Computer Sciences Commons^™

Vascular Tree Structure: Fast Curvature Regularization And Validation, Egor Chesakov

Electronic Thesis and Dissertation Repository

This work addresses the challenging problem of accurate vessel structure analysis in high resolution 3D biomedical images. Typical segmentation methods fail on recent micro-CT data sets resolving near-capillary vessels due to limitations of standard first-order regularization models. While regularization is needed to address noise and partial volume issues in the data, we argue that extraction of thin tubular structures requires higher-order curvature-based regularization. There are no standard segmentation methods regularizing surface curvature in 3D that could be applied to large 3D volumes. However, we observe that standard measures for vessels structure are more concerned with topology, bifurcation angles, and other …

Bm3d Image Denoising Using Learning-Based Adaptive Hard Thresholding, Farhan Bashar

Electronic Thesis and Dissertation Repository

Image denoising is an important pre-processing step in most imaging applications. Block Matching and 3D Filtering (BM3D) is considered to be the current state-of-art algorithm for additive image denoising. But this algorithm uses a fixed hard thresholding scheme to attenuate noise from a 3D block. Experiments show that this fixed hard thresholding deteriorates the performance of BM3D because it does not consider the context of corresponding blocks. In this thesis, we propose a learning based adaptive hard thresholding method to solve this issue. Also, BM3D algorithm requires as an input the value of the noise level in the input image. …

Predicting Energy Demand Peak Using M5 Model Trees, Sara S. Abdelkader, Katarina Grolinger, Miriam Am Capretz

Electrical and Computer Engineering Publications

Predicting energy demand peak is a key factor for reducing energy demand and electricity bills for commercial customers. Features influencing energy demand are many and complex, such as occupant behaviours and temperature. Feature selection can decrease prediction model complexity without sacrificing performance. In this paper, features were selected based on their multiple linear regression correlation coefficients. This paper discusses the capabilities of M5 model trees in energy demand prediction for commercial buildings. M5 model trees are similar to regression trees; however they are more suitable for continuous prediction problems. The M5 model tree prediction was developed based on a selected …

Adaptive Non-Local Means Using Weight Thresholding, Asif Khan

Electronic Thesis and Dissertation Repository

Non-local means (NLM) is a popular image denoising scheme for reducing additive Gaussian noise. It uses a patch-based approach to find similar regions within a search neighborhood and estimate the denoised pixel based on the weighted average of all the pixels in the neighborhood. All the pixels are considered for averaging, irrespective of the value of their weights. This thesis proposes an improved variant of the original NLM scheme, called Weight Thresholded Non-Local Means (WTNLM), by thresholding the weights of the pixels within the search neighborhood, where the thresholded weights are used in the averaging step. The key parameters of …

Optical Flow At Occlusion Boundaries And In Occlusion Regions, Hua Meng

Electronic Thesis and Dissertation Repository

Optical flow is an important research area in the Computer Vision field, with the estimation of optical flow at occlusion still an open problem. Traditional approaches to this problem have either used additional terms in a regularization calculation (the flow still tends to “bleed” across occlusion boundaries) or a local least squares calculation that attempted to minimize the influence of two adjacent differently moving regions on the optical flow at points close to both regions (the flow still tends to be “corrupted” by the two regions). Ideally, optical flow for two adjacent differently moving regions should be distinct right up …

Surface Reconstruction From Noisy And Sparse Data, Mark A. Brophy

Electronic Thesis and Dissertation Repository

We introduce a set of algorithms for registering, filtering and measuring the similarity of unorganized 3d point clouds, usually obtained from multiple views.

We contribute a method for computing the similarity between point clouds that represent closed surfaces, specifically segmented tumors from CT scans. We obtain watertight surfaces and utilize volumetric overlap to determine similarity in a volumetric way. This similarity measure is used to quantify treatment variability based on target volume segmentation both prior to and following radiotherapy planning stages.

