Computer Engineering Commons^™

Artificial Sociality, Simone Natale, Iliana Depounti

Human-Machine Communication

This article proposes the notion of Artificial Sociality to describe communicative AI technologies that create the impression of social behavior. Existing tools that activate Artificial Sociality include, among others, Large Language Models (LLMs) such as ChatGPT, voice assistants, virtual influencers, socialbots and companion chatbots such as Replika. The article highlights three key issues that are likely to shape present and future debates about these technologies, as well as design practices and regulation efforts: the modelling of human sociality that foregrounds it, the problem of deception and the issue of control from the part of the users. Ethical, social and cultural …

Mediatization And Human-Machine Communication: Trajectories, Discussions, Perspectives, Andreas Hepp, Göran Bolin, Andrea L. Guzman, Wiebke Loosen

Human-Machine Communication

As research fields, mediatization and Human-Machine Communication (HMC) have distinct historical trajectories. While mediatization research is concerned with the fundamental interrelation between the transformation of media and communications and cultural and societal changes, the much younger field of HMC delves into human meaning-making in interactions with machines. However, the recent wave of “deep mediatization,” characterized by an increasing emphasis on general communicative automation and the rise of communicative AI, highlights a shared interest in technology’s role within human interaction. This introductory article examines the trajectories of both fields, demonstrating how mediatization research “zooms out” from overarching questions of societal and …

A Spatial Data Framework For Indoor Positioning Using Machine Learning Techniques, Venkateswari P

Theses and Dissertations

The last few years have seen an increase in interest in indoor positioning and localization as potential research and development areas. WiFi is a strong substitute that supports positioning based on indoor floor plans. In this thesis, the Principal Featured - Kohonen Deep Structure (PF-KDS) model is developed to position WiFi devices more accurately and efficiently for indoor floor planning. Initially, spatial data analysis is conducted using the Principal Feature Enhanced Auto-Encoder algorithm, extracting principal features for dimensionality reduction.

Following this, the Kohonen Self- Organizing Deep Structured Learning technique is devised for precise position estimation by considering a new path …

Energy-Aware Vehicle Routing Problem, Derek Redmond

Student Research Symposium

Outline

• Motivation
• The Vehicle Routing Problem (VRP)
• Solution Techniques
• Ant Colony Optimization
• Current Work
• Future Work

Multi Base Station Energy Efficient Cluster-Aware Routing For Wireless Sensor Networks With Realtime Data Backup, Martinaa M

Theses and Dissertations

Wireless Sensor Networks (WSNs) is created, stemming from their applications in distinct areas. This research focuses on implementing an efficient clustering and routing protocols to maximize the lifespan of the WSN by proposing a novel method known as the Energy Efficient Cluster-aware Routing Protocol (EECR). The proposed method comprises of three steps: cluster formation, cluster head (CH) selection, and multi-hop data transmission. The factors needed are residual energy, the minimum distance to the base station (BS), and the minimum Load Count as given in the Energy and Distance CH selection algorithm. The shortest pathway is estimated by the Energy Route …

Stiffness And Strength-Based Concurrent Shape And Fiber Path Optimization Of Continuous Fiber Composites, Zhelong He, Ali Tamijani

Publications

A computer-implemented method of optimizing a computer model including a shape and a fiber path for a continuous fiber composite can include initializing a fixed finite element mesh. The method can also include creating an updated version of the shape and the fiber path by iterating updates of the shape and the fiber path using the fixed finite element mesh. The method can also include initializing an adapted finite element mesh on the updated version of the shape and the fiber path. The method can also include creating an optimized version of the shape and the fiber path by iterating …

Trend Tour, Aaron Ancheta, Khushboo Gupta, Xiomara Quinonez

Computer Science and Engineering Senior Theses

Choosing outfits as a college student can prove challenging – especially for new college students and students new to the area where their college is. Trend Tour, our web-based application, displays what the fashion trends are in the user's college and near their area. This helps the user with ideas on how to dress. Furthermore, the user can change the color, silhouette, and/or accessories of outfits they want to see at that college and near their area. This web application aims to help college students feel more confident and comfortable.

