scholarly journals Demonstrated Wavelength Portability of Raman Reference Data for Explosives and Chemical Detection

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Timothy J. Johnson ◽  
Yin-Fong Su ◽  
Kristin H. Jarman ◽  
Brenda M. Kunkel ◽  
Jerome C. Birnbaum ◽  
...  

As Raman spectroscopy continues to evolve, questions arise as to the portability of Raman data: dispersive versus Fourier transform, wavelength calibration, intensity calibration, and in particular the frequency of the excitation laser. While concerns about fluorescence arise in the visible or ultraviolet, most modern (portable) systems use near-infrared excitation lasers, and many of these are relatively close in wavelength. We have investigated the possibility of porting reference data sets from one NIR wavelength system to another: We have constructed a reference library consisting of 145 spectra, including 20 explosives, as well as sundry other compounds and materials using a 1064 nm spectrometer. These data were used as a reference library to evaluate the same 145 compounds whose experimental spectra were recorded using a second 785 nm spectrometer. In 128 cases of 145 (or 88.3% including 20/20 for the explosives), the compounds were correctly identified with a mean “hit score” of 954 of 1000. Adding in criteria for when to declare a correct match versus when to declare uncertainty, the approach was able to correctly categorize 134 out of 145 spectra, giving a 92.4% accuracy. For the few that were incorrectly identified, either the matched spectra were spectroscopically similar to the target or the 785 nm signal was degraded due to fluorescence. The results indicate that imported data recorded at a different NIR wavelength can be successfully used as reference libraries, but key issues must be addressed: the reference data must be of equal or higher resolution than the resolution of the current sensor, the systems require rigorous wavelength calibration, and wavelength-dependent intensity response should be accounted for in the different systems.

2013 ◽  
Vol 67 (2) ◽  
pp. 149-157 ◽  
Author(s):  
James C. Weatherall ◽  
Jeffrey Barber ◽  
Carolyn S. Brauer ◽  
Timothy J. Johnson ◽  
Yin-Fong Su ◽  
...  

Raman spectral data collected with high-resolution laboratory spectrometers are processed into a format suitable for importing as a user library on a 1064 nm DeltaNu first generation, field-deployable spectrometer prototype. The two laboratory systems used are a 1064 nm Bruker Fourier transform (FT)-Raman spectrometer and a 785 nm Kaiser dispersive spectrometer. The steps taken to adapt for device-dependent spectral resolution, wavenumber shifts between instruments, and relative intensity response are described. Effects due to the differing excitation laser wavelengths were found to be minimal, indicating—at least for the near-infrared (NIR)—that data can be ported between different systems, so long as certain measures are taken with regard to the reference and field spectra.


1997 ◽  
Vol 36 (5) ◽  
pp. 61-68 ◽  
Author(s):  
Hermann Eberl ◽  
Amar Khelil ◽  
Peter Wilderer

A numerical method for the identification of parameters of nonlinear higher order differential equations is presented, which is based on the Levenberg-Marquardt algorithm. The estimation of the parameters can be performed by using several reference data sets simultaneously. This leads to a multicriteria optimization problem, which will be treated by using the Pareto optimality concept. In this paper, the emphasis is put on the presentation of the calibration method. As an example identification of the parameters of a nonlinear hydrological transport model for urban runoff is included, but the method can be applied to other problems as well.


2021 ◽  
Vol 7 (2) ◽  
pp. 21
Author(s):  
Roland Perko ◽  
Manfred Klopschitz ◽  
Alexander Almer ◽  
Peter M. Roth

Many scientific studies deal with person counting and density estimation from single images. Recently, convolutional neural networks (CNNs) have been applied for these tasks. Even though often better results are reported, it is often not clear where the improvements are resulting from, and if the proposed approaches would generalize. Thus, the main goal of this paper was to identify the critical aspects of these tasks and to show how these limit state-of-the-art approaches. Based on these findings, we show how to mitigate these limitations. To this end, we implemented a CNN-based baseline approach, which we extended to deal with identified problems. These include the discovery of bias in the reference data sets, ambiguity in ground truth generation, and mismatching of evaluation metrics w.r.t. the training loss function. The experimental results show that our modifications allow for significantly outperforming the baseline in terms of the accuracy of person counts and density estimation. In this way, we get a deeper understanding of CNN-based person density estimation beyond the network architecture. Furthermore, our insights would allow to advance the field of person density estimation in general by highlighting current limitations in the evaluation protocols.


Small ◽  
2016 ◽  
Vol 12 (13) ◽  
pp. 1732-1743 ◽  
Author(s):  
Akshaya Bansal ◽  
Haichun Liu ◽  
Muthu Kumara Gnanasammandhan Jayakumar ◽  
Stefan Andersson-Engels ◽  
Yong Zhang

Solid Earth ◽  
2016 ◽  
Vol 7 (2) ◽  
pp. 323-340 ◽  
Author(s):  
Sascha Schneiderwind ◽  
Jack Mason ◽  
Thomas Wiatr ◽  
Ioannis Papanikolaou ◽  
Klaus Reicherter

