Teaching and learning programming effectively is a struggle for both teachers and students. Many students struggle to read and understand code when they are first learning to code. Many students who are new to programming struggle to follow the code for numerous reasons including getting lost in all of the method calls within the code. To help with this problem of struggling students, Code Animation was developed. Code Animation is a visual and audio tool developed using HTML5, CSS, and JavaScript to trace the execution of a program. Code Animation goes through code line by line giving the user annotations and other visualizations in an attempt to better explain code to a student than if the student were to simply read the code on their own or if they were to attempt to follow along with an instructor going over it. Code Animation allows for students to go at their own pace which helps prevent students from getting lost while looking at code leading them to not understanding the rest of code or the entire program all together.

Since the effectiveness of Code Animation is untested, we will determine if Code Animation is an effective tool or not for teaching students how to understand code. We will also look to find improvements that can be made to Code Animation in order to improve it. Students will be tested on their understanding of recursion, which is a common and important programming technique that many students struggle with. Before being tested on recursion, one group of students will be shown a Code Animation explanation of a recursive program written in Java while the other group will not be shown a Code Animation explanation. Based on the results from the students, we will determine Code Animations appears to have an impact on the performance of students on the test.

In the operation of a scramjet engine, which operates at hypersonic velocities, one of the most important factors is mixing the fuel and air before the high velocity air stream through the engine blows the mixture out of the engine before it could burn. Because of the importance of rapidly mixing fuel and air within a scramjet engine, there are multiple design elements used to increase mixing. One of which is called a flame holder cavity, which is usually located behind fuel injectors, and designed with an open (length to depth ratio is less than 10) geometry to promote recirculation of the fuel and air. Additional factors which may effect the mixing within the engine are the spacing between fuel injectors, the angle of the fuel injectors, and the blowing ratio of the fuel injectors which is the ratio of fluid entering through the fuel injectors to fluid entering the engines main inlet. These three factors based around the fuel injectors are studied utilizing multiple models of as base scramjet, with modified fuel injectors to test each of these variables. Utilizing the scramjet models prepared in Solidworks, Ansys CFX could then be used to test how the modifications preformed. These tests allow the optimal combination of fuel injector spacing, angle, and blowing ratio to be found.

Modern machine learning problems require vast amounts of data to train and achieve optimal performance. Currently, the availability of data is highly reliant upon the previous existence of curated datasets or a strenuous collection process. This stifles research into innovative machine learning applications and often disproportionally affects smaller and less well-funded research teams. To address these concerns, a tool is proposed to help automate the image collection process. Composed of a graphical user interface and an adaptive network training scheme, the tool will expand access to large, individualized datasets for smaller and more inexperienced teams.

This project aimed to compare the performance of multiple different artificial intelligence training methods using their performance controlling a vehicle on a testing track. Some of the methods used in this project were a Dense Convolutional Network (DCN), Residual Neural Network (RNN). Using each of these methods, the vehicle was trained to be able to go around the track successfully, though each model had different levels of error and time to go around the track. Based on the results of speed vs errors made, the best model can be determined based on both accuracy, speed, and training time.

Aircraft are one of the most used alternatives of traveling long distances and making them safer is a global necessity. For this reason, being able to create a functional prototype where the aircraft would be capable to acquire and process information in real time from the environment generating wingtip collision detection and simulation of a collection of exteroceptive sensors is necessary in progressing air flight safety systems. The aim of this project is to design and build an electronic aircraft undercarriage composed with multiple exteroceptive sensors that will be able to determine and process digital information of the aircraft envelope, and give an analytical output represented in different visuals and active commands in order to avoid obstacles for the aircraft. This will be achieved by the new concept of Wingtip Collision Detection developed in this thesis.

Sports are not simply an entertainment source. For many, it creates a sense of community, support, and trust among both fans and athletes alike. In order to continue the sense of community sports provides, athletes must be properly cared for in order to perform at the highest level possible. Thus, their fitness and health must be monitored continuously. In a professional sense, one can expect individualized attention to athletes daily due to an abundance of funding and resources. However, when looking at college communities and student athletes within them, the number of athletes per athletic trainer increases due to both limited funds and resources. Athletic trainers are responsible for athlete care but can be overwhelmed with high ratios of athletes per athletic trainer. Thus, the question comes into play, how can adequate monitoring of student athletes’ health and fitness levels be implemented on a consistent basis to ensure appropriate exercise regimens are being followed to allow for maximum performance? In order to help alleviate this issue, a web application was developed to ensure student athletes are getting appropriate accommodations and exercise routines needed on an individualized basis. The algorithm used assesses the activity and fitness levels of each student athlete through user input and evaluates what type of exercise regimen is needed based on various factors discussed throughout this paper. After the deployment of this application, it was found to be effective in monitoring students’ health and fitness levels.

