Search results for: high-resolution infrared spectra
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1692

Search results for: high-resolution infrared spectra

1632 Sorting Maize Haploids from Hybrids Using Single-Kernel Near-Infrared Spectroscopy

Authors: Paul R Armstrong

Abstract:

Doubled haploids (DHs) have become an important breeding tool for creating maize inbred lines, although several bottlenecks in the DH production process limit wider development, application, and adoption of the technique. DH kernels are typically sorted manually and represent about 10% of the seeds in a much larger pool where the remaining 90% are hybrid siblings. This introduces time constraints on DH production and manual sorting is often not accurate. Automated sorting based on the chemical composition of the kernel can be effective, but devices, namely NMR, have not achieved the sorting speed to be a cost-effective replacement to manual sorting. This study evaluated a single kernel near-infrared reflectance spectroscopy (skNIR) platform to accurately identify DH kernels based on oil content. The skNIR platform is a higher-throughput device, approximately 3 seeds/s, that uses spectra to predict oil content of each kernel from maize crosses intentionally developed to create larger than normal oil differences, 1.5%-2%, between DH and hybrid kernels. Spectra from the skNIR were used to construct a partial least squares regression (PLS) model for oil and for a categorical reference model of 1 (DH kernel) or 2 (hybrid kernel) and then used to sort several crosses to evaluate performance. Two approaches were used for sorting. The first used a general PLS model developed from all crosses to predict oil content and then used for sorting each induction cross, the second was the development of a specific model from a single induction cross where approximately fifty DH and one hundred hybrid kernels used. This second approach used a categorical reference value of 1 and 2, instead of oil content, for the PLS model and kernels selected for the calibration set were manually referenced based on traditional commercial methods using coloration of the tip cap and germ areas. The generalized PLS oil model statistics were R2 = 0.94 and RMSE = .93% for kernels spanning an oil content of 2.7% to 19.3%. Sorting by this model resulted in extracting 55% to 85% of haploid kernels from the four induction crosses. Using the second method of generating a model for each cross yielded model statistics ranging from R2s = 0.96 to 0.98 and RMSEs from 0.08 to 0.10. Sorting in this case resulted in 100% correct classification but required models that were cross. In summary, the first generalized model oil method could be used to sort a significant number of kernels from a kernel pool but was not close to the accuracy of developing a sorting model from a single cross. The penalty for the second method is that a PLS model would need to be developed for each individual cross. In conclusion both methods could find useful application in the sorting of DH from hybrid kernels.

Keywords: NIR, haploids, maize, sorting

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1631 Assessment of Pre-Processing Influence on Near-Infrared Spectra for Predicting the Mechanical Properties of Wood

Authors: Aasheesh Raturi, Vimal Kothiyal, P. D. Semalty

Abstract:

We studied mechanical properties of Eucalyptus tereticornis using FT-NIR spectroscopy. Firstly, spectra were pre-processed to eliminate useless information. Then, prediction model was constructed by partial least squares regression. To study the influence of pre-processing on prediction of mechanical properties for NIR analysis of wood samples, we applied various pretreatment methods like straight line subtraction, constant offset elimination, vector-normalization, min-max normalization, multiple scattering. Correction, first derivative, second derivatives and their combination with other treatment such as First derivative + straight line subtraction, First derivative+ vector normalization and First derivative+ multiplicative scattering correction. The data processing methods in combination of preprocessing with different NIR regions, RMSECV, RMSEP and optimum factors/rank were obtained by optimization process of model development. More than 350 combinations were obtained during optimization process. More than one pre-processing method gave good calibration/cross-validation and prediction/test models, but only the best calibration/cross-validation and prediction/test models are reported here. The results show that one can safely use NIR region between 4000 to 7500 cm-1 with straight line subtraction, constant offset elimination, first derivative and second derivative preprocessing method which were found to be most appropriate for models development.

Keywords: FT-NIR, mechanical properties, pre-processing, PLS

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1630 Development of a Non-Dispersive Infrared Multi Gas Analyzer for a TMS

Authors: T. V. Dinh, I. Y. Choi, J. W. Ahn, Y. H. Oh, G. Bo, J. Y. Lee, J. C. Kim

Abstract:

A Non-Dispersive Infrared (NDIR) multi-gas analyzer has been developed to monitor the emission of carbon monoxide (CO) and sulfur dioxide (SO2) from various industries. The NDIR technique for gas measurement is based on the wavelength absorption in the infrared spectrum as a way to detect particular gasses. NDIR analyzers have popularly applied in the Tele-Monitoring System (TMS). The advantage of the NDIR analyzer is low energy consumption and cost compared with other spectroscopy methods. However, zero/span drift and interference are its urgent issues to be solved. Multi-pathway technique based on optical White cell was employed to improve the sensitivity of the analyzer in this work. A pyroelectric detector was used to detect the Infrared radiation. The analytical range of the analyzer was 0 ~ 200 ppm. The instrument response time was < 2 min. The detection limits of CO and SO2 were < 4 ppm and < 6 ppm, respectively. The zero and span drift of 24 h was less than 3%. The linearity of the analyzer was less than 2.5% of reference values. The precision and accuracy of both CO and SO2 channels were < 2.5% of relative standard deviation. In general, the analyzer performed well. However, the detection limit and 24h drift should be improved to be a more competitive instrument.

