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- All Subjects: Machine Learning
- Creators: Barrett, The Honors College
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
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Leveraging Machine Learning and Wireless Sensing for Robot Localization - Location Variance Analysis
Description
Object localization is used to determine the location of a device, an important aspect of applications ranging from autonomous driving to augmented reality. Commonly-used localization techniques include global positioning systems (GPS), simultaneous localization and mapping (SLAM), and positional tracking, but all of these methodologies have drawbacks, especially in high traffic indoor or urban environments. Using recent improvements in the field of machine learning, this project proposes a new method of localization using networks with several wireless transceivers and implemented without heavy computational loads or high costs. This project aims to build a proof-of-concept prototype and demonstrate that the proposed technique is feasible and accurate.
Modern communication networks heavily depend upon an estimate of the communication channel, which represents the distortions that a transmitted signal takes as it moves towards a receiver. A channel can become quite complicated due to signal reflections, delays, and other undesirable effects and, as a result, varies significantly with each different location. This localization system seeks to take advantage of this distinctness by feeding channel information into a machine learning algorithm, which will be trained to associate channels with their respective locations. A device in need of localization would then only need to calculate a channel estimate and pose it to this algorithm to obtain its location.
As an additional step, the effect of location noise is investigated in this report. Once the localization system described above demonstrates promising results, the team demonstrates that the system is robust to noise on its location labels. In doing so, the team demonstrates that this system could be implemented in a continued learning environment, in which some user agents report their estimated (noisy) location over a wireless communication network, such that the model can be implemented in an environment without extensive data collection prior to release.
Modern communication networks heavily depend upon an estimate of the communication channel, which represents the distortions that a transmitted signal takes as it moves towards a receiver. A channel can become quite complicated due to signal reflections, delays, and other undesirable effects and, as a result, varies significantly with each different location. This localization system seeks to take advantage of this distinctness by feeding channel information into a machine learning algorithm, which will be trained to associate channels with their respective locations. A device in need of localization would then only need to calculate a channel estimate and pose it to this algorithm to obtain its location.
As an additional step, the effect of location noise is investigated in this report. Once the localization system described above demonstrates promising results, the team demonstrates that the system is robust to noise on its location labels. In doing so, the team demonstrates that this system could be implemented in a continued learning environment, in which some user agents report their estimated (noisy) location over a wireless communication network, such that the model can be implemented in an environment without extensive data collection prior to release.
ContributorsChang, Roger (Co-author) / Kann, Trevor (Co-author) / Alkhateeb, Ahmed (Thesis director) / Bliss, Daniel (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
At present, the vast majority of human subjects with neurological disease are still diagnosed through in-person assessments and qualitative analysis of patient data. In this paper, we propose to use Topological Data Analysis (TDA) together with machine learning tools to automate the process of Parkinson’s disease classification and severity assessment. An automated, stable, and accurate method to evaluate Parkinson’s would be significant in streamlining diagnoses of patients and providing families more time for corrective measures. We propose a methodology which incorporates TDA into analyzing Parkinson’s disease postural shifts data through the representation of persistence images. Studying the topology of a system has proven to be invariant to small changes in data and has been shown to perform well in discrimination tasks. The contributions of the paper are twofold. We propose a method to 1) classify healthy patients from those afflicted by disease and 2) diagnose the severity of disease. We explore the use of the proposed method in an application involving a Parkinson’s disease dataset comprised of healthy-elderly, healthy-young and Parkinson’s disease patients.
