Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Engineering (5735)
- Physical Sciences and Mathematics (2950)
- Aerospace Engineering (1674)
- Electrical and Computer Engineering (1344)
- Operations Research, Systems Engineering and Industrial Engineering (1247)
-
- Computer Sciences (1236)
- Business (993)
- Physics (919)
- Operational Research (610)
- Signal Processing (459)
- Civil and Environmental Engineering (422)
- Computer Engineering (414)
- Aviation (353)
- Electrical and Electronics (351)
- Social and Behavioral Sciences (349)
- Operations and Supply Chain Management (346)
- Materials Science and Engineering (335)
- Optics (330)
- Oceanography and Atmospheric Sciences and Meteorology (279)
- Navigation, Guidance, Control and Dynamics (252)
- Other Operations Research, Systems Engineering and Industrial Engineering (233)
- Human Resources Management (231)
- Systems Engineering (229)
- Atomic, Molecular and Optical Physics (198)
- Electromagnetics and Photonics (195)
- Aerodynamics and Fluid Mechanics (188)
- Environmental Sciences (188)
- Environmental Engineering (185)
- Nuclear Engineering (180)
- Applied Mathematics (178)
- Keyword
-
- #antcenter (380)
- #csra (134)
- Machine learning (93)
- Decision making (89)
- Algorithms (75)
-
- Global Positioning System (75)
- Image processing (73)
- Kalman filtering (65)
- Optimization (64)
- #afcec (62)
- Computer networks--Security measures (62)
- Drone aircraft (59)
- Computer security (57)
- Target acquisition (57)
- Neural networks (Computer science) (54)
- Software engineering (54)
- Additive manufacturing (52)
- Remote sensing (49)
- Flight control (48)
- Microelectromechanical systems (45)
- Computer vision (44)
- Artificial satellites (43)
- Decision support systems (43)
- #ctisr (42)
- Adaptive optics (42)
- Composite materials (42)
- Neural networks (41)
- Simulation (41)
- Wireless communication systems (41)
- Scheduling (40)
- Publication Year
- Publication
- Publication Type
- File Type
Articles 841 - 870 of 8791
Full-Text Articles in Entire DC Network
Identification Of Return-Oriented Programming Attacks Using Risc-V Instruction Trace Data, Daniel F. Koranek, Scott R. Graham, Brett J. Borghetti, Wayne C. Henry
Identification Of Return-Oriented Programming Attacks Using Risc-V Instruction Trace Data, Daniel F. Koranek, Scott R. Graham, Brett J. Borghetti, Wayne C. Henry
Faculty Publications
An increasing number of embedded systems include dedicated neural hardware. To benefit from this specialized hardware, deep learning techniques to discover malware on embedded systems are needed. This effort evaluated candidate machine learning detection techniques for distinguishing exploited from non-exploited RISC-V program behavior using execution traces. We first developed a dataset of execution traces containing Return Oriented Programming (ROP) exploitation on the RISC-V Instruction Set Architecture (ISA) and then developed several deep learning bidirectional Long Short-Term Memory (LSTM) models capable of distinguishing exploited traces from non-exploited traces, each using subsets of features from the execution traces. An objective of this …
Aerial Radiation Detection Identification And Measurement System Detector Material Comparison Study, Benjamin C. Troxell, Kacey D. Mcgee, Christina L. Dugan
Aerial Radiation Detection Identification And Measurement System Detector Material Comparison Study, Benjamin C. Troxell, Kacey D. Mcgee, Christina L. Dugan
Faculty Publications
The 20th Chemical Biological Radiological Nuclear and Explosives Command (CBRNE) currently utilizes an airborne sodium iodide gamma and beta detection system to map radiation fields over large areas of interest. The 20th CBRNE explored emergent detector technologies utilizing two detection materials; thallium-activated cesium iodide and high purity germanium (HPGe). These detectors were simulated at various altitudes and compared to background measurements. The sodium iodide detector failed to provide isotopic discrimination at distance. The thallium-activated cesium iodide CsI(Tl) detector provided sufficient absolute efficiency and energy resolution to identify isotopics at distance. The HPGe detector provided the best energy resolution. However, current …
Augmenting Field Nuclear Forensics Capabilities With Handheld Atomic Spectroscopy Devices For Nuclear Debris Analysis, Ashwin P. Rao, Christopher M. Sutphin, Christina L. Dugan
