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Mead, James B. "Comparison of Meteorological Radar Signal Detectability with Noncoherent and Spectral-Based Processing." Journal of Atmospheric and Oceanic Technology 33, no. 4 (April 2016): 723–39. http://dx.doi.org/10.1175/jtech-d-14-00198.1.
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AbstractDetection of meteorological radar signals is often carried out using power averaging with noise subtraction either in the time domain or the spectral domain. This paper considers the relative signal processing gain of these two methods, showing a clear advantage for spectral-domain processing when normalized spectral width is less than ~0.1. A simple expression for the optimal discrete Fourier transform (DFT) length to maximize signal processing gain is presented that depends only on the normalized spectral width and the time-domain weighting function. The relative signal processing gain between noncoherent power averaging and spectral processing is found to depend on a variety of parameters, including the radar wavelength, spectral width, available observation time, and the false alarm rate. Expressions presented for the probability of detection for noncoherent and spectral-based processing also depend on these same parameters. Results of this analysis show that DFT-based processing can provide a substantial advantage in signal processing gain and probability of detection, especially when the normalized spectral width is small and when a large number of samples are available. Noncoherent power estimation can provide superior probability of detection when the normalized spectral width is greater than ~0.1, especially when the desired false alarm rate exceeds 10%.
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Minty, Brian R. S. "Multichannel models for the estimation of radon background in airborne gamma‐ray spectrometry." GEOPHYSICS 63, no. 6 (November 1998): 1986–96. http://dx.doi.org/10.1190/1.1444492.
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Adequate background correction is a crucial step in processing airborne gamma‐ray spectrometric data because any errors are amplified during subsequent processing procedures. Two multichannel models for the estimation of atmospheric radon background are proposed. The spectral‐ratio method uses the relative heights of uranium (U) series photopeaks to estimate the contribution of atmospheric radon to observed spectra. The full‐spectrum method estimates the atmospheric radon contribution through the weighted least‐squares fitting of potassium (K), U, thorium (Th), and radon component spectra to the observed spectra. Both the spectral‐ratio and full‐spectrum methods are adequately calibrated through the estimation of component spectra from calibration experiments on the ground using radioactive calibration sources and wood to simulate the attenuation of gamma rays by air. The simulated heights used in these calibrations must be mapped onto real heights through calibration flights over an airborne calibration range. The spectral‐ratio method is also adequately calibrated using a heuristic calibration procedure. An iterative minimization method is used to find the optimum values of the calibration constants such that the radon background over suitable calibration lines is best removed.
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Blahovec, J., and S. Yanniotis. "'GAB' generalised equation as a basis for sorption spectral analysis." Czech Journal of Food Sciences 28, No. 5 (October 14, 2010): 345–54. http://dx.doi.org/10.17221/146/2009-cjfs.
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The transformed sorption isotherm (represented by the ratio of water activity and moisture content (d.b.) versus water activity) was approximated by polynomials of 2<sup>nd</sup>–<sup>6th</sup> order. It is shown that the relative derivative of the transformed equation expresses the deviation of the sorption isotherm from the linear relationship between the moisture content and water activity either to the sorption isotherm of the Lagmuir's type (the positive relative derivative) or to the sorption isotherm of the solution type (the negative relative derivative). The relative derivative plotted versus water activity then serves as a spectral indicator of the prevailing sorption mechanism. Spectral analysis is applied to sorption isotherms of potato and wheat starches and some fruits and vegetables. For starches, the differences in the spectral indicator between resorption and desorption as well as the effect of starch processing (gelatinisation and hydrolysis) on spectral analysis are discussed. The role of spectral analysis in the assessment of the prevailing sorption mechanism (surface vs solution sorption) is demonstrated for fruits and vegetables.
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Jödicke, Katrin, Robin Zirkler, Timo Eckhard, Werner Hofacker, and Bernd Jödicke. "High End Quality Measuring in Mango Drying through Multi-Spectral Imaging Systems." ChemEngineering 4, no. 1 (February 1, 2020): 8. http://dx.doi.org/10.3390/chemengineering4010008.
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In modern fruit processing technology, non-destructive quality measuring techniques are sought for determining and controlling changes in the optical, structural, and chemical properties of the products. In this context, changes inside the product can be measured during processing. Especially for industrial use, fast, precise, but robust methods are particularly important to obtain high-quality products. In this work, a newly developed multi-spectral imaging system was implemented and adapted for drying processes. Further it was investigated if the system could be used to link changes in the surface spectral reflectance during mango drying with changes in moisture content and contents of chemical components. This was achieved by recovering the spectral reflectance from multi-spectral image data and comparing the spectral changes with changes of the total soluble solids (TSS), pH-value and the relative moisture content xwb of the products. In a first step, the camera was modified to be used in drying, then the changes in the spectra and quality criteria during mango drying were measured. For this, mango slices were dried at air temperatures of 40–80 °C and relative air humidities of 5%–30%. Samples were analyzed and pictures were taken with the multi-spectral imaging system. The quality criteria were then predicted from spectral data. It could be shown that the newly developed multi-spectral imaging system can be used for quality control in fruit drying. There are strong indications as well, that it can be employed for the prediction of chemical quality criteria of mangoes during drying. This way, quality changes can be monitored inline during the process using only one single measuring device.
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Dong, Chun Hong, Jun Li, Ying Fan Liu, Shao Wei Zhao, and Guo Qing Wang. "Dependent Component Analysis and its Applications for Estimation of Source Ultraviolet Spectral Profiles and Characterization of Processing Batch for Preparation of Radix scutellariae." Advanced Materials Research 781-784 (September 2013): 30–34. http://dx.doi.org/10.4028/www.scientific.net/amr.781-784.30.
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Dependent component analysis (DCA), which is an extension of independent component analysis (ICA) for blind source separation (BSS) and requires no assumption on the distributions of the sources, was used to directly estimate source spectral profiles from ultraviolet spectra (UV) of mixtures. By simply assuming that the sources are dependent only through their variances and have temporal correlations, variance DCA was established. The efficiency of DCA for estimation of source UV spectral profiles was qualified by synthetic mixed UV data. It was shown that the estimation efficiency of DCA is better than that of FastICA when the sources are seriously overlapped. Then the DCA was used to directly estimate source spectral profiles from UV data that were measured at different steaming periods during the processing procedure batch for preparation of radix scutellariae. The estimated dependent components (DCs) and their variations of relative concentrations were used to characterize the processing batch. The results show that the estimated DCs are corresponding to sterol and flavonoid compounds, respectively. By inspection of the change trends of the estimated DCs, the endpoint of the processing batch was determined as 55 min, which is more accurate than that it should be located in 30~60 min by traditional sensory analysis. DCA provides an alternative approach for estimation of source spectral profiles from the overlapped spectral signals, and UV-DCA can be used as a novel way for characterization of the traditional Chinese medicines processing procedure.
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Omberg, Kristin M., Jill C. Osborn, Shuliang L. Zhang, James P. Freyer, Judith R. Mourant, and Jon R. Schoonover. "Raman Spectroscopy and Factor Analysis of Tumorigenic and Non-Tumorigenic Cells." Applied Spectroscopy 56, no. 7 (July 2002): 813–19. http://dx.doi.org/10.1366/000370202760171464.
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Raman spectra, measured for viable suspensions of M1 and MR1 cells, demonstrate spectral differences correlating with an increased protein and phospholipid content relative to DNA in the MR1 cells. The M1 and MR1 cell lines consist of rat fibroblast cells that have been transfected with a gene causing immortality, and the MR1 line has been further transfected with a gene causing tumor formation. The cell suspensions were prepared from monolayer cultures in the same phase of growth and remained viable throughout the experiment. The Raman data have been further examined by principal factor analysis with two approaches, (1) a constrained analysis to provide a relative contribution to the Raman data from cellular components, and (2) analysis of differences in the raw data files of the two cell lines. Utilizing the constrained principal factor analysis for the two cell lines analyzed separately provides a measure of the relative contribution of protein, lipid, DNA, RNA, and buffer to the cell Raman spectra. Factor analysis of M1 and MR1 Raman spectra analyzed together demonstrates that the two cell lines can be differentiated by Raman spectroscopy with no prior spectral processing.
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Hamilton, Victoria E., Christopher W. Haberle, and Thomas G. Mayerhöfer. "Effects of small crystallite size on the thermal infrared (vibrational) spectra of minerals." American Mineralogist 105, no. 11 (November 1, 2020): 1756–60. http://dx.doi.org/10.2138/am-2020-7602.
