Analysis Of Spectral Features Research Articles

Face recognition using spectral features

Face recognition is a challenging task in computer vision and pattern recognition. It is well-known that obtaining a low-dimensional feature representation with enhanced discriminatory power is of paramount importance to face recognition. Moreover, recent research has shown that the face images reside on a possibly nonlinear manifold. Thus, how to effectively exploit the hidden structure is a key problem that significantly affects the recognition results. In this paper, we propose a new unsupervised nonlinear feature extraction method called spectral feature analysis (SFA). The main advantages of SFA over traditional feature extraction methods are: (1) SFA does not suffer from the small-sample-size problem; (2) SFA can extract discriminatory information from the data, and we show that linear discriminant analysis can be subsumed under the SFA framework; (3) SFA can effectively discover the nonlinear structure hidden in the data. These appealing properties make SFA very suitable for face recognition tasks. Experimental results on three benchmark face databases illustrate the superiority of SFA over traditional methods.

G-Anisotropy of the S2-State Manganese Cluster in Single Crystals of Cyanobacterial Photosystem II Studied by W-Band Electron Paramagnetic Resonance Spectroscopy

The multiline signal from the S2-state manganese cluster in the oxygen evolving complex of photosystem II (PSII) was observed in single crystals of a thermophilic cyanobacterium Thermosynechococcus vulcanus for the first time by W-band (94 GHz) electron paramagnetic resonance (EPR). At W-band, spectra were characterized by the g-anisotropy, which enabled the precise determination of the tensor. Distinct hyperfine splittings (hfs's) as seen in frozen solutions of PSII at X-band (9.5 GHz) were detected in most of the crystal orientations relative to the magnetic field. In some orientations, however, the hfs's disappeared due to overlapping of a large number of EPR lines from eight crystallographic symmetry-related sites of the manganese cluster within the unit cell of the crystal. Analysis of the orientation-dependent spectral features yielded the following g-tensor components: g(x) = 1.988, g(y) = 1.981, g(z) = 1.965. The principal values suggested an approximate axial symmetry around the Mn(III) ion in the cluster.

Multi-seasonal spectral characteristics analysis of coastal salt marsh vegetation in Shanghai, China

Remote sensing technology has become the primary tool for ecological research on a large scale. The spectral characteristics of the salt marsh vegetation canopy, including four main communities, Phragmites australis community, Spartina alterniflora community, Scirpus mariqueter community and Carex scabrifolia community, were measured in the seasons of spring, summer and autumn by a ground FieldSpec™ Pro JR spectroradiometer, at the Chongming Dongtan Nature Reserve in Shanghai. The spectral data were converted to the reflectance curves, and their first derivative curves between 350 nm and 1000 nm were calculated. The differences in the reflectance and first derivative curves were then analyzed, with particular attention paid to the characteristics in the bands of visible, “green peak”, “red edge” and near infrared. The results from this study showed that the different salt marsh communities had different and rather unique spectral characteristics during the three seasons studied. The near-ground spectral reflectance varied with the growing season, community type and its phenology. The discrimination ability, in terms of variations in the spectral reflectance, among the four major salt marsh communities was highest in autumn. It is proposed that a realistic strategy for classifying the salt marsh vegetation could be adopted by integrating and analyzing their remotely sensed images of multi-seasons. The implications of the results from this study in terms of serving as a tool for monitoring and mapping the distribution pattern and dynamics of salt marsh vegetation on the eastern coast of China are discussed.

Polarization and experimental configuration analyses of sum frequency generation vibrational spectra, structure, and orientational motion of the air/water interface

