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Articles 1 - 13 of 13
Full-Text Articles in Physical Sciences and Mathematics
Case Study On An Investigation Of Information Security Management Among Law Firms, Sameera Mubarak, Elena Sitnikova
Case Study On An Investigation Of Information Security Management Among Law Firms, Sameera Mubarak, Elena Sitnikova
Australian Information Security Management Conference
The integrity of lawyers trust accounts as come under scrutiny in the last few years. There have been many incidents of trust account fraud reported internationally, including a case in Australia, where an employee of a law firm stole $4,500,000 from the trust funds of forty-two clients. Our study involved interviewing principles of ten law companies to find out solicitors’ attitudes to computer security and the possibility of breaches of their trust accounts. An overall finding highlights that law firms were not current with technology to combat computer crime, and inadequate access control was a major concern in safeguarding account …
A Generalised Feedforward Neural Network Architecture And Its Applications To Classification And Regression, Ganesh Arulampalam
A Generalised Feedforward Neural Network Architecture And Its Applications To Classification And Regression, Ganesh Arulampalam
Theses: Doctorates and Masters
Shunting inhibition is a powerful computational mechanism that plays an important role in sensory neural information processing systems. It has been extensively used to model some important visual and cognitive functions. It equips neurons with a gain control mechanism that allows them to operate as adaptive non-linear filters. Shunting Inhibitory Artificial Neural Networks (SIANNs) are biologically inspired networks where the basic synaptic computations are based on shunting inhibition. SIANNs were designed to solve difficult machine learning problems by exploiting the inherent non-linearity mediated by shunting inhibition. The aim was to develop powerful, trainable networks, with non-linear decision surfaces, for classification …
Contrast Enhancement Of Ultrasound Images Using Shunting Inhibitory Cellular Neural Networks, Murali M. Gogineni
Contrast Enhancement Of Ultrasound Images Using Shunting Inhibitory Cellular Neural Networks, Murali M. Gogineni
Theses: Doctorates and Masters
Evolving from neuro-biological insights, neural network technology gives a computer system an amazing capacity to actually generate decisions dynamically. However, as the amount of data to be processed increases, there is a demand for developing new types of networks such as Cellular Neural Networks (CNN), to ease the computational burden without compromising the outcomes. The objective of this thesis is to research the capability of Shunting Inhibitory Cellular Neural Networks (SICNN) to solve the clarity problems in ultrasound imaging. In this thesis, we begin by reviewing a number of traditional enhancement techniques and measures. Since the entire work of this …
An Investigation Into The Use Of Software Code Metrics In The Industrial Software Development Environment, Tim Littlefair
An Investigation Into The Use Of Software Code Metrics In The Industrial Software Development Environment, Tim Littlefair
Theses: Doctorates and Masters
This work describes a project that investigates the use of software metrics based on measurement of source code in industrial software development. Literature is examined relating to considerations of quality in industry; to software engineering; to emergent technologies in the software industry including the object-oriented paradigm and software patterns; to software product and process metrics; and to cultural factors affecting workplaces in the software industry. It then expounds theoretical and practical work aimed at specifying, designing and implementing a source code analyzer for use in a typical industrial project setting. There is an explanation of the design and outcomes of …
An Adaptive Hierarchical Fuzzy Logic System For Modelling And Prediction Of Financial Systems, Mark Kingham
An Adaptive Hierarchical Fuzzy Logic System For Modelling And Prediction Of Financial Systems, Mark Kingham
Theses: Doctorates and Masters
In this thesis, an intelligent fuzzy logic system using genetic algorithms for the prediction and modelling of interest rates is developed. The proposed system uses a Hierarchical Fuzzy Logic system in which a genetic algorithm is used as a training method for learning the fuzzy rules knowledge bases. A fuzzy logic system is developed to model and predict three month quarterly interest rate fluctuations. The system is further trained to model and predict interest rates for six month and one year periods. The proposed system is developed with first two, three, then four and finally five hierarchical knowledge bases to …
A Methodology For The Selection Of A Paradigm Of Reasoning Under Uncertainty In Expert System Development, Vivian Campbell
A Methodology For The Selection Of A Paradigm Of Reasoning Under Uncertainty In Expert System Development, Vivian Campbell
Theses: Doctorates and Masters
The aim of this thesis is to develop a methodology for the selection of a paradigm of reasoning under uncertainty for the expert system developer. This is important since practical information on how to select a paradigm of reasoning under uncertainty is not generally available. The thesis explores the role of uncertainty in an expert system and considers the process of reasoning under uncertainty. The possible sources of uncertainty are investigated and prove to be crucial to some aspects of the methodology. A variety of Uncertainty Management Techniques (UMTs) are considered, including numeric, symbolic and hybrid methods. Considerably more information …
An Approach To Display Layout Of Dynamic Windows, Nihar Trivedi
An Approach To Display Layout Of Dynamic Windows, Nihar Trivedi
Theses: Doctorates and Masters