Augmenting Field Nuclear Forensics Capabilities With Handheld Atomic Spectroscopy Devices For Nuclear Debris Analysis, Ashwin P. Rao, Christopher M. Sutphin, Christina L. Dugan
Faculty Publications
The realm of technical nuclear forensics remains a critical part of joint counterproliferation capabilities. Since the passage of the Nuclear Forensics and Attribution Act (H.R.730) in 2010, the nuclear science community has undertaken steps to bolster national nuclear forensics capabilities under the National Technical Nuclear Forensics Center. Within the technical nuclear forensics umbrella, one particular area of interest involves developing capabilities for in-field analysis of nuclear material. This includes engaging in field training exercises across relevant branches of the military and investigating new technologies to conduct field nuclear forensic analyses. The integration of novel analytical technologies into real-world nuclear detection …
Survivability Analysis In The Shadow Of Apollo: Part Ii - Spacecraft Charging Vulnerability Near The Stable Earth-Moon Lagrange Points, Robert A. Bettinger, Nathan R. Boone, Nicholas S. Hamilton, Bryan D. Little
Survivability Analysis In The Shadow Of Apollo: Part Ii - Spacecraft Charging Vulnerability Near The Stable Earth-Moon Lagrange Points, Robert A. Bettinger, Nathan R. Boone, Nicholas S. Hamilton, Bryan D. Little
Faculty Publications
Though the reality of routine travel and sustained operations in space likely remains several decades away, the building blocks of space exploration and space system development necessary to realize this reality are currently being laid by peer, near-peer, and emerging space-faring nations. The pursuance of sustained cislunar space operations will necessitate a renewed examination of spacecraft survivability and the capability of spacecraft to avoid and/or withstand the natural and manmade environmental risks posed by this “new” ultimate high ground.
Biomechanical And Psychological Predictors Of Failure In The Air Force Physical Fitness Test, Jeffrey Turner, Brent T. Langhals, Torrey J. Wagner
Biomechanical And Psychological Predictors Of Failure In The Air Force Physical Fitness Test, Jeffrey Turner, Brent T. Langhals, Torrey J. Wagner
Faculty Publications
Physical fitness is a pillar of U.S. Air Force (USAF) readiness and ensures that Airmen can fulfill their assigned mission and be fit to deploy in any environment. The USAF assesses the fitness of service members on a periodic basis, and discharge can result from failed assessments. In this study, a 21-feature dataset was analyzed related to 223 active-duty Airmen who participated in a comprehensive mental and social health survey, body composition assessment, and physical performance battery. Graphical analysis revealed pass/fail trends related to body composition and obesity. Logistic regression and limited-capacity neural network algorithms were then applied to predict …
Evaluating Climatic Influences On The Technical Performance Of Built Infrastructure Assets, Sarah L. Brown, Steven J. Schuldt, Michael N. Grussing, Michael A. Johnson, Justin D. Delorit
Evaluating Climatic Influences On The Technical Performance Of Built Infrastructure Assets, Sarah L. Brown, Steven J. Schuldt, Michael N. Grussing, Michael A. Johnson, Justin D. Delorit
Faculty Publications
Asset performance evaluations serve as a benchmark that can be used to make asset manufacturer selection decisions, i.e., choosing the brand of manufacturer that provides the highest performance among all brand competitors. Understanding the environmental conditions to which assets are subjected provides facility managers another data point to understand asset performance. This research builds upon a previously published performance-based manufacturer selection metric by investigating the linkage between asset performance and exposure to local climate, using chiller and air handler data from 20 United States Air Force installations. The link between environmental factors such as Heating Degree Days (HDD); Cooling Degree …
Pseudo-Modal Expansions For Generating Random Electromagnetic Beams, Milo W. Hyde Iv, Olga Korotkova
Pseudo-Modal Expansions For Generating Random Electromagnetic Beams, Milo W. Hyde Iv, Olga Korotkova
Faculty Publications
Excerpt: We derive two pseudo-modal expansions that provide insight into the structure of stationary electromagnetic sources and can be used for their physical realization and in computer simulations. Both expansions are derived from the vectorial version of Bochner’s theorem of functional analysis.
