. In this paper, near-infrared spectroscopy (NIRS) has been developed for identifying eleven drug substances including calcium pantothenate, cefaclor, cefoperazone, cephradine, dextromethorphan, ehtambutol, nicotinamide, pyrozinamide, tramadol, vitamin C, and vitamin E. Also the aim of ths work is to consturct a new algorithm for calibration model using soft independence modeling of class analogy (SIMCA) with Malinowskis Indicator Function (IND), which is used for finding the number of principal components of each class of the SIMACA model. The use of NIR technique with pattern recognition to qualify raw materials can make it possible to monitor process in real time as well as to control all procedures in the pharmaceutical industry. As the result, the samples identified of 183 different batches from 11 different compounds were separated clearly by SIMCA with 2nd derivative spectra in the NIR region of 1100∼2400 nm.

Simulation of Nonlinear Water Waves using Boundary Element Method (경계요소법을 이용한 비선형파의 재현)

  • 오영민;이길성;전인식
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.5 no.3
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    • pp.204-211
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    • 1993
  • Boundary element method is applied to simulate nonlinear water waves using Green's identity formula in a numerical wave flume. A system of linear equations is formulated from the governing equation and free surface boundary conditions in order to calculate velocity potential and water surface elevation at each nodal point. The velocity square terms are included in the dynamic free surface boundary condition. The free surface is treated as a moving boundary. the vertical variation of velocity potential being considered in calculating the time derivative of the velocity potential at the free surface. The present method is applied to simulate solitary wave and Stokes 2nd order wave, and shows excellent agreements with their theoretical values.

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PREDICTION OF PHYSICO-CHEMICAL AND TEXTURE CHARACTERISTICS OF BEEF BY NEAR INFRARED TRANSMITTANCE SPECTROSCOPY

  • Olivan, Mamen;Delaroza, Begona;Mocha, Mercedes;Martinez, Maria Jesus
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1256-1256
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    • 2001
  • The physico-chemical and texture characteristics of meat determine the nutritional, technological and sensory quality. However, the analysis of meat quality requires expensive, laborious and time consuming analytical methods. The objective of this study was to evaluate NIR spectroscopy using transmittance for determining the moisture, fat, protein and total pigment content, the water holding capacity (WHC) and the toughness of beef meat. A total of 318 spectra were recorded from ground beef samples by a Feed Analyzer 1265 of Infratec. The samples were obtained from the Longissimus muscle of the 10$^{th}$ rib of yearling bulls, ground with an electrical chopper, vacuum packaged, aged during 7 days and frozen at -24$^{\circ}C$ until the analyses were done. Moisture content was measured by oven drying at 10$0^{\circ}C$, fat content was determined by Soxhlet extraction and protein content was estimated from nitrogen content using the Kjeldahl analysis. The total pigment content was determined by the method of Hornsey and the WHC using the method of filter paper press. The instrumental evaluation of texture (maximum load WB, maximum stress MS and toughness) was conducted in an Instron equipment with a Warner-Bratzler shearing device. This analysis was performed on a chop of 3.5 cm obtained from the longissimus of the 8$^{th}$ rib, aged during 7 days, kept frozen at -24$^{\circ}C$ and cooked before the analysis. Near infrared spectra were recorded as log 1/T (T=transmittance) at 2 nm intervals from 850 to 1050 nm using a Feed Analyzer 1265 of Infratec. Calibrations were performed with the WinISI software (vs. 1.02) using the MPLS method. To examine the effect of scatter correction o. derivation of spectra on the calibration performance, calibrations were calculated with the crude spectra or pretreated with different mathematical treatments (inverse MSC, SNVD) and/or second derivative operation. For chemical composition, the use of the scatter corrections improved the calibration statistics, in terms of lower SECV and higher $r^2$. In most of the variables, the use of the 2$^{nd}$ derivative improved the predictions, mainly when combined with the SNVD treatment. However, for predicting the texture traits, the best estimation was obtained from the crude spectrum. These results showed that the equations obtained for predicting moisture, fat and total pigments were very accurate, with $r^2$ being higher that 0.9. However, the prediction of the texture traits (WB, MS, toughness) from ground meat was poor.

