Computer Engineering Commons^™

Exploring The Psychological Consequences Of Distances In Virtual Reality, Gary D. Jacobs

Frameless

This presentation will examine common concepts of traveling between formalized spaces inside virtual reality (VR) experiences.

The common method for traveling in virtual reality is to click on an area or trigger and be transported to that location. These “teleportations”, however, remove the notion of distances from our virtual worlds. This is akin to a magic wand that eliminates the consequences of travel in VR. Often heralded as a boon for the virtual worlds we can create, wherein we can travel to far away lands without lag in time and without effort on the part of the participant. We posit …

Vr Sound Mapping: Make Sound Accessible For Dhh People In Virtual Reality Environments, Ziming Li, Roshan Peiris

Frameless

In-game audio plays an important role in enhancing the sense of reality and immersion in the gaming experience. In many games, sounds are also used to provide notifications and clues which are essential to the gameplay. However, in this case, the DHH (deaf and hard of hearing) players may fail to access the information conveyed by sounds, which degrades their gaming experience (Jain et al. 2021).

A Deep Reinforcement Learning Approach With Prioritized Experience Replay And Importance Factor For Makespan Minimization In Manufacturing, Jose Napoleon Martinez

LSU Doctoral Dissertations

In this research, we investigated the application of deep reinforcement learning (DRL) to a common manufacturing scheduling optimization problem, max makespan minimization. In this application, tasks are scheduled to undergo processing in identical processing units (for instance, identical machines, machining centers, or cells). The optimization goal is to assign the jobs to be scheduled to units to minimize the maximum processing time (i.e., makespan) on any unit.

Machine learning methods have the potential to "learn" structures in the distribution of job times that could lead to improved optimization performance and time over traditional optimization methods, as well as to adapt …

Development Of A Compliant Gripper Driven By 3 Dof Soft Robot, Derek M. Price Ii, Ricardo Ramirez, Pt Angel Tran

Symposium of Student Scholars

Industrial robots are moving toward automation, which makes it increasingly necessary to replace the functions traditionally performed by humans with robotics. Pick and place operation is a prime example of such automation. Robots that pick up and place objects mimic the human action of picking an object up and placing it in a targeted location. It has led to the development of robotic end-effectors that have a human-like feel. Grippers can be articulated in various ways depending on their application area and well-defined desired tasks. As compliant and soft links deflect more under the same load than their rigid body …

Iot Clusters Platform For Data Collection, Analysis, And Visualization Use Case, Soin Abdoul Kassif Baba M Traore

Symposium of Student Scholars

Climate change is happening, and many countries are already facing devastating consequences. Populations worldwide are adapting to the season's unpredictability they relay to lands for agriculture. Our first research was to develop an IoT Clusters Platform for Data Collection, analysis, and visualization. The platform comprises hardware parts with Raspberry Pi and Arduino's clusters connected to multiple sensors. The clusters transmit data collected in real-time to microservices-based servers where the data can be accessed and processed. Our objectives in developing this platform were to create an efficient data collection system, relatively cheap to implement and easy to deploy in any part …

Analysis Of The Internal Delays Of Various Wireless Technologies For Autonomous Vehicle Applications, Luanne Seaman

Symposium of Student Scholars

Analysis of the Internal Delays of Various Wireless Technologies for Autonomous Vehicle Applications

Poster Presentation Undergraduate Student: Luanne Seaman

Research Mentor: Dr. Billy Kihei

Autonomous vehicles use VANETs (vehicular ad-hoc networks) to communicate with the world around them. Despite the simple premise, VANETs rely on a variety of wireless technologies depending on range, internal delay, urgency of information, and other factors. Therefore, VANET algorithms will need to weigh these elements accordingly. Through this research, I hope to contribute reliable measurements of internal delay to reduce the algorithms’ complexity. To calculate internal delay, I connected two Arduinos to a STM32 Nucleo …

A Brief Literature Review For Machine Learning In Autonomous Robotic Navigation, Jake Biddy, Jeremy Evert

Student Research

Machine learning is becoming very popular in many technological aspects worldwide, including robotic applications. One of the unique aspects of using machine learning in robotics is that it no longer requires the user to program every situation. The robotic application will be able to learn and adapt from its mistakes. In most situations, robotics using machine learning is designed to fulfill a task better than a human could, and with the machine learning aspect, it can function at the highest level of efficiency and quality. However, creating a machine learning program requires extensive coding and programming knowledge that can be …

Computational Analysis Of The Synthesis Of Hydrogels Using The Diels Alder Reaction, Avery Boley

Honors Theses

No abstract provided.