Application Of Machine Learning To Predict The Performance Of An Emipg Reactor Using Data From Numerical Simulations, Owen Sedej, Eric G. Mbonimpa, Trevor Sleight, Jeremy Slagley
Application Of Machine Learning To Predict The Performance Of An Emipg Reactor Using Data From Numerical Simulations, Owen Sedej, Eric G. Mbonimpa, Trevor Sleight, Jeremy Slagley
Faculty Publications
Microwave-driven plasma gasification technology has the potential to produce clean energy from municipal and industrial solid wastes. It can generate temperatures above 2000 K (as high as 30,000 K) in a reactor, leading to complete combustion and reduction of toxic byproducts. Characterizing complex processes inside such a system is however challenging. In previous studies, simulations using computational fluid dynamics (CFD) produced reproducible results, but the simulations are tedious and involve assumptions. In this study, we propose machine-learning models that can be used in tandem with CFD, to accelerate high-fidelity fluid simulation, improve turbulence modeling, and enhance reduced-order models. A two-dimensional …
Method Of Making Hinged Self-Referencing Fabry–Pérot Cavity Sensors, Jeremiah C. Williams, Hengky Chandrahalim
Method Of Making Hinged Self-Referencing Fabry–Pérot Cavity Sensors, Jeremiah C. Williams, Hengky Chandrahalim
AFIT Patents
A method is provided for fabricating a passive optical sensor on a tip of an optical fiber. The method includes perpendicularly cleaving a tip of an optical fiber and mounting the tip of the optical fiber in a specimen holder of a photosensitive polymer three-dimensional micromachining machine. The method includes forming a three-dimensional microscopic optical structure within the photosensitive polymer that comprises a two cavity Fabry-Perot Interferometer (FPI) having a hinged optical layer that is pivotally coupled to a suspended structure. The method includes removing an uncured portion of the photosensitive polymer using a solvent. The method includes depositing a …
A Statistical Principal Component Regression-Based Approach To Modeling The Degradative Effects Of Local Climate And Traffic On Airfield Pavement Performance, Evan M. Fortney, Steven J. Schuldt, Sarah L. Brown, James P. Allen, Justin D. Delorit
A Statistical Principal Component Regression-Based Approach To Modeling The Degradative Effects Of Local Climate And Traffic On Airfield Pavement Performance, Evan M. Fortney, Steven J. Schuldt, Sarah L. Brown, James P. Allen, Justin D. Delorit
Faculty Publications
Airfield pavement systems support the global economy, passenger travel, and national defense. Accurate pavement degradation predictions are critical inputs for maintenance and repair decisions, and when skillful, they may reduce the need for time-intensive, costly physical inspections that disrupt airfield operations. Existing airport pavement management systems (APMS) compute expected degradation as a function of pavement type and age, but they do not account for local climate and traffic conditions and they are not built to adapt to future changes in either mode of variability. This paper implements a bias-reduced statistical model that reveals the effects of local conditions using observed …
Considerations For Radio Frequency Fingerprinting Across Multiple Frequency Channels, Jose A. Gutierrez Del Arroyo, Brett J. Borghetti, Michael A. Temple
Considerations For Radio Frequency Fingerprinting Across Multiple Frequency Channels, Jose A. Gutierrez Del Arroyo, Brett J. Borghetti, Michael A. Temple
Faculty Publications
Radio Frequency Fingerprinting (RFF) is often proposed as an authentication mechanism for wireless device security, but application of existing techniques in multi-channel scenarios is limited because prior models were created and evaluated using bursts from a single frequency channel without considering the effects of multi-channel operation. Our research evaluated the multi-channel performance of four single-channel models with increasing complexity, to include a simple discriminant analysis model and three neural networks. Performance characterization using the multi-class Matthews Correlation Coefficient (MCC) revealed that using frequency channels other than those used to train the models can lead to a deterioration in performance from …
Madfam: Microarchitectural Data Framework And Methodology, Tor J. Langehaug, Scott R. Graham, Christine M. Schubert Kabban, Brett J. Borghetti
Madfam: Microarchitectural Data Framework And Methodology, Tor J. Langehaug, Scott R. Graham, Christine M. Schubert Kabban, Brett J. Borghetti
Faculty Publications
