Now showing items 1-20 of 39

    • Affect, Affective Contagion and Decisions in Agile Development 

      Alhubaishy, Abdulaziz Abdurabuh (Faculty of Graduate Studies and Research, University of Regina, 2018-09)
      During the past decade, research on how affects—including emotions, moods, and feelings—influence software developers’ performance has increased. In software development, this influence has been considered and investigated ...
    • Agent Trust Management Based on Human Plausible Reasoning and Rough Sets: Application to Agent-based Web search 

      Abedinzadeh, Sadra (Faculty of Graduate Studies and Research, University of Regina, 2013-12)
      Nowadays, there is a growing need to manage trust in open systems. Service providers can autonomously join and leave the open system at any time. Thus, an open system may contain untrustworthy service providers. In order ...
    • AHP-Based Methodology for a Complex Decision Support in Extreme Programming 

      Alshehri, Sultan Abdullah J. (Faculty of Graduate Studies and Research, University of Regina, 2014-01)
      Extreme Programming (XP) is one of the most successful methods in software development. It offers a set of practices designed to work together in order to provide value to the customer. The XP process emphasizes simplicity, ...
    • Analytical and Semi-Analytical Models for Composite Reservoirs with Complex Well Completions 

      Idorenyin, Etim Hope (Faculty of Graduate Studies and Research, University of Regina, 2016-04)
      With the current increasing productivity and the proliferation of shale and tight sand resource plays in Canada, and North America in general, the need to understand and characterize these resource plays, for the purpose ...
    • An Application of Artificial Neural Networks in Forecasting Future Oil Price Return Volatilities 

      Shafiee Hasanabadi, Hamed (Faculty of Graduate Studies and Research, University of Regina, 2014-05)
      This study focuses on a novel application of Artificial Neural Networks (ANNs) in Financial Engineering. Here Artificial Neural Networks are applied for simulating both direct and inverse of some financial models. This ...
    • Application of Function Approximations to Reservoir Engineering 

      Elmabrouk, Saber Khaled (Faculty of Graduate Studies and Research, University of Regina, 2012-02)
      The need for function approximations arises in many branches of engineering, and in particular, petroleum engineering. A function approximation estimates an unknown function, which then finds an underlying relationship ...
    • Auction Shill Detection Framework Based on SWM 

      Ganguly, Swati (Faculty of Graduate Studies and Research, University of Regina, 2016-12)
      Online auctioning has attracted serious in-auction fraud, such as shill bidding, given the huge amount of money involved and the anonymity of users. Due to the fact that shill bidding is difficult to detect as well as ...
    • Bayesian Network Inference Using Marginal Trees 

      Oliveira, Jhonatan de Souza (Faculty of Graduate Studies and Research, University of Regina, 2016-06)
      Bayesian networks (BNs) are formal probabilistic graphical models for reasoning un- der uncertainty. BNs are used in a variety of applications, including the state-of- the-art forensic software tool, a ranking system for ...
    • Can Meaning Associated with Perceptual Grouping Modulate Attention? 

      Pandey, Mamata (Faculty of Graduate Studies and Research, University of Regina, 2013-05)
      In an environment rich with information, performance on a task depends on the ability to select only the relevant pieces of information for achieving a current goal. Cognitive psychologists propose that selective attention ...
    • Conditional Preference Networks: Learning and Optimization 

      Alanazi, Eisa Ayed (Faculty of Graduate Studies and Research, University of Regina, 2016-12)
      The last two decades have shown a great body of work in the eld of Arti cial Intelligence (AI) addressing issues related to representing, reasoning and learning preferences. One of the main models for graphical ...
    • A Cost-Sensitive Approach to Ternary Classification 

      Zhou, Bing (Faculty of Graduate Studies and Research, University of Regina, 2012-07)
      Bayesian inference and rough set theory provide two approaches to data analysis. There are close connections between the two theories as they both use probabilities to express uncertainties and knowledge about data. ...
    • Discovering Group Differences from Qualitative and Quantitative Attributes Using Contrast Set Mining with Discretization and Measures of Interestingness 

      Simeon, Mondelle (Faculty of Graduate Studies and Research, University of Regina, 2012-12)
      Identifying differences between groups is a fundamental problem in many disciplines. Groups are defined by a selected property that distinguishes one group from the other. For example, gender (male and female students) ...
    • A Dynamic Stage-Based Fraud Monitoring Framework for Multiple Live Auctions 

      Wang, Xuegang (Faculty of Graduate Studies and Research, University of Regina, 2016-04)
      In this thesis, a new approach to monitoring live auction frauds is proposed. Monitor- ing progressing auctions for fraudulent bidding activities is becoming crucial in order to detect and stop fraud on time, so fraudsters ...
    • Elicitation of Constraints and Qualitative Preferences in Multi-Attribute Auctions 

      Shil, Shubhashis Kumar (Faculty of Graduate Studies and Research, University of Regina, 2013-11)
      Multi-Attribute Reverse Auctions (MARAs) allow negotiation between the buyer and sellers over price along with other non-price attributes such as delivery time, sellers' reputation, and product quality. The seller with ...
    • Evolutionary Winner Determination in Advanced Combinatorial Reverse Auctions 

      Shil, Shubhashis Kumar (Faculty of Graduate Studies and Research, University of Regina, 2017-09)
      Traditional Combinatorial Reverse Auctions (CRAs) are already very hard problems to solve. By considering the multiplicity of units, attributes and objectives of items; the complexity of CRAs increases. Winner Determination ...
    • An Experimental Approach to the Construction of Binary Decision Classes from Card Sort Data 

      Almestadi, Emad Hamdan (Faculty of Graduate Studies and Research, University of Regina, 2013-07)
      This thesis presents work done towards understanding the data collected from a card sorting study of facial photographs. In that study, 25 participants sorted 356 photos (178 Caucasian and 178 First Nations) into piles ...
    • A Framework for Divisible Load E-science Applications in Optical Grids 

      Abouelela, Mohamed Moustafa Mohamed (Faculty of Graduate Studies and Research, University of Regina, 2013-05)
      E-science applications require discovering, collecting, transferring and processing large volumes of scientific data. In divisible load e-science applications, data is generated and stored in geographically distributed ...
    • Geo-Coordinated Parallel Coordinates (GCPC): A Case Study of Environmental Data Analysis 

      El Meseery, Maha Mohamed Nabil (Faculty of Graduate Studies and Research, University of Regina, 2016-03)
      The large number of environmental problems faced by society in recent years has driven researchers to collect and study massive amounts of environmental data. Such environmental datasets are often high dimensional and ...
    • Handling Qualitative and Quantitative Preferences with Constraints in Interactive Applications 

      Mohammed, Bandar (Faculty of Graduate Studies and Research, University of Regina, 2017-03)
      Preference elicitation is very important for interactive systems. A potential buyer typically has speci c expectations in the attributes of the product he or she is interested in. While the current interactive systems ...
    • Identifying Structure and Semantics in Bayesian Network Inference 

      Yan, Wen (Faculty of Graduate Studies and Research, University of Regina, 2013-06)
      Bayesian networks are a semantic modeling tool for managing uncertainty in complex domains. While the numerous techniques for exact inference vary when they apply the multiplication and marginalization (addition) operators, ...