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Effect of Tuberculin Skin Test on Ex-vivo Interferon-gamma Assay for Latent Tuberculosis Infection (투베르쿨린 검사가 결핵에 대한 체외 IFN-γ 검사 결과에 미치는 영향)

  • Lee, Jung Yeon;Choi, Hee Jin;Cho, Sang-Nae;Park, I-Nae;Oh, Yeon-Mok;Lee, Sang Do;Kim, Woo Sung;Kim, Dong Soon;Kim, Won Dong;Shim, Tae Sun
    • Tuberculosis and Respiratory Diseases
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    • v.59 no.4
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    • pp.406-412
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    • 2005
  • Background : Recently, two commercialized whole-blood assays, $QuantiFERON^{(R)}-TB$ Gold (QFT) and T $SPOT-TB^{(R)}$ (SPOT), which measure the $IFN-{\gamma}$ released in the whole blood after being incubation with mycobacterial antigens, were approved for the diagnosis of a latent tuberculosis infection (LTBI). However, there is data on whether or not the previously used PPD skin tests (TST) have any influence on the diagnostic ability of these ex-vivo $IFN-{\gamma}$ assays. Methods : Forty-six 15 year-old students who did not appear to be infected with Mycobacterium tuberculosis were enrolled in this study. The peripheral blood was collected and used for two $IFN-{\gamma}$ assays. The $IFN-{\gamma}$ assays and TST were performed at the baseline ($1^{st}$). The TST was repeated two months later ($2^{nd}$), and the $IFN-{\gamma}$ assays were repeated two ($2^{nd}$) and four months ($3^{rd}$) later only in those subjects who had negative results at the baseline in both the $IFN-{\gamma}$ assays and TST. An induration size > 10 mm was considered to be positive in the TST. Results : The mean TST value was $3.1{\pm}5.4mm$ (range: 0-20). Of the 46 subjects examined, 13 subjects (28.3%) showed positive results in the two-step TST. Nine (19.6%) were SPOT-positive and only one (2.2%) was QFT-positive. The $2^{nd}$ and $3^{rd}$ QFT were carried out in 23 and 25 all-negative subjects, respectively, and all showed negative results. The $2^{nd}$ SPOT was performed in 23 subjects and only one (4.3%) showed a weak-positive result. Conclusion : Even though there were some discrepancies in the results of the two ex-vivo $IFN-{\gamma}$ assays, it appears that their results were not influenced by a previous TST carried out in two or four months earlier.

Preparation and characterization of immobilized 8-hydroxyquinoline for chromatographic application (크로마토그래피용 고정화 8-hydroxyquinoline의 제조 및 특성분석)

  • Kim, Bum-Soo
    • Analytical Science and Technology
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    • v.13 no.1
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    • pp.49-54
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    • 2000
  • The 8-hydroxyquinoline derivative of silica gel has been prepared through the 5 step reaction. We carried out infrared as well as nuclear magnetic resonance spectrometric characterization of products taken from each step of reaction. IR study of bare silica gel showed free and hydrogen bonded hydroxyl. From the 1st step reaction, we observed IR bands for N-H and C-H as well as NMR peaks for three methylene carbons in APTS group. From the 2nd step, we observed IR bands for carbonyl, nitro and aromatic carbon group with NMR peaks for aliphatic, aromatic and carbonyl carbons. The reduction of $NO_2$ group to $NH_2$ group is confirmed by IR and NMR from 3rd step reaction. In the last step, the immobilization of 8-quinolinol is confirmed by disappearance of $N{\equiv}N$ IR peak observed in 4th step.

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Non-destructive Method for Selection of Soybean Lines Contained High Protein and Oil by Near Infrared Reflectance Spectroscopy

  • Choung, Myoung-Gun;Baek, In-Youl;Kang, Sung-Taeg;Han, Won-Young;Shin, Doo-Chull;Moon, Huhn-Pal;Kang, Kwang-Hee
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.46 no.5
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    • pp.401-406
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    • 2001
  • The applicability of non-destructive near infrared reflectance spectroscopic (NIRS) method was tested to determine the protein and oil contents of intact soybean [Glycine max (L.) Merr.] seeds. A total of 198 soybean calibration samples and 101 validation samples were used for NIRS equation development and validation, respectively. In the developed non-destructive NIRS equation for analysis of protein and oil contents, the most accurate equation was obtained at 2, 8, 6, 1(2nd derivative, 8 nm gap, 6 points smoothing, and 1 point second smoothing) and 2, 1, 20, 10 math treatment conditions with Standard Normal Variate and Detrend (SNVD) scatter correction method and entire spectrum (400-2500 nm) by using Modified Partial Least Squares (MPLS) regression, respectively. Validation of these non-destructive NIRS equations showed very low bias (protein: 0.060%, oil: -0.017%) and standard error of prediction (SEP, protein: 0.568 %, oil : 0.451 %) as well as high coefficient of determination ($R^2$, protein: 0.927, oil: 0.906). Therefore, these non-destructive NIRS equations can be applicable and reliable for determination of protein and oil content of intact soybean seeds, and non-destructive NIRS method could be used as a mass screening technique for selection of high protein and oil soybean in breeding programs.

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