Efficient FPGA-based regular expression pattern matching

An approach to the automatic generation of efficient Field Programmable Gate Arrays (FPGAs) circuits for the Regular Expression-based (RegEx) Pattern Matching problems is presented. Using a novel design strategy, as proposed, circuits that are highly area-and-time-efficient can be automatically generated for arbitrary sets of regular expressions. This makes the technique suitable for applications that must handle very large sets of patterns at high speed, such as in the network security and intrusion detection application domains. We have combined several existing techniques to optimise our solution for such domains and proposed the way the whole process of dynamic generation of FPGAs for RegEX pattern matching could be automated efficiently.

Compositional technique for synthesising multi-phase regular arrays

We describe a high-level design method to synthesize multi-phase regular arrays. The method is based on deriving component designs using classical regular (or systolic) array synthesis techniques and composing these separately evolved component design into a unified global design. Similarity transformations ar e applied to component designs in the composition stage in order to align data ow between the phases of the computations. Three transformations are considered: rotation, re ection and translation. The technique is aimed at the design of hardware components for high-throughput embedded systems applications and we demonstrate this by deriving a multi-phase regular array for the 2-D DCT algorithm which is widely used in many vide ocommunications applications.

Condition number estimates for combined potential integral operators in acoustics and their boundary element discretisation

We consider the classical coupled, combined-field integral equation formulations for time-harmonic acoustic scattering by a sound soft bounded obstacle. In recent work, we have proved lower and upper bounds on the $L^2$ condition numbers for these formulations, and also on the norms of the classical acoustic single- and double-layer potential operators. These bounds to some extent make explicit the dependence of condition numbers on the wave number $k$, the geometry of the scatterer, and the coupling parameter. For example, with the usual choice of coupling parameter they show that, while the condition number grows like $k^{1/3}$ as $k\to\infty$, when the scatterer is a circle or sphere, it can grow as fast as $k^{7/5}$ for a class of `trapping' obstacles. In this paper we prove further bounds, sharpening and extending our previous results. In particular we show that there exist trapping obstacles for which the condition numbers grow as fast as $\exp(\gamma k)$, for some $\gamma>0$, as $k\to\infty$ through some sequence. This result depends on exponential localisation bounds on Laplace eigenfunctions in an ellipse that we prove in the appendix. We also clarify the correct choice of coupling parameter in 2D for low $k$. In the second part of the paper we focus on the boundary element discretisation of these operators. We discuss the extent to which the bounds on the continuous operators are also satisfied by their discrete counterparts and, via numerical experiments, we provide supporting evidence for some of the theoretical results, both quantitative and asymptotic, indicating further which of the upper and lower bounds may be sharper.

A simple method of calculating eigenvalues and resonances in domains with infinite regular ends

A new approach is presented for the solution of spectral problems on infinite domains with regular ends, which avoids the need to solve boundary-value problems for many trial values of the spectral parameter. We present numerical results both for eigenvalues and for resonances, comparing with results reported by Aslanyan, Parnovski and Vassiliev.

Neurofuzzy network model construction using Bézier-Bernstein polynomial functions

Neurofuzzy modelling systems combine fuzzy logic with quantitative artificial neural networks via a concept of fuzzification by using a fuzzy membership function usually based on B-splines and algebraic operators for inference, etc. The paper introduces a neurofuzzy model construction algorithm using Bezier-Bernstein polynomial functions as basis functions. The new network maintains most of the properties of the B-spline expansion based neurofuzzy system, such as the non-negativity of the basis functions, and unity of support but with the additional advantages of structural parsimony and Delaunay input space partitioning, avoiding the inherent computational problems of lattice networks. This new modelling network is based on the idea that an input vector can be mapped into barycentric co-ordinates with respect to a set of predetermined knots as vertices of a polygon (a set of tiled Delaunay triangles) over the input space. The network is expressed as the Bezier-Bernstein polynomial function of barycentric co-ordinates of the input vector. An inverse de Casteljau procedure using backpropagation is developed to obtain the input vector's barycentric co-ordinates that form the basis functions. Extension of the Bezier-Bernstein neurofuzzy algorithm to n-dimensional inputs is discussed followed by numerical examples to demonstrate the effectiveness of this new data based modelling approach.

