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Journal articles on the topic 'Analysis of the infrared spectrum'

Author: Grafiati

Published: 2 June 2025

Last updated: 22 June 2025

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1

Čejka, J. "Vandenbrandeite, CuUO2(OH)4: Thermal analysis and infrared spectrum." Neues Jahrbuch für Mineralogie - Monatshefte 1994, no. 3 (1994): 112–20. http://dx.doi.org/10.1127/njmm/1994/1994/112.

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2

S., Bakkialakshmi, and Roy Jayoti. "INFRARED SPECTRUM ANALYSIS OF SOME FLAVONOIDS WITH HEMOGLOBIN." International Journal of Applied and Advanced Scientific Research 2, no. 2 (2017): 107–10. https://doi.org/10.5281/zenodo.851536.

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Infrared spectra of some flavonoids Rutin & Hesperidin were recorded. Infrared spectra of hemoglobin and hemoglobin with Rutin & with Hesperidin were also recorded. The spectral data of the complexes (Hemoglobin-Rutin and Hemoglobin-Hesperidin) were interpreted as indicating the near position valency band of the carbonyl group in relation to its position in Rutin and Hesperidin.

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3

Zhou, Hao, Pinhui Zhao, Qiang Xu, et al. "Study on Infrared Spectrum Analysis of Asphalt Aging Based on Full Spectrum Segmentation." Coatings 14, no. 12 (2024): 1505. http://dx.doi.org/10.3390/coatings14121505.

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Infrared spectroscopy is an effective method for studying asphalt aging. To improve the effectiveness of infrared spectroscopy in asphalt aging, this paper first performs preprocessing of the infrared spectral signals and divides the full spectrum into six segments. By quantitative analysis of the relation of noise and signals of different segments, a correlation model between noise and errors was established and a reasonable signal analysis range was determined. A stable method for describing the aging degree, which is based on the area change values of the infrared spectral curve over a wide wavelength range, was determined, and the aging model was established. Based on the relationship between PAV aging and natural aging, a model has been established to describe the relationship between the spectral area increase and aging in the asphalt pavement aging process. This model can be used to determine the actual service time of the asphalt pavement through infrared spectral analysis.

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4

Giorgianni, S., B. De Carli, R. Visinoni, and S. Ghersetti. "Infrared Spectrum and Vibrational Analysis of Bromochloromethane." Spectroscopy Letters 19, no. 10 (1986): 1207–14. http://dx.doi.org/10.1080/00387018608069320.

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5

Tsai, Cheng-Mu, Tzu-Chyang King, Yi-Chin Fang, Nai-Wie Hsueh, and Che-Wei Lin. "Optical Design for Novel Glasses-Type 3D Wearable Ophthalmoscope." Applied Sciences 9, no. 4 (2019): 717. http://dx.doi.org/10.3390/app9040717.

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This paper proposes a new optical design that will cooperate with 3D image technology, infrared spectrum technology, future medical diagnostics, the cloud, and big data analysis. We first conducted image recognition experiments to compare the pros and cons of 2D and 3D frameworks in order to make sure that the optical and mechanical framework of a glasses-type 3D ophthalmoscope would be a better choice. The experimental results showed that a 3D image recognition rate (90%) was higher than a 2D image recognition rate (84%), and hence the 3D mechanism design was selected. The glasses-type 3D ophthalmoscope design is primarily based on the specification of indirect ophthalmoscope requirements and two working spectrums: a near infrared and a visible spectrum. The design is a 2.5x magnification fixed focal telecentric relay system with a right-angle prism, which uses a large aperture to increase the amount of incident light (F/# = 2.0). As the infrared spectrums that have better transmittance towards human eye tissue are 965 nm and 985 nm, so that we took account of the visible spectrum and the near-infrared spectrum simultaneously to increase the basis of the physician’s diagnosis. In this research, we conclude that a wearable ophthalmoscope can be designed optically and mechanically with 3D technology, an infrared and a visible working spectrum and further, possibly in cooperation with the cloud and big data analysis.

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6

Zhang Yupeng, 张与鹏, 刘东 Liu Dong, 杨甬英 Yang Yongying, et al. "Spectrum Filter Performance Analysis on Near-Infrared High-Spectral-Resolution Lidar." Chinese Journal of Lasers 43, no. 4 (2016): 0414004. http://dx.doi.org/10.3788/cjl201643.0414004.

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7

Zilhadia, Zilhadia, Y. Anggraeni, Y. F. Apriyanti, M. Mustafidah, and I. Jaswir. "Analysis of lard in cod liver oil emulsion using FTIR spectroscopy combined principal component analysis." Food Research 8, no. 3 (2024): 424–31. http://dx.doi.org/10.26656/fr.2017.8(3).329.

