A survey of outlier detection methodologies

Outlier detection has been used for centuries to detect and, where appropriate, remove anomalous observations from data. Outliers arise due to mechanical faults, changes in system behaviour, fraudulent behaviour, human error, instrument error or simply through natural deviations in populations. Their detection can identify system faults and fraud before they escalate with potentially catastrophic consequences. It can identify errors and remove their contaminating effect on the data set and as such to purify the data for processing. The original outlier detection methods were arbitrary but now, principled and systematic techniques are used, drawn from the full gamut of Computer Science and Statistics. In this paper, we introduce a survey of contemporary techniques for outlier detection. We identify their respective motivations and distinguish their advantages and disadvantages in a comparative review

Modeling of evolving textures using granulometries

This chapter describes a statistical approach to classification of dynamic texture images, called parallel evolution functions (PEFs). Traditional classification methods predict texture class membership using comparisons with a finite set of predefined texture classes and identify the closest class. However, where texture images arise from a dynamic texture evolving over time, estimation of a time state in a continuous evolutionary process is required instead. The PEF approach does this using regression modeling techniques to predict time state. It is a flexible approach which may be based on any suitable image features. Many textures are well suited to a morphological analysis and the PEF approach uses image texture features derived from a granulometric analysis of the image. The method is illustrated using both simulated images of Boolean processes and real images of corrosion. The PEF approach has particular advantages for training sets containing limited numbers of observations, which is the case in many real world industrial inspection scenarios and for which other methods can fail or perform badly. [41] G.W. Horgan, Mathematical morphology for analysing soil structure from images, European Journal of Soil Science, vol. 49, pp. 161–173, 1998. [42] G.W. Horgan, C.A. Reid and C.A. Glasbey, Biological image processing and enhancement, Image Processing and Analysis, A Practical Approach, R. Baldock and J. Graham, eds., Oxford University Press, Oxford, UK, pp. 37–67, 2000. [43] B.B. Hubbard, The World According to Wavelets: The Story of a Mathematical Technique in the Making, A.K. Peters Ltd., Wellesley, MA, 1995. [44] H. Iversen and T. Lonnestad. An evaluation of stochastic models for analysis and synthesis of gray-scale texture, Pattern Recognition Letters, vol. 15, pp. 575–585, 1994. [45] A.K. Jain and F. Farrokhnia, Unsupervised texture segmentation using Gabor filters, Pattern Recognition, vol. 24(12), pp. 1167–1186, 1991. [46] T. Jossang and F. Feder, The fractal characterization of rough surfaces, Physica Scripta, vol. T44, pp. 9–14, 1992. [47] A.K. Katsaggelos and T. Chun-Jen, Iterative image restoration, Handbook of Image and Video Processing, A. Bovik, ed., Academic Press, London, pp. 208–209, 2000. [48] M. K¨oppen, C.H. Nowack and G. R¨osel, Pareto-morphology for color image processing, Proceedings of SCIA99, 11th Scandinavian Conference on Image Analysis 1, Kangerlussuaq, Greenland, pp. 195–202, 1999. [49] S. Krishnamachari and R. Chellappa, Multiresolution Gauss-Markov random field models for texture segmentation, IEEE Transactions on Image Processing, vol. 6(2), pp. 251–267, 1997. [50] T. Kurita and N. Otsu, Texture classification by higher order local autocorrelation features, Proceedings of ACCV93, Asian Conference on Computer Vision, Osaka, pp. 175–178, 1993. [51] S.T. Kyvelidis, L. Lykouropoulos and N. Kouloumbi, Digital system for detecting, classifying, and fast retrieving corrosion generated defects, Journal of Coatings Technology, vol. 73(915), pp. 67–73, 2001. [52] Y. Liu, T. Zhao and J. Zhang, Learning multispectral texture features for cervical cancer detection, Proceedings of 2002 IEEE International Symposium on Biomedical Imaging: Macro to Nano, pp. 169–172, 2002. [53] G. McGunnigle and M.J. Chantler, Modeling deposition of surface texture, Electronics Letters, vol. 37(12), pp. 749–750, 2001. [54] J. McKenzie, S. Marshall, A.J. Gray and E.R. Dougherty, Morphological texture analysis using the texture evolution function, International Journal of Pattern Recognition and Artificial Intelligence, vol. 17(2), pp. 167–185, 2003. [55] J. McKenzie, Classification of dynamically evolving textures using evolution functions, Ph.D. Thesis, University of Strathclyde, UK, 2004. [56] S.G. Mallat, Multiresolution approximations and wavelet orthonormal bases of L2(R), Transactions of the American Mathematical Society, vol. 315, pp. 69–87, 1989. [57] S.G. Mallat, A theory for multiresolution signal decomposition: the wavelet representation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 11, pp. 674–693, 1989. [58] B.S. Manjunath and W.Y. Ma, Texture features for browsing and retrieval of image data, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, pp. 837–842, 1996. [59] B.S. Manjunath, G.M. Haley and W.Y. Ma, Multiband techniques for texture classification and segmentation, Handbook of Image and Video Processing, A. Bovik, ed., Academic Press, London, pp. 367–381, 2000. [60] G. Matheron, Random Sets and Integral Geometry, Wiley Series in Probability and Mathematical Statistics, John Wiley and Sons, New York, 1975