First-Year Engineering Students And Genai: Experience, Attitudes, Trust, And Ethics., Elisabeth Thomas, Cenetria Crockett, Campbell Rightmyer Bego

Undergraduate Research Events

Generative AI (GenAI) has the potential to benefit student learning by offering personalized feedback, idea generation, research, and analysis support, writing aid, and administrative support (Chan and Hu, 2023; Zhang, 2023). However, if used inappropriately, the same tools can lead to false/biased content creation and reduced ethical awareness leading to possible academic dishonesty and privacy issues (Schwartz, 2016; Wu, 2023). At this early stage, ethical standards and professorial guidance are unavailable, so it is important to understand what students are thinking about the recent technologies (Shen et al., 2013). Spring 2023 survey results revealed that some students used ChatGPT, a …

Automated Fabrication Workcell, Kira Hofelmann, Amy Kiyama, Alexander Torres, Cameron Mcginnis, Samuel Lim

Computer Science and Engineering Senior Theses

There is a rise of automation in the workplace, everywhere from automated manufacturing to biomedical fields, and more. These technologies are becoming increasingly accessible for customers to use and explore. Going into this project, we were curious to see if automation could be brought into our University, and applied to the Maker space. Furthermore, as these technologies are becoming more readily available, they remain fairly costly. Thus, we have created a functioning, small-scale workcell that produces a variety of small products in large batches while remaining low cost, reliable, and accessible to those who want to learn more and create …

Optimising The Fashion E-Commerce Journey: A Data-Driven Approach To Customer Retention, Hasna Luthfiana Fadhila, Vynska Amalia Permadi, Sylvert Prian Tahalea

Knowledge Engineering and Data Science

A fashion e-commerce company offers a wide range of products from domestic and international brands that are popular with young people. However, there has been an increase in non-organically acquired customers, many of whom do not return to make repeat purchases. This has led to a higher customer churn rate, with a significant proportion of non-organically sourced customers failing to become repeat purchasers. Consequently, a churn analysis and prediction model were developed to address this issue. This paper employs the Recency, Frequency, and Monetary (RFM) framework for churn analysis and prediction. The framework is underpinned by three key dimensions: last …

Cyber Attacks Against Industrial Control Systems, Adam Kardorff

LSU Master's Theses

Industrial Control Systems (ICS) are the foundation of our critical infrastructure, and allow for the manufacturing of the products we need. These systems monitor and control power plants, water treatment plants, manufacturing plants, and much more. The security of these systems is crucial to our everyday lives and to the safety of those working with ICS. In this thesis we examined how an attacker can take control of these systems using a power plant simulator in the Applied Cybersecurity Lab at LSU. Running experiments on a live environment can be costly and dangerous, so using a simulated environment is the …

Autonomous Humanoid Soccer Robot With Ml Applications, Zichen Huang, Wesley Tu

Computer Science and Engineering Senior Theses

As the sports industry increasingly incorporates technological advancements, robotics has found a unique application in the field of soccer, traditionally dominated by human players. This transition has sparked significant interest in examining the performance and dynamics of robots in athletic contexts. In this senior design project, we focus on the development of autonomous movement, ball control, and game strategy algorithms for the NAO humanoid to play soccer. Utilizing an array of sensors and actuators, the robot is designed to perform fundamental soccer skills such as dribbling and shooting. The robot is able to identify both the goal and the ball …

A Trustworthy Self-Sovereign Data And Identity Management Framework, Efat Fathalla

Electrical & Computer Engineering Theses & Dissertations

Data is a fundamental building block in the digital world, providing a basis for decision making and growth across numerous applications. In our modern world, we have become accustomed to collecting data on everything, including devices, machines, and people. The increased value of such data has led to aggressive harvesting mechanisms that prioritize data collection, storage, and pervasiveness while often disregarding security, privacy concerns, and compliance with regulations and standards. Such a pervasive attitude towards data has resulted in a loss of control, prompting concerns among individuals and mobilizing the scientific community towards advocating for data self-sovereignty.

