"Icon," "representation," and "virtuality," are key elements to consider when reading multi-modal narratives, including graphic narratives. By considering in detail how these elements are realized in various examples, the author shows how the study of the comics can lay groundwork for critical reading across the technological continuum of storytelling.The author looks at how icon, representation, and virtuality interact in a reading of William Hogarth's A Harlot's Progress. He then examines each term in more detail through readings of a variety of graphic narratives including Max Ernst's, Une Semaine de Bonte, Winsor McCay's Little Nemo in Slumberland, Kurt Vonnegut's Breakfast of Champions, Craig Thompson's Blankets, Phoebe Gloeckner's Diary of a Teenage Girl, and Posy Simmonds's Gemma Bovery. The author distinguishes between two types of virtuality, internal and external, and ties the construction of virtuality to reader response theory. In exploring issues related to the icon, the author builds on Scott McCloud's conjecture that the iconic character is the means through which the reader inhabits the virtual space of the graphic story. The author advances the proposition that icons are metonymies and that graphic narratives are centered in metonymic, not metaphoric devices. He also undertakes a discussion of how icon operates within the expanding tradition of the "illustrated novel." Throughout the dissertation an attempt is made to express observation and analysis through continuous instead of binary descriptors in order to emphasize the cooperative rather than oppositional arrangements of word and image within the graphic narrative.The dissertation concludes with an extended examination of Will Eisner's contention that the use of stereotype is a necessity in graphic storytelling. Examples from Frederik Strömberg's Black Images in the Comics are used to test this theory and illustrate its consequences. The treatise finishes with an analysis of approaches to representation that avoid stereotypical treatment, are inclusive but sufficiently flexible to operate through caricature..These observations are applied to issues of characterization and representation in electronic gaming narrative. The author concludes that ethics, effectiveness, reputation and empathy are all compromised when artists resort to stereotypes.

Sub-pixel image alignment estimation is desirable for co-registration of objects in multiple images to a common spatial reference and as alignment input to multi-image processing. Applications include super-resolution, image fusion, change detection, object tracking, object recognition, video motion tracking, and forensics.Information theoretical measures are commonly used for co-registration in medical imaging. The published methods apply Shannon's Entropy to the Joint Measurement Space (JMS) of two images. This work introduces into the same context a new set of statistical divergence measures derived from Fisher Information. The new methods described in this work are applicable to uncorrelated imagery and imagery that becomes statistically least dependent upon co-alignment. Both characteristics occur with multi-modal imagery and cause cross-correlation methods, as well as maximum dependence indicators, to fail. Fisher Information-based estimators, together as a set with an Entropic estimator, provide substantially independent information about alignment. This increases the statistical degrees of freedom, allowing for precision improvement and for reduced estimator failure rates compared to Entropic estimator performance alone.The new Fisher Information methods are tested for performance on real remotely-sensed imagery that includes Landsat TM multispectral imagery and ESR SAR imagery, as well as randomly generated synthetic imagery. On real imagery, the co-registration cost function is qualitatively examined for features that reveal the correct point of alignment. The alignment estimates agree with manual alignment to within manual alignment precision. Alignment truth in synthetic imagery is used to quantitatively evaluate co-registration accuracy. The results from the new Fisher Information-based algorithms are compared to Entropy-based Mutual Information and correlation methods revealing equal or superior precision and lower failure rate at signal-to-noise ratios below one.

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Digital media storytelling and the creation of narrative texts using digital technology is an emerging social process that is being utilized by social workers as a means of engaging in critical reflection. As an emerging practice, little is known about the contributions that these texts make to critical social work knowledge; to this end this thesis considers social worker's use of digital media storytelling as a tool for resisting and remembering and as a tool for critical reflection about their changing field. Six digital media stories are considered in this thesis. The texts are deconstructed using multi-modal analysis informed by internet/digital media research scholarship. The layers produced through this deconstruction are crystalized using critical discourse, narrative and metaphor analysis in order to develop a complex understanding of the multi-modal and multi-vocal meaning making processes inherent in these stories. The analysis reveals the way in which discourses and themes present in the contemporary context of social work practice such as neo-liberalism, managerialism and professionalization, are brought to life in the narratives produced by the social workers, who each tell their stories using different genres, from unique points of view, based on their individual subjective positions. The findings point to the significance of digital media storytelling as an important resources for knowledge production and knowledge dissemination. The analysis further points to the significance of connections between and among these texts as demonstrating the tensions and contradictions that are produced through the workers’ attempts to bring to life the social justice values, goals and objectives of social work to which they are committed in a social climate that is increasingly hostile to such approaches to human service work.