The development of windows based user interface has introduced a new dimension to the field of human computer interaction. Now a user is able to perform multiple tasks at a time, often switching from one task to another. However windows environment also imposes the burden of manual windows management on the user. Several studies have suggested that manual window management is an unproductive chore often resulting in clutter and confusion on the display screen. Therefore we need a automatic windows layout generator to free the user to perform other useful tasks. This thesis introduces SPORDAC {Shadow Propagation for Overlap Removal …
A Search Tool To Enhance The Selection And Utilisation Of Reusable Software Modules Within The Object-Oriented Paradigm, Robert H. Cross
A Search Tool To Enhance The Selection And Utilisation Of Reusable Software Modules Within The Object-Oriented Paradigm, Robert H. Cross
Theses: Doctorates and Masters
The affinity for reuse within the object-oriented paradigm may enable high levels of productivity; however, gains will become realisable only if a systems developer has access to tools which aid in the selection of classes. A method for object-oriented analysis and design is detailed and its process is assisted by an object-oriented search tool based on reference and corporate library technology. The search tool contributes to the determination of suitable existing inheritable classes and an explanation of its construction and use is included. A practical demonstration of the method, using the search tool, is elaborated. The thesis demonstrates that text …
Applications Of Fuzzy Counterpropagation Neural Networks To Non-Linear Function Approximation And Background Noise Elimination, I. M. Wiryana
Applications Of Fuzzy Counterpropagation Neural Networks To Non-Linear Function Approximation And Background Noise Elimination, I. M. Wiryana
Theses: Doctorates and Masters
An adaptive filter which can operate in an unknown environment by performing a learning mechanism that is suitable for the speech enhancement process. This research develops a novel ANN model which incorporates the fuzzy set approach and which can perform a non-linear function approximation. The model is used as the basic structure of an adaptive filter. The learning capability of ANN is expected to be able to reduce the development time and cost of the designing adaptive filters based on fuzzy set approach. A combination of both techniques may result in a learnable system that can tackle the vagueness problem …
A Model Of Visual Recognition Implemented Using Neural Networks, Vincent C. Phillips
A Model Of Visual Recognition Implemented Using Neural Networks, Vincent C. Phillips
Theses: Doctorates and Masters
The ability to recognise and classify objects in the environment is an important property of biological vision. It is highly desirable that artificial vision systems also have this ability. This thesis documents research into the use of artificial neural networks to implement a prototype model of visual object recognition. The prototype model, describing a computtional architecture, is derived from relevant physiological and psychological data, and attempts to resolve the use of structural decomposition and invariant feature detection. To validate the research a partial implementation of the model has been constructed using multiple neural networks. A linear feed-forward network performs pre-procesing …
A Study Of The Methodologies Currently Available For The Maintenance Of The Knowledge-Base In An Expert System, Kai Teh
Theses: Doctorates and Masters
This research studies currently available maintenance methodologies for expert system knowledge bases and taxonomically classifies them according to the functions they perform. The classification falls into two broad categories. These are: (1) Methodologies for building a more maintainable expert system knowledge base. This section covers techniques applicable to the development phases. Software engineering approaches as well as other approaches are discussed. (2) Methodologies for maintaining an existing knowledge base. This section is concerned with the continued maintenance of an existing knowledge base. It is divided into three subsections. The first subsection discusses tools and techniques which aid the understanding of …
An Examination And Analysis Of The Boltzmann Machine, Its Mean Field Theory Approximation, And Learning Algorithm, Vincent Clive Phillips
An Examination And Analysis Of The Boltzmann Machine, Its Mean Field Theory Approximation, And Learning Algorithm, Vincent Clive Phillips
Theses : Honours
It is currently believed that artificial neural network models may form the basis for inte1ligent computational devices. The Boltzmann Machine belongs to the class of recursive artificial neural networks and uses a supervised learning algorithm to learn the mapping between input vectors and desired outputs. This study examines the parameters that influence the performance of the Boltzmann Machine learning algorithm. Improving the performance of the algorithm through the use of a naïve mean field theory approximation is also examined. The study was initiated to examine the hypothesis that the Boltzmann Machine learning algorithm, when used with the mean field approximation, …
The Development Of An Expert System For The Diagnosis Of Diseases In Fibre And Dairy Goats, Tim S. Roberts
The Development Of An Expert System For The Diagnosis Of Diseases In Fibre And Dairy Goats, Tim S. Roberts
Theses: Doctorates and Masters
This thesis details the development of an expert system for the diagnosis of diseases in fibre and dairy goats. Divided into five sections, five appendices, and a bibliography, this thesis centres on the methods used to build the expert system: the decisions taken at the outset of, and during the course of, development; some of the problems encountered, and the solutions to those problems. A detailed appraisal is made of the development process and suggestions are made for future developments over similar domains (for example, the diagnosis of diseases in animals other than goats). Much emphasis is placed on three …