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Full-Text Articles in Physical Sciences and Mathematics
Using Natural Language Processing To Categorize Fictional Literature In An Unsupervised Manner, Dalton J. Crutchfield
Using Natural Language Processing To Categorize Fictional Literature In An Unsupervised Manner, Dalton J. Crutchfield
Electronic Theses and Dissertations
When following a plot in a story, categorization is something that humans do without even thinking; whether this is simple classification like “This is science fiction” or more complex trope recognition like recognizing a Chekhov's gun or a rags to riches storyline, humans group stories with other similar stories. Research has been done to categorize basic plots and acknowledge common story tropes on the literary side, however, there is not a formula or set way to determine these plots in a story line automatically. This paper explores multiple natural language processing techniques in an attempt to automatically compare and cluster …
A Longitudinal Study Of Mammograms Utilizing The Automated Wavelet Transform Modulus Maxima Method, Brian C. Toner
A Longitudinal Study Of Mammograms Utilizing The Automated Wavelet Transform Modulus Maxima Method, Brian C. Toner
Electronic Theses and Dissertations
Breast cancer is a disease which predominatly affects women. About 1 in 8 women are diagnosed with breast cancer during their lifetime. Early detection is key to increasing the survival rate of breast cancer patients since the longer the tumor goes undetected, the more deadly it can become. The modern approach for diagnosing breast cancer relies on a combination of self-breast exams and mammography to detect the formation of tumors. However, this approach only accounts for tumors which are either detectable by touch or are large enough to be observed during a screening mammogram. For some individuals, by the time …
Improving Random Forests By Feature Dependence Analysis, Silu Zhang
Improving Random Forests By Feature Dependence Analysis, Silu Zhang
Electronic Theses and Dissertations
Random forests (RFs) have been widely used for supervised learning tasks because of their high prediction accuracy good model interpretability and fast training process. However they are not able to learn from local structures as convolutional neural networks (CNNs) do when there exists high dependency among features. They also cannot utilize features that are jointly dependent on the label but marginally independent of it. In this dissertation we present two approaches to address these two problems respectively by dependence analysis. First a local feature sampling (LFS) approach is proposed to learn and use the locality information of features to group …
Knowledge-Based Task Structure Planning For An Information Gathering Agent, John Phelps
Knowledge-Based Task Structure Planning For An Information Gathering Agent, John Phelps
Electronic Theses and Dissertations
An effective solution to model and apply planning domain knowledge for deliberation and action in probabilistic, agent-oriented control is presented. Specifically, the addition of a task structure planning component and supporting components to an agent-oriented architecture and agent implementation is described. For agent control in risky or uncertain environments, an approach and method of goal reduction to task plan sets and schedules of action is presented. Additionally, some issues related to component-wise, situation-dependent control of a task planning agent that schedules its tasks separately from planning them are motivated and discussed.
Asynchronous Validity Resolution In Sequentially Consistent Shared Virtual Memory, Jonathan Thomas
Asynchronous Validity Resolution In Sequentially Consistent Shared Virtual Memory, Jonathan Thomas
Electronic Theses and Dissertations
Shared Virtual Memory (SVM) is an effort to provide a mechanism for a distributed system, such as a cluster, to execute shared memory parallel programs. Unfortunately, SVM has performance problems due to its underlying distributed architecture. Recent developments have increased performance of SVM by reducing communication. Unfortunately this performance gain was only possible by increasing programming complexity and by restricting the types of programs allowed to execute in the system. Validity resolution is the process of resolving the validity of a memory object such as a page. Current SVM systems use synchronous or deferred validity resolution techniques in which user …