Abstract. Two normal faults on the island of Crete and mainland Greece were studied to test an innovative workflow with the goal of obtaining a more objective palaeoseismic trench log, and a 3-D view of the sedimentary architecture within the trench walls. Sedimentary feature geometries in palaeoseismic trenches are related to palaeoearthquake magnitudes which are used in seismic hazard assessments. If the geometry of these sedimentary features can be more representatively measured, seismic hazard assessments can be improved. In this study more representative measurements of sedimentary features are achieved by combining classical palaeoseismic trenching techniques with multispectral approaches. A conventional trench log was firstly compared to results of ISO (iterative self-organising) cluster analysis of a true colour photomosaic representing the spectrum of visible light. Photomosaic acquisition disadvantages (e.g. illumination) were addressed by complementing the data set with active near-infrared backscatter signal image from t-LiDAR measurements. The multispectral analysis shows that distinct layers can be identified and it compares well with the conventional trench log. According to this, a distinction of adjacent stratigraphic units was enabled by their particular multispectral composition signature. Based on the trench log, a 3-D interpretation of attached 2-D ground-penetrating radar (GPR) profiles collected on the vertical trench wall was then possible. This is highly beneficial for measuring representative layer thicknesses, displacements, and geometries at depth within the trench wall. Thus, misinterpretation due to cutting effects is minimised. This manuscript combines multiparametric approaches and shows (i) how a 3-D visualisation of palaeoseismic trench stratigraphy and logging can be accomplished by combining t-LiDAR and GPR techniques, and (ii) how a multispectral digital analysis can offer additional advantages to interpret palaeoseismic and stratigraphic data. The multispectral data sets are stored allowing unbiased input for future (re)investigations.


2015 ◽  
Vol 8 (6) ◽  
pp. 2589-2608 ◽  
Author(s):  
P. Köhler ◽  
L. Guanter ◽  
J. Joiner

Abstract. Global retrievals of near-infrared sun-induced chlorophyll fluorescence (SIF) have been achieved in the last few years by means of a number of space-borne atmospheric spectrometers. Here, we present a new retrieval method for medium spectral resolution instruments such as the Global Ozone Monitoring Experiment-2 (GOME-2) and the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY). Building upon the previous work by Guanter et al. (2013) and Joiner et al. (2013), our approach provides a solution for the selection of the number of free parameters. In particular, a backward elimination algorithm is applied to optimize the number of coefficients to fit, which reduces also the retrieval noise and selects the number of state vector elements automatically. A sensitivity analysis with simulated spectra has been utilized to evaluate the performance of our retrieval approach. The method has also been applied to estimate SIF at 740 nm from real spectra from GOME-2 and for the first time, from SCIAMACHY. We find a good correspondence of the absolute SIF values and the spatial patterns from the two sensors, which suggests the robustness of the proposed retrieval method. In addition, we compare our results to existing SIF data sets, examine uncertainties and use our GOME-2 retrievals to show empirically the relatively low sensitivity of the SIF retrieval to cloud contamination.


2020 ◽  
Author(s):  
Kiran Mahat ◽  
Andrew Mitchell ◽  
Tshelthrim Zangpo

AbstractWe report the first detection of Fall Armyworm (FAW), Spodoptera frugiperda (Smith, 1797), in Bhutan. FAW feeds on more than 300 plant species and is a serious pest of many. It has been spreading through Africa since 2016 and Asia since 2018. In Bhutan, this species was first detected in maize fields in the western part of the country in September 2019 and subsequently found infesting maize crop in southern parts of the country in December 2019 and April 2020. Using morphological and molecular techniques the presence of the first invading populations of S. frugiperda in Bhutan is confirmed through this study. We present an updated reference DNA barcode data set for FAW comprising 374 sequences, which can be used to reliably identify this serious pest species, and discuss some of the reasons why such compiled reference data sets are necessary, despite the publicly availability of the underlying data. We also report on a second armyworm species, the Northern Armyworm, Mythimna separata (Walker, 1865), in rice, maize and other crops in eighteen districts of Bhutan.


1998 ◽  
Vol 6 (A) ◽  
pp. A13-A19 ◽  
Author(s):  
T.G. Axon ◽  
R. Brown ◽  
S.V. Hammond ◽  
S.J. Maris ◽  
F. Ting

The early use of near infrared (NIR) spectroscopy in the pharmaceutical industry was for raw material identification, later moving on to some conventional “calibrations” for various ingredients in a variety of sample types. The approach throughout this development process has always been “conventional” with one measurement by NIR directly replacing some other slower method, be it Mid-IR identification, or determinations by Karl Fischer, high performance liquid chromatography (HPLC)etc. A significant change in approach was demonstrated by Plugge and Van der Vlies1 in 1993, where a qualitative system was used to provide “quantitative like” answers for potency of a drug substance. Following on from that key paper, there has been a realisation that the qualitative analysis ability of NIR, has the potential to be a powerful tool for process investigation, control and validation. The final step has been to develop “model free” approaches, that consider individual data sets as unique systems, and present the opportunity for NIR to escape the shackles of “calibration” in one form or another. The use of qualitative, or model free, approaches to NIR spectroscopy provides an effective tool for satisfying many of the demands of modern pharmaceutical production. “Straight through production,” “right first time,” “short cycle time” and “total quality management” philosophies can be realised. Eventually the prospect of parametric release may be materialised with a strong contribution from NIR spectroscopy. This paper will illustrate the above points with some real life examles.


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