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Abstract The thermal infrared (TIR, or vibrational) emission spectra of a suite of synthetic Mg-Fe olivines exhibit notable differences from their natural igneous counterparts in terms of their band shapes, relative depths, and reduced shifts in some band positions with Mg-Fe solid solution. Comparable reflectance spectra acquired from olivine-dominated matrices and fusion crusts of some carbonaceous chondrite meteorites exhibit similar deviations. Here we show that these unusual spectral characteristics are consistent with crystallite sizes much smaller than the resolution limit of infrared light. We hypothesize that these small crystallites denote abbreviated crystal growth and also may be linked to the size of nucleation sites. Other silicates and non-silicates, such as carbonates, exhibit similar spectral behaviors. Because the spectra of mineral separates are commonly used in the modeling and analysis of comparable bulk rock, meteorite, and remote sensing data, understanding these spectral variations is important to correctly identifying the minerals and interpreting the origin and/or secondary processing histories of natural materials.
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Chiba, Toru, Yoshimi Obara, Masaharu Murata, and Tomohiko Akahoshi. "Advanced multispectral image-processing endoscopy system for visualizing two-dimensional hemoglobin saturation and relative hemoglobin concentration." Endoscopy International Open 07, no. 11 (October 22, 2019): E1442—E1447. http://dx.doi.org/10.1055/a-0990-9189.
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Abstract Background and study aims The association of tumor hypoxia and vascularization with malignant progression is recognized, and detection by measuring tissue hemoglobin (Hb) saturation and concentration has attracted attention. In this study, we designed a simple algorithm and multispectral image-processing endoscopy system to map relative Hb concentration and Hb saturation for detection of tumors in small animal viscera in vivo. Materials and methods We designed and validated an optical filter-equipped endoscope system for two-dimensional visualization of Hb concentration and saturation maps and used it in a real-time video examination. A simplified method based on spectral data capture and analysis of defuse reflection of mucosa, including image capture and data processing of the spectral features of Hb oxygenation, was developed. Results An Hb saturation calibration curve was obtained. Then, differences in oxygenation levels between normal mucosa and in vivo tumors in a small animal model were determined by using the new method and endoscope system. Conclusions A multispectral image-processing endoscopic system with a mapping frame rate comparable to that of white light imaging systems (7.5 frames/second) was developed.
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Jiang, Eric Y., William J. McCarthy, David L. Drapcho, and Richard A. Crocombe. "Generalized Two-Dimensional Fourier Transform Infrared Photoacoustic Spectral Depth-Profiling Analysis." Applied Spectroscopy 51, no. 11 (November 1997): 1736–40. http://dx.doi.org/10.1366/0003702971939442.
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This paper reports the first application of a generalized two-dimensional (G2D) correlation method in photoacoustic spectral depth-profiling analysis of laminate/heterogeneous samples. In this method, photoacoustic magnitude spectra at different modulation frequencies are used to generate two-dimensional (2D) correlation spectra. The relative spatial origins of correlated signals are then determined from the signs of the corresponding contours. The unique features and advantages of this technique over previously reported depth-profiling methods are demonstrated and discussed. These include simplification of step-scan photoacoustic phase-modulation experiments as well as 2D correlation-analysis rules, avoidance of phase-related negative-band ambiguities, and enhancement of both spectral and depth resolutions, etc. The recently developed software-based digital signal-processing (DSP) technique for step-scan photoacoustic measurements offers an efficient means (sampling-depth multiplexing advantage) to collect within a single scan all necessary data for this type of 2D correlation analysis. Index Headings: Photoacoustic; PAS; Two-dimensional; Step-scan; FT-IR; Depth profiling; Polymer films; DSP.
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Bauer, Jacob Renzo, Arnoud A. Bruins, Jon Yngve Hardeberg, and Rudolf M. Verdaasdonk. "A Spectral Filter Array Camera for Clinical Monitoring and Diagnosis: Proof of Concept for Skin Oxygenation Imaging." Journal of Imaging 5, no. 8 (July 26, 2019): 66. http://dx.doi.org/10.3390/jimaging5080066.
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The emerging technology of spectral filter array (SFA) cameras has great potential for clinical applications, due to its unique capability for real time spectral imaging, at a reasonable cost. This makes such cameras particularly suitable for quantification of dynamic processes such as skin oxygenation. Skin oxygenation measurements are useful for burn wound healing assessment and as an indicator of patient complications in the operating room. Due to their unique design, in which all pixels of the image sensor are equipped with different optical filters, SFA cameras require specific image processing steps to obtain meaningful high quality spectral image data. These steps include spatial rearrangement, SFA interpolations and spectral correction. In this paper the feasibility of a commercially available SFA camera for clinical applications is tested. A suitable general image processing pipeline is proposed. As a ’proof of concept’ a complete system for spatial dynamic skin oxygenation measurements is developed and evaluated. In a study including 58 volunteers, oxygenation changes during upper arm occlusion were measured with the proposed SFA system and compared with a validated clinical device for localized oxygenation measurements. The comparison of the clinical standard measurements and SFA results show a good correlation for the relative oxygenation changes. This proposed processing pipeline for SFA cameras shows to be effective for relative oxygenation change imaging. It can be implemented in real time and developed further for absolute spatial oxygenation measurements.
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Der, Z. A., M. R. Hirano, and R. H. Shumway. "Coherent processing of regional signals at small seismic arrays." Bulletin of the Seismological Society of America 80, no. 6B (December 1, 1990): 2161–76. http://dx.doi.org/10.1785/bssa08006b2161.
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Abstract Regional arrivals, similarly to short-period teleseismic P waves, have a spectral structure that the Fourier transforms of individual sensors at arrays for events located in limited source regions can be decomposed into source and site spectral factors. This structure has been demonstrated to be valid for Pn and Lg arrivals at NORESS. This property of regional arrivals can be exploited for: (a) Grouping events with respect to relative location; (b) Identifying events with differing source mechanisms; and (c) Finding differences in the source time functions between closely spaced events. Potentially useful techniques for accomplishing such analyses consist of computing site-averaged interevent coherences, interevent and intersite equalization methods combined with correlation techniques. The advantage of such approaches is that we need not know much about the propagation characteristics (Green's functions) along the paths to an array.
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Yang, Jeong-Gyu, and Hee-Duk Park. "Real Time Relative Radiometric Calibration Processing of Short Wave Infra-Red Sensor for Hyper Spectral Imager." Journal of the Korea Society of Computer and Information 21, no. 11 (November 30, 2016): 1–7. http://dx.doi.org/10.9708/jksci.2016.21.11.001.
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Gandour, Jack, Donald Wong, Mark Lowe, Mario Dzemidzic, Nakarin Satthamnuwong, Yunxia Tong, and Xiaojian Li. "A Cross-Linguistic fMRI Study of Spectral and Temporal Cues Underlying Phonological Processing." Journal of Cognitive Neuroscience 14, no. 7 (October 1, 2002): 1076–87. http://dx.doi.org/10.1162/089892902320474526.
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It remains a matter of controversy precisely what kind of neural mechanisms underlie functional asymmetries in speech processing. Whereas some studies support speech-specific circuits, others suggest that lateralization is dictated by relative computational demands of complex auditory signals in the spectral or time domains. To examine how the brain processes linguistically relevant spectral and temporal information, a functional magnetic resonance imaging study was conducted using Thai speech, in which spectral processing associated with lexical tones and temporal processing associated with vowel length can be differentiated. Ten Thai and 10 Chinese subjects were asked to perform discrimination judgments of pitch and timing patterns presented in the same auditory stimuli under two different conditions: speech (Thai) and nonspeech (hums). In the speech condition, tasks required judging Thai tones (T) and vowel length (VL); in the nonspeech condition, homologous pitch contours (P) and duration patterns (D). A remaining task required listening passively to nonspeech hums (L). Only the Thai group showed activation in the left inferior prefrontal cortex in speech minus nonspeech contrasts for spectral (T vs. P) and temporal (VL vs. D) cues. Thai and Chinese groups, however, exhibited similar fronto-parietal activation patterns in nonspeech hums minus passive listening contrasts for spectral (P vs. L) and temporal (D vs. L) cues. It appears that lower level specialization for acoustic cues in the spectral and temporal domains cannot be generalized to abstract higher order levels of phonological processing. Regardless of the neural mechanisms underlying low-level auditory processing, our findings clearly indicate that hemispheric specialization is sensitive to language-specific factors.
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Schläpfer, D., R. Richter, C. Popp, and P. Nygren. "DROACOR<sup>®</sup> REFLECTANCE RETRIEVAL FOR HYPERSPECTRAL MINERAL EXPLORATION USING A GROUND-BASED ROTATING PLATFORM." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2021 (June 28, 2021): 209–14. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2021-209-2021.