Self-Sovereign Identity (SSI) …

Broadband Dielectric Spectroscopic Detection Of Volatile Organic Compounds With Zinc Oxide And Metal-Organic Frameworks As Solid-State Sensor Materials, Papa Kojo Amoah

Electrical & Computer Engineering Theses & Dissertations

The industrial revolution drove technological progress but also increased the release of harmful pollutants, posing significant risks to human health and the environment. Volatile organic compounds (VOCs), which have various anthropogenic and natural sources, are particularly concerning due to their impact on public health, especially in urban areas. Addressing these adverse effects requires comprehensive strategies for mitigation as traditional gas sensing techniques have limitations and there is a need for innovative approaches to VOC detection.

VOCs encompass a diverse group of chemicals with high volatility, emitted from various human activities and natural sources. These compounds play a crucial role in …

Understanding The Impact Of Emergent Conflict On Communication And Team Cognition: A Multilevel Study In Engineering Teams, Francisco Cima

Engineering Management & Systems Engineering Theses & Dissertations

The development of team cognition is crucial for fostering high-performing teams. In cognitive-intensive fields like engineering, effective communication serves as a primary precursor to team knowledge development, enabling group members to effectively retrieve and utilize each other's expertise. Despite the critical role of communication, there is a lack of empirical research examining how conflict situations, which are critical emerging factors inherent to teamwork, interact with communication processes to constrain team knowledge development and utilization. This study, rooted in information processing theory, investigates how emerging conflict shapes multilevel team knowledge structures by interacting with communication processes in engineering project teams. Prior …

Reducing Bias In Cyberbullying Detection With Advanced Llms And Transformer Models, Dahana Moz Ruiz, Annaliese Watson, Anjana Manikandan, Zachary Gordon

Center for Cybersecurity

This paper delved into a comprehensive exploration of the inherent biases present in Large Language Models (LLMs) and various Transformer models, with a focus on their role in identifying and addressing instances of cyberbullying. The objective was to refine and enhance the accuracy and fairness of these models by mitigating the biases deeply ingrained in their structures. This was crucial because language models could inadvertently perpetuate and amplify existing biases present in the data they were trained on.

The Impact Of Government Data Open Platform Construction On Promoting The Development Of Digital Government: An Econometric Analysis Based On Psm Model, Taitian Mao, Tang Gan, Jinliang Chen

Journal of Scientific Information Research

[Purpose/significance]Open government data is the direction of the digital development of government, and exploring the impact of the Open Government Data Platform （OGDP） on the development of digital government is of guiding significance in advancing the goal of modernizing the national governance system and governance capacity. [Method/process]Based on the establishment or not of OGDP, this paper uses the propensity score matching method to investigate the causal relationship between OGDP construction and digital government development by using the cross-sectional data of 101 prefecture-level cities across China in 2019 as the research sample for empirical analysis. [Result/conclusion]Overcoming sample selection bias and eliminating …

Objective.Gg: Uniting Scholastic Esports, Douglas Beirne

Posters - 2024

Objective.gg is a startup recruitment platform within the scholastic esports scene that seeks to unite esports prospects with collegiate esports programs in an effective manner. Objective.gg seeks to accomplish its mission by operating an online platform that allows prospects and collegiate coaches to create their own profiles and connect with one another, building a community in the process. This platform will begin with a free tier, but additional features will be offered through a subscription-based model with two additional pricing tiers to choose from. The online platform will be supported by free online and paid in-person tournaments for Objective.gg platform …

Drivertech Vehicle Monitoring System, Sarah Aldhafeeri, Fillip Cannard, Kaitlyn Ledon, Shea Spellman

Posters - 2024

DriverTech provides critical data to shipping companies about their fleets of vehicles and drivers. This is done through their vehicle monitoring system. Unfortunately, Windows 10 is reaching end of life, and DriverTech is looking for a new software solution.