Keywords: analyzer, CEMS, monitoring, NDIR, TMS

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1629 Quantification of Glucosinolates in Turnip Greens and Turnip Tops by Near-Infrared Spectroscopy

Authors: S. Obregon-Cano, R. Moreno-Rojas, E. Cartea-Gonzalez, A. De Haro-Bailon

Abstract:

The potential of near-infrared spectroscopy (NIRS) for screening the total glucosinolate (t-GSL) content, and also, the aliphatic glucosinolates gluconapin (GNA), progoitrin (PRO) and glucobrassicanapin (GBN) in turnip greens and turnip tops was assessed. This crop is grown for edible leaves and stems for human consumption. The reference values for glucosinolates, as they were obtained by high performance liquid chromatography on the vegetable samples, were regressed against different spectral transformations by modified partial least-squares (MPLS) regression (calibration set of samples n= 350). The resulting models were satisfactory, with calibration coefficient values from 0.72 (GBN) to 0.98 (tGSL). The predictive ability of the equations obtained was tested using a set of samples (n=70) independent of the calibration set. The determination coefficients and prediction errors (SEP) obtained in the external validation were: GNA=0.94 (SEP=3.49); PRO=0.41 (SEP=1.08); GBN=0.55 (SEP=0.60); tGSL=0.96 (SEP=3.28). These results show that the equations developed for total glucosinolates, as well as for gluconapin can be used for screening these compounds in the leaves and stems of this species. In addition, the progoitrin and glucobrassicanapin equations obtained can be used to identify those samples with high, medium and low contents. The calibration equations obtained were accurate enough for a fast, non-destructive and reliable analysis of the content in GNA and tGSL directly from NIR spectra. The equations for PRO and GBN can be employed to identify samples with high, medium and low contents.

Keywords: brassica rapa, glucosinolates, gluconapin, NIRS, turnip greens

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1628 Detection of Internal Mold Infection of Intact Tomatoes by Non-Destructive, Transmittance VIS-NIR Spectroscopy

Authors: K. Petcharaporn

Abstract:

The external characteristics of tomatoes, such as freshness, color and size are typically used in quality control processes for tomatoes sorting. However, the internal mold infection of intact tomato cannot be sorted based on a visible assessment and destructive method alone. In this study, a non-destructive technique was used to predict the internal mold infection of intact tomatoes by using transmittance visible and near infrared (VIS-NIR) spectroscopy. Spectra for 200 samples contained 100 samples for normal tomatoes and 100 samples for mold infected tomatoes were acquired in the wavelength range between 665-955 nm. This data was used in conjunction with partial least squares-discriminant analysis (PLS-DA) method to generate a classification model for tomato quality between groups of internal mold infection of intact tomato samples. For this task, the data was split into two groups, 140 samples were used for a training set and 60 samples were used for a test set. The spectra of both normal and internally mold infected tomatoes showed different features in the visible wavelength range. Combined spectral pretreatments of standard normal variate transformation (SNV) and smoothing (Savitzky-Golay) gave the optimal calibration model in training set, 85.0% (63 out of 71 for the normal samples and 56 out of 69 for the internal mold samples). The classification accuracy of the best model on the test set was 91.7% (29 out of 29 for the normal samples and 26 out of 31 for the internal mold tomato samples). The results from this experiment showed that transmittance VIS-NIR spectroscopy can be used as a non-destructive technique to predict the internal mold infection of intact tomatoes.

Keywords: tomato, mold, quality, prediction, transmittance

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1627 Detection of Internal Mold Infection of Intact For Tomatoes by Non-Destructive, Transmittance VIS-NIR Spectroscopy

Authors: K. Petcharaporn, N. Prathengjit

Abstract:

The external characteristics of tomatoes, such as freshness, color and size are typically used in quality control processes for tomatoes sorting. However, the internal mold infection of intact tomato cannot be sorted based on a visible assessment and destructive method alone. In this study, a non-destructive technique was used to predict the internal mold infection of intact tomatoes by using transmittance visible and near infrared (VIS-NIR) spectroscopy. Spectra for 200 samples contained 100 samples for normal tomatoes and 100 samples for mold infected tomatoes were acquired in the wavelength range between 665-955 nm. This data was used in conjunction with partial least squares-discriminant analysis (PLS-DA) method to generate a classification model for tomato quality between groups of internal mold infection of intact tomato samples. For this task, the data was split into two groups, 140 samples were used for a training set and 60 samples were used for a test set. The spectra of both normal and internally mold infected tomatoes showed different features in the visible wavelength range. Combined spectral pretreatments of standard normal variate transformation (SNV) and smoothing (Savitzky-Golay) gave the optimal calibration model in training set, 85.0% (63 out of 71 for the normal samples and 56 out of 69 for the internal mold samples). The classification accuracy of the best model on the test set was 91.7% (29 out of 29 for the normal samples and 26 out of 31 for the internal mold tomato samples). The results from this experiment showed that transmittance VIS-NIR spectroscopy can be used as a non-destructive technique to predict the internal mold infection of intact tomatoes.

Keywords: tomato, mold, quality, prediction, transmittance

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1626 Possibilities of Output Technology the Project ADAPTIV for Use in Infrared Camouflage

Authors: Jiří Barta, Teodor Baláž, Tomáš Ludík, Jiří. F. Urbánek

Abstract:

This article deals with the outputs of project acronym ADAPTIV of Czech Defence Research Project. This Project solved tends to adaptive camouflage. The camouflage is concealment by means of disguise. Perceptive interface between recipient and camouflaged object is visualized by means of textile modular screens. Screens special light semi-permeability enables front/ back projection with nearly identical light parameters. Information permeability, towards illusion creation, must be controlled by the camouflage provider by means sophisticated and mastered illusion with perfect scenarios. The project ADAPTIV was primarily funded with the maximum possible use of COTS (Commercial-Off-The-Shelf) principle asks special definition of feasibility conditions, especially recipient space position. This paper deals with uses the ADAPTIV output with name DATAsam with modification for infrared camouflage. It is focused on active camouflage in infrared spectrum of emissivity at <8;14> μm for laboratory conditions. The main chapter provides basic experiments and testing physical properties needed for camouflage in infrared environment. The evaluation experiments revealed the possibility of use case in various types of camouflage.

