Abstract
Two function allocation methods developed from differing perspectives are contrasted. One takes as its scope the organizational structure of a system and models the allocation of function from the perspective of this structure. The other takes the individual partnership between a human and machine as its scope and models the allocation of function from the perspective of the situational context within which this partnership operates. In the process of contrasting these methods, the essence of a new function allocation process that combines the best features of both is introduced. The new method is intended to support the design of complex dynamic control systems consisting of multiple agents.

Abstract
We introduce two formulations for training support vector machines, based on considering the L-1 and L-infinity norms instead of the currently used L-2 norm, and maximising the margin between the separating hyperplane and each data sets using L-1 and L-infinity distances. We exploit the geometrical properties of these different norms. and propose what kind of results should be expected for them. Formulations in mathematical programming for linear problems corresponding to L-1 and L-infinity norms are also provided, for both the separable and non-separable cases. We report results obtained for some standard benchmark problems. which confirmed that the performance of all the formulations is similar. As expected, the CPU time required for machines solvable with linear programming is much shorter.

Abstract
Matching and searching computations play an important role in the indexing of data. These computations are typically encoded in very tight loops with a single index variable and a simple search/matching predicate. Their inherent sequential nature, either because of data dependences but more often because of very strong control dependences, makes it impossible to apply existing data dependence and parallelization analysis to exploit significant levels parallelism on traditional architectures. This paper describes a class of searching and matching computations and describes a mapping strategy to map these computations to hardware. We have developed a compiler analysis in SUIF using array data dependence analysis and implicit loop unrolling analysis to expose more parallelism for the parallel evaluation of these computations. Our compiler generates parallel hardware specifications in VHDL. The resulting parallel hardware yields significant performance improvements when these kernel operators are repeated over shifted portions of the input data on FPGA-based computing architectures.

Abstract
Fused biconical wavelength division multiplexers have been used to replace standard couplers in an intensity-sensor multiplexing network. The wavelength-selective power splitting and the low insertion losses of these devices (< 0.2dB) improve the power budget, while providing network overall optical isolations > 30dB. With this isolation, crosstalk effects in the network are proven to be negligible.

Abstract
Commercially available behavioral synthesis tools do not adequately support FPGA vendor-specific external memory interfaces making it extremely difficult to exploit pipelined memory access modes as well as application specific memory operations scheduling critical for high-performance solutions. This lack of support substantially increases the complexity and the burden on designers in the mapping of applications to FPGA- based computing engines. In this paper we address the problem of external memory interfacing and aggressive scheduling of memory operations by proposing a decoupled architecture with two components - one component captures the specific target architecture timing while the other component uses application specific memory access pattern information. Our results support the claim that it is possible to exploit application specific information and integrate that knowledge into custom schedulers that mix pipelined and non-pipelined access modes aimed at reducing the overhead associated with external memory accesses. The results also reveal that the additional design complexity of the scheduler, and its impact in the overall design is minimal.

Abstract
This paper presents a smart composite for structural monitorisation, based on fibre Bragg grating sensors. The sensor plate, a carbon fibre reinforced plastic laminate having an embedded optical strain gauge rosette, was designed, produced, and tested. These instrumented carbon fibre laminates can be used for monitoring of reinforcement and protection of structures, playing an important role in the control of repaired constructions. The smart structures developed are shown to have the ability of measuring temperature and strain.