Digital media storytelling and the creation of narrative texts using digital technology is an emerging social process that is being utilized by social workers as a means of engaging in critical reflection. As an emerging practice, little is known about the contributions that these texts make to critical social work knowledge; to this end this thesis considers social worker's use of digital media storytelling as a tool for resisting and remembering and as a tool for critical reflection about their changing field. Six digital media stories are considered in this thesis. The texts are deconstructed using multi-modal analysis informed by internet/digital media research scholarship. The layers produced through this deconstruction are crystalized using critical discourse, narrative and metaphor analysis in order to develop a complex understanding of the multi-modal and multi-vocal meaning making processes inherent in these stories. The analysis reveals the way in which discourses and themes present in the contemporary context of social work practice such as neo-liberalism, managerialism and professionalization, are brought to life in the narratives produced by the social workers, who each tell their stories using different genres, from unique points of view, based on their individual subjective positions. The findings point to the significance of digital media storytelling as an important resources for knowledge production and knowledge dissemination. The analysis further points to the significance of connections between and among these texts as demonstrating the tensions and contradictions that are produced through the workers’ attempts to bring to life the social justice values, goals and objectives of social work to which they are committed in a social climate that is increasingly hostile to such approaches to human service work.

This thesis introduces a new optimization algorithm for simulation-based design of systems with multi-modal, nonlinear, black box objective functions. The algorithm extends the recently introduced adaptive multi-modal optimization by incorporating surrogate modeling features similar to response surface methods (RSM). The resulting optimization algorithm has reduced computational intensity and is therefore well-suited for optimization of expensive black box objective functions. The algorithm relies on an adaptive and multi-resolution mesh to obtain an initial estimation of the objective function surface. Local surrogate models are then constructed to represent the objective function and to generate additional trial points in the vicinity of local minima discovered. The steps of mesh refinement and surrogate modeling continue until convergence criteria are met. An important property of this algorithm is that it produces progressively accurate surrogate models around the local minima; these models can be used for post-optimization studies such as sensitivity and tolerance analyses with minimal computational effort. This algorithm is suitable for optimal design of complex engineering systems and enhances the design cycle by enabling computationally affordable uncertainty analysis. The mathematical basis of the algorithm is explained in detail. The thesis also demonstrates the effectiveness of the algorithm using comparative optimization of several multi-modal objective functions. It also shows several practical applications of the algorithm in the design of complex power and power-electronic systems.

This thesis introduces a new optimization algorithm for simulation-based design of systems with multi-modal, nonlinear, black box objective functions. The algorithm extends the recently introduced adaptive multi-modal optimization by incorporating surrogate modeling features similar to response surface methods (RSM). The resulting optimization algorithm has reduced computational intensity and is therefore well-suited for optimization of expensive black box objective functions. The algorithm relies on an adaptive and multi-resolution mesh to obtain an initial estimation of the objective function surface. Local surrogate models are then constructed to represent the objective function and to generate additional trial points in the vicinity of local minima discovered. The steps of mesh refinement and surrogate modeling continue until convergence criteria are met. An important property of this algorithm is that it produces progressively accurate surrogate models around the local minima; these models can be used for post-optimization studies such as sensitivity and tolerance analyses with minimal computational effort. This algorithm is suitable for optimal design of complex engineering systems and enhances the design cycle by enabling computationally affordable uncertainty analysis. The mathematical basis of the algorithm is explained in detail. The thesis also demonstrates the effectiveness of the algorithm using comparative optimization of several multi-modal objective functions. It also shows several practical applications of the algorithm in the design of complex power and power-electronic systems.

