Evaluating Virtual Reality And Artificial Intelligence As Solutions For Delayed Flight Progress In Aviation Pilot Training

Three studies in this dissertation examined a topic centered around delayed flight progress in aviation pilot training. Study one explored the impact of nonconcurrent flight laboratory training on the academic outcomes of collegiate aviation students, while studies two and three explored virtual reality and artificial intelligence as potential solutions to help alleviate the strain of delayed flight progress on the flight training organization. In the first study (n = 144), it was found that concurrent enrollment in an aviation classroom ground course and flight training laboratory positively impacts the mean academic block exam scores of students. In study two (n = 120), virtual reality was shown to be an effective training technology in the quantitative measure of pilot performance, as well as the qualitative measures of acceptance and adoption of the technology. Finally, the third study (n = 37) showed that an artificial intelligence-based flight instructor performs comparably to a human flight instructor, when transferring a student pilot’s skills from the simulator to the aircraft. Findings from each of these studies are valuable for flight training organizations looking to find ways of better preparing their student pilots and supplementing the strain of reduced flight instructor staffing within the organization

PYDAC: A DISTRIBUTED RUNTIME SYSTEM AND PROGRAMMING MODEL FOR A HETEROGENEOUS MANY-CORE ARCHITECTURE

Heterogeneous many-core architectures that consist of big, fast cores and small, energy-efficient cores are very promising for future high-performance computing (HPC) systems. These architectures offer a good balance between single-threaded perfor- mance and multithreaded throughput. Such systems impose challenges on the design of programming model and runtime system. Specifically, these challenges include (a) how to fully utilize the chip’s performance, (b) how to manage heterogeneous, un- reliable hardware resources, and (c) how to generate and manage a large amount of parallel tasks. This dissertation proposes and evaluates a Python-based programming framework called PyDac. PyDac supports a two-level programming model. At the high level, a programmer creates a very large number of tasks, using the divide-and-conquer strategy. At the low level, tasks are written in imperative programming style. The runtime system seamlessly manages the parallel tasks, system resilience, and inter- task communication with architecture support. PyDac has been implemented on both an field-programmable gate array (FPGA) emulation of an unconventional het- erogeneous architecture and a conventional multicore microprocessor. To evaluate the performance, resilience, and programmability of the proposed system, several micro-benchmarks were developed. We found that (a) the PyDac abstracts away task communication and achieves programmability, (b) the micro-benchmarks are scalable on the hardware prototype, but (predictably) serial operation limits some micro-benchmarks, and (c) the degree of protection versus speed could be varied in redundant threading that is transparent to programmers

McNair Research Journal

Full issue of the Georgia Southern University McNair Journal presented by the Ronald E. McNair Post-Baccalaureate Achievement Program at Georgia Southern University. Understanding Charter Schools: An Alternative Education Program for Students Quail T. Arnold; Dorothy A. Battle, PhD. The Reality of Aversive Racism Christina Clarke; Jerome Steffen PhD. Where Did the Water Go? An Experimental Look into the Light Path of a Mirage Lisa DeBeer; Mark Edwards, PhD. Minorities As The Majority: The Overrepresentation of African American Students in Special Education Penny Teachy-Gary; Rosemari Stallworth-Clark PhD. Wireless Sensor Tracking Network-TinyOS Perceptions of Rape Low Income Rural Women and Non-Compliance to Recommended Exams An Investigation of Gender Stereotyping Based on a Content Analysis of BET Commercials Preparing Engineers for Management The Black Scare: The Bureau of Investigation’s Attack on African American Radicals During the Red Scare Teacher Attachment Styles and Disciplinary Technique

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

URI Undergraduate and Graduate Course Catalog 2016-2017

This is a downloadable PDF version of the University of Rhode Island course catalog.https://digitalcommons.uri.edu/course-catalogs/1068/thumbnail.jp

URI Undergraduate and Graduate Course Catalog 2012-2013

This is a downloadable PDF version of the University of Rhode Island course catalog.https://digitalcommons.uri.edu/course-catalogs/1064/thumbnail.jp

URI Undergraduate and Graduate Course Catalog 2015-2016

This is a downloadable PDF version of the University of Rhode Island course catalog.https://digitalcommons.uri.edu/course-catalogs/1067/thumbnail.jp

Introduction to Logic Circuits & Logic Design with VHDL

The overall goal of this book is to fill a void that has appeared in the instruction of digital circuits over the past decade due to the rapid abstraction of system design. Up until the mid-1980s, digital circuits were designed using classical techniques. Classical techniques relied heavily on manual design practices for the synthesis, minimization, and interfacing of digital systems. Corresponding to this design style, academic textbooks were developed that taught classical digital design techniques. Around 1990, large-scale digital systems began being designed using hardware description languages (HDL) and automated synthesis tools. Broad-scale adoption of this modern design approach spread through the industry during this decade. Around 2000, hardware description languages and the modern digital design approach began to be taught in universities, mainly at the senior and graduate level. There were a variety of reasons that the modern digital design approach did not penetrate the lower levels of academia during this time. First, the design and simulation tools were difficult to use and overwhelmed freshman and sophomore students. Second, the ability to implement the designs in a laboratory setting was infeasible. The modern design tools at the time were targeted at custom integrated circuits, which are cost- and time-prohibitive to implement in a university setting. Between 2000 and 2005, rapid advances in programmable logic and design tools allowed the modern digital design approach to be implemented in a university setting, even in lower-level courses. This allowed students to learn the modern design approach based on HDLs and prototype their designs in real hardware, mainly field programmable gate arrays (FPGAs). This spurred an abundance of textbooks to be authored teaching hardware description languages and higher levels of design abstraction. This trend has continued until today. While abstraction is a critical tool for engineering design, the rapid movement toward teaching only the modern digital design techniques has left a void for freshman- and sophomore-level courses in digital circuitry. Legacy textbooks that teach the classical design approach are outdated and do not contain sufficient coverage of HDLs to prepare the students for follow-on classes. Newer textbooks that teach the modern digital design approach move immediately into high-level behavioral modeling with minimal or no coverage of the underlying hardware used to implement the systems. As a result, students are not being provided the resources to understand the fundamental hardware theory that lies beneath the modern abstraction such as interfacing, gate-level implementation, and technology optimization. Students moving too rapidly into high levels of abstraction have little understanding of what is going on when they click the “compile and synthesize” button of their design tool. This leads to graduates who can model a breadth of different systems in an HDL but have no depth into how the system is implemented in hardware. This becomes problematic when an issue arises in a real design and there is no foundational knowledge for the students to fall back on in order to debug the problem