Here we report a detailed study on spectroscopy, structure, and orientational distribution, as well as orientational motion, of water molecules at the air/water interface, investigated with sum frequency generation vibrational spectroscopy (SFG-VS). Quantitative polarization and experimental configuration analyses of the SFG data in different polarizations with four sets of experimental configurations can shed new light on our present understanding of the air/water interface. Firstly, we concluded that the orientational motion of the interfacial water molecules can only be in a limited angular range, instead of rapidly varying over a broad angular range in the vibrational relaxation time as suggested previously. Secondly, because different vibrational modes of different molecular species at the interface has different symmetry properties, polarization and symmetry analyses of the SFG-VS spectral features can help the assignment of the SFG-VS spectra peaks to different interfacial species. These analyses concluded that the narrow 3693 cm(-1) and broad 3550 cm(-1) peaks belong to C(infinityv) symmetry, while the broad 3250 and 3450 cm(-1) peaks belong to the symmetric stretching modes with C2v symmetry. Thus, the 3693 cm(-1) peak is assigned to the free OH, the 3550 cm(-1) peak is assigned to the singly hydrogen-bonded OH stretching mode, and the 3250 and 3450 cm(-1) peaks are assigned to interfacial water molecules as two hydrogen donors for hydrogen bonding (with C2v symmetry), respectively. Thirdly, analysis of the SFG-VS spectra concluded that the singly hydrogen-bonded water molecules at the air/water interface have their dipole vector directed almost parallel to the interface and is with a very narrow orientational distribution. The doubly hydrogen-bonded donor water molecules have their dipole vector pointing away from the liquid phase.

Emission spectroscopy of clay minerals and evidence for poorly crystalline aluminosilicates on Mars from Thermal Emission Spectrometer data

To understand the aqueous history of Mars, it is critical to constrain the alteration mineralogy of the Martian surface. Previously published analyses of thermal infrared (λ = 6–25 μm) remote sensing data of Mars suggest that dark regions have ∼15–20% clay minerals. However, near‐infrared (λ = 1–3 μm) spectral results generally do not identify widespread clay minerals. Thermal infrared detections of clays on Mars are difficult to interpret owing in part to the relative paucity of published spectral analyses of clay minerals and clay‐bearing materials using similar spectra (thermal infrared emission spectra). In this study, we present an analysis of the thermal emission spectral features (λ = ∼6–25 μm or 400–1650 cm−1) of a suite of clay mineral reference materials and clay‐bearing rocks, linking their spectral features to the crystal chemical properties of the clays. On the basis of this context provided by the emission spectral analysis of clay minerals and clay‐bearing rocks, we reconsider the evidence for clay minerals on Mars from Thermal Emission Spectrometer (TES) results. We propose that global‐scale clay abundances determined from TES probably represent a geologically significant surface component, though they may actually correspond to poorly crystalline aluminosilicates with similar Si/O ratios to clay minerals (0.3–0.4), rather than well‐crystalline clays. If clay minerals or clay‐like materials on Mars are poorly crystalline and/or dessicated, they may be detectable in the thermal infrared, but not easily detected with near‐infrared data sets.

Photometric properties of young blue compact dwarf galaxy candidates

A tiny fraction (<1%) of very metal-deficient (12+log(O/H) 7.6) blue compact dwarf (BCD) galaxies exhibits a nearly galaxy-wide starburst activity and no signatures of an old stellar host galaxy. The evolutionary status and formation history of these most metal-deficient BCDs are still a subject of debate. Various lines of evidence suggest, however, that these systems do not contain a substantial population of stars older than ∼1Gyr and hence qualify as nearby younggalaxy candidates. Elaborated multiwavelength studies of these rare, most metal-deficient BCDs may therefore provide crucial insights into the formation and starburst-driven evolution of lowmass galaxies in the early universe. In particular, these extremely metal-poor BCDs constitute excellent nearby laboratories for studying high-ionization emission and the hardness of the ionizing radiation in nearly pristine extragalactic environments. If we wish to understand the spectra of primeval galaxies, it is highly important to understand how the UV radiation field of these systems changes as metallicity decreases. It is well established that the lower the metallicity, the harder is the radiation from massive stars (Campbell et al. 1986). As a consequence, strong high-ionization lines are expected in the spectra of these most chemically unevolved BCDs. Indeed, deep spectroscopy has led recently to the discovery of high-ionization emission lines, such as [Fe v] λ4227 and [Ne v] λ3346,3426, in addition to strong He ii λ4686 emission, in a few of the most metal-deficient star-forming galaxies known in the local universe, as e.g. the young BCD candidates Tol 1214– 277 (Fricke et al. (2001), Izotov et al. (2004); cf. Fig. 1b, d) and SBS 0335–052 (Izotov et al. (2001); see Fig. 1c). Evidently, spectroscopic studies with large telescopes are crucial for the detection and accurate analysis of those faint spectral features. In order to assess the photometric structure and evolutionary status of young BCD candidates it is of critical importance to correct for the effect of extended nebular emission, as the latter may severely affect colors and age estimates obtained therefrom. One such example is I Zw 18 (Fig. 1a), the second most metal-poor emission-line galaxy known (12+log(O/H)=7.17. . . 7.23; Thuan & Izotov (2005)). This system is embedded within a filamentary low-surface brightness (LSB) envelope, extending out to 18 ′′ (∼1.3 kpc, assuming a distance of 15 Mpc) from its starforming regions. Papaderos et al. (2002), using broad(BV RI) and narrow-band (Hα, [OIII]) HST data, have shown that the extended LSB envelope of this young BCD candidate is entirely due to nebular line emission: ionized gas accounts for more than 80% of the line-of-sight emission at a galactocentric distance of 8 ′′ (∼0.65 kpc) and for up to 50% of the total R light of I Zw 18. Consequently, a twodimensional subtraction of ionized gas emission is indispensable for a meaningful study of the photometric structure of this system. As evident from Fig. 1b, this correction leads to the complete removal of the filamentary LSB envelope in IZw18’s main body, leaving behind a very compact (exponential scale length α ≈ 120 pc) dwarf galaxy (see Papaderos et al. (2002) for details).

