Women remain underrepresented in Science, Technology, Engineering, and Math (STEM) disciplines. A lot of research has examined individual-level impacts of their absence, such as women's lack of interest in STEM, their lack of sense of belonging, and low math confidence. In this dissertation, I use Acker's theory of gendered organizations as a…

Constraint satisfaction problems are a powerful way to abstract and represent academic and real-world problems from both artificial intelligence and operations research. A constraint satisfaction problem is typically addressed by a sequential constraint solver running on a single processor. Rather than construct a new, parallel solver, this work…

The goal of the dissertation study was to evaluate the existing DG scheduling algorithm. The evaluation was developed through previously explored simulated analyses of DGs performed by researchers in the field of DG scheduling optimization and to improve the current RT framework of the DG at TTU. The author analyzed the RT of an actual DG, thereby…

With the rapid growth of the Internet and the popularity of digital imaging devices, digital imagery has become our major information source. Meanwhile, the development of digital manipulation techniques employed by most image editing software brings new challenges to the credibility of photographic images as the definite records of events. We…

Many of the devices we interact with on a daily basis are currently equipped with wireless connectivity. Soon this will be extended to the vehicles we drive/ride every day. Wirelessly connected vehicles will form a new kind of network that will enable a wide set of innovative applications ranging from enhanced safety to entertainment. To…

This dissertation transforms a set of system complexity reduction problems to feature selection problems. Three systems are considered: classification based on association rules, network structure learning, and time series classification. Furthermore, two variable importance measures are proposed to reduce the feature selection bias in tree…

Information dispersal algorithms (IDA) are used for distributed data storage because they simultaneously provide security, reliability and space efficiency, constituting a trustworthy computing framework for many critical applications, such as cloud computing, in the information society. In the most general sense, this is achieved by dividing data…

Research in the field of Automated Planning is largely focused on the problem of constructing plans or sequences of actions for going from a specific initial state to a goal state. The complexity of this task makes it desirable to find "generalized" plans which can solve multiple problem instances from a class of similar problems. Most approaches…

Wireless Sensor Networks (WSNs) have unique characteristics which constrain them; including small energy stores, limited computation, and short range communication capability. Most traditional security algorithms use cryptographic primitives such as Public-key cryptography and are not optimized for energy usage. Employing these algorithms for the…

Traditional information systems return answers after a user submits a complete query. Users often feel "left in the dark" when they have limited knowledge about the underlying data, and have to use a try-and-see approach for finding information. The trend of supporting autocomplete in these systems is a first step towards solving this problem. A…

This thesis investigates and develops a few acceleration techniques for the search engine algorithms used in PageRank and HITS computations. PageRank and HITS methods are two highly successful applications of modern Linear Algebra in computer science and engineering. They constitute the essential technologies accounted for the immense growth and…

My research interest has been in understanding the human communities formed through interpersonal social activities. Participation in online communities on social network sites such as Twitter has been observed to influence people's behavior in diverse ways including financial decision-making and political choices, suggesting the rich potential…

Thesis Statement: "Availability-dependent global predicates can be efficiently and scalably realized for a class of distributed services, in spite of specific selfish and colluding behaviors, using local and decentralized protocols". Several types of large-scale distributed systems spanning the Internet have to deal with availability variations…

This empirical study evaluates the document category prediction effectiveness of Naive Bayes (NB) and K-Nearest Neighbor (KNN) classifier treatments built from different feature selection and machine learning settings and trained and tested against textual corpora of 2300 Gang-Of-Four (GOF) design pattern documents. Analysis of the experiment's…

With the increasing wealth of information on the Web, information integration is ubiquitous as the same real-world entity may appear in a variety of forms extracted from different sources. This dissertation proposes supervised and unsupervised algorithms that are naturally integrated in a scalable framework to solve the entity resolution problem,…