63 results for Working or discussion paper, 1999

  • Adaptive, evolving, hybrid connectionist systems for image pattern recognition

    Kasabov, Nikola; Israel, Steven; Woodford, Brendon J (1999-05)

    Working or discussion paper
    University of Otago

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  • Finding medical information on the Internet: Who should do it and what should they know

    Parry, David (1999-06)

    Working or discussion paper
    University of Otago

    More and more medical information is appearing on the Internet, but it is not easy to get at the nuggets amongst all the spoil. Bruce McKenzie's editorial in the December 1997 edition of SIM Quarterly dealt very well with the problems of quality, but I would suggest that the problem of accessibility is as much of a challenge. As ever-greater quantities of high quality medical information are published electronically, the need to be able to find it becomes imperative. There are a number of tools to find what you want on the Internet---search engines, agents, indexing and classification schemes and hyperlinks, but their use requires care, skill and experience.

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  • Hybrid neuro-fuzzy inference systems and their application for on-line adaptive learning of nonlinear dynamical systems

    Kim, Jaesoo; Kasabov, Nikola (1999-03)

    Working or discussion paper
    University of Otago

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  • Wayfinding/navigation within a QTVR virtual environment: preliminary results

    Norris, Brian; Rashid, Da'oud; Wong, B L William (1999-09)

    Working or discussion paper
    University of Otago

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  • Modifications to Smith’s method for deriving normalised relations from a functional dependency diagram

    Stanger, Nigel (1999-12)

    Working or discussion paper
    University of Otago

    Smith’s method is a formal technique for deriving a set of normalised relations from a functional dependency diagram (FDD). Smith’s original rules for deriving these relations are incomplete, as they do not fully address the issue of determining the foreign key links between relations. In addition, one of the rules for deriving foreign keys can produce incorrect results, while the other rule is difficult to automate. In this paper are described solutions these issues.

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  • Using rough sets to study expert behaviour in induction of labour

    Parry, David; Yeap, Wai Kiang; Pattison, Neil (1999-12)

    Working or discussion paper
    University of Otago

    The rate of induction of labour (IOL) is increasing, despite no obvious increase in the incidence of the major indications. However the rate varies widely between different centres and practitioners and this does not seem to be due to variations in patient populations. The IOL decision-making process of six clinicians was recorded and examined using hypothetical scenarios presented on a computer. Several rules were identified from a rough sets analysis of the data. These rules were compared to the actual practise of these clinicians in 1994 Initial tests of these rules show that they may form a suitable set for developing an expert system for the induction of labour.

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  • Automating iterative tasks with programming by demonstration: a user evaluation

    Paynter, Gordon W.; Witten, Ian H. (1999-05)

    Working or discussion paper
    University of Waikato

    Computer users often face iterative tasks that cannot be automated using the tools and aggregation techniques provided by their application program: they end up performing the iteration by hand, repeating user interface actions over and over again. We have implemented an agent, called Familiar, that can be taught to perform iterative tasks using programming by demonstration (PBD). Unlike other PBD systems, it is domain independent and works with unmodified, widely-used, applications in a popular operating system. In a formal evaluation, we found that users quickly learned to use the agent to automate iterative tasks. Generally, the participants preferred to use multiple selection where possible, but could and did use PBD in situations involving iteration over many commands, or when other techniques were unavailable.

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  • Using the Internet to teach health informatics

    Parry, David; Breton, Alice; Abernethy, David; Cockcroft, Sophie; Gillies, John (1999-12)

    Working or discussion paper
    University of Otago

    Since July 1998 we have been teaching an Internet-based distance learning course in health informatics. The development of this course and the experiences we have had running it are described in this paper. The course was delivered using paper materials, a face-to-face workshop, a CD-ROM and Internet communication tools. We currently have about 30 students around New Zealand, a mixture of physicians, nurses and other health staff. Some teaching methods have worked, some haven't, but in the process we have learned a number of valuable lessons.

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  • The development of an electronic distance learning course in health informatics

    Parry, David; Cockcroft, Sophie; Breton, Alice; Abernethy, David; Gillies, John (1999-12)

    Working or discussion paper
    University of Otago

    Since 1997 the authors have been involved in the development of a distance learning course in health informatics. The course is delivered via CD-ROM and the Internet. During this process we have learned valuable lessons about computer-assisted collaboration and cooperative work. In particular we have developed methods of using the software tools available for communication and education. We believe that electronic distance learning offers a realistic means of providing education in health informatics and other fields to students whom for reasons of geography or work commitments would not be able to participate in a conventional course.

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  • Spatial-temporal adaptation in evolving fuzzy neural networks for on-line adaptive phoneme recognition

    Kasabov, Nikola; Watts, Michael (1999-03)

    Working or discussion paper
    University of Otago

    Please note that this is a searchable PDF derived via optical character recognition (OCR) from the original source document. As the OCR process is never 100% perfect, there may be some discrepancies between the document image and the underlying text. Searching and selecting the text of this PDF may also not work in all viewers; for example, they have been found to not work in Apple's Preview application. We therefore recommend Adobe Reader for viewing and searching this PDF.