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Abstract. The acquisition of imaging spectroscopy data from ground based rotating stages is a novel approach which is more and more used in open pit mines for prospection and controlling. The special radiometric situation of such data sets asks for new processing approaches for geometric processing as well as for reflectance retrieval. Herein, a new method for atmospheric correction and relative reflectance retrieval is presented which is optimized for the special horizontal scanning situation by hyperspectral instruments from rotating ground based platforms. The method is implemented within the recently developed drone atmospheric correction framework DROACOR®. It combines a physical inversion of a radiative transfer code with semi-empirical correction approaches for illumination and spectral absorption. Sample results from two open pit mines show that mineral detection after reflectance retrieval allows the discrimination of iron minerals and that the retrieved spectra are well comparable to standard library spectra.
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Munira, Sirajum, James J. Dynes, Mofizul Islam, Fahad Khan, Theresa Adesanya, Tom Z. Regier, Kurt A. Spokas, and Annemieke Farenhorst. "Relative proportions of organic carbon functional groups in biochars as influenced by spectral data collection and processing." Chemosphere 283 (November 2021): 131023. http://dx.doi.org/10.1016/j.chemosphere.2021.131023.
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Anandan, V. K., C. J. Pan, T. Rajalakshmi, and G. Ramachandra Reddy. "Multitaper spectral analysis of atmospheric radar signals." Annales Geophysicae 22, no. 11 (November 29, 2004): 3995–4003. http://dx.doi.org/10.5194/angeo-22-3995-2004.
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Abstract. Multitaper spectral analysis using sinusoidal taper has been carried out on the backscattered signals received from the troposphere and lower stratosphere by the Gadanki Mesosphere-Stratosphere-Troposphere (MST) radar under various conditions of the signal-to-noise ratio. Comparison of study is made with sinusoidal taper of the order of three and single tapers of Hanning and rectangular tapers, to understand the relative merits of processing under the scheme. Power spectra plots show that echoes are better identified in the case of multitaper estimation, especially in the region of a weak signal-to-noise ratio. Further analysis is carried out to obtain three lower order moments from three estimation techniques. The results show that multitaper analysis gives a better signal-to-noise ratio or higher detectability. The spectral analysis through multitaper and single tapers is subjected to study of consistency in measurements. Results show that the multitaper estimate is better consistent in Doppler measurements compared to single taper estimates. Doppler width measurements with different approaches were studied and the results show that the estimation was better in the multitaper technique in terms of temporal resolution and estimation accuracy.
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Marang, Ian J., Patrick Filippi, Tim B. Weaver, Bradley J. Evans, Brett M. Whelan, Thomas F. A. Bishop, Mohammed O. F. Murad, Dhahi Al-Shammari, and Guy Roth. "Machine Learning Optimised Hyperspectral Remote Sensing Retrieves Cotton Nitrogen Status." Remote Sensing 13, no. 8 (April 7, 2021): 1428. http://dx.doi.org/10.3390/rs13081428.
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Hyperspectral imaging spectrometers mounted on unmanned aerial vehicle (UAV) can capture high spatial and spectral resolution to provide cotton crop nitrogen status for precision agriculture. The aim of this research was to explore machine learning use with hyperspectral datacubes over agricultural fields. Hyperspectral imagery was collected over a mature cotton crop, which had high spatial (~5.2 cm) and spectral (5 nm) resolution over the spectral range 475–925 nm that allowed discrimination of individual crop rows and field features as well as a continuous spectral range for calculating derivative spectra. The nominal reflectance and its derivatives clearly highlighted the different treatment blocks and were strongly related to N concentration in leaf and petiole samples, both in traditional vegetation indices (e.g., Vogelman 1, R2 = 0.8) and novel combinations of spectra (R2 = 0.85). The key hyperspectral bands identified were at the red-edge inflection point (695–715 nm). Satellite multispectral was compared against the UAV hyperspectral remote sensing’s performance by testing the ability of Sentinel MSI to predict N concentration using the bands in VIS-NIR spectral region. The Sentinel 2A Green band (B3; mid-point 559.8 nm) explained the same amount of variation in N as the hyperspectral data and more than the Sentinel Red Edge Point 1 (B5; mid-point 704.9 nm) with the lower 10 m resolution Green band reporting an R2 = 0.85, compared with the R2 = 0.78 of downscaled Sentinel Red Edge Point 1 at 5 m. The remaining Sentinel bands explained much lower variation (maximum was NIR at R2 = 0.48). Investigation of the red edge peak region in the first derivative showed strong promise with RIDAmid (R2 = 0.81) being the best index. The machine learning approach narrowed the range of bands required to investigate plant condition over this trial site, greatly improved processing time and reduced processing complexity. While Sentinel performed well in this comparison and would be useful in a broadacre crop production context, the impact of pixel boundaries relative to a region of interest and coarse spatial and temporal resolution impacts its utility in a research capacity.
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Dolomatova, Milana M., Mikhail Yu Dolomatov, Rashid I. Hairudinov, Ildar R. Hairudinov, and Rafael S. Manapov. "Predicting possibility of the fractional composition high-viscosity oils by the integral optical spectral characteristics." Butlerov Communications 60, no. 12 (December 31, 2019): 43–48. http://dx.doi.org/10.37952/roi-jbc-01/19-60-12-43.
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Express determination of the properties of hydrocarbon fractions is of great practical importance for operational control of operating modes of various technological equipment in petrochemical and oil refining industries. Currently, complex equipment is required to determine the fractional composition of high-viscosity oils. Analysis of the fractional composition on this equipment is a long process and takes several hours. Therefore, to solve the problem of Express oil quality control, the task of finding ways to quickly determine the fractional composition is urgent. The purpose of this study is to study the possibility of fractional composition of high-viscosity oils by integral spectral descriptors of optical absorption. Processing of data on the fractional composition of oil fractions and optical spectra in the UV and visible ranges by the least squares method established a linear relationship between the temperature parameters (the boiling point and the boiling point) and the integral parameters (the integral forces of the oscillator) of the optical absorption spectra. The adequacy of the results is confirmed by statistical data processing. The correlation coefficients for the start and end boiling point are 0.97. The absolute error of the calculations is 11.24, the relative error is from 3.90 and 3.64, respectively. These values are within the experimental error, which indicates the adequacy of the calculated data.
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Wollman, Indiana, Pablo Arias, Jean-Julien Aucouturier, and Benjamin Morillon. "Neural entrainment to music is sensitive to melodic spectral complexity." Journal of Neurophysiology 123, no. 3 (March 1, 2020): 1063–71. http://dx.doi.org/10.1152/jn.00758.2018.
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During auditory perception, neural oscillations are known to entrain to acoustic dynamics but their role in the processing of auditory information remains unclear. As a complex temporal structure that can be parameterized acoustically, music is particularly suited to address this issue. In a combined behavioral and EEG experiment in human participants, we investigated the relative contribution of temporal (acoustic dynamics) and nontemporal (melodic spectral complexity) dimensions of stimulation on neural entrainment, a stimulus-brain coupling phenomenon operationally defined here as the temporal coherence between acoustical and neural dynamics. We first highlight that low-frequency neural oscillations robustly entrain to complex acoustic temporal modulations, which underscores the fine-grained nature of this coupling mechanism. We also reveal that enhancing melodic spectral complexity, in terms of pitch, harmony, and pitch variation, increases neural entrainment. Importantly, this manipulation enhances activity in the theta (5 Hz) range, a frequency-selective effect independent of the note rate of the melodies, which may reflect internal temporal constraints of the neural processes involved. Moreover, while both emotional arousal ratings and neural entrainment were positively modulated by spectral complexity, no direct relationship between arousal and neural entrainment was observed. Overall, these results indicate that neural entrainment to music is sensitive to the spectral content of auditory information and indexes an auditory level of processing that should be distinguished from higher-order emotional processing stages. NEW & NOTEWORTHY Low-frequency (<10 Hz) cortical neural oscillations are known to entrain to acoustic dynamics, the so-called neural entrainment phenomenon, but their functional implication in the processing of auditory information remains unclear. In a behavioral and EEG experiment capitalizing on parameterized musical textures, we disentangle the contribution of stimulus dynamics, melodic spectral complexity, and emotional judgments on neural entrainment and highlight their respective spatial and spectral neural signature.
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Chen, Zhen, and Lan Cai. "Volume Water Content Prediction of Variable Bulk Density Soil Based on Spectral Characteristics." Applied Mechanics and Materials 321-324 (June 2013): 309–13. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.309.
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In order to eliminate effects of soil bulk density variance and soil properties difference on soil water content forecast precision, a method was proposed to forecast soil volume water content based on near-infrared spectroscopy. This paper investigated relationship between volume water content and near infrared spectral reflectance characteristics in 900-2500nm band, used spectral parameters and support vector machine to built quantitative prediction model for three type variable bulk density soil volume water content, normalized signal characteristics by relative dry soil characteristic vector, putted forward three further processing methods. It was used support vector machine (SVM) method to establish spectral characteristics inverting soil volume water content model of undisturbed soil, and model parameters were optimized by genetic algorithm, through predict error comparison, the final determination was that relative characteristics variation of first-order derivative signal as model input characteristic vector, GA-SVM model prediction had best effect and its forecast error was 1.7866.
