Open Theses and Dissertations
Permanent URI for this collection
This collection is the result of a joint project between the Faculty of Graduate Studies and Libraries and Cultural Resources which provides Graduate students with the opportunity to archive their thesis with University Archives in our digital repository.
If you are a Graduate student submitting your final thesis to PRISM, please ensure you have read and submitted all required documents: http://grad.ucalgary.ca/current/thesis
If you require assistance submitting your thesis please contact thesis@ucalgary.ca
The electronic theses and dissertations on this site are for the personal use of students, scholars and the public. Any commercial use, publication or lending of them in libraries is strictly prohibited.
Browse
Browsing Open Theses and Dissertations by Department "Computer Science"
Now showing 1 - 20 of 416
Results Per Page
Sort Options
Item Open Access 3D Design Review Systems in Immersive Environments(2023-09-21) Addam, Omar Khodr; Maurer, Frank O; Willett, Wesley; Jacob, Christian J; El-Hacha, Raafat; Irani, Pourang PoladDesign reviews play a crucial role in the development process, ensuring the quality and effectiveness of designs in various industries. However, traditional design review methods face challenges in effectively understanding and communicating complex 3D models. Immersive technologies, particularly Head-Mounted Displays (HMDs), offer new opportunities to enhance the design review process. In this thesis, we investigate using immersive environments, specifically HMDs, for 3D design reviews. We begin with a systematic literature review to understand the current state of employing HMDs in industry for design reviews. As part of this review, we utilize a detailed taxonomy from the literature to categorize and analyze existing approaches. Additionally, we present four iterations of an immersive design review system developed during my industry experience. Two of these iterations are evaluated through case studies involving domain experts, including engineers, designers, and clients. A formal semi-structured focus group is conducted to gain further insights into traditional design review practices. The outcomes of these evaluations and the focus group discussions are thoroughly discussed. Based on the literature review and the focus group findings, we uncover a new challenge associated with using HMDs in immersive design reviews—asynchronous and remote collaboration. Unlike traditional design reviews, where participants view the same section on a shared screen, HMDs allow independent exploration of areas of interest, leading to a shift from synchronous to asynchronous communication. Consequently, important feedback may be missed as the lead designer disconnects from the users' perspectives. To address this challenge, we collaborate with a domain expert to develop a prototype that utilizes heatmap visualization to display 3D gaze data distribution. This prototype enables lead designers to quickly identify areas of review and missed regions. The study incorporates the Design Critique approach and provides valuable insights into different heatmap visualization variants (top view projection, object-based, and volume-based). Furthermore, a list of well-defined requirements is outlined for future spatio-temporal visualization applications aimed at integrating into existing workflows. Overall, this thesis contributes to the understanding and improvement of immersive design review systems, particularly in the context of utilizing HMDs. It offers insights into the current state of employing HMDs for design reviews, utilizes a taxonomy from the literature to analyze existing approaches, highlights challenges associated with asynchronous collaboration, and proposes a prototype solution with heatmap visualization to address the identified challenge.Item Open Access 3D Geological Modeling from Concept Sketches and Annotations(2017) Mendonça Amorim, Ronan; Costa Sousa, Mário; Famil Samavati, Faramarz; Eaton, David W. S.; Sharlin, Ehud; Katz, Larry; Mould, DavidDuring the early stages of any design project, specialists explore and refine ideas collaboratively by constructing conceptual models through hand-drawn sketches and renderings. The resulting models are then used to make decisions before moving to the detailed design phase of development. Sketch-Based Interfaces and Modeling (SBIM) is an area of research devoted to the development of computational tools to aid in this prototyping process. The main goal of SBIM is to construct models directly from hand-drawn sketches, leveraging the sketching skills of experts in different domains such as art, science, and engineering. In this thesis, I investigate the theory and practice of concept sketching applied to the problem of constructing conceptual models of geological structures describing subsurface environments. Geological models describe the disposition, geometry, and types of rocks in the subsurface, and are critical to a wide range of applications, such as oil/gas exploration. Current subsurface modeling workflows lack more interpretive and interactive modeling tools, which could enable experts