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  • Software forensics for discriminating between program authors using case-based reasoning, feed-forward neural networks and multiple discriminant analysis

    MacDonell, Stephen; Gray, Andrew; MacLennan, Grant; Sallis, Philip (1999-06)

    Working or discussion paper
    University of Otago

    Software forensics is a research field that, by treating pieces of program source code as linguistically and stylistically analyzable entities, attempts to investigate aspects of computer program authorship. This can be performed with the goal of identification, discrimination, or characterization of authors. In this paper we extract a set of 26 standard authorship metrics from 351 programs by 7 different authors. The use of feed-forward neural networks, multiple discriminant analysis, and case-based reasoning is then investigated in terms of classification accuracy for the authors on both training and testing samples. The first two techniques produce remarkably similar results, with the best results coming from the case-based reasoning models. All techniques have high prediction accuracy rates, supporting the feasibility of the task of discriminating program authors based on source-code measurements.

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  • A practical guide to GMM (with applications to option pricing)

    Arnold, Tom; Crack, Timothy (1999-10)

    Working or discussion paper
    University of Otago

    The full text of this document is only available from the Social Science Research Network. Please use the related link to access the full text.

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  • The NZDIS project: An agent-based distributed information systems architecture

    Purvis, Martin; Cranefield, Stephen; Bush, Geoff; Carter, Dan; McKinlay, Bryce; Nowostawski, Mariusz; Ward, Roy (1999-08)

    Working or discussion paper
    University of Otago

    This paper describes an architecture for building distributed information systems from existing information resources, based on distributed object and software agent technologies. This architecture is being developed as part of the New Zealand Distributed Information Systems (NZDIS) project. An agent-based architecture is used: information sources are encapsulated as information agents that accept messages in an agent communication language (the FIPA ACL). A user agent assists users to browse ontologies appropriate to their domain of interest and to construct queries based on terms from one or more ontologies. One or more query processing agents are then responsible for discovering (from a resource broker agent) which data source agents are relevant to the query, decomposing the query into subqueries suitable for those agents (including the translation of the query into the specific ontologies implemented by those agents), executing the subqueries and translating and combining the subquery results into the desired result set. Novel features of this system include the use of standards from the object-oriented community such as the Common Object Request Broker Architecture (CORBA) (as a communications infrastructure), the Unified Modeling Language (used as an ontology representation language), the Object Data Management Group's Object Query Language (used for queries) and the Object Management Group's Meta Object Facility (used as the basis for an ontology repository agent). Query results need not be returned within an ACL message, but may instead be represented by a CORBA object reference which may be used to obtain the result set.

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  • Software metrics data analysis—Exploring the relative performance of some commonly used modeling techniques

    Gray, Andrew; MacDonell, Stephen (1999-06)

    Working or discussion paper
    University of Otago

    Whilst some software measurement research has been unquestionably successful, other research has struggled to enable expected advances in project and process management. Contributing to this lack of advancement has been the incidence of inappropriate or non-optimal application of various model-building procedures. This obviously raises questions over the validity and reliability of any results obtained as well as the conclusions that may have been drawn regarding the appropriateness of the techniques in question. In this paper we investigate the influence of various data set characteristics and the purpose of analysis on the effectiveness of four model-building techniques---three statistical methods and one neural network method. In order to illustrate the impact of data set characteristics, three separate data sets, drawn from the literature, are used in this analysis. In terms of predictive accuracy, it is shown that no one modeling method is best in every case. Some consideration of the characteristics of data sets should therefore occur before analysis begins, so that the most appropriate modeling method is then used. Moreover, issues other than predictive accuracy may have a significant influence on the selection of model-building methods. These issues are also addressed here and a series of guidelines for selecting among and implementing these and other modeling techniques is discussed.

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  • A distributed architecture for environmental information systems

    Purvis, Martin; Cranefield, Stephen; Nowostawski, Mariusz (1999-04)

    Working or discussion paper
    University of Otago

    The increasing availability and variety of large environmental data sets is opening new opportunities for data mining and useful cross-referencing of disparate environmental data sets distributed over a network. In order to take advantage of these opportunities, environmental information systems will need to operate effectively in a distributed, open environment. In this paper, we describe the New Zealand Distributed Information System (NZDIS) software architecture for environmental information systems. In order to optimise extensibility, openness, and flexible query processing, the architecture is organised into collaborating software agents that communicate by means of a standard declarative agent communication language. The metadata of environmental data sources are stored as part of agent ontologies, which represent information models of the domain of the data repository. The agents and the associated ontological framework are designed as much as possible to take advantage of standard object-oriented technology, such as CORBA, UML, and OQL, in order to enhance the openness and accessibility of the system.