ContributorsRahman, Farhan Nadir (Co-author) / Nawar, Afra (Co-author) / Turaga, Pavan (Thesis director) / Krishnamurthi, Narayanan (Committee member) / Electrical Engineering Program (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
In this project, the use of deep neural networks for the process of selecting actions to execute within an environment to achieve a goal is explored. Scenarios like this are common in crafting based games such as Terraria or Minecraft. Goals in these environments have recursive sub-goal dependencies which form a dependency tree. An agent operating within these environments have access to low amounts of data about the environment before interacting with it, so it is crucial that this agent is able to effectively utilize a tree of dependencies and its environmental surroundings to make judgements about which sub-goals are most efficient to pursue at any point in time. A successful agent aims to minimizes cost when completing a given goal. A deep neural network in combination with Q-learning techniques was employed to act as the agent in this environment. This agent consistently performed better than agents using alternate models (models that used dependency tree heuristics or human-like approaches to make sub-goal oriented choices), with an average performance advantage of 33.86% (with a standard deviation of 14.69%) over the best alternate agent. This shows that machine learning techniques can be consistently employed to make goal-oriented choices within an environment with recursive sub-goal dependencies and low amounts of pre-known information.
ContributorsKoleber, Derek (Author) / Acuna, Ruben (Thesis director) / Bansal, Ajay (Committee member) / W.P. Carey School of Business (Contributor) / Software Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This thesis dives into the world of artificial intelligence by exploring the functionality of a single layer artificial neural network through a simple housing price classification example while simultaneously considering its impact from a data management perspective on both the software and hardware level. To begin this study, the universally accepted model of an artificial neuron is broken down into its key components and then analyzed for functionality by relating back to its biological counterpart. The role of a neuron is then described in the context of a neural network, with equal emphasis placed on how it individually undergoes training and then for an entire network. Using the technique of supervised learning, the neural network is trained with three main factors for housing price classification, including its total number of rooms, bathrooms, and square footage. Once trained with most of the generated data set, it is tested for accuracy by introducing the remainder of the data-set and observing how closely its computed output for each set of inputs compares to the target value. From a programming perspective, the artificial neuron is implemented in C so that it would be more closely tied to the operating system and therefore make the collected profiler data more precise during the program's execution. The program is designed to break down each stage of the neuron's training process into distinct functions. In addition to utilizing more functional code, the struct data type is used as the underlying data structure for this project to not only represent the neuron but for implementing the neuron's training and test data. Once fully trained, the neuron's test results are then graphed to visually depict how well the neuron learned from its sample training set. Finally, the profiler data is analyzed to describe how the program operated from a data management perspective on the software and hardware level.
ContributorsRichards, Nicholas Giovanni (Author) / Miller, Phillip (Thesis director) / Meuth, Ryan (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Since Dylan Roof, a white supremacist, shot and killed nine members of a black church in Charleston on June 17, 2015, Confederate symbols have stood at the center of much controversy across the United States. Although the Confederate battle flag remains the most obvious example, the debate took a particular form in Tennessee, centering on the image of General Nathan Bedford Forrest. Born in 1822 to a poor family, he left school early to work. Although his work in the slave trade made him a millionaire, his later participation in the massacre of over 300 black soldiers at Fort Pillow in 1864 during the Civil War and association with the Ku Klux Klan cemented his reputation as a violent racist. Yet, many white Tennesseans praised him as a hero and memorialized him. This thesis examines Nathan Bedford Forrest State Park in Benton County and Forrest Park, now Health Sciences Park, in Memphis to examine what characteristics denote a controversial memorial. Specifically, I focus on the physical form, the location, and the demographics of the area, investigating how these components work together to give rise to controversy or acceptance of the memorial's image. Physical representations greatly impact the ideas associated with the memorial while racial demographics affect whether or not Forrest's representation as a hero speaks true to modern interpretations and opinions.
ContributorsFish, Caroline Rose (Author) / Longley, Rodney (Thesis director) / Suk, Mina (Committee member) / School of Historical, Philosophical and Religious Studies (Contributor) / School of Politics and Global Studies (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Space microbiology, or the study of microorganisms in space, has significant applications for both human spaceflight and Earth-based medicine. This thesis traces the evolution of the field of space microbiology since its creation in 1935. Beginning with simple studies to determine if terrestrial life could survive spaceflight, the field of space microbiology has grown to encompass a substantial body of work that is now recognized as an essential component of NASA' research endeavors. Part one provides an overview of the early period of space microbiology, from high-altitude balloon and rocket studies to work conducted during the Apollo program. Part two summarizes the current state of the field, with a specific focus on the revolutionary contributions made by the Nickerson lab at the Biodesign Institute at ASU using the NASA-designed Rotating Wall Vessel (RWV) Bioreactor. Finally, part three highlights the research I've conducted in the Nickerson lab, as well as continuing studies within the field of space microbiology.
