Barrett, The Honors College Thesis/Creative Project Collection

This thesis proposes hardware and software security enhancements to the robotic explorer of a capstone team, in collaboration with the NASA Psyche Mission Student Collaborations program. The NASA Psyche Mission, launching in 2022 and reaching the metallic asteroid of the same name in 2026, will explore from orbit what is hypothesized to be remnant core material of an early planet, potentially providing key insights to planet formation. Following this initial mission, it is possible there would be scientists and engineers interested in proposing a mission to land an explorer on the surface of Psyche to further document various properties of the asteroid. As a proposal for a second mission, an interdisciplinary engineering and science capstone team at Arizona State University designed and constructed a robotic explorer for the hypothesized surfaces of Psyche, capable of semi-autonomously navigating simulated surfaces to collect scientific data from onboard sensors. A critical component of this explorer is the command and data handling subsystem, and as such, the security of this system, though outside the scope of the capstone project, remains a crucial consideration. This thesis proposes the pairing of Trusted Platform Module (TPM) technology for increased hardware security and the implementation of SELinux (Security Enhanced Linux) for increased software security for Earth-based testing as well as space-ready missions.

Edge computing is a new and growing market that Company X has an opportunity to expand their presence. Within this paper, we compare many external research studies to better quantify the Total Addressable Market of the Edge Computing space. Furthermore, we highlight which Segments within Edge Computing have the most opportunities for growth, along with identify a specific market strategy that Company X could do to capture market share within the most opportunistic segment.

Suitcases packed, armed with a PowerPoint presentation of matrices and frameworks, and an eloquent vocabulary of “synergies” and “core competencies,” another consultant prepares to deliver million-dollar advice to some of the leading executives of Fortune 500 companies. We all know who they are, but we have no idea what they do. In 2019, over 20% of the graduating MBA class from Harvard university chose to pursue management consulting, a number that has been progressively increasing from years prior. With over 300 million people in the United States, and another 8 billion across the globe, a decision is being made every nano-second. From which stock to buy to which color socks to purchase, to every innovative (and incompetent) decision made, consultants have a hand in it all. While consultants contribute a healthy service in stimulating the economy and keeping big business, in business, there are a multitude of pitfalls that can occur in the profession and have drastic legal and ethical implications. <br/> To further examine this dichotomy of theoretical versus applied consulting, I decided to put my consulting skills to the test. By partnering with the New Venture Group, we delivered consulting services to Marni Anbar, the founder and creator of the DiscoverRoom, a hands-on, self-directed initiative allowing students to explore their curiosity in fields ranging from evolutionary studies to geology and astronomy. In response to the DiscoverRoom’s increasing demand and capacity to grow, New Venture Group consultants engaged with Marni Anbar in an attempt to analyze the important question of “what steps (from a business perspective) should Marni consider to further the DiscoverRoom (in a way that can make it both profitable and continue to serve as a creative space to further child development)?” <br/> This project was a hands-on way to examine the fundamentally complicated relationship that exists between consultants and their clients, and whether or not it was possible for college students to advise an initiative to remove the disparities that exist in STEM education in one of the worst-rated states for public school education in the country. By applying the research and findings uncovered when analyzing the theory of management consulting to this real life engagement, several parallels were discovered. As in the case of many consultants, our solution was never implemented due to external factors, which further creates a gap in allowing us to analyze whether or not our proposed solutions contained any value or not. As seen in our case, consultants often fall victim to not having their solution implemented due to a variety of external environmental trends and factors. This “incomplete” understanding of the picture further creates an aura of skepticism behind consultants and the work they do.

Radiation hardening of electronic devices is generally necessary when designing for the space environment. Non-volatile memory technologies are of particular concern when designing for the mitigation of radiation effects. Among other radiation effects, single-event upsets can create bit flips in non-volatile memories, leading to data corruption. In this paper, a Verilog implementation of a Reed-Solomon error-correcting code is considered for its ability to mitigate the effects of single-event upsets on non-volatile memories. This implementation is compared with the simpler procedure of using triple modular redundancy.

