Computer Engineering Commons^™

Flexible Strain Gauge Sensors As Real-Time Stretch Receptors For Use In Biomimetic Bpa Muscle Applications, Rochelle Jubert

Student Research Symposium

This work presents a novel approach to real-time length sensing for biomimetic Braided Pneumatic Actuators (BPAs) as artificial muscles in soft robotics applications. The use of artificial muscles enables the development of more interesting robotic designs that no longer depend on single rotation joints controlled by motors. Developing robots with these capabilities, however, produces more complexities in control and sensing. Joint encoders, the mainstay of robotic feedback, can no longer be used, so new methods of sensing are needed to get feedback on muscle behavior to implement intelligent controls. To address this need, flexible strain gauge sensors from Portland company, …

Estimating Effects Of Tourism Using Multiple Data Sources: The Miranda Tool As Part Of A Spatial Decision Support System For Sustainable Destination Development, Tobias Heldt

GSTC Academic Symposium - In conjunction with the GSTC Global Conference Sweden April 23, 2024

Planning for sustainable mobility and destination development in rural areas is increasingly important when tourism grows in numbers. A key to address the challenge of transformation and adaptation of local communities to mitigate adverse effects in seasonal peak hours like traffic congestion, power failure, waste management and sewage flooding, is to properly estimate the number of visitors to a destination.

The problem of estimating tourism numbers is a known challenge since, for example, guest nights statistics are in-complete and non-commercial lodging (sharing solutions) are increasing. Recently, the promising utilization of mobile phone data has emerged as a means to estimate …

A Design Science Approach To Investigating Decentralized Identity Technology, Janelle Krupicka

Cybersecurity Undergraduate Research Showcase

The internet needs secure forms of identity authentication to function properly, but identity authentication is not a core part of the internet’s architecture. Instead, approaches to identity verification vary, often using centralized stores of identity information that are targets of cyber attacks. Decentralized identity is a secure way to manage identity online that puts users’ identities in their own hands and that has the potential to become a core part of cybersecurity. However, decentralized identity technology is new and continually evolving, which makes implementing this technology in an organizational setting challenging. This paper suggests that, in the future, decentralized identity …

Breast Cancer Classification With Machine Learning, Rahanuma Tarannum

ATU Research Symposium

Breast cancer is one of the foremost causes of death amongst women worldwide. Breast tumours are characteristically classified as either benign (non-cancerous) or malignant (cancerous). Benign tumours do not spread external side of the breast and are not fatal, whereas malignant tumours can metastasize and be incurable if untreated. Rapidly and accurate diagnosis of malignant tumours is significant for efficient treatment and advanced outcomes. In 2022, breast cancer claimed 670 000 lives worldwide. Women without any particular risk factors other than age and sex account for half of all cases of breast cancer. In 157 out of 185 nations, breast …

Advisync: A Dynamic Academic Course Scheduler, Spencer M. Anderson, Wilson Escobar, Devin Scott Sandlin, Nathan Patrick Doyle

ATU Research Symposium

Academic advising at universities can be a tedious and disorganized process for both students and advisors. Each advisor may have several dozen advisees to manage each semester, and each individual student has unique sets of classes they need to take to graduate. This might lead to scheduling errors. These errors can put the student behind in their degree, thus extending the time it takes for them to graduate past financial aid periods and delay their entry into the workforce. To address this issue, we create AdviSync. It is a tool for both students and advisors that aims to provide a …

Pyroscan: Wildfire Behavior Prediction System, Derek H. Thompson, Parker A. Padgett, Timothy C. Johnson

ATU Research Symposium

During a wildfire, it is of the utmost importance to be updated about all information of the wildfire. Wind speed, wind direction and dry grass often works as fuel for the fire allowing it to spread in multiple directions. These different factors are often issues for any firefighting organization that is trying to help fight the fire. An uncontrolled wildfire is often a threat to wildlife, property, and worse, human and animal lives. In our paper, we propose an artificial intelligence (AI) powered fire tracking and prediction application utilizing Unmanned Aerial Vehicles (UAV) to inform fire fighters regarding the probability …

Pipe Conveyor System For Cylindrical Steel Pipe, Josiah Paynter, Hannah Harris, Sam Bowden, Nicolas Fuentes

Scholar Week 2016 - present

The Peddinghaus Pipe Conveyor Senior Engineering Design Team was given the task of equipping an existing conveyor system with the ability to convey cylindrical steel pipe down the system while keeping the pipe in line with the datum and passline planes and restricting axial rotation. A metal prototype was constructed out of 0.25” mild steel that can store safely underneath the existing conveyor when not in use and extend when needed to constrain the pipes. Three pneumatic cylinders to actuate the main arm of the prototype were equipped with a polyurethane-coated roller to hold the pipe against both the conveyor …

