Ultra Wide Band technology has attracted a lot of attention recently as a viable solution for high data rate, low power, short-range wireless link. The growing multi-media home networking is demanding more bandwidth and wireless throughput has become a bottleneck for high quality multi-media services. With the maximum data rate above 100 Mbps, UWB is a perfect solution for such applications. This paper describe such a system that takes advantage of the high data rate offered by UWB. We first implemented the complete MB-OFDM PHY layer using multi-FPGA hardware and discrete RF design. Out implementation is fully compliant to the WiMedia/MBOA PHY specifications and the FCC power regulations. The system achieved 110Mbps maximum data rate with a BER better than 10-6 over a range of 4 meters. Subsequently, we developed a testbed that demonstrates simultaneous transmission of multiple High Definition video streams over the MB-OFDM link. The use-case scenario is a Multimedia Client-Server application where we have one Media Server (transmitter) and several Media

We have studied the prediction of globular protein secondary structures by neural networks. Protein secondary structures are allocated to amino acid residues using Kabsch and Sander's dictionary of protein secondary structures and the neural network is taught the protein secondary structures. The input layer of the neural network allows sequences of residues including 20 amino acids, chain break, B, X and Z. We consider classifying secondary structures into groups of 3, 4 and 8. In each case, we calculate the percentage of correct predictions. We discuss the effect of overlearning on the protein secondary structure prediction. In addition, we include the application of a neural network with a modular architecture to prediction of protein secondary structures. We compare the results from neural networks with a modular architecture and with a simple three-layer structure.

This paper describes a multiple alignment method using a workstation and supercomputer. The method is based on the alignment of a set of aligned sequences with the new sequence, and uses a recursive procedure of such alignment. The alignment is executed in a reasonable computation time on diverse levels from a workstation to a supercomputer, from the viewpoint of alignment results and computational speed by parallel processing. The application of the algorithm is illustrated by several examples of multiple alignment of 12 amino acid and DNA sequences of HIV (human immunodeficiency virus) env genes. Colour graphic programs on a workstation and parallel processing on a supercomputer are discussed.