Character recognition systems using Fourier transformation in incoherent light

Many attempts have been made to overcome problems involved in character recognition which have resulted in the manufacture of character reading machines. An investigation into a new approach to character recognition is described. Features for recognition are Fourier coefficients. These are generated optically by convolving characters with periodic gratings. The development of hardware to enable automatic measurement of contrast and position of periodic shadows produced by the convolution is described. Fourier coefficients of character sets were measured, many of which are tabulated. Their analysis revealed that a few low frequency sampling points could be selected to recognise sets of numerals. Limited treatment is given to show the effect of type face variations on the values of coefficients which culminated in the location of six sampling frequencies used as features to recognise numerals in two type fonts. Finally, the construction of two character recognition machines is compared and contrasted. The first is a pilot plant based on a test bed optical Fourier analyser, while the second is a more streamlined machine d(3signed for high speed reading. Reasons to indicate that the latter machine would be the most suitable to adapt for industrial and commercial applications are discussed.

Causality and synchronisation in complex systems with applications to neuroscience

This thesis presents an investigation, of synchronisation and causality, motivated by problems in computational neuroscience. The thesis addresses both theoretical and practical signal processing issues regarding the estimation of interdependence from a set of multivariate data generated by a complex underlying dynamical system. This topic is driven by a series of problems in neuroscience, which represents the principal background motive behind the material in this work. The underlying system is the human brain and the generative process of the data is based on modern electromagnetic neuroimaging methods . In this thesis, the underlying functional of the brain mechanisms are derived from the recent mathematical formalism of dynamical systems in complex networks. This is justified principally on the grounds of the complex hierarchical and multiscale nature of the brain and it offers new methods of analysis to model its emergent phenomena. A fundamental approach to study the neural activity is to investigate the connectivity pattern developed by the brain’s complex network. Three types of connectivity are important to study: 1) anatomical connectivity refering to the physical links forming the topology of the brain network; 2) effective connectivity concerning with the way the neural elements communicate with each other using the brain’s anatomical structure, through phenomena of synchronisation and information transfer; 3) functional connectivity, presenting an epistemic concept which alludes to the interdependence between data measured from the brain network. The main contribution of this thesis is to present, apply and discuss novel algorithms of functional connectivities, which are designed to extract different specific aspects of interaction between the underlying generators of the data. Firstly, a univariate statistic is developed to allow for indirect assessment of synchronisation in the local network from a single time series. This approach is useful in inferring the coupling as in a local cortical area as observed by a single measurement electrode. Secondly, different existing methods of phase synchronisation are considered from the perspective of experimental data analysis and inference of coupling from observed data. These methods are designed to address the estimation of medium to long range connectivity and their differences are particularly relevant in the context of volume conduction, that is known to produce spurious detections of connectivity. Finally, an asymmetric temporal metric is introduced in order to detect the direction of the coupling between different regions of the brain. The method developed in this thesis is based on a machine learning extensions of the well known concept of Granger causality. The thesis discussion is developed alongside examples of synthetic and experimental real data. The synthetic data are simulations of complex dynamical systems with the intention to mimic the behaviour of simple cortical neural assemblies. They are helpful to test the techniques developed in this thesis. The real datasets are provided to illustrate the problem of brain connectivity in the case of important neurological disorders such as Epilepsy and Parkinson’s disease. The methods of functional connectivity in this thesis are applied to intracranial EEG recordings in order to extract features, which characterize underlying spatiotemporal dynamics before during and after an epileptic seizure and predict seizure location and onset prior to conventional electrographic signs. The methodology is also applied to a MEG dataset containing healthy, Parkinson’s and dementia subjects with the scope of distinguishing patterns of pathological from physiological connectivity.

Computational mechanics of molecular systems:quantifying high-dimensional dynamics by distribution of Poincaré recurrence times

A framework that connects computational mechanics and molecular dynamics has been developed and described. As the key parts of the framework, the problem of symbolising molecular trajectory and the associated interrelation between microscopic phase space variables and macroscopic observables of the molecular system are considered. Following Shalizi and Moore, it is shown that causal states, the constituent parts of the main construct of computational mechanics, the e-machine, define areas of the phase space that are optimal in the sense of transferring information from the micro-variables to the macro-observables. We have demonstrated that, based on the decay of their Poincare´ return times, these areas can be divided into two classes that characterise the separation of the phase space into resonant and chaotic areas. The first class is characterised by predominantly short time returns, typical to quasi-periodic or periodic trajectories. This class includes a countable number of areas corresponding to resonances. The second class includes trajectories with chaotic behaviour characterised by the exponential decay of return times in accordance with the Poincare´ theorem.

