The Elliptic Curve Digital Signature Algorithm (ECDSA) is the elliptic curve analog of the Digital Signature Algorithm (DSA) and a federal government approved digital signature method. In this thesis work, software optimization techniques were applied to speed up the ECDSA for a particular NTST curve over GF(p). The Montgomery multiplication...
Reinforcement Learning (RL) is the study of agents that learn optimal
behavior by interacting with and receiving rewards and punishments from an unknown
environment. RL agents typically do this by learning value functions that
assign a value to each state (situation) or to each state-action pair. Recently,
there has been...
Coarse resolution imagery, such as that produced by the MODIS instrument, poses the challenge of estimating sub-pixel proportions of di erent land cover types. This problem is di cult because of the variety and variability of vegetation within individual pixels. This thesis describes and compares two existing algorithms for estimating...
Farm machinery continues to increase in its importance to the agricultural sector. Depreciation, the decline in value of a durable asset over time, represents one of the largest costs of agricultural production. The general objectives of this study were to update and expand the number of Remaining Value (RV) functions...
End-user programmers are writing an unprecedented number of programs, due in large part to the significant effort put forth to bring programming power to end users. Unfortunately, this effort has not been supplemented by a comparable effort to increase the correctness of these often faulty programs. To address this need,...
Supervised learning is concerned with discovering the relationship between example sets of features and their corresponding classes. The traditional supervised learning formulation assumes that all examples are independent from one another. The order of the examples contains no information. Nonetheless, many problems have a sequential nature. Classifiers for these problems...
This thesis presents the results of two studies that investigate the question of what interruption-styles are most appropriate for end-user programmers who are debugging programs. In the studies, end-user programmers are presented with surprises that encourage them to investigate, use, and learn about debugging devices in their programming environment. We...
Edit distances are a well-established technique for classification problems. They have been employed successfully in many classification problems including chromosome classification and hand-written digit recognition. Virtually all machine learning algorithms represent the objects to be classified as vectors of features. However, edit distances provide only a measure of the difference...
Image segmentation continues to be a fundamental problem in computer vision and image understanding. In this thesis, we present a Bayesian network that we use for object boundary detection in which the MPE (most probable explanation) before any evidence can produce multiple non-overlapping, non-self-intersecting closed contours and the MPE with...
Hardwood lumber is a major forest product, and board grading is an important part of its manufacturing and marketing. Computer grading programs have been used to train graders and to grade lumber for board data banks, but they have not been used to machine-grade boards in an industrial environment because...
End-user programming is growing at a rapid rate, but there has been little in the way of tools or environments to improve the correctness of programs created by end users. We present an approach to dynamic assertions in one of the most widely used end-user programming paradigms - namely the...
End users develop more software than any other group of programmers, using software authoring devices such as e-mail filtering editors, by-demonstration macro builders, and spreadsheet environments. Despite this, there has been only a little research on finding ways to help these programmers with the dependability of the software they create....
This thesis presents a novel technique for retiming keyframe-based animation. We call our approach Performance Timing. Keyframing is a standard technique for generating computer animation that typically requires artistic ability and a set of skills for the software package being used. From our experience observing novice animators and their work,...
Graph-based approaches for sequencing motion capture data have produced some of the most realistic and controllable character motion to date. Most previous graph-based approaches have employed a run-time global search to find paths through the motion graph that meet user-defined constraints such as a desired locomotion path. Such searches do...
Professional software developers do not test code adequately, even though testing tools are widely available. Until developers realize the deficiencies in their tests, inadequate testing of software seems likely to remain a major problem. To support developers writing tests, industry and researchers have proposed systems that visualize “testedness” for end-user...
Machine learning encompasses probabilistic and statistical techniques that can build models from large quantities of extensional information (examples) with minimal dependence on intensional information (domain knowledge). This focus of machine learning is reflected in the never-ending quest for "off-the-shelf" classifiers. To generalize to unseen data, however, we must make use...
Functional programming is concerned with referential transparency, that is, given a certain function and its parameter, that the result will always be the same. However, it seems that this is violated in applications involving uncertainty, such as rolling a dice. This thesis defines the background of probabilistic programming and domain-specific...
