Network Similarity Measures and Automatic Construction of Graph Models using Genetic Programming

A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.

(Re)writing the other/self : autoethnography in the transcultural arena of representation

Abstract: In Imperial Eyes Mary Louise Pratt (1992: 7, emphasis original) defines autoethnography as "instances in which colonized subjects undertake to represent themselves in ways that engage with the colonizer's own terms ... in response to or in dialogue with . . . metropolitan representations." Although Pratt's conceptualization of autoethnography has much to offer post-colonial studies, it has received little attention in the field. In this thesis, I interrogate Pratt's notion of autoethnography as a theoretical tool for understanding the self-representations of subordinate peoples within transcultural terrains of signification. I argue that autoethnography is a concept that allows us to move beyond some theoretical dualisms, and to recognize the (necessary) coexistence of subordinate peoples' simultaneous accommodation of and resistance to dominant representations of themselves. I suggest that even when autoethnographic expressions seem to rely on or to reproduce dominant knowledges, their very existence as speech acts implicitly resists dominant discourses which objectify members of oppressed populations and re-create them as Native Informants. I use Pratt's concept to analyze two books by Islamic feminist sociologist Fatima Memissi. Memissi's Dreams ofTrespass and Scheherazade Goes West illustrate the simultaneity of accommodation and disruption evident in autoethnographic communication. Across the two books, Memissi shows herself renegotiating the discourses which discipline her (and her speech). She switches back and forth between the positions of reader and author, demonstrates the reciprocity of the disciplinary gaze (she looks back at her dominants, reading their own reading of her representation of her social group), and provides a model of autoethnographic dialogue.

American Desi : representation and reproduction in diaspora /

This study explores ~ow South Asian diasporic film represents and reproduces South Asian identity in the diaspora. It commences with a review of the literature in cultural studies and post-colonial theory on identity in the diaspora. A textual analysis of three films: American Desi, Bollywood/Hollywood, and East Is East, helps frame the characteristics of South Asian diasporic film. Theoretical concepts of diaspora and identity are extended to this reading of the films. In-depth, open-ended, semi structured interviews were conducted with eight participants to test the validity of theoretical concepts through participants' own reading of American Desi. Findings indicate that while theoretical concepts of identity can be usefully applied at the level of the text, these perspectives do not always easily explain participants' interpretation of the film in relation to their everyday experiences.

Properties and algorithms of the hyper-star graph and its related graphs

The hyper-star interconnection network was proposed in 2002 to overcome the drawbacks of the hypercube and its variations concerning the network cost, which is defined by the product of the degree and the diameter. Some properties of the graph such as connectivity, symmetry properties, embedding properties have been studied by other researchers, routing and broadcasting algorithms have also been designed. This thesis studies the hyper-star graph from both the topological and algorithmic point of view. For the topological properties, we try to establish relationships between hyper-star graphs with other known graphs. We also give a formal equation for the surface area of the graph. Another topological property we are interested in is the Hamiltonicity problem of this graph. For the algorithms, we design an all-port broadcasting algorithm and a single-port neighbourhood broadcasting algorithm for the regular form of the hyper-star graphs. These algorithms are both optimal time-wise. Furthermore, we prove that the folded hyper-star, a variation of the hyper-star, to be maixmally fault-tolerant.

Quadtree representation and compression of spatial data

Spatial data representation and compression has become a focus issue in computer graphics and image processing applications. Quadtrees, as one of hierarchical data structures, basing on the principle of recursive decomposition of space, always offer a compact and efficient representation of an image. For a given image, the choice of quadtree root node plays an important role in its quadtree representation and final data compression. The goal of this thesis is to present a heuristic algorithm for finding a root node of a region quadtree, which is able to reduce the number of leaf nodes when compared with the standard quadtree decomposition. The empirical results indicate that, this proposed algorithm has quadtree representation and data compression improvement when in comparison with the traditional method.

A Foucauldian Analysis of Power and Representation in an Attempt to Run a Photovoice Project with Youth

This project evolved out of a search for ways to conduct research on “others” in a way that does not exploit, stigmatize or misrepresent their experience. This thesis is an ethnographic study in leisure research and youth work and an experiment in running a photovoice project. Photovoice is a participatory visual method that embodies the emancipatory ideal of empowering others through self-representation. The literature on photovoice lacks a comprehensive discussion on the complexity of power and representation. Postmodern theorists have proposed that participatory methods are not benign and that initiatives are acts of power in themselves that produce effects (Cook & Kothari, 2001). A Foucauldian analysis of power is used to deconstruct the researcher’s practice and reflect on why and how youth are “engaged”. This project seeks to embrace the principle of working “with” others, but also work from a postmodern perspective that acknowledges power and representation as ongoing problems.