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Cod liver oil (CLO) contains essential fatty acids and has a high price in the market. Therefore, CLO can be targeted for adulteration to increase economic profits. One of the substances used for adulteration of CLO is lard. This study aimed to analyze the spectral profile of lard and CLO in cod liver oil emulsion using Fourier transform infrared (FTIR) spectroscopy combined with principal component analysis (PCA). Lard and CLO were mixed with a range of concentrations of 0-100% used as the control. CLO emulsions were made with a composition of lard and CLO in concentrations similar to those of the control. To analyze the lard and CLO spectrum, lard and CLO were extracted from the emulsion using liquid-liquid extraction, and then the oil extracted from the emulsion was analyzed using FTIR spectroscopy and PCA. Fourier transform infrared spectrum absorption at region 1117–1098 cm-1 is specific to identifying the different spectrums of CLO and lard. The results of PCA showed that clustering between similar oil content and a combination of FTIR and PCA is effective in distinguishing the spectrum of lard and CLO in cod liver oil emulsion.

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8

Ni, Jiabao, Changjiang Ding, Yaming Zhang, et al. "Infrared Spectrum Analysis of Goji Berry during Electrohydrodynamic Drying." Journal of Spectroscopy 2020 (March 20, 2020): 1–9. http://dx.doi.org/10.1155/2020/4395425.

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This paper aims to study the effects of different needle spacings on goji berry structure during electrohydrodynamic (EHD) drying. The drying characteristics and the product quality parameters of goji berry during the drying process were measured. The infrared spectrum of the dried product was analyzed in detail. The results showed that the average drying rate of goji berry under different needle spacing conditions was significantly higher than that of the control group, and the average drying rate decreased with the increase of needle spacing. The change of needle spacing has great influence on goji berry polysaccharide content and flavonoid content. Fourier transform infrared spectroscopy showed that the infrared spectra of goji berry in each treatment group were generally similar. The first-order infrared spectra of different treatment groups were mainly different in the range of 1740 cm−1 and 2800 cm−1–2950 cm−1. The shape and intensity of the absorption peaks of the second derivative infrared spectrum of goji berry in different needle spacing treatment groups were different. When the needle spacing is 2 cm and 4 cm, there is a highly variant peak ratio and a low common peak ratio, which proves that the best drying effect is at 2 cm and 4 cm. It provides experimental and theoretical basis for the study of the application and drying mechanism of infrared spectroscopy in the field of electrohydrodynamic drying.

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9

Lin, Xiao Mei, Juan Wang, and Qing Hua Yao. "Wavelet Analysis of Near Infrared Spectral Data in the Application of Denoising." Applied Mechanics and Materials 48-49 (February 2011): 1358–62. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.1358.

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Spectrum signal may contain many peaks or mutations and noise also is not smooth white noise, to this kind of signal analysis, must do signal pretreatment, remove part of signal and extract useful part of signal.Based on the data of blood glucose near-infrared spectrum as the research object to explore the application of wavelet transform in the near infrared spectrum signal denoising, and through the simulation results show that using wavelet analysis of near infrared spectral data pretreatment than the traditional Fourier method can be higher precision of prediction.

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10

Polyansky, O. L., and A. R. W. McKellar. "Improved analysis of the infrared spectrum of D2H+." Journal of Chemical Physics 92, no. 7 (1990): 4039–43. http://dx.doi.org/10.1063/1.457817.

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11

Ogilvie, John F., Hiromichi Uehara, and Koui Horiai. "Analysis of the Infrared Spectrum of RbCl Vapor." Bulletin of the Chemical Society of Japan 73, no. 2 (2000): 321–27. http://dx.doi.org/10.1246/bcsj.73.321.

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12

Palencia, Víctor J., and Jina M. Martínez. "Spectral data transformation analysis by simple mathematical functions: Fourier transform infrared spectrum." Journal of Science with Technological Applications 3 (November 2017): 44–55. http://dx.doi.org/10.34294/j.jsta.17.3.23.

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13

Ma, Shun Bin. "Infrared Spectrum Test and Analysis of Regenerated Cellulose Fibers." Advanced Materials Research 671-674 (March 2013): 1954–57. http://dx.doi.org/10.4028/www.scientific.net/amr.671-674.1954.

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In this paper, the infrared spectrum of regenerated fibers have been tested and analyzed, such as Lyocell fiber, Modal fiber, regenerated cellulose fiber and Bamboo pulp fiber. Test results shown that: Lyocell fiber, Modal fiber, Bamboo pulp fiber are similar to viscose fiber in their infrared spectrogram, but the transmittance of characteristic absorption peaks of them are different.

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14

Jankovská, R., and K. Šustová. "Analysis of cow milk by near-infrared spectroscopy." Czech Journal of Food Sciences 21, No. 4 (2011): 123–28. http://dx.doi.org/10.17221/3488-cjfs.