Keywords: camouflage, ADAPTIV, infrared camouflage, computer-aided, COTS

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1625 Spectral Properties of Fiber Bragg Gratings

Authors: Y. Hamaizi, H. Triki, A. El-Akrmi

Abstract:

In this paper, the reflection spectra, group delay and dispersion of a uniform fiber Bragg grating (FBG) are obtained. FBGs with two types of apodized variations of the refractive index were modeled to show how the side-lobes can be suppressed. Apodization techniques are used to get optimized reflection spectra. The simulation is based on solving coupled mode equations together with the transfer matrix method.

Keywords: fiber bragg gratings, coupled-mode theory, reflectivity, apodization

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1624 Automatic Diagnosis of Electrical Equipment Using Infrared Thermography

Authors: Y. Laib Dit Leksir, S. Bouhouche

Abstract:

Analysis and processing of data bases resulting from infrared thermal measurements made on the electrical installation requires the development of new tools in order to obtain correct and additional information to the visual inspections. Consequently, the methods based on the capture of infrared digital images show a great potential and are employed increasingly in various fields. Although, there is an enormous need for the development of effective techniques to analyse these data base in order to extract relevant information relating to the state of the equipments. Our goal consists in introducing recent techniques of modeling based on new methods, image and signal processing to develop mathematical models in this field. The aim of this work is to capture the anomalies existing in electrical equipments during an inspection of some machines using A40 Flir camera. After, we use binarisation techniques in order to select the region of interest and we make comparison between these methods of thermal images obtained to choose the best one.

Keywords: infrared thermography, defect detection, troubleshooting, electrical equipment

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1623 Photoluminescence in Cerium Doped Fluorides Prepared by Slow Precipitation Method

Authors: Aarti Muley, S. J. Dhoblae

Abstract:

CaF₂ and BaF₂ doped with cerium were prepared by slow precipitation method with different molar concentration and different cerium concentration. Both the samples were also prepared by direct method for comparison. The XRD of BaF₂:Ce shows that it crystallizes to BCC structure. The peak matches with JCPDS file no. 4-0452. Also, The XRD pattern of CaF₂:Ce matches well with the JCPDS file number 75- 0363 and crystallized to BCC phase. In CaF₂, the double-humped photoluminescence spectra were observed at 320nm and 340nm when the sample was prepared by the direct precipitation method, and the ratio between these peaks is unity. However when the sample prepared by slow precipitation method the double-humped emission spectra of CaF₂:Ce was observed at 323nm and 340nm. The ratio between these peaks is 0.58, and the optimum concentration is obtained for 0.1 molar CaF₂ with Ce concentration 1.5%. When the cerium concentration is increased by 2% the peak at 323nm vanishes, and the emission was observed at 342nm with the shoulder at 360nm. In this case, the intensity reduces drastically. The excitation is observed at 305nm with a small peak at 254nm. One molar BaF₂ doped with 0.1% of cerium was synthesized by direct precipitation method gives double humped spectra at 308nm and 320nm, when it is prepared with slow precipitation method with the cerium concentration 0.05m%, 0.1m%, 0.15m%, 0.2m% the broad emission is observed around 325nm with the shoulder at 350nm. The excitation spectra are narrow and observed at 290nm. As the percentage of cerium is increased further again shift is observed. The emission spectra were observed at 360nm with a small peak at 330nm. The phenomenon of shifting of emission spectra at low concentration of cerium can directly relate with the particle size and reported for nanomaterials also.

Keywords: calcium fluoride, barium fluoride, photoluminescence, slow precipitation method

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1622 Spectroscopic and 1.08mm Laser Properties of Nd3+ Doped Oxy-Fluoro Borate Glasses

Authors: Swapna Koneru, Srinivasa Rao Allam, Vijaya Prakash Gaddem

Abstract:

The different concentrations of neodymium-doped (Nd-doped) oxy fluoroborate (OFB) glasses were prepared by melt quenching method and characterized through optical absorption, emission and decay curve measurements to understand the lasing potentialities of these glasses. Optical absorption spectra were recorded and have been analyzed using Judd–Ofelt theory. The dipole strengths are parameterized in terms of three phenomenological Judd–Ofelt intensity parameters Ωλ (λ=2, 4 and 6) to elucidate the glassy matrix around Nd3+ ion as well as to determine the 4F3/2 metastable state radiative properties such as the transition probability (AR), radiative lifetime (τR), branching ratios (βR) and integrated absorption cross-section (σa) have been measured for most of the fluorescent levels of Nd3+. The emission spectra recorded for these glasses exhibit two peaks at 1085 and 1328 nm corresponding to 4F3/2 to 4I11/2 and 4I13/2 transitions have been obtained for all the glasses upon 808 nm diode laser excitation in the near infrared region. The emission intensity of the 4F3/2 to 4I11/2 transition increases with increase of Nd3+ concentration up to 1 mol% and then concentration quenching is observed for 2.0 mol% of Nd3+ concentration. The lifetimes for the 4F3/2 level are found to decrease with increase in Nd2O3 concentration in the glasses due to the concentration quenching. The decay curves of all these glasses show single exponential behavior. The spectroscopy of Nd3+ in these glasses is well understood and laser properties can be accurately determined from measured spectroscopic properties. The results obtained are compared with reports on similar glasses. The results indicate that the present glasses could be useful for 1.08 µm laser applications.