Software development management using metamodels and activity networks

This thesis develops the concept, management and control of metamodels for the management of software development projects. Metamodels provide a more flexible approach for managing and controlling the software engineering process and are based on the integration of several software development paradigms. Generalised Activity Networks are used to provide the more powerful planning techniques required for managing metamodels. In this thesis, both new node logics, that clarify previous work in this field, and Generalised Activity-on-the-Arrow and Generalised Activity-on-the-Node representations are developed and defined. Activity-on-the-Node representations reflect the current mood of the project management industry and allow constraints to be applied directly to logical dependencies between activities. The Generalised Activity Networks defined within this thesis can be used as tools to manage risks and uncertainties in both software developments and general engineering projects. They reflect the variation and uncertainties in projects more realistically and improve the planning and scheduling of such projects. [Continues.

The development of a structured methodology for the construction and integrity control of spreadsheet models

Numerous studies and reported cases have established the seriousness of the frequency and impact of user-generated spreadsheet errors. This thesis presents a structured methodology for spreadsheet model development, which enables improved integrity control of the models. The proposed methodology has the potential to ensure consistency in the development process and produce more comprehensible, reliable and maintainable models, which can reduce the occurrence of user-generated errors. An insight into the nature and properties of spreadsheet errors is essential for the development of a methodology for controlling the integrity of spreadsheet models. An important by-product of the research is the development of a comprehensive classification or taxonomy of the different types of user-generated spreadsheet errors based on a rational taxonomic scheme. Research on the phenomenon of spreadsheet errors has revealed the need to adopt a software engineering based methodology as a framework for spreadsheet development in practical situations. The proposed methodology represents a new approach to the provision of a structured, software engineering based discipline for the development of spreadsheet models. It is established in this thesis that software engineering principles can in fact be applied to the process of spreadsheet model building to help improve the quality of the models. The methodology uses Jackson structures to produce the logical design of the spreadsheet model. This is followed by a technique to derive the physical model, which is then implemented as a spreadsheet. The methodology’s potential for improving the quality of spreadsheet models is demonstrated. In order to evaluate the effectiveness of the proposed framework, the various features of the proposed structured methodology are tested on a range of spreadsheet models through a series of experiments. The results of the tests provide adequate evidence of the methodology’s potential to reduce the occurrence of user-generated errors and enhance the comprehensibility of the models

Exploring ‘events’ as an information systems research methodology

This paper builds upon existing research and commentary from a variety of disciplinary sources including Information Systems, Organisational and Management Studies, and the Social Sciences that focus upon the meaning, significance and impact of ‘events’ in both an organisational and a social sense. The aim of this paper is to define how the examination of the event is an appropriate, viable and useful Information Systems methodology. Our argument is that focusing on the ‘event’ enables the researcher to more clearly observe and capture the complexity, multiplicity and mundaneity of everyday lived experience. The use and notion of ‘event’ has the potential to reduce the methodological dilemmas associated with the micromanagement of the research process – an inherent danger of traditional and ‘virtual' ethnographic approaches. Similarly, this paper addresses the over-emphasis upon managerialist, structured and time-fixated praxis that is currently symptomatic of Information Systems research. All of these concerns are pivotal points of critique found within eventoriented literature. An examination of event-related theory within interpretative disciplines directs the focus of this paper towards the more specific realm of the ‘event scene’. The notion of the ‘event scene’ originated in the action based (and anti-academy) imperatives of the Situationists and emerged in an academic sense as critical situational analysis. Event scenes are a focus for contemporary critical theory where they are utilised as a means of representing theoried inquiry in order to loosen the restrictions that historical and temporally bound analysis imposes upon most interpretative approaches. The use of event scenes as the framework for critiquing established conceptual assumptions is exemplified by their use in CTheory. In this journal's version and articulation of the event scene poetry, commentary, multi-vocal narrative and other techniques are legitimated as academic forms. These various forms of multi-dimensional expression are drawn upon to enrich the understandings of the ‘event’, to extricate its meaning and to provide a sense of the moment from which the point of analysis stems. The objective of this paper is to advocate how Information Systems research can (or should) utilize an event scene oriented methodology