Flexible Strain Gauge Sensors As Real-Time Stretch Receptors For Use In Biomimetic Bpa Muscle Applications, 2024 Portland State University
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, …
Automatic Speech Recognition For Air Traffic Control Using Convolutional Lstm, 2024 California State University, San Bernardino
Automatic Speech Recognition For Air Traffic Control Using Convolutional Lstm, Sakshi Nakashe
Electronic Theses, Projects, and Dissertations
The need for automatic speech recognition in air traffic control is critical as it enhances the interaction between the computer and human. Speech recognition helps to automatically transcribe the communication between the pilots and the air traffic controllers, which reduces the time taken for administrative tasks. This project aims to provide improvement to the Automatic Speech Recognition (ASR) system for air traffic control by investigating the impact of convolution LSTM model on ASR as suggested by previous studies. The research questions are: (Q1) Comparing the performance of ConvLSTM with other conventional models, how does ConvLSTM perform with respect to recognizing …
Diegetic Sonification For Low Vision Gamers, 2024 Kennesaw State University
Diegetic Sonification For Low Vision Gamers, Jhané Dawes
Master's Theses
There are not many games designed for all players that provide accommodations for low vision users. This means that low vision users may not get to engage with the gaming community in the same way as their sighted peers. In this thesis, I explore how diegetic sonification can be used as a tool to support these low vision gamers in the typical gaming environment. I asked low vision players to engage with a prototype game level with two diegetic sonification techniques applied, without the use of their corrective lenses. I found that participants had more enjoyment and experienced less difficulty …
Side Channel Detection Of Pc Rootkits Using Nonlinear Phase Space, 2024 University of South Alabama
Side Channel Detection Of Pc Rootkits Using Nonlinear Phase Space, Rebecca Clark
Poster Presentations
Cyberattacks are increasing in size and scope yearly, and the most effective and common means of attack is through malicious software executed on target devices of interest. Malware threats vary widely in terms of behavior and impact and, thus, effective methods of detection are constantly being sought from the academic research community to offset both volume and complexity. Rootkits are malware that represent a highly feared threat because they can change operating system integrity and alter otherwise normally functioning software. Although normal methods of detection that are based on signatures of known malware code are the standard line of defense, …
Side Channel Detection Of Pc Rootkits Using Nonlinear Phase Space, 2024 University of South Alabama
Side Channel Detection Of Pc Rootkits Using Nonlinear Phase Space, Rebecca Clark
Undergraduate Honors Theses
Cyberattacks are increasing in size and scope yearly, and the most effective and common means of attack is through malicious software executed on target devices of interest. Malware threats vary widely in terms of behavior and impact and, thus, effective methods of detection are constantly being sought from the academic research community to offset both volume and complexity. Rootkits are malware that represent a highly feared threat because they can change operating system integrity and alter otherwise normally functioning software. Although normal methods of detection that are based on signatures of known malware code are the standard line of defense, …
A Smart Hybrid Enhanced Recommendation And Personalization Algorithm Using Machine Learning, 2024 California State University - San Bernardino
A Smart Hybrid Enhanced Recommendation And Personalization Algorithm Using Machine Learning, Aswin Kumar Nalluri
Electronic Theses, Projects, and Dissertations
In today’s age of streaming services, the effectiveness and precision of recommendation systems are crucial in improving user satisfaction. This project introduces the Smart Hybrid Enhanced Recommendation and Personalization Algorithm (SHERPA) a cutting-edge machine learning approach aimed at transforming how movie suggestions are made. By combining Term Frequency Inverse Document Frequency (TF-IDF) for content based filtering and Alternating Squares (ALS) with Weighted Regularization for filtering SHERPA offers a sophisticated method for delivering tailored recommendations.
