Performance scaling laws for electric propulsion mission analysis
Electric propulsion spacecraft mission performance scaling laws for invariant trajectory, obtaining optimum gross payload over wide range of system input parameters
Bartz, D. R.↗
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Hand-Based Biometric Analysis
Hand-based biometric analysis systems and techniques provide robust hand-based identification and verification. An image of a hand is obtained, which is then segmented into a palm region and separate finger regions. Acquisition of the image is performed without requiring particular orientation or placement restrictions. Segmentation is performed without the use of reference points on the images. Each segment is analyzed by calculating a set of Zernike moment descriptors for the segment. The feature parameters thus obtained are then fused and compared to stored sets of descriptors in enrollment templates to arrive at an identity decision. By using Zernike moments, and through additional manipulation, the biometric analysis is invariant to rotation, scale, or translation or an input image. Additionally, the analysis uses re-use of commonly seen terms in Zernike calculations to achieve additional efficiencies over traditional Zernike moment calculation.
Bebis, George↗
Hand-Based Biometric Analysis
Hand-based biometric analysis systems and techniques are described which provide robust hand-based identification and verification. An image of a hand is obtained, which is then segmented into a palm region and separate finger regions. Acquisition of the image is performed without requiring particular orientation or placement restrictions. Segmentation is performed without the use of reference points on the images. Each segment is analyzed by calculating a set of Zernike moment descriptors for the segment. The feature parameters thus obtained are then fused and compared to stored sets of descriptors in enrollment templates to arrive at an identity decision. By using Zernike moments, and through additional manipulation, the biometric analysis is invariant to rotation, scale, or translation or an in put image. Additionally, the analysis utilizes re-use of commonly-seen terms in Zernike calculations to achieve additional efficiencies over traditional Zernike moment calculation.
Bebis, George↗
Improved Spectral and Angular Characterization of Libya-4 and Dome-C for consistent MODIS and VIIRS Radiometric Scaling
The NASA CERES observed SW and LW fluxes are utilized by the climate community for monitoring the Earth’s energy imbalance and for climate model validation. To facilitate seamless flux and cloud properties across MODIS, VIIRS, and geostationary (GEO) imagers the CERES project intercalibrates the imagers directly comparing the coincident ray-matched analogous channel radiances. For CERES edition 4 products, the MODIS, VIIRS and GEO imagers were radiometrically scaled to the Aqua-MODIS C5 calibration reference. There are no direct comparison opportunities between NPP and NOAA20 VIIRS, since they are positioned a half an orbit apart. The previous usage of Aqua-MODIS as a transfer radiometer is coming to an end, since the Aqua orbit is slowly drifting towards the terminator and will be deorbited in 2026. The CERES project will utilize the Libya-4 and Dome-C invariant targets to radiometrically scale between MODIS and VIIRS reflective solar bands. The Libya-4 and Dome-C Earth invariant targets will be characterized by the repeat cycle angular configuration. The target spectral band adjustment factors (SBAF) will be derived using EMIT and DESIS hyper-spectral observations onboard the ISS and will be compared with the existing SCIAMACHY, GOME-2, and Hyperion SBAFs. The DESIS and EMIT SBAF approach can incorporate the future CLARREO CPF SI traceable hyper-spectral measurements allowing the targets to be referenced to an absolute calibration reference. Utilizing the BRDF and atmospheric corrected characterization of one sensor with another will provide the scaling factors. Consistent scaling factors between the two invariant target validates the method.
David R. Doelling↗
Hypothesis Support Mechanism for Mid-Level Visual Pattern Recognition
A method of mid-level pattern recognition provides for a pose invariant Hough Transform by parametrizing pairs of points in a pattern with respect to at least two reference points, thereby providing a parameter table that is scale- or rotation-invariant. A corresponding inverse transform may be applied to test hypothesized matches in an image and a distance transform utilized to quantify the level of match.