Deapsecure Computational Training For Cybersecurity: Third-Year Improvements And Impacts, Bahador Dodge, Jacob Strother, Rosby Asiamah, Karina Arcaute, Wirawan Purwanto, Masha Sosonkina, Hongyi Wu

Modeling, Simulation and Visualization Student Capstone Conference

The Data-Enabled Advanced Training Program for Cybersecurity Research and Education (DeapSECURE) was introduced in 2018 as a non-degree training consisting of six modules covering a broad range of cyberinfrastructure techniques, including high performance computing, big data, machine learning and advanced cryptography, aimed at reducing the gap between current cybersecurity curricula and requirements needed for advanced research and industrial projects. By its third year, DeapSECURE, like many other educational endeavors, experienced abrupt changes brought by the COVID-19 pandemic. The training had to be retooled to adapt to fully online delivery. Hands-on activities were reformatted to accommodate self-paced learning. In this paper, …

Putin And Putnam: Interpreting Russian Military Activity Through A Three Player, Two-Level Game, Nathan M. Colvin

Modeling, Simulation and Visualization Student Capstone Conference

Is Vladimir Putin a bad strategist, perhaps irrational? Previous military activity by Russia, such as the annexation of Crimea of 2014, yielded limited international gains, at a significant economic and reputational cost. Yet as the 2022 invasion of Ukraine shows, Putin is willing to commit military power, despite the cost of sanctions and other possible retaliation. This three-player simultaneous game, originally created in June, 2021, demonstrates how domestic and international considerations of President Vladimir Putin might lead to otherwise unpredictable Russian military behavior. In this extended version of Robert Putnam’s “two-level game,” President Putin rationally uses the international venue as …

Real-Time External Labeling For Interactive Visualization In Virtual Environments, Shan Liu, Yuzhong Shen

Modeling, Simulation and Visualization Student Capstone Conference

A real-time external labeling algorithm has been developed to explore the potential for applying annotation and visualization to virtual reality environments, which manages label placement in the projections of virtual 3D models on the view plane. The approach intends to place labels with visual constraints, such as no overlapping, intersections, and occlusions, close proximity to the model parts, by adjusting external annotations' positions concerning available space in the view plane. This algorithm is based on the projected model's contour and adapts to camera viewpoint changes within interactive frame rates. It solves the visibility problem of annotations and operates in real-time …

Multi-Modality Breast Mri Segmentation Using Nn-Unet For Preoperative Planning Of Robotic Surgery Navigation, Motaz Alqaoud, John Plemmons Md, Eric Feliberti Md, Facs, Krishnanand Kaipa, Siqin Dong, Gabor Fichtinger, Yimming Xiao, Michel Audette

Modeling, Simulation and Visualization Student Capstone Conference

Segmentation of the chest region and breast tissues is essential for surgery planning and navigation. This paper proposes the foundation for preoperative segmentation based on two cascaded architectures of deep neural networks (DNN) based on the state-of-the-art nnU-Net. Additionally, this study introduces a polyvinyl alcohol cryogel (PVA-C) breast phantom based on the segmentation of the DNN automated approach, enabling the experiments of navigation system for robotic breast surgery. Multi-modality breast MRI datasets of T2W and STIR images were acquired from 10 patients. Segmentation evaluation utilized the Dice Similarity Coefficient (DSC), segmentation accuracy, sensitivity, and specificity. First, a single class labeling …

Rapid Development Of Advanced Virtual Labs For In-Person And Online Education, Yiyang Li, Pauline Delacruz, Yuzhong Shen

Modeling, Simulation and Visualization Student Capstone Conference

This abstract discusses methodologies and preliminary findings on rapid development of advanced virtual labs using modeling and simulation for in-person and online education, including rapid generation of virtual environment, integration of state-of-the-art industry leading software tools, advanced software design techniques that enables large scale software reuse, and innovative user interface design that facilitate the configuration and use of virtual labs by instructors and students. The latest design and development of the virtual lab for electronic circuits is presented.

Future Wireless Networking Experiments Escaping Simulations, Sachin Sharma, Saish Urumkar, Gianluca Fontanesi, Byrav Ramamurthy, Avishek Nag

Articles

In computer networking, simulations are widely used to test and analyse new protocols and ideas. Currently, there are a number of open real testbeds available to test the new protocols. In the EU, for example, there are Fed4Fire testbeds, while in the US, there are POWDER and COSMOS testbeds. Several other countries, including Japan, Brazil, India, and China, have also developed next-generation testbeds. Compared to simulations, these testbeds offer a more realistic way to test protocols and prototypes. In this paper, we examine some available wireless testbeds from the EU and the US, which are part of an open-call EU …

Machine Learning Based Medical Image Deepfake Detection: A Comparative Study, Siddharth Solaiyappan, Yuxin Wen

Engineering Faculty Articles and Research

Deep generative networks in recent years have reinforced the need for caution while consuming various modalities of digital information. One avenue of deepfake creation is aligned with injection and removal of tumors from medical scans. Failure to detect medical deepfakes can lead to large setbacks on hospital resources or even loss of life. This paper attempts to address the detection of such attacks with a structured case study. Specifically, we evaluate eight different machine learning algorithms, which include three conventional machine learning methods (Support Vector Machine, Random Forest, Decision Tree) and five deep learning models (DenseNet121, DenseNet201, ResNet50, ResNet101, VGG19) …

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 …

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 …