Physical Sciences and Mathematics Commons^™

Design Of Environment Aware Planning Heuristics For Complex Navigation Objectives, Carter D. Bailey

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

A heuristic is the simplified approximations that helps guide a planner in deducing the best way to move forward. Heuristics are valued in many modern AI algorithms and decision-making architectures due to their ability to drastically reduce computation time. Particularly in robotics, path planning heuristics are widely leveraged to aid in navigation and exploration. As the robotic platform explores and navigates, information about the world can and should be used to augment and update the heuristic to guide solutions. Complex heuristics that can account for environmental factors, robot capabilities, and desired actions provide optimal results with little wasted exploration, but …

Syntax Exercises And Their Effect On Computational Thinking, Marina Johnson

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Abstract—Job opportunities and the need for programmers are increasing. Companies are looking for new hires who have the ability to learn how to learn, who have computational thinking skills. Student dropout rate in computer science is the highest among college majors. Educators are striving to find a way to teach efficiently and effectively the technical and the problem solving skills students need. In this paper we will be studying the effects of syntax exercises on a subject’s ability to think computationally and precisely. We tested our process on professionals and students. Half of the professionals were in the computer science …

Programming Process, Patterns And Behaviors: Insights From Keystroke Analysis Of Cs1 Students, Raj Shrestha

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

With all the experiences and knowledge, I take programming as granted. But learning to program is still difficult for a lot of introductory programming students. This is also one of the major reasons for a high attrition rate in CS1 courses. If instructors were able to identify struggling students then effective interventions can be taken to help them. This thesis is a research done on programming process data that can be collected non-intrusively from CS1 students when they are programming. The data and their findings can be leveraged in understanding students’ thought process, detecting patterns and identifying behaviors that could …

A Computer Programming Intervention For Second Grade Math Students, Eric B. Bagley

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The multiplication algorithms taught to elementary students are made to help students find answers quickly, but why the algorithm works and how it relates to multiplication is not widely known. For example, one intuitive meaning of multiplication is that of iterated, or, repeated, addition. In this paper, we look at the ways a visual, block-based, programming activity uses the concept of iteration to help second-graders learn multiplication. The results of the study observing second-grade students use visual programming and iteration to setup and solve multiplication story problems. We found that generally students enjoyed these activities and found them helpful during …

Development Of A Machine Learning-Based Financial Risk Control System, Zhigang Hu

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

With the gradual end of the COVID-19 outbreak and the gradual recovery of the economy, more and more individuals and businesses are in need of loans. This demand brings business opportunities to various financial institutions, but also brings new risks. The traditional loan application review is mostly manual and relies on the business experience of the auditor, which has the disadvantages of not being able to process large quantities and being inefficient. Since the traditional audit processing method is no longer suitable some other method of reducing the rate of non-performing loans and detecting fraud in applications is urgently needed …

Artificial Intelligence And Deep Reinforcement Learning Stock Market Predictions, Andrew W. Brim

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Billions of dollars are traded automatically in the stock market every day, including algorithms that use artificial intelligence (AI) techniques, but there are still questions regarding how AI trades successfully. The black box nature of these AI techniques, namely neural networks, gives pause to entrusting it with valuable trading funds. This dissertation applies AI techniques to stock market trading strategies, but it also provides exploratory research into how these techniques predict the stock market successfully.

This dissertation presents the work of three research papers. The first paper presented in this dissertation applies a artificial intelligence technique, reinforcement learning, to candlestick …

Fitting Physical Models To Spatiotemporal Observations: Discovering Developmental Regulatory Networks Of Drosophila, Dj Holt

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Deep learning continues to solve significant scientific and engineering problems, but the solutions found are neural networks with thousands of parameters that provide no scientific or engineering insights. A solution to this problem, explored in this work, is to learn mathematical models that represent mechanisms that can be interpreted by scientists and engineers.

A challenging learning problem is to discover the genetic regulatory mechanisms that drive pattern formation during early biological development. Using known mathematical models of these processes, consisting of coupled ordinary differential and partial differential equations, we aim to identify the model parameters that describe the biological mechanisms …