League Of Learning: Deep Learning For Soccer Action Video Classification, Musfikur Rahaman

ATU Research Symposium

The field of sports video analysis using deep learning is rapidly advancing. Proper classification and analysis of sports videos are essential to manage the growing sports media content. It offers numerous benefits for the media, advertising, analytics, and education sectors. Soccer, also known as football, worldwide, is among the most popular sports. This research study used a deep learning-based approach for soccer action detection. Deep learning has become a popular machine learning technique, especially for image and video classification. We have used the SoccerAct dataset, which consists of ten soccer actions like corner, foul, freekick, goal kick, long pass, on …

Analyzing The Impact Of Socioeconomic Factors On Cancer Clinical Trials Accessibility In The U.S. Using Machine Learning, Krysta L. Ray, Hiromi Honda

ATU Research Symposium

While cancer impacts all segments of the United States population, specific groups experience a disproportionate burden of the disease due to social, environmental, and economic disadvantages. This research examines the correlation between socioeconomic factors and the accessibility of cancer clinical trials across U.S. counties, employing a comprehensive dataset, County-Level Socioeconomic and Cancer Clinical Trial Data from Noah Ripper, and advanced machine-learning techniques. Our findings, derived from regression analysis and machine learning models like gradient boosting, highlight significant disparities in trial availability linked to socioeconomic indicators, including poverty rates, population estimates, median income, incidence rates, and mortality rates. Many regression models …

Enhancing Disease Detection In South Asian Freshwater Fish Aquaculture Through Convolutional Neural Networks, Hayin Tamut, Musfikur Rahaman, Dr. Robin Ghosh

ATU Research Symposium

Aquaculture expansion necessitates innovative disease detection methods for sustainable production. This study investigates the efficacy of Convolutional Neural Networks (CNNs) in classifying diseases affecting South Asian freshwater fish species. The dataset comprises 1747 images representing 7 class, healthy specimens and various diseases: bacterial, fungal, parasitic, and viral. The CNN architecture includes convolutional layers for feature extraction, max-pooling layers for down sampling, dense layers for classification, and dropout layers for regularization. Training employs categorical cross-entropy loss and the Adam optimizer over 30 epochs, monitoring both training and validation performance. Results indicate promising accuracy levels, with the model achieving 92.14% and test …

Predictive Ai Applications For Sar Cases In The Us Coast Guard, Joshua Nelson

Cybersecurity Undergraduate Research Showcase

This paper explores the potential integration of predictive analytics AI into the United States Coast Guard's (USCG) Search and Rescue Optimal Planning System (SAROPS) for deep sea and nearshore search and rescue (SAR) operations. It begins by elucidating the concept of predictive analytics AI and its relevance in military applications, particularly in enhancing SAR procedures. The current state of SAROPS and its challenges, including complexity and accuracy issues, are outlined. By integrating predictive analytics AI into SAROPS, the paper argues for streamlined operations, reduced training burdens, and improved accuracy in locating drowning personnel. Drawing on insights from military AI applications …

Revolutionizing Feature Selection: A Breakthrough Approach For Enhanced Accuracy And Reduced Dimensions, With Implications For Early Medical Diagnostics, Shabia Shabir Khan, Majid Shafi Kawoosa, Bonny Bannerjee, Subhash C. Chauhan, Sheema Khan

Research Symposium

Background: The system's performance may be impacted by the high-dimensional feature dataset, attributed to redundant, non-informative, or irrelevant features, commonly referred to as noise. To mitigate inefficiency and suboptimal performance, our goal is to identify the optimal and minimal set of features capable of representing the entire dataset. Consequently, the Feature Selector (Fs) serves as an operator, transforming an m-dimensional feature set into an n-dimensional feature set. This process aims to generate a filtered dataset with reduced dimensions, enhancing the algorithm's efficiency.

Methods: This paper introduces an innovative feature selection approach utilizing a genetic algorithm with an ensemble crossover operation …

Text Summarization, Varun Gottam, Anusha Vunnam, Purna Sarovar Puvvada

Symposium of Student Scholars

The current era is known as the information era. Every day, millions of gigabytes of data are being transferred from one point to another. As the creation of data became easy, it became hard to keep track of the important points and the gist of data especially in areas such as research and news. To solve this conundrum, text summarization is introduced. This is a process of summarizing text from across different documents or large datasets such that it can be read and understood easily by both humans and machines.

Securing Edge Computing: A Hierarchical Iot Service Framework, Sajan Poudel, Nishar Miya, Rasib Khan

Posters-at-the-Capitol

Title: Securing Edge Computing: A Hierarchical IoT Service Framework

Authors: Nishar Miya, Sajan Poudel, Faculty Advisor: Rasib Khan, Ph.D.