Keywords: glasses, luminescence, optical properties, photoluminescence spectroscopy

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1621 Investigating the Potential of Spectral Bands in the Detection of Heavy Metals in Soil

Authors: Golayeh Yousefi, Mehdi Homaee, Ali Akbar Norouzi

Abstract:

Ongoing monitoring of soil contamination by heavy metals is critical for ecosystem stability and environmental protection, and food security. The conventional methods of determining these soil contaminants are time-consuming and costly. Spectroscopy in the visible near-infrared (VNIR) - short wave infrared (SWIR) region is a rapid, non-destructive, noninvasive, and cost-effective method for assessment of soil heavy metals concentration by studying the spectral properties of soil constituents. The aim of this study is to derive spectral bands and important ranges that are sensitive to heavy metals and can be used to estimate the concentration of these soil contaminants. In other words, the change in the spectral properties of spectrally active constituents of soil can lead to the accurate identification and estimation of the concentration of these compounds in soil. For this purpose, 325 soil samples were collected, and their spectral reflectance curves were evaluated at a range of 350-2500 nm. After spectral preprocessing operations, the partial least-squares regression (PLSR) model was fitted on spectral data to predict the concentration of Cu and Ni. Based on the results, the spectral range of Cu- sensitive spectra were 480, 580-610, 1370, 1425, 1850, 1920, 2145, and 2200 nm, and Ni-sensitive ranges were 543, 655, 761, 1003, 1271, 1415, 1903, 2199 nm. Finally, the results of this study indicated that the spectral data contains a lot of information that can be applied to identify the soil properties, such as the concentration of heavy metals, with more detail.

Keywords: heavy metals, spectroscopy, spectral bands, PLS regression

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1620 Depth Estimation in DNN Using Stereo Thermal Image Pairs

Authors: Ahmet Faruk Akyuz, Hasan Sakir Bilge

Abstract:

Depth estimation using stereo images is a challenging problem in computer vision. Many different studies have been carried out to solve this problem. With advancing machine learning, tackling this problem is often done with neural network-based solutions. The images used in these studies are mostly in the visible spectrum. However, the need to use the Infrared (IR) spectrum for depth estimation has emerged because it gives better results than visible spectra in some conditions. At this point, we recommend using thermal-thermal (IR) image pairs for depth estimation. In this study, we used two well-known networks (PSMNet, FADNet) with minor modifications to demonstrate the viability of this idea.

Keywords: thermal stereo matching, deep neural networks, CNN, Depth estimation

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1619 Different Ergonomic Exposures and Infrared Thermal Temperature on Low Back

Authors: Sihao Lin

Abstract:

Objectives: Infrared thermography (IRT) has been little documented in the objective measurement of ergonomic exposure. We aimed to examine the association between different ergonomic exposures and low back skin temperature measured by IRT. Methods: A total of 114 subjects among sedentary students, sports students and cleaning workers were selected as different ergonomic exposure levels. Low back skin temperature was measured by infrared thermography before and post ergonomic exposure. Ergonomic exposure was assessed by Quick Exposure Check (QEC) and quantitative scores were calculated on the low back. Multiple regressions were constructed to examine the possible associations between ergonomic risk exposures and the skin temperature over the low back. Results: Compared to the two student groups, clean workers had significantly higher ergonomic exposure scores on the low back. The low back temperature variations were different among the three groups. The temperature decreased significantly among students with ergonomic exposure (P < 0.01), while it increased among cleaning workers. With adjustment of confounding, the post-exposure temperature and the temperature changes after exposure showed a significantly negative association with ergonomic exposure scores. For maximum temperature, one increasing ergonomic score decreased -0.23◦C (95% CI -0.37, -0.10) of temperature after ergonomic exposure over the low back. Conclusion: There was a significant association between ergonomic exposures and infrared thermal temperature over low back. IRT could be used as an objective assessment of ergonomic exposure on the low back.

Keywords: ergonomic exposure, infrared thermography, musculoskeletal disorders, skin temperature, low back

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1618 Nondestructive Testing for Reinforced Concrete Buildings with Active Infrared Thermography

Authors: Huy Q. Tran, Jungwon Huh, Kiseok Kwak, Choonghyun Kang

Abstract:

Infrared thermography (IRT) technique has been proven to be a good method for nondestructive evaluation of concrete material. In the building, a broad range of applications has been used such as subsurface defect inspection, energy loss, and moisture detection. The purpose of this research is to consider the qualitative and quantitative performance of reinforced concrete deteriorations using active infrared thermography technique. An experiment of three different heating regimes was conducted on a concrete slab in the laboratory. The thermal characteristics of the IRT method, i.e., absolute contrast and observation time, are investigated. A linear relationship between the observation time and the real depth was established with a well linear regression R-squared of 0.931. The results showed that the absolute contrast above defective area increases with the rise of the size of delamination and the heating time. In addition, the depth of delamination can be predicted by using the proposal relationship of this study.

Keywords: concrete building, infrared thermography, nondestructive evaluation, subsurface delamination

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1617 Detecting and Disabling Digital Cameras Using D3CIP Algorithm Based on Image Processing

Authors: S. Vignesh, K. S. Rangasamy

Abstract:

The paper deals with the device capable of detecting and disabling digital cameras. The system locates the camera and then neutralizes it. Every digital camera has an image sensor known as a CCD, which is retro-reflective and sends light back directly to its original source at the same angle. The device shines infrared LED light, which is invisible to the human eye, at a distance of about 20 feet. It then collects video of these reflections with a camcorder. Then the video of the reflections is transferred to a computer connected to the device, where it is sent through image processing algorithms that pick out infrared light bouncing back. Once the camera is detected, the device would project an invisible infrared laser into the camera's lens, thereby overexposing the photo and rendering it useless. Low levels of infrared laser neutralize digital cameras but are neither a health danger to humans nor a physical damage to cameras. We also discuss the simplified design of the above device that can used in theatres to prevent piracy. The domains being covered here are optics and image processing.

