Computer Engineering Commons^™

Practical Considerations And Applications For Autonomous Robot Swarms, Rory Alan Hector

LSU Doctoral Dissertations

In recent years, the study of autonomous entities such as unmanned vehicles has begun to revolutionize both military and civilian devices. One important research focus of autonomous entities has been coordination problems for autonomous robot swarms. Traditionally, robot models are used for algorithms that account for the minimum specifications needed to operate the swarm. However, these theoretical models also gloss over important practical details. Some of these details, such as time, have been considered before (as epochs of execution). In this dissertation, we examine these details in the context of several problems and introduce new performance measures to capture practical …

Performing Memory Forensics For Object Recovery From Android Application Memory, Sneha Sudhakaran

LSU Doctoral Dissertations

The analysis of application-specific behavior has become an increasingly important technique in cyber forensics and incident response. The ability to determine the precise actions taken by a user can be the difference between a successful analysis and one that fails to meet its goals. The precise actions includes URLs visited, files downloaded, messages sent and received, images viewed, and data accessed. Evidence extraction from application memory at runtime is an effective solution to successfully extract valuable objects allocated by each application, and it is evident that there is a need for more Android forensics analysis tools that support recovering evidence …

Applications For Nutrition Education In Developed And Developing Countries, Emma Allegrucci

Computer Science and Engineering Master's Theses

Food is vitally important for human beings. Without food, humanity would perish. Not only does food provide us with energy, but it also provides us with adequate nutrients so the systems throughout our body can function properly. Unfortunately, many people throughout the world, from top rated athletes to people living in impoverished areas, are either uninformed or do not have easy access to nutritional information or advice. There is a huge malnutrition epidemic among elite collegiate athletes and an even bigger malnutrition problem among the rural population of Uganda.

To solve the problem of malnourishment of collegiate athletes, I have …

Exoskeletons And The Future Of Work: Envisioning Power And Control In A Workforce Without Limits, Gavin L. Kirkwood, J. Nan Wilkenfeld, Norah E. Dunbar

Human-Machine Communication

Exoskeletons are an emerging form of technology that combines the skills of both machines and humans to give wearers the ability to complete physically demanding tasks that would be too strenuous for most humans. Exoskeleton adoption has the potential to both enhance and disrupt many aspects of work, including power dynamics in the workplace and the human-machine interactions that take place. Dyadic Power Theory (DPT) is a useful theory for exploring the impacts of exoskeleton adoption. In this conceptual paper, we extend DPT to relationships between humans and machines in organizations, as well as human-human communication where use of an …

Human-Machine Communication: Complete Volume 4

Human-Machine Communication

This is the complete volume of HMC Volume 4.

Embracing Ai-Based Education: Perceived Social Presence Of Human Teachers And Expectations About Machine Teachers In Online Education, Jihyun Kim, Kelly Merrill Jr., Kun Xu, Deanna D. Sellnow

Human-Machine Communication

Technological advancements in education have turned the idea of machines as teachers into a reality. To better understand this phenomenon, the present study explores how college students develop expectations (or anticipations) about a machine teacher, particularly an AI teaching assistant. Specifically, the study examines whether students’ previous experiences with online courses taught by a human teacher would influence their expectations about AI teaching assistants in future online courses. An online survey was conducted to collect data from college students in the United States. Findings indicate that positively experienced social presence of a human teacher helps develop positive expectations about an …

Sex With Robots And Human-Machine Sexualities: Encounters Between Human-Machine Communication And Sexuality Studies, Marco Dehnert

Human-Machine Communication

Sex robots are a controversial topic. Understood as artificial-intelligence enhanced humanoid robots designed for use in partnered and solo sex, sex robots offer ample opportunities for theorizing from a Human-Machine Communication (HMC) perspective. This comparative literature review conjoins the seemingly disconnected literatures of HMC and sexuality studies (SeS) to explore questions surrounding intimacy, love, desire, sex, and sexuality among humans and machines. In particular, I argue for understanding human-machine sexualities as communicative sexuotechnical-assemblages, extending previous efforts in both HMC and SeS for more-than-human, ecological, and more fluid approaches to humans and machines, as well as to sex and sexuality. This …