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Lin, Junyi, Xiangyu Zhang, Kaiyun Liu, and Wenjie Zhang. "Emissivity Characteristics of Hydrocarbon Flame and Temperature Measurement by Color Image Processing." Energies 12, no. 11 (June 7, 2019): 2185. http://dx.doi.org/10.3390/en12112185.
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Non-gray radiation should be considered in the temperature and emissivity measurements of hydrocarbon flames. In this paper an improved ratio pyrometry by spectral analysis and color image processing is proposed. A Newton-type iterative method is utilized to analyze the spectrometer signals for the detection of monochromatic emissivity, and then the ratio pyrometry based on color image processing is corrected by the detected monochromatic emissivity without making approximations of the filter profiles of CCD camera. The experiments were conducted on a tubular heating furnace with coal gas and a propane flame. The spectral and spatial distributions of emissivity of hydrocarbon flame were detected, and the temperature measurement results at four conditions coincided with the thermocouple with relative errors less than 8.34%. The soot volume fractions in the turbulent diffusion hydrocarbon flame were approximately estimated from the detected emissivity, and are influenced by the O/C in the combustion. This study will provide a simple and effective method for the detection of non-gray radiation of hydrocarbon flames in the combustion industry.
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Tsai, Tsung-Heng, Meena Choi, Balazs Banfai, Yansheng Liu, Brendan X. MacLean, Tom Dunkley, and Olga Vitek. "Selection of Features with Consistent Profiles Improves Relative Protein Quantification in Mass Spectrometry Experiments." Molecular & Cellular Proteomics 19, no. 6 (March 31, 2020): 944–59. http://dx.doi.org/10.1074/mcp.ra119.001792.
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In bottom-up mass spectrometry-based proteomics, relative protein quantification is often achieved with data-dependent acquisition (DDA), data-independent acquisition (DIA), or selected reaction monitoring (SRM). These workflows quantify proteins by summarizing the abundances of all the spectral features of the protein (e.g. precursor ions, transitions or fragments) in a single value per protein per run. When abundances of some features are inconsistent with the overall protein profile (for technological reasons such as interferences, or for biological reasons such as post-translational modifications), the protein-level summaries and the downstream conclusions are undermined. We propose a statistical approach that automatically detects spectral features with such inconsistent patterns. The detected features can be separately investigated, and if necessary, removed from the data set. We evaluated the proposed approach on a series of benchmark-controlled mixtures and biological investigations with DDA, DIA and SRM data acquisitions. The results demonstrated that it could facilitate and complement manual curation of the data. Moreover, it can improve the estimation accuracy, sensitivity and specificity of detecting differentially abundant proteins, and reproducibility of conclusions across different data processing tools. The approach is implemented as an option in the open-source R-based software MSstats.
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Skylas, Daniel J., Mark P. Molloy, Robert D. Willows, Hayfa Salman, Christopher L. Blanchard, and Ken J. Quail. "Effect of Processing on Mungbean (Vigna radiata) Flour Nutritional Properties and Protein Composition." Journal of Agricultural Science 10, no. 11 (October 15, 2018): 16. http://dx.doi.org/10.5539/jas.v10n11p16.
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Pulses are traditionally processed prior to consumption, providing opportunities for modifying nutritional composition, dependant on the type of pulse and method used. In this study, we investigated the effect of whole seed, dehulling (dahl), germination and roasting on changes in mungbean flour nutritional properties, protein composition and relative protein abundance. Processed flours were analysed and compared for protein content, moisture, fat, ash, dietary fibre, total starch and amylose. Significant differences were imparted on dietary fibre content, with roasting and germination increasing the ratio of insoluble/soluble fibre as well as resistant starch. Comparative proteomic analysis resulted in a combined total of 539 protein identifications, searching against the Mungbean reference genome (NCBI Vigna radiata Annotation Release 100). Normalised spectral abundance factors were used as a measure of relative abundance and statistical analysis was applied (Students’ T-Test), where proteins with a p-value of < 0.05 considered significantly different. Processing imparted considerable changes to nutritional composition and should be further exploited for food applications. The comparative proteomic analyses carried out in this study proved useful for investigating the effect of processing on subsequent changes in protein composition and relative abundance.
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Fiori, C. E., and C. R. Swyt. "Is spectrometer resolution or system count rate performance more important in quantitative energy-dispersive x-ray microanalysis?" Proceedings, annual meeting, Electron Microscopy Society of America 50, no. 2 (August 1992): 1770–71. http://dx.doi.org/10.1017/s0424820100133485.
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Recently, important improvements have been achieved in both the resolution of energy dispersive spectrometers (EDS) and their count rate performance. Figure 1 is a plot of the count rate performance versus resolution for one EDS system. This particular system was chosen for our study because data were available for 6 pulse processing times. It can be seen that there is a direct trade off between count rate performance and energy resolution. The purpose of this study is to examine the consequences of the various pulse processor conditions for quantitative analysis. A number of analytical problems were simulated including various combinations of acquisition times, degree of spectral overlap, and relative peak heights.We provide here one example from the study, the analysis of PbS, which offers a difficult spectral overlap of the Pb M lines and the S K lines. We used the recently available computer program DTSA (Desk Top Spectrum Analyzer), to simulate 1000 spectra for each of the pulse processor resolution conditions shown in Figure 1. A linear least squares procedure was used to determine the peak areas.
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Dolce, G., F. Riganello, M. Quintieri, A. Candelieri, and D. Conforti. "Personal Interaction in the Vegetative State." Journal of Psychophysiology 22, no. 3 (January 2008): 150–56. http://dx.doi.org/10.1027/0269-8803.22.3.150.
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Background and purpose: Brain processing at varying levels of functional complexity and emotional reactions to relatives are anecdotally reported by the caregivers of patients in a vegetative state. In this study, computer-assisted machine-learning procedures were applied to identify heart rate variability changes or galvanic skin responses to a relative’s presence. Methods: The skin conductance (galvanic skin response) and heart beats were continuously recorded in 12 patients in a vegetative state, at rest (baseline) and while approached by a relative (usually the mother; test condition) or by a nonfamiliar person (control condition). The cardiotachogram (the series of consecutive intervals between heart beats) was analyzed in the time and frequency domains by computing the parametric and nonparametric frequency spectra. A machine-learning algorithm was applied to sort out the significant spectral parameter(s). For all patients, each condition (baseline, test, control) was characterized by the values of its spectral parameters, and the association between spectral parameters values and experimental condition was tested (WEKA machine-learning software). Results and comments: A galvanic skin response was obtained in two patients. The machine-learning procedure independently selected the nu_LF spectral parameter and attributed each nu_LF measure to any of the three experimental conditions. 69.4% of attributions were correct (baseline: 58%; test condition: 75%; control. 75%). In seven patients, attribution changed when the subject was approached by the test person; specifically, sequential shifts from baseline to test condition (“the Mom effect”) to control condition were identified in four patients (30.0%); the change from test to control was attributed correctly in seven patients (58%). The observation of heart rate changes tentatively attributable to emotional reaction in a vegetative state suggest residual rudimentary personal interaction, consistent with functioning limbic and paralimbic systems after massive brain damage. Machine-learning proved applicable to sort significant measure(s) out of large samples and to control for statistical alpha inflation.
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Qu, Yanhuai, Shuai Zhang, and Qingkai Han. "Comparison of Non-linear Signals Analysis Methods." MATEC Web of Conferences 232 (2018): 01014. http://dx.doi.org/10.1051/matecconf/201823201014.
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In modern engineering, linear is relative, while non-linear and non-stationary is absolute. There are many methods in non-linear signals processing. How to select a most suitable analysis method quickly for the nonlinear signal is particularly important, which can improve the signal processing efficiently. In this paper, three common analysis methods for nonlinear signals, Wavelet spectrum, Hilbert spectral analysis (HSA) and Poincaré mapping are researched and analyzed by some typical nonlinear signals from the complex electromechanical model test system. The effectiveness and application scopes of these approaches are obtained, which can provide a theoretical and practical basis for engineering application.
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Markelin, L., E. Honkavaara, R. Näsi, N. Viljanen, T. Rosnell, T. Hakala, M. Vastaranta, T. Koivisto, and M. Holopainen. "RADIOMETRIC CORRECTION OF MULTITEMPORAL HYPERSPECTRAL UAS IMAGE MOSAICS OF SEEDLING STANDS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W3 (October 19, 2017): 113–18. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w3-113-2017.
