263 resultados para infrared parametric laser
Resumo:
The chief challenge facing persistent robotic navigation using vision sensors is the recognition of previously visited locations under different lighting and illumination conditions. The majority of successful approaches to outdoor robot navigation use active sensors such as LIDAR, but the associated weight and power draw of these systems makes them unsuitable for widespread deployment on mobile robots. In this paper we investigate methods to combine representations for visible and long-wave infrared (LWIR) thermal images with time information to combat the time-of-day-based limitations of each sensing modality. We calculate appearance-based match likelihoods using the state-of-the-art FAB-MAP [1] algorithm to analyse loop closure detection reliability across different times of day. We present preliminary results on a dataset of 10 successive traverses of a combined urban-parkland environment, recorded in 2-hour intervals from before dawn to after dusk. Improved location recognition throughout an entire day is demonstrated using the combined system compared with methods which use visible or thermal sensing alone.
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While the emission rate of ultrafine particles has been measured and quantified, there is very little information on the emission rates of ions and charged particles from laser printers. This paper describes a methodology that can be adopted for measuring the surface charge density on printed paper and the ion and charged particle emissions during operation of a high-emitting laser printer and shows how emission rates of ultrafine particles, ions and charged particles may be quantified using a controlled experiment within a closed chamber.
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Quantifying spatial and/or temporal trends in environmental modelling data requires that measurements be taken at multiple sites. The number of sites and duration of measurement at each site must be balanced against costs of equipment and availability of trained staff. The split panel design comprises short measurement campaigns at multiple locations and continuous monitoring at reference sites [2]. Here we present a modelling approach for a spatio-temporal model of ultrafine particle number concentration (PNC) recorded according to a split panel design. The model describes the temporal trends and background levels at each site. The data were measured as part of the “Ultrafine Particles from Transport Emissions and Child Health” (UPTECH) project which aims to link air quality measurements, child health outcomes and a questionnaire on the child’s history and demographics. The UPTECH project involves measuring aerosol and particle counts and local meteorology at each of 25 primary schools for two weeks and at three long term monitoring stations, and health outcomes for a cohort of students at each school [3].
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The mining environment presents a challenging prospect for stereo vision. Our objective is to produce a stereo vision sensor suited to close-range scenes consisting mostly of rocks. This sensor should produce a dense depth map within real-time constraints. Speed and robustness are of foremost importance for this application. This paper compares a number of stereo matching algorithms in terms of robustness and suitability to fast implementation. These include traditional area-based algorithms, and algorithms based on non-parametric transforms, notably the rank and census transforms. Our experimental results show that the rank and census transforms are robust with respect to radiometric distortion and introduce less computational complexity than conventional area-based matching techniques.
Resumo:
The mining environment, being complex, irregular and time varying, presents a challenging prospect for stereo vision. For this application, speed, reliability, and the ability to produce a dense depth map are of foremost importance. This paper assesses the suitability of a number of matching techniques for use in a stereo vision sensor for close range scenes consisting primarily of rocks. These include traditional area-based matching metrics, and non-parametric transforms, in particular, the rank and census transforms. Experimental results show that the rank and census transforms exhibit a number of clear advantages over area-based matching metrics, including their low computational complexity, and robustness to certain types of distortion.
Resumo:
A frame-rate stereo vision system, based on non-parametric matching metrics, is described. Traditional metrics, such as normalized cross-correlation, are expensive in terms of logic. Non-parametric measures require only simple, parallelizable, functions such as comparators, counters and exclusive-or, and are thus very well suited to implementation in reprogrammable logic.