to rapidly construct a variety of digital conceptual geological models directly from their interpretation sketches. In this thesis, I am addressing fundamental research in SBIM motivated by the challenges of constructing conceptual geological models from 2D hand-drawn sketches. This thesis explores the use of SBIM to complement existing geological modeling tools with more interpretive and interactive methods, with the goal of expediting the construction of concept geological structures described at the early stages of subsurface modeling. To this end, two new SBIM methods are proposed: (1) Geo-Editor aims to enable experts to more easily and rapidly edit/augment existing geological surfaces, using sketches directly in 3D with/without geological data. (2) Geo-Sketcher complements the previous approach by allowing the rapid construction of conceptual geological models from a blank-screen environment using rule-based SBIM. It leverages the standard language provided by geological and topographic maps to provide experts with a familiar notation for sketching. The results and feedback from domain experts demonstrate that the proposed methods can significantly reduce the time necessary to create or edit 3D geological models.Item Open Access A 3D Multiscale Model of Chemotaxis in Bacteria(2015-07-09) Wu, Andrew; Jacob, ChristianWe present a multiscale 3D model of a colony of \ecoli\ bacteria. We simulate four distinct yet computationally interconnected levels. Each level represents a layer of detail with each level getting progressively more complex. We present a multiscale 3D model of a colony of \ecoli\ bacteria. We simulate four distinct yet computationally interconnected levels. In the first and second level, we simulate chemical diffusion in the environment to capture the colony population’s chemotactic behaviour. The bacterium interact with a discrete grid which models diffusion of chemicals. The first level presents this population behaviour in the form of a colour gradient, and proceeding to the second level we present the behaviour as particles. The third level, the chemotactic motions of the individual bacterium is presented. And in the fourth level, the cellular processes that drive the chemotactic behaviour is presented. We show four interconnected model layers that capture the biological processes from the colony layer down to the level of interacting molecules. The aim of this work is to construct a platform that enhances understanding of natural life by serving as a valuable educational tool. Moving into the third level a single bacterium cell is presented in the simulation. In this third level, the chemotactic motions of the individual cell is presented. In the fourth level, we present the cellular processes that drive the chemotactic behaviour. Implementation of the cellular process is comprised of the two key chemotactic pathway responses: excitation and adaptation. Together the two responses regulate the motor and influence the movement of the bacterium through the agar medium. We show four interconnected model layers that capture the biological processes from the colony layer down to the level of interacting molecules. The simulation's visual effects, interactivity and biological relevance are the foundations of this thesis. The aim of this work is to construct a platform that enhances understanding of natural life by serving as a valuable educational tool.Item Open Access A Computational Study of Tree Architecture(2013-01-18) Palubicki, Wojtek; Prusinkiewicz, PrzemyslawSince their inception in the 1970s, architectural tree models (Hallé et al. 1978) have provided the dominant framework for describing tree forms. An architectural tree model is viewed as a “genetic blueprint” of tree development: a precise developmental pattern subject to disruptive modifications by the environment (Hallé et al. 1978, p. 74): Organization in plants reflects the precisely controlled genetic program, which determines their development. [...] This program is disrupted by exogenous, environmental factors.” On the basis of extensive field data, Halle, Oldeman and Tomlinson distinguished 23 such programs and postulated that they capture the diversity of trees observed in nature. An alternative perspective of tree form was proposed by Sachs and Novoplansky (1995). They viewed environmentally-mediated interactions – in particular, competition between buds and branches for light and space – not merely as a modifier, but as a key determinant of tree form. According to their perspective, genetic and molecular mechanisms do not define tree forms directly, but only set up the rules for tree self-organization through competition between branches (Sachs and Novoplansky 1995): “The form of a tree is generated by self-organization in which alternative branches compete with one another, following no strict plan or pre-pattern.” In spite of the apparent dichotomy between both views, Sachs and Novoplansky postulated that architectural models and self-organization have a complementary character and the diversity of tree forms in nature results from an interplay between them. Here in this thesis I examine the concepts of architectural