Mapping the optical properties of slab-type two-dimensional photonic crystal waveguides

We report on systematic experimental mapping of the transmission properties of two-dimensional silicon-on-insulator photonic crystal waveguides for a broad range of hole radii, slab thicknesses and waveguide lengths for both TE and TM polarizations. Detailed analysis of numerous spectral features allows a direct comparison of experimental data with 3D plane wave and finite-difference time-domain calculations. We find, counter-intuitively, that the bandwidth for low-loss propagation completely vanishes for structural parameters where the photonic band gap is maximized. Our results demonstrate that, in order to maximize the bandwidth of low-loss waveguiding, the hole radius must be significantly reduced. While the photonic band gap considerably narrows, the bandwidth of low-loss propagation in PhC waveguides is increased up to 125nm with losses as low as 8$\pm$2dB/cm.

Time–frequency analysis and estimation of muscle fiber conduction velocity from surface EMG signals during explosive dynamic contractions

Time–frequency analysis of the surface electromyographic (EMG) signal is used to assess muscle fiber membrane properties during dynamic contractions. The aim of this study was to compare the direct estimation of average muscle fiber conduction velocity (CV) with instantaneous mean frequency (iMNF) of surface EMG signals in isometric and explosive dynamic contractions. The muscles investigated were the vastus lateralis and medialis of both thighs in 12 male subjects. The isometric contractions were at linearly increasing force (0–100% of the maximal voluntary contraction in 10 s). The explosive contractions were performed on a multipurpose ergometer-dynamometer (MED). The subject, sitting on the MED, performed six explosive contractions, separated by 2 min rest, by pushing against two force platforms and thrusting himself backwards with the maximum possible speed, while completely extending his legs. The estimated CV significantly increased with force in both the isometric (mean ± S.D., from 3.24 ± 0.34 to 5.12 ± 0.31 m/s for vastus lateralis and from 3.17 ± 0.26 to 5.11 ± 0.34 m/s for vastus medialis, with force in the range 10–100% of the maximal voluntary contraction level) and explosive contractions (from 4.36 ± 0.49 to 5.00 ± 0.47 m/s for vastus lateralis, and from 4.32 ± 0.46 to 4.94 ± 0.44 m/s for vastus medialis, with force in the range 17.5–100% of maximal thrusting force). Moreover, estimated CV was not significantly different at the maximal force in the two exercises. On the contrary, iMNF, computed from the Choi–Williams time–frequency transform, was significantly lower in the explosive (57.7 ± 8.2 and 66.5 ± 10.3 Hz for vastus laterialis and medialis, respectively) than in the isometric exercises (73.7 ± 9.2 and 75.0 ± 8.5 Hz for vastus laterialis and medialis, respectively) and did not change with force in any of the conditions. It was concluded that EMG spectral features provide different information with respect to average muscle fiber CV in dynamic contractions. Thus, in general, they cannot be used to infer CV changes during the exertion of a dynamic task. A joint analysis of CV and EMG spectral features is necessary in this type of contractions.