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An important component of current models for interstellar and circumstellar evolution is the infrared (IR)spectral data collected from stellar outflows around oxygen-rich stars and from the general interstellar medium [1]. IR spectra from these celestial bodies are usually interpreted as showing the general properties of sub-micron sized silicate grains [2]. Two major features at 10 and 20 microns are reasonably attributed to amorphous olivine or pyroxene (e.g. Mg2Si04 or MgSi03) on the basis of comparisons with natural standards and vapor condensed silicates [3-6]. In an attempt to define crystallisation rates for spectrally amorphous condensates, Nuth and Donn [5] annealed experimentally produced amorphous magnesium silicate smokes at 1000K. On analysing these smokes at various annealing times, Nuth and Donn [5] showed that changes in crystallinity measured by bulk X-ray diffraction occured at longer annealing times (days) than changes measured by IR spectra (a few hours). To better define the onset of crystallinity in these magnesium silicates, we have examined each annealed product using a JEOL 1OOCX analytical electron microscope (AEM). In addition, the development of chemical diversity with annealing has been monitored using energy dispersive spectroscopy of individual grains from areas <20nm in diameter. Furthermore, the crystallisation kinetics of these smokes under ambient, room temperature conditions have been examined using bulk and fourier transform infrared (FTIR)spectra.
Resumo:
Experimentally obtained Mg.SiO smokes were studied by analytical electron microscopy using the same samples that had been previously characterized by repeated infrared spectroscopy. Analytical electron microscopy shows that unannealed smokes contain some degree of microcrystallinity which increases with increased annealing for up to 30 hr. An SiO2 polymorph (tridymite) and MgO may form contemporaneously as a result of growth of forsterite (Mg2SiO4) microcrystallites in the initially nonstoichiometric smokes. After 4 hr annealing, forsterite and tridymite react to enstatite (MgSiO3). We suggest that infrared spectroscopy and X-ray diffraction analysis should be complemented by detailed analytical electron microscopy to detect budding crystallinity in vapor phase condensates.
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The Clay Minerals Society Source Clay kaolinites, Georgia KGa-1 and KGa-2, have been subjected to particle size determinations by 1) conventional sedimentation methods, 2) electron microscopy and image analysis, and 3) laser scattering using improved algorithms for the interaction of light with small particles. Particle shape, size distribution, and crystallinity vary considerably for each kaolinite. Replicate analyses of separated size fractions showed that in the <2 µm range, the sedimentation/centrifugation method of Tanner and Jackson (1947) is reproducible for different kaolinite types and that the calculated size ranges are in reasonable agreement with the size bins estimated from laser scattering. Particle sizes determined by laser scattering must be calculated using Mie theory when the dominant particle size is less than ∼5 µm. Based on this study of two well-known and structurally different kaolinites, laser scattering, with improved data reduction algorithms that include Mie theory, should be considered an internally consistent and rapid technique for clay particle sizing.
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In this research, we have used vibrational spectroscopy to study the phosphate mineral kosnarite KZr2(PO4)3. Interest in this mineral rests with the ability of zirconium phosphates (ZP) to lock in radioactive elements. ZP have the capacity to concentrate and immobilize the actinide fraction of radioactive phases in homogeneous zirconium phosphate phases. The Raman spectrum of kosnarite is characterized by a very intense band at 1,026 cm−1 assigned to the symmetric stretching vibration of the PO4 3− ν1 symmetric stretching vibration. The series of bands at 561, 595 and 638 cm−1 are assigned to the ν4 out-of-plane bending modes of the PO4 3− units. The intense band at 437 cm−1 with other bands of lower wavenumber at 387, 405 and 421 cm−1 is assigned to the ν2 in-plane bending modes of the PO4 3− units. The number of bands in the antisymmetric stretching region supports the concept that the symmetry of the phosphate anion in the kosnarite structure is preserved. The width of the infrared spectral profile and its complexity in contrast to the well-resolved Raman spectrum show that the pegmatitic phosphates are better studied with Raman spectroscopy.