models, self-organization, and their synthesis in light of computer models implementing these paradigms. In particular, among the results is presented a theoretical morphospace constructed by only a small number of model parameters that captures major characteristics of most of the architectural models. Hallé, F., Oldeman, R. A., & Tomlinson, P. B. (1978). Tropical trees and forests. Berlin: Springer-Verlag. Sachs, T., & Novoplansky, A. (1995). Tree from: Architectural models do not suffice. Israel Journal of Plant Sciences 43, 203–212.Item Open Access A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images(2024-04-29) Graham, Benjamin; Jacob, Christian; Alim, Usman; Zhao, Richard; Garcia Flores, Julio; Hoyer, PeterImage registration is used in many medical image analysis applications, such as tracking the motion of tissue in cardiac images, where cardiac kinematics can be an indicator of tissue health. Registration is a challenging problem for deep learning algorithms because ground truth transformations are not feasible to create, and because there are potentially multiple transformations that can produce images that appear correlated with the goal. Unsupervised methods have been proposed to learn to predict effective transformations, but these methods take significantly longer to predict than established baseline methods. For a deep learning method to see adoption in wider research and clinical settings, it should be designed to run in a reasonable time on common, mid-level hardware. Fast methods have been proposed for the task of image registration but often use patch-based methods which can affect registration accuracy for a highly dynamic organ such as the heart. In this thesis, a fast, volumetric registration model is proposed for the use of quantifying cardiac strain. The proposed Deep Learning Neural Network (DLNN) is designed to utilize an architecture that can com-pute convolutions incredibly efficiently, allowing the model to achieve registration fidelity similar to other state-of-the-art models while taking a fraction of the time to perform inference. The proposed fast and lightweight registration (FLIR) model is used to predict tissue motion which is then used to quantify the non-uniform strain experienced by the tissue. For acquisitions taken from the same patient at approximately the same time, it would be expected that strain values measured between the acquisitions would have very small differences. Using this metric, strain values computed using the FLIR method are shown to be very consistent.Item Open Access A Demographic-driven Peer-Assisted CDN for Sharing User-Generated Media Content(2017) Rougeau, Bradley; Wang, Mea; Tang, Tony; Alim, Usman; Wang, MeaInternet traffic is increasingly dominated by user-generated content, predominantly by multimedia content (photos and videos). The content is primarily shared in online social networks (OSNs) such as Pinterest, Twitter, and Facebook. In this thesis, we are interested in studying the traffic imposed by user-generated multimedia content in OSNs and exploring the potential of involving end-user devices for more efficient delivery of user-generated media content. To do so, we developed Viewcount, a Facebook application, to collect traces of user-generated multimedia traffic. Through analyzing social activities around user-generated multimedia content (such as user demographics and viewing distributions), we drew insightful observations correlating demographics and social activities to network traffic. These observations shed light on the design of DEPA, a demographic-driven peer-assisted content delivery network (CDN) to reduce redundant network traffic and workload on the OSN servers. In contrast to existing attempts towards peer-assisted OSNs, DEPA adapts existing OSN architecture and introduces various demographic-driven caching schemes. Through a trace-driven simulator, we evaluated DEPA in both the Viewcount network and on OSNs with different demographic properties. DEPA provided a significant reduction of traffic on the OSN servers even with very small caches on our peer-assistants. Furthermore, the demographic caching algorithm in DEPA is more adaptive to dynamic changes of user online status in OSNs.Item Open Access A Graph Based Approach for Making Recommendations Based on Multiple Data Sources(2015-05-27) Dhaliwal, Sukhpreet; Alhajj, Reda; Rokne, JonRecommendation system is an information filtering system that predicts customer preferences. Customer preferences are extracted through analyzing the behaviour patterns of customers from multiple data sources. Graph-based models play an important role in recommendation systems to extract the customer preferences from multiple data sources. However, graph-based models have been rarely used in traditional recommendation systems. The main objective of this thesis is to use a graph-based recommender system that uses multiple data sources. A graph-based hybrid recommender model is developed to integrate content-based, collaborative filtering and association rule mining techniques. Moreover, the PageRank algorithm is used to produce a ranked list of recommendation. Our analysis on a Retail store