In the aftermath of Spectre and Meltdown researchers have proposed a variety of attack detection solutions by applying machine learning to data collected from hardware performance monitoring units. Although many microarchitectural attack detection systems provide high-accuracy detection results, the behavior of the underlying data collection mechanisms is not well described or understood. This research introduces the MicroArchitectural Data Framework And Methodology (MADFAM) to prescribe a systematic approach to collecting and preserving the information available in sequences of microarchitectural data. The proposed framework focuses on hardware performance counters (HPCs) as the primary data source. HPC configuration is complex, which makes it …
Development And Assessment Of A Model-Based Framework On User Toolkits, Brandon J. Koury
Development And Assessment Of A Model-Based Framework On User Toolkits, Brandon J. Koury
Theses and Dissertations
The Department of Defense (DoD) has a limited number of resources to accomplish a variety of missions which involve deploying personnel to support and maintain aircraft operating throughout the world. The DoDs maintenance structure codes maintainers to perform maintenance on specific airframes. This structure limits the flexibility of maintainers and leads to deploying resources in a reactionary manner to address capability gaps in deployed environments. The Just-In-Time Multi-Mission Airman (JIT MMA) concept aims to resolve these issues. Currently, the necessary technologies are unknown, but user toolkits are a concept to consider. A user toolkit is a concept that allows users …
Thermo-Fluidic Transport Process In A Novel M-Shaped Cavity Packed With Non-Darcian Porous Medium And Hybrid Nanofluid: Application Of Artificial Neural Network (Ann), Dipak Kumar Mandal, Nirmalendu Biswas, Nirmal K. Manna, Dilip Kumar Gayen, Rama S. R. Gorla, Ali J. Chamkha
Thermo-Fluidic Transport Process In A Novel M-Shaped Cavity Packed With Non-Darcian Porous Medium And Hybrid Nanofluid: Application Of Artificial Neural Network (Ann), Dipak Kumar Mandal, Nirmalendu Biswas, Nirmal K. Manna, Dilip Kumar Gayen, Rama S. R. Gorla, Ali J. Chamkha
Faculty Publications
In this work, an attempt has been made to explore numerically the thermo-fluidic transport process in a novel M-shaped enclosure filled with permeable material along with Al2O3-Cu hybrid nanoparticles suspended in water under the influence of a horizontal magnetizing field. To exercise the influence of geometric parameters, a classical trapezoidal cavity is modified with an inverted triangle at the top to construct an M-shaped cavity. The cavity is heated isothermally from the bottom and cooled from the top, whereas the inclined sidewalls are insulated. The role of geometric parameters on the thermal performance is scrutinized thoroughly …
Improving Anonymized Search Relevance With Natural Language Processing And Machine Learning, Niko A. Petrocelli
Improving Anonymized Search Relevance With Natural Language Processing And Machine Learning, Niko A. Petrocelli
Theses and Dissertations
Users often sacrifice personal data for more relevant search results, presenting a problem to communities that desire both search anonymity and relevant results. To balance these priorities, this research examines the impact of using Siamese networks to extend word embeddings into document embeddings and detect similarities between documents. The predicted similarity can locally re-rank search results provided from various sources. This technique is leveraged to limit the amount of information collected from a user by a search engine. A prototype is produced by applying the methodology in a real-world search environment. The prototype yielded an additional function of finding new …
Narrative Analysis Of Open-Source Social Media Activity In The Indopacom Aor, Aaron K. Glenn
Narrative Analysis Of Open-Source Social Media Activity In The Indopacom Aor, Aaron K. Glenn
Theses and Dissertations
Emotion classification can be a powerful tool to derive narratives from social media data. Recurrent Neural Networks (RNN) can meet or exceed the performance of state-of-the-art traditional machine learning techniques using exclusively open-source data and models. Specifically, these results show that RNN variants can produce more than an 8% gain in accuracy in comparison to Logistic Regression and SVM techniques and a 15% gain over Random Forest when using FastText embeddings. This research found a statistical significance in the performance of a single layer Bi-directional Long Short-Term Memory (Bi-LSTM) model over a 2-layer stacked Bi-LSTM model. This research also found …
Applications Of A Lightning Proxy To Generate Synthetic Lightning For Use In Physics-Based Image-Chain Models, Bryan G. Castro