3D datasets acquire great importance in the context of medical imaging. In this thesis we survey and enhance solutions to problems inherently associated with 3D datasets-processing time,noise and visualization. Efforts include development of a tool kit to provide a multi-threaded processing platform to cut processing time, produce real time visualization...
Protein secondary structure prediction plays a pivotal role in predicting protein folding in three-dimensions. Its task is to assign each residue one of the three secondary structure classes helix, strand, or random coil. This is an instance of the problem of sequential supervised learning in machine learning. This thesis describes...
Although researchers have begun to explicitly support end-user programmers’ debugging by providing information to help them find bugs, there is little research addressing the right content to communicate to these users. The specific semantic content of these debugging communications matters because, if the users are not actually seeking the information...
Popular applications such as P2P file sharing, multiplayer gaming, videoconferencing, etc. rely on the efficiency of content distribution from a single source to multiple receivers. Most users of these applications are on the widely prevalent source constraint networks such as the Digital Subscriber Line (DSL) and wireless networks. Overlay multicast...
This thesis presents a domain specific visual language designed to allow coaches to create content that exhibits the complex 2D interactions observed in the game of American football. Coaches can visually program the content by using symbols and drawing primitives similar to those that they currently use to design static...
As broadband Internet becomes widely available, Peer-to-Peer (P2P) applications over the Internet are becoming increasingly popular. Such an example is a video multicast application in which, one source streams a video to a large number of destination nodes through an overlay multicast tree consisting of peers.
These overlay multicast-based applications,...
Traditional application of Voronoi diagrams for space partitioning creates Voronoi regions, with areas determined by the generators’ relative locations and weights. Especially in the area of information space (re)construction, however, there is a need for inverse solutions; i.e., finding weights that result in regions with predefined areas. In this thesis,...
This thesis presents a model for simulating individual pedestrian motion based on empirical data. The model keeps track of a pedestrian’s position, orientation, and body configuration and leverages motion capture data to generate plausible motion. Our model can automatically incorporate a pedestrian’s physical limitations when making movement decisions, since it...
We present an approach for generating a character’s response in anticipation of an impending impact. Protective anticipatory movement is built upon several simple actions that have been identified as response mechanisms in monkeys and in humans. These actions are parameterized by a model of the interaction based on the approaching...
Packet loss, delay and time-varying bandwidth are three main problems facing multimedia streaming applications over the Internet. Existing techniques such as Media-aware network protocol, network adaptive source and channel coding, etc. have been proposed to either overcome or alleviate these drawbacks of the Internet. But these techniques either need specialized...
The Line Integral Convolution (LIC) is a mainstay of flow visualization. It is, however, computationally intensive, which limits its interactivity. Also, when used to view three-dimensional (3D) vector fields, the resulting images are dense and cluttered, making it difficult to perceive the flow on the interior parts of the field....
Oftentimes in visualization, the goal of using volume datasets is not just to visualize them but also to analyze and compare them. In order to compare the two volumes, we cannot take all the voxels into consideration. The size of a typical volume data set is quite large (maybe a...
Finding information can cost a significant amount of time, even when the information is already stored on the user’s local computer system. There is significant research aimed at reducing these time costs, but little research into exactly what these costs are or how they impact people’s use of tools and...
A basic tradeoff to consider when designing a distributed data-mining framework is the need for a compromise between the cost of communication and computation resources and the accuracy of the mining results. This is essentially a decision of whether it is more efficient to communicate all of the data to...
Domain-independent automated planning is concerned with computing a sequence of actions that can transform an initial state into a desired goal state. Resource production domains form an interesting class of such problems, in that they typically require reasoning about concurrent durative-actions with continuous effects while minimizing some cost function. Although...
Most of the work so far in the subfield of Gender HCI has followed a theory-driven approach. Established theories, however, do not take into account specific issues that arise in end-user debugging. We suspected that there may be important information that we were overlooking. We therefore employed a methodology change:...
There has been little research into how end-user programming environments can provide explanations that could fill a critical information gap for end-user debuggers – help with debugging strategy. To address this need, we designed and prototyped a video-based approach for explaining debugging strategy, and accompanied it with a text-only approach....
