Programmers forgo existing solutions to problems in other programming lan- guages where software interoperation proves too cumbersome; they remake so- lutions, rather than reuse them. To facilitate reuse, interoperation must resolve language incompatibilities transparently. To address part of this problem, we present a model of computation that resolves incompatible lazy and eager eval- uation strategies using dual notions of evaluation contexts and values to mirror the lazy evaluation strategy in the eager one. This method could be extended to resolve incompatible evaluation strategies for any pair of languages with common expressions.

With advances in mobile phone hardware, the demand for mobile applica- tions has risen drastically. This has resulted in mobile phones becoming a pop- ular new medium for application development. However, the body of knowledge for contextual examples and tutorials leaves much to be desired. As of January 2010, California Polytechnic State University has offered a mobile development class that teaches students how to write applications for phones running Google’s Android platform. This class aims at taking advantage of students’ current in- terest in mobile applications to teach them about difficult computer science topics. As a corollary, the class hopes to foster and encourage a sense of inde- pendence and entrepreneurship through having students design, implement, and publish their own applications to the Android Application Marketplace. The main contribution of this thesis project comes in the form of a series of detailed educational laboratory exercises and a system for grading student submissions in an automated fashion. These labs are designed to supplement the Android documentation by providing contextual examples, activities, and tutorials. It is therefore the goal of this thesis project to aid in transforming the class of mobile development students into a group of successful, practicing, mobile developers.

Systems of linear equations are central to many science and engineering application domains. Given the abundance of low-cost parallel processing fabrics, the study of fast and accurate parallel algorithms for solving such systems is receiving attention. Fast linear solvers generally use a form of LU factorization. These methods face challenges with workload distribution and communication overhead that hinder their application in a true broadcast communication environment. Presented is an efficient framework for solving large-scale linear systems by means of a novel utilization of Cramer's rule. While the latter is often perceived to be impractical when considered for large systems, it is shown that the algorithm proposed has an order N^3 complexity with pragmatic forward and backward stability. To the best of our knowledge, this is the first time that Cramer's rule has been demonstrated to be an order N^3 process. Empirical results are provided to substantiate the stated accuracy and computational complexity, clearly demonstrating the efficacy of the approach taken. The unique utilization of Cramer's rule and matrix condensation techniques yield an elegant process that can be applied to parallel computing architectures that support a broadcast communication infrastructure. The regularity of the communication patterns, and send-ahead ability, yields a viable framework for solving linear equations using conventional computing platforms. In addition, this dissertation demonstrates the algorithm's potential for solving large-scale sparse linear systems.

In the hedonic coalition formation game model Roles Based Hedonic Games (RBHG), agents view teams as compositions of available roles. An agent's utility for a partition is based upon which role she fulfills within the coalition and which additional roles are being fulfilled within the coalition. I consider optimization and stability problems for settings with variable power on the part of the central authority and on the part of the agents. I prove several of these problems to be NP-complete or coNP-complete. I introduce heuristic methods for approximating solutions for a variety of these hard problems. I validate heuristics on real-world data scraped from League of Legends games.

Autism Spectrum Disorder makes it difficult to for a child communicate, have social interactions and go through daily life. Visual cues are often used to help a child associate an image with an event. With technology becoming more and more advanced, we now have a way to remind a child of an event with wearable technology, such as a watch. This new technology can help a child directly with the Visual Scheduling Application and various other applications. These applications allow children and their families to be easily able to keep track of the events on their schedule and notify them when an event occurs. With the Autism Management Platform and related website, a parent can easily create events to help a child throughout the day. The child can associate an image with events, allowing for a clearer understanding of what to do when an event occurs. Wearable technology has become a new way to interact with the user in a very unobtrusive manner. With this new technology, we can help associate a visual event to a child’s schedule and interrupt when needed to help make the child’s life easier on a daily basis.

