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Articles 1 - 14 of 14
Full-Text Articles in Hardware Systems
Automatic Scoring Cornhole Board System, Eric Diffendal, Jonah Harsh, Connor Lengel, Brett Sukie
Automatic Scoring Cornhole Board System, Eric Diffendal, Jonah Harsh, Connor Lengel, Brett Sukie
Williams Honors College, Honors Research Projects
The objective is to create a self-scoring cornhole board that can detect and calculate each team's score based on the bags thrown each round and to be created at a low cost/eventually being sold at the current cost of a normal board. When playing cornhole, the game is simple: throw a bag on the board; however, the scores are variable (deduct and add) across each round. The most common issue when playing cornhole is miscalculations of the scores and forgetting the correct scores. Thus, this invention will make gameplay easy for all to play.
Fuzzing Drones For Anomaly Detection: A Systematic Literature Review, Vikas Kumar Malviya, Wei Minn, Lwin Khin Shar, Lingxiao Jiang
Fuzzing Drones For Anomaly Detection: A Systematic Literature Review, Vikas Kumar Malviya, Wei Minn, Lwin Khin Shar, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
Drones, also referred to as Unmanned Aerial Vehicles (UAVs), are becoming popular today due to their uses in different fields and recent technological advancements which provide easy control of UAVs via mobile apps. However, UAVs may contain vulnerabilities or software bugs that cause serious safety and security concerns. For example, the communication protocol used by the UAV may contain authentication and authorization vulnerabilities, which may be exploited by attackers to gain remote access over the UAV. Drones must therefore undergo extensive testing before being released or deployed to identify and fix any software bugs or security vulnerabilities. Fuzzing is one …
Brushbuds: Toothbrushing Tracking Using Earphone Imus, Qiang Yang, Yang Liu, Jake Stuchbury-Wass, Kayla-Jade Butkow, Dong Ma, Cecilia Mascolo
Brushbuds: Toothbrushing Tracking Using Earphone Imus, Qiang Yang, Yang Liu, Jake Stuchbury-Wass, Kayla-Jade Butkow, Dong Ma, Cecilia Mascolo
Research Collection School Of Computing and Information Systems
Inadequate toothbrushing habits are a leading cause of oral health problems such as tooth decay. Many individuals are uncertain if they are brushing effectively or over-focusing on specific areas. While high-end electric toothbrushes can address these concerns, manual toothbrushes remain widely used due to their simplicity and affordability. In this paper, we introduce BrushBuds, an earphone-based toothbrushing monitoring system aimed at tracking brushing areas, which leverages the ubiquitous presence of earphones to enhance manual toothbrushing. BrushBuds utilizes Inertial Measurement Units (IMUs) in earphones to detect subtle head movements incurred by toothbrushing. By capturing distinct motion patterns specific to brushing for …
Development Of Feature Extraction Models To Improve Image Analysis Applications In Cancer, Yu Shi
Development Of Feature Extraction Models To Improve Image Analysis Applications In Cancer, Yu Shi
Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–
Cancer poses a significant global health challenge. With an estimated 20 million new cases diagnosed worldwide in 2022 and 9.7 million fatalities attributable to the disease, the economic burden of cancer is immense. It impacts healthcare systems and imposes substantial costs for its care on patients and their families. Despite advancements in early detection, prevention, and treatment that have reduced overall cancer mortality rates, the growing prevalence of cancer, particularly among younger individuals, remains a pressing issue.
Recent advancements in medical imaging technology have progressed significantly with the help of emerging computer vision and artificial intelligence (AI) technology. Despite these …
Vysion Software, Isaias Hernandez-Dominguez Jr, Chander Luderman Miller
Vysion Software, Isaias Hernandez-Dominguez Jr, Chander Luderman Miller
2024 Symposium
Vision loss presents significant challenges in daily life. Existing solutions for blind and visually impaired individuals are often limited in functionality, expensive, or complex to use. Vysion Software addresses this gap by developing a user-friendly, all-in-one AI companion app that provides features including text summarization, real-time audio descriptions, and AI-enhanced navigation. This project details the development plan, initial functionalities, and future vision for Vysion Software.