Keywords: CCD, optics, image processing, D3CIP

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1616 Spectroscopic Studies and Reddish Luminescence Enhancement with the Increase in Concentration of Europium Ions in Oxy-Fluoroborate Glasses

Authors: Mahamuda Sk, Srinivasa Rao Allam, Vijaya Prakash G.

Abstract:

The different concentrations of Eu3+ ions doped in Oxy-fluoroborate glasses of composition 60 B2O3-10 BaF2-10 CaF2-15 CaF2- (5-x) Al2O3 -x Eu2O3 where x = 0.1, 0.5, 1.0 and 2.0 mol%, have been prepared by conventional melt quenching technique and are characterized through absorption and photoluminescence (PL), decay, color chromaticity and Confocal measurements. The absorption spectra of all the glasses consists of six peaks corresponding to the transitions 7F0→5D2, 7F0→5D1, 7F1→5D1, 7F1→5D0, 7F0→7F6 and 7F1→7F6 respectively. The experimental oscillator strengths with and without thermal corrections have been evaluated using absorption spectra. Judd-Ofelt (JO) intensity parameters (Ω2 and Ω4) have been evaluated from the photoluminescence spectra of all the glasses. PL spectra of all the glasses have been recorded at excitation wavelengths 395 nm (conventional excitation source) and 410 nm (diode laser) to observe the intensity variation in the PL spectra. All the spectra consists of five emission peaks corresponding to the transitions 5D0→7FJ (J = 0, 1, 2, 3 and 4). Surprisingly no concentration quenching is observed on PL spectra. Among all the glasses the glass with 2.0 mol% of Eu3+ ion concentration possesses maximum intensity for the transition 5D0→7F2 (612 nm) in bright red region. The JO parameters derived from the photoluminescence spectra have been used to evaluate the essential radiative properties such as transition probability (A), radiative lifetime (τR), branching ratio (βR) and peak stimulated emission cross-section (σse) for the 5D0→7FJ (J = 0, 1, 2, 3 and 4) transitions of the Eu3+ ions. The decay rates of the 5D0 fluorescent level of Eu3+ ions in the title glasses are found to be single exponential for all the studied Eu3+ ion concentrations. A marginal increase in lifetime of the 5D0 level has been noticed with increase in Eu3+ ion concentration from 0.1 mol% to 2.0 mol%. Among all the glasses, the glass with 2.0 mol% of Eu3+ ion concentration possesses maximum values of branching ratio, stimulated emission cross-section and quantum efficiency for the transition 5D0→7F2 (612 nm) in bright red region. The color chromaticity coordinates are also evaluated to confirm the reddish luminescence from these glasses. These color coordinates exactly fall in the bright red region. Confocal images also recorded to confirm reddish luminescence from these glasses. From all the obtained results in the present study, it is suggested that the glass with 2.0 mol% of Eu3+ ion concentration is suitable to emit bright red color laser.

Keywords: Europium, Judd-Ofelt parameters, laser, luminescence

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1615 Site Specific Ground Response Estimations for the Vulnerability Assessment of the Buildings of the Third Biggest Mosque in the World, Algeria’s Mosque

Authors: S. Mohamadi, T. Boudina, A. Rouabeh, A. Seridi

Abstract:

Equivalent linear and non-linear ground response analyses are conducted at many representative sites at the mosque of Algeria, to compare the free field acceleration spectra with local code of practice. Spectral Analysis of Surface Waves (SASW) technique was adopted to measure the in-situ shear wave velocity profile at the representative sites. The seismic movement imposed on the rock is the NS component of Keddara station recorded during the earthquake in Boumerdes 21 May 2003. The site-specific elastic design spectra for each site are determined to further obtain site specific non-linear acceleration spectra. As a case study, the results of site-specific evaluations are presented for two building sites (site of minaret and site of the prayer hall) to demonstrate the influence of local geological conditions on ground response at Algerian sites. A comparison of computed response with the standard code of practice being used currently in Algeria for the seismic zone of Algiers indicated that the design spectra is not able to capture site amplification due to local geological conditions.

Keywords: equivalent linear, non-linear, ground response analysis, design response spectrum

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1614 Estimating X-Ray Spectra for Digital Mammography by Using the Expectation Maximization Algorithm: A Monte Carlo Simulation Study

Authors: Chieh-Chun Chang, Cheng-Ting Shih, Yan-Lin Liu, Shu-Jun Chang, Jay Wu

Abstract:

With the widespread use of digital mammography (DM), radiation dose evaluation of breasts has become important. X-ray spectra are one of the key factors that influence the absorbed dose of glandular tissue. In this study, we estimated the X-ray spectrum of DM using the expectation maximization (EM) algorithm with the transmission measurement data. The interpolating polynomial model proposed by Boone was applied to generate the initial guess of the DM spectrum with the target/filter combination of Mo/Mo and the tube voltage of 26 kVp. The Monte Carlo N-particle code (MCNP5) was used to tally the transmission data through aluminum sheets of 0.2 to 3 mm. The X-ray spectrum was reconstructed by using the EM algorithm iteratively. The influence of the initial guess for EM reconstruction was evaluated. The percentage error of the average energy between the reference spectrum inputted for Monte Carlo simulation and the spectrum estimated by the EM algorithm was -0.14%. The normalized root mean square error (NRMSE) and the normalized root max square error (NRMaSE) between both spectra were 0.6% and 2.3%, respectively. We conclude that the EM algorithm with transmission measurement data is a convenient and useful tool for estimating x-ray spectra for DM in clinical practice.