Amador, Jose J↗
Multi-Scale Fractal Analysis of Image Texture and Pattern
Fractals embody important ideas of self-similarity, in which the spatial behavior or appearance of a system is largely independent of scale. Self-similarity is defined as a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. An ideal fractal (or monofractal) curve or surface has a constant dimension over all scales, although it may not be an integer value. This is in contrast to Euclidean or topological dimensions, where discrete one, two, and three dimensions describe curves, planes, and volumes. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution. However, most geographical phenomena are not strictly self-similar at all scales, but they can often be modeled by a stochastic fractal in which the scaling and self-similarity properties of the fractal have inexact patterns that can be described by statistics. Stochastic fractal sets relax the monofractal self-similarity assumption and measure many scales and resolutions in order to represent the varying form of a phenomenon as a function of local variables across space. In image interpretation, pattern is defined as the overall spatial form of related features, and the repetition of certain forms is a characteristic pattern found in many cultural objects and some natural features. Texture is the visual impression of coarseness or smoothness caused by the variability or uniformity of image tone or color. A potential use of fractals concerns the analysis of image texture. In these situations it is commonly observed that the degree of roughness or inexactness in an image or surface is a function of scale and not of experimental technique. The fractal dimension of remote sensing data could yield quantitative insight on the spatial complexity and information content contained within these data. A software package known as the Image Characterization and Modeling System (ICAMS) was used to explore how fractal dimension is related to surface texture and pattern. The ICAMS software was verified using simulated images of ideal fractal surfaces with specified dimensions. The fractal dimension for areas of homogeneous land cover in the vicinity of Huntsville, Alabama was measured to investigate the relationship between texture and resolution for different land covers.
Emerson, Charles W.↗
The cosmological dependence of cluster density profiles
We use N-body simulations to study the shape of mean cluster density and velocity profiles in the nonlinear regime formed via gravitational instability. The dependence of the final structure on both cosmology and initial density field is examined, using a grid of cosmologies and scale-free initial power spectra P(k) varies as k(exp n). Einstein-de Sitter, open (Omega(sub 0) = 0.2 and 0.1) and flat, low density (Omega(sub 0) = 0.2 lambda(sub 0) = 0.8) models are examined, with initial spectral indices n = -2, -1 and 0. For each model, we stack clusters in an appropriately scaled manner to define an average density profile in the nonlinear regime. The profiles are well fit by a power law rho(r) varies as r(exp -alpha) for radii whereat the local density contrast is between 100 and 3000. This covers 99% of the cluster volume. We find a clear trend toward steeper slopes (larger alphas) with both increasing n and decreasing Omega(sub 0). The Omega(sub 0) dependence is partially masked by the n dependence; there is degeneracy in the values of alpha between the Einstein-de Sitter and flat, low-density cosmologies. However, the profile slopes in the open models are consistently higher than the Omega = 1 values for the range of n examined. Cluster density profiles are thus potentially useful cosmological diagnostics. We find no evidence for a constant density core in any of the models, although the density profiles do tend to flatten at small radii. Much of the flattening is due to the force softening required by the simulations. An attempt is made to recover the unsoftened profiles assuming angular momentum invariance. The recovered profiles in Einstein-de Sitter cosmologies are consistent with a pure power law up to the highest density contrasts (10(exp 6)) accessible with our resolution. The low-density models show significant deviation from a power law above density contrasts approximately 10(exp 5). We interpret this curvature as reflecting the non-scale-invariant nature of the background cosmology in these models. These results are at the limit of our resolution and so should be tested in the future using simulations with larger numbers of particles. Such simulations will also provide insight on the broader problem of understanding, in a statistical sense, the full phase space structure of collapsed, cosmological halos.