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In this work, the major components (total solids, fat, protein, casein, urea nitrogen, lactose, and somatic cells) were determined in cow milk by near-infrared spectroscopy. Fifty calibration samples of milk were analysed by reference methods and by FT NIR spectroscopy in reflectance mode at wavelengths ranging from 4000 to 10&nbsp;000&nbsp;cm<sup>&ndash;1 </sup>with 100 scan. Each sample was analysed three times and the average spectrum was used for calibration. Partial least squares (PLS) regression was used to develop calibration models for the milk components examined. Determined were the highest correlation coefficients for total solids (0.928), fat (0.961), protein (0.985), casein (0.932), urea nitrogen (0.906), lactose (0.931), and somatic cells (0.872). The constructed calibration models were validated by full cross validation. The results of this study indicated that NIR spectroscopy is applicable for a rapid analysis of milk composition. &nbsp;

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15

Qasim, Razan Y., Yaman Q. Sadullah, Ammar Abd Aljabar Aziz, and Farah Younis Hamid. "Infrared spectrum of organic compounds: A review." International Journal of Multidisciplinary Research and Growth Evaluation 5, no. 4 (2024): 41–49. http://dx.doi.org/10.54660/ijmcr.2024.3.3.41-49.

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Infrared radiation (IR; or mid-infrared, miR; 4000-400 cm-1; 2500-25000 nm) has become one of the most powerful tools in the analysis process of chemicals. Due to its high molecular peculiarities, application to a wide range of samples, rapid measurement and unambiguity, infrared spectroscopy forms a powerful approach to clarifying qualitative and quantitative information from various types of biological and chemical substances. For these reasons, it has become a bioanalytical technique with diverse applications. This work aims to be a comprehensive and critical review of recent achievements in the field of biomolecular infrared spectroscopy and analysis.

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16

McColloug, M. L., and S. L. Mufson. "Analysis of Multiwavelength Observations of IC443." International Astronomical Union Colloquium 101 (1988): 403–6. http://dx.doi.org/10.1017/s025292110010274x.

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AbstractHigh resolution observations at radio, infrared, optical and X-ray wavelengths have been made (Mufson et al. 1986). The infrared spectrum determined from the IRAS observations has been fitted with models which include shock heated dust, infrared line emission, and radiatively heated dust emission. Numerical simulations of a supernova expanding into a uniform medium, which describe the X-ray and large scale radio emission, are presented.

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17

Salje, Ekhard K. H., Michael A. Carpenter, Thomas Malcherek, and Tiziana Boffa Ballaran. "Autocorrelation analysis of infrared spectra from minerals." European Journal of Mineralogy 12, no. 3 (2000): 503–19. http://dx.doi.org/10.1127/0935-1221/2000/0012-0503.

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18

Li, Wen Shi, H. Li, S. Lu, and Q. Hu. "Lie Detection Experiment Methodology: Infrared Image and Spectrum Analysis." Key Engineering Materials 381-382 (June 2008): 365–68. http://dx.doi.org/10.4028/www.scientific.net/kem.381-382.365.

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Infrared-based lie detection experiment methodology can open the human life window (0.6µm-16µm) through which the body spontaneous or active infrared responding images be gathered and analyzed by spectrum scoring in features of geography and computation. These raw images mainly load the indirect physiological, biochemical or direct brain evidences of cognitive lie and truth. Aiming at the mimic play card test, three tests of lie detection based on the medium or near infrared spectrum (NIRS) in four kinds of spectrum analysis are discussed. The instruments include the lock-in phase amplifier of Stanford University, TTM (Thermal Texture Maps) in US patent, and self-made auricular point NIRS (Chinese Jiangsu appraisal certificate No. 1017). The subjects’ signals sampling positions are on glabella, brows, abdomen or auricular point Antitragus No. 2. The spectrum analysis methods utilize the self-built feature extraction algorithms, the wavelet microscopy, and the bispetrum in validities of 92%, 100%, 80% and 80%. The results support the lie-truth law of “truth be the baseline of lie detection in view of brain power” (the statistical finding from review of 3D-MRI lie-detection reports included our work, subjects n = 4) for making foundation to the future lie detection 3D-SoC design.

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19

陈, 继超. "Infrared Spectrum Analysis of Different Parts of Houttuynia cordata." Advances in Analytical Chemistry 09, no. 02 (2019): 127–31. http://dx.doi.org/10.12677/aac.2019.92016.

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20

Pringle, W. C., R. C. Cohen, and S. M. Jacobs. "Analysis of collision induced far infrared spectrum of ethylene." Molecular Physics 62, no. 3 (1987): 661–68. http://dx.doi.org/10.1080/00268978700102461.

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21

Hildebrand, R. H., J. L. Dotson, C. D. Dowell, D. A. Schleuning, and J. E. Vaillancourt. "The Far‐Infrared Polarization Spectrum: First Results and Analysis." Astrophysical Journal 516, no. 2 (1999): 834–42. http://dx.doi.org/10.1086/307142.

