SDM applications to machine tools and engines

Machine Learning Algorithms for GeoSpatial Data. Applications and Software Tools

Nowadays machine learning (ML), including Artificial Neural Networks (ANN) of different architectures and Support Vector Machines (SVM), provides extremely important tools for intelligent geoand environmental data analysis, processing and visualisation. Machine learning is an important complement to the traditional techniques like geostatistics. This paper presents a review of several contempor...

Applications of Matrix Computations to Search Engines

The central part of the algorithm deals with computing a dominant eigenvector (called the PageRank vector) of a huge stochastic irreducible matrix (the number of columns is in the order of billions). For practical and theoretical reasons the original matrix is modified or perturbed by introducing a so-called personalization vector, which allows to manipulate not only the ranks of particular Web...

Machine Descriptions to Build Tools for Embedded Systems Machine Descriptions for Machine-level Tools

Because of poor tools, developing embedded systems can be unnecessarily hard. Machine descriptions based on register-transfer lists (RTLs) have proven useful in building retargetable compilers, but not in building other retargetable tools. Simulators, assemblers, linkers, debug-gers, and proolers are built by hand if at all|previous machine descriptions have lacked the detail and precision need...

Finite Element Analysis of Desktop Machine Tools for Micromachining Applications

Using Machine Learning to Explore Huge Parameter Spaces for High End Computing Applications: Tools and Examples

With constantly increasing software and architectural complexities and machine scales, creating accurate performance models for applications with large parameter spaces becomes extremely challenging. Approaches using analytic models are difficult and time consuming to construct, limited in scope, and can fail to capture full system and application complexity. To retain these details and at the ...