Spectral feature analysis for assessment of water status and health level in coast live oak (Quercus agrifolia) leaves

Reflectance and relative water content (RWC %) were measured from a total of 306 coast live oak (Quercus agrifolia) leaf samples. The maximum (or minimum) first derivative (1D) and its corresponding wavelength position (WP) were extracted from 10 spectral slopes along each spectral reflectance curve. A correlation analysis was conducted between these spectral features (1Ds and WPs) and the corresponding RWC of oak leaves. An analysis of the variance of spectral features and RWC was also carried out between two health levels of oak leaves, healthy and infected. The results indicate that high correlations exist between some derivative spectral features (1Ds and WPs) and the RWC of oak leaves. With all 306 leaf spectra covering a wide range of RWC of oak leaves (including healthy, infected and newly dead), maximum (or minimum) derivative values at both sides of the absorption valleys near 1200, 1400 and 1940 nm and the WP of the right side of the 1200 nm valley and of both sides of the 1400 nm and 1940 nm valleys were found to have high correlations with RWC; and with a selection of 260 samples of only green and green–yellowish leaves (including only healthy and infected levels), the WPs at the right side of the 1400 nm valley, at the left side of the 1940 nm valley and at the red well each have a stable relationship with leave RWC. The result of an ANOVA of 20 spectral features suggests that the difference of some spectral features corresponding to two health levels of oak leaves is significant at a 0.95 confidence level, especially for the above-mentioned wavelength position features.

Characteristics of human sperm DNA and its relationship with male infertility

To determine variation in sperm chromatin among different categories of human semen samples. 34 human semen samples including 16 normozoospermic, 15 asthenozoospermic and 3 oligoasthenozoospermic. Assessment of the purity of the DNA samples was performed by spectral characteristic analysis (within a wavelength of 230–290nm) as well as calculation of A260/A280 ratio. Estimation of the DNA content, RNA and protein as contaminants were done by diphenylamine method, orcinol method and Lowry's method respectively. RAPD analyses of sperm DNA samples (categorized on the basis of motility difference) were done using random decamer primer (5'AATCGGGCTG 3') solely to detect polymorphism within different categories of semen samples. A dissimilarity matrix was prepared for identifying the extent of variation. Band frequencies were also calculated. Spectral analysis revealed no observable differences for respective DNA samples. The A260/A280ratios (1.98± 0.2) indicated pure DNA samples. Results of DNA content estimation showed a lack of correlation with the nature of the semen samples. RNA was absent in all cases and some of the DNA samples had protein contamination. Identification of the major bands for each category of DNA samples was performed only on higher values of the band frequencies (0.75–1.0). Four major bands were recognized in sperm DNA from samples with normal motility (70–80%), with higher dissimilarity indices of 1.0 and 0.8. Five major bands were identified in sperm DNA with 60–70% motility with low values of dissimilarity indices (0.07–0.53). RAPD of sperm DNA with 50–60% motility also showed 5 major bands with frequency of 1.0. The number of major bands recognized in sperm DNA with a motility percentage of (40–50), (30–40) and (0–30) were 1, 5 and 10, respectively. Sperm DNA in two of the oligoasthenozoospermic samples revealed 100% similarity. RAPD analysis of sperm DNA in different semen categories revealed the lack of existence of even a single band with a band frequency of 1.0. The present investigation provides a clear view of the genetic variation among different categories of human semen specimens at the level of sperm chromatin.

