Engineering Commons^™

Energy Planning Model Design For Forecasting The Final Energy Consumption Using Artificial Neural Networks, Haidy Eissa

Theses and Dissertations

“Energy Trilemma” has recently received an increasing concern among policy makers. The trilemma conceptual framework is based on three main dimensions: environmental sustainability, energy equity, and energy security. Energy security reflects a nation’s capability to meet current and future energy demand. Rational energy planning is thus a fundamental aspect to articulate energy policies. The energy system is huge and complex, accordingly in order to guarantee the availability of energy supply, it is necessary to implement strategies on the consumption side. Energy modeling is a tool that helps policy makers and researchers understand the fluctuations in the energy system. Over the …

A Longitudinal Analysis Of Pathways To Computing Careers: Defining Broadening Participation In Computing (Bpc) Success With A Rearview Lens, Mercy Jaiyeola

Theses and Dissertations

Efforts to increase the participation of groups historically underrepresented in computing studies, and in the computing workforce, are well documented. It is a national effort with funding from a variety of sources being allocated to research in broadening participation in computing (BPC). Many of the BPC efforts are funded by the National Science Foundation (NSF) but as existing literature shows, the growth in representation of traditionally underrepresented minorities and women is not commensurate to the efforts and resources that have been directed toward this aim.

Instead of attempting to tackle the barriers to increasing representation, this dissertation research tackles the …

Advanced Analytics In Smart Manufacturing: Anomaly Detection Using Machine Learning Algorithms And Parallel Machine Scheduling Using A Genetic Algorithm, Meiling He

Theses and Dissertations

Industry 4.0 offers great opportunities to utilize advanced data processing tools by generating Big Data from a more connected and efficient data collection system. Making good use of data processing technologies, such as machine learning and optimization algorithms, will significantly contribute to better quality control, automation, and job scheduling in Smart Manufacturing. This research aims to develop a new machine learning algorithm for solving highly imbalanced data processing problems, implement both supervised and unsupervised machine learning auto-selection frameworks for detecting anomalies in smart manufacturing, and develop a genetic algorithm for optimizing job schedules on unrelated parallel machines. This research also …

A Deep Recurrent Neural Network With Iterative Optimization For Inverse Image Processing Applications, Masaki Ikuta

Theses and Dissertations

Many algorithms and methods have been proposed for inverse image processing applications, such as super-resolution, image de-noising, and image reconstruction, particularly with the recent surge of interest in machine learning and deep learning methods.

As for Computed Tomography (CT) image reconstruction, the most recently proposed methods are limited to image domain processing, where deep learning is used to learn the mapping between a true image data set and a noisy image data set in the image domain. While deep learning-based methods can produce higher quality images than conventional model-based algorithms, these methods have a limitation. Deep learning-based methods used in …

Robot Area Coverage Path Planning In Aquatic Environments, Nare Karapetyan

Theses and Dissertations

This thesis is motivated by real world problems faced in aquatic environments. It addresses the problem of area coverage path planning with robots - the problem of moving an end-effector of a robot over all available space while avoiding existing obstacles. The problem is considered first in a 2D space with a single robot for specific environmental monitoring operations, and then with multi-robot systems — a known NP-complete problem. Next we tackle the coverage problem in 3D space - a step towards underwater mapping of shipwrecks or monitoring of coral reefs.

The first part of this thesis leverages human expertise …

Enterprise Resource Allocation For Intruder Detection And Interception, Adam B. Haywood

Theses and Dissertations

This research considers the problem of an intruder attempting to traverse a defender's territory in which the defender locates and employs disparate sets of resources to lower the probability of a successful intrusion. The research is conducted in the form of three related research components. The first component examines the problem in which the defender subdivides their territory into spatial stages and knows the plan of intrusion. Alternative resource-probability modeling techniques as well as variable bounding techniques are examined to improve the convergence of global solvers for this nonlinear, nonconvex optimization problem. The second component studies a similar problem but …

Medical Image Segmentation Using Machine Learning, Masoud Khani

Theses and Dissertations

Image segmentation is the most crucial step in image processing and analysis. It can divide an image into meaningfully descriptive components or pathological structures. The result of the image division helps analyze images and classify objects. Therefore, getting the most accurate segmented image is essential, especially in medical images. Segmentation methods can be divided into three categories: manual, semiautomatic, and automatic. Manual is the most general and straightforward approach. Manual segmentation is not only time-consuming but also is imprecise. However, automatic image segmentation techniques, such as thresholding and edge detection, are not accurate in the presence of artifacts like noise …

Development Of A 7 Dof Exoskeleton Robot For Rehabilitation Of Lower Extremity, Sk Hasan

Theses and Dissertations

The World Health Organization reports that worldwide about 1 billion people have some form ofdisability. Of these, 110-190 million people have significant difficulties in functioning (mainly upper and lower extremity disability) independently. The major causes of human lower extremity disability include stroke, trauma, spinal cord injuries, and muscular dystrophy. Every 40 seconds, someone in the United States has a stroke. A statistic shows that approximately 65% of post-stroke patients suffer lower extremity impairment. Rehabilitation programs are the main method to promote functional recovery in disabled individuals. The conventional therapeutic approach requires a long commitment from a therapist or a clinician. …

Rebalancing Shared Mobility Systems By User Incentive Scheme Via Reinforcement Learning, Matthew Brian Schofield

Theses and Dissertations

Shared mobility systems regularly suffer from an imbalance of vehicle supply within the system, leading to users being unable to receive service. If such imbalance problems are not mitigated some users will not be serviced. There is an increasing interest in the use of reinforcement learning (RL) techniques for improving the resource supply balance and service level of systems. The goal of these techniques is to produce an effective user incentivization policy scheme to encourage users of a shared mobility system to slightly alter their travel behavior in exchange for a small monetary incentive. These slight changes in user behavior …

Stock Markets Performance During A Pandemic: How Contagious Is Covid-19?, Yara Abushahba

Theses and Dissertations

Background and Motivation: The coronavirus (“COVID-19”) pandemic, the subsequent policies and lockdowns have unarguably led to an unprecedented fluid circumstance worldwide. The panic and fluctuations in the stock markets were unparalleled. It is inarguable that real-time availability of news and social media platforms like Twitter played a vital role in driving the investors’ sentiment during such global shock.

Purpose:The purpose of this thesis is to study how the investor sentiment in relation to COVID-19 pandemic influenced stock markets globally and how stock markets globally are integrated and contagious. We analyze COVID-19 sentiment through the Twitter posts and investigate its …

Design Of A Novel Manual And Automated Penetration Testing Framework For Connected Industrial Control Systems (Ics), Rafat Elsharef

Theses and Dissertations

This research presents the design of new framework—a manually executed and an automated penetration testing process for Connected Industrial Control Systems (ICS). Both frameworks were built using open-source security software and ICS equipment currently used in critical infrastructure, manufacturing companies, and other institutions in the United States and around the world. Existing penetration testing frameworks have largely been focused on manual testing and are specific to Information Technology (IT). In addition, a