A sorter-based architecture for a parallel implementation of communication intensive algorithms

This paper deals with the parallel execution of algorithms with global and/or irregular data dependencies on a regularly and locally connected processor array. The associated communication problems are solved by the use of a two-dimensional sorting algorithm. The proposed architecture, which is based on a two-dimensional sorting network, offers a high degree of flexibility and allows an efficient mapping of many irregularly structured algorithms. In this architecture a one-dimensional processor array performs all required control and arithmetic operations, whereas the sorter solves complex data transfer problems. The storage capability of the sorting network is also used as memory for data elements. The algorithms for sparse matrix computations, fast Fourier transformation and for the convex hull problem, which are mapped onto this architecture, as well as the simulation of a shared-memory computer show that the utilization of the most complex components, the processors, is O(1).     

Quality assessment of SRTM C- and X-band interferometric data: Implications for the retrieval of vegetation canopy height

The Shuttle Radar Topography Mission distinguished itself as the first near-global spaceborne mission to demonstrate direct sensitivity to vertical vegetation structure. Whether this sensitivity is viewed as exploitable signal or unwanted bias, a great deal of interest exists in retrieving vegetation canopy height information from the SRTM data. This study presents a comprehensive application-specific assessment of SRTM data quality, focusing on the characterization and mitigation of two primary sources of relative vertical error: uncompensated Shuttle mast motion and random phase noise. The assessment spans four test sites located in the upper Midwestern United States and examines the dependence of data quality on both frequency, i.e., C-band vs. X-band, and the number of acquired datatakes. The results indicate that the quality of SRTM data may be higher than previously thought. Novel mitigation strategies include a knowledge-based approach to sample averaging, which has the potential to reduce phase noise error by 43 to 80%. The strategies presented here are being implemented as part of an ongoing effort to produce regional- to continental-scale estimates of vegetation canopy height within the conterminous U.S.     

Numerische Berechnung von Holzkonstruktionen unter Verwendung eines orthotropen elasto-plastischen Werkstoffmodells

To be able to perform more realistic simulations of timber constructions with modern numerical simulation methods like the finite element method (FEM), a suitable constitutive material model is required. Such a material model was developed by Mackenzie-Helnwein et al. (2005) for clear spruce wood. This paper presents an application-oriented adaption and usage of the mentioned material model, its implementation in a FE software as well as performing ultimate load analyses using FEM and the validation of the material model by means of the comparison of results of FE Simulations and experiments on the structure level (Fleischmann 2005). Further, some aspects with respect to the standardisation are discussed in one of the two examples.     

An empirical InSAR-optical fusion approach to mapping vegetation canopy height

Exploiting synergies afforded by a host of recently available national-scale data sets derived from interferometric synthetic aperture radar (InSAR) and passive optical remote sensing, this paper describes the development of a novel empirical approach for the provision of regional- to continental-scale estimates of vegetation canopy height. Supported by data from the 2000 Shuttle Radar Topography Mission (SRTM), the National Elevation Dataset (NED), the LANDFIRE project, and the National Land Cover Database (NLCD) 2001, this paper describes a data fusion and modeling strategy for developing the first-ever high-resolution map of canopy height for the conterminous U.S. The approach was tested as part of a prototype study spanning some 62,000 km² in central Utah (NLCD mapping zone 16). A mapping strategy based on object-oriented image analysis and tree-based regression techniques is employed. Empirical model development is driven by a database of height metrics obtained from an extensive field plot network administered by the USDA Forest Service-Forest Inventory and Analysis (FIA) program. Based on data from 508 FIA field plots, an average absolute height error of 2.1 m (r = 0.88) was achieved for the prototype mapping zone.     

Estimation in Random Coefficient Autoregressive Models

Abstract. We propose the quasi‐maximum likelihood method to estimate the parameters of an RCA(1) process, i.e. a random coefficient autoregressive time series of order 1. The strong consistency and the asymptotic normality of the estimators are derived under optimal conditions.     

Photocurrents and degradation rates on particulate TiO2 layers: Effect of layer thickness, concentration of oxidizable substance and illumination direction

Different routes for immobilization of TiO₂ on conducting substrates were compared to find active and stable photocatalysts, which could either be operated in open circuit (photocatalysis) or with applied electric potential (photoelectrocatalysis). The advantage of applying an electric potential was investigated. Polarization curves and photoelectrochemical degradation reactions served to characterize catalysts and to find a way of predicting the optimum synthesis conditions. The difference between front side (EE) and back side (SE) illumination is discussed as a function of layer thickness, as well as the influence of oxidizable substance concentration on photocurrents. Stability of catalysts was investigated in repetitive degradation experiments.