Kβ-Detected XANES of Framework-Substituted FeZSM-5 Zeolites

The valence and local symmetry of iron in framework-substituted FeZSM-5 with a high Fe dilution (Si/Fe = 360) was studied by means of Kβ-detected X-ray absorption spectroscopy. This technique combines high-resolution (ΔE ∼1 eV) fluorescence detection of the 3p to 1s (Kβ) transition with the X-ray absorption near-edge structure (XANES) at the Fe K-edge. An absorption-like spectrum is recorded by detecting the Kβ fluorescence intensity as a function of the incident energy that is scanned through the K absorption edge. Kβ-detected XANES spectra allow for a more precise separation of the weak K pre-edge structure from the main edge as compared to conventional absorption spectroscopy. Subsequent analysis and interpretation of the pre-edge spectral features therefore is more accurate. The pre-edge is sensitive to changes in the local coordination and oxidation state of Fe. Using this technique we were able to quantitatively determine the degree of iron extraction out of a zeolite framework upon steaming. With the use of appropriate reference compounds, the pre-edge analysis was used to monitor the activation of low-loaded, framework-substituted FeZSM-5 (0.3 wt % Fe). Template removal and calcination distort the zeolite framework and induce a deviation from Td symmetry for incorporated iron. The (deliberate) presence of water at high temperature (T > 500 °C) facilitates the hydrolysis of the Si−O−Fe bonds and increases the formation of extraframework iron species. The amount of FeIII occupying tetrahedral sites in the MFI-type zeolite decreases to 32% and 19%, respectively, for mild- and hard-steamed samples.

Analysis of spectral absorption features in hyperspectral imagery

Spectral reflectance in the visible and near-infrared wavelengths provides a rapid and inexpensive means for determining the mineralogy of samples and obtaining information on chemical composition. Absorption-band parameters such as the position, depth, width, and asymmetry of the feature have been used to quantitatively estimate composition of samples from hyperspectral field and laboratory reflectance data. The parameters have also been used to develop mapping methods for the analysis of hyperspectral image data. This has resulted in techniques providing surface mineralogical information (e.g., classification) using absorption-band depth and position. However, no attempt has been made to prepare images of the absorption-band parameters. In this paper, a simple linear interpolation technique is proposed in order to derive absorption-band position, depth and asymmetry from hyperspectral image data. AVIRIS data acquired in 1995 over the Cuprite mining area (Nevada, USA) are used to demonstrate the technique and to interpret the data in terms of the known alteration phases characterizing the area. A sensitivity analysis of the methods proposed shows that good results can be obtained for estimating the absorption wavelength position, however the estimated absorption-band-depth is sensitive to the input parameters chosen. The resulting parameter images (depth, position, asymmetry of the absorption) when carefully examined and interpreted by an experienced remote sensing geologist provide key information on surface mineralogy. The estimates of depth and position can be related to the chemistry of the samples and thus allow to bridge the gap between field geochemistry and remote sensing.

Imaging spectroscopy: Earth and planetary remote sensing with the USGS Tetracorder and expert systems

Imaging spectroscopy is a tool that can be used to spectrally identify and spatially map materials based on their specific chemical bonds. Spectroscopic analysis requires significantly more sophistication than has been employed in conventional broadband remote sensing analysis. We describe a new system that is effective at material identification and mapping: a set of algorithms within an expert system decision‐making framework that we call Tetracorder. The expertise in the system has been derived from scientific knowledge of spectral identification. The expert system rules are implemented in a decision tree where multiple algorithms are applied to spectral analysis, additional expert rules and algorithms can be applied based on initial results, and more decisions are made until spectral analysis is complete. Because certain spectral features are indicative of specific chemical bonds in materials, the system can accurately identify and map those materials. In this paper we describe the framework of the decision making process used for spectral identification, describe specific spectral feature analysis algorithms, and give examples of what analyses and types of maps are possible with imaging spectroscopy data. We also present the expert system rules that describe which diagnostic spectral features are used in the decision making process for a set of spectra of minerals and other common materials. We demonstrate the applications of Tetracorder to identify and map surface minerals, to detect sources of acid rock drainage, and to map vegetation species, ice, melting snow, water, and water pollution, all with one set of expert system rules. Mineral mapping can aid in geologic mapping and fault detection and can provide a better understanding of weathering, mineralization, hydrothermal alteration, and other geologic processes. Environmental site assessment, such as mapping source areas of acid mine drainage, has resulted in the acceleration of site cleanup, saving millions of dollars and years in cleanup time. Imaging spectroscopy data and Tetracorder analysis can be used to study both terrestrial and planetary science problems. Imaging spectroscopy can be used to probe planetary systems, including their atmospheres, oceans, and land surfaces.

Near-infrared Raman spectroscopy of human coronary arteries: histopathological classification based on Mahalanobis distance.