Applications Of A Lightning Proxy To Generate Synthetic Lightning For Use In Physics-Based Image-Chain Models, Bryan G. Castro
Theses and Dissertations
A method of generating synthetic lightning through the use of a convective available potential energy (CAPE) times precipitation rate (P) proxy is applied over three distinct climatological zones of the world for a single warm season: central and southern AZ of the United States, central Cuba, and North Korea. Global Forecast System (GFS) 0.25° by 0.25° forecast data for June, July, and August of 2019 is used to provide 6-hourly CAPE and precipitation rate, while Global Lightning Dataset (GLD360) data for the period 2016 to 2020 is used to provide observed lightning strokes. A five-year lightning climatology study is conducted …
Evaluating The Military Medical Evacuation Dispatching And Delivery Problem Via Simulation And Self-Exciting Hawkes Process, Virbon B. Frial
Evaluating The Military Medical Evacuation Dispatching And Delivery Problem Via Simulation And Self-Exciting Hawkes Process, Virbon B. Frial
Theses and Dissertations
The location, allocation, and utilization of military medical evacuation (MEDEVAC) resources significantly impact the quality and timeliness of medical care to injured troops. In 2009, Secretary of Defense Robert Gates introduced the Golden Hour mandate that entails the evacuation of critically-injured troops to military treatment facilities (MTFs) within an hour to prevent further complications. To develop high-quality policies that improve MEDEVAC system performance, several papers in the current literature assume that MTFs have both the capacity and capability of treating any patient, regardless of the type of injury. However, these assumptions are unrealistic when conducting high-intensity operations. While acknowledging MTF …
Approximate Dynamic Programming For An Unmanned Aerial Vehicle Routing Problem With Obstacles And Stochastic Target Arrivals, Kassie M. Gurnell
Approximate Dynamic Programming For An Unmanned Aerial Vehicle Routing Problem With Obstacles And Stochastic Target Arrivals, Kassie M. Gurnell
Theses and Dissertations
The United States Air Force is investing in artificial intelligence (AI) to speed analysis in efforts to modernize the use of autonomous unmanned combat aerial vehicles (AUCAVs) in strike coordination and reconnaissance (SCAR) missions. This research examines an AUCAVs ability to execute target strikes and provide reconnaissance in a SCAR mission. An orienteering problem is formulated as anMarkov decision process (MDP) model wherein a single AUCAV must optimize its target route to aid in eliminating time-sensitive targets and collect imagery of requested named areas of interest while evading surface-to-air missile (SAM) battery threats imposed as obstacles. The AUCAV adjusts its …
Experimental Design On High-Speed Sliding Wear, Irene D. Liew
Experimental Design On High-Speed Sliding Wear, Irene D. Liew
Theses and Dissertations
The purpose of this research is to develop, conduct, and analyze an experimental design that characterizes wear rates of various materials sliding at high speeds along AISI 4340 steel. This work is in support of Holloman Air Force Base, which is invested in engineering a more wear-resistant rocket slipper for its high-speed test track. This research uses a design of experiments approach to systematically identify and evaluate potential slipper attributes that mitigate wear according to a heat transfer model. Final findings include recommendations of slipper materials that theoretically perform similar to or better than the baseline Vascomax®C300 maraging steel material. …
A Decision Support Simulation To Analyze Scheduling Alternatives For Applicant Processing At Military Entrance Processing Stations (Meps), Jonathan M. Escamilla
A Decision Support Simulation To Analyze Scheduling Alternatives For Applicant Processing At Military Entrance Processing Stations (Meps), Jonathan M. Escamilla
Theses and Dissertations
Applicant processing at Military Entrance Processing Stations (MEPS) is conducted via a batch arrival process by which all applicants arrive at the beginning of the processing day. Pursuit of alternate processing scenarios has never progressed beyond the pilot stage, possibly because the Command lacks a general decision support model to evaluate the impacts of proposed policies on applicant processing operations. This research creates a discrete event simulation of MEPS applicant processing operations and applies the model to three alternative applicant processing scenarios: split-shift, appointment- based, and express-lane. Results are examined and compared to benchmarks using multiple performance measurements.