We also contribute an algorithm for the drift-free registration of thin, non- rigid scans, where drift is the build-up …

Energy Forecasting For Event Venues: Big Data And Prediction Accuracy, Katarina Grolinger, Alexandra L'Heureux, Miriam Am Capretz, Luke Seewald

Electrical and Computer Engineering Publications

Advances in sensor technologies and the proliferation of smart meters have resulted in an explosion of energy-related data sets. These Big Data have created opportunities for development of new energy services and a promise of better energy management and conservation. Sensor-based energy forecasting has been researched in the context of office buildings, schools, and residential buildings. This paper investigates sensor-based forecasting in the context of event-organizing venues, which present an especially difficult scenario due to large variations in consumption caused by the hosted events. Moreover, the significance of the data set size, specifically the impact of temporal granularity, on energy …

Management's Perspective On Critical Success Factors Affecting Mobile Learning In Higher Education Institutions - An Empirical Study, Muasaad Alrasheedi, Luiz Fernando Capretz, Arif Raza

Electrical and Computer Engineering Publications

Mobile learning (m-Learning) is considered to be one of the fastest growing learning platforms. The immense interest in m-Learning is attributed to the incredible rate of growth of mobile technology and its proliferation into every aspect of modern life. Despite this, m-Learning has not experienced a similar adoption rate in the education sector, chiefly higher education. Researchers have attempted to explain this anomaly by conducting several studies in the area. However, mostly the research in m-Learning is examined from the perspective of the students and educators. In this research, it is contended that there is a third important stakeholder group …

Students' Perspectives Of Mobile Learning Platforms: An Empirical Study, Muasaad Alrasheedi, Luiz Fernando Capretz, Arif Raza

Electrical and Computer Engineering Publications

Educational institutions are becoming involved in adopting technological innovations like th e mobile learning (m-Learning) platform for education. Mobile technologies are the next frontier as infrast ructure for m-Learning because they can provide high-quality learning capab ilities to satisfy the rising student demand for mobility and flexibility due to the ubiquitous nature of mobile tec hnology (smartphones) and the va st opportunities it offers, there ar e indications that smartphones could lead the next generation for learning platforms. Researchers have examin ed the idea from several angles and produced a copious amount of literature devoted to explaining the interrelationships of …

Mlaas: Machine Learning As A Service, Mauro Ribeiro, Katarina Grolinger, Miriam Am Capretz

Electrical and Computer Engineering Publications

The demand for knowledge extraction has been increasing. With the growing amount of data being generated by global data sources (e.g., social media and mobile apps) and the popularization of context-specific data (e.g., the Internet of Things), companies and researchers need to connect all these data and extract valuable information. Machine learning has been gaining much attention in data mining, leveraging the birth of new solutions. This paper proposes an architecture to create a flexible and scalable machine learning as a service. An open source solution was implemented and presented. As a case study, a forecast of electricity demand was …

Formal Models Of The Extension Activity Of Dna Polymerase Enzymes, Srujan Kumar Enaganti

Electronic Thesis and Dissertation Repository

The study of formal language operations inspired by enzymatic actions on DNA is part of ongoing efforts to provide a formal framework and rigorous treatment of DNA-based information and DNA-based computation. Other studies along these lines include theoretical explorations of splicing systems, insertion-deletion systems, substitution, hairpin extension, hairpin reduction, superposition, overlapping concatenation, conditional concatenation, contextual intra- and intermolecular recombinations, as well as template-guided recombination.