In this study, near-infrared Raman spectroscopy (NIRS) was used for evaluation of human atherosclerotic lesions using a simple algorithm based on discriminant analysis. The Mahalanobis distance was used to classify the clustered spectral features extracted from NIRS of a total of 111 arterial fragments of human coronary arteries. Raman spectroscopy has been used for diagnosis of a variety of diseases. For real-time applications, it is important to have a simple algorithm that could perform fast data acquisition and analysis. The ultimate goal is to obtain a feasible diagnosis, which discriminates various atherosclerotic lesions with high sensitivities and specificities. Non-atherosclerotic (NA) arteries, atherosclerotic plaques without calcification (NC), and atherosclerotic plaques with classification (C) were obtained and scanned with an NIR Raman spectrometer with 830-nm laser excitation. An algorithm based on the discriminant analysis using the Mahalanobis distance of the clustered spectral features was used for tissue classification into three categories: Na, NC, and C. Human coronary arteries exhibit different spectral signatures depending on different bio-chemicals present in each tissue type such as collagen, cholesterol, and calcium hydroxyapatite, respectively. It is shown that our algorithm has a maximum sensitivity and specificity of 85% and 89%, respectively, for the diagnosis of the NA tissue type, 85% and 89% for the NC tissue type, and 100% and 100% for the C tissue type. An algorithm (with a minimum of mathematical and computational requirements) based on the discriminant analysis of spectral features has been developed to classify atherosclerotic lesions with high sensitivities and specificities.

Experimental determination of the temperature distribution in trench-confined oxide vertical-cavity surface-emitting lasers

We measured the temperature profile of operating vertical-cavity surface-emitting lasers by means of a contactless optical micro-probe technique, based on the analysis of spectral features in the spontaneous electroluminescence escaping the top Bragg mirror. Increasing the injected current above threshold in the range of 4-10 mA leads to a progressively nonuniform and bell-shaped distribution of temperatures with the laser center ∼40% warmer than the edges. These results validate previous numerical calculations and show the usefulness of the proposed technique compared with the laser wavelength shift method.

Introduction and application of secured principal component regression for analysis of uncalibrated spectral features in optical spectroscopy and chemical sensing.

In this study, a novel chemometric algorithm for improved evaluation of analytical data is presented and applied to three spectroscopic data sets obtained by different analytical methods. This so-called secured principal component regression (sPCR) was developed for detecting and correcting uncalibrated spectral features newly emerging in spectra after finalizing the PCR calibration, which may result in major concentration errors. Hence, detection and correction of uncalibrated features is essential. Furthermore, detected uncalibrated features provide qualitative information for sensing and process monitoring applications indicating problems in the process flow. After conventional PCR calibration, sPCR analyzes measurement data in two steps: The first step investigates whether the obtained data set is consistent with the calibration model or not. If spectroscopic features are found that cannot be modeled by the principal components, they are extracted from the measurement spectrum. This corrected spectrum is then evaluated by conventional PCR. In the Experimental Section, sPCR was successfully applied to three data sets obtained by different spectroscopic measurements in order to corroborate general applicability of the proposed concept. For each data set, one of several substances was excluded from the calibration acting in the sPCR assessment as uncalibrated absorber. The test sets consisted of disturbed and undisturbed samples. A total of 109 out of 110 test samples were correctly classified as disturbed or undisturbed by an uncalibrated absorber. It was confirmed that the extracted disturbance spectra are in accordance with the spectra of the uncalibrated analytes. The concentration results obtained with sPCR were found to be equivalent to conventional PCR results in the case of undisturbed samples and more precise for disturbed samples.

Localized helium excitations in4HeN-benzene clusters

We compute ground and excited state properties of small helium clusters 4He_N containing a single benzene impurity molecule. Ground-state structures and energies are obtained for N=1,2,3,14 from importance-sampled, rigid-body diffusion Monte Carlo (DMC). Excited state energies due to helium vibrational motion near the molecule surface are evaluated using the projection operator, imaginary time spectral evolution (POITSE) method. We find excitation energies of up to ~23 K above the ground state. These states all possess vibrational character of helium atoms in a highly anisotropic potential due to the aromatic molecule, and can be categorized in terms of localized and collective vibrational modes. These results appear to provide precursors for a transition from localized to collective helium excitations at molecular nanosubstrates of increasing size. We discuss the implications of these results for analysis of anomalous spectral features in recent spectroscopic studies of large aromatic molecules in helium clusters.