Biology of sensory systems

A comprehensive and highly illustrated text providing a broad and invaluable overview of sensory systems at the molecular, cellular and neurophysiological level of vertebrates, invertebrates and prokaryotes. It retains a strong focus on human systems, and takes an evolutionary and comparative approach to review the mechanosenses, chemosenses, photosenses, and other sensory systems including those for detecting pain, temperature electric and magnetic fields etc. It incorporates exciting and significant new insights provided by molecular biology which demonstrate how similar the molecular architecture and physiology of sensory cells are across species and across sensory modality, often indicationg a common ancestry dating back over half a billion years. Written by a renowned author, with extensive teaching experience in the biology of sensory systems, this book includes: - Over 400 illustrations - Self–assessment questions - Full bibliography preceded by short bibliographical essays - Boxes containing useful supplementary material. It will be invaluable for undergraduates and postgraduates studying biology, zoology, animal physiology, neuroscience, anatomy, molecular biology, physiological psychology and related courses.

Canonical solution groups of a homomorphism : manipulator kinematics, nonparametric regression and distributed object systems

The kinematic mapping of a rigid open-link manipulator is a homomorphism between Lie groups. The homomorphisrn has solution groups that act on an inverse kinematic solution element. A canonical representation of solution group operators that act on a solution element of three and seven degree-of-freedom (do!) dextrous manipulators is determined by geometric analysis. Seven canonical solution groups are determined for the seven do! Robotics Research K-1207 and Hollerbach arms. The solution element of a dextrous manipulator is a collection of trivial fibre bundles with solution fibres homotopic to the Torus. If fibre solutions are parameterised by a scalar, a direct inverse funct.ion that maps the scalar and Cartesian base space coordinates to solution element fibre coordinates may be defined. A direct inverse pararneterisation of a solution element may be approximated by a local linear map generated by an inverse augmented Jacobian correction of a linear interpolation. The action of canonical solution group operators on a local linear approximation of the solution element of inverse kinematics of dextrous manipulators generates cyclical solutions. The solution representation is proposed as a model of inverse kinematic transformations in primate nervous systems. Simultaneous calibration of a composition of stereo-camera and manipulator kinematic models is under-determined by equi-output parameter groups in the composition of stereo-camera and Denavit Hartenberg (DH) rnodels. An error measure for simultaneous calibration of a composition of models is derived and parameter subsets with no equi-output groups are determined by numerical experiments to simultaneously calibrate the composition of homogeneous or pan-tilt stereo-camera with DH models. For acceleration of exact Newton second-order re-calibration of DH parameters after a sequential calibration of stereo-camera and DH parameters, an optimal numerical evaluation of DH matrix first order and second order error derivatives with respect to a re-calibration error function is derived, implemented and tested. A distributed object environment for point and click image-based tele-command of manipulators and stereo-cameras is specified and implemented that supports rapid prototyping of numerical experiments in distributed system control. The environment is validated by a hierarchical k-fold cross validated calibration to Cartesian space of a radial basis function regression correction of an affine stereo model. Basic design and performance requirements are defined for scalable virtual micro-kernels that broker inter-Java-virtual-machine remote method invocations between components of secure manageable fault-tolerant open distributed agile Total Quality Managed ISO 9000+ conformant Just in Time manufacturing systems.

A methodology for analysis and control of discrete event dynamic systems

The rapid developments in computer technology have resulted in a widespread use of discrete event dynamic systems (DEDSs). This type of system is complex because it exhibits properties such as concurrency, conflict and non-determinism. It is therefore important to model and analyse such systems before implementation to ensure safe, deadlock free and optimal operation. This thesis investigates current modelling techniques and describes Petri net theory in more detail. It reviews top down, bottom up and hybrid Petri net synthesis techniques that are used to model large systems and introduces on object oriented methodology to enable modelling of larger and more complex systems. Designs obtained by this methodology are modular, easy to understand and allow re-use of designs. Control is the next logical step in the design process. This thesis reviews recent developments in control DEDSs and investigates the use of Petri nets in the design of supervisory controllers. The scheduling of exclusive use of resources is investigated and an efficient Petri net based scheduling algorithm is designed and a re-configurable controller is proposed. To enable the analysis and control of large and complex DEDSs, an object oriented C++ software tool kit was developed and used to implement a Petri net analysis tool, Petri net scheduling and control algorithms. Finally, the methodology was applied to two industrial DEDSs: a prototype can sorting machine developed by Eurotherm Controls Ltd., and a semiconductor testing plant belonging to SGS Thomson Microelectronics Ltd.

