Significant enhancement of electrosorption of hydrogen into palladium via a facile annealing process

The behaviors of the electrosorption of hydrogen into untreated and annealed Pd thin foil were systematically investigated with a primary effort concentrated on the elucidating the effect of annealing on the hydrogen uptake capacity. The change of the crystalline structure of Pd during the annealing process was monitored by in situ X-ray diffraction. The scanning electron microscopic images revealed the significant effect of the annealing temperature on the morphology of the Pd thin foil. Cyclic voltammetric and chronoamperometric techniques were employed to study the kinetics of hydrogen electrosorption, where α phase, β phase and their transition were determined with respect to the electrode potential. The morphological and structural changes, as well as lattice parameters, played an important role in the hydrogen uptake. The Pd thin foil annealed at 700 °C exhibited an over 19-fold increase in hydrogen uptake capacity in comparison to the untreated one.     

A sparsity-based Bayesian approach for hyperspectral unmixing using normal compositional model

A new Bayesian-based method is developed for unmixing of hyperspectral images. Endmembers are assumed variable based on the Gaussian distribution. A semi-supervised scenario is considered, and as a practical aspect, the abundance vectors are assumed sparse. We propose the Dirichlet prior to represent the sparsity and derive the corresponding posteriors in Bayesian sense. Numerical results are used to evaluate different methods for both simulated and real data. It is shown that the proposed method achieves a lower error in abundance estimation and image reconstruction.     

ML-SLSTSVM: a new structural least square twin support vector machine for multi-label learning

Pattern Analysis and Applications - Multi-label learning (MLL) is a special supervised learning task, where any single instance possibly belongs to several classes simultaneously. Nowadays, MLL...     

Regionalizing Flood Magnitudes using Landscape Structural Patterns of Catchments

Emerging as an important issue in the disciplines of landscape ecology and landscape hydrology which inspired it, defining the concept of landscape metrics in a hydrological context has become a challenge to both landscape planners and engineers. Accordingly, the present study addresses the relationships existing between flooding phenomena and landscape metrics (shape index, fractal dimension index, perimeter-area ratio, related circumscribing circle, and contiguity index) of land use/land cover, hydrological soil groups and geological permeability classes. A regionalization approach was adopted employing 39 select catchments (33—4800 km² in area, 0.47—21 m³ s^?1 in mean discharge), located within the southern basin of the Caspian Sea. These catchments were predominantly covered by forest (57.4%), while rangeland, farmland and urban areas accounted for 25.9%, 11.7%, and 1.6%, respectively. Class-level landscape structural metrics of land use/land cover, hydrological soil groups and geological permeability classes have then been served as inputs to stepwise multiple linear regression analysis in an attempt to explain the flood magnitudes. The regression models (0.69?≤?r² ≤?0.84) suggested that the catchments’ flood magnitude could explicitly be predicted using average measure of the shape and related circumscribing circle indices for the land use/land cover classes and those of hydrologic soil groups and geological permeability classes of the catchments. This indicated that regularity (vs. irregularity) of the landscape, pedoscape, and lithoscape, as represented by the shape index as well as the circumscribing circle index (for elongation and convolution), explained 69–84% of the variation in the flood magnitudes in the catchment.     

Landscaper: A Modeling System for 3D Printing Scale Models of Landscapes

Landscape models of geospatial regions provide an intuitive mechanism for exploring complex geospatial information. However, the methods currently used to create these scale models require a large amount of resources, which restricts the availability of these models to a limited number of popular public places, such as museums and airports. In this paper, we have proposed a system for creating these physical models using an affordable 3D printer in order to make the creation of these models more widely accessible. Our system retrieves GIS relevant to creating a physical model of a geospatial region and then addresses the two major limitations of affordable 3D printers, namely the limited number of materials and available printing volume. This is accomplished by separating features into distinct extruded layers and splitting large models into smaller pieces, allowing us to employ different methods for the visualization of different geospatial features, like vegetation and residential areas, in a 3D printing context. We confirm the functionality of our system by printing two large physical models of relatively complex landscape regions.