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Novel miniaturized multi- and hyperspectral imaging sensors on board of unmanned aerial vehicles have recently shown great potential in various environmental monitoring and measuring tasks such as precision agriculture and forest management. These systems can be used to collect dense 3D point clouds and spectral information over small areas such as single forest stands or sample plots. Accurate radiometric processing and atmospheric correction is required when data sets from different dates and sensors, collected in varying illumination conditions, are combined. Performance of novel radiometric block adjustment method, developed at Finnish Geospatial Research Institute, is evaluated with multitemporal hyperspectral data set of seedling stands collected during spring and summer 2016. Illumination conditions during campaigns varied from bright to overcast. We use two different methods to produce homogenous image mosaics and hyperspectral point clouds: image-wise relative correction and image-wise relative correction with BRDF. Radiometric datasets are converted to reflectance using reference panels and changes in reflectance spectra is analysed. Tested methods improved image mosaic homogeneity by 5&thinsp;% to 25&thinsp;%. Results show that the evaluated method can produce consistent reflectance mosaics and reflectance spectra shape between different areas and dates.
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Magendran, T., and S. Sanjeevi. "Processing and Analysis of Hyperspectral Fingerprints to Characterise Haematite of Singbhum Iron Ore Belt, Orissa, India." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (December 23, 2014): 1341–43. http://dx.doi.org/10.5194/isprsarchives-xl-8-1341-2014.
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The demand for iron ore has been increasing in the recent years, thereby requiring the adoption of fast and accurate approaches to iron ore exploration and its grade-assessment. It is in this context that hyperspectral sensing is deemed as a potential tool. This paper examines the potential of hyperspectral fingerprints in the visible, NIR and SWIR regions of the EMR to assess the grades of haematite of the western Singhbhum iron ore belt of Orissa, eastern India, in a rapid manner. Certain spectro-radiometric measurements and geochemical analysis were carried out and the results have been presented. From the spectral measurements, it is seen that the strength of reflectance and absorption at definite wavelength regions is controlled by the chemical composit ion of the iron ores. It is observed that the primary spectral characteristics of these haematites lie in the 650–750 nm, 850 to 900 nm and 2130–2230 nm regions. The laboratory based hyperspectral fingerprints and multiple regression analysis of spectral parameters and geochemical parameters (Fe% and Al2O3%) predicted the concentration of iron and alumina content in the haematite. A very strong correlation (R<sup>2</sup> = 0.96) between the spectral parameters and Fe% in the haematite with a minimum error of 0.1%, maximum error of 7.4% and average error of 2.6% is observed. Similarly, a very strong correlation (R<sup>2</sup> = 0.94) between the spectral parameters and Al2O3% in the iron ores with a minimum error of 0.04%, maximum error of 7.49% and average error of 2.5% is observed. This error is perhaps due to the presence of other components (SiO<sub>2</sub>, TiO<sub>2</sub>, P<sub>2</sub>O etc.) in the samples which can alter the degree of reflectance and hence the spectral parameters. Neural network based multi-layer perception (MLP) analysis of various spectral parameters and geochemical parameters helped to understand the relative importance of the spectral parameters for predictive models. The strong correlations (Iron: R<sup>2</sup> = 0.96; Alumina: R<sup>2</sup> = 0.94) indicate that the laboratory hyperspectral signatures in the visible, NIR and SWIR regions can give a better estimate of the grades of haematite in a rapid manner.
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Gao, S. "A Bayesian nonlinear inversion of seismic body-wave attenuation factors." Bulletin of the Seismological Society of America 87, no. 4 (August 1, 1997): 961–70. http://dx.doi.org/10.1785/bssa0870040961.
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Abstract It is a well-known fact that the uncertainties in measuring relative attenuation factors within a local or regional seismic network are usually high, due to noise of different kinds and unrealistic assumptions. Numerical experiments using nine synthetic seismograms, created using t* values ranging from 0.1 to 0.9 sec, reveal that the commonly used spectral ratio method is strongly affected by the selection of data processing parameters such as width of the spectral smoothing window, reference station, and so on. The numerical experiments demonstrate that a Bayesian nonlinear inversion approach that directly matches the spectra is better at finding the correct parameters used to generate the synthetic seismograms. The Bayesian inversion approach uses a priori information to simultaneously search for the t* values, the common spectrum for all the records from an event, and the near-receiver amplification factors by using all the recordings from an event. When z, the ratio of Gaussian noise to signal, ≦ 0.1, the spectral ratio and Bayesian methods yield similar results with mean t* measurement errors <0.05 sec. For 0.1 < z ≦ 0.8, the mean errors of the spectral ratio method are larger than 0.1 sec and in some cases as large as 0.6 sec, while those of the Bayesian method are less than 0.08 sec. Frequency-independent t* and near-receiver amplification factors are assumed. A multi-step procedure is proposed to reject records with a large misfit.
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Waddell, Walter H., Kimberly A. Benzing, Larry R. Evans, Syed K. Mowdood, David A. Weil, John M. McMahon, Robert H. Cody, and James A. Kinsinger. "Laser Mass Spectral Investigations of Rubber Compound Surface Species." Rubber Chemistry and Technology 64, no. 4 (September 1, 1991): 622–34. http://dx.doi.org/10.5254/1.3538577.
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Abstract Laser desorption mass spectrometry has proven a uniquely useful technique for the direct characterization of rubber-compound surface species. Mass spectra were obtained for intact molecular ions (M+) of organic chemical rubber additives such as the aromatic processing oil, and the aromatic antiozonant and antioxidants incorporated to protect the rubber. Molecular-weight information from the molecular ions and structural information from the fragmentation ions could be obtained without interference from the fragmentation peaks of the rubber backbone. Rubber compounding ingredients were also characterized by LDMS techniques. Differences in the structure of two carbon blacks were apparent, based upon the relative intensities of the various peaks present such as the significantly higher m/z 26 peak thought to be due to CN− compared to the m/z 24 peak thought to be due to C2−, and the peaks resulting from the presence of hydrogen atom(s) on the carbon clusters for the high NSA and DBPA black. Laser and thermal desorption mass spectral techniques provided complementary structural information, and when coupled with current analytical methods to characterize rubber compounds, can provide the necessary information to positively identify various organic species present on the surfaces of vulcanized rubber.
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Zhang, Li, Charles B. Theurer, Robert X. Gao, and David O. Kazmer. "Analytic Wavelet-Based Ultrasonic Pulse Differentiation for Injection Mold Cavity Pressure Measurement." Journal of Manufacturing Science and Engineering 128, no. 1 (July 20, 2005): 370–74. http://dx.doi.org/10.1115/1.2123048.
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A new signal-processing technique based on analytic wavelet transform has been developed for detecting and differentiating temporally overlapped ultrasonic pulse trains that carry spatially distributed pressure information across an injection mold cavity. Compared to conventional wavelets that have a constant relative bandwidth at all the scales, the analytic wavelets investigated in this paper feature variable relative bandwidth, making it possible to simultaneously match the frequency characteristics of the ultrasonic pulse trains transmitted from the mold-embedded pressure sensors. As a result, more accurate detection and differentiation of the temporal and spectral information embedded within the ultrasonic pulse trains could be achieved. Theoretical framework for the analytic wavelet transform was established, and a multichannel ultrasonic pulse detector based on the complex Morlet wavelet was designed and experimentally investigated. The results have confirmed the effectiveness of the new signal-processing technique for on-line pressure sensing for injection molding process monitoring.
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Nikanorov, Nikolai, and Alexey Artemov. "COMBINED METHOD OF CENTERING LENSES OF OPAQUE IN THE VISIBLE SPECTRUM OF MATERIALS." Interexpo GEO-Siberia 8 (2019): 269–78. http://dx.doi.org/10.33764/2618-981x-2019-8-269-278.
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The mixed method of optical components which is nontransparent in visual spectral range during frame processing is discussed. Theproposed method requires the following: one lens surface is positioned under mechanical control method and another lens surface is positioned under optical control method (collimation method) in floating holder. The article presents the comparison of the mixed method with centration method by two Zabelin tubes, and relative decentering measurements of lenses in frames centered by means of these methods.
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Sagaidachnyi, A. A., D. A. Usanov, A. V. Skripal, and A. V. Fomin. "Thermal imaging of the skin blood flow oscillations in extremities: modification of the spectral components." Regional blood circulation and microcirculation 14, no. 1 (March 30, 2015): 46–52. http://dx.doi.org/10.24884/1682-6655-2015-14-1-46-52.
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Objective. The aim of the study was description of the method of skin blood flow imaging via spectral processing of the dynamic thermograms of extremities. Materials and methods. The method realized by decomposition of the temperature signal into spectral components, modification of the spectral components and inverse transform of the spectral components into a new signal, which is considered as blood flow. Modification of spectral components was accomplished taking into account skin properties, and intended for the compensation of attenuation and time lag of temperature spectral components relative to blood flow components. Results. Blood flow maps of hands during arm cuff test have been demonstrated. Blood flow values calculated from the dynamic thermogram have been validated by photoplethysmography. The technique allows restoring of the blood flow oscillations at any point of the thermogram of the object. Benefits of thermal imaging of blood flow are the following: results are not depended from the ambient light, the method not critical to the camera angle, and blood flow maps can be registered both from the whole body and small areas. The method of blood flow imaging, in a long view, applicable for the monitoring of the skin microcirculation in progression and treatment of diabetic foot syndrome, Raynaud's syndrome, as well as burn, frostbite, mechanical injury, and atherosclerosis.