ContributorsMcCarthy, Breanne E. (Author) / Lynch, John (Thesis director) / Foy, Joseph (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Interaction is key to education, as students who perform their own inquiry into a subject retain information longer. The field of interactive fiction, which emphasizes personal decision making and freedom of choice, is ripe for opportunity as it is relatively simple to develop and deploy to audiences of any size. However, few interactive fiction platforms exist with the openness and flexibility required for classroom use. My project attempted to create an interactive fiction platform that can be created for and engaged with by both teachers and students. This led to the creation of an interactive fiction platform that conforms to a variety of requirements, such as openness and compatibility across multiple platforms, and which can display meaningful content. This was accomplished by someone with a content area education background and only limited computer science experience, and shows promise for similar future endeavors.
ContributorsWilley, Kyle Allen (Author) / Bruhn, Karen (Thesis director) / Foy, Joseph (Committee member) / Viles, Rebecca (Committee member) / Barrett, The Honors College (Contributor) / Division of Teacher Preparation (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor)
Created2014-12
Description
The Phoenix Coyotes entered bankruptcy and NHL stewardship in 2009 because of poor initial planning, short-sighted private ownership, and geographical constraints associated with the team's location in Glendale. The subsequent sale process extended from 2009-2013 and included multiple potential suitors, municipal politics, and international finance as the NHL fought to keep the troubled franchise in Phoenix.
ContributorsPorter, Brendan Francis (Author) / Simpson, Brooks (Thesis director) / Lynch, John (Committee member) / Barrett, The Honors College (Contributor) / School of Politics and Global Studies (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor)
Created2014-12
Description
The Walt Disney Company has been a worldwide phenomenon for over half a century. Disney's animated films in particular impact a large number of individuals around the world. The fact that they rerelease popular films every few years lends to the lasting influence these movies will hold in the lives of children to come. It is important to examine the messages Disney animated films can teach children in regards to women's roles, United States history, and racial difference. This essay examines these topics as they appear in Disney's Snow White and the Seven Dwarves, The Little Mermaid, Pocahontas, and The Lion King. Lastly, it examines the potential impact these films can leave on children and suggests ways in which adults can help children analyze what they see in the media.
ContributorsMonnig, Elizabeth Ann (Author) / Baker, Aaron (Thesis director) / Sandlin, Jennifer (Committee member) / Barrett, The Honors College (Contributor) / School of Film, Dance and Theatre (Contributor) / Department of English (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor)
Created2014-12
Description
The purpose of this thesis will be to compare and contrast films made by German and American directors about World War II and the Vietnam War, respectively. First, we will provide a list of the films including a brief summary and the reasons why that specific film was chosen for this analysis. Next, we will give background information about the two wars and the time period in the respective nations. The next steps are the actual project. First, we will list the criteria for analysis and why we chose those specific items to focus on. Lastly, we will provide an analysis of each film individually; going through the criteria previously provided. After reading the thesis the reader will be able to understand how filmmaking can show the feelings and sentiments of a nation during a specific time period, like war.
ContributorsRen, Haimo (Co-author) / Ahern, Jared (Co-author) / Bradley, Christopher (Thesis director) / Forss, Brennan (Committee member) / Barrett, The Honors College (Contributor) / School of Accountancy (Contributor) / Department of Supply Chain Management (Contributor) / W. P. Carey School of Business (Contributor) / School of Politics and Global Studies (Contributor)
Created2015-05