Mild wear in dry and lubricated sliding systems

A vertical pin on horizontal disc machine has been used to conduct a series of experiments in air under dry and lubricating sliding conditions. For dry sliding low load and speed combinations were chosen to correspond to the mild wear region below the Welsh T1 transition. Lubricated tests were conducted under flooded conditions using Esso Technical White Oil alone and with a 0.1% stearic acid additive, for load and speed ranges that produced substantial amounts of asperity contact and thus a boundary lubricated regime of wear. The test material in all cases was AISI 52100 steel, for unlubricated sliding subjected to loads from 5 to 50 N and a range of speeds from 10-3 to 1.0 ms-1, and for lubricated sliding loads of 50 to 123 N and for speeds of 10-2 to 1.0 ms-1. Unlubricated wear debris was found to be a mixture of -Fe_2O_3 and -Fe. Unlubricated wear was found to occur via a thin film logarithmic oxide growth followed by agglomeration into thicker oxide plateaux 2 to 10 m in thickness. Lubricated wear occurred via thick film diffusion controlled oxide growth producing homogeneous oxide plateaux 0.1 to 0.2 m in thickness. X-ray photoelectron spectroscopy identified the presence of a surface film on pins worn in White Oil with stearic acid, which is thought to be iron stearate. A model has been developed for unlubricated wear based upon the postulated growth of thin film oxides by a logarithmic rate law. The importance of sliding geometry and environment to the dominant wear mechanism has been illustrated.

Visual data mining: integrating machine learning with information visualization

Today, the data available to tackle many scientific challenges is vast in quantity and diverse in nature. The exploration of heterogeneous information spaces requires suitable mining algorithms as well as effective visual interfaces. Most existing systems concentrate either on mining algorithms or on visualization techniques. Though visual methods developed in information visualization have been helpful, for improved understanding of a complex large high-dimensional dataset, there is a need for an effective projection of such a dataset onto a lower-dimension (2D or 3D) manifold. This paper introduces a flexible visual data mining framework which combines advanced projection algorithms developed in the machine learning domain and visual techniques developed in the information visualization domain. The framework follows Shneiderman’s mantra to provide an effective user interface. The advantage of such an interface is that the user is directly involved in the data mining process. We integrate principled projection methods, such as Generative Topographic Mapping (GTM) and Hierarchical GTM (HGTM), with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates, billboarding, and user interaction facilities, to provide an integrated visual data mining framework. Results on a real life high-dimensional dataset from the chemoinformatics domain are also reported and discussed. Projection results of GTM are analytically compared with the projection results from other traditional projection methods, and it is also shown that the HGTM algorithm provides additional value for large datasets. The computational complexity of these algorithms is discussed to demonstrate their suitability for the visual data mining framework.

Magnetic drive system for a new centrifugal rotary blood pump

The purpose of this investigation was to design a novel magnetic drive and bearing system for a new centrifugal rotary blood pump (CRBP). The drive system consists of two components: (i) permanent magnets within the impeller of the CRBP; and (ii) the driving electromagnets. Orientation of the magnets varies from axial through to 60° included out-lean (conical configuration). Permanent magnets replace the electromagnet drive to allow easier characterization. The performance characteristics tested were the axial force of attraction between the stator and rotor at angles of rotational alignment, Ø, and the corresponding torque at those angles. The drive components were tested for various magnetic cone angles, ?. The test was repeated for three backing conditions: (i) non-backed; (ii) steel-cupped; and (iii) steel plate back-iron, performed on an Instron tensile testing machine. Experimental results were expanded upon through finite element and boundary element analysis (BEM). The force/torque characteristics were maximal for a 12-magnet configuration at 0° cone angle with steel-back iron (axial force = 60 N, torque = 0.375 Nm). BEM showed how introducing a cone angle increases the radial restoring force threefold while not compromising axial bearing force. Magnets in the drive system may be orientated not only to provide adequate coupling to drive the CRBP, but to provide significant axial and radial bearing forces capable of withstanding over 100 m/s2 shock excitation on the impeller. Although the 12 magnet 0° (?) configuration yielded the greatest force/torque characteristic, this was seen as potentially unattractive as this magnetic cone angle yielded poor radial restoring force characteristics.