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22

Masiello, Tony, Arthur Maki, and Thomas A. Blake. "Analysis of the high-resolution infrared spectrum of cyclopropane." Journal of Molecular Spectroscopy 255, no. 1 (2009): 45–55. http://dx.doi.org/10.1016/j.jms.2009.02.005.

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23

Gribov, L. A., O. B. Zubkova, and A. A. Sigarev. "Theoretical analysis of infrared spectrum of 9,10-anthraquinone molecule." Journal of Structural Chemistry 34, no. 1 (1993): 147–54. http://dx.doi.org/10.1007/bf00745414.

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24

Nguyen, Tam. "Full Spectrum Infrared Light Analysis Enhances Web Gauging Applications." AM&P Technical Articles 172, no. 6 (2014): 28–29. http://dx.doi.org/10.31399/asm.amp.2014-06.p028.

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Abstract Accurate multi-component thickness and moisture data is critical to the productivity and efficiency of producers of plastic films, extrusion coatings, blown films, and nonwoven fabrics. Collecting this data on production lines in real-time ensures that raw materials are not wasted and that all products meet relevant specifications. This article describes several different noncontact online analysis techniques, which primarily measure thickness by passing either nuclear or electromagnetic radiation through the web and measuring its absorption patterns via a detector on the other side of the material.

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25

Yan, Li Ping, Shu Li, Lai Gen Luo, Min Zhang, and Jing Xin Dong. "Measurement and Analysis of near Infrared Spectrum of Gasoline Vapor." Advanced Materials Research 571 (September 2012): 243–47. http://dx.doi.org/10.4028/www.scientific.net/amr.571.243.

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In the fiber-sensing gas detection system, characteristic of near infrared absorption spectrum of the detected gas is greatly significant. The volatilized gasoline vapor is a mixture rich in various components, of which near infrared absorption spectrum shall be determined by means of experimental measurement. In this paper, an experimental platform is constructed by analyzing absorption characteristic of liquid composition in gasoline within the range of near infrared spectrum, which achieves measurement of the volatilized gasoline vapor with different concentration. In addition, reliability of this measurement method is inspected, a comparison between features of absorption spectrograms of liquid and gas is made, and linear relation of absorbance and concentration of gasoline vapor is verified. The result shows that the experimental data is acceptable and may be used as the basis of further analysis and for design of the online detecting system of gasoline vapor concentration in the hazardous environment.

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26

Li, Yongxiang, Tianzheng Wang, Hui Yuan, Gang Yang, and Na Zhang. "Study on Application of Infrared Spectrum Technology in Power Equipment." MATEC Web of Conferences 260 (2019): 02010. http://dx.doi.org/10.1051/matecconf/201926002010.

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In this paper, the application of infrared spectrum acquisition technology in power equipment is studied. Infrared spectrum identification and analysis technology and fault diagnosis technology can monitor and analyze the operation parameters of important equipment in real time, so as to improve the work efficiency of substation staff and achieve higher economic benefits. Therefore, infrared spectrum technology has great practical value and application prospect in power equipment.

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27

БОРКОВ, Ю. Г., О. Н. СУЛАКШИНА, В. И. СЕРДЮКОВ, and Л. Н. СИНИЦА. "ANALYSIS OF 14N18O SPECTRUM IN THE 5200-5500 CM-1 INFRARED SPECTRAL REGION." Optika atmosfery i okeana 36, no. 10(417) (2023): 799–806. http://dx.doi.org/10.15372/aoo20231002.

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Впервые зарегистрирован спектр поглощения молекулы 14N18O в области 5200-5500 см-1 с помощью Фурье-спектрометра Bruker IFS 125M со спектральным разрешением 0,0056 см-1. Анализ спектра позволил обнаружить колебательно-вращательные линии полосы 3-0 основных переходов в электронном состоянии Х2П молекулы 14N18O. Для основных переходов 2Π1/2 - 2Π1/2 и 2Π3/2 - 2Π3/2 зарегистрировано 102 положения линий Λ-дублетов в трех ветвях. Для 61 разрешенного дублета определены положения и относительные интенсивности каждой компоненты дублета. Максимальное вращательное квантовое число J = 29,5. Найденные экспериментальные положения линий в полосе 3-0 подтвердили рассчитанные данные, приведенные в базе данных HITRAN. Проведена обработка частот зарегистрированных переходов, взвешенных в соответствии с экспериментальными погрешностями, и определены спектроскопические постоянные для колебательного состояния v = 3. С найденными спектроскопическими постоянными выполнены предсказательные расчеты волновых чисел вращательных уровней колебательного состояния v = 3 до J = 35,5 и, соответственно, частот переходов в колебательных полосах 3-3 и 3-0 для электронных состояний 2Π1/2 и 2Π3/2. Результаты расчетов показали согласие с данными, приведенными в HITRAN, в пределах указанной в базе данных погрешности. The absorption spectrum of 14N18O molecule in the 5200-5500 cm-1 range was recorded for the first time using a Bruker IFS 125M Fourier spectrometer with a spectral resolution of 0.0056 cm-1. The analysis of the spectrum made it possible to detect the vibrational-rotational lines of 3-0 band of the main transitions in X2Π electronic state of 14N18O molecule. For the main transitions 2Π1/2 - 2Π1/2 and 2Π3/2 - 2Π3/2, 102 line positions of Λ-doublet in three branches were registered. For 61 resolved doublets, the positions and relative intensities of each component of a doublet were determined. The maximum value of the rotational quantum number J was 29.5. The found experimental line positions in 3-0 band confirmed the calculated data given in HITRAN database. The frequencies of registered transitions, weighted in accordance with experimental uncertainties, have been processed, and the spectroscopic constants for the vibrational state v = 3 been determined. With the found spectroscopic constants, we predicted the rotational energy values up to J = 35.5 for the vibrational state v = 3 and, accordingly, the transition frequencies in 3-3 and 3-0 vibrational bands for 2Π1/2 and 2Π3/2 electronic states. The calculations performed showed agreement with the data given in HITRAN within the error specified in this database.