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Tian, Gao, Yan Yang, and Wang Qi. "Research of Radar Waveform Based on Pulse Position Jitter and Relative LPI Performance Analysis." Applied Mechanics and Materials 457-458 (October 2013): 1338–43. http://dx.doi.org/10.4028/www.scientific.net/amm.457-458.1338.
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The low probability of intercept (LPI) radar waveform is reflected in a lower pulse power and complex structure of the pulse series. The previous one ensures that it avoids being intercepted by the electronic measures system (ESM) carried by the goal; the latter makes it difficult for ESM to separate and identify. As for pulse position jitter pulse array, because of pulse position's random jitter in a specific pulse interval of the pulse repetition interval (PRI), the spectrum broadens and spectral density reduces, making it hard for the ESM to intercept. Meanwhile, because the waveform doesn't have a fixed PRI, it's also difficult to be sorted or identified Therefore pulse position jitter waveform is a rational LPI waveform. Combined with a design about the LPI radar signal waveform, this paper carries out a research on PRI jitter waveform, and provides a waveform generating and echo signal processing method; then the paper simulates the LPI characteristics and comes to a conclusion which has an important applying value .
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Morris, Michael D., Kenneth A. Christensen, and Nancy L. Bradley. "Raman imaging in the real world." Proceedings, annual meeting, Electron Microscopy Society of America 54 (August 11, 1996): 254–55. http://dx.doi.org/10.1017/s0424820100163733.
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Recent technological advances including high spectral resolution liquid-crystal tunable filters and high-transmission well-corrected imaging spectrographs have made Raman microscopy a practical technique for study of real-world chemical systems. With modem multivariate signal processing techniques, such as image reconstruction and principal components analysis (PCA) detailed information can be obtained from sets of relatively noisy images or spectra. In this talk we discuss techniques and results in two areas of materials chemistry: crystallization and freeze-drying mechanisms of alkali phosphates and strengthening mechanisms of glasses employed in dental restoration.We employ Raman microspectroscopy to elucidate the structure of aqueous phosphates in solutions ranging in concentration from dilute to supersaturated. PCA of the concentration-dependent spectra of dihydrogen phosphate solutions unambiguously demonstrates the presence of at least three species, monomer, dimer and trimer or short polymer (Figure 1). PCA resolves long-standing disputes over the number and relative concentration of dihydrogen phosphate species PCA can to identify the spectrally unresolved solution species near the surface of a growing dihydrogen phosphate crystal.
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Fiodоrtsev, R. V., A. R. Silie Cuenca, D. A. Kozhevnikov, V. M. Medina, and R. Delgado. "Application of Satellite Image Processing Methods for Hydrocarbon Field Search." Devices and Methods of Measurements 10, no. 4 (December 12, 2019): 373–81. http://dx.doi.org/10.21122/2220-9506-2019-10-4-373-381.
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The object of the study is software methods of the Earth surface images processing obtained from the VRSS-2 satellite to determine the spectral composition of the vegetation cover to detect the presence of carotenoids during prolonged exposure to hydrocarbons.The photosynthetic pigments of higher plants (chlorophylls, carotenoids and phytobiliproteins) were analyzed. In the chloroplasts of higher plants, chlorophyll and carotenoids are present in a ratio of about 3:1. The presence of hydrocarbons increases the amount of carotenoids. Carotenoids have absorption bands in the blue-violet region from 400 to 500 nm and a high reflection coefficient in the red-orange and yellow spectral regions, which corresponds to the multispectral MSS operating mode (B2) of the VRSS-2 satellite camera. An analysis of the vegetation growing in the study area of the Puerto Kumarebo settlement showed that the best indicator of the presence of hydrocarbons in the soil is Prosopis juliflora – CUJI with a deep root system of up to 50 m, growing in the study area.Using ENVI software, a comparative evaluation of the efficiency of photographs image processing was carried out using the normalized relative vegetation index (NDVI) and the structure-insensitive pigment index (SIPI) to detect changes in the color of green vegetation. It has been established that the SIPI index is more applicable for hydrocarbon search tasks. Moreover, the recorded index fluctuations in the area of uniform vegetation at the level of 2.5 % are characteristic of normal growing conditions and cannot serve as evidence of the presence of factors indicating the presence of hydrocarbons in the soil. For a more detailed assessment of the presence of carotenoids in the foliage and the presence of hydrocarbons in the soil, photographs with high optical resolution of objects on the surface are required.
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Tran, Hai-Tan, Emma Heading, and Brian W. H. Ng. "On the Slow-Time k-Space and its Augmentation in Doppler Radar Tomography." Sensors 20, no. 2 (January 16, 2020): 513. http://dx.doi.org/10.3390/s20020513.
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Doppler Radar Tomography (DRT) relies on spatial diversity from rotational motion of a target rather than spectral diversity from wide bandwidth signals. The slow-time k-space is a novel form of the spatial frequency space generated by the relative rotational motion of a target at a single radar frequency, which can be exploited for high-resolution target imaging by a narrowband radar with Doppler tomographic signal processing. This paper builds on a previously published work and demonstrates, with real experimental data, a unique and interesting characteristic of the slow-time k-space: it can be augmented and significantly enhance imaging resolution by signal processing. High resolution can reveal finer details in the image, providing more information to identify unknown targets detected by the radar.
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Nguyen, Lydia, Shraddha Shende, Daniel Llano, and Raksha Mudar. "EEG Measures of Value-Directed Strategic Processing in Older Adults With and Without Mild Cognitive Impairment." Innovation in Aging 4, Supplement_1 (December 1, 2020): 292–93. http://dx.doi.org/10.1093/geroni/igaa057.937.
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Abstract Value-directed strategic processing is important for daily functioning. It allows selective processing of important information and inhibition of irrelevant information. This ability is relatively preserved in normal cognitive aging, but it is unclear if mild cognitive impairment (MCI) affects strategic processing and its underlying neurophysiological mechanisms. The current study examined behavioral and EEG spectral power differences between 16 cognitively normal older adults (CNOA; mean age: 74.5 ± 4.0 years) and 16 individuals with MCI (mean age: 77.1 ± 4.3 years) linked to a value-directed strategic processing task. The task used five unique word lists where words were assigned high- or low-value based on letter case and were presented sequentially while EEG was recorded. Participants were instructed to recall as many words as possible after each list to maximize their score. Results revealed no group differences in recall of low-value words, but individuals with MCI recalled significantly fewer high-value words and total number of words relative to CNOA. Group differences were observed in theta and alpha bands for low-value words, with greater synchronized theta power for CNOA than MCI and greater desynchronized alpha power for MCI than CNOA. Collectively, these findings demonstrate that more effortful neural processing of low-value words in the MCI group, relative to the CNOA group, allowed them to match their behavioral performance to the CNOA group. Individuals with MCI appear to utilize more cognitive resources to inhibit low-value information and might show memory-related benefits if taught strategies to focus on high-value information processing.
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Choudhury, Sutanay, and V. Chandrasekar. "Wideband Reception and Processing for Dual-Polarization Radars with Dual Transmitters." Journal of Atmospheric and Oceanic Technology 24, no. 1 (January 1, 2007): 95–101. http://dx.doi.org/10.1175/jtech1958.1.
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Abstract Oversampling pulsed Doppler radar returns at a rate larger than the pulse bandwidth, whitening the range samples, and subsequent averaging has been pursued as a potential way to decrease the measured standard deviation of signal parameter estimates. It has been shown that the application of oversampling, whitening, and subsequent averaging improves the quality of reflectivity, mean velocity, and spectral width estimates in agreement with theory. Application of this procedure to a dual-polarization radar with dual transmitters is evaluated in this paper. Oversampled data collected from the Colorado State University (CSU)-University of Chicago–Illinois State Water Survey (CHILL) radar using a wideband receiver are analyzed to evaluate the performance of dual-polarization parameter estimators, such as differential reflectivity and differential phase. The negative impact of relative phase characteristics of the transmitted pulses in two polarizations on the copolar correlation, and subsequently on polarimetric parameter estimation, is analyzed. CSU-CHILL radar’s transmitted pulse sampling capability is used to evaluate the impact of the transmitted waveform’s mismatch on whitening and estimation.
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Kohonen, Kukka-Maaria, Pasi Kolari, Linda M. J. Kooijmans, Huilin Chen, Ulli Seibt, Wu Sun, and Ivan Mammarella. "Towards standardized processing of eddy covariance flux measurements of carbonyl sulfide." Atmospheric Measurement Techniques 13, no. 7 (July 22, 2020): 3957–75. http://dx.doi.org/10.5194/amt-13-3957-2020.