Approximating differentiable relationships between delay embedded dynamical systems with radical basis functions

This thesis is about the study of relationships between experimental dynamical systems. The basic approach is to fit radial basis function maps between time delay embeddings of manifolds. We have shown that under certain conditions these maps are generically diffeomorphisms, and can be analysed to determine whether or not the manifolds in question are diffeomorphically related to each other. If not, a study of the distribution of errors may provide information about the lack of equivalence between the two. The method has applications wherever two or more sensors are used to measure a single system, or where a single sensor can respond on more than one time scale: their respective time series can be tested to determine whether or not they are coupled, and to what degree. One application which we have explored is the determination of a minimum embedding dimension for dynamical system reconstruction. In this special case the diffeomorphism in question is closely related to the predictor for the time series itself. Linear transformations of delay embedded manifolds can also be shown to have nonlinear inverses under the right conditions, and we have used radial basis functions to approximate these inverse maps in a variety of contexts. This method is particularly useful when the linear transformation corresponds to the delay embedding of a finite impulse response filtered time series. One application of fitting an inverse to this linear map is the detection of periodic orbits in chaotic attractors, using suitably tuned filters. This method has also been used to separate signals with known bandwidths from deterministic noise, by tuning a filter to stop the signal and then recovering the chaos with the nonlinear inverse. The method may have applications to the cancellation of noise generated by mechanical or electrical systems. In the course of this research a sophisticated piece of software has been developed. The program allows the construction of a hierarchy of delay embeddings from scalar and multi-valued time series. The embedded objects can be analysed graphically, and radial basis function maps can be fitted between them asynchronously, in parallel, on a multi-processor machine. In addition to a graphical user interface, the program can be driven by a batch mode command language, incorporating the concept of parallel and sequential instruction groups and enabling complex sequences of experiments to be performed in parallel in a resource-efficient manner.

The use of deterministic parsers on sublanguage for machine translation

For more than forty years, research has been on going in the use of the computer in the processing of natural language. During this period methods have evolved, with various parsing techniques and grammars coming to prominence. Problems still exist, not least in the field of Machine Translation. However, one of the successes in this field is the translation of sublanguage. The present work reports Deterministic Parsing, a relatively new parsing technique, and its application to the sublanguage of an aircraft maintenance manual for Machine Translation. The aim has been to investigate the practicability of using Deterministic Parsers in the analysis stage of a Machine Translation system. Machine Translation, Sublanguage and parsing are described in general terms with a review of Deterministic parsing systems, pertinent to this research, being presented in detail. The interaction between machine Translation, Sublanguage and Parsing, including Deterministic parsing, is also highlighted. Two types of Deterministic Parser have been investigated, a Marcus-type parser, based on the basic design of the original Deterministic parser (Marcus, 1980) and an LR-type Deterministic Parser for natural language, based on the LR parsing algorithm. In total, four Deterministic Parsers have been built and are described in the thesis. Two of the Deterministic Parsers are prototypes from which the remaining two parsers to be used on sublanguage have been developed. This thesis reports the results of parsing by the prototypes, a Marcus-type parser and an LR-type parser which have a similar grammatical and linguistic range to the original Marcus parser. The Marcus-type parser uses a grammar of production rules, whereas the LR-type parser employs a Definite Clause Grammar(DGC).

Combining data driven programming with component based software development:with applications in geovisualisation and dynamic data driven application systems

