22,229 research outputs found
A graph rewriting programming language for graph drawing
This paper describes Grrr, a prototype visual graph drawing tool. Previously there were no visual languages for programming graph drawing algorithms despite the inherently visual nature of the process. The languages which gave a diagrammatic view of graphs were not computationally complete and so could not be used to implement complex graph drawing algorithms. Hence current graph drawing tools are all text based. Recent developments in graph rewriting systems have produced computationally complete languages which give a visual view of graphs both whilst programming and during execution. Grrr, based on the Spider system, is a general purpose graph rewriting programming language which has now been extended in order to demonstrate the feasibility of visual graph drawing
Transforming planar graph drawings while maintaining height
There are numerous styles of planar graph drawings, notably straight-line
drawings, poly-line drawings, orthogonal graph drawings and visibility
representations. In this note, we show that many of these drawings can be
transformed from one style to another without changing the height of the
drawing. We then give some applications of these transformations
An approach to CMG steering using feedback linearization
This paper presents an approach for controlling spacecraft equipped with control moment gyroscopes. A technique from feedback linearization theory is used to transform the original nonlinear problem to an equivalent linear form without approximating assumptions. In this form, the spacecraft dynamics appear linearly, and are decoupled from redundancy in the system of gyroscopes. A general approach to distributing control effort among the available actuators is described which includes provisions for redistribution of rotors, explicit bounds in gimbal rates, and guaranteed operation at or near singular configurations. A particular algorithm is developed for systems of double-gimbal devices, and demonstrated in two examples for which existing approaches fail to give adequate performance
Why (and How) Networks Should Run Themselves
The proliferation of networked devices, systems, and applications that we
depend on every day makes managing networks more important than ever. The
increasing security, availability, and performance demands of these
applications suggest that these increasingly difficult network management
problems be solved in real time, across a complex web of interacting protocols
and systems. Alas, just as the importance of network management has increased,
the network has grown so complex that it is seemingly unmanageable. In this new
era, network management requires a fundamentally new approach. Instead of
optimizations based on closed-form analysis of individual protocols, network
operators need data-driven, machine-learning-based models of end-to-end and
application performance based on high-level policy goals and a holistic view of
the underlying components. Instead of anomaly detection algorithms that operate
on offline analysis of network traces, operators need classification and
detection algorithms that can make real-time, closed-loop decisions. Networks
should learn to drive themselves. This paper explores this concept, discussing
how we might attain this ambitious goal by more closely coupling measurement
with real-time control and by relying on learning for inference and prediction
about a networked application or system, as opposed to closed-form analysis of
individual protocols
Theory and Techniques for Synthesizing a Family of Graph Algorithms
Although Breadth-First Search (BFS) has several advantages over Depth-First
Search (DFS) its prohibitive space requirements have meant that algorithm
designers often pass it over in favor of DFS. To address this shortcoming, we
introduce a theory of Efficient BFS (EBFS) along with a simple recursive
program schema for carrying out the search. The theory is based on dominance
relations, a long standing technique from the field of search algorithms. We
show how the theory can be used to systematically derive solutions to two graph
algorithms, namely the Single Source Shortest Path problem and the Minimum
Spanning Tree problem. The solutions are found by making small systematic
changes to the derivation, revealing the connections between the two problems
which are often obscured in textbook presentations of them.Comment: In Proceedings SYNT 2012, arXiv:1207.055
A Generative Model of Natural Texture Surrogates
Natural images can be viewed as patchworks of different textures, where the
local image statistics is roughly stationary within a small neighborhood but
otherwise varies from region to region. In order to model this variability, we
first applied the parametric texture algorithm of Portilla and Simoncelli to
image patches of 64X64 pixels in a large database of natural images such that
each image patch is then described by 655 texture parameters which specify
certain statistics, such as variances and covariances of wavelet coefficients
or coefficient magnitudes within that patch.
To model the statistics of these texture parameters, we then developed
suitable nonlinear transformations of the parameters that allowed us to fit
their joint statistics with a multivariate Gaussian distribution. We find that
the first 200 principal components contain more than 99% of the variance and
are sufficient to generate textures that are perceptually extremely close to
those generated with all 655 components. We demonstrate the usefulness of the
model in several ways: (1) We sample ensembles of texture patches that can be
directly compared to samples of patches from the natural image database and can
to a high degree reproduce their perceptual appearance. (2) We further
developed an image compression algorithm which generates surprisingly accurate
images at bit rates as low as 0.14 bits/pixel. Finally, (3) We demonstrate how
our approach can be used for an efficient and objective evaluation of samples
generated with probabilistic models of natural images.Comment: 34 pages, 9 figure
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