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28

FRASCA, MARCO. "INFRARED ANALYSIS OF QUANTUM FIELD THEORIES." International Journal of Modern Physics A 22, no. 08n09 (2007): 1727–34. http://dx.doi.org/10.1142/s0217751x07036129.

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We show that for a λϕ4 theory having many components, the solution with all equal components in the infrared regime is stable with respect to our expansion given by a recently devised approach to analyze strongly coupled quantum field theory. The analysis is extended to a pure Yang–Mills theory showing how, in this case, the given asymptotic series exists. In this way, many components theories in the infrared regime can be mapped to a single component scalar field theory obtaining their spectrum.

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29

Villar-Hernández, Bartolo de Jesús, Nicolò Amalfitano, Alessio Cecchinato, Michele Pazzola, Giuseppe Massimo Vacca, and Giovanni Bittante. "Phenotypic Analysis of Fourier-Transform Infrared Milk Spectra in Dairy Goats." Foods 12, no. 4 (2023): 807. http://dx.doi.org/10.3390/foods12040807.

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The infrared spectrum of bovine milk is used to predict many interesting traits, whereas there have been few studies on goat milk in this regard. The objective of this study was to characterize the major sources of variation in the absorbance of the infrared spectrum in caprine milk samples. A total of 657 goats belonging to 6 breeds and reared on 20 farms under traditional and modern dairy systems were milk-sampled once. Fourier-transform infrared (FTIR) spectra were taken (2 replicates per sample, 1314 spectra), and each spectrum contained absorbance values at 1060 different wavenumbers (5000 to 930 × cm−1), which were treated as a response variable and analyzed one at a time (i.e., 1060 runs). A mixed model, including the random effects of sample/goat, breed, flock, parity, stage of lactation, and the residual, was used. The pattern and variability of the FTIR spectrum of caprine milk was similar to those of bovine milk. The major sources of variation in the entire spectrum were as follows: sample/goat (33% of the total variance); flock (21%); breed (15%); lactation stage (11%); parity (9%); and the residual unexplained variation (10%). The entire spectrum was segmented into five relatively homogeneous regions. Two of them exhibited very large variations, especially the residual variation. These regions are known to be affected by the absorbance of water, although they also exhibited wide variations in the other sources of variation. The average repeatability of these two regions were 45% and 75%, whereas for the other three regions it was about 99%. The FTIR spectrum of caprine milk could probably be used to predict several traits and to authenticate the origin of goat milk.

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30

Lee, Y. K., Y. Hannachi, C. Xu, L. Andrews, and L. Manceron. "Infrared Spectrum of Nickel−Monoethylene. An Infrared Argon Matrix and Normal Coordinate Analysis Study." Journal of Physical Chemistry 100, no. 27 (1996): 11228–34. http://dx.doi.org/10.1021/jp960292j.

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31

Van De Voort, Frederick R., Jacqueline Sedman, Gary Emo, and Ashraf A. Ismail. "Assessment of Fourier Transform Infrared Analysis of Milk." Journal of AOAC INTERNATIONAL 75, no. 5 (1992): 780–85. http://dx.doi.org/10.1093/jaoac/75.5.780.

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Abstract A Nicolet 510 Fourier transform infrared (FTIR) spectrometer was modified to perform IR milk analyses by incorporating a temperature-controlled 37 µm CaF2 flow cell and a homogenizer into the analytical system. The unit was evaluated for its ability to predict the chemical values of calibration milks, and its performance was compared with that of a commercial filter-based IR milk analyzer (Multispec MK1). Conventional dual-wavelength multiple regression methods and whole-spectrum multivariate analysis techniques (classical least squares and partial least squares) were also compared for their predictive capabilities. We found that the prototype FTIR unit met AOAC standards for milk analyses and performed as well as or better than the filter instrument. The macro-programming capability of the FTIR software, which enables the user to combine strings of FTIR commands and parameters into a single command, allowed automation of data processing. The whole-spectrum multivariate analysis methods were able to provide total solids data directly in addition to fat, protein, and lactose. On the basis of this evaluation, FTIR appears to be a viable alternative means for performing milk analyses.

