Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “random networks”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Learning random networks for compression of still and moving images

Image compression for both still and moving images is an extremely important area of investigation, with numerous applications to videoconferencing, interactive education, home entertainment, and potential applications to earth observations, medical imaging, digital libraries, and many other areas. We describe work on a neural network methodology to compress/decompress still and moving images. We use the 'point-process' type neural network model which is closer to biophysical reality than standard models, and yet is mathematically much more tractable. We currently achieve compression ratios of the order of 120:1 for moving grey-level images, based on a combination of motion detection and compression. The observed signal-to-noise ratio varies from values above 25 to more than 35. The method is computationally fast so that compression and decompression can be carried out in real-time. It uses the adaptive capabilities of a set of neural networks so as to select varying compression ratios in real-time as a function of quality achieved. It also uses a motion detector which will avoid retransmitting portions of the image which have varied little from the previous frame. Further improvements can be achieved by using on-line learning during compression, and by appropriate compensation of nonlinearities in the compression/decompression scheme. We expect to go well beyond the 250:1 compression level for color images with good quality levels.

Gelenbe, Erol↗
NASA NTRS1997

Routing in Networks with Random Topologies

We examine the problems of routing and server assignment in networks with random connectivities. In such a network the basic topology is fixed, but during each time slot and for each of tis input queues, each server (node) is either connected to or disconnected from each of its queues with some probability.

Random Topologies routing↗
NASA NTRS1987

Hybrid analog-digital associative neural network

Random access memory is used to store synaptic information in the form of a matrix of rows and columns of binary digits. N rows read in sequence are processed through switches and resistors, and a summing amplifier to N neural amplifiers in sequence, one row for each amplifier, using a first array of sample-and-hold devices S/H1 for commutation. The outputs of the neural amplifiers are stored in a second array of sample-and-hold devices S/H2 so that after N rows are processed, all of the second array of sample-and-hold devices are updated. A second memory may be added for binary values of 0 and -1, and processed simultaneously with the first to provide for values of 1, 0, and -1, the results of which are combined in a difference amplifier.

Moopenn, Alexander W.↗
NASA NTRS1989

Hybrid analog-digital associative neural network

Random access memory is used to store synaptic information in the form of a matrix of rows and columns of binary digits. N rows read in sequence are processed through switches and resistors, and a summing amplifier to N neural amplifiers in sequence, one row for each amplifier, using a first array of sample-and-hold devices S/H1 for commutation. The outputs of the neural amplifiers are stored in a second array of sample-and-hold devices S/H2 so that after N rows are processed, all of said second array of sample-and-hold devices are updated. A second memory may be added for binary values of 0 and -1, and processed simultaneously with the first to provide for values of 1, 0, and -1, the results of which are combined in a difference amplifier.

Moopenn, Alexander W.↗
NASA NTRS1990

Topology-selective jamming of fully-connected, code-division random-access networks

The purpose is to introduce certain models of topology selective stochastic jamming and examine its impact on a class of fully-connected, spread-spectrum, slotted ALOHA-type random access networks. The theory covers dedicated as well as half-duplex units. The dominant role of the spatial duty factor is established, and connections with the dual concept of time selective jamming are discussed. The optimal choices of coding rate and link access parameters (from the users' side) and the jamming spatial fraction are numerically established for DS and FH spreading.

Polydoros, Andreas↗
NASA NTRS2003

Scale-free Graphs for General Aviation Flight Schedules

In the late 1990s a number of researchers noticed that networks in biology, sociology, and telecommunications exhibited similar characteristics unlike standard random networks. In particular, they found that the cummulative degree distributions of these graphs followed a power law rather than a binomial distribution and that their clustering coefficients tended to a nonzero constant as the number of nodes, n, became large rather than O(1/n). Moreover, these networks shared an important property with traditional random graphs as n becomes large the average shortest path length scales with log n. This latter property has been coined the small-world property. When taken together these three properties small-world, power law, and constant clustering coefficient describe what are now most commonly referred to as scale-free networks. Since 1997 at least six books and over 400 articles have been written about scale-free networks. In this manuscript an overview of the salient characteristics of scale-free networks. Computational experience will be provided for two mechanisms that grow (dynamic) scale-free graphs. Additional computational experience will be given for constructing (static) scale-free graphs via a tabu search optimization approach. Finally, a discussion of potential applications to general aviation networks is given.

Alexandov, Natalia M.↗
NASA NTRS1993

A diffusion-limited aggregation model for the evolution of drainage networks

We propose a modified diffusion-limited aggregation (DLA) model for the evolution of fluvial drainage networks. Random walkers are introduced randomly on a grid, and each two-dimensional random walk proceeds until the walker finds a drainage network on which to accrete. This model for headward growth of drainage networks generates drainage patterns remarkably similar to actual drainages. The model also predicts statistical features which agree with actual networks, including the frequency-order (bifurcation) ratio (R(sub b) = 3.98) and the stream length-order (R(sub r) = 2.09). Using the definition of network fractal dimension D = log R(sub b)/log R(sub r), we find that our DLA model gives D = 1.87, near the observed range of D approximately equal to 1.80 - 1.85.