Adaptive Neh With Constrained Nearest Neighbor Subtours For The Electric Vehicle Routing Problem With Time Windows, Andrew Struthers
Adaptive Neh With Constrained Nearest Neighbor Subtours For The Electric Vehicle Routing Problem With Time Windows, Andrew Struthers
All Master's Theses
The development of electric vehicles is currently considered one of the most innovative areas in manufacturing. Largely driven by the desire to reduce greenhouse emissions, electric vehicles are seen as a viable alternative to internal combustion engine cars. Starting from consumer cars, a dedicated effort is being made to translate this into commercial vehicles for freight and delivery. This research introduces a novel adaptive Nawaz, Enscore, Ham (NEH) algorithm with constrained nearest neighbor subtour (NEH-NN). This algorithm is tested on the standard benchmark problems in literature and used as a seed solution for the Genetic Algorithm (GA). The performance and …
Cross-Layer Design Of Highly Scalable And Energy-Efficient Ai Accelerator Systems Using Photonic Integrated Circuits, Sairam Sri Vatsavai
Cross-Layer Design Of Highly Scalable And Energy-Efficient Ai Accelerator Systems Using Photonic Integrated Circuits, Sairam Sri Vatsavai
Theses and Dissertations--Electrical and Computer Engineering
Artificial Intelligence (AI) has experienced remarkable success in recent years, solving complex computational problems across various domains, including computer vision, natural language processing, and pattern recognition. Much of this success can be attributed to the advancements in deep learning algorithms and models, particularly Artificial Neural Networks (ANNs). In recent times, deep ANNs have achieved unprecedented levels of accuracy, surpassing human capabilities in some cases. However, these deep ANN models come at a significant computational cost, with billions to trillions of parameters. Recent trends indicate that the number of parameters per ANN model will continue to grow exponentially in the foreseeable …
The Integration Of Neuromorphic Computing In Autonomous Robotic Systems, Md Abu Bakr Siddique
The Integration Of Neuromorphic Computing In Autonomous Robotic Systems, Md Abu Bakr Siddique
Dissertations, Master's Theses and Master's Reports
Deep Neural Networks (DNNs) have come a long way in many cognitive tasks by training on large, labeled datasets. However, this method has problems in places with limited data and energy, like when planetary robots are used or when edge computing is used [1]. In contrast to this data-heavy approach, animals demonstrate an innate ability to learn by communicating with their environment and forming associative memories among events and entities, a process known as associative learning [2-4]. For instance, rats in a T-maze learn to associate different stimuli with outcomes through exploration without needing labeled data [5]. This learning paradigm …
Characterization And Estimation Of Musculoskeletal Pain Using Machine Learning, Boluwatife Faremi
Characterization And Estimation Of Musculoskeletal Pain Using Machine Learning, Boluwatife Faremi
Master's Theses
Traditional scales utilized for recording pain are known to be highly subjective and biased due to inaccuracies in recollecting actual pain intensities. As a result, machine learning (ML) models that are trained using these scores as ground truth are reported to have low performance for objective pain classification because of the huge disparity between what was felt in moments of pain and the scores recorded afterward.
In the present study, two devices were designed for gathering real-time, continuous in-session subjective pain scores and the recording of the autonomic nervous system (ANS) altered endodermal (EDA) activity. 24 participants were recruited to …
Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)
Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)
Library Philosophy and Practice (e-journal)
Abstract
Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …
Warehouse And Logistics: Smart Picking With Vuzix Smart Glasses, Elise Hemink
Warehouse And Logistics: Smart Picking With Vuzix Smart Glasses, Elise Hemink
Frameless
Vuzix is an industry leader in augmented reality (AR) technology. We provide innovative products to an array of industries, a few being defense, security, enterprise, and consumers. Our AR technology provides a perfect balance of engagement in the digital and real worlds thanks to their innovative optics, AI apps and 5G capability.
Comparative Analysis Of Rgb-Based Eye-Tracking For Large-Scale Human-Machine Applications, Brett Thaman, Trung Cao
Comparative Analysis Of Rgb-Based Eye-Tracking For Large-Scale Human-Machine Applications, Brett Thaman, Trung Cao
Posters-at-the-Capitol
Gaze tracking has become an established technology that enables using an individual’s gaze as an input signal to support a variety of applications in the context of Human-Computer Interaction. Gaze tracking primarily relies on sensing devices such as infrared (IR) cameras. Nevertheless, in the recent years, several attempts have been realized at detecting gaze by acquiring and processing images acquired from standard RGB cameras. Nowadays, there are only a few publicly available open-source libraries and they have not been tested extensively. In this paper, we present the result of a comparative analysis that studied a commercial eye-tracking device using IR …
Signal Fingerprinting And Machine Learning Framework For Uav Detection And Identification., Olusiji Oloruntobi Medaiyese
Signal Fingerprinting And Machine Learning Framework For Uav Detection And Identification., Olusiji Oloruntobi Medaiyese
Electronic Theses and Dissertations
Advancement in technology has led to creative and innovative inventions. One such invention includes unmanned aerial vehicles (UAVs). UAVs (also known as drones) are now an intrinsic part of our society because their application is becoming ubiquitous in every industry ranging from transportation and logistics to environmental monitoring among others. With the numerous benign applications of UAVs, their emergence has added a new dimension to privacy and security issues. There are little or no strict regulations on the people that can purchase or own a UAV. For this reason, nefarious actors can take advantage of these aircraft to intrude into …
Improved Microrobotic Control Through Image Processing And Automated Hardware Interfacing, Archit R. Aggarwal, Wuming Jing, David J. Cappelleri
Improved Microrobotic Control Through Image Processing And Automated Hardware Interfacing, Archit R. Aggarwal, Wuming Jing, David J. Cappelleri
The Summer Undergraduate Research Fellowship (SURF) Symposium
Untethered submilliliter-sized robots (microrobots) are showing potential use in different industrial, manufacturing and medical applications. A particular type of these microrobots, magnetic robots, have shown improved performance in power and control capabilities compared to the other thermal and electrostatic based robots. However, the magnetic robot designs have not been assessed in a robust manner to understand the degree of control in different environments and their application feasibility. This research project seeks to develop a custom control software interface to provide a holistic tool for researchers to evaluate the microrobotic performance through advance control features. The software deliverable involved two main …