First, a formal language operation is proposed and investigated, inspired by the naturally occurring phenomenon of DNA primer extension by a DNA-template-directed DNA polymerase enzyme. Given two DNA strings u and v, where the shorter …

Empirical Investigation Of Key Business Factors For Digital Game Performance, Saiqa Aleem, Luiz Fernando Capretz, Faheem Ahmed

Electrical and Computer Engineering Publications

Game development is an interdisciplinary concept that embraces software engineering, business, management, and artistic disciplines. This research facilitates a better understanding of the business dimension of digital games. The main objective of this research is to investigate empirically the effect of business factors on the performance of digital games in the market and to answer the research questions asked in this study. Game development organizations are facing high pressure and competition in the digital game industry. Business has become a crucial dimension, especially for game development organizations. The main contribution of this paper is to investigate empirically the influence of …

Computing In Algebraic Closures Of Finite Fields, Javad Doliskani

Electronic Thesis and Dissertation Repository

We present algorithms to construct and perform computations in algebraic closures of finite fields. Inspired by algorithms for constructing irreducible polynomials, our approach for constructing closures consists of two phases; First, extension towers of prime power degree are built, and then they are glued together using composita techniques. To be able to move elements around in the closure we give efficient algorithms for computing isomorphisms and embeddings. In most cases, our algorithms which are based on polynomial arithmetic, rather than linear algebra, have quasi-linear complexity.

Implementation Techniques For The Truncated Fourier Transform, Li Zhang

Electronic Thesis and Dissertation Repository

We study various algorithms for the Truncated Fourier Transform (TFT) which is a variation of the Discrete Fourier Transform (DFT) that allows one to work with an input vector of arbitrary size without zero padding. After a review of the original algorithms for the forward and inverse TFT introduced by J. van der Hoeven, we consider the variation of D. Harvey as well as that of J. Johnson and L.C. Meng. Both variations are based on Cooley-Tukey like formulas. The former is called strict general radix as it strictly follows the specifications proposed by J. van der Hoeven, while the …

Clustering-Based Personalization, Seyed Nima Mirbakhsh

Electronic Thesis and Dissertation Repository

Recommendation systems have been the most emerging technology in the last decade as one of the key parts in e-commerce ecosystem. Businesses offer a wide variety of items and contents through different channels such as Internet, Smart TVs, Digital Screens, etc. The number of these items sometimes goes over millions for some businesses. Therefore, users can have trouble finding the products that they are looking for. Recommendation systems address this problem by providing powerful methods which enable users to filter through large information and product space based on their preferences. Moreover, users have different preferences. Thus, businesses can employ recommendation …

A Study Of Pseudo-Periodic And Pseudo-Bordered Words For Functions Beyond Identity And Involution, Manasi Kulkarni

Electronic Thesis and Dissertation Repository

Periodicity, primitivity and borderedness are some of the fundamental notions in combinatorics on words. Motivated by the Watson-Crick complementarity of DNA strands wherein a word (strand) over the DNA alphabet \{A, G, C, T\} and its Watson-Crick complement are informationally ``identical", these notions have been extended to consider pseudo-periodicity and pseudo-borderedness obtained by replacing the ``identity" function with ``pseudo-identity" functions (antimorphic involution in case of Watson-Crick complementarity). For a given alphabet $\Sigma$, an antimorphic involution $\theta$ is an antimorphism, i.e., $\theta(uv)=\theta(v) \theta(u)$ for all $u,v \in \Sigma^{*}$ and an involution, i.e., $\theta(\theta(u))=u$ for all $u \in \Sigma^{*}$. In this thesis, …

Generalized Inclusion-Exclusion, Mike W. Ghesquiere

Electronic Thesis and Dissertation Repository

Sets are a foundational structure within mathematics and are commonly used as a building block for more complex structures. Just above this we have functions and sequences before an explosion of increasingly specialized structures. We propose a re-hanging of the tree with hybrid sets (that is, signed multi-sets), as well hybrid functions (functions with hybrid set domains) joining the ranks of sequences and functions. More than just an aesthetic change, this allows symbolic manipulation of structures in ways that might otherwise be cumbersome or inefficient. In particular, we will consider simplifying the product and sum of two piecewise functions or …

Algorithms For Peptide Identification From Mixture Tandem Mass Spectra, Yi Liu

Electronic Thesis and Dissertation Repository

The large amount of data collected in an mass spectrometry experiment requires effective computational approaches for the automated analysis of those data. Though extensive research has been conducted for such purpose by the proteomics community, there are still remaining challenges, among which, one particular challenge is that the identification rate of the MS/MS spectra collected is rather low. One significant reason that contributes to this situation is the frequently observed mixture spectra, which result from the concurrent fragmentation of multiple precursors in a single MS/MS spectrum. However, nearly all the mainstream computational methods still take the assumption that the acquired …