Automatic Inference of Graph Models for Complex Networks with Genetic Programming

Complex networks can arise naturally and spontaneously from all things that act as a part of a larger system. From the patterns of socialization between people to the way biological systems organize themselves, complex networks are ubiquitous, but are currently poorly understood. A number of algorithms, designed by humans, have been proposed to describe the organizational behaviour of real-world networks. Consequently, breakthroughs in genetics, medicine, epidemiology, neuroscience, telecommunications and the social sciences have recently resulted. The algorithms, called graph models, represent significant human effort. Deriving accurate graph models is non-trivial, time-intensive, challenging and may only yield useful results for very specific phenomena. An automated approach can greatly reduce the human effort required and if effective, provide a valuable tool for understanding the large decentralized systems of interrelated things around us. To the best of the author's knowledge this thesis proposes the first method for the automatic inference of graph models for complex networks with varied properties, with and without community structure. Furthermore, to the best of the author's knowledge it is the first application of genetic programming for the automatic inference of graph models. The system and methodology was tested against benchmark data, and was shown to be capable of reproducing close approximations to well-known algorithms designed by humans. Furthermore, when used to infer a model for real biological data the resulting model was more representative than models currently used in the literature.

Object-Oriented Genetic Programming for the Automatic Inference of Graph Models for Complex Networks

Complex networks are systems of entities that are interconnected through meaningful relationships. The result of the relations between entities forms a structure that has a statistical complexity that is not formed by random chance. In the study of complex networks, many graph models have been proposed to model the behaviours observed. However, constructing graph models manually is tedious and problematic. Many of the models proposed in the literature have been cited as having inaccuracies with respect to the complex networks they represent. However, recently, an approach that automates the inference of graph models was proposed by Bailey [10] The proposed methodology employs genetic programming (GP) to produce graph models that approximate various properties of an exemplary graph of a targeted complex network. However, there is a great deal already known about complex networks, in general, and often specific knowledge is held about the network being modelled. The knowledge, albeit incomplete, is important in constructing a graph model. However it is difficult to incorporate such knowledge using existing GP techniques. Thus, this thesis proposes a novel GP system which can incorporate incomplete expert knowledge that assists in the evolution of a graph model. Inspired by existing graph models, an abstract graph model was developed to serve as an embryo for inferring graph models of some complex networks. The GP system and abstract model were used to reproduce well-known graph models. The results indicated that the system was able to evolve models that produced networks that had structural similarities to the networks generated by the respective target models.

‘Designer Vaginas': The Representation of Female Genitals on Canadian Cosmetic Surgeons' Websites

This thesis critically examines the online marketing tactics of 10 (English language) Canadian cosmetic surgery clinics’ websites that offer Female Genital Cosmetic Surgery (FGCS), specifically, labiaplasty (labial reduction) and vaginoplasty (vaginal tightening). Drawing on a qualitative Multimodal Critical Discourse Analysis (MCDA) and a feminist-informed social constructionist framework (Lazar, 2007), I examine how FGCS discourses reiterate and reinforce heteronormative sexual scripts for women, and impose restrictive models of femininity through the pathologization of genital diversity and the appropriation of postfeminist and neoliberal discourses of individual choice and empowerment. I explore feminist analyses of the links between FGCS and contemporary Western women’s postfeminist subjectivity, and the reconfiguration of women’s sexual agency, to better understand what these contemporary shifts may mean for women’s sexual anxiety and expression. My analysis highlights several discourses that organize the online marketing material of Canadian FGCS websites, including: the pathologization of genital diversity; restrictive models of femininity; heteronormative sexual scripts; neoliberal and post-feminist rhetorics of individual choice and empowerment; and psychological and sexual transformation. Overall, these discourses undermine acceptance of women’s genital diversity, legitimize the FGCS industry and frame FGCS as the only viable solution to alleviate women’s genital and sexual distress despite the lack of evidence regarding the long-term benefits and risks of these procedures, and the recommendations against FGCS by professional medical organizations.