Department: School of Computing and Analytics, College of Informatics, Northern Kentucky University

Abstract:

Edge computing, a paradigm shift in data processing, faces a critical challenge: ensuring security in a landscape marked by decentralization, distributed nodes, and a myriad of devices. These factors make traditional security measures inadequate, as they cannot effectively address the unique vulnerabilities of edge environments. Our research introduces a hierarchical framework that excels in securing IoT-based edge services against these inherent risks.

Our secure by design approach prioritizes …

Motivations Driving Video Research Podcasts: Impact On Value And Creation Of Research Video Presentations, My Doan, Anh Tran, Na Le

Posters-at-the-Capitol

Abstract

Purpose: The purpose of the study is to better understand the role and impact of video research podcasts in bridging the gap between academia and the general public, especially concerning the challenges of accessibility and comprehension of scholarly research.

Methods: A 10-question survey was administered to evaluate the effectiveness, utility, and acceptance of video recordings in research presentations. The survey also aimed to gather insights into the motivations, challenges, and benefits of using video podcasts for research dissemination. Results were then analyzed using the Unified Theory of Acceptance and Use of Technology (UTAUT) model.

Results: There were 102 respondents …

Potential Security Vulnerabilities In Raspberry Pi Devices With Mitigation Strategies, Briana Tolleson

Cybersecurity Undergraduate Research Showcase

For this research project I used a Raspberry Pi device and conducted online research to investigate potential security vulnerabilities along with mitigation strategies. I configured the Raspberry Pi by using the proper peripherals such as an HDMI cord, a microUSB adapter that provided 5V and at least 700mA of current, a TV monitor, PiSwitch, SD Card, keyboard, and mouse. I installed the Rasbian operating system (OS). The process to install the Rasbian took about 10 minutes to boot starting at 21:08 on 10/27/2023 and ending at 21:18. 1,513 megabytes (MB) was written to the SD card running at (2.5 MB/sec). …

Integrating Ai Into Uavs, Huong Quach

Cybersecurity Undergraduate Research Showcase

This research project explores the application of Deep Learning (DL) techniques, specifically Convolutional Neural Networks (CNNs), to develop a smoke detection algorithm for deployment on mobile platforms, such as drones and self-driving vehicles. The project focuses on enhancing the decision-making capabilities of these platforms in emergency response situations. The methodology involves three phases: algorithm development, algorithm implementation, and testing and optimization. The developed CNN model, based on ResNet50 architecture, is trained on a dataset of fire, smoke, and neutral images obtained from the web. The algorithm is implemented on the Jetson Nano platform to provide responsive support for first responders. …

Knowing Just Enough To Be Dangerous: The Sociological Effects Of Censoring Public Ai, David Hopkins

Cybersecurity Undergraduate Research Showcase

This paper will present the capabilities and security concerns of public AI, also called generative AI, and look at the societal and sociological effects of implementing regulations of this technology.

Kwad - Ksu All Weather Autonomous Drone, Nick Farinacci, Sebastian Gomez, Stewart Baker, Ed Sheridan

Symposium of Student Scholars

"KWAD" or "KSU all-Weather Autonomous Drone" project was sponsored by Ultool, LLC to the KSU Research and Service Foundation to create a lightweight drone capable of capturing HD video during all-weather operations. The conditions of all-weather operation include rainfall of one inch per hour and wind speeds of up to twenty miles per hour. In addition, a global minimum structural safety factor of two is required to ensure the system's integrity in extreme weather conditions. Potential mission profiles include autonomous aerial delivery, topological mapping in high moisture areas, security surveillance, search and rescue operations, emergency transportation of medical supplies, and …

Large Language Model Use Cases For Instruction, Plus A Primer On Prompt Engineering, Roy Haggerty, Justin Cochran

LSU Health New Orleans Symposium Series on Artificial Intelligence

AMA Credit Designation Statement: The Louisiana State University School of Medicine, New Orleans designates this live activity for a maximum of 1.0 AMA PRA Category 1 Credit™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

NCPD Credit Designation Statement: Nursing participants may earn 1.0 NCPD contact hours. Each nursing participant must be present for the entire session for which NCPD contact hours are requested and must complete an evaluation of the session to receive credit.

The Intersection Of Ai And Employment, Sachit Kamat

River Cities Industrial and Organizational Psychology Conference

Artificial Intelligence (AI) is rapidly transforming every industry. This session will focus on the practical applications of AI within employment hiring and succession strategies, enabling organizations to automate processes, improve efficiency, and uncover data-driven insights for enhanced decision making. We will discuss advancements using AI in the recruitment process, including the use of machine learning algorithms to screen resumes and identify successful candidates. The talk will highlight the regulatory environment and the intersection of the IO and AI fields within this rapidly evolving landscape. Additionally, the presentation will explore where AI is being used to improve organizational retention and performance. …

Data For Ai In Network Systems Workshop Report, Kuang-Ching Wang, Ron Hutchins, Anita Nikolich

Workshop on Data for AI in Network Systems

No abstract provided.

