Korean coastal water depth/sediment and land cover mapping (1:25,000) by computer analysis of LANDSAT imagery

Computer analysis was applied to single date LANDSAT MSS imagery of a sample coastal area near Seoul, Korea equivalent to a 1:50,000 topographic map. Supervised image processing yielded a test classification map from this sample image containing 12 classes: 5 water depth/sediment classes, 2 shoreline/tidal classes, and 5 coastal land cover classes at a scale of 1:25,000 and with a training set accuracy of 76%. Unsupervised image classification was applied to a subportion of the site analyzed and produced classification maps comparable in results in a spatial sense. The results of this test indicated that it is feasible to produce such quantitative maps for detailed study of dynamic coastal processes given a LANDSAT image data base at sufficiently frequent time intervals

A hill-sliding strategy for initialization of Gaussian clusters in the multidimensional space

A hill sliding technique was devised to extract Gaussian clusters from the multivariate probability density estimate of sample data for the first step of iterative unsupervised classification. Each cluster was assumed to posses a unimodal normal distribution. A clustering function proposed distinguished elements of a cluster under formation from the rest in the feature space. Initial clusters were extracted one by one according to the hill sliding tactics. A dimensionless cluster compactness parameter was proposed as a universal measure of cluster goodness and used satisfactorily in test runs with LANDSAT multispectral scanner data. The normalized divergence, defined by the cluster divergence divided by the entropy of the entire sample data, was utilized as a general separability measure between clusters. An overall clustering objective function was set forth in terms of cluster covariance matrices, from which the cluster compactness measure could be deduced. Minimal improvement of initial data partitioning was evaluated by this objective function in eliminating scattered sparse data points. The hill sliding clustering technique developed herein has the potential applicability to decomposition any multivariate mixture distribution into a number of unimodal distributions when an appropriate distribution function to the data set is employed

Suppressed Andreev Reflection at the Normal-Metal / Heavy-Fermion Superconductor CeCoIn5_5 Interface

Dynamic conductance spectra are taken from Au/CeCoIn$_5$ point contacts in the Sharvin limit along the (001) and (110) directions. Our conductance spectra, reproducibly obtained over wide ranges of temperature, constitute the cleanest data sets ever reported for HFSs. A signature for the emerging heavy-fermion liquid is evidenced by the development of the asymmetry in the background in the normal state. Below $T_c$, an enhancement of the sub-gap conductance arising from Andreev reflection is observed, with the magnitude of $\sim$ 13.3 % and $\sim$ 11.8 % for the (001) and the (110) point contacts, respectively, an order of magnitude smaller than those observed in conventional superconductors but consistent with those in other HFSs. Our zero-bias conductance data for the (001) point contacts are best fit with the extended BTK model using the d-wave order parameter. The fit to the full conductance curve of the (001) point contact indicates the strong coupling nature ($2\Delta/k_{B}T_c = 4.64$). However, our observed suppression of both the Andreev reflection signal and the energy gap indicates the failure of existing models. We provide possible directions for theoretical formulations of the electronic transport across an N/HFS interface. Several qualitative features observed in the (110) point contacts provide the first clear spectroscopic evidence for the $d_{x^2-y^2}$ symmetry.Comment: 13 pages, 7 figures, LaTeX, paper invited and submitted to SPIE Conference on Strongly Correlated Electron Materials: Physics and Nanoengineering, in San Diego, California, July 31 - August 4, 200