The main goal of this research project is to determine the effectiveness of commercially available air filters and to compare different kinds of commercially available air filters in certain categories. With recent record-breaking wildfires and the Covid-19 pandemic, research on the effects and features of nanoparticles has become increasingly important. Inhalation of nanoparticles in smoke can result in severe health effects on humans, affecting especially the respiratory system. As nanoparticles can pass through cell membranes, absorption occurs rapidly and affects many different parts and functions of the human body. While air filters are an effective method of reducing small-sized particles in flowing air, current filtration standards only apply to larger scaled microparticles, and filtration efficiencies for nanoparticles are often unknown.

A good understanding of the effectiveness of air filters and masks is crucial to prevent inhalation of nanoparticles. Using a wind tunnel and two different types of woodsmokes, the penetration rates of nanoparticles through air filters were determined. Tests were performed with four different air filters using woodsmoke from hickory and applewood pallets. Due to outliers affecting mean and standard deviation values, a JavaScript code was written to eliminate outliers from the data sets. Trials with hickory smoke provided more consistent results than with applewood smoke. Average filtration effectiveness using hickory smoke was relatively close for all air filters at around 50%. Results from applewood smoke were relatively inconsistent. Due to a wide range of data and high standard deviations, effectiveness could not be established precisely.

As society continues to globalize and advance in complexity, the increased demand for the business aviation has caused the travel rate of airlines globally to increase with each year. With this continual increase in aviation travel, the Federal Aviation Administration (FAA) predicts that the fuel consumption rate is to increase by 1.6 percent as of the year 2025. While this increase in fuel consumption is a positive trait of a thriving aviation community, concerns also arise regarding increased greenhouse gas emissions and enlarged contributions to the global greenhouse effect. The most destructive greenhouse gasses associated with jet engine emissions are carbon dioxide, nitrogen oxide, water vapor (which is a key aspect to contrail formation), and small carbon soot particulates. A solution to this growing issue is the use of synthetic fuels as an alternative to traditional fossil fuels seeing that synthetic fuels have a much cleaner carbon footprint. The research performed in this paper will focus on the Noise, Vibrations, and Harshness (NVH) studies paired with the emissions analysis of synthetic fuels along an turbo jet engine. The efficiency analysis of the synthetic fuels used in this research will be completed through the application of high precision measurement microphones, accelerometers, and emissions analyzers which are able to detect the sounds, vibrations, and levels of greenhouse gasses output by the jet engine.

This research concerns climate change mitigation technologies through the investigations of sustainable alternative fuels. The test fuels are analyzed in order to observe the correlation of ignition delay (ID), combustion delay (CD), the negative temperature coefficient region (NTC), and the low temperature heat release region (LTHR), in a constant volume combustion chamber (CVCC) in relation to blended amounts of iso-paraffinic kerosene (IPK) by mass with Jet-A and their derived cetane numbers (DCN). All testing utilizes the ASTM standard D7668-14.a in a PAC CID 510 CVCC. The DCN is calculated using the ID and CD measured over 15 combustion events. The fuel blends investigated were 75%Jet-A blended with 25%IPK, 50%Jet-A50%IPK, and 25%Jet-A75%IPK. The ID of neat Jet-A and IPK are 3.26ms and 5.31ms, respectively, and the CD of the fuels are 5.00ms and 17.17 ms, respectively. The ID between the 75%Jet-A25%IPK, 50%Jet-A50%IPK, 25%Jet-A75% IPK, blends are 3.5ms, 3.8ms, and 4.2ms, respectively. The CD between the 75%Jet-A25%IPK, 50%Jet-A50%IPK, 25%Jet-A75% IPK, blends are 5.8ms, 7.0ms, and 9.4ms, respectively. The DCNs of the following blends were 43.1, 38.7, and 33.5, respectively. The % difference of each of the fuel blends DCN compared to neat Jet-A is: 10.7%, for 75%Jet-A25%IPK, 21.5% for 50%Jet-A50%IPK, and 35.6% for 25%Jet-A75%IPK. Blends with larger amounts by mass of IPK resulted in extended ignition and combustion delays. It is concluded in the apparent heat release rate (AHRR) of each of these fuel blends, that the blends that have larger amounts of IPK blended within them have extended NTC regions, LTHR regions, and decreased ringing intensity during combustion.