Electromagnetic Scattering and Statistic Analysis of Clutter from Oil Contaminated Sea Surface

In order to investigate the electromagnetic (EM) scattering characteristics of the three dimensional sea surface contaminated by oil, a rigorous numerical method multilevel fast multipole algorithm (MLFMA) is developed to preciously calculate the electromagnetic backscatter from the two-layered oil contaminated sea surface. Illumination window and resistive window are combined together to depress the edge current induced by artificial truncation of the sea surface. By using this combination, the numerical method can get a high efficiency at a less computation cost. The differences between backscatters from clean sea and oil contaminated sea are investigated with respect to various incident angles and sea states. Also, the distribution of the sea clutter is examined for the oil-spilled cases in this paper

Electronic state and superconductivity of YBa2Cu3-xO7-y (M=Al,Zn and Sn) systems

A series of YBa2Cu(3-x)MxO(7-y) (M=Al,Zn and Sn) single phase samples were prepared, and the measurements of the crystal structure, oxygen content, electric resistivity, thermoelectric power, Mossbauer spectrum, XPS and superconductivity were performed. The experimental results of X ray powder diffraction, Mossbauer spectrum and oxygen content show that the Zn(2+) and the Al(3+) occupy the Cu(2) site in Cu-O planes and the Cu(1) site in Cu-O chains respectively, but the Sn(4+) occupies both the Cu(1) sites. As regards the properties in superconducting state, both the Zn(2+) and the Al(3+) depress T(sub c) strongly, but the Sn(4+) does not. As for the electronic transport properties in normal state, the system doped by Al(3+) displays a rapid increase of resistivity and some electron localization-like effects, and the thermoelectric power enhances obviously; the series contained Zn(2+) almost shows no changes of electric resistivity but the sign of the thermoelectric power is reversed. Other results are given and briefly discussed

Distributed Clustering in Cognitive Radio Ad Hoc Networks Using Soft-Constraint Affinity Propagation

Absence of network infrastructure and heterogeneous spectrum availability in cognitive radio ad hoc networks (CRAHNs) necessitate the self-organization of cognitive radio users (CRs) for efficient spectrum coordination. The cluster-based structure is known to be effective in both guaranteeing system performance and reducing communication overhead in variable network environment. In this paper, we propose a distributed clustering algorithm based on soft-constraint affinity propagation message passing model (DCSCAP). Without dependence on predefined common control channel (CCC), DCSCAP relies on the distributed message passing among CRs through their available channels, making the algorithm applicable for large scale networks. Different from original soft-constraint affinity propagation algorithm, the maximal iterations of message passing is controlled to a relatively small number to accommodate to the dynamic environment of CRAHNs. Based on the accumulated evidence for clustering from the message passing process, clusters are formed with the objective of grouping the CRs with similar spectrum availability into smaller number of clusters while guaranteeing at least one CCC in each cluster. Extensive simulation results demonstrate the preference of DCSCAP compared with existing algorithms in both efficiency and robustness of the clusters