Rapid Implementation and Optimisation of DSP Systems on FPGA-Centric Hetrogeneous Platforms

This paper, chosen as a best paper from the 2005 SAMOS Workshop on Computer Systems: describes the for the first time the major Abhainn project for automated system level design of embedded signal processing systems. In particular, this describes four key novelties: novel algorithm modelling techniques for DSP systems, automated implementation realisation, algorithm transformation for system optimisation and automated inter-processor communication. This is applied to two complex systems: a radar and sonar system. In both cases technology which allows non-experts to automatically create low-overhead, high performance embedded signal processing systems is exhibited.

Freeze-dried, mucoadhesive system for vaginal delivery of the HIV microbicide, dapivirine: Optimisation by an artificial neural network

Dapivirine mucoadhesive gels and freeze-dried tablets were prepared using a 3 x 3 x 2 factorial design. An artificial neural network (ANN) with multi-layer perception was used to investigate the effect of hydroxypropyl-methylcellulose (HPMC): polyvinylpyrrolidone (PVP) ratio (XI), mucoadhesive concentration (X2) and delivery system (gel or freeze-dried mucoadhesive tablet, X3) on response variables; cumulative release of dapivirine at 24 h (Q(24)), mucoadhesive force (F-max) and zero-rate viscosity. Optimisation was performed by minimising the error between the experimental and predicted values of responses by ANN. The method was validated using check point analysis by preparing six formulations of gels and their corresponding freeze-dried tablets randomly selected from within the design space of contour plots. Experimental and predicted values of response variables were not significantly different (p > 0.05, two-sided paired t-test). For gels, Q(24) values were higher than their corresponding freeze-dried tablets. F-max values for freeze-dried tablets were significantly different (2-4 times greater, p > 0.05, two-sided paired t-test) compared to equivalent gets. Freeze-dried tablets having lower values for X1 and higher values for X2 components offered the best compromise between effective dapivirine release, mucoadhesion and viscosity such that increased vaginal residence time was likely to be achieved. (C) 2009 Elsevier B.V. All rights reserved.

Optimisation of a two-liquid component pre-filled acrylic bone cement system: A design of experiments approach to optimise cement final properties

The initial composition of acrylic bone cement along with the mixing and delivery technique used can influence its final properties and therefore its clinical success in vivo. The polymerisation of acrylic bone cement is complex with a number of processes happening simultaneously. Acrylic bone cement mixing and delivery systems have undergone several design changes in their advancement, although the cement constituents themselves have remained unchanged since they were first used. This study was conducted to determine the factors that had the greatest effect on the final properties of acrylic bone cement using a pre-filled bone cement mixing and delivery system. A design of experiments (DoE) approach was used to determine the impact of the factors associated with this mixing and delivery method on the final properties of the cement produced. The DoE illustrated that all factors present within this study had a significant impact on the final properties of the cement. An optimum cement composition was hypothesised and tested. This optimum recipe produced cement with final mechanical and thermal properties within the clinical guidelines and stated by ISO 5833 (International Standard Organisation (ISO), International standard 5833: implants for surgery—acrylic resin cements, 2002), however the low setting times observed would not be clinically viable and could result in complications during the surgical technique. As a result further development would be required to improve the setting time of the cement in order for it to be deemed suitable for use in total joint replacement surgery.

Plug Force Monitoring for the Control and Optimisation of the Thermoforming Process

Thermoforming processes generally employ sheet temperature monitoring as the primary means of process control. In this paper the development of an alternative system that monitors plug force is described. Tests using a prototype device have shown that the force record over a forming cycle creates a unique map of the process operation. Key process features such as the sheet modulus, sheet sag and the timing of the process stages may be readily observed, and the effects of changes in all of the major processing parameters are easily distinguished. Continuous, cycle-to-cycle tests show that the output is consistent and repeatable over a longer time frame, providing the opportunity for development of an on-line process control system. Further testing of the system is proposed.

Model selection approaches for non-linear system identification: a review

The identification of non-linear systems using only observed finite datasets has become a mature research area over the last two decades. A class of linear-in-the-parameter models with universal approximation capabilities have been intensively studied and widely used due to the availability of many linear-learning algorithms and their inherent convergence conditions. This article presents a systematic overview of basic research on model selection approaches for linear-in-the-parameter models. One of the fundamental problems in non-linear system identification is to find the minimal model with the best model generalisation performance from observational data only. The important concepts in achieving good model generalisation used in various non-linear system-identification algorithms are first reviewed, including Bayesian parameter regularisation and models selective criteria based on the cross validation and experimental design. A significant advance in machine learning has been the development of the support vector machine as a means for identifying kernel models based on the structural risk minimisation principle. The developments on the convex optimisation-based model construction algorithms including the support vector regression algorithms are outlined. Input selection algorithms and on-line system identification algorithms are also included in this review. Finally, some industrial applications of non-linear models are discussed.

Integrated structure selection and parameter optimisation for eng-genes neural models

The eng-genes concept involves the use of fundamental known system functions as activation functions in a neural model to create a 'grey-box' neural network. One of the main issues in eng-genes modelling is to produce a parsimonious model given a model construction criterion. The challenges are that (1) the eng-genes model in most cases is a heterogenous network consisting of more than one type of nonlinear basis functions, and each basis function may have different set of parameters to be optimised; (2) the number of hidden nodes has to be chosen based on a model selection criterion. This is a mixed integer hard problem and this paper investigates the use of a forward selection algorithm to optimise both the network structure and the parameters of the system-derived activation functions. Results are included from case studies performed on a simulated continuously stirred tank reactor process, and using actual data from a pH neutralisation plant. The resulting eng-genes networks demonstrate superior simulation performance and transparency over a range of network sizes when compared to conventional neural models. (c) 2007 Elsevier B.V. All rights reserved.

3D die shape optimisation for net-shape forging of aerofoil blades

This paper reports on work in developing a finite element (FE) based die shape optimisation for net-shape forging of 3D aerofoil blades for aeroengine applications. Quantitative representations of aerofoil forging tolerances were established to provide a correlation between conventional dimensional and shape specifications in forging production and those quantified in FE simulation. A new direct compensation method was proposed, employing variable weighting factors to minimise the total forging tolerances in forging optimisation computations. A surface approximation using a B-spline surface was also developed to ensure improved die surface quality for die shape representation and design. For a Ni-alloy blade test case, substantial reduction in dimensional and shape tolerances was achieved using the developed die shape optimisation system.

Dynamic global security-aware synthesis using System-C

A dynamic global security-aware synthesis flow using the SystemC language is presented. SystemC security models are first specified at the system or behavioural level using a library of SystemC behavioural descriptions which provide for the reuse and extension of security modules. At the core of the system is incorporated a global security-aware scheduling algorithm which allows for scheduling to a mixture of components of varying security level. The output from the scheduler is translated into annotated nets which are subsequently passed to allocation, optimisation and mapping tools for mapping into circuits. The synthesised circuits incorporate asynchronous secure power-balanced and fault-protected components. Results show that the approach offers robust implementations and efficient security/area trade-offs leading to significant improvements in turnover.