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The mineral beryllonite has been characterized by the combination of Raman spectroscopy and infrared spectroscopy. SEM–EDX was used for the chemical analysis of the mineral. The intense sharp Raman band at 1011 cm-1, was assigned to the phosphate symmetric stretching mode. Raman bands at 1046, 1053, 1068 and the low intensity bands at 1147, 1160 and 1175 cm-1 are attributed to the phosphate antisymmetric stretching vibrations. The number of bands in the antisymmetric stretching region supports the concept of symmetry reduction of the phosphate anion in the beryllonite structure. This concept is supported by the number of bands found in the out-of-plane bending region. Multiple bands are also found in the in-plane bending region with Raman bands at 399, 418, 431 and 466 cm-1. Strong Raman bands at 304 and 354 cm-1 are attributed to metal oxygen vibrations. Vibrational spectroscopy served to determine the molecular structure of the mineral. The pegmatitic phosphate minerals such as beryllonite are more readily studied by Raman spectroscopy than infrared spectroscopy.
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Detailed investigation of an intermediate member of the reddingite–phosphoferrite series, using infrared and Raman spectroscopy, scanning electron microcopy and electron microprobe analysis, has been carried out on a homogeneous sample from a lithium-bearing pegmatite named Cigana mine, near Conselheiro Pena, Minas Gerais, Brazil. The determined formula is (Mn1.60Fe1.21Ca0.01Mg0.01)∑2.83(PO4)2.12⋅(H2O2.85F0.01)∑2.86 indicating predominance in the reddingite member. Raman spectroscopy coupled with infrared spectroscopy supports the concept of phosphate, hydrogen phosphate and dihydrogen phosphate units in the structure of reddingite-phosphoferrite. Infrared and Raman bands attributed to water and hydroxyl stretching modes are identified. Vibrational spectroscopy adds useful information to the molecular structure of reddingite–phosphoferrite.
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Determining the properties and integrity of subchondral bone in the developmental stages of osteoarthritis, especially in a form that can facilitate real-time characterization for diagnostic and decision-making purposes, is still a matter for research and development. This paper presents relationships between near infrared absorption spectra and properties of subchondral bone obtained from 3 models of osteoarthritic degeneration induced in laboratory rats via: (i) menisectomy (MSX); (ii) anterior cruciate ligament transaction (ACL); and (iii) intra-articular injection of mono-ido-acetate (1 mg) (MIA), in the right knee joint, with 12 rats per model group (N = 36). After 8 weeks, the animals were sacrificed and knee joints were collected. A custom-made diffuse reflectance NIR probe of diameter 5 mm was placed on the tibial surface and spectral data were acquired from each specimen in the wavenumber range 4000–12 500 cm− 1. After spectral acquisition, micro computed tomography (micro-CT) was performed on the samples and subchondral bone parameters namely: bone volume (BV) and bone mineral density (BMD) were extracted from the micro-CT data. Statistical correlation was then conducted between these parameters and regions of the near infrared spectra using multivariate techniques including principal component analysis (PCA), discriminant analysis (DA), and partial least squares (PLS) regression. Statistically significant linear correlations were found between the near infrared absorption spectra and subchondral bone BMD (R2 = 98.84%) and BV (R2 = 97.87%). In conclusion, near infrared spectroscopic probing can be used to detect, qualify and quantify changes in the composition of the subchondral bone, and could potentially assist in distinguishing healthy from OA bone as demonstrated with our laboratory rat models.
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Infrared spectroscopy has been used to characterize and compare four palygorskite mineral samples from China. The position of the main bands identified by infrared spectra is similar, but there are some differences in intensity, which are significant. In addition, several additional bands are observed in the spectra of palygorskite and their impurities. This variability is attributed to differences in the geological environment, such as the degree of weathering and the extent of transportation of the minerals during formation or deposition, and the impurity content in these palygorskites. The bands of water and hydroxyl groups in these spectra of palygorskite samples have been studied. The characteristic band of palygorskite is observed at 1195 cm�1. Another four bands observed at 3480, 3380, 3266 and 3190 cm�1 are attributed to the water molecules in the palygorskite structure. These results suggest that the infrared spectra of palygorskites mineral from different regions are decided not only by the main physicochemical properties of palygorskite, but also by the amount and kind of impurities.