Computing and Information Systems - Theses

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    Practical declarative debugging of mercury programs
    MacLarty, Ian Douglas. (University of Melbourne, 2006)
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    Practical declarative debugging of mercury programs
    MacLarty, Ian Douglas. (University of Melbourne, 2006)
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    A multistage computer model of picture scanning, image understanding, and environment analysis, guided by research into human and primate visual systems
    Rogers, T. J. (University of Melbourne, Faculty of Engineering,, 1983)
    This paper describes the design and some testing of a computational model of picture scanning and image understanding (TRIPS), which outputs a description of the scene in a subset of English. This model can be extended to control the analysis of a three dimensional environment and changes of the viewing system's position within that environment. The model design is guided by a summary of neurophysiological, psychological, and psychophysical observations and theories concerning visual perception in humans and other primates, with an emphasis on eye movements. These results indicate that lower level visual information is processed in parallel in a spatial representation while higher level processing is mostly sequential, using a symbolic, post iconic, representation. The emphasis in this paper is on simulating the cognitive aspects of eye movement control and the higher level post iconic representation of images. The design incorporates several subsystems. The highest level control module is described in detail, since computer models Of eye movement which use cognitively guided saccade selection are not common. For other modules, the interfaces with the whole system and the internal computations required are out lined, as existing image processing techniques can be applied to perform these computations. Control is based on a production . system, which uses an "hypothesising" system - a simplified probabilistic associative production system - to determine which production to apply. A framework for an image analysis language (TRIAL), based on "THINGS". and "RELATIONS" is presented, with algorithms described in detail for the matching procedure and the transformations of size, orientation, position, and so On. TRIAL expressions in the productions are used to generate "cognitive expectations" concerning future eye movements and their effects which can influence the control of the system. Models of low level feature extraction, with parallel processing of iconic representations have been common in computer vision literature, as are techniques for image manipulation and syntactic and statistical analysis� Parallel and serial systems have also been extensively investigated. This model proposes an integration Of these approaches using each technique in the domain to which it is suited. The model proposed for the inferotemporal cortex could be also suitable as a model of the posterior parietal cortex. A restricted version of the picture scanning model (TRIPS) has been implemented, which demonstrates the consistency of the model and also exhibits some behavioural characteristics qualitatively similar to primate visual systems. A TRIAL language is shown to be a useful representation for the analysis and description of scenes. key words: simulation, eye movements, computer vision systems, inferotemporal, parietal, image representation, TRIPS, TRIAL.
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    Digital forensics: increasing the evidential weight of system activity logs
    AHMAD, ATIF ( 2007)
    The application of investigative techniques within digital environments has lead to the emergence of a new field of specialization that may be termed ‘digital forensics’. Perhaps the primary challenge concerning digital forensic investigations is how to preserve evidence of system activity given the volatility of digital environments and the delay between the time of the incident and the start of the forensic investigation. This thesis hypothesizes that system activity logs present in modern operating systems may be used for digital forensic evidence collection. This is particularly true in modern organizations where there is growing recognition that forensic readiness may have considerable benefits in case of future litigation. An investigation into the weighting of evidence produced by system activity logs present in modern operating systems takes place in this thesis. The term ‘evidential weight’ is used loosely as a measure of the suitability of system activity logs to digital forensic investigations. This investigation is approached from an analytical perspective. The first contribution of this thesis is to determine the evidence collection capability of system activity logs by a simple model of the logging mechanism. The second contribution is the development of evidential weighting criteria that can be applied to system activity logs. A unique and critical role for system activity logs by which they establish the reliability of other kinds of computer-derived evidence from hard disk media is also identified. The primary contribution of this thesis is the identification of a comprehensive range of forensic weighting issues arising from the use of log evidence that concern investigators and legal authorities. This contribution is made in a comprehensive analytical discussion utilizing both the logging model and the evidential weighting criteria. The practical usefulness of the resulting evidential weighting framework is demonstrated by rigorous and systematic application to a real-world logging system.