Masek, Jeffrey G.↗
NASA NTRS2022

A Comprehensive Machine Learning Study to Classify Precipitation Type over Land from Global Precipitation Measurement Microwave Imager (GPM-GMI) Measurements

Precipitation type is a key parameter used for better retrieval of precipitation characteristics as well as to understand the cloud–convection–precipitation coupling processes. Ice crystals and water droplets inherently exhibit different characteristics in different precipitation regimes (e.g., convection, stratiform), which reflect on satellite remote sensing measurements that help us distinguish them. The Global Precipitation Measurement (GPM) Core Observatory’s microwave imager (GMI) and dual-frequency precipitation radar (DPR) together provide ample information on global precipitation characteristics. As an active sensor, the DPR provides an accurate precipitation type assignment, while passive sensors such as the GMI are traditionally only used for empirical understanding of precipitation regimes. Using collocated precipitation type flags from the DPR as the “truth”, this paper employs machine learning (ML) models to train and test the predictability and accuracy of using passive GMI-only observations together with ancillary information from a reanalysis and GMI surface emissivity retrieval products. Out of six ML models, four simple ones (support vector machine, neural network, random forest, and gradient boosting) and the 1-D convolutional neural network (CNN) model are identified to produce 90–94% prediction accuracy globally for five types of precipitation (convective, stratiform, mixture, no precipitation, and other precipitation), which is much more robust than previous similar effort. One novelty of this work is to introduce data augmentation (subsampling and bootstrapping) to handle extremely unbalanced samples in each category. A careful evaluation of the impact matrices demonstrates that the polarization difference (PD), brightness temperature (Tc) and surface emissivity at high-frequency channels dominate the decision process, which is consistent with the physical understanding of polarized microwave radiative transfer over different surface types, as well as in snow and liquid clouds with different microphysical properties. Furthermore, the view-angle dependency artifact that the DPR’s precipitation flag bears with does not propagate into the conical-viewing GMI retrievals. This work provides a new and promising way for future physics-based ML retrieval algorithm development.

machine learning/artificial intelligence↗
NASA NTRS1986

Analytic method for calculating properties of random walks on networks

A method for calculating the properties of discrete random walks on networks is presented. The method divides complex networks into simpler units whose contribution to the mean first-passage time is calculated. The simplified network is then further iterated. The method is demonstrated by calculating mean first-passage times on a segment, a segment with a single dangling bond, a segment with many dangling bonds, and a looplike structure. The results are analyzed and related to the applicability of the Einstein relation between conductance and diffusion.

Goldhirsch, I.↗
NASA NTRS1993

Fabrication of Si-As-Te ternary amorphous semiconductor in the microgravity environment (M-13)

Ternary chalcogenide Si-As-Te system is an interesting semiconductor from the aspect of both basic physics and technological applications. Since a Si-As-Te system consists of a IV-III-II hedral bonding network, it has a very large glass forming region with a wide physical constant controllability. For example, its energy gap can be controlled in a range from 0.6 eV to 2.5 eV, which corresponds to the classical semiconductor Ge (0.66 eV), Si (1.10 eV), GaAs (1.43 eV), and GaP (2.25 eV). This fact indicates that it would be a suitable system to investigate the compositional dependence of the atomic and electronic properties in the random network of solids. In spite of these significant advantages in the Si-As-Te amorphous system, a big barrier impending the wide utilization of this material is the huge difficulty encountered in the material preparation which results from large differences in the weight density, melting point, and vapor pressure of individual elements used for the alloying composition. The objective of the FMPT/M13 experiment is to fabricate homogeneous multi-component amorphous semiconductors in the microgravity environment of space, and to make a series of comparative characterizations of the amorphous structures and their basic physical constants on the materials prepared both in space and in normal terrestrial gravity.

Hamakawa, Yoshihiro↗
NASA NTRS1982

Ion beam deposition of amorphous carbon films with diamond like properties

Carbon films were deposited on silicon, quartz, and potassium bromide substrates from an ion beam. Growth rates were approximately 0.3 micron/hour. The films were featureless and amorphous and contained only carbon and hydrogen in significant amounts. The density and carbon/hydrogen ratio indicate the film is a hydrogen deficient polymer. One possible structure, consistent with the data, is a random network of methylene linkages and tetrahedrally coordinated carbon atoms.

Angus, John C.↗
NASA NTRS1991

Remote sensing of earth terrain

Abstracts from 46 refereed journal and conference papers are presented for research on remote sensing of earth terrain. The topics covered related to remote sensing include the following: mathematical models, vegetation cover, sea ice, finite difference theory, electromagnetic waves, polarimetry, neural networks, random media, synthetic aperture radar, electromagnetic bias, and others.

