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Full-Text Articles in Physical Sciences and Mathematics
Gt-Ches And Dycon: Improved Classification For Human Evolutionary Systems, Joseph S. Johnson
Gt-Ches And Dycon: Improved Classification For Human Evolutionary Systems, Joseph S. Johnson
Theses and Dissertations
The purpose of this work is to rethink the process of learning in human evolutionary systems. We take a sober look at how game theory, network theory, and chaos theory pertain specifically to the modeling, data, and training components of generalization in human systems. The value of our research is three-fold. First, our work is a direct approach to align machine learning generalization with core behavioral theories. We made our best effort to directly reconcile the axioms of these heretofore incompatible disciplines -- rather than moving from AI/ML towards the behavioral theories while building exclusively on AI/ML intuition. Second, this …
Semantic-Driven Unsupervised Image-To-Image Translation For Distinct Image Domains, Wesley Ackerman
Semantic-Driven Unsupervised Image-To-Image Translation For Distinct Image Domains, Wesley Ackerman
Theses and Dissertations
We expand the scope of image-to-image translation to include more distinct image domains, where the image sets have analogous structures, but may not share object types between them. Semantic-Driven Unsupervised Image-to-Image Translation for Distinct Image Domains (SUNIT) is built to more successfully translate images in this setting, where content from one domain is not found in the other. Our method trains an image translation model by learning encodings for semantic segmentations of images. These segmentations are translated between image domains to learn meaningful mappings between the structures in the two domains. The translated segmentations are then used as the basis …
Inclusion Of Women In Computer Science, Naomi Johnson, Dr. Kevin Seppi
Inclusion Of Women In Computer Science, Naomi Johnson, Dr. Kevin Seppi
Journal of Undergraduate Research
Since the 1980’s, the percentage of computer science degrees awarded to women in the United States has fallen dramatically. There are growing numbers of men earning bachelor’s degrees in CS, and the numbers of women are increasing very slowly. For decades, researchers have been studying recruitment and retention of women and other minorities in CS, yet it is still not apparent what departments, professors, or students can do in order to get the numbers of women earning degrees in CS up again.
Kiwivault: Encryption Software For Portable Storage Devices, Trevor Bradshaw Florence
Kiwivault: Encryption Software For Portable Storage Devices, Trevor Bradshaw Florence
Theses and Dissertations
While many people use USB flash drives, most do not protect their stored documents. Solutions for protecting flash drives exist but inherently limit functionality found in unprotected drives such as portability, usability, and the ability to share documents between multiple people. In addition, other drawbacks are introduced such as the possibility of losing access to protected documents if a password is lost. Assuming protecting portable documents is important, in order for people to be willing to protect their documents they should be required to make as few sacrifices in functionality as possible. We introduce KiwiVault, a USB flash drive encryption …
An Analysis Of Document Retrieval And Clustering Using An Effective Semantic Distance Measure, Nathan Scott Davis
An Analysis Of Document Retrieval And Clustering Using An Effective Semantic Distance Measure, Nathan Scott Davis
Theses and Dissertations
As large amounts of digital information become more and more accessible, the ability to effectively find relevant information is increasingly important. Search engines have historically performed well at finding relevant information by relying primarily on lexical and word based measures. Similarly, standard approaches to organizing and categorizing large amounts of textual information have previously relied on lexical and word based measures to perform grouping or classification tasks. Quite often, however, these processes take place without respect to semantics, or word meanings. This is perhaps due to the fact that the idea of meaningful similarity is naturally qualitative, and thus difficult …
A Direct Algorithm For The K-Nearest-Neighbor Classifier Via Local Warping Of The Distance Metric, Tohkoon Neo
A Direct Algorithm For The K-Nearest-Neighbor Classifier Via Local Warping Of The Distance Metric, Tohkoon Neo
Theses and Dissertations
The k-nearest neighbor (k-NN) pattern classifier is a simple yet effective learner. However, it has a few drawbacks, one of which is the large model size. There are a number of algorithms that are able to condense the model size of the k-NN classifier at the expense of accuracy. Boosting is therefore desirable for increasing the accuracy of these condensed models. Unfortunately, there does not exist a boosting algorithm that works well with k-NN directly. We present a direct boosting algorithm for the k-NN classifier that creates an ensemble of models with locally modified distance weighting. An empirical study conducted …