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  • Automated scoring of practical tests in an introductory course in information technology

    Kennedy, Geoffrey (1999-09)

    Working or discussion paper
    University of Otago

    In an introductory course in information technology at the University of Otago the acquisition of practical skills is considered to be a prime objective. An effective way of assessing the achievement of this objective is by means of a `practical test', in which students are required to accomplish simple tasks in a controlled environment. The assessment of such work demands a high level of expertise, is very labour intensive and can suffer from marker inconsistency, particularly with large candidatures. This paper describes the results of a trial in which the efforts of one thousand students in a practical test of word processing were scored by means of a program written in MediaTalk. Details of the procedure are given, including sampling strategies for the purpose of validation and examples of problems that were encountered. It was concluded that the approach was useful, and once properly validated gave rise to considerable savings in the time and effort.

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  • Evolving connectionist systems for on-line, knowledge-based learning: Principles and applications

    Kasabov, Nikola (1999-03)

    Working or discussion paper
    University of Otago

    The paper introduces evolving connectionist systems (ECOS) as an effective approach to building on-line, adaptive intelligent systems. ECOS evolve through incremental, hybrid (supervised/unsupervised), on-line learning. They can accommodate new input data, including new features, new classes, etc. through local element tuning. New connections and new neurons are created during the operation of the system. The ECOS framework is presented and illustrated on a particular type of evolving neural networks---evolving fuzzy neural networks (EFuNNs). EFuNNs can learn spatial-temporal sequences in an adaptive way, through one pass learning. Rules can be inserted and extracted at any time of the system operation. The characteristics of ECOS and EFuNNs are illustrated on several case studies that include: adaptive pattern classification; adaptive, phoneme-based spoken language recognition; adaptive dynamic time-series prediction; intelligent agents.

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  • Assessing prediction systems

    Kitchenham, Barbara; MacDonell, Stephen; Pickard, Lesley; Shepperd, Martin (1999-06)

    Working or discussion paper
    University of Otago

    For some years software engineers have been attempting to develop useful prediction systems to estimate such attributes as the effort to develop a piece of software and the likely number of defects. Typically, prediction systems are proposed and then subjected to empirical evaluation. Claims are then made with regard to the quality of the prediction systems. A wide variety of prediction quality indicators have been suggested in the literature. Unfortunately, we believe that a somewhat confusing state of affairs prevails and that this impedes research progress. This paper aims to provide the research community with a better understanding of the meaning of, and relationship between, these indicators. We critically review twelve different approaches by considering them as descriptors of the residual variable. We demonstrate that the two most popular indicators MMRE and pred(25) are in fact indicators of the spread and shape respectively of prediction accuracy where prediction accuracy is the ratio of estimate to actual (or actual to estimate). Next we highlight the impact of the choice of indicator by comparing three prediction systems derived using four different simulated datasets. We demonstrate that the results of such a comparison depend upon the choice of indicator, the analysis technique, and the nature of the dataset used to derive the predictive model. We conclude that prediction systems cannot be characterised by a single summary statistic. We suggest that we need indicators of the central tendency and spread of accuracy as well as indicators of shape and bias. For this reason, boxplots of relative error or residuals are useful alternatives to simple summary metrics.

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  • Factors systematically associated with errors in subjective estimates of software development effort: The stability of expert judgment

    Gray, Andrew; MacDonell, Stephen; Shepperd, Martin (1999-06)

    Working or discussion paper
    University of Otago

    Software metric-based estimation of project development effort is most often performed by expert judgment rather than by using an empirically derived model (although such may be used by the expert to assist their decision). One question that can be asked about these estimates is how stable are they with respect to characteristics of the development process and product? This stability can be assessed in relation to the degree to which the project has advanced over time, the type of module for which the estimate is being made, and the characteristics of that module. In this paper we examine a set of expert-derived estimates for the effort required to develop a collection of modules from a large health-care system. Statistical tests are used to identify relationships between the type (screen or report) and characteristics of modules and the likelihood of the associated development effort being under-estimated, approximately correct, or over-estimated. Distinct relationships are found that suggest that the estimation process being examined was not unbiased to such characteristics.

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  • Fuzzy logic for software metric models throughout the development life-cycle

    Gray, Andrew; MacDonell, Stephen (1999-09)

    Working or discussion paper
    University of Otago

    One problem faced by managers who are using project management models is the elicitation of numerical inputs. Obtaining these with any degree of confidence early in a project is not always feasible. Related to this difficulty is the risk of precisely specified outputs from models leading to overcommitment. These problems can be seen as the collective failure of software measurements to represent the inherent uncertainties in managers' knowledge of the development products, resources, and processes. It is proposed that fuzzy logic techniques can help to overcome some of these difficulties by representing the imprecision in inputs and outputs, as well as providing a more expert-knowledge based approach to model building. The use of fuzzy logic for project management however should not be the same throughout the development life cycle. Different levels of available information and desired precision suggest that it can be used differently depending on the current phase, although a single model can be used for consistency.

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