Keywords: digital mammography, expectation maximization algorithm, X-Ray spectrum, X-Ray

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1613 Synthesis, Structural and Magnetic Properties of CdFe2O4 Ferrite

Authors: Justice Zakhele Msomi

Abstract:

Nanoparticles of CdFe2O4 with particle size of about 10 nm have been synthesized by high energy ball milling and co-precipitation processes. The synthesis route appears to have some effects on the properties. The compounds have been characterized by X-ray diffraction, Fourier Transform Infrared (FTIR), transmission electron microscopy (TEM), Mössbauer and magnetization measurements. The XRD pattern of CdFe2O4 provides information about single-phase formation of spinel structure with cubic symmetry. The FTIR measurements between 400 and 4000 cm-1 indicate intrinsic cation vibration of the spinel structure. The Mössbauer spectra were recorded at 4 K and 300 K. The hyperfine fields appear to be highly sensitive on particle size. The evolution of the properties as a function of particle size is also presented.

Keywords: ferrite, nanoparticles, magnetization, Mössbauer

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1612 The Synthesis of AgInS₂/SnS₂/RGO Heterojunctions with Enhanced Photocatalytic Degradation of Norfloxacin

Authors: Mingmei Zhang, Xinyong Li

Abstract:

Novel AgInS2/SnS2/RGO (AISR) heterojunctions photocatalysts were synthesized by simple hydrothermal method. The morphology and composition of the fabricated AISR nanocomposites were investigated by field-emission scanning electron microscopy (SEM), X-ray diffraction (XRD), high resolution transmission electron microscopy (HRTEM) and X-ray photoelectron spectroscopy (XPS). Moreover, the as-prepared AISR photocatalysts exhibited excellent photocatalytic activities for the degradation of Norfloxacin (NOR), mainly due to its high optical absorption and separation efficiency of photogenerated electron-hole pairs, as evidenced by UV–vis diffusion reflection spectra (DRS) and Surface photovoltage (SPV) spectra. Furthermore, laser flash photolysis technique was conducted to test the lifetime of charge carriers of the fabricated nanocomposites. The interfacial charges transfer mechanism was also discussed.

Keywords: AISR heterojunctions, electron-hole pairs, SPV spectra, charges transfer mechanism

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1611 The Mechanism Study of Degradative Solvent Extraction of Biomass by Liquid Membrane-Fourier Transform Infrared Spectroscopy

Authors: W. Ketren, J. Wannapeera, Z. Heishun, A. Ryuichi, K. Toshiteru, M. Kouichi, O. Hideaki

Abstract:

Degradative solvent extraction is the method developed for biomass upgrading by dewatering and fractionation of biomass under the mild condition. However, the conversion mechanism of the degradative solvent extraction method has not been fully understood so far. The rice straw was treated in 1-methylnaphthalene (1-MN) at a different solvent-treatment temperature varied from 250 to 350 oC with the residence time for 60 min. The liquid membrane-Fourier Transform Infrared Spectroscopy (FTIR) technique is applied to study the processing mechanism in-depth without separation of the solvent. It has been found that the strength of the oxygen-hydrogen stretching  (3600-3100 cm-1) decreased slightly with increasing temperature in the range of 300-350 oC. The decrease of the hydroxyl group in the solvent soluble suggested dehydration reaction taking place between 300 and 350 oC. FTIR spectra in the carbonyl stretching region (1800-1600 cm-1) revealed the presence of esters groups, carboxylic acid and ketonic groups in the solvent-soluble of biomass. The carboxylic acid increased in the range of 200 to 250 oC and then decreased. The prevailing of aromatic groups showed that the aromatization took place during extraction at above 250 oC. From 300 to 350 oC, the carbonyl functional groups in the solvent-soluble noticeably decreased. The removal of the carboxylic acid and the decrease of esters into the form of carbon dioxide indicated that the decarboxylation reaction occurred during the extraction process.

Keywords: biomass waste, degradative solvent extraction, mechanism, upgrading

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1610 Remote Sensing-Based Prediction of Asymptomatic Rice Blast Disease Using Hyperspectral Spectroradiometry and Spectral Sensitivity Analysis

Authors: Selvaprakash Ramalingam, Rabi N. Sahoo, Dharmendra Saraswat, A. Kumar, Rajeev Ranjan, Joydeep Mukerjee, Viswanathan Chinnasamy, K. K. Chaturvedi, Sanjeev Kumar

Abstract:

Rice is one of the most important staple food crops in the world. Among the various diseases that affect rice crops, rice blast is particularly significant, causing crop yield and economic losses. While the plant has defense mechanisms in place, such as chemical indicators (proteins, salicylic acid, jasmonic acid, ethylene, and azelaic acid) and resistance genes in certain varieties that can protect against diseases, susceptible varieties remain vulnerable to these fungal diseases. Early prediction of rice blast (RB) disease is crucial, but conventional techniques for early prediction are time-consuming and labor-intensive. Hyperspectral remote sensing techniques hold the potential to predict RB disease at its asymptomatic stage. In this study, we aimed to demonstrate the prediction of RB disease at the asymptomatic stage using non-imaging hyperspectral ASD spectroradiometer under controlled laboratory conditions. We applied statistical spectral discrimination theory to identify unknown spectra of M. Oryzae, the fungus responsible for rice blast disease. The infrared (IR) region was found to be significantly affected by RB disease. These changes may result in alterations in the absorption, reflection, or emission of infrared radiation by the affected plant tissues. Our research revealed that the protein spectrum in the IR region is impacted by RB disease. In our study, we identified strong correlations in the region (Amide group - I) around X 1064 nm and Y 1300 nm with the Lambda / Lambda derived spectra methods for protein detection. During the stages when the disease is developing, typically from day 3 to day 5, the plant's defense mechanisms are not as effective. This is especially true for the PB-1 variety of rice, which is highly susceptible to rice blast disease. Consequently, the proteins in the plant are adversely affected during this critical time. The spectral contour plot reveals the highly correlated spectral regions 1064 nm and Y 1300 nm associated with RB disease infection. Based on these spectral sensitivities, we developed new spectral disease indices for predicting different stages of disease emergence. The goal of this research is to lay the foundation for future UAV and satellite-based studies aimed at long-term monitoring of RB disease.

