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Full-Text Articles in Physical Sciences and Mathematics
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 …
Critical Thinking Traits Of Top-Tier Experts And Implications For Computer Science Education, Dean Bushey
Critical Thinking Traits Of Top-Tier Experts And Implications For Computer Science Education, Dean Bushey
All Dissertations
A documented shortage of technical leadership and top-tier performers in
computer science jeopardizes the technological edge, security, and economic well-being of the nation. The 2005 President's Information and Technology Advisory Committee (PITAC) Report on competitiveness in computational sciences highlights the major impact of science, technology, and innovation in keeping America competitive in the global marketplace. It stresses the fact that the supply of science, technology, and engineering experts is at the core
of America's technological edge, national competitiveness and security. However, recent data shows that both undergraduate and postgraduate production of computer scientists is falling.
Past research on expert performance …
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.