The Game Of Traffic Lights (Tgotl), Faith Chapman

Posters - 2024

“Computer Science can be applied to nearly ANY field.” In college, and high school especially, the phrase is just that—early comp. sci (CS) students don’t have realworld examples of how/where else they can use CS knowledge outside of CS focused jobs. For high school students, this a missed opportunity to plan for a career outside the obvious. One such career is in traffic lights.

U.S. traffic can be better. Engineering has a subfield dedicated to improving traffic, and part of that entails studying ways to improve traffic lights’ efficacy. Someone with CS knowledge can program a traffic simulator for data …

Use Of Mobile Technology To Identify Behavioral Mechanisms Linked To Mental Health Outcomes In Kenya: Protocol For Development And Validation Of A Predictive Model, Willie Njoroge, Rachel Maina, Frank Elena, Lukoye Atwoli, Anthony Ngugi, Srijan Sen, Stephen Wong, Linda Khakali, Andrew Aballa, James Orwa, Moses Nyongesa, Jasmit Shah, Amina Abubakar, Zul Merali

Brain and Mind Institute

Objective:This study proposes to identify and validate weighted sensor stream signatures that predict near-term risk of a major depressive episode and future mood among healthcare workers in Kenya.

Approach: The study will deploy a mobile application (app) platform and use novel data science analytic approaches (Artificial Intelligence and Machine Learning) to identifying predictors of mental health disorders among 500 randomly sampled healthcare workers from five healthcare facilities in Nairobi, Kenya.

Expectation: This study will lay the basis for creating agile and scalable systems for rapid diagnostics that could inform precise interventions for mitigating depression and ensure a healthy, resilient …

2024 (Spring) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department

ENSI Informer Magazine Archive

The ENSI Informer Magazine published in the spring of 2024.

Performing Information Extraction For Mission Engineering Applications, Samuel R. Koski

Engineering Management & Systems Engineering Theses & Dissertations

The process of extracting structured data from unstructured and semi-structured text is manual, time consuming and error prone. Current natural language processing approaches for automating this process are difficult to verify for non-trivial and context-sensitive corpora. Large Language Models (LLMs) like ChatGPT have become a subject of considerable interest, opening a promising avenue of exploration. However, there is limited evidence on the performance of LLMs for information extraction.

In this dissertation, an approach is proposed to evaluate the accuracy of Stanford OpenIE and OpenAI's ChatGPT for this purpose. This includes comparing Resource Description Framework (RDF) triples extracted by each of …

Towards A Wearable Device For Measuring Impedance Plethysmography Of The Radial Artery, Pritom Chowdhury

Dartmouth College Master’s Theses

Recent advancements in bioimpedance technology have demonstrated significant promise in the application of cardiac health monitoring. This research explores the design and development of a forearm-based wearable bioimpedance device for non-invasive measurement of heart rate and respiratory rate at an accuracy level comparable to medical-grade monitors. It utilizes a tetrapolar electrode configuration to analyze bioimpedance changes in the radial artery due to blood flow.

An ongoing aspect of this work involves the preliminary development of an embedded framework intended to integrate signal generation, acquisition, and processing within the device to achieve compact and efficient system design, anticipated to contribute to …

Preserving Location Authenticity: Multi-Sensor System To Thwart Gps Spoofing In Self-Driving Vehicles, Peng Jiang

Electrical & Computer Engineering Theses & Dissertations

The ubiquity of the Global Positioning System (GPS) has cemented its role as the cornerstone for an array of location-based services and navigation systems, spanning applications from autonomous vehicles and drones to maritime vessels and wearable technology. Nonetheless, ensuring the integrity of reported geographical coordinates poses a formidable challenge, owing to the proliferation of diverse GPS spoofing tools. This predicament is compounded by the pervasive availability of tools like Fake GPS, Lockito, and software-defined radios, enabling even unsophisticated users to commandeer and disseminate counterfeit GPS coordinates. This dissertation undertakes the task of devising an encompassing and resilient framework, integrating a …