Keywords: rice blast, asymptomatic stage, spectral sensitivity, IR

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1609 Rapid, Automated Characterization of Microplastics Using Laser Direct Infrared Imaging and Spectroscopy

Authors: Andreas Kerstan, Darren Robey, Wesam Alvan, David Troiani

Abstract:

Over the last 3.5 years, Quantum Cascade Lasers (QCL) technology has become increasingly important in infrared (IR) microscopy. The advantages over fourier transform infrared (FTIR) are that large areas of a few square centimeters can be measured in minutes and that the light intensive QCL makes it possible to obtain spectra with excellent S/N, even with just one scan. A firmly established solution of the laser direct infrared imaging (LDIR) 8700 is the analysis of microplastics. The presence of microplastics in the environment, drinking water, and food chains is gaining significant public interest. To study their presence, rapid and reliable characterization of microplastic particles is essential. Significant technical hurdles in microplastic analysis stem from the sheer number of particles to be analyzed in each sample. Total particle counts of several thousand are common in environmental samples, while well-treated bottled drinking water may contain relatively few. While visual microscopy has been used extensively, it is prone to operator error and bias and is limited to particles larger than 300 µm. As a result, vibrational spectroscopic techniques such as Raman and FTIR microscopy have become more popular, however, they are time-consuming. There is a demand for rapid and highly automated techniques to measure particle count size and provide high-quality polymer identification. Analysis directly on the filter that often forms the last stage in sample preparation is highly desirable as, by removing a sample preparation step it can both improve laboratory efficiency and decrease opportunities for error. Recent advances in infrared micro-spectroscopy combining a QCL with scanning optics have created a new paradigm, LDIR. It offers improved speed of analysis as well as high levels of automation. Its mode of operation, however, requires an IR reflective background, and this has, to date, limited the ability to perform direct “on-filter” analysis. This study explores the potential to combine the filter with an infrared reflective surface filter. By combining an IR reflective material or coating on a filter membrane with advanced image analysis and detection algorithms, it is demonstrated that such filters can indeed be used in this way. Vibrational spectroscopic techniques play a vital role in the investigation and understanding of microplastics in the environment and food chain. While vibrational spectroscopy is widely deployed, improvements and novel innovations in these techniques that can increase the speed of analysis and ease of use can provide pathways to higher testing rates and, hence, improved understanding of the impacts of microplastics in the environment. Due to its capability to measure large areas in minutes, its speed, degree of automation and excellent S/N, the LDIR could also implemented for various other samples like food adulteration, coatings, laminates, fabrics, textiles and tissues. This presentation will highlight a few of them and focus on the benefits of the LDIR vs classical techniques.

Keywords: QCL, automation, microplastics, tissues, infrared, speed

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1608 YOLO-IR: Infrared Small Object Detection in High Noise Images

Authors: Yufeng Li, Yinan Ma, Jing Wu, Chengnian Long

Abstract:

Infrared object detection aims at separating small and dim targets from cluttered backgrounds, and its capabilities extend beyond the limits of visible light, making it invaluable in a wide range of applications, such as improving safety, security, efficiency, and functionality. However, existing methods are usually sensitive to the noise of the input infrared image, leading to a decrease in target detection accuracy and an increase in the false alarm rate in high-noise environments. To address this issue, an infrared small target detection algorithm called YOLO-IR is proposed in this paper to improve the robustness to high infrared noise. To address the problem that high noise significantly reduces the clarity and reliability of target features in infrared images, we design a soft-threshold coordinate attention mechanism to improve the model’s ability to extract target features and its robustness to noise. Since the noise may overwhelm the local details of the target, resulting in the loss of small target features during depth down-sampling, we propose a deep and shallow feature fusion neck to improve the detection accuracy. In addition, because the generalized Intersection over Union (IoU)-based loss functions may be sensitive to noise and lead to unstable training in high-noise environments, we introduce a Wasserstein-distance based loss function to improve the training of the model. The experimental results show that YOLO-IR achieves a 5.0% improvement in recall and a 6.6% improvement in the F1 score over the existing state-of-the-art model.

Keywords: infrared small target detection, high noise, robustness, soft-threshold coordinate attention, feature fusion

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1607 Simulation and Characterization of Compact Magnetic Proton Recoil Spectrometer for Fast Neutron Spectra Measurements

Authors: Xingyu Peng, Qingyuan Hu, Xuebin Zhu, Xi Yuan

Abstract:

Neutron spectrometry has contributed much to the development of nuclear physics since 1932 and has also become an importance tool in several other fields, notably nuclear technology, fusion plasma diagnostics and radiation protection. Compared with neutron fluxes, neutron spectra can provide more detailed information on the internal physical process of neutron sources, such as fast neutron reactors, fusion plasma, fission-fusion hybrid reactors, and so on. However, high performance neutron spectrometer is not so commonly available as it requires the use of large and complex instrumentation. This work describes the development and characterization of a compact magnetic proton recoil (MPR) spectrometer for high-resolution measurements of fast neutron spectra. The compact MPR spectrometer is featured by its large recoil angle, small size permanent analysis magnet, short beam transport line and dual-purpose detector array for both steady state and pulsed neutron spectra measurement. A 3-dimensional electromagnetic particle transport code is developed to simulate the response function of the spectrometer. Simulation results illustrate that the performance of the spectrometer is mainly determined by n-p recoil foil and proton apertures, and an overall energy resolution of 3% is achieved for 14 MeV neutrons. Dedicated experiments using alpha source and mono-energetic neutron beam are employed to verify the simulated response function of the compact MPR spectrometer. These experimental results show a good agreement with the simulated ones, which indicates that the simulation code possesses good accuracy and reliability. The compact MPR spectrometer described in this work is a valuable tool for fast neutron spectra measurements for the fission or fusion devices.