dataset shows the impact of using multiple data sources on the accuracy of a recommender system while handling the sparsity problem. Usage of demographic information of customers remedies the cold start problem. Grouping the products based on product type produced better results and it also showed the impact of using the different level of product taxonomy. Additionally, assembling content-based, collaborative filtering and association rule mining also showed many improvements in results. Moreover, indirect connections improve the coverage of our recommender system.Item Open Access A Heuristic Stock Portfolio Optimization Approach Based on Data Mining Techniques(2013-03-11) Koochakzadeh, Negar; Alhajj, RedaPortfolio optimization is the process of making investment decisions on holding a set of financial assets to meet various criteria. A variety of investment assets around the world make this multi-faceted decision problem very complicated. Econometric and statistical models as well as machine learning and data mining techniques have been used by many researchers and analysts to propose heuristic solutions for portfolio optimization. However, a literature review shows that the existing models are still not practical as they do not always perform better than even the naïve strategy of investing in all available assets in the market. The methodology proposed in this thesis is an alternative heuristic solution to help investors make stock investment decisions through a semi-automated process. The proposed solution is based on the fact that the investment decision cannot be fully automated because investors’ preferences that are the key factors in making investment decision, vary among different people. For this purpose, a semi-automated framework called SMPOpt (Stock Market Portfolio Optimizer) has been designed and implemented. In the proposed framework, the goal is to learn from the historical fundamental analysis of companies to discover the optimum portfolio by considering investors’ preferences. The Portfolio optimization problem is formulated and broken down into steps to be able to apply data mining techniques such as Clustering and Ranking, and Social Network Analysis. Some of these techniques are customized based on the temporal behaviour of financial datasets. For instance, the ranking algorithm based on Support Vector Machine (SVMRank) is modified and a new algorithm called Time- Series SVMRank is proposed. A comprehensive experimental study has been conducted using the real stock exchange market datasets from the past recent decades to evaluate the proposed portfolio optimization solution. The obtained results confirmed the strength of the proposed methodology.Item Open Access A Hybrid Release Planning Method for Accommodating Advanced Feature Dependencies(2012-10-03) Przepiora, Mark Richard; Ruhe, Günther; Høyer, PeterSoftware release planning addresses the problem of assigning features to future releases in consideration of technological and resource constraints. Modeling the interdependencies of a feature set is vital to the success of release planning, as dependencies can drastically alter the landscape of which plans are feasible as well as which plans maximize the value of a release. This thesis addresses the problem of efficiently and effectively accommodating feature dependencies in the context of software release planning. A decision support framework for modeling arbitrary feature dependencies, called Hybrid-RP, is proposed and implemented, together with an algorithm for computing high-quality release plans that are consistent with the modeled dependencies. Our method, based on the paradigm of Constraint Programming, is proven to model a much larger spectrum of dependencies than existing release planning methods can. An initial evaluation of the method is conducted using real-world software feature sets containing up to 914 features.Item Open Access A Hybrid Search Method for Evolutionary Dynamic Optimization of the 3-dimensional Personnel Assignment Problem and its Case Study Evaluation at The City of Calgary(2016-01-18) Niknafs, Arash; Ruhe, Guenther; Jacob, Christian; Kremer, RobEvolutionary dynamic optimization is receiving more attention as it continues to deliver value in more application areas. In this thesis, an evolutionary dynamic optimization method for solving both static and dynamic personnel assignment optimization problems is proposed. This evolutionary method is based on the idea of genetic algorithms. Starting with the static scenario, I build an evolutionary algorithm that utilizes two variations of an OR-tree-based search method in generating the initial population and offspring. I then use the evolutionary algorithm for the static scenario as a framework into which I integrate two new strategies for tackling dynamism in the problem. In this thesis, I focus on the type of changes that require getting new (i.e. up-to-date) solutions as fast as possible right after the change. This type of changes has many applications in areas such as aircraft landing and take-off scheduling and mobile wireless network routing. Motivated by a real-world problem (at the City of Calgary), I