Hardware trends have motivated the development of mixed precision algorithms in numerical linear algebra, which aim to decrease runtime while maintaining acceptable accuracy. One recent development is the development of an adaptive precision sparse matrix-vector produce routine, which may be used to accelerate the solution of sparse linear systems by iterative methods. This approach is also applicable to the application of inexact preconditioners, such as sparse approximate inverse preconditioners used in Krylov subspace methods. In this work, we develop an adaptive precision sparse approximate inverse preconditioner and demonstrate its use within a five-precision GMRES-based iterative refinement method. We call this algorithm variant BSPAI-GMRES-IR. We then analyze the conditions for the convergence of BSPAI-GMRES-IR, and determine settings under which BSPAI-GMRES-IR will produce similar backward and forward errors as the existing SPAI-GMRES-IR method, the latter of which does not use adaptive precision in preconditioning. Our numerical experiments show that this approach can potentially lead to a reduction in the cost of storing and applying sparse approximate inverse preconditioners, although a significant reduction in cost may comes at the expense of increasing the number of GMRES iterations required for convergence.

Reaction-diffusion systems (RDS) help us to understand the distribution of the concentration of substances in space or time under the influence of two phenomena: local chemical reactions where the substances are transmuted into one another, and diffusion which causes the substances to spread out over a surface in space. Analytical solutions for these behavioral models are still lacking, therefore it is essential to use some numerical methods to find approximate solution to these systems as the numerical results will allow us the use of parameters fitting. This study focuses on the numerical approximation based on finite-element scheme together with the powerful DUNE-PDELab package to investigate the spatio-temporal dynamics of the structure of predator-prey diffusive model. The scheme is introduced for approximation of predator-prey with Holling type-II functional response, while the growth is logistic, subject to some appropriate initial and boundary conditions. The simulations were obtained in the two-dimensional case, which demonstrate that the initial and boundary conditions play an important role in identifying the spatio-temporal dynamics of predator-prey interactions.

Due to rapid and constant evolution of wireless communication technologies, standards, protocols, applications, and systems, it is hard to rely on personal experience to make their selection, design and deployment. Testing helps to determine actual performance and limitations of technologies. Testing is also important to avoid the financial and reputation losses of the company as well as to ensure uninterrupted flow of the information for essential services such as healthcare, airports, railways, and military services. Testing covers many aspects of a communications network, including interoperability, conformance, performance and availability. The end-to-end quality of service management implies that features such as service scalability between different networks have to be available. However, wireless QoS requirements are very diverse due to its seamless applications, and moreover, differences in QoS properties between both wired and wireless applications have a considerable effect on the level of user service quality as well as platform and application dimensions of network interoperability. The aim of this paper is to establish the network performance and availability requirements for the integrated use of satellite communication technology together with terrestrial network technology in a particular, niche application area, namely the seamless delivery of educational services in rural and remote areas. The suggested testing programme aims to identify the performance and availability issues for the operation of heterogeneous satellite-terrestrial network technologies.

Synthetic aperture radar (SAR) imaging allows the remote sensing community to globally study land and sea based physical phenomena with ever finer accuracy and reliability. Time domain SAR processors for optimum resolution and frequency domain SAR processors based on the FFT for fast image throughput with reduced resolution have been developed by various establishments. Over the last few years the wavelet transform has been applied to a wide range of signal and image processing applications with significant success. It has proved particularly successful in nonstationary applications such as radar and sonar detection and in image compression codec design where improved quality is obtained using the subband compression. The key processing features of SAR are: (a) SAR image processing is a time-varying problem; (b) speckle noise makes interpretation of the processed image difficult and, (c) browsing and archiving requirements for SAR are complicated due to the excessive amount of data involved. This paper is concerned with the use of the wavelet transform as an alternative to the FFT for several aspects of synthetic aperture radar image production and analysis. A new Improved Resolution MultiScale SAR Processor (IRMS) and its relative performance to the conventional multilook FFT SAR processor is given. A new wavelet transform based SAR digital image product distribution strategy is presented