I Get By With A Little Help From My Bots: Implications Of Machine Agents In The Context Of Social Support, Austin Beattie, Andrew C. High

Human-Machine Communication

In this manuscript we discuss the increasing use of machine agents as potential sources of support for humans. Continued examination of the use of machine agents, particularly chatbots (or “bots”) for support is crucial as more supportive interactions occur with these technologies. Building off extant research on supportive communication, this manuscript reviews research that has implications for bots as support providers. At the culmination of the literature review, several propositions regarding how factors of technological efficacy, problem severity, perceived stigma, and humanness affect the process of support are proposed. By reviewing relevant studies, we integrate research on human-machine and supportive …

Considering The Context To Build Theory In Hci, Hri, And Hmc: Explicating Differences In Processes Of Communication And Socialization With Social Technologies, Andrew Gambino, Bingjie Liu

Human-Machine Communication

The proliferation and integration of social technologies has occurred quickly, and the specific technologies with which we engage are ever-changing. The dynamic nature of the development and use of social technologies is often acknowledged by researchers as a limitation. In this manuscript, however, we present a discussion on the implications of our modern technological context by focusing on processes of socialization and communication that are fundamentally different from their interpersonal corollary. These are presented and discussed with the goal of providing theoretical building blocks toward a more robust understanding of phenomena of human-computer interaction, human-robot interaction, human-machine communication, and interpersonal …

Fight For Flight: The Narratives Of Human Versus Machine Following Two Aviation Tragedies, Andrew Prahl, Rio Kin Ho Leung, Alicia Ning Shan Chua

Human-Machine Communication

This study provides insight into the relationship between human and machine in the professional aviation community following the 737 MAX accidents. Content analysis was conducted on a discussion forum for professional pilots to identify the major topics emerging in discussion of the accidents. A subsequent narrative analysis reveals dominant arguments of human versus machine as zero-sum, surrender to machines, and an epidemic of mistrust. Results are discussed in the context of current issues in human-machine communication, and we discuss what other quickly automating industries can learn from aviation’s experience.

Human-Machine Communication Scholarship Trends: An Examination Of Research From 2011 To 2021 In Communication Journals, Riley J. Richards, Patric R. Spence, Chad Edwards

Human-Machine Communication

Despite a relatively short history, the modern-day study of communication has grown into multiple subfields. To better understand the relationship between Human-Machine Communication (HMC) research and traditional communication science, this study examines the published scholarship in 28 communication-specific journals from 2011–2021 focused on human-machine communication (HMC). Findings suggest limited prior emphasis of HMC research within the 28 reviewed journals; however, more recent trends show a promising future for HMC scholarship. Additionally, HMC appears to be diverse in the specific context areas of research in the communication context. Finally, we offer future directions of research and suggestions for the development of …

Art To Influence Creativity In Algorithmic Composition, Tyler Braithwaite

Honors Theses

Advances in Recurrent Neural Network (RNN) techniques have caused an explosion of problems posed that revolve around the mass analysis and generation of sequential data, including symbolic music. Building off the work of Nathaniel Patterson’s Musical Autocomplete: An LSTM Approach, we extend this problem of continuing a composition by examining the creative impact that injecting latent-space encoded image data, specifically fine art from the WikiArt Dataset, has on the musical output of RNN architectures designed for autocomplete. For comparison purposes with Patterson, we will also be using a corpus of Erik Satie’s piano music for training, validation, and testing.

A Cascade Framework For Privacy-Preserving Point-Of-Interest Recommender System, Longyin Cui, Xiwei Wang

Computer Science Faculty Publications

Point-of-interest (POI) recommender systems (RSes) have gained significant popularity in recent years due to the prosperity of location-based social networks (LBSN). However, in the interest of personalization services, various sensitive contextual information is collected, causing potential privacy concerns. This paper proposes a cascaded privacy-preserving POI recommendation (CRS) framework that protects contextual information such as user comments and locations. We demonstrate a minimized trade-off between the privacy-preserving feature and prediction accuracy by applying a semi-decentralized model to real-world datasets.