Workshop On Data For Ai In Network Systems - Event Summary, Kuang-Ching Wang, Ron Hutchins, Anita Nikolich

Workshop on Data for AI in Network Systems

No abstract provided.

Studazon, Gage Stevens, Michelle Thoi, Umangkumar Patel, Gavin Minney

Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity

Studazon is a book listing for students to list textbooks they no longer need. Studazon acts as an advertising site to help connect students who have textbooks with students who need those textbooks.

Towards Carbon-Aware Spatial Computing: Challenges And Opportunities, Bharat Jayaprakash, Matthew Eagon, Mingzhou Yang, William F. Northrop, Shashi Shekhar

I-GUIDE Forum

Carbon-aware spatial computing (CASC) is focused on reducing the carbon footprint of spatial computing itself and leveraging spatial computing techniques to minimize carbon emissions in other domains. The significance of CASC lies in its potential to mitigate anthropogenic climate change by offering numerous societal applications, such as carbon-aware supply chain development and carbon-aware site selection. CASC is challenging because of the spatiotemporal variability and the high dimensionality of carbon emissions data, involving spatial coordinates and timestamps. Related work, known as carbon-aware computing, mostly focuses on job scheduling of cloud computing, and there is a lack of surveys and review papers …

Streamlined Hpc Environments With Cvmfs And Cybergis-Compute, Alexander C. Michels, Mit Kotak, Anand Padmanabhan, Shaowen Wang

I-GUIDE Forum

High-Performance Computing (HPC) resources provide the potential for complex, large-scale modeling and analysis, fueling scientific progress over the last few decades, but these advances are not equally distributed across disciplines. Those in computational disciplines are often trained to have the necessary technical skills to utilize HPC (e.g. familiarity with the terminal), but many disciplines face technical hurdles when trying to apply HPC resources to their work. This unequal familiarity with HPC is increasingly a problem as cross-discipline teams work to tackle critical interdisciplinary issues like climate change and sustainability. CyberGIS-Compute is middle-ware designed to democratize to HPC services with the …

A Social Profile-Based E-Learning Model, Xola Ntlangula

African Conference on Information Systems and Technology

Many High Education Institutions (HEIs) have migrated to blended or complete online learning to cater for less interruption with learning. As such, there is a growing demand for personalized e-learning to accommodate the diversity of students' needs. Personalization can be achieved using recommendation systems powered by artificial intelligence. Although using student data to personalize learning is not a new concept, collecting and identifying appropriate data is necessary to determine the best recommendations for students. By reviewing the existing data collection capabilities of the e-learning platforms deployed by public universities in South Africa, we were able to establish the readiness of …

Experiences Of African Women In Stem Careers: A Systematic Literature Review., Kaluwa Siwale, Gwamaka Mwalemba, Ulrike Rivett

African Conference on Information Systems and Technology

The discourse on women's underrepresentation in science, technology, engineering, and mathematics (STEM) mainly centres on the global north, leaving a gap in understanding the perspectives of African women in STEM. To address this, a systematic literature review was conducted to explore African women's experiences in STEM careers and education. After applying inclusion and criteria, 18 published articles were analysed. 8 key issues emerge: work environment, education system, work-life balance, gender-based stereotypes, racial bias, sexual harassment, inadequate support/mentorship, and self-imposed limits. These themes intertwine, with some aspects influencing others. Grasping the complexities and interactions of these factors provides insights into challenges …

E-Wild Life Alert: Tackling The Human-Wildlife Conflict Problem, Eliel Kundai Zhuwankinyu, Sibonile Moyo, Catherine Chivasa, Smart Ncube

African Conference on Information Systems and Technology

Depletion of resources meant for both human and animal survival leads to competition for these. Human-wildlife conflict (HWC) occurs when these two parties compete for resources such as space, water, and food. If not properly managed, HWC can lead to loss of livelihoods and even loss of life. This paper discusses the design and development of an E-Wildlife Alert application that uses machine learning to detect dangerous animals. Using the Design Science Research method, a convolutional neural network is trained to build an artifact that detects five dangerous animals from an African context. The artifact is mounted on a robot …

A Customized Artificial Intelligence Based Career Choice Recommender System For A Rural University, Nosipho Carol Mavuso, Nobert Jere, Darelle Vangreunen

African Conference on Information Systems and Technology

Rapid technological developments have enabled users to be supported and guided in decision-making. An example of this is the ability of tertiary students to use technology to explore different career options and make informed decisions about their future. Notwithstanding the increasing use of technology in general, the technology for career guidance and personalized career recommendations in South Africa is still limited. There are some limiting factors such as the ever-looming challenge of limited access to technology, language barriers and cultural differences that are prevalent in rural areas. With this premise, this study collected quantitative data from students at an Eastern …