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32

Dekys, Vladimír, Zuzana Stankovicova, Pavol Novak, and Ondrej Stalmach. "The contribution to the modal analysis using an infrared camera." MATEC Web of Conferences 157 (2018): 05003. http://dx.doi.org/10.1051/matecconf/201815705003.

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The paper deals with modal analysis using an infrared camera. The test objects were excited by the modal exciter with narrowband noise and the response was registered as a frame sequence by the high speed infrared camera FLIR SC7500. The resonant frequencies and the modal shapes were determined from the infrared spectrum recordings. Lock-in technology has also been used. The experimental results were compared with calculated natural frequencies and modal shapes.

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33

Zuxin, XU, WANG Xiao, LI Peng, and QIAO Jun. "Research on infrared imaging deblurring algorithm based on spectrum analysis." Journal of Applied Optics 45, no. 4 (2024): 751–58. http://dx.doi.org/10.5768/jao202445.0402004.

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34

Yu, Xiangyang, Yuliang Zhao, Linghong Yao, Shi Zhao, and Lingu. "Infrared temperature spectrum analysis of air conductor considering vibration factor." IOP Conference Series: Materials Science and Engineering 631 (November 7, 2019): 022085. http://dx.doi.org/10.1088/1757-899x/631/2/022085.

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35

Li, Yanfen, Chunmin Zhang, Dongdong Liu, et al. "CO2 retrieval model and analysis in short-wave infrared spectrum." Optik 127, no. 10 (2016): 4422–25. http://dx.doi.org/10.1016/j.ijleo.2016.01.144.

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36

Cohen, R. C., and W. C. Pringle. "Analysis of the collision induced far infrared spectrum of ethane." Spectrochimica Acta Part A: Molecular Spectroscopy 42, no. 2-3 (1986): 241–49. http://dx.doi.org/10.1016/0584-8539(86)80186-6.

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37

Kastner, S. O. "Re-analysis of an observed solar near-infrared eclipse spectrum." Solar Physics 143, no. 1 (1993): 197–200. http://dx.doi.org/10.1007/bf00619105.

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Mahouachi, Dorra, and Moulay A. Akhloufi. "Recent Advances in Infrared Face Analysis and Recognition with Deep Learning." AI 4, no. 1 (2023): 199–233. http://dx.doi.org/10.3390/ai4010009.

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Besides the many advances made in the facial detection and recognition fields, face recognition applied to visual images (VIS-FR) has received increasing interest in recent years, especially in the field of communication, identity authentication, public safety and to address the risk of terrorism and crime. These systems however encounter important problems in the presence of variations in pose, expression, age, occlusion, disguise, and lighting as these factors significantly reduce the recognition accuracy. To prevent problems in the visible spectrum, several researchers have recommended the use of infrared images. This paper provides an updated overview of deep infrared (IR) approaches in face recognition (FR) and analysis. First, we present the most widely used databases, both public and private, and the various metrics and loss functions that have been proposed and used in deep infrared techniques. We then review deep face analysis and recognition/identification methods proposed in recent years. In this review, we show that infrared techniques have given interesting results for face recognition, solving some of the problems encountered with visible spectrum techniques. We finally identify some weaknesses of current infrared FR approaches as well as many future research directions to address the IR FR limitations.

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Liu, Jingrui. "Review Of Near Infrared Spectrum Detection Based on Deep Learning." Highlights in Science, Engineering and Technology 57 (July 11, 2023): 101–7. http://dx.doi.org/10.54097/hset.v57i.9986.

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Near infrared spectroscopy technology has the characteristics of accurate analysis of material composition and characteristics, quantitative testing, non-destructive testing, and so on. With the progress of artificial intelligence and the development of deep learning technology, near-infrared spectroscopy detection systems based on deep learning algorithms have emerged, which include various typical methods and have achieved good application results in food safety monitoring, pollutant detection, and drug analysis. This article provides a systematic review of domestic and foreign literature, introducing the principles, characteristics, and development history of deep learning and near-infrared spectroscopy technology. It discusses the research significance of near-infrared spectroscopy detection based on deep learning. It also reviews the latest progress in deep learning based near-infrared spectroscopy related technologies, elaborates on the advantages, disadvantages, and applicable fields of the methods, and makes prospects and predictions for the future development trends in this field.

