A system for the generation of stylized video from real-world captured 2D material will be presented. A set of passes is used to extract interesting features such as edges and large color areas. To resolve previously encountered issues with frame-to-frame coherence, an approach using optical flow is chosen. The end result is a stylized drawing of configurable style that does not exhibit the traditional "jitter" seen in systems that are not aware of image sequences.

This paper describes the development and implementation of a new pen-based approach to Chinese character input on a personal computer. As opposed to the standard method of keyboard input, an electronic tablet and pen is used to draw the Chinese character on a digital canvas. We explain how we process the collection of strokes generated by the pen and tablet, and how we use this data to predict the character represented by the strokes. Using 10-fold cross validation to analyze the character recognition engine, we achieve an accuracy rate of 74.9% on the top match, 86.4% on the top 2 matches and 90.1% on the top 3 matches.

Through computational clustering methods, genes in various organisms have traditionally been organized into groups exhibiting similar activity under similar conditions. By probing the biological basis for such gene activity and by exploiting the architecture of gene networks through the use of network search algorithms, a more biologically realistic picture of gene networks begins to emerge.

It is often useful to represent a string by a context-free grammar which produces the singleton language containing just that string. We investigate the problem of finding the smallest such grammar for a given string.

This is a problem of significant theoretical and practical interest. Recently much work has been done on using the grammar for string compression, and competent schemes have been developed. An algorithm which produces a small grammar from a string has direct application to such schemes. The size of the smallest grammar for a string is of theoretical interest as an efficiently computable complexity measure of the string, in lieu of Kolmogorov complexity. The grammar representation has also been suggested as a heuristic for uncovering hierarchical structures in the string.

We give the first efficient algorithm with a logarithmic approximation factor. Our algorithm is based on the Lempel-Ziv compression algorithm LZ77, and a novel balancing procedure for grammars. The smallest grammar is known to be hard to approximate within a certain constant factor, and an approximation factor of $o(\log(n)/\log\log n)$ would imply progress on an outstanding problem in a well-studied area. Previously, the best proven approximation ratio was $O(n^{1/2})$. Our main result is an exponential improvement of this ratio; we give an $O(\log \frac{n}{g^*})$ approximation algorithm, where $g^*$ is the size of the smallest grammar.

Other results we have show that the complexity of a string defined under certain other natural models can also be well-approximated: we give an $O(\log^2 n)$ approximation for the smallest non-deterministic finite automaton (Mealy machine) with advice producing the string; we show the equivalence of the grammar model to the ``advice-grammar'' model which is a natural and well-motivated model of defining the complexity of a string; also we show how our algorithm for approximating the smallest grammar can be used to approximate the smallest ``edit-grammar'', which is a more powerful model.

Since high-level design is critical for system performance, designers use high-level simulation models to guide their design decisions. Unfortunately, modeling times permit only a few alternatives to be explored before committing to a high-level design. However, a system that allows models to be created from easy to use and easy to build reusable components can dramatically increase the number of designs explored.

This talk will describe the Liberty Simulation Environment (LSE). LSE is a high-level hardware modeling tool designed to allow and encourage extensive component reuse among hardware models. Experience with LSE has shown great promise for the tool. A model of an out-of-order IA64 processor was single handedly constructed in a couple months. Furthermore, with only modest optimization techniques, LSE yields performance similar to models built with non-reusable components in other structural modeling systems.