An awareness of mercury (Hg) contamination in various aquatic environments around the world has increased over the past decade, mostly due to its ability to concentrate in the biota. Because the presence and distribution of Hg in aquatic systems depend on many factors (e.g., pe, pH, salinity, temperature, organic and inorganic ligands, sorbents, etc.), it is crucial to understand its fate and transport in the presence of complexing constituents and natural sorbents, under those different factors. An improved understanding of the subject will support the selection of monitoring, remediation, and restoration technologies. The coupling of equilibrium chemical reactions with transport processes in the model PHREEQC offers an advantage in simulating and predicting the fate and transport of aqueous chemical species of interest. Thus, a great variety of reactive transport problems could be addressed in aquatic systems with boundary conditions of specific interest. Nevertheless, PHREEQC lacks a comprehensive thermodynamic database for Hg. Therefore, in order to use PHREEQC to address the fate and transport of Hg in aquatic environments, it is necessary to expand its thermodynamic database, confirm it and then evaluate it in applications where potential exists for its calibration and continued validation. The objectives of this study were twofold: 1) to develop, expand, and confirm the Hg database of the hydrogeochemical PHREEQC to enhance its capability to simulate the fate of Hg species in the presence of complexing constituents and natural sorbents under different conditions of pH, redox, salinity and temperature; and 2) to apply and evaluate the new database in flow and transport scenarios, at two field test beds: Oak Ridge Reservation, Oak Ridge, TN and Everglades National Park, FL, where Hg is present and is of much concern. Overall, this research enhanced the capability of the PHREEQC model to simulate the coupling of the Hg reactions in transport conditions. It also demonstrated its usefulness when applied to field situations.

Information Extraction (IE) is the process of analyzing documents and identifying desired pieces of information within them. Many IE systems have been developed over the last couple of decades, but there is still room for improvement as IE remains an open problem for researchers. This work discusses the development of a hybrid IE system that attempts to combine the strengths of rule-based and statistical IE systems while avoiding their unique pitfalls in order to achieve high performance for any type of information on any type of document. Test results show that this system operates competitively in cases where target information belongs to a highly-structured data type and when critical contextual information is in close proximity to the target.

Pruning of indeterminate tomato plants is vital for a profitable yield and it still remains a manual process. There has been research in automated pruning of grapevines, trees, and other plants, but tomato plants have yet to be explored. Wage increases are contributing to the depleting profits of greenhouse tomato farmers. Rises in population are the driving force behind the need for efficient growing techniques. The major contribution of this thesis is a computer vision algorithm for detecting greenhouse tomato pruning points without the use of depth sensors. Given an up-close 2-D image of a tomato stem with the background excluded, the algorithm proposed in this work can detect and mark the tomato suckers.

Hand drawn ornamentation, such as floral or geometric patterns, is a tedious and time consuming task that requires much skill and training in ornamental design principles and aesthetics. Ornamental drawings both historically and presently play critical roles in all things from art to architecture; however, little work has been done in exploring their algorithmic and interactive generation. The field of computer graphics offers many algorithmic possibilities for assisting an artist in creating two-dimensional ornamental art. When computers handle the repetition and overall structure of ornament, considerable savings in time and money can result. Today, the few existing computer algorithms used to generate 2D ornament have over-generalized and over-simplified the process of ornamentation, resulting in the substitution of limited amounts of generic and static "clip art" for once personalized artistic innovations. Two possible approaches to computational ornamentation exist: interactive tools give artists instant feedback on their work while non-interactive programs can carry out complex and sometimes lengthy computations to produce mathematically precise ornamental compositions. Due to the importance of keeping an artist in the loop for the production of ornamentation, we present an application designed and implemented utilizing a user-driven global planning strategy, to help guide the generation of two-dimensional ornament. The system allows for the creation of beautiful organic ornamental 2D art which follows a user-defined curve. We present the application, the algorithmic approaches used, and the potential uses of this application.

As engineering systems grow in complexity so too must the design tools that we use evolve and allow for decision makers to efficiently ask questions of their model and obtain meaningful answers. The process of whitespace exploration has recently been developed to aid in engineering design and provide insight into a design space where traditional design exploration methods may fail. In an effort to further the research and development of whitespace exploration algorithms, a software package called Thalia has been created to allow for automated data collection and experimentation with the whitespace exploration methodology. In this work, whitespace exploration is defined and the current state of the art of whitespace exploration algorithms is reviewed. The whitespace exploration library Thalia along with a collection of benchmarking cases are described in detail. A set of experiments on the benchmark cases are run and analyzed to further understand the behavior of the algorithm and outline initial performance results which can later be used for comparison to aid in improving the methodology.