The algorithm underwent evaluation using a dataset that included over 50 million ratings from 480,000 Netflix users encompassing 17,000 movie titles. The performance of SHERPA was …
Automated Brain Tumor Classifier With Deep Learning, 2024 California State University – San Bernardino
Automated Brain Tumor Classifier With Deep Learning, Venkata Sai Krishna Chaitanya Kandula
Electronic Theses, Projects, and Dissertations
Brain Tumors are abnormal growth of cells within the brain that can be categorized as benign (non-cancerous) or malignant (cancerous). Accurate and timely classification of brain tumors is crucial for effective treatment planning and patient care. Medical imaging techniques like Magnetic Resonance Imaging (MRI) provide detailed visualizations of brain structures, aiding in diagnosis and tumor classification[8].
In this project, we propose a brain tumor classifier applying deep learning methodologies to automatically classify brain tumor images without any manual intervention. The classifier uses deep learning architectures to extract and classify brain MRI images. Specifically, a Convolutional Neural Network (CNN) …
Cultural Awareness Application, 2024 California State University, San Bernardino
Cultural Awareness Application, Bharat Gupta
Electronic Theses, Projects, and Dissertations
In an increasingly interconnected global landscape, cultural awareness and competency have become indispensable skills for individuals and organizations alike. This paper introduces a pioneering cultural awareness application, grounded in the Cultural Orientation Model—a comprehensive framework devised by Dr. Walker [8]to guide individuals in understanding, appreciating, and effectively engaging with diverse cultures. The application encompasses ten primary dimensions, each representing fundamental aspects of social life shared by members of any socio-cultural environment. Through a combination of cultural education, interactive learning, guidance on cultural etiquette, and integration of cultural events, the application aims to foster empathy, tolerance, and effective cross-cultural communication skills. …
Data Engineering: Building Software Efficiency In Medium To Large Organizations, 2024 Whittier College
Data Engineering: Building Software Efficiency In Medium To Large Organizations, Alessandro De La Torre
Whittier Scholars Program
The introduction of PoetHQ, a mobile application, offers an economical strategy for colleges, potentially ushering in significant cost savings. These savings could be redirected towards enhancing academic programs and services, enriching the educational landscape for students. PoetHQ aims to democratize access to crucial software, effectively removing financial barriers and facilitating a richer educational experience. By providing an efficient software solution that reduces organizational overhead while maximizing accessibility for students, the project highlights the essential role of equitable education and resource optimization within academic institutions.
Estimating Effects Of Tourism Using Multiple Data Sources: The Miranda Tool As Part Of A Spatial Decision Support System For Sustainable Destination Development, 2024 Centre for Tourism and Leisure Research- Dalarna University
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, 2024 William & Mary
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 …
Enhancing Cybersecurity Learning Efficiency: Leveraging Spaced Repetition Systems For Rapid Adaptation, 2024 Collin College
Enhancing Cybersecurity Learning Efficiency: Leveraging Spaced Repetition Systems For Rapid Adaptation, Takudzwanashe Nyabadza
Research Week
No abstract provided.
Secure Cislunar Communication Architecture: Cryptographic Capabilities And Protocols For Lunar Missions, 2024 Collin College
Secure Cislunar Communication Architecture: Cryptographic Capabilities And Protocols For Lunar Missions, Michael Hamblin, Bilal Abu Bakr
Research Week
The surge in lunar missions intensifies concerns about congestion and communication reliability. This study proposes a secure cislunar architecture for real-time, cross-mission information exchange. We focus on cryptographic protocols and network design for a native IPv6 cislunar transit system.
Through a review of internet and space communication advancements, we emphasize the need for a secure network, exemplified by LunaNet. A robust data transit system with encryption is crucial for a common communication infrastructure. Traditional protocols face latency challenges. We advocate for user-friendly encryption methods to address confidentiality within the CIA Triad. Integrity is maintained through cryptographic message authentication codes. Availability …
Breast Cancer Classification With Machine Learning, 2024 Rahanuma Tarannum
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, 2024 Arkansas Tech University
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, 2024 Arkansas Tech University
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, 2024 Olivet Nazarene University
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, 2024 Arkansas Tech University
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, 2024 Arkansas Tech University
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, 2024 Arkansas Tech University
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 …