Tropical Cyclone Wind Hazard Assessment For Southeast Part Of Coastal Region Of China, Sihan Li

Electronic Thesis and Dissertation Repository

Tropical cyclone (TC) or typhoon wind hazard and risk are significant for China. The return period value of the maximum typhoon wind speed is used to characterize the typhoon wind hazard and assign wind load in building design code. Since the historical surface observations of typhoon wind speed are often scarce and of short period, the typhoon wind hazard assessment is often carried out using the wind field model and TC track model. For a few major cities in the coastal region of mainland China, simple or approximated wind field models and a circular subregion method (CSM) have been used …

Generating Invalid Input Strings For Software Testing, Benjamin D. Revington

Electronic Thesis and Dissertation Repository

Grammar-based testing has interested the academic community for decades, but little work has been done with regards to testing with invalid input strings. For our research, we generated LR parse tables from grammars. We then generated valid and invalid strings based on coverage of these tables. We evaluated the effectiveness of these strings in terms of code coverage and fault detection by inputting them to subject programs which accept input based on the grammars. For a baseline, we then compared the effectiveness of these strings to a more general approach where the tokens making up each string are chosen randomly. …

In Need Of A Domain-Specific Language Modeling Notation For Smartphone Applications With Portable Capability, Hamza Ghandorh, Luiz Fernando Capretz Dr., Ali Bou Nassif Dr.

Electrical and Computer Engineering Publications

The rapid growth of the smartphone market and its increasing revenue has motivated developers to target multiple platforms. Market leaders, such as Apple, Google, and Microsoft, develop their smartphone applications complying with their platform specifications. The specification of each platform makes a platform-dedicated application incompatible with other platforms due to the diversity of operating systems, programming languages, and design patterns. Conventional development methodologies are applied to smartphone applications, yet they perform less well. Smartphone applications have unique hardware and software requirements. All previous factors push smartphone developers to build less sophisticated and low-quality products when targeting multiple smartphone platforms. Model-driven …

Algorithms To Compute Characteristic Classes, Martin Helmer

Electronic Thesis and Dissertation Repository

In this thesis we develop several new algorithms to compute characteristics classes in a variety of settings. In addition to algorithms for the computation of the Euler characteristic, a classical topological invariant, we also give algorithms to compute the Segre class and Chern-Schwartz-MacPherson (CSM) class. These invariants can in turn be used to compute other common invariants such as the Chern-Fulton class (or the Chern class in smooth cases).

We begin with subschemes of a projective space over an algebraically closed field of characteristic zero. In this setting we give effective algorithms to compute the CSM class, Segre class and …

Using Cellular Automata And Lattice Boltzmann Methods To Model Cancer Growth: Analysis Of Combination Treatment Outcomes, Jenna L. Butler

Electronic Thesis and Dissertation Repository

In Canada it is estimated that 76,600 people will die of cancer in 2014. Cancer, a collection of over 200 diseases, has differences existing between globally, between individuals and overtime in one individual. Treatment options are similarly varied. These differences make selecting the best possible treatment for every type of cancer very challenging. In addition, with no single cure for cancer, treatments are often combined in different ways to form the best overall option. In an attempt to synthesize the properties of these diseases into a collection of common cellular changes, Hanahan and Weinberg proposed ``the hallmarks of cancer" -- …

An Approach To Artificial Society Generation For Video Games, Bryan Sarlo

Electronic Thesis and Dissertation Repository

Since their inception in the 1940s, video games have always had a need for non-player characters (NPCs) driven by some form of artificial intelligence (AI). More recently, researchers and developers have attempted to create believable, or human-like, agents by modeling them after humans by borrowing concepts from the social sciences. This thesis explores an approach to generating a society of such believable agents with human-like attributes and social connections. This approach allows agents to form various kinds of relationships with other agents in the society, and even provides an introductory form of shared or influenced attributes based on their spouse …