There has been little prior research reporting strategy usage in end-user problem solving, and even less using gender as a factor. Without this type of information, enduser programming systems cannot know the “target” at which to aim, if they are to support male and female end-user programmers’ debugging. As a...
Nowadays, sports events are a significant part of the every-day entertainment with local, national, and international championships. A lot of money is invested by broadcasting companies to attract new and more viewers, acquire broadcasting rights, or send entire crews on site to cover such events. Journalists are among the few...
Remote sensors are becoming the standard for observing and recording ecological data in the field. Such sensors can record data at fine temporal resolutions, and they can operate under extreme conditions prohibitive to human access. Unfortunately, sensor data streams exhibit many kinds of errors ranging from corrupt communications to partial...
Web applications are popular attack targets. Misuse detection systems use signature databases to detect known attacks. However, it is difficult to keep the database up to date with the rate of discovery of vulnerabilities. They also cannot detect zero-day attacks. By contrast, anomaly detection systems learn the normal behavior of...
Forward Error Correction and retransmission are two approaches used to reliably broadcast data in a network with poor quality of service. Taking some assumptions, it has been suggested that a retransmission based reliable broadcasting scheme using network coding should in theory provide an increase in bandwidth efficiency by combining packets...
Fluid simulation is an interesting research problem with a wide range of applications including mechanical engineering, special effects in movies and games, and scientific simulation. Due to the complex nature of typical fluid flow equations, there are circumstances where a full volumetric fluid simulation may not be necessary to generate...
This thesis addresses the problem of learning dynamic Bayesian network (DBN) models to support reinforcement learning. It focuses on learning regression tree models of the conditional probability distributions of the DBNs. Existing algorithms presume that the stochasticity in the domain can be modeled as a deterministic function with additive noise....
In diversity combining automatic repeat request (ARQ), erroneous packets are combined together forming a single, more reliable, packet. In this thesis, we give a diversity combining scheme for the m-ary unidirectional channel. A system using the given scheme with a t-unidirectional error detecting code is able to correct up to...
Recent efforts in user-control of data-driven characters have focused on designing high-level graph data-structures that we call a Behavior Finite State Machine (BFSM). A BFSM is an interactive data-structure that benefits from the advantages of both motion graphs and blend-based techniques for generating animated motion. Each node in a BFSM...
Transportation infrastructure provides a vital service for the functionality of a
city. The efficient design of road networks poses an interesting topic in computer
science for digital content developers. For civil engineers, the visualization of
analysis results on infrastructure both efficiently and intuitively is crucial. The
following contributions are made...
Motion capture data is a digital representation of the complex temporal structure of human motion. Motion capture is widely used for data-driven animation in sports,medicine and entertainment, because of its ability to capture complex and realistic
motions. Due to its efficiency and cost, methods for reusing collections of motion capture...
Many applications in surveillance, monitoring, scientific discovery, and data cleaning require the identification of anomalies. Although many methods have been developed to identify statistically significant anomalies, a more difficult task is to identify anomalies that are both interesting and statistically significant. Category detection is an emerging area of machine learning...
We consider the problem of tactical assault planning in real-time strategy games where a team of friendly agents must launch an assault on an enemy. This problem offers many challenges including a highly dynamic and uncertain environment, multiple agents, durative actions, numeric attributes, and different optimization objectives. While the dynamics...
Markov models are commonly used for joint inference of label sequences. Unfortunately, inference scales quadratically in the number of labels, which is problematic for training methods where inference is repeatedly preformed and is the primary computational bottleneck for large label sets. Recent work has used output coding to address this...
Ensuring correctness of real-world software applications is a challenging task. Testing can be used to find many bugs, but is typically not sufficient for proving correctness or even eliminating entire classes of bugs. However, formal proof and verification techniques tend to be very heavy weight and are simply not available...
Open source software has become a powerful force in the world of computing. While once confined to the domain of technical specialists, people of all types have begun to adopt this software – from the casual web-surfer who uses Firefox, to the professional web developer who codes in PHP or...