Software development methodologies are becoming increasingly abstract, progressing from low level assembly and implementation languages such as C and Ada, to component based approaches that can be used to assemble applications using technologies such as JavaBeans and the .NET framework. Meanwhile, model driven approaches emphasise the role of higher level models and notations, and embody a process of automatically deriving lower level representations and concrete software implementations. The relationship between data and software is also evolving. Modern data formats are becoming increasingly standardised, open and empowered in order to support a growing need to share data in both academia and industry. Many contemporary data formats, most notably those based on XML, are self-describing, able to specify valid data structure and content, and can also describe data manipulations and transformations. Furthermore, while applications of the past have made extensive use of data, the runtime behaviour of future applications may be driven by data, as demonstrated by the field of dynamic data driven application systems. The combination of empowered data formats and high level software development methodologies forms the basis of modern game development technologies, which drive software capabilities and runtime behaviour using empowered data formats describing game content. While low level libraries provide optimised runtime execution, content data is used to drive a wide variety of interactive and immersive experiences. This thesis describes the Fluid project, which combines component based software development and game development technologies in order to define novel component technologies for the description of data driven component based applications. The thesis makes explicit contributions to the fields of component based software development and visualisation of spatiotemporal scenes, and also describes potential implications for game development technologies. The thesis also proposes a number of developments in dynamic data driven application systems in order to further empower the role of data in this field.

The prediction of vibration in large electric machines

This thesis reports the development of a reliable method for the prediction of response to electromagnetically induced vibration in large electric machines. The machines of primary interest are DC ship-propulsion motors but much of the work reported has broader significance. The investigation has involved work in five principal areas. (1) The development and use of dynamic substructuring methods. (2) The development of special elements to represent individual machine components. (3) Laboratory scale investigations to establish empirical values for properties which affect machine vibration levels. (4) Experiments on machines on the factory test-bed to provide data for correlation with prediction. (5) Reasoning with regard to the effect of various design features. The limiting factor in producing good models for machines in vibration is the time required for an analysis to take place. Dynamic substructuring methods were adopted early in the project to maximise the efficiency of the analysis. A review of existing substructure- representation and composite-structure assembly methods includes comments on which are most suitable for this application. In three appendices to the main volume methods are presented which were developed by the author to accelerate analyses. Despite significant advances in this area, the limiting factor in machine analyses is still time. The representation of individual machine components was addressed as another means by which the time required for an analysis could be reduced. This has resulted in the development of special elements which are more efficient than their finite-element counterparts. The laboratory scale experiments reported were undertaken to establish empirical values for the properties of three distinct features - lamination stacks, bolted-flange joints in rings and cylinders and the shimmed pole-yoke joint. These are central to the preparation of an accurate machine model. The theoretical methods are tested numerically and correlated with tests on two machines (running and static). A system has been devised with which the general electromagnetic forcing may be split into its most fundamental components. This is used to draw some conclusions about the probable effects of various design features.

Cost effectiveness of production control systems

This thesis deals with the problems associated with the planning and control of production, with particular reference to a small aluminium die casting company. The main problem areas were identified as: (a) A need to be able to forecast the customers demands upon the company's facilities. (b) A need to produce a manufacturing programme in which the output of the foundry (or die casting section) was balanced with the available capacity in the machine shop. (c) The need to ensure that the resultant system enabled the company's operating budget to have a reasonable chance of being achieved. At the commencement of the research work the major customers were members of the automobile industry and had their own system of forecasting, from which they issued manufacturing schedules to their component suppliers, The errors in the forecast were analysed and the distributions noted. Using these distributions the customer's forecast was capable of being modified to enable his final demand to be met with a known degree of confidence. Before a manufacturing programme could be developed the actual manufacturing system had to be reviewed and it was found that as with many small companies there was a remarkable lack of formal control and written data. Relevant data with regards to the component and the manufacturing process had therefore to be collected and analysed. The foundry process was fixed but the secondary machining operations were analysed by a technique similar to Component Flow Analysis and as a result the machines were arranged in a series of flow lines. A system of manual production control was proposed and for comparison, a local computer bureau was approached and a system proposed incorporating the production of additional management information. These systems are compared and the relative merits discussed and a proposal made for implementation.

The autonomous navigation of an electric vehicle

A navigation and positioning system for an electric automatic guided vehicle has been designed and implemented on an industrial pallet truck. The system includes an optical sensor mounted on the vehicle, capable of recognizing special markers at a distance of 0.3m. Software implemented in a z-80 microprocessor controls the sensor, performs all data processing and contains the decision making processes necessary for the vehicle to navigate its way to its task location. A second microprocessor is used to control the vehicle's drive motors under instruction from the navigation unit, to accurately position the vehicle at its destination. The sensor reliably recognises markers at vehicle speeds up to 1ms- 1, and the system has been integrated into a multiprocessor controlled wire-guidance system and applied to a prototype vehicle.