Interactive Visualization For Deep Organizational Data, Arash Khosravi

Electronic Thesis and Dissertation Repository

During the last decade, there has been a growing interest in investigating how and why people use organizational data to solve problems, make decisions, and perform other cognitive activities, especially in the social network, healthcare, and education domains. Working with organizational data is challenging because of the complex and multi-structured nature of it. One way to support cognitive activities with organizational data is through the use of interactive visualization tools that provide different representations and mechanisms for interacting with deep layers of the data. In this research, we have deep organizational data which is mainly about collaborations inside universities. The …

Geological Object Recognition In Extraterrestrial Environments, Gregory M. Elfers

Electronic Thesis and Dissertation Repository

On July 4 1997, the landing of NASA’s Pathnder probe and its rover Sojourner marked the beginning of a new era in space exploration; robots with the ability to move have made up the vanguard of human extraterrestrial exploration ever since. With Sojourners landing, for the rst time, a ground traversing robot was at a distance too far from earth to make direct human control practical. This has given rise to the development of autonomous systems to improve the e?ciency of these robots,in both their ability to move,and their ability to make decisions regarding their environment. Computer Vision comprises a …

Trust Based Privacy Policy Enforcement In Cloud Computing, Karthick Ramachandran

Electronic Thesis and Dissertation Repository

Cloud computing offers opportunities for organizations to reduce IT costs by using the computation and storage of a remote provider. Despite the benefits offered by cloud computing paradigm, organizations are still wary of delegating their computation and storage to a cloud service provider due to trust concerns. The trust issues with the cloud can be addressed by a combination of regulatory frameworks and supporting technologies. Privacy Enhancing Technologies (PET) and remote attestation provide the technologies for addressing the trust concerns. PET provides proactive measures through cryptography and selective dissemination of data to the client. Remote attestation mechanisms provides reactive measures …

Metagenome Assembly, Wenjing Wan

Electronic Thesis and Dissertation Repository

The advent of the next generation sequencing technology (NGS) makes it possible to study metagenomics data which is directly extracted and cloned from assemblage of micro-organisms. Metagenomics data are diverse in species and abundance. Because most genome assemblers are designed for single genome assembly, they could not perform well on metagenomics data. To deal with the mixed and not uniformly distributed metagenomics reads, we developed a novel metagenomic assembler named MetaSAGE, on the platform of the existing SAGE assembler. MetaSAGE finds contigs from the overlap graph based on the minimum cost flow theory and uses mate-pair information to extract scaffolds …

An Investigation Of Cognitive Implications In The Design Of Computer Games, Robert Haworth

Electronic Thesis and Dissertation Repository

Computer games have been touted for their ability to engage players in cognitive activities (e.g., decision making, learning, planning, problem solving). By ‘computer game’ we mean any game that uses computational technology as its platform, regardless of the actual hardware or software; games on personal computers, tablets, game consoles, cellphones, or specialized equipment can all be called computer games. However, there remains much uncertainty regarding how to design computer games so that they support, facilitate, and promote the reflective, effortful, and conscious performance of cognitive activities. The goal of this dissertation is to relieve some of this uncertainty, so that …

Geography Aware Virtual Machine Migrations And Replications For Distributed Cloud Data Centers, Sakif Shahriar Pritom

Electronic Thesis and Dissertation Repository

Cloud computing provides access to computing resources for a fee. Client applications and services can be hosted in clouds. Cloud computing typically uses a network of data centers that are geographically dispersed. The distance between clients and applications is impacted by geographical distance. The geographical distribution of client requests can be random and difficult to predict. This suggests a need to reconsider the placement of services at run-time through migration. This thesis describes a framework based on software-defined networking (SDN) principles. It demonstrates algorithms that are periodically executed and determine candidate services to migrate and replicate as well as target …