focus on the changes in the availability of personnel in personnel assignment problems. I have two proposed solution approaches to the dynamism which utilize OR-tree-based search features and epigenetics mechanisms (both inside the evolutionary algorithm). Three additional strategies for tackling other types of changes are also presented. In this research, multidimensionality and dynamism are for the first time brought together into the personnel assignment problem. Using both real-world data (for the case study) and synthetic data (for additional evaluation) in the experiments, the experimental results prove the usefulness and responsiveness of my proposed solution approaches. Moreover, the feedback from the domain experts and higher level management in the case study show a strong preference for using my system and its outputs over the current practice. The case study took place in the Waste and Recycling Services business unit at the City of Calgary in Alberta, Canada. The synthetic data was generated based on the real-world data.Item Open Access A Methodology for Analyzing Cost and Cost-Drivers of Technical Software Documentation(2012-09-06) Sun, Bo; Ruhe, Günther; Garousi, VahidSoftware documentation is an important impact factor to achieve high software maintainability, especially for those large-scale complex changing legacy systems. The question: “how much documentation is enough”, is concerned by organizations who are turning their software process to agile development that claims “just enough” documentation. It is therefore important to be able to understand the cost of documentation activities, and what are the underlying cost-drivers, in order to monitor, control and improve documentation practice. However, there is a general lack of such studies dedicated for software documentation cost and cost-drivers. To address this need, a systematic methodology is proposed to analyze cost and cost-drivers of technical software documentation. The methodology primarily consists of the definition of documentation cost and cost-driver metrics, mining software repositories with tool support for automatic measurements, and cost-driver analysis. The main contributions of this thesis are to provide a practical way to understand documentation cost from the perspectives of single document, one documentation type and each author, and to identify underlying cost-drivers towards documentation process improvement. Results from an initial validation from an industrial case study at NovAtel, a leading provider for a comprehensive line of Global Navigation Satellite System (GNSS) products, are reported.Item Open Access A MULTIMODAL BIOMETRIC SYSTEM BASED ON RANK LEVEL FUSION(2013-01-07) MONWAR, MD. MARUF; Gavrilova, MarinaIn recent years, biometric based security systems achieved more attention due to continuous terrorism threats around the world. However, a security system comprised of a single form of biometric information cannot fulfill users’ expectations and may suffer from noisy sensor data, intra and inter class variations and continuous spoof attacks. To overcome some of these problems, multimodal biometric aims at increasing the reliability of biometric systems through utilizing more than one biometric in decision-making process. In order to take full advantage of the multimodal approaches, an effective fusion scheme is necessary for combining information from various sources. Such information can be integrated at several distinct levels, such as sensor level, feature level, match score level, rank level and decision level. In this doctoral research, I present a new methodology based on fusion at the rank level, which is a relatively new approach compared to others, to combine multimodal biometric information from three biometric identifiers (face, ear and iris). I investigate different rank fusion methods, such as highest rank, Borda count and logistic regression. I introduce a novel rank fusion algorithm based on Markov chain which significantly increases the recognition performance of the multimodal biometric system, can handle partial ranking lists, and satisfies the Condorcet criteria essential for fair ranking process. In order to increase the processing speed and to obtain the level of confidence of recognition outcomes of the multimodal biometric system, I further employ fuzzy logic based fusion for biometric authentication. The fuzzy fusion method is based on fuzzy logic and uses match score and rank information of the multimodal biometric system. The experiment results tested within different multimodal biometric database framework show superiority of the proposed approaches to other biometric information fusion methods. The developed system can be effectively used by security and intelligence services for controlling access to prohibited areas and protecting important national or public information.Item Open Access A Novel Approach to White-Box Policy Analysis(2013-01-25) Balasubramaniam, Jayalakshmi; Fong, Philip Wai LeungThe access control systems in dynamic environments contain composite access control policies, that combine decisions from multiple component policies using policy combining algorithms. In