Kong, Jin AU↗
NASA NTRS1990

Distributed memory approaches for robotic neural controllers

The suitability is explored of two varieties of distributed memory neutral networks as trainable controllers for a simulated robotics task. The task requires that two cameras observe an arbitrary target point in space. Coordinates of the target on the camera image planes are passed to a neural controller which must learn to solve the inverse kinematics of a manipulator with one revolute and two prismatic joints. Two new network designs are evaluated. The first, radial basis sparse distributed memory (RBSDM), approximates functional mappings as sums of multivariate gaussians centered around previously learned patterns. The second network types involved variations of Adaptive Vector Quantizers or Self Organizing Maps. In these networks, random N dimensional points are given local connectivities. They are then exposed to training patterns and readjust their locations based on a nearest neighbor rule. Both approaches are tested based on their ability to interpolate manipulator joint coordinates for simulated arm movement while simultaneously performing stereo fusion of the camera data. Comparisons are made with classical k-nearest neighbor pattern recognition techniques.

Jorgensen, Charles C.↗
NASA NTRS2001

Multifunctional Carbon Foams for Aerospace Applications

Carbon foams produced by the controlled thermal decomposition of inexpensive coal extracts exhibit a combination of structural and thermal properties that make them attractive for aerospace applications. Their thermal conductivity can be tailored between 0.5 and 100 W/mK through precursor selection/modification and heat treatment conditions; thus, they can serve in either thermal protection or heat transfer systems such as heat exchangers. Because their structure is essentially a 3D random network of graphite-like members, they also can be considered low-cost, easily fabricated replacements for multi-directional structural carbon fiber preforms. Strengths of over 4000 psi in compression are common. Their density can be designed between 0.1 and 0.8 g/cc, and they can be impregnated with a variety of matrices or used, unfilled, in sandwich structures. These foams also exhibit intriguing electrochemical properties that offer potential in high-efficiency fuel cell and battery applications, mandrels and tooling for composite manufacture, ablative performance, and fire resistance. This paper presents the results of research conducted under NASA SBIR Topic 99.04.01, General Aviation Technology, supported from Langley Research Center. The potential of foam design through precursor selection, cell size and density control, density grading, and heat treatment is demonstrated.

Rogers, D. K.↗
NASA NTRS1993

The velocity dispersion of the caustic network due to random motion of individual stars in the lensing galaxy

We present a method of computing the velocity distribution of the caustic network due to the random motion of stars in the lensing galaxy. This method is illustrated on the example of the two-point mass lens and then applied to a large sample of stars. We conclude that the proper motion of the stars increases significantly the frequency of the high magnification events in comparison with a static lens configuration with constant stream or constant bulk velocity. The stream velocity is the velocity of the star field relative to the global bulk velocity of the galaxy. We show that the global bulk and the stream velocity of the star field have to be considered separately for any microlensing situation. The higher the surface mass density of the stars in the lensing galaxy, the higher the influence of proper motion of stars on the statistics of high magnification events. The influence of a Gaussian velocity distribution of the stars in the lensing galaxy compared with a constant stream velocity of the stars increases the number of high magnification events by a factor 1.30 +/- 0.06 for a normalized surface density of the stars cr = 0.1 and by a factor 1.7 +/- 0.1 for sigma = 0.5. This means that for some microlensing situations the proper motion of the stars in a lensing galaxy has to be considered for exact microlensing predictions.

Kundik, Tomislav↗
NASA NTRS1990

Random access to mobile networks with advanced error correction

A random access scheme for unreliable data channels is investigated in conjunction with an adaptive Hybrid-II Automatic Repeat Request (ARQ) scheme using Rate Compatible Punctured Codes (RCPC) Forward Error Correction (FEC). A simple scheme with fixed frame length and equal slot sizes is chosen and reservation is implicit by the first packet transmitted randomly in a free slot, similar to Reservation Aloha. This allows the further transmission of redundancy if the last decoding attempt failed. Results show that a high channel utilization and superior throughput can be achieved with this scheme that shows a quite low implementation complexity. For the example of an interleaved Rayleigh channel and soft decision utilization and mean delay are calculated. A utilization of 40 percent may be achieved for a frame with the number of slots being equal to half the station number under high traffic load. The effects of feedback channel errors and some countermeasures are discussed.

Dippold, Michael↗
NASA NTRS1983

Performance of a random access packet network with time-capture capability

The Joint Tactical Information Distribution System (JTIDS) is applied to a digital network supporting the command, control and communication requirements of 105 highly mobile users. User data traffic is bursty and the slotted ALOHA channel access scheme is therefore employed. This paper focuses on the determination of JTIDS system performance in this particular application. Emphasis is directed at the specific time-capture capability of JTIDS. Significant system performance parameters are quantified with analysis and simulation.

Lin, Y. H.↗