This thesis describes the development of microfluidic (MF) platforms for the study of biological and chemical processes. In particular the thesis is divided into two distinct parts: (i) development of a MF methodology to generate tunable cell-laden microenvironments for detailed studies of cell behavior, and (ii) the design and fabrication of MF reactors for studies of chemical reactions. First, this thesis presented the generation of biopolymer microenvironments for cell studies. In the first project we demonstrated a high-throughput MF system for generating cell-laden agarose microgels with a controllable ratio of two different types of cells. The MF co-encapsulation system was shown to be a robust method for identifying autocrine and/or paracrine dependence of specific cell subpopulations. In the second project we studied the effect of the mechanical properties on the behavior of acute myeloid leukemia (AML2) cancer cells. Cell-laden macroscopic agarose gels were prepared at varying agarose concentrations. A modest range of the elastic modulus of the agarose gels were achieved, ranging from 0.62 kPa to 20.21 kPa at room temperature. We observed a pronounced decrease in cell proliferation in stiffer gels when compared to the gels with lower elastic moduli. The second part of the thesis focuses on the development of MF platforms for studying chemical reactions. In the third project presented in this thesis, we exploited the temperature dependent solubility of CO2 in order to: (i) study the temperature mediated CO2 transfer between the gas and the various liquid phases on short time scales, and (ii) to generate bubbles with a dense layer of colloid particles (armoured bubbles). The fourth project involved the fabrication of a multi-modal MF device with integrated analytical probes. The MF device comprised a pH, temperature, and ATR-FTIR probes for in-situ analysis of chemical reactions in real-time. Furthermore, the MF reactor featured a temperature controlled feedback system capable of maintaining on-chip temperatures at flow rates up to 50 mL/hr.

In order to leverage the use of various modalities such as audio-visual-touch in instilling learning behaviour, we present an intuitive approach of annotation based hapto-audio-visual interaction with the traditional digital learning materials such as eBooks. By integrating the traditional home entertainment system and respective media in the user's reading experience combined with haptic interfaces, we examine whether such augmentation of modalities influence the user's reading experience in terms of attention, entertainment and retention. The proposed Haptic E-Book (HE-Book) system leverages the haptic jacket, haptic arm band as well as haptic sofa interfaces to receive haptic emotive signals wirelessly in the form of patterned vibrations of the actuators and expresses the learning material by incorporating audio-video based augmentation in order to pave ways for intimate reading experience in the popular eBook platform. We have designed and developed desktop, mobile/tablet based HE-Book system as well as a semi-automated annotation authoring tool. Our system also supports multimedia based diverse quiz augmentations, which can help in learning tracking. We have conducted quantitative and qualitative tests using the developed prototype systems. We have adopted the indirect objective based performance analysis methodology, which is commonly used for multimedia based learning investigation. The user study shows that, there is a positive tendency of accepting multimodal interactions including haptics with traditional eBook reading experience. Though our limited number of laboratory tests reveal, that haptics can be an influencing media in eBook reading experience, but it requires large scale real life tests to provide a concluding remarks.

>Magister Scientiae - MSc / The recent years have seen an increase in the number of users accessing online services using communication devices such as computers, mobile phones and cards based credentials such as credit cards. This has prompted most governments and business organizations to change the way they do business and manage their identity information. The coming of the online services has however made most Internet users vulnerable to identity fraud and theft. This has resulted in a subsequent increase in the number of reported cases of identity theft and fraud, which is on the increase and costing the global industry excessive amounts. Today with more powerful and effective technologies such as artificial intelligence, wireless communication, mobile storage devices and biometrics, it should be possible to come up with a more effective multi-modal authentication system to help reduce the cases of identity fraud and theft. A multi-modal digital identity management system is proposed as a solution for managing digital identity information in an effort to reduce the cases of identity fraud and theft seen on most online services today. The proposed system thus uses technologies such as artificial intelligence and biometrics on the current unsecured networks to maintain the security and privacy of users and service providers in a transparent, reliable and efficient way. In order to be authenticated in the proposed multi-modal authentication system, a user is required to submit more than one credential attribute. An artificial intelligent technology is used to implement a technique of information fusion to combine the user’s credential attributes for optimum recognition. The information fusion engine is then used to implement the required multi-modal authentication system.