Qualitative Insights On The Military Entrance Processing Station (Meps) Of Excellence Program, Brian T. Johnson
Qualitative Insights On The Military Entrance Processing Station (Meps) Of Excellence Program, Brian T. Johnson
Theses and Dissertations
The Military Entrance Processing Station (MEPS) of Excellence Program (MOE) is a program to improve operations through recognition and motivation and to sustain excellence in MEPSs core services. Quantitative MOE program data was studied using a hybrid approach of descriptive statistics, statistical process control, and logistic regression to gain relevant insights with respect to the program objectives of improvement, excellence, motivation, and recognition. Future work should employ information such as climate surveys, worker performance reports, and the civilian awards program for further insights into the MOEs effectiveness as a motivator.
A New Approach To Career Field Matching For Commissioning Air Force Cadets, Daniel Griffen Laird
A New Approach To Career Field Matching For Commissioning Air Force Cadets, Daniel Griffen Laird
Theses and Dissertations
The current method of assigning graduating cadets from the United States Air Force Academy and Reserve Officers' Training Corps (ROTC) detachments to their career fields uses an integer programming model to maximize \global" Air Force utility, subject to several Air Force-defined constraints. This utility evaluates the positive benefit of assigning a certain cadet to a certain career field. This paper discusses the issues with such a model, as well as presents a new, more refined approach to the problem. Rather than provide a one-size-fits-all formulation of this particular assignment problem, a Value-Focused Thinking (VFT) framework is applied, in conjunction with …
Optimal Aircraft Maneuvering Models For Cruise Missile Engagement: A Modeling And Computational Study, Izaiah G. Laduke
Optimal Aircraft Maneuvering Models For Cruise Missile Engagement: A Modeling And Computational Study, Izaiah G. Laduke
Theses and Dissertations
Given the increased threat and proliferation of adversary military capabilities, this research seeks to develop reasonably accurate and computationally tractable models to optimally maneuver aircraft to intercept cruise missile attacks. The research leveraged mathematical programming to model the problem, informed by constraints representing a system of (temporal) difference equations. The research began by comparing six models having alternative representations of velocity and acceleration constraints while analyzing situations with stationary targets. The Multiple Aircraft, Multiple Stationary Target Engagement Problem with Box Constraint Bounds (MAMSTEP-BC) Model yielded superior overall performance and was further analyzed through alternative mathematical programming model enhancements to create …
Comparison Of Lightning Warning Radii Distributions, Michael M. Maestas
Comparison Of Lightning Warning Radii Distributions, Michael M. Maestas
Theses and Dissertations
Previous research investigating lightning warning radii about the Cape Canaveral space launch facilities have focused on reducing these radii from either 5 nautical miles (NM) to 4 NM or from 6 NM to 5 NM depending on the structures being protected. Some of these findings have suggested the possibility of both a seasonal difference (warm versus cold) and lightning detection events (cloud-to-ground lightning (CG) or total lightning (TL)) impacting these radii and associated risk levels. Utilizing the 2017-2020 data provided by the 45th Weather Squadron at Patrick Space Force Base via the Mesoscale Eastern Range Lightning Information System (MERLIN), this …
Automated Reconstructions For The Digital Forensic Examiner Workflow, Ryan P. Montgomery
Automated Reconstructions For The Digital Forensic Examiner Workflow, Ryan P. Montgomery
Theses and Dissertations
One product of a digital forensics examination is a reconstruction of events recorded in the media. A reconstruction places all of the case relevant trace into temporal, identity and associative relationships. Creating this reconstruction is a manual and time consuming process for the examiner. This thesis presents AIER. AIER integrates automation, abstraction and visualization into the Autopsy forensic software to improve the reconstruction process. The integration utilizes a custom Autopsy ingest module to extract and abstract artifact data and an interactive graph-based timeline visualization module. These improvements to the forensic examiner workflow are evaluated through a series of use cases.