Ransomware Incident Preparations With Ethical Considerations And Command System Framework Proposal, Stanley Mierzwa, James Drylie, Dennis Bogdan

Center for Cybersecurity

Concerns with cyber-attacks in the form of ransomware are on the mind of many executives and leadership staff in all industries. Inaction is not an option, and approaching the topic with real, honest, and hard discussions will be valuable ahead of such a possible devastating experience. This research note aims to bring thoughtfulness to the topics of ethics in the role of cybersecurity when dealing with ransomware events. Additionally, a proposed set of non-technical recovery preparation tasks are outlined to help organizations bring about cohesiveness and planning for dealing with the real potential of a ransomware event. Constraints from many …

A Component-Based Analysis For Online Proctoring, Salma Roshdy Ali

Theses and Dissertations

The switch to online learning due to the COVID-19 revealed flaws in the existing learning methods, especially with online proctored assessments. Hence, online proctoring using computers was needed for a fair evaluation. Many studies develop cheating detection systems using several approaches. However, to the best of our knowledge, none of the existing studies investigated the impact of their system components in detecting cheating behaviors. Combining system components, even if they do not significantly improve the system performance in cheating detection, can cause an overload on the system. Therefore, our goal is to investigate the system components’ impact, individually and combined, …

Machine Learning Assisted Discovery Of Shape Memory Polymers And Their Thermomechanical Modeling, Cheng Yan

LSU Doctoral Dissertations

As a new class of smart materials, shape memory polymer (SMP) is gaining great attention in both academia and industry. One challenge is that the chemical space is huge, while the human intelligence is limited, so that discovery of new SMPs becomes more and more difficult. In this dissertation, by adopting a series of machine learning (ML) methods, two frameworks are established for discovering new thermoset shape memory polymers (TSMPs). Specifically, one of them is performed by a combination of four methods, i.e., the most recently proposed linear notation BigSMILES, supplementing existing dataset by reasonable approximation, a mixed dimension (1D …

Manipulating Image Luminance To Improve Eye Gaze And Verbal Behavior In Autistic Children, Louanne Boyd, Vincent Berardi, Deanna Hughes, Franceli L. Cibrian, Jazette Johnson, Viseth Sean, Eliza Delpizzo-Cheng, Brandon Mackin, Ayra Tusneem, Riya Mody, Sara Jones, Karen Lotich

Engineering Faculty Articles and Research

Autism has been characterized by a tendency to attend to the local visual details over surveying an image to understand the gist–a phenomenon called local interference. This sensory processing trait has been found to negatively impact social communication. Although much work has been conducted to understand these traits, little to no work has been conducted to intervene to provide support for local interference. Additionally, recent understanding of autism now introduces the core role of sensory processing and its impact on social communication. However, no interventions to the end of our knowledge have been explored to leverage this relationship. This work …

Image Provenance Analysis, Daniel Moreira, William Theisen, Walter Scheirer, Aparna Bharati, Joel Brogan, Anderson Rocha

Computer Science: Faculty Publications and Other Works

The literature of multimedia forensics is mainly dedicated to the analysis of single assets (such as sole image or video files), aiming at individually assessing their authenticity. Different from this, image provenance analysis is devoted to the joint examination of multiple assets, intending to ascertain their history of edits, by evaluating pairwise relationships. Each relationship, thus, expresses the probability of one asset giving rise to the other, through either global or local operations, such as data compression, resizing, color-space modifications, content blurring, and content splicing. The principled combination of these relationships unveils the provenance of the assets, also constituting an …

Using Deep Neural Network And Transformers To Extract Graphene Compounds And Properties, Ayman Ibn Jaman

Computer Science Graduate Research Workshop

No abstract provided.

Visual Homing For Robot Teams: Do You See What I See?, Damian Lyons, Noah Petzinger

Faculty Publications

Visual homing is a lightweight approach to visual navigation which does not require GPS. It is very attractive for robot platforms with a low computational capacity. However, a limitation is that the stored home location must be initially within the field of view of the robot. Motivated by the increasing ubiquity of camera information we propose to address this line-of-sight limitation by leveraging camera information from other robots and fixed cameras. To home to a location that is not initially within view, a robot must be able to identify a common visual landmark with another robot that can be used …