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Nisha, R. Nagori *1 Raju. A. Rathod 2. "DETECTION OF RECYCLABLE AND NON-RECYCLABLE PLASTIC BY SPECTROSCOPY ANALYSIS." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 6, no. 10 (2017): 310–13. https://doi.org/10.5281/zenodo.1012529.

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Plastic is widely used material all over the world. Use of plastic creates waste which is necessary to sort. Plastic waste must be sorted so as to recycle into its various types. This article presents idea of using microcontroller based near infrared spectroscopy system to sort the type of plastic waste. Near infrared spectroscopy is a spectroscopic method that uses the near infrared region of the electromagnetic spectrum of about 700nm to 2500 nm. A prototype model has been developed which is able to control LED’S (Various wavelengths) and detectors.

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Solomon, Peter R., Robert M. Carangelo, David G. Hamblen, and Philip E. Best. "Infrared Analysis of Particulates by FT-IR Emission/Transmission Spectroscopy." Applied Spectroscopy 40, no. 6 (1986): 746–59. http://dx.doi.org/10.1366/0003702864508421.

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In this paper we report on a new method for the on-line chemical characterization of gas-suspended particulate and liquid droplet streams. The method is a combination of emission and transmission (E/T) spectroscopy performed using a Fourier transform infrared (FT-IR) spectrometer and a cell which allows analysis of room-temperature particulates surrounded by hot walls. The method was based on the discovery that the spectrum of radiation coming from such particles contained structure corresponding to the infrared absorption spectrum of the particulates. It was determined that the observed energy was wall radiation which reaches the detector after refraction by, and transmission through the particles. The shape of the observed spectrum relative to that of the wall spectrum is reduced at the absorption bands of the particulates. The general concepts of the E/T method were validated by samples with sizes varying from a few to several hundred microns with varying optical properties. For solids, excellent results were achieved for composition measurements. For a sample of known particle size, quantitative absorbance spectra were obtained from the E/T spectra with the use of a model based on ray optics. The spectra were in good quantitative agreement with absorbance spectra derived by the KBr pellet method for the same sample thickness. The E/T derived spectra were somewhat noisier than the KBr pellet spectra, but were free of Christiansen effect band distortions and scattering contributions. The E/T method has the additional advantage of requiring little or no sample preparation.

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Čejka, Jiři, Alexander Muck, Zdeněk Urbanec, and Jiři Čejka. "Thermal and infrared spectrum analyses of curite." Thermochimica Acta 93 (September 1985): 637–40. http://dx.doi.org/10.1016/0040-6031(85)85160-1.

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Mark, Howard L., and Peter R. Griffiths. "Analysis of Noise in Fourier Transform Infrared Spectra." Applied Spectroscopy 56, no. 5 (2002): 633–39. http://dx.doi.org/10.1366/0003702021955196.

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The currently accepted theory of spectroscopic noise causes most spectroscopists to accept the statement that when the limiting noise source is constant detector noise (e.g., as in mid- and near-IR spectroscopy) the noise of a transmittance spectrum is also constant, and independent of the sample transmittance. A careful examination of the effect of noise on spectra, however, reveals that most of the previous derivations have neglected the effect of noise in the reference reading on the noise content of the spectra. The consequences range from the fact that even with constant detector noise, the error of a transmittance spectrum is NOT constant, to the fact that the optimum value of sample transmittance, to obtain best relative precision, is not 36.8%, as usually stated, but 33%. We also present the results of experiments performed to distinguish between the results predicted by the two theories and to verify that taking the reference noise into account does, in fact, make a difference. “The trouble with the world is not that people know too little, it's that they know so many things that ain't so.” (Mark Twain)

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Lodder, Robert A., and Gary M. Hieftje. "Subsurface Image Reconstruction by Near-Infrared Reflectance Analysis." Applied Spectroscopy 42, no. 2 (1988): 309–12. http://dx.doi.org/10.1366/0003702884428194.

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A method is described for reconstructing decorative images concealed by layers of overcoatings. The method employs a nonparametric multivariate algorithm and a cellular-automaton construct to convert the near-infrared spectrum of a surface into digital images of the surface layers. The technique is potentially applicable to the restoration of historic buildings where aging, previous restoration attempts, and even political considerations have resulted in the alteration of the original historic surfaces.

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Whitfield, Richard G., Mark E. Gerger, and Robert L. Sharp. "Near-Infrared Spectrum Qualification via Mahalanobis Distance Determination." Applied Spectroscopy 41, no. 7 (1987): 1204–13. http://dx.doi.org/10.1366/0003702874447572.

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The use of near-infrared reflectance analysis (NIRA) for the quantitation of components of complex mixtures is well established. The lack of qualitative feedback in this approach is a major drawback. In view of this, it is believed that qualitative evaluation of the sample spectrum is also necessary for routine application of the NIRA technique. A method for qualifying a spectrum for application of a quantitative equation is described. The method involves generation of a quantitative equation, followed by the development of a qualitative equation based on the Mahalanobis distance algorithm, which is used to determine if the spectrum is suitable for analysis. This approach is demonstrated for the determination of lincomycin in an agricultural premix. The determination of proper control limits on the Mahalanobis distance is discussed. The improvement in precision obtained with the use of spectral selection is reviewed.