Time Series Models For Predicting Application Gpu Utilization And Power Draw Based On Trace Data, Dorothy Xiaoshuang Parry

Electrical & Computer Engineering Theses & Dissertations

This work explores collecting performance metrics and leveraging various statistical and machine learning time series predictive models on a memory-intensive application, Inception v3. Trace data collected using nvidia-smi measured GPU utilization and power draw for two runs of Inception3. Experimental results from the statistical and machine learning-based time series predictive algorithms showed that the predictions from statistical-based models were unable to capture the complex changes in the trace data. The Probabilistic TNN model provided the best results for the power draw trace, according to the test evaluation metrics. For the GPU utilization trace, the RNN models produced the most accurate …

Random Forest Algorithm To Measure The Air Pollution Standard Index, Ariyono Setiawan, Untung Lestari Wibowo, Ahmad Mubarok, Khoirunnisa Larasati

Knowledge Engineering and Data Science

This study uses the Random Forest algorithm to measure and predict the Air Pollution Standard Index (APSI) at Blimbing Banyuwangi Airport. Air pollution data, including concentrations of O3, CO, NO2, SO2, PM2.5, and PM10, were collected from air monitoring stations at the airport from April 15-30, 2024. APSI measurement followed established formulas by relevant authorities. Data analysis utilized statistical approaches and computational algorithms. The findings reveal that air quality at the airport is generally "Moderate," with occasional "Good" days. The Random Forest algorithm effectively predicts APSI based on existing pollution data. These results provide insights for improving air pollution management …

Computational Modeling And Analysis Of Facial Expressions And Gaze For Discovery Of Candidate Behavioral Biomarkers For Children And Young Adults With Autism Spectrum Disorder, Megan Anita Witherow

Electrical & Computer Engineering Theses & Dissertations

Facial expression production and perception in autism spectrum disorder (ASD) suggest the potential presence of behavioral biomarkers that may stratify individuals on the spectrum into prognostic or treatment subgroups. High-speed internet and the ease of technology have enabled remote, scalable, affordable, and timely access to medical care, such as measurements of ASDrelated behaviors in familiar environments to complement clinical observation. Machine and deep learning (DL)-based analysis of video tracking (VT) of expression production and eye tracking (ET) of expression perception may aid stratification biomarker discovery for children and young adults with ASD. However, there are open challenges in 1) facial …

Implementation Of Path Planning Methods To Detect And Avoid Gps Signal Degradation In Urban Environments, Ayush Raminedi

Doctoral Dissertations and Master's Theses

In the modern world, various missions are being carried out under the assistance of autonomous flight vehicles due to their ability to operate in a wide range of flight conditions. Regardless, these autonomous vehicles are prone to GPS signal loss in urban environments due to obstructions that cause scintillation, multi-path, and shadowing. These effects that decrease the GPS functionality can deteriorate the accuracy of GPS positioning causing losses in signal tracking leading to a decrease in navigation performance. These effects are modeled into the simulation environment and are used as part of the path planning algorithm to provide better navigation …

State Omniscience For Cooperative Local Catalog Maintenance Of Close Proximity Satellite Systems, Chris Hays

Doctoral Dissertations and Master's Theses

Resiliency in multi-agent system navigation is reliant on the inherent ability of the system to withstand, overcome, or recover from adverse conditions and disturbances. In large part, resiliency is achieved through reducing the impact of critical failure points to the success and/or performance of the system. In this view, decentralized multi-agent architectures have become an attractive solution for multi-agent navigation, but decentralized architectures place the burden of information acquisition directly on the agents themselves. In fact, the design of distributed estimators has been a growing interest to enable complex multi-sensor/multi-agent tasks. In such scenarios, it is important that each local …