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…

Elementary actions online establish an individual's existence on the web and her/his orientation toward different issues. In this sense, actions truly define a user in spaces like online forums and communities and the aggregate of elementary actions shape the atmosphere of these online spaces. This observation, coupled with the unprecedented scale…

Data in many growing fields has an underlying network structure that can be taken advantage of. In this dissertation we apply data and network science to problems in the domains of systems biology and healthcare. Data challenges in these fields include noisy, heterogeneous data, and a lack of ground truth. The primary thesis of this work is that…

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 security has been a particularly hot topic since the enhanced internal control requirements of Sarbanes-Oxley (SOX) were introduced in 2002. At about this same time, cloud computing started its explosive growth. Outsourcing of mission-critical functions has always been a gamble for managers, but the advantages of cloud computing are…

Program comprehension is the most important and frequent process in software maintenance. Extensive research has found that individual characteristics of programmers, differences of computer programs, and differences of task-driven motivations are the major factors that affect the program comprehension results. There is no study specifically…

Signal detection is a challenging task for regulatory and intelligence agencies. Subject matter experts in those agencies analyze documents, generally containing narrative text in a time bound manner for signals by identification, evaluation and confirmation, leading to follow-up action e.g., recalling a defective product or public advisory for…

The educational system is changing to meet the needs of 21st century learners, technology integration has become critical in meeting that need. One-to-one computing may close the digital gap that exists and equips students with the skills necessary for success in the 21st century workplace (Lemke & Martin, 2004). While much research exists on…

We studied the problem of constraint-based pattern mining for three different data formats, item-set, sequence and graph, and focused on mining patterns of large sizes. Colossal patterns in each data formats are studied to discover pruning properties that are useful for direct mining of these patterns. For item-set data, we observed robustness of…

Many universities and colleges have placed increased emphasis on teaching excellence in higher education. Efforts to promote teaching excellence vary from the development of alternative new pedagogies as well as research exploring strategies to improve existing teaching practices. Logically, different disciplines employ different instructional…

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…

Radiology data, in the form of images and reports, is growing at a high rate due to the introduction of new imaging modalities, new uses of existing modalities, and the growing importance of objective image information in the diagnosis and treatment of patients. This increase has resulted in an enormous set of image data that is richly annotated…

Software metrics are measures of software products and processes. Metrics are widely used by software organizations to help manage projects, improve product quality and increase efficiency of the software development process. However, metrics programs tend to have a high failure rate in organizations, and developer pushback is one of the sources…

With the dramatic growth of text information, there is an increasing need for powerful text mining systems that can automatically discover useful knowledge from text. Text is generally associated with all kinds of contextual information. Those contexts can be explicit, such as the time and the location where a blog article is written, and the…

Existing research on context and context awareness has broadly focused on the technical aspects of context acquisition and interpretation of users' surroundings, also called physical or sensor-based context. Such an approach has lacked from reconciling the perception of real-world context exhibited by humans, also known as user context, and…