Fusion of time-dependent gamma production spectra from thermal neutron capture and fast neutron inelastic scattering to improve material detection

Neutron-based inspection techniques are unique in their ability to provide material specific signatures, thus offering very high performance and automatic detection of explosives and other contraband. Thermal neutron capture gamma spectroscopy provides excellent sensitivities to hydrogen, nitrogen, chlorine, and other elements, which are characteristic to most explosives, drugs and other contraband that may be smuggled into the country. Fast neutron gamma production (mostly through inelastic scattering) provides good sensitivity to carbon and oxygen. When necessary, these two types of complementary interactions can be combined to yield a more accurate material determination inside small to medium size containers.Standard pulsed 14MeV electronic neutron generators offer an efficient way to obtain these two types of interactions. Fast (14MeV) neutrons are produced during the pulse. After the pulse, only the decaying thermal neutron population exists, and thus pure neutron capture gamma-rays are produced. Unfortunately, during the pulse (which is normally much longer than the neutron thermalization time) the fast neutron interactions are highly “contaminated” by the interactions of thermal neutrons within the object and the nearby gamma-ray detectors. This creates high background and spectral interferences in the common medium resolution detectors, such as NaI, BGO, etc. The use of an appropriate shielding, neutron spectrum tailoring, full spectral feature analysis as well as temporal information (“die-away” time) resulted in significant performance enhancements in detection of explosives, drugs and other contraband in difficult geometries.

Geographic song variation within and between populations and subspecies of the rufous bristlebird, Dasyornis broadbenti

This work investigated whether the songs of the rufous bristlebird, Dasyornis broadbenti, vary between populations that have become isolated through habitat clearance, in a similar way to that found between island populations of other bird species, separated by ocean. In addition, the extent of song variation between the two extant subspecies of D. broadbenti was investigated. The nature of song elements did not differ between isolated sites within each subspecies' distribution more than between sites sampled within continuous populations. However, multivariate analyses of spectral and temporal features suggested that these features differed between isolated populations more than within continuous populations. In addition, both the nature of song elements and spectral and temporal features differed significantly between the two extant subspecies of D. broadbenti. These taxonomic analyses of song thus supported recent revisions of the subspecific boundaries of D. broadbenti. While there was some evidence that temporal and spectral song features varied more between isolated populations than within a continuous population, it was difficult to eliminate the effect of distance on song variation. Although evidence for song variation as a result of isolation was not strong for this species, clearance of the habitat utilised by D. broadbenti is relatively recent. The suggestion that communication systems of animal populations can be disrupted following isolation through habitat clearance is one that warrants further investigation, especially in taxa with older histories of fragmentation. This study also highlighted the potential for using behavioural information to assist with taxonomic investigations.

Mapping vegetation in Yellowstone National Park using spectral feature analysis of AVIRIS data

Knowledge of the distribution of vegetation on the landscape can be used to investigate ecosystem functioning. The sizes and movements of animal populations can be linked to resources provided by different plant species. This paper demonstrates the application of imaging spectroscopy to the study of vegetation in Yellowstone National Park (Yellowstone) using spectral feature analysis of data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS data, acquired on August 7, 1996, were calibrated to surface reflectance using a radiative transfer model and field reflectance measurements of a ground calibration site. A spectral library of canopy reflectance signatures was created by averaging pixels of the calibrated AVIRIS data over areas of known forest and nonforest vegetation cover types in Yellowstone. Using continuum removal and least squares fitting algorithms in the US Geological Survey's Tetracorder expert system, the distributions of these vegetation types were determined by comparing the absorption features of vegetation in the spectral library with the spectra from the AVIRIS data. The 0.68 μm chlorophyll absorption feature and leaf water absorption features, centered near 0.98 and 1.20 μm, were analyzed. Nonforest cover types of sagebrush, grasslands, willows, sedges, and other wetland vegetation were mapped in the Lamar Valley of Yellowstone. Conifer cover types of lodgepole pine, whitebark pine, Douglas fir, and mixed Engelmann spruce/subalpine fir forests were spectrally discriminated and their distributions mapped in the AVIRIS images. In the Mount Washburn area of Yellowstone, a comparison of the AVIRIS map of forest cover types to a map derived from air photos resulted in an overall agreement of 74.1% (kappa statistic=0.62).