The destructive capacity of wildfires and the dangers and limitations associated with observing actual wildfires has led researchers to develop mathematical models in order to better understand their behavior; unfortunately, current two-dimensional visualization techniques make discerning driving forces of a fire difficult and restrict comprehension to the trained eye. VFire is an immersive wildfire visualization application that aims to ameliorate these problems. We discuss several recent enhancements made to VFire in order to not only increase the amount of meaningfully visualized data and visual fidelity but also improve user interaction.

We present an improved adaptive echo cancellation algorithm designed for use with sparse echo path impulse responses such as arise from packet-switched networks. The new approach implicitly segments the impulse response into 'active' and 'inactive' regions, and employs different proportionate updating in each region. An efficient partial updating scheme is then formulated for the new algorithm. Evaluation results are presented to compare the new algorithm against three existing methods in terms of convergence and computational complexity. The results show that the new algorithm outperforms the best existing technique and has lower complexity.

The most important property of the codes derived in this paper is that two numbers, i and j, have coded forms, C(i) and C(j) that when added in a conventional binary adder, give a sum C(i)+C(j) that differs from C(i+j), the code for the sum, by (at most) an additive constant. This makes possible the detection and/or correction of errors committed by the arithmetic element of a computer. In addition, messages can be coded and decoded and errors can be detected and corrected by arithmetic procedures, making it possible to elininate some or all of the special-purpose equipment usually associated with error-detecting or correcting codes. This property may make these codes useful for data transmission as well as for computation.