such dynamic environments, analysis of policies is a challenge. In this thesis, I propose a white-box policy analysis Decision in Context (DIC), that would analyse component policies situated inside a composite policy. For generality, the DIC query is defined in an XACML-style policy composition framework. The DIC query is implemented via a reduction to either propositional satisfiability or pseudo boolean satisfiability instances, after which standard solvers can be invoked to complete the evaluation. Empirical analyses have been conducted to compare the relative efficiency of the SAT and PBS encodings. The latter is found to be the more effective encoding, in reducing DIC queries containing majority voting policy combining algorithms.Item Open Access A Phase-Entrained Particle Filter for Human Motion Synchronization(2015-09-17) Manikashani, Peyman; Boyd, Jeffrey EdwinHumans have a specialized ability to synchronize their movements with a perceived auditory feedback. The association between human locomotion and sound feedback is especially profound when the movement has a periodic nature and the feedback is rhythmic. Dancing or marching with rhythmic music are examples of such association. This thesis presents a human motion feedback system capable of generating rhythmic auditory feedback synchronized to a periodic movement. We demonstrate the synchronization in the context of an everyday, yet complex example of human locomotion: normal walking gait. Our system relies on visual measurements provided by a conventional RGB camera and utilizes a phase-entrained particle filter to synchronize an oscillator with a subject's movement in real-time. A long-term prospect of this research is that rhythmic sonic feedback in sync with walking gaits has potential to be used in therapeutic applications for clinical treatment of gait disorders.Item Open Access A Study of the Multiple-Unicast Network Coding Conjecture Using Riemannian Manifolds(2016) Fang, Wei; Li, Zongpeng; Hoyer, Peter Christian; Niu, DiNetwork coding encourages information mixing at the intermediate nodes within a network. The multiple-unicast conjecture proposed by Li and Li [18] in 2004 is one of the most well-known unsolved problems in network coding field. The conjecture asserts that, for multiple independent unicast transmissions in an undirected network, network coding has no advantage over traditional routing. In this thesis, we study the conjecture by embedding graphs into Riemannian manifolds using a geometric framework developed by Xiahou el al. [32]. We prove that isometric embedding of graphs into a Riemannian manifold is impossible. Then, interestingly, we construct an embedding that achieves an infinitesimally small distortion. We show that if the multiple-unicast network coding conjecture is true on Riemannian manifolds, it is also true for undirected networks. Our hope is to develop a Riemannian geometry approach for making new progresses against the long-time open conjecture.Item Open Access A Study on Energy-Efficiency in Multimedia Streaming(2013-11-19) Liu, Yongxin; Wang, MeaThe increasing demand for multimedia content imposes a heavy workload on the content sources and routers, leading to high energy bills. Among many works towards greening the Internet, very little attention has been paid to make the entire multimedia streaming system energy-efficient, from source to end-users. In this thesis, we perform an energy measurement of the entire multimedia streaming system, and conclude that the energy usage is affected by the session size, the underlay network setting, and network infrastructure. Based on the measurement, we propose E2Stream, an application-layer approach to make the multimedia streaming energy-efficient. Our evaluation results show that E2Stream is effective in reducing system-wide work-induced power, and is flexible in adapting to various network infrastructures and existing systems.Item Open Access A View-Based Protection Model to Prevent Inference Attacks by Third-Party Extensions to Social Computing Platforms(2016-01-18) Ahmadinejad, Seyed Hossein; Fong, Philip W. L.; Fong, Philip W. L.; Safavi-Naini, Reihaneh; Locasto, Michael E.; Bauer, Mark; Debbabi, MouradThe recent significant growth in popularity of Social Network Systems (SNSs) raised serious concerns regarding user privacy. One of such concerns, called inference attacks, is the leakage of users' private information from their public information. This dissertation identifies a more dangerous type of inference attacks where users' private information is inferred by third-party extensions to SNS platforms. SNSs provide an Application Programming Interface (API) that could be used by third-party applications to access SNS user profiles, and in return provide some functionality for the users. Systematic inference of user inaccessible information by third-party extensions from the information accessible through the SNS APIs is called SNS API inference attacks. Due to the large number of users who subscribe to third-party extensions, even with a meager success rate, SNS API inference attacks could violate the privacy of millions of users. Moreover, SNS API inference