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Abstract. Carbonyl sulfide (COS) flux measurements with the eddy covariance (EC) technique are becoming popular for estimating gross primary productivity. To compare COS flux measurements across sites, we need standardized protocols for data processing. In this study, we analyze how various data processing steps affect the calculated COS flux and how they differ from carbon dioxide (CO2) flux processing steps, and we provide a method for gap-filling COS fluxes. Different methods for determining the time lag between COS mixing ratio and the vertical wind velocity (w) resulted in a maximum of 15.9 % difference in the median COS flux over the whole measurement period. Due to limited COS measurement precision, small COS fluxes (below approximately 3 pmol m−2 s−1) could not be detected when the time lag was determined from maximizing the covariance between COS and w. The difference between two high-frequency spectral corrections was 2.7 % in COS flux calculations, whereas omitting the high-frequency spectral correction resulted in a 14.2 % lower median flux, and different detrending methods caused a spread of 6.2 %. Relative total uncertainty was more than 5 times higher for low COS fluxes (lower than ±3 pmol m−2 s−1) than for low CO2 fluxes (lower than ±1.5 µmol m−2 s−1), indicating a low signal-to-noise ratio of COS fluxes. Due to similarities in ecosystem COS and CO2 exchange, we recommend applying storage change flux correction and friction velocity filtering as usual in EC flux processing, but due to the low signal-to-noise ratio of COS fluxes, we recommend using CO2 data for time lag and high-frequency corrections of COS fluxes due to the higher signal-to-noise ratio of CO2 measurements.
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Xu, Ze Min, and Yu Jing Sun. "Impact Analysis of Ultrahigh Pressure Treatment Pesticide Residues in Vegetables on near Infrared Spectroscopy Detection." Applied Mechanics and Materials 142 (November 2011): 46–49. http://dx.doi.org/10.4028/www.scientific.net/amm.142.46.
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In order to simplify the process of detecting pesticide residues in vegetables, reducing detection time to find a more efficient detection method, ultrahigh pressure processing technique was applied to NIR detection experiments on dimethoate residues in Chinese cabbage, the spectral data was pre-processed and optimized and a spectrum model was established. The results show that: ultrahigh-pressure extraction process did not affect the absorption of near infrared spectroscopy of extraction reagent acetone. A PLS model on near-infrared spectroscopy of samples within the range of 4100-11000cm-1 was established, obtaining a correlation coefficient R of 87.14%, Rank of 9 and RMSECV of 0.139. Residual concentration of 10-4-10-5 has a small relative error, the prediction is better. Further processing and selection of samples will expand the range of predicted concentration.
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Foley, Elaine, Gina Rippon, and Carl Senior. "Modulation of Neural Oscillatory Activity during Dynamic Face Processing." Journal of Cognitive Neuroscience 30, no. 3 (March 2018): 338–52. http://dx.doi.org/10.1162/jocn_a_01209.
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Various neuroimaging and neurophysiological methods have been used to examine neural activation patterns in response to faces. However, much of previous research has relied on static images of faces, which do not allow a complete description of the temporal structure of face-specific neural activities to be made. More recently, insights are emerging from fMRI studies about the neural substrates that underpin our perception of naturalistic dynamic face stimuli, but the temporal and spectral oscillatory activity associated with processing dynamic faces has yet to be fully characterized. Here, we used MEG and beamformer source localization to examine the spatiotemporal profile of neurophysiological oscillatory activity in response to dynamic faces. Source analysis revealed a number of regions showing enhanced activation in response to dynamic relative to static faces in the distributed face network, which were spatially coincident with regions that were previously identified with fMRI. Furthermore, our results demonstrate that perception of realistic dynamic facial stimuli activates a distributed neural network at varying time points facilitated by modulations in low-frequency power within alpha and beta frequency ranges (8–30 Hz). Naturalistic dynamic face stimuli may provide a better means of representing the complex nature of perceiving facial expressions in the real world, and neural oscillatory activity can provide additional insights into the associated neural processes.
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Margrave, Gary F. "Seismic signal band estimation by interpretation of f-x spectra." GEOPHYSICS 64, no. 1 (January 1999): 251–60. http://dx.doi.org/10.1190/1.1444522.
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The signal band of reflection seismic data is that portion of the temporal Fourier spectrum which is dominated by reflected source energy. The signal bandwidth directly determines the spatial and temporal resolving power and is a useful measure of the value of such data. The realized signal band, which is the signal band of seismic data as optimized in processing, may be estimated by the interpretation of appropriately constructed f-x spectra. A temporal window, whose length has a specified random fluctuation from trace to trace, is applied to an ensemble of seismic traces, and the temporal Fourier transform is computed. The resultant f-x spectra are then separated into amplitude and phase sections, viewed as conventional seismic displays, and interpreted. The signal is manifested through the lateral continuity of spectral events; noise causes lateral incoherence. The fundamental assumption is that signal is correlated from trace to trace while noise is not. A variety of synthetic data examples illustrate that reasonable results are obtained even when the signal decays with time (i.e., is nonstationary) or geologic structure is extreme. Analysis of real data from a 3-C survey shows an easily discernible signal band for both P-P and P-S reflections, with the former being roughly twice the latter. The potential signal band, which may be regarded as the maximum possible signal band, is independent of processing techniques. An estimator for this limiting case is the corner frequency (the frequency at which a decaying signal drops below background noise levels) as measured on ensemble‐averaged amplitude spectra from raw seismic data. A comparison of potential signal band with realized signal band for the 3-C data shows good agreement for P-P data, which suggests the processing is nearly optimal. For P-S data, the realized signal band is about half of the estimated potential. This may indicate a relative immaturity of P-S processing algorithms or it may be due to P-P energy on the raw radial component records.
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Marcolli, C., M. R. Canagaratna, D. R. Worsnop, R. Bahreini, J. A. de Gouw, C. Warneke, P. D. Goldan, et al. "Cluster Analysis of the Organic Peaks in Bulk Mass Spectra Obtained During the 2002 New England Air Quality Study with an Aerodyne Aerosol Mass Spectrometer." Atmospheric Chemistry and Physics 6, no. 12 (December 19, 2006): 5649–66. http://dx.doi.org/10.5194/acp-6-5649-2006.
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Abstract. We applied hierarchical cluster analysis to an Aerodyne aerosol mass spectrometer (AMS) bulk mass spectral dataset collected aboard the NOAA research vessel R. H. Brown during the 2002 New England Air Quality Study off the east coast of the United States. Emphasizing the organic peaks, the cluster analysis yielded a series of categories that are distinguishable with respect to their mass spectra and their occurrence as a function of time. The differences between the categories mainly arise from relative intensity changes rather than from the presence or absence of specific peaks. The most frequent category exhibits a strong signal at m/z 44 and represents oxidized organic matter probably originating from both anthropogenic as well as biogenic sources. On the basis of spectral and trace gas correlations, the second most common category with strong signals at m/z 29, 43, and 44 contains contributions from isoprene oxidation products. The third through the fifth most common categories have peak patterns characteristic of monoterpene oxidation products and were most frequently observed when air masses from monoterpene rich regions were sampled. Taken together, the second through the fifth most common categories represent on average 17% of the total organic mass that stems likely from biogenic sources during the ship's cruise. These numbers have to be viewed as lower limits since the most common category was attributed to anthropogenic sources for this calculation. The cluster analysis was also very effective in identifying a few contaminated mass spectra that were not removed during pre-processing. This study demonstrates that hierarchical clustering is a useful tool to analyze the complex patterns of the organic peaks in bulk aerosol mass spectra from a field study.
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Lee, Jeong-Seok, Gyuhae Park, Chun-Gon Kim, and Charles R. Farrar. "Use of Relative Baseline Features of Guided Waves for In situ Structural Health Monitoring." Journal of Intelligent Material Systems and Structures 22, no. 2 (January 2011): 175–89. http://dx.doi.org/10.1177/1045389x10395643.
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This article presents a new signal-processing technique, which utilizes ‘‘relative baselines’’ instead of ‘‘pre-stored baselines,’’ for Lamb wave based SHM. Several successful SHM methods utilizing wave propagations usually involve recording baseline measurements and comparing them to a newly measured response for structural damage identification. However, maintaining an accurate database of baselines remains challenging because of the effects of varying environmental conditions. Therefore, in this study, the relative baseline concept is proposed, in which measured Lamb waves are correlated between different sensor-actuator sets, as opposed to being correlated to pre-stored baseline data. This study focuses on determining the feature best used for this relative baseline concept, and cross-correlation and power spectral density analysis techniques are performed on data sets recorded from composite and aluminum plates. Experiments are performed with these plates under the presence of temperature variations in order to demonstrate the capability of the relative baseline concept. Our experimental results clearly indicate that the proposed technique reduces the complications associated with using pre-stored baselines for SHM under varying environmental conditions, and provides a quantitative means of identifying structural damage.