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    Strategic information security policy quality assessment: a multiple constituency perspective
    MAYNARD, SEAN ( 2010)
    An integral part of any information security management program is the information security policy. The purpose of an information security policy is to define the means by which organisations protect the confidentiality, integrity and availability of information and its supporting infrastructure from a range of security threats. The tenet of this thesis is that the quality of information security policy is inadequately addressed by organisations. Further, although information security policies may undergo multiple revisions as part of a process development lifecycle and, as a result, may generally improve in quality, a more explicit systematic and comprehensive process of quality improvement is required. A key assertion of this research is that a comprehensive assessment of information security policy requires the involvement of the multiple stakeholders in organisations that derive benefit from the directives of the information security policy. Therefore, this dissertation used a multiple-constituency approach to investigate how security policy quality can be addressed in organisations, given the existence of multiple stakeholders. The formal research question under investigation was: How can multiple constituency quality assessment be used to improve strategic information security policy? The primary contribution of this thesis to the Information Systems field of knowledge is the development of a model: the Strategic Information Security Policy Quality Model. This model comprises three components: a comprehensive model of quality components, a model of stakeholder involvement and a model for security policy development. The strategic information security policy quality model gives a holistic perspective to organisations to enable management of the security policy quality assessment process. This research contributes six main contributions as stated below:  This research has demonstrated that a multiple constituency approach is effective for information security policy assessment  This research has developed a set of quality components for information security policy quality assessment  This research has identified that efficiency of the security policy quality assessment process is critical for organisations  This research has formalised security policy quality assessment within policy development  This research has developed a strategic information security policy quality model  This research has identified improvements that can be made to the security policy development lifecycle The outcomes of this research contend that the security policy lifecycle can be improved by: enabling the identification of when different stakeholders should be involved, identifying those quality components that each of the different stakeholders should assess as part of the quality assessment, and showing organisations which quality components to include or to ignore based on their individual circumstances. This leads to a higher quality information security policy, and should impact positively on an organisation’s information security.
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    Towards interpreting informal place descriptions
    Tytyk, Igor (The University of Melbourne, 2012)
    Informal place descriptions are human-generated descriptions of locations, ex- pressed by the means of natural language in an arbitrary fashion. The aim we pur- sued in this thesis is _nding methods for better automatic interpretation of situated informal place descriptions. This work presents a framework within which we attempt to automatically classify informal place descriptions for the accuracy of the location information they contain. Having an available corpus of informal place descriptions, we identified placenames contained therein and manually annotated them for properties such as geospatial granularity and identifiability. First, we make use of the annotations and a machine learning method to conduct the classification task, and then report the accuracy scores reaching 84%. Next, we classify the descriptions again, but instead of using the manual annotations we identify the properties of placenames automatically.
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    Extracting characteristics of human-produced video descriptions
    Korvas, Matěj ( 2012)
    This thesis contributes to the SMILE project, aiming for video understanding. We focus on the final stage of the project where information extracted from a video should be transformed into a natural language description. Working with a corpus of human-made video descriptions, we examine it to find patterns in the descriptions. We develop a machine-learning procedure for finding statistical dependencies between linguistic features of the descriptions. Evaluating its results when run on a small sample of data, we conclude that it can be successfully extended to larger datasets. e method is generally applicable for finding dependencies in data, and extends methods for association rule mining for the option to specify distributions of features. We show future directions which, if followed, will lead to extracting a specification of common sentence patterns of video descriptions. This would allow for generating naturally sounding descriptions from the video understanding software.
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    Understanding the business benefits of ERP system use
    Staehr, Lorraine Jean ( 2006)
    ERP systems are large, complex, integrated software packages used for business transaction processing by thousands of major organizations worldwide. Yet outcomes from ERP system implementation and use can be very different, and current understanding of how and why such variation exists is limited. Since most studies of ERP systems to date have focused on ERP implementation, this research focused on the post-implementation period. The aim was to better understand the 'what', 'how' and 'why' of achieving business benefits from ERP systems during ERP use. Achieving business benefits from ERP systems was considered as a process of organizational change occurring over time within various societal and organizational contexts. A retrospective, interpretive case study approach was used to study this process. The post-implementation periods of four Australian manufacturing organizations that had implemented ERP systems were studied. This study makes three important contributions to the information systems research literature. First, a new framework was developed to explain 'how' and 'why' business benefits were achieved from ERP systems. This explanatory framework is theoretically based and is firmly grounded in the empirical data. Three types of themes, along with the interrelationships between them, were identified as influencing the business benefits achieved from ERP systems. The first group of themes, the process themes, are 'Education, training and support', 'Technochange management' and 'People resources'. The second group of themes, the outcome themes, are 'Efficient and effective use of the ERP system', 'Business process improvement' and 'New projects to leverage off the ERP system'. The third group of themes, the contextual themes, are the 'External context', the 'Internal context' and the 'ERP planning and implementation phases'. This new framework makes a significant contribution to understanding how and why some organizations achieve more business benefits from ERP systems than others. Second, the case studies provide a rich description of four manufacturing organizations that have implemented and used ERP systems. Examining the 'what' of business benefits from ERP systems in these four manufacturing organizations resulted in a confirmed, amended and improved Shang and Seddon (2000) ERP business benefits framework. This replication and extension of previous research is the third contribution of this study. The results of this research are of interest not only to information systems researchers, but also to information systems practitioners and senior management in organizations that either plan to, or have implemented ERP systems. Overall this research provides an improved understanding of business benefits from ERP systems and a sound foundation for future studies of ERP system use.