Every communication system has a receiver and a transmitter. Irrespective if it is wired or wireless.The future of wireless communication consists of a massive number of transmitters and receivers. The question arises, can we use computer vision to help wireless communication? To satisfy the high data requirement, a large number of antennas are required. The devices that employ large-antenna arrays have other sensors such as RGB camera, depth camera, or LiDAR sensors.These vision sensors help us overcome the non-trivial wireless communication challenges, such as beam blockage prediction and hand-over prediction.This is further motivated by the recent advances in deep learning and computer vision that can extract high-level semantics from complex visual scenes, and the increasing interest of leveraging machine/deep learning tools in wireless communication problems.[1] <br/><br/>The research was focused solely based on technology like 3D cameras,object detection and object tracking using Computer vision and compression techniques. The main objective of using computer vision was to make Milli-meter Wave communication more robust, and to collect more data for the machine learning algorithms. Pre-build lossless and lossy compression algorithms, such as FFMPEG, were used in the research. An algorithm was developed that could use 3D cameras and machine learning models such as YOLOV3, to track moving objects using servo motors and low powered computers like the raspberry pi or the Jetson Nano. In other words, the receiver could track the highly mobile transmitter in 1 dimension using a 3D camera. Not only that, during the research, the transmitter was loaded on a DJI M600 pro drone, and then machine learning and object tracking was used to track the highly mobile drone. In order to build this machine learning model and object tracker, collecting data like depth, RGB images and position coordinates were the first yet the most important step. GPS coordinates from the DJI M600 were also pulled and were successfully plotted on google earth. This proved to be very useful during data collection using a drone and for the future applications of position estimation for a drone using machine learning. <br/><br/>Initially, images were taken from transmitter camera every second,and those frames were then converted to a text file containing hex-decimal values. Each text file was then transmitted from the transmitter to receiver, and on the receiver side, a python code converted the hex-decimal to JPG. This would give an efect of real time video transmission. However, towards the end of the research, an industry standard, real time video was streamed using pre-built FFMPEG modules, GNU radio and Universal Software Radio Peripheral (USRP). The transmitter camera was a PI-camera. More details will be discussed as we further dive deep into this research report.

Lossy compression is a form of compression that slightly degrades a signal in ways that are ideally not detectable to the human ear. This is opposite to lossless compression, in which the sample is not degraded at all. While lossless compression may seem like the best option, lossy compression, which is used in most audio and video, reduces transmission time and results in much smaller file sizes. However, this compression can affect quality if it goes too far. The more compression there is on a waveform, the more degradation there is, and once a file is lossy compressed, this process is not reversible. This project will observe the degradation of an audio signal after the application of Singular Value Decomposition compression, a lossy compression that eliminates singular values from a signal’s matrix.

The PPP Loan Program was created by the CARES Act and carried out by the Small Business Administration (SBA) to provide support to small businesses in maintaining their payroll during the Coronavirus pandemic. This program was approved for $350 billion, but this amount was expanded by an additional $320 billion to meet the demand by struggling businesses, since initial funding was exhausted under two weeks.<br/><br/>Significant controversy surrounds the program. In December 2020, the Department of Justice reported 90 individuals were charged for fraudulent use of funds, totaling $250 million. The loans, which were intended for small business, were actually approved for 450 public companies. Furthermore, the methods of approval are<br/>shrouded in mystery. In an effort to be transparent, the SBA has released information about loan recipients. Conveniently, the SBA has released information of all recipients. Detailed information was released for 661,218 recipients who have received a PPP loan in excess of $150,000. These recipients are the central point of this research.<br/><br/>This research sought to answer two primary questions: how did the SBA determine which loans, and therefore which industries are approved, and did the industries most affected by the pandemic receive the most in PPP loans, as intended by Congress? It was determined that, generally, PPP Loans were approved on the basis of employment percentages relative to the individual state. Furthermore, in general, the loans approved were approved fairly, with respect to the size of the industry. The loans, when adjusted for GDP and Employment factors, yielded a clear ranking that prioritized vulnerable industries first.<br/><br/>However, significant questions remain. The effectiveness of the PPP has been hindered by unclear incentives and negative outcomes, characterized by a government program that has essentially been rushed into service. Furthermore, limitations of available data to regress and compare the SBA's approved loans are not representative of small business.

Self-efficacy in engineering, engineering identity, and coping in engineering have been shown in previous studies to be highly important in the advancement of one’s development in the field of engineering. Through the creation and deployment of a 17 question survey, undergraduate and first year masters students were asked to provide information on their engagement at their university, their demographic information, and to rank their level of agreement with 22 statements relating to the aforementioned ideas. Using the results from the collected data, exploratory factor analysis was completed to identify the factors that existed and any correlations. No statistically significant correlations between the identified three factors and demographic or engagement information were found. There needs to be a significant increase in the data sample size for statistically significant results to be found. Additionally, there is future work needed in the creation of an engagement measure that successfully reflects the level and impact of participation in engineering activities beyond traditional coursework.

Student academic performance has far-reaching implications not only on individual students but also the universities and colleges they attend. Student academic performance can affect their time in school as well as their future earning potential, and colleges and universities have a shared interest in the academic performance and retention of their students as many state and federal funding opportunities consider these metrics when allocating taxpayer dollars. To assist in the mutual desire for students to succeed, the Calm Connection start-up venture formed with the goal of integrating biofeedback therapy with a student’s unique education needs. For students, one of the largest barriers to effective learning is issues of focus and information retention, and the repeated use of biofeedback therapy trains students to overcome these focus issues and works in conjunction with our app’s study aid and scheduling ability.