Implications of cross section errors for cosmic ray propagation

Errors in nuclear interaction cross sections are the single most important limitation on the analysis of cosmic ray composition data. At the 18th International Cosmic Ray Conference, the potential importance of correlations in cross section errors in determining cosmic ray source abundances was demonstrated. In this paper the magnitude of cross section error correlation is estimated. Analysis suggests that cross section errors are essentially uncorrelated for nuclei with Z 29 and that the actual errors may be less than the nominal 35%

Gamma ray line production from cosmic ray spallation reactions

The gamma ray line intensities due to cosmic ray spallation reactions in clouds, the galactic disk and accreting binary pulsars are calculated. With the most favorable plausible assumptions, only a few lines may be detectable to the level of 0.0000001 per sq. cm per sec. The intensities are compared with those generated in nuclear excitation reactions

Calculation of improved spallation cross sections

Several research groups have recently carried out highly precise measurements (to about 10 percent) of high-energy nuclear spallation cross sections. These measurements, above 5 GeV, cover a broad range of elements: V, Fe, Cu, Ag, Ta and Au. Even the small cross sections far off the peak of the isotopic distribution curves have been measured. The semiempirical calculations are compared with the measured values. Preliminary comparisons indicate that the parameters of our spallation relations (Silberberg and Tsao, 1973) for atomic numbers 20 to 83 need modifications, e.g. a reduced slope of the mass yield distribution, broader isotopic distributions, and a shift of the isotopic distribution toward the neutron-deficient side. The required modifications are negligible near Fe and Cu, but increase with increasing target mass

Propagation of cosmic rays and new evidence for distributed acceleration

The origin and propagation of cosmic rays in terms of conventional and supplementary newer assumptions were explored. Cosmic rays are considered to be accelerated by supernoava shock waves and to traverse clouds in the source region. After rigidity-dependent escape from these clouds into interstellar space, cosmic rays are further accelerated by the weakened shocks of old supernova remnants and then pass through additional material. The distributed acceleration hypothesis is discussed with emphasis on recent data on the abundances of cosmic-ray isotopes of N above 1 GeV/u and of He near 6 GeV/u

Two generalizations of Kohonen clustering

The relationship between the sequential hard c-means (SHCM), learning vector quantization (LVQ), and fuzzy c-means (FCM) clustering algorithms is discussed. LVQ and SHCM suffer from several major problems. For example, they depend heavily on initialization. If the initial values of the cluster centers are outside the convex hull of the input data, such algorithms, even if they terminate, may not produce meaningful results in terms of prototypes for cluster representation. This is due in part to the fact that they update only the winning prototype for every input vector. The impact and interaction of these two families with Kohonen's self-organizing feature mapping (SOFM), which is not a clustering method, but which often leads ideas to clustering algorithms is discussed. Then two generalizations of LVQ that are explicitly designed as clustering algorithms are presented; these algorithms are referred to as generalized LVQ = GLVQ; and fuzzy LVQ = FLVQ. Learning rules are derived to optimize an objective function whose goal is to produce 'good clusters'. GLVQ/FLVQ (may) update every node in the clustering net for each input vector. Neither GLVQ nor FLVQ depends upon a choice for the update neighborhood or learning rate distribution - these are taken care of automatically. Segmentation of a gray tone image is used as a typical application of these algorithms to illustrate the performance of GLVQ/FLVQ

Image segmentation using fuzzy LVQ clustering networks

In this note we formulate image segmentation as a clustering problem. Feature vectors extracted from a raw image are clustered into subregions, thereby segmenting the image. A fuzzy generalization of a Kohonen learning vector quantization (LVQ) which integrates the Fuzzy c-Means (FCM) model with the learning rate and updating strategies of the LVQ is used for this task. This network, which segments images in an unsupervised manner, is thus related to the FCM optimization problem. Numerical examples on photographic and magnetic resonance images are given to illustrate this approach to image segmentation

A feasibility study of signal processing to improve antenna gain Final report

Feasibility of signal processor with phase isolator for adaptive antenna arra

Development of physical and mathematical models for the Porous Ceramic Tube Plant Nutrification System (PCTPNS)

A physical model of the Porous Ceramic Tube Plant Nutrification System (PCTPNS) was developed through microscopic observations of the tube surface under various operational conditions. In addition, a mathematical model of this system was developed which incorporated the effects of the applied suction pressure, surface tension, and gravitational forces as well as the porosity and physical dimensions of the tubes. The flow of liquid through the PCTPNS was thus characterized for non-biological situations. One of the key factors in the verification of these models is the accurate and rapid measurement of the 'wetness' or holding capacity of the ceramic tubes. This study evaluated a thermistor based moisture sensor device and recommendations for future research on alternative sensing devices are proposed. In addition, extensions of the physical and mathematical models to include the effects of plant physiology and growth are also discussed for future research

Updated Semiempirical Cross Sections for Cosmic Rays Propagation

High precision cross sections estimates are crucial to help infer the source abundance of elements and isotopes that have large secondary components in the arriving cosmic-ray abundances, e.g., N, Na, Al and P. We propose here correction factors to further refine our recent semiempirical cross sections estimates. Factors for elements that are nearly purely secondary, e.g, B and F, are also proposed for improved propagation calculations. We also point to some inconsistencies in the measured cross sections. The nucleus-nucleus component, including scaling factors, as well as a non-nuclear contribution to the inelastic cross section therein are also discussed

A Comparison of Models of Cosmic-Ray Source Composition

Several models for the origin of cosmic rays have been proposed to explain the relative differences of cosmic-ray source abundances and the general abundances of elements and isotopes. One model, for example, assumes injection at normal stars like the sun, using FIP-modified coronal rather than photospheric abundances. Another with acceleration and breakup of grains by supernova shock waves has been popular with several authors. On the basis of the known abundances of few elements, we demonstrate how a critical evaluation of one model's merits against the others can be made