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    Hierarchical clustering and summarization of network traffic data
    Mahmood, Abdun Naser ( 2008)
    An important task in managing IP networks is understanding the different types of traffic that are utilizing a network, based on a given trace of the packets or flows in the network. One of the key challenges in this task is the volume and complexity of the data that is available in traffic traces. What is needed by network managers in this context is a concise report of the significant traffic patterns that are present in the network. In this thesis, we address the problem of how to generate a succinct traffic report that contains a set of aggregated traffic flows, such that each aggregate flow corresponds to a significant traffic pattern in the network. We view the problem of generating a report of the significant traffic patterns in a network as a form of clustering problem. In particular, some distance-based hierarchical clustering techniques have advantages in terms of scalability when analyzing the types of large traffic traces that arise in this context. However, there are several important problems that need to be addressed before we can effectively use these types of clustering techniques on network traffic traces. The first research problem we address is how to handle non-numeric attributes that appear in network traffic data, such as attributes with a categorical or hierarchical structure. We have proposed a hierarchical similarity measure that is suitable for comparing hierarchical attributes in network traffic data. We have then developed a one-pass, hierarchical clustering scheme that can exploit the structure of hierarchical attributes in combination with categorical and numerical attributes. We demonstrate that our clustering scheme achieves significant improvements in both accuracy and execution time on a standard benchmark dataset, compared to an existing approach based on frequent itemset clustering. The second research problem we address is how to improve the scalability of our hierarchical clustering scheme when computing resources are limited. We propose an adaptive, two-stage sampling technique, which controls the rate at which records from frequently seen patterns are received by our clustering scheme. This enables more computational resources to be allocated to clustering new or unusual traffic patterns. We demonstrate that our two-stage sampling technique can identify less frequent traffic patterns with greater accuracy than when traditional systematic sampling is used. The third research problem we address is how to generate a concise yet accurate summary report from the results of our hierarchical clustering. We present two approaches to summarization, based on the size and the homogeneity of the clusters in the hierarchical cluster tree. We demonstrate that these approaches to summarization can substantially reduce the final report size with little impact on the accuracy of the report.
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    Statistical modeling of multiword expressions
    Su, Kim Nam ( 2008)
    In natural languages, words can occur in single units called simplex words or in a group of simplex words that function as a single unit, called multiword expressions (MWEs). Although MWEs are similar to simplex words in their syntax and semantics, they pose their own sets of challenges (Sag et al. 2002). MWEs are arguably one of the biggest roadblocks in computational linguistics due to the bewildering range of syntactic, semantic, pragmatic and statistical idiomaticity they are associated with, and their high productivity. In addition, the large numbers in which they occur demand specialized handling. Moreover, dealing with MWEs has a broad range of applications, from syntactic disambiguation to semantic analysis in natural language processing (NLP) (Wacholder and Song 2003; Piao et al. 2003; Baldwin et al. 2004; Venkatapathy and Joshi 2006). Our goals in this research are: to use computational techniques to shed light on the underlying linguistic processes giving rise to MWEs across constructions and languages; to generalize existing techniques by abstracting away from individual MWE types; and finally to exemplify the utility of MWE interpretation within general NLP tasks. In this thesis, we target English MWEs due to resource availability. In particular, we focus on noun compounds (NCs) and verb-particle constructions (VPCs) due to their high productivity and frequency. Challenges in processing noun compounds are: (1) interpreting the semantic relation (SR) that represents the underlying connection between the head noun and modifier(s); (2) resolving syntactic ambiguity in NCs comprising three or more terms; and (3) analyzing the impact of word sense on noun compound interpretation. Our basic approach to interpreting NCs relies on the semantic similarity of the NC components using firstly a nearest-neighbor method (Chapter 5), then verb semantics based on the observation that it is often an underlying verb that relates the nouns in NCs (Chapter 6), and finally semantic variation within NC sense collocations, in combination with bootstrapping (Chapter 7). Challenges in dealing with verb-particle constructions are: (1) identifying VPCs in raw text data (Chapter 8); and (2) modeling the semantic compositionality of VPCs (Chapter 5). We place particular focus on identifying VPCs in context, and measuring the compositionality of unseen VPCs in order to predict their meaning. Our primary approach to the identification task is to adapt localized context information derived from linguistic features of VPCs to distinguish between VPCs and simple verb-PP combinations. To measure the compositionality of VPCs, we use semantic similarity among VPCs by testing the semantic contribution of each component. Finally, we conclude the thesis with a chapter-by-chapter summary and outline of the findings of our work, suggestions of potential NLP applications, and a presentation of further research directions (Chapter 9).