Obstacle Avoidance And Path Traversal Using Interactive Machine Learning, Jonathan M. Turner
Obstacle Avoidance And Path Traversal Using Interactive Machine Learning, Jonathan M. Turner
Theses and Dissertations
Recently there has been a growing interest in using robots in activities that are dangerous or cost prohibitive for humans to do. Such activities include military uses and space exploration. While robotic hardware is often capable of being used in these types of situations, the ability of human operators to control robots in an effective manner is often limited. This deficiency is often related to the control interface of the robot and the level of autonomy that control system affords the human operator. This thesis describes a robot control system, called the safe/unsafe system, which gives a human operator the …
On-The-Fly Dynamic Dead Variable Analysis, Joel P. Self
On-The-Fly Dynamic Dead Variable Analysis, Joel P. Self
Theses and Dissertations
State explosion in model checking continues to be the primary obstacle to widespread use of software model checking. The large input ranges of variables used in software is the main cause of state explosion. As software grows in size and complexity the problem only becomes worse. As such, model checking research into data abstraction as a way of mitigating state explosion has become more and more important. Data abstractions aim to reduce the effect of large input ranges. This work focuses on a static program analysis technique called dead variable analysis. The goal of dead variable analysis is to discover …
System For Collision Detection Between Deformable Models Built On Axis Aligned Bounding Boxes And Gpu Based Culling, David Owen Tuft
System For Collision Detection Between Deformable Models Built On Axis Aligned Bounding Boxes And Gpu Based Culling, David Owen Tuft
Theses and Dissertations
Collision detection between deforming models is a difficult problem for collision detection systems to handle. This problem is even more difficult when deformations are unconstrained, objects are in close proximity to one another, and when the entity count is high. We propose a method to perform collision detection between multiple deforming objects with unconstrained deformations that will give good results in close proximities. Currently no systems exist that achieve good performance on both unconstrained triangle level deformations and deformations that preserve edge connectivity. We propose a new system built as a combination of Graphics Processing Unit (GPU) based culling and …
Implicit Affinity Networks, Matthew Scott Smith
Implicit Affinity Networks, Matthew Scott Smith
Theses and Dissertations
Although they clearly exist, affinities among individuals are not all easily identified. Yet, they offer unique opportunities to discover new social networks, strengthen ties among individuals, and provide recommendations. We propose the idea of Implicit Affinity Networks (IANs) to build, visualize, and track affinities among groups of individuals. IANs are simple, interactive graphical representations that users may navigate to uncover interesting patterns. This thesis describes a system supporting the construction of IANs and evaluates it in the context of family history and online communities.
Improving Record Linkage Through Pedigrees, Burdette N. Pixton
Improving Record Linkage Through Pedigrees, Burdette N. Pixton
Theses and Dissertations
Record linkage, in a genealogical context, is the process of identifying individuals from multiple sources which refer to the same real-world entity. Current solutions focus on the individuals in question and on complex rules developed by human experts. Genealogical databases are highly-structured with relationships existing between the individuals and other instances. These relationships can be utilized and human involvement greatly minimized by using a filtered structured neural network. These neural networks, using traditional back-propagation methods, are biased in a way to make the network human readable. The results show an increase in precision and recall when pedigree data is available …
Query Rewriting For Extracting Data Behind Html Forms, Xueqi Chen
Query Rewriting For Extracting Data Behind Html Forms, Xueqi Chen
Theses and Dissertations
Much of the information on the Web is stored in specialized searchable databases and can only be accessed by interacting with a form or a series of forms. As a result, enabling automated agents and Web crawlers to interact with form-based interfaces designed primarily for humans is of great value. This thesis describes a system that can fill out Web forms automatically according to a given user query against a global schema for an application domain and, to the extent possible, extract just the relevant data behind these Web forms. Experimental results on two application domains show that the approach …