International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada / Compiling a PCM data frame with super commutation poses problems of maintaining constant sample intervals for the parameters whilst keeping within channel bandwidth limitations. Add an extra requirement of using variable word lengths to optimise the use of available bit rate and the problem becomes more challenging. The available telemetry or tape recorder channel bandwidth rather than the capabilities of the data acquisition system normally govern the amount of data that can be acquired by the aircraft instrumentation system. The amount of data demanded usually expands to fill all available bandwidth and the bit rates are operated at the maximum for the particular channel. The use of variable word lengths can, in some circumstances, increase the utilisation of a channel bandwidth. In order to visualise if a particular requirement can be accommodated within a given data structure a method of sketching PCM data frames containing a wide mixture of sample rates using an intermediate matrix has been devised. The method is described in three stages. 1. Compiling a simple PCM frame. 2. Sketching the intermediate matrix to assist in visualising super commutation limits. 3. Mixing variable word lengths and super commutation in the same PCM format. The method is not guaranteed to be the most efficient but does give a relatively simple, non mathematical, way to visualise if the required sample rates can be accommodated in a given data structure. If the requirement will not fit into the data structure then the method allows the impact of the necessary changes to the structure to be rapidly assessed. The paper includes comments on the relevant characteristics needed in the aircraft data acquisition system. These include variable word lengths, frame lengths, incremental bit rates and coherency of multiple data bus word parameters

Extraction of information from semi-structured or unstructured documents, such as Web pages, is a useful yet complex task. Research has demonstrated that ontologies may be used to achieve a high degree of accuracy in data extraction while maintaining resiliency in the face of document changes. Ontologies do not, however, diminish the complexity of a data-extraction system. As research in the field progresses, the need for a modular data-extraction system that de-couples the various functional processes involved continues to grow. In this thesis we propose a framework for such a system. The nature of the framework allows new algorithms and ideas to be incorporated into a data extraction system without requiring wholesale rewrites of a large part of the system’s source code. It also allows researchers to focus their attention on parts of the system relevant to their research without having to worry about introducing incompatibilities with the remaining components. We demonstrate the value of the framework by providing a implementation of it, and we show that our implementation is capable of achieving accuracy in its extraction results comparable to that achieved by the legacy BYU-Ontos data-extraction system. We also suggest alternate ways in which the framework may be extended and implemented, and we supply documentation on the framework for future use by data-extraction researchers.