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Articles 1 - 8 of 8
Full-Text Articles in Other Electrical and Computer Engineering
Threat-Analysis Oriented Digital Twinning Of Ml-Powered Future Autonomous Weapon Systems, Thomas Neubert
Threat-Analysis Oriented Digital Twinning Of Ml-Powered Future Autonomous Weapon Systems, Thomas Neubert
Doctoral Dissertations and Master's Theses
Warfare is undergoing a rapid transformation with the integration of artificial intelligence (AI) and machine learning (ML) into autonomous weapon systems (AWS) for perception, decision support, and control. As these systems become more software-defined, their cyber attack surface expands across sensing, communications, autonomy logic, and human-machine interfaces. As human oversight diminishes, ensuring the cybersecurity, resilience, and reliability of these systems becomes critical to mission success. This thesis investigates how a digital twin-driven threat modeling framework that integrates system-centric analysis with adversary-informed methodologies can support structured cybersecurity vulnerability evaluation and defensive strategy development associated with ML-powered AWS. First, the study analyzes …
Insect Inspired Behavioral Strategies For Improving Multi-Agent System Resilience In The Presence Of Contagious Faults, James E. Hand
Insect Inspired Behavioral Strategies For Improving Multi-Agent System Resilience In The Presence Of Contagious Faults, James E. Hand
Doctoral Dissertations and Master's Theses
As Multi-Agent Systems (MASs) become increasingly involved in every aspect of everyday life the need to maintain reliability and resilience within these systems grows. However, in equal measure bad actors wishing to maliciously control or alter these systems are growing in both scale and capability. Thus, there is a present need for control schemes and agent behaviors that provide security against these threats while also avoiding large degradation in system performance as a tradeoff. Current research has covered a wide breadth of avenues and strategies that provide measurable resilience to faulted agents. However, these strategies often require group consensus, specialized …
Balloon Borne Gps-Enabled Radiosondes That Enable Simultaneous Multi-Point Atmospheric Sensing With A Single Ground Station, Peter A. Ribbens
Balloon Borne Gps-Enabled Radiosondes That Enable Simultaneous Multi-Point Atmospheric Sensing With A Single Ground Station, Peter A. Ribbens
Doctoral Dissertations and Master's Theses
Radiosondes are balloon borne atmospheric instruments that are a critical tool for understanding dynamics in the lower layers of the atmosphere. The low-cost radiosondes developed in the Space and Atmospheric Instrumentation Lab have been further developed to improve the system's use as a science-quality atmospheric instrument that is unique in its ability to simultaneously track multiple sondes with a single ground station. Sensors to measure temperature and pressure were added to improve measurements of the atmospheric state. A printed circuit board shield and 3D-printed shell were designed to make mass manufacturing possible. A thermistor-based temperature sensor was developed and tested …
Machine Learning For Intrusion Detection Into Unmanned Aerial System 6g Networks, Faisal Alrefaei
Machine Learning For Intrusion Detection Into Unmanned Aerial System 6g Networks, Faisal Alrefaei
Doctoral Dissertations and Master's Theses
Progress in the development of wireless network technology has played a crucial role in the evolution of societies and provided remarkable services over the past decades. It remotely offers the ability to execute critical missions and effective services that meet the user's needs. This advanced technology integrates cyber and physical layers to form cyber-physical systems (CPS), such as the Unmanned Aerial System (UAS), which consists of an Unmanned Aerial Vehicle (UAV), ground network infrastructure, communication link, etc. Furthermore, it plays a crucial role in connecting objects to create and develop the Internet of Things (IoT) technology. Therefore, the emergence of …
Wireless Coupled Feed Structure For Additively Manufactured Conformal Antennas, Blake Roberts
Wireless Coupled Feed Structure For Additively Manufactured Conformal Antennas, Blake Roberts
Doctoral Dissertations and Master's Theses
Due to advancements in additive manufacturing, it is possible to create electromagnetic devices that can be conformally printed directly onto 3D surfaces using conductive inks and dielectric pastes. Instance, the traditional antenna radomes that had the purpose of protecting the antenna on its inside can now become the antenna itself. With the components on the surface of the structure, instead of inside if it, a direct feed line would require cutting through dielectric layers and creating a direct electrical connection, also called vertical interconnect access (VIA). Such interconnects are frequent sources of failures, especially in applications that are subject to …
Machine Learning For Unmanned Aerial System (Uas) Networking, Jian Wang
Machine Learning For Unmanned Aerial System (Uas) Networking, Jian Wang
Doctoral Dissertations and Master's Theses
Fueled by the advancement of 5G new radio (5G NR), rapid development has occurred in many fields. Compared with the conventional approaches, beamforming and network slicing enable 5G NR to have ten times decrease in latency, connection density, and experienced throughput than 4G long term evolution (4G LTE). These advantages pave the way for the evolution of Cyber-physical Systems (CPS) on a large scale. The reduction of consumption, the advancement of control engineering, and the simplification of Unmanned Aircraft System (UAS) enable the UAS networking deployment on a large scale to become feasible. The UAS networking can finish multiple complex …
Feasibility Of Neural Networks For Maritime Visual Detection On A Mobile Platform, Robert Goring
Feasibility Of Neural Networks For Maritime Visual Detection On A Mobile Platform, Robert Goring
Doctoral Dissertations and Master's Theses
Object detection through computer vision has traditionally been difficult to reliably implement due to various lighting conditions caused by weather and time of day. Any changes in conditions can be detrimental to the detector’s ability to accurately identify objects. A modern approach implements deep learning techniques to classify and train a neural network. While highly effective, this approach can be cumbersome and computationally intensive. This project will investigate the feasibility of using deep learning to detect, classify, and track objects in near real-time while being processed on a mobile platform. I will investigate the feasibility of these processes on a …
Geometric And Pattern Recognition Combined Algorithms Applied To Digital Image Processing In Aerial Search And Rescue Applications, Jamil Efren Anaguano Correa
Geometric And Pattern Recognition Combined Algorithms Applied To Digital Image Processing In Aerial Search And Rescue Applications, Jamil Efren Anaguano Correa
Doctoral Dissertations and Master's Theses
The difficult task of generating an automated target detection system from aerial imagery can be achieved through different approaches. However, the robustness of any machine vision system lays on the implementation of vision algorithms. By combining geometric and pattern recognition algorithms, a more effective machine vision scheme is developed. Three modules-Color Identification (CIM), Color Matching (CMM), and Pattern Recognition (PRM)- work as main filters to process images and predict the location of targets based on a set templates. Multiple target detection is also accomplished by implementing a hide and seek method where all matching objects are scanned individually and isolated …