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Guryleva, Anastasiya V., Alexei M. Khorokhorov, and Vitaly S. Kobozev. "Methods Of Increasing Spectral Resolution Of Imaging Spectrometers Built On The Basis Of Multi–channel Radiation Detectors." Volume 28, Number 6, 2020, no. 03-2020 (December 2020): 95–104. http://dx.doi.org/10.33383/2019-098.
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The article proposes the methods of object shooting by means of a spectrometer based on a multi-channel radiation detector and further processing of its results allowing spectral resolution of such spectrometers significantly to increase with the same original spatial resolution. The mathematical model of the shooting process is provided. It is determined that restoration of spectral radiance of objects based on the shooting data using the proposed method is a mathematically incorrect inverse task. The Greville method, the method of wavelet transformation, the Tikhonov regularisation method, and the Godunov method were considered as methods for its solution. The results of computational modelling of the considered methods are shown and it is found that restoration of spectral radiance of objects based on the shooting data using the considered methods is possible and relative error of restoration is at a fraction of per cent scale. It is determined that the wavelet transformation method is an optimal method of solution of the incorrect spectral radiance restoration task. It is also shown that the proposed method of imaging spectrometry is applicable both when using matrix radiation detectors with increased number of narrow-band filters and when using widely spread standard three-channel matrix RGB detectors of radiation.
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Castro, Jeyne Pricylla, Edenir Rodrigues Pereira-Filho, and Rasmus Bro. "Laser-induced breakdown spectroscopy (LIBS) spectra interpretation and characterization using parallel factor analysis (PARAFAC): a new procedure for data and spectral interference processing fostering the waste electrical and electronic equipment (WEEE) recycling process." Journal of Analytical Atomic Spectrometry 35, no. 6 (2020): 1115–24. http://dx.doi.org/10.1039/d0ja00026d.
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For the first time, PARAFAC was used to interpret and characterize LIBS spectra, providing the pure spectra, the signal profile and relative concentration of base and noble elements present on a printed circuit board from the hard disk.
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Kozyolkin, O. A., and A. A. Kuznietsov. "ELECTROENCEPHALOGRAPHIC MARKERS OF LATERAL SHIFTS OF BRAIN MIDLINE STRUCTURES IN PATIENTS WITH ACUTE SPONTANEOUS SUPRATENTORIAL INTRACEREBRAL HAEMORRHAGE." Актуальні проблеми сучасної медицини: Вісник Української медичної стоматологічної академії 20, no. 3 (November 12, 2020): 124–33. http://dx.doi.org/10.31718/2077-1096.20.3.124.
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The aim of this study is to improve the diagnostic approaches in acute period of spontaneous supratentorial intracerebral hemorrhage by detecting the most informative parameters of spectral analysis of the electroencephalographic pattern in the evaluation of cerebral bioelectrical activity changes caused by the lateral shifts of brain midline structures. Materials and methods. We carried out clinical and paraclinical examination of 156 patients (90 men and 66 women, mean age 66,7±0,8 years) with firstly appeared hypertensive spontaneous supratentorial intracerebral hemorrhage. The diagnosis was based on the findings of computed tomography. Lateral shift was evaluated as an average from septum pellucidum and pineal gland displacements. Clinical neurological investigation included the evaluation according to the National Institute of Health Stroke Scale. Computed electroencephalography was carried out within the first 48 hours from the disease onset. Spectral rhythm power, fronto-occipital gradients, interhemispheric rhythm asymmetry parameters were analyzed. Statistical processing included evaluating differences between the groups studied, logistic regression analysis, ROC-analysis. Results. No lateral shift of brain midline structure was found in 57 (36.5%) patients; lateral shift ranged from 1-5mm was diagnosed in 72 (46.2%) patients; the lateral shift over 5 mm was found in 27 (17.3%) patients. We have found out the following values can be used as electroencephalographic criteria of lateral shift of brain midline structures: values of relative spectral power rhythm of alpha band ≤20,5% in affected hemisphere (Se=79,8%, Sp=77,2%) and ≤17,7% in intact hemisphere (Se=71,7%, 75,4%), fronto-occipital rhythm gradients of alpha2 band >–0,085 in affected hemisphere (Se=71,7%, Sp=63,2%) and >–0,266 in intact hemisphere (Se=80,8%, Sp=54,4%), while relative spectral rhythm power of delta band >48,4% in affected hemisphere (Se=88,9%, Sp=74,2%) and >46,8% in intact hemisphere (Se=92,6%, Sp=72,4%), fronto-occipital rhythm gradients of alpha band >–0,001 in affected hemisphere (Se=81,5%, Sp=65,1%). These values demonstrate disturbances in cerebral bioelectrical activity caused by lateral shift over 5 mm. Conclusions. The values of relative spectral rhythm power and fronto-occipital rhythm gradients of alpha band in affected and intact hemispheres are the most informative parameters of spectral electroencephalographic pattern analysis for detection of bioelectrical brain activity deteriorations caused by the lateral shift of brain midline structure due to acute spontaneous supratentorial intracerebral haemorrhage.
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Boyer, E., M. Petitdidier, W. Corneil, C. Adnet, and P. Larzabal. "Application of model-based spectral analysis to wind-profiler radar observations." Annales Geophysicae 19, no. 8 (August 31, 2001): 815–24. http://dx.doi.org/10.5194/angeo-19-815-2001.
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Abstract. A classical way to reduce a radar’s data is to compute the spectrum using FFT and then to identify the different peak contributions. But in case an overlapping between the different echoes (atmospheric echo, clutter, hydrometeor echo. . . ) exists, Fourier-like techniques provide poor frequency resolution and then sophisticated peak-identification may not be able to detect the different echoes. In order to improve the number of reduced data and their quality relative to Fourier spectrum analysis, three different methods are presented in this paper and applied to actual data. Their approach consists of predicting the main frequency-components, which avoids the development of very sophisticated peak-identification algorithms. The first method is based on cepstrum properties generally used to determine the shift between two close identical echoes. We will see in this paper that this method cannot provide a better estimate than Fourier-like techniques in an operational use. The second method consists of an autoregressive estimation of the spectrum. Since the tests were promising, this method was applied to reduce the radar data obtained during two thunder-storms. The autoregressive method, which is very simple to implement, improved the Doppler-frequency data reduction relative to the FFT spectrum analysis. The third method exploits a MUSIC algorithm, one of the numerous subspace-based methods, which is well adapted to estimate spectra composed of pure lines. A statistical study of performances of this method is presented, and points out the very good resolution of this estimator in comparison with Fourier-like techniques. Application to actual data confirms the good qualities of this estimator for reducing radar’s data.Key words. Meteorology and atmospheric dynamics (tropical meteorology)- Radio science (signal processing)- General (techniques applicable in three or more fields)
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Basso, Luiz Carlos Pietrowski, Vagner Alex Pesck, Mailson Roik, Afonso Figueiredo Filho, Thiago Floriani Stepka, Gerson dos Santos Lisboa, Ismael Konkol, André Felipe Hess, and Ana Paula Brandalize. "Aboveground Biomass Estimates of Araucaria angustifolia (Bertol.) Kuntze, Using Vegetation Indexes in Wolrdview-2 Image." Journal of Agricultural Science 11, no. 11 (July 31, 2019): 93. http://dx.doi.org/10.5539/jas.v11n11p93.
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The present research aims to evaluate the biomass estimates of Araucaria angustifolia (Bertol.) Kuntze trees obtained by the direct method, then present results generated from a 2.0 m resolution spectral image Worldview-2 satellite. The quantification of the biomass in the field was first carried out of 29 trees of the specie of interest with DBH ≥ 40 cm and then with the image aid the crowns were delimited for analysis. From the spectral bands (B2-blue, B3-green, B4-yellow, B5-red, B6-near red, B7-near infrared 2 and B8-near infrared 2), it was possible to obtain vegetation indexes proposed by the literature (NDVI, NDVI_2, RS and SAVI_0,25) and later incorporated with dendrometric data a correlation matrix was formed. Additionally, mathematical equations were used to estimate biomass and carbon as a function of dendrometric variables and information obtained from the satellite image processing. From these equations, the ones that presented better results were those that contained independent dendrometric variables (DBH) and those that contained vegetation indices (NDVI_2 and NDVI). For the dendrometers, the relative error found was 14.42% and 14.32% for biomass and carbon respectively, while for the digital ones, NDVI_2 found a relative error of 37.82% and an adjusted coefficient of determination of 0.88 in the biomass equations. In the carbon equations, the NDVI variable presented the best results, being 38.56% the relative error and 0.87 the determination coefficient.