Evaluating The Use Of Boot Image Encryption On Talos Ii Architecture, Calvin M. Muramoto
Evaluating The Use Of Boot Image Encryption On Talos Ii Architecture, Calvin M. Muramoto
Theses and Dissertations
Sensitive devices operating in unprotected environments are vulnerable to hardware attacks like reverse engineering and side channel analysis. This represents a security concern because the root of trust can be invalidated through boot firmware manipulation. For example, boot data is rarely encrypted and typically travels across an accessible bus like the LPC bus, allowing data to be easily intercepted and possibly manipulated during system startup. The ash chip storing the boot data can also be removed from these devices and examined to reveal detailed boot information. This paper details an implementation of encrypting a section of the boot image and …
Monocular Camera Localization Using A Bag Of Visual Words From Virtual World Data, Joshua A. Rinaldi
Monocular Camera Localization Using A Bag Of Visual Words From Virtual World Data, Joshua A. Rinaldi
Theses and Dissertations
The Visual Localization problem is the question of how to use visual information to determine the location of the camera that captured that data. The wide availability and low price of RGB cameras has made this useful in many fields such as SLAM, SAM and AR. This research seeks to determine if a BOVW can adequately overcome repetitious features in indoor environments and be effectively incorporated into a VL pipeline.
Dds-Cerberus: Improving Security In Dds Middleware Using Kerberos Tickets, Andrew T. Park
Dds-Cerberus: Improving Security In Dds Middleware Using Kerberos Tickets, Andrew T. Park
Theses and Dissertations
The military deploys many IoT in battlefield operations to provide information on terrain and enemy combatants. It also deploys automated robots or UAVs where securing and trusting collected data is essential. Choosing the middleware that handles this message transfer is crucial for real-time operations. Networks with multiple entities, including IoT devices, UAVs, and small computers, require robust middleware facilitating message sending in real-time. Ideally, the middleware would provide QoS to handle lost packets and retransmissions in lossy environments, especially between low-power machines. DDS is a middleware that implements real-time and QoS capabilities by sending messages, not based on endpoints but …
Exploring Learning Classifier System Behaviors In Multi-Action, Turn-Based Wargames, Garth J.S. Terlizzi Iii
Exploring Learning Classifier System Behaviors In Multi-Action, Turn-Based Wargames, Garth J.S. Terlizzi Iii
Theses and Dissertations
State of the art game-playing Artificial Intelligence research focuses heavily on non-symbolic learning methods. These methods offer little explainable insight into their decision-making processes. Learning Classifier Systems (LCSs) provide an alternative. LCSs use rule-based learning, guided by a Genetic Algorithm (GA), to produce a human-readable rule-set. This thesis explores LCS usefulness in game-playing agents for multi-agent wargames. Several Multi-Agent Learning Classifier System (MALCS) variants are implemented in the wargame Stratagem MIST: a Zeroeth-Level Classifier System (ZCS), an extended Classifier System (XCS), and an Adaptive Pittsburgh Classifier System (APCS). These algorithms were tested against baseline agents as well as the Online …