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Bai, Peng, Yan Li, and Peng Liu. "SVM Analysis Method for Infrared Spectra of Mixed Gas." Applied Mechanics and Materials 58-60 (June 2011): 1681–84. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.1681.

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In order to solving the problem that the mass samples of mixed gas spectra data samples being unable to obtain, characteristic absorption spectrum line of the component gas for mixed gas being overlap, and the problem of randomness of component concentration distribution for mixed gas and so on, support vector machine is introduced for the infrared spectra analysis for the mixed gas. Key technologies as feature selection of spectra data samples, data preprocessing, SVM calibration model parameters optimization and level structure for spectrum analysis of a mixed gas is proposed in the paper. The influence of above-mentioned four key technologies to the analysis results is discussed by using experimental means. The experimental result shows that with adoption of the key technologies, the maximum absolute error of component concentration analysis for the mixed gas is 2.93%, and the maximum average absolute error is of 0.73%. The method can also be used for infrared spectra analysis for other mixed gas, and it has practical application value.

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Hang, Yin. "The Degradation Features of Ancient Lu Embroidery Fabric." Advanced Materials Research 422 (December 2011): 505–8. http://dx.doi.org/10.4028/www.scientific.net/amr.422.505.

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The present study focus on the degradation features of ancient Lu Embroidery have been discussed from the molecule structure of protein via the infrared spectrum and XRD analysis. The ancient Lu Embroidery has N-H feature absorb peak at wavenumber of 3300 in the infrared spectrum. The XRD analysis of ancient Lu Embroidery fabric shows that the peptide in the un-crystallization can be depredated quickly and the crystallization is relative slow.

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Xie, Busheng, Wenfei Mao, Boqi Peng, Shengyu Zhou, and Lixin Wu. "Thermal-Infrared Spectral Feature Analysis and Spectral Identification of Monzonite Using Feature-Oriented Principal Component Analysis." Minerals 12, no. 5 (2022): 508. http://dx.doi.org/10.3390/min12050508.

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Rock spectral analysis is an important research field in hyperspectral remote sensing information processing. Compared with the spectra in the short-wave infrared and visible–near-infrared regions, the emittance spectrum of rocks in the thermal infrared (TIR) region is highly significant for identifying some major rock-forming minerals, including feldspar, biotite, pyroxene and hornblende. Even for the same rock type, slight differences in mineral composition generally result in varying spectral signatures, undoubtedly increasing the difficulty in discriminating rock types on the Earth’s surface via TIR spectroscopy. In this study, amounts of monzonite samples from different regions were collected in the central part of Hunan Province, China, and emission spectra at 8–14 μm were measured using a portable thermal infrared spectrometer. The experimental result illustrates 13 remarkable feature positions for all the monzonite samples from different geological environments. Furthermore, by combining the extracted features with the principal component analysis (PCA) method, feature-oriented PCA was applied to establish a model for identifying monzonite accurately and quickly without performing spectral library matching and spectral deconvolution. This study provides an important method for rock type identification in the TIR region that is helpful for the rock spectral analysis, geological mapping and pixel unmixing of remote sensing images.

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Gao Sun, Mei Lin, Ping Wu, Kai Li, and Zhen Hua Gen. "Application of Ant Colony Algorithm in Plant Leaves Classification Based on Infrared Spectroscopy Analysis." Key Engineering Materials 633 (November 2014): 503–6. http://dx.doi.org/10.4028/www.scientific.net/kem.633.503.

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Intelligent classification is realized according to different components of featured information included in near infrared spectrum data of plants. The core of this theory is to research applications of ant colony algorithm in spectral analysis of plant leaves through theories and experiments. In aspect of theoretical exploration, the built-in function of clustering algorithm is used to compress and process data. In aspect of experimental research, the near infrared diffuse emission spectrum curves of the leaves of Cinnamomum camphora and Acer saccharum Marsh in two groups, which have 75 leaves respectively. Then, the obtained data are processed using ant colony algorithm and the same leaves can be classified as a class by ant colony clustering algorithm. Finally, the two groups of data are classified into two classes. Our results show the distinguishability can be 100%. Keywords:Near infrared spectroscopy; ant colony algorithm; clustering algorithm; signal processing

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Nakamura, Takahiro, Toshiaki Kawamura, Koh-ichi Mochiki, and Taichi Michikawa. "Development of a plastic discriminator based on near infrared spectrum analysis." IEEJ Transactions on Electronics, Information and Systems 122, no. 10 (2002): 1779–85. http://dx.doi.org/10.1541/ieejeiss1987.122.10_1779.

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