attacks could be used as a building block for further security attacks (e.g., identification attacks). This work first evaluate the feasibility of SNS API inference attacks by conducting an experiment where sample inference algorithms will be developed and executed against enough number of real user profiles and then their success rate will be assessed. Next, a view-based protection model will be proposed for the purpose of preventing SNS API inference attacks. This model allows users to share a sanitized version of their profiles with extensions. Sanitizing transformations must be designed to preserve both privacy and usefulness of the user profiles. The proposed model has a theoretical framework that defines measures to evaluate the effectiveness of sanitizing transformations. The theoretical framework will be paired with an enforcement model to show how transformations can actually be designed and sanitize user profiles. The enforcement model will include a declarative language for articulating transformations. Moreover, the enforcement model will have a model of computation that can describe transformations and access queries. The proposed model of computation has enough expressive power and meets the required properties. Finally, the proposed model will be evaluated by assessing the correctness of the theoretical framework and the enforcement model.Item Open Access A Visual Interaction Cue Framework from Video Game Environments for Augmented Reality(2018-09-18) Dillman, Kody R.; Tang, Tony C. T.; Wong, Nelson; Willett, Wesley J.Based on an analysis of 49 popular contemporary video games, I develop a descriptive framework of visual interaction cues in video games. These cues are used to inform players what can be interacted with, where to look, and where to go within the game world. These cues vary along three dimensions: the purpose of the cue, the visual design of the cue, and the circumstances under which the cue is shown. I demonstrate that this framework can also be used to describe interaction cues for augmented reality applications. Beyond this, I show how the framework can be used to generatively derive new design ideas for visual interaction cues in augmented reality experiences and use the framework as a guide to create three novel AR prototypes. Finally, I suggest design considerations for the creation of visual interaction cues for augmented reality and examine how the framework might be employed in future work.Item Open Access Abstraction Mechanisms Towards Large-Scale Agent-Based Simulations(2013-10-02) Sarraf Shirazi, Abbas; Jacob, ChristianThe typically large degrees of interaction in agent-based simulations come at considerable computational costs. In this thesis, we propose an abstraction framework to reduce the run-time of the simulations by learning recurring patterns. We employ machine learning techniques to abstract groups of agents or their behaviours to cut down computational complexity, while preserving the inherent flexibility of agent-based models. The learned abstractions, which subsume the underlying model agents' interactions, are constantly tested for their validity---after all, the dynamics of a system may change over time to such an extent that previously learned patterns would not reoccur. An invalid abstraction is, therefore, removed from the simulation. The creation and removal of abstractions continues throughout the course of a simulation in order to ensure an adequate adaptation to the system dynamics. Experimental results on biological agent-based simulations show that our proposed framework can successfully boost the simulation speed while maintaining the freedom of arbitrary interactions.Item Open Access ACM: Atlas of Connectivity Maps(2015-05-05) Mahdavi-Amiri, Ali; Samavati, FaramarzSemiregular models are an important subset of the graphical models used in computer graphics. They are typically obtained by applying repetitive regular refinements on an initial arbitrary model and, as a result, their connectivity exhibits a high degree of regularity. Although data structures exist for regular or irregular models, a data structure designed to take advantage of this semiregularity is desirable. We introduce such a data structure called the atlas of connectivity maps (ACM), which efficiently represents semiregular models resulting from various types of refinements. This atlas maps the connectivity information of vertices and faces onto separate 2D domains called connectivity maps, and handles connectivity queries within each connectivity map using simple algebraic operations or between connectivity maps using a set of linear transformations. We demonstrate the effectiveness of ACM for use in subdivision, multiresolution, and Digital Earth applications. In addition, the generality of ACM has been examined on a variety of face-types (e.g. triangles, hexagons, quads) as well as uniform and adaptive refinements. We compare the performance of ACM to various data structures including the standard half-edge, and show that the performance of ACM is better than these available data structures in supporting important queries such as neighborhood finding and hierarchical traversal.