Keywords: neutron spectrometry, magnetic proton recoil spectrometer, neutron spectra, fast neutron

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1606 Synthesis, Spectral, Thermal, Optical and Dielectric Studies of Some Organic Arylidene Derivatives

Authors: S. Sathiyamoorthi, P. Srinivasan, K. Suganya Devi

Abstract:

Arylidene derivatives are the subclass of chalcone derivatives. Chalcone derivatives are studied widely for the past decade because of its nonlinearity. To seek new organic group of crystals which suit for fabrication of optical devices, three-member organic arylidene crystals were synthesized by using Claisen–Schmidt condensation reaction. Good quality crystals were grown by slow evaporation method. Functional groups were identified by FT-IR and FT-Raman spectrum. Optical transparency and optical band gap were determined by UV-Vis-IR studies. Thermal stability and melting point were calculated using TGA and DSC. Variation of dielectric loss and dielectric constant with frequency were calculated by dielectric measurement.

Keywords: DSC and TGA studies, nonlinear optic studies, Fourier Transform Infrared Spectroscopy, UV-vis-NIR spectra

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1605 Dow Polyols near Infrared Chemometric Model Reduction Based on Clustering: Reducing Thirty Global Hydroxyl Number (OH) Models to Less Than Five

Authors: Wendy Flory, Kazi Czarnecki, Matthijs Mercy, Mark Joswiak, Mary Beth Seasholtz

Abstract:

Polyurethane Materials are present in a wide range of industrial segments such as Furniture, Building and Construction, Composites, Automotive, Electronics, and more. Dow is one of the leaders for the manufacture of the two main raw materials, Isocyanates and Polyols used to produce polyurethane products. Dow is also a key player for the manufacture of Polyurethane Systems/Formulations designed for targeted applications. In 1990, the first analytical chemometric models were developed and deployed for use in the Dow QC labs of the polyols business for the quantification of OH, water, cloud point, and viscosity. Over the years many models have been added; there are now over 140 models for quantification and hundreds for product identification, too many to be reasonable for support. There are 29 global models alone for the quantification of OH across > 70 products at many sites. An attempt was made to consolidate these into a single model. While the consolidated model proved good statistics across the entire range of OH, several products had a bias by ASTM E1655 with individual product validation. This project summary will show the strategy for global model updates for OH, to reduce the number of models for quantification from over 140 to 5 or less using chemometric methods. In order to gain an understanding of the best product groupings, we identify clusters by reducing spectra to a few dimensions via Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP). Results from these cluster analyses and a separate validation set allowed dow to reduce the number of models for predicting OH from 29 to 3 without loss of accuracy.

Keywords: hydroxyl, global model, model maintenance, near infrared, polyol

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1604 Solar Wind Turbulence and the Role of Circularly Polarized Dispersive Alfvén Wave

Authors: Swati Sharma, R. P. Sharma

Abstract:

We intend to study the nonlinear evolution of the parallel propagating finite frequency Alfvén wave (also called Dispersive Alfvén wave/Hall MHD wave) propagating in the solar wind regime of the solar region when a perpendicularly propagating magnetosonic wave is present in the background. The finite frequency Alfvén wave behaves differently from the usual non-dispersive behavior of the Alfvén wave. To study the nonlinear processes (such as filamentation) taking place in the solar regions such as solar wind, the dynamical equation of both the waves are derived. Numerical simulation involving finite difference method for the time domain and pseudo spectral method for the spatial domain is then performed to analyze the transient evolution of these waves. The power spectra of the Dispersive Alfvén wave is also investigated. The power spectra shows the distribution of the magnetic field intensity of the Dispersive Alfvén wave over different wave numbers. For DAW the spectra shows a steepening for scales larger than the proton inertial length. This means that the wave energy gets transferred to the solar wind particles as the wave reaches higher wave numbers. This steepening of the power spectra can be explained on account of the finite frequency of the Alfvén wave. The obtained results are consistent with the observations made by CLUSTER spacecraft.

Keywords: solar wind, turbulence, dispersive alfven wave

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1603 Evaluation of Heterogeneity of Paint Coating on Metal Substrate Using Laser Infrared Thermography and Eddy Current

Authors: S. Mezghani, E. Perrin, J. L. Bodnar, J. Marthe, B. Cauwe, V. Vrabie

Abstract:

Non contact evaluation of the thickness of paint coatings can be attempted by different destructive and nondestructive methods such as cross-section microscopy, gravimetric mass measurement, magnetic gauges, Eddy current, ultrasound or terahertz. Infrared thermography is a nondestructive and non-invasive method that can be envisaged as a useful tool to measure the surface thickness variations by analyzing the temperature response. In this paper, the thermal quadrupole method for two layered samples heated up with a pulsed excitation is firstly used. By analyzing the thermal responses as a function of thermal properties and thicknesses of both layers, optimal parameters for the excitation source can be identified. Simulations show that a pulsed excitation with duration of ten milliseconds allows to obtain a substrate-independent thermal response. Based on this result, an experimental setup consisting of a near-infrared laser diode and an Infrared camera was next used to evaluate the variation of paint coating thickness between 60 µm and 130 µm on two samples. Results show that the parameters extracted for thermal images are correlated with the estimated thicknesses by the Eddy current methods. The laser pulsed thermography is thus an interesting alternative nondestructive method that can be moreover used for non conductive substrates.

Keywords: non destructive, paint coating, thickness, infrared thermography, laser, heterogeneity

Procedia PDF Downloads 612