Head-controlled assistive telerobot with extended physiological proprioception capability

People with disabilities such as quadriplegia can use mouth-sticks and head-sticks as extension devices to perform desired manipulations. These extensions provide extended proprioception which allows users to directly feel forces and other perceptual cues such as texture present at the tip of the mouth-stick. Such devices are effective for two principle reasons: because of their close contact with the user's tactile and proprioceptive sensing abilities; and because they tend to be lightweight and very stiff, and can thus convey tactile and kinesthetic information with high-bandwidth. Unfortunately, traditional mouth-sticks and head-sticks are limited in workspace and in the mechanical power that can be transferred because of user mobility and strength limitations. We describe an alternative implementation of the head-stick device using the idea of a virtual head-stick: a head-controlled bilateral force-reflecting telerobot. In this system the end-effector of the slave robot moves as if it were at the tip of an imaginary extension of the user's head. The design goal is for the system is to have the same intuitive operation and extended proprioception as a regular mouth-stick effector but with augmentation of workspace volume and mechanical power. The input is through a specially modified six DOF master robot (a PerForceTM hand-controller) whose joints can be back-driven to apply forces at the user's head. The manipulation tasks in the environment are performed by a six degree-of-freedom slave robot (the Zebra-ZEROTM) with a built-in force sensor. We describe the prototype hardware/software implementation of the system, control system design, safety/disability issues, and initial evaluation tasks.

Chain extension in electrospun polystyrene fibres: a SANS study

Small angle neutron scattering techniques were used to quantify the size and shape of the chain conformation in electrospun fibres of atactic polystyrene prepared from solutions in methyl ethyl ketone. Aligned arrays of fibres were collected onto a rotating collector with tangential velocity varying between 0 ms-1 and approximately 15 ms-1. The measured radii of gyration of the polystyrene chains were found to be slightly higher than that expected for samples prepared from solutions in the concentrated regime. The ratio of the radius of gyration parallel and perpendicular to the chain axis was found to be approximately 1.05 in contrast to the substantial macroscopic shape transformation intrinsic to electrospinning. When the tangential velocity of the rotating collector was greater than the flight velocity of the fibres (ca. 4 ms-1), a further extension of the polymer chains was observed with a ratio of the radii of gyration increasing to 1.20 at the highest collector speeds. It is proposed that the heterogeneous processes involved, particularly solvent evaporation and the formation of a polymer skin during electrospinning play a significant role in determining the level of molecular anisotropy in the fibres.

Adapting to new challenges: extension theory and practice for the 21st century

Twenty first century challenges facing agriculture include climate change, threats to food security for a growing population and downward economic pressures on rural livelihoods. Addressing these challenges will require innovation in extension theory, policy and education, at a time when the dominance of the state in the provision of knowledge and information services to farmers and rural entrepreneurs continues to decline. This paper suggests that extension theory is catching up with and helping us to understand innovative extension practice, and therefore provides a platform for improving rural development policies and strategies. Innovation is now less likely to be spoken of as something to be passed on to farmers, than as a continuing process of creativity and adaptation that can be nurtured and sustained. Innovation systems and innovation platforms are concepts that recognise the multiple factors that lead to farmers’ developing, adapting and applying new ideas and the importance of linking all actors in the value chain to ensure producers can access appropriate information and advice for decision making at all stages in the production process. Concepts of social learning, group development and solidarity, social capital, collective action and empowerment all help to explain and therefore to apply more effectively group extension approaches in building confidence and sustaining innovation. A challenge facing educators is to ensure the curricula for aspiring extension professionals in our higher education institutions are regularly reviewed and keep up with current and future developments in theory, policy and practice.

Multi-layer radial basis function networks: an extension to the radial basis function

This paper presents the initial research carried out into a new neural network called the multilayer radial basis function network (MRBF). The network extends the radial basis function (RBF) in a similar way to that in which the multilayer perceptron extends the perceptron. It is hoped that by connecting RBFs together in a layered fashion, an equivalent increase in ability can be gained, as is gained from using MLPs instead of single perceptrons. The results of a practical comparison between individual RBFs and MRBF's are also given.