Crone, Mary M.↗
Applications of Fractal Analytical Techniques in the Estimation of Operational Scale
The observational scale and the resolution of remotely sensed imagery are essential considerations in the interpretation process. Many atmospheric, hydrologic, and other natural and human-influenced spatial phenomena are inherently scale dependent and are governed by different physical processes at different spatial domains. This spatial and operational heterogeneity constrains the ability to compare interpretations of phenomena and processes observed in higher spatial resolution imagery to similar interpretations obtained from lower resolution imagery. This is a particularly acute problem, since longterm global change investigations will require high spatial resolution Earth Observing System (EOS), Landsat 7, or commercial satellite data to be combined with lower resolution imagery from older sensors such as Landsat TM and MSS. Fractal analysis is a useful technique for identifying the effects of scale changes on remotely sensed imagery. The fractal dimension of an image is a non-integer value between two and three which indicates the degree of complexity in the texture and shapes depicted in the image. A true fractal surface exhibits self-similarity, a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution, and the slope of the fractal dimension-resolution relationship would be zero. Most geographical phenomena, however, are not self-similar at all scales, but they can be modeled by a stochastic fractal in which the scaling properties of the image exhibit patterns that can be described by statistics such as area-perimeter ratios and autocovariances. Stochastic fractal sets relax the self-similarity assumption and measure many scales and resolutions to represent the varying form of a phenomenon as the pixel size is increased in a convolution process. We have observed that for images of homogeneous land covers, the fractal dimension varies linearly with changes in resolution or pixel size over the range of past, current, and planned space-borne sensors. This relationship differs significantly in images of agricultural, urban, and forest land covers, with urban areas retaining the same level of complexity, forested areas growing smoother, and agricultural areas growing more complex as small pixels are aggregated into larger, mixed pixels. Images of scenes having a mixture of land covers have fractal dimensions that exhibit a non-linear, complex relationship to pixel size. Measuring the fractal dimension of a difference image derived from two images of the same area obtained on different dates showed that the fractal dimension increased steadily, then exhibited a sharp decrease at increasing levels of pixel aggregation. This breakpoint of the fractal dimension/resolution plot is related to the spatial domain or operational scale of the phenomenon exhibiting the predominant visible difference between the two images (in this case, mountain snow cover). The degree to which an image departs from a theoretical ideal fractal surface provides clues as to how much information is altered or lost in the processes of rescaling and rectification. The measured fractal dimension of complex, composite land covers such as urban areas also provides a useful textural index that can assist image classification of complex scenes.
Emerson, Charles W.↗
Research In Optical Processing Of Data
Report describes current research in optical processing of data at NASA's Ames Research Center. Describes advanced optical feature extractor performing Fourier-Mellin transform to generate feature vector invariant under changes of scale and position and responds to rotation with simple translation. Potential advantages include high speed and low cost.
Ennis, David↗
Higher-order neural network software for distortion invariant object recognition
The state-of-the-art in pattern recognition for such applications as automatic target recognition and industrial robotic vision relies on digital image processing. We present a higher-order neural network model and software which performs the complete feature extraction-pattern classification paradigm required for automatic pattern recognition. Using a third-order neural network, we demonstrate complete, 100 percent accurate invariance to distortions of scale, position, and in-plate rotation. In a higher-order neural network, feature extraction is built into the network, and does not have to be learned. Only the relatively simple classification step must be learned. This is key to achieving very rapid training. The training set is much smaller than with standard neural network software because the higher-order network only has to be shown one view of each object to be learned, not every possible view. The software and graphical user interface run on any Sun workstation. Results of the use of the neural software in autonomous robotic vision systems are presented. Such a system could have extensive application in robotic manufacturing.
Reid, Max B.↗
Magnetic neutral sheets in evolving fields. I - General theory. II - Formation of the solar corona
The problem of the hydrostatic equilibrium of a large-scale magnetic field embedded in a fluid with infinite electrical conductivity is considered. It is pointed out that a necessary condition for static equilibrium is the invariance of the small-scale pattern in the field along the large-scale direction. A varying topological pattern implies that no fluid pressure distribution exists for which the field is everywhere static. Magnetic neutral sheets form, and dynamical reconnection of the field takes place. It is shown here that the invariance is also a sufficient condition for the existence of a fluid pressure distribution producing static equilibrium. Even in the simplest cases, however, the requirements on the fluid pressure are extreme and, a priori, are unlikely. It is concluded that almost all twisted flux tubes packed together produce dynamical nonequilibrium and dissipation of their twisting. This is the basic effect underlying the long-standing conjecture that the shuffling of the footpoints of the bipolar magnetic fields in the sun is responsible for heating the active corona. Attention is then given to the consequences of this general dynamical dissipation in the magnetic fields that produce the active corona of the sun. The footpoints of the field are continually manipulated by the subphotospheric convection in such a way that the lines of force are continually wrapped and rotated about one another.
Parker, E. N.↗
Similarity Rules for Scaling Solar Sail Systems
Future science missions will require solar sails on the order 10,000 sq m (or larger). However, ground and flight demonstrations must be conducted at significantly smaller Sizes (400 sq m for ground demo) due to limitations of ground-based facilities and cost and availability of flight opportunities. For this reason, the ability to understand the process of scalability, as it applies to solar sail system models and test data, is crucial to the advancement of this technology. This report will address issues of scaling in solar sail systems, focusing on structural characteristics, by developing a set of similarity or similitude functions that will guide the scaling process. The primary goal of these similarity functions (process invariants) that collectively form a set of scaling rules or guidelines is to establish valid relationships between models and experiments that are performed at different orders of scale. In the near term, such an effort will help guide the size and properties of a flight validation sail that will need to be flown to accurately represent a large, mission-level sail.
Canfield, Stephen L.↗
Estimates of crater size for large-body impact Gravity-scaling results
A scaling analysis based upon dimensional invariance is used in conjunction with centrifuge experiments to estimate cratering efficiency as a function of impact velocity for kilometer-sized impactors. Complementing earlier, conventional small-scale impact experiments, centrifuge experiments were performed to substantiate these scaling laws in a scaled-size regime of interest. This technique provided empirical scaling laws used to estimate crater size for large bodies impacting the earth. From these scaling laws a 10-km-diameter body impacting at 25 km/s would be expected to produce a 66-km-diameter crater and to inject approximately 12 times its mass into the atmosphere.
Schmidt, R. M.↗
On the Asymptotic Regimes and the Strongly Stratified Limit of Rotating Boussinesq Equations
Asymptotic regimes of geophysical dynamics are described for different Burger number limits. Rotating Boussinesq equations are analyzed in the asymptotic limit, of strong stratification in the Burger number of order one situation as well as in the asymptotic regime of strong stratification and weak rotation. It is shown that in both regimes horizontally averaged buoyancy variable is an adiabatic invariant for the full Boussinesq system. Spectral phase shift corrections to the buoyancy time scale associated with vertical shearing of this invariant are deduced. Statistical dephasing effects induced by turbulent processes on inertial-gravity waves are evidenced. The 'split' of the energy transfer of the vortical and the wave components is established in the Craya-Herring cyclic basis. As the Burger number increases from zero to infinity, we demonstrate gradual unfreezing of energy cascades for ageostrophic dynamics. The energy spectrum and the anisotropic spectral eddy viscosity are deduced with an explicit dependence on the anisotropic rotation/stratification time scale which depends on the vertical aspect ratio parameter. Intermediate asymptotic regime corresponding to strong stratification and weak rotation is analyzed where the effects of weak rotation are accounted for by an asymptotic expansion with full control (saturation) of vertical shearing. The regularizing effect of weak rotation differs from regularizations based on vertical viscosity. Two scalar prognostic equations for ageostrophic components (divergent velocity potential and geostrophic departure ) are obtained.
Babin, A.↗
Natural inflation with pseudo Nambu-Goldstone bosons
It is shown that a pseudo-Nambu-Goldstone boson of given potential can naturally give rise to an epoch of inflation in the early universe. Mass scales which arise in particle physics models with a gauge group that becomes strongly interacting at a certain scales are shown to be conditions for successful inflation. The density fluctuation spectrum is nonscale-invariant, with extra power on large length scales.
Freese, Katherine↗
General consequences of the violated Feynman scaling
The problem of scaling of the hadronic production cross sections represents an outstanding question in high energy physics especially for interpretation of cosmic ray data. A comprehensive analysis of the accelerator data leads to the conclusion of the existence of breaked Feynman scaling. It was proposed that the Lorentz invariant inclusive cross sections for secondaries of a given type approaches constant in respect to a breaked scaling variable x sub s. Thus, the differential cross sections measured in accelerator energy can be extrapolated to higher cosmic ray energies. This assumption leads to some important consequences. The distribution of secondary multiplicity that follows from the violated Feynman scaling using a similar method of Koba et al is discussed.
Kamberov, G.↗
Exponential stability of large-scale discrete systems
The concept of vector Liapunov functions is used to obtain conditions for the exponential stability of large-scale discrete systems which can be decomposed into a number of interconnected subsystems with the same stability property. Both the structurally invariant composite systems and the large-scale systems under structural perturbations are considered. Connective absolute stability of a large-scale system composed of the interconnected Lur'e-type subsystems is defined and resolved in this context, resulting in a computationally and conceptually attractive alternative to a straightforward stability analysis of the system by frequency-domain criteria.
Grujic, L. T.↗
An algorithm for recognition and localization of rotated and scaled objects
An algorithm for recognition and localization of objects, which is invariant to displacement and rotation, is extended to the recognition and localization of differently scaled, rotated, and displaced objects. The proposed algorithm provides an optimum way to find if a match exists between two objects that are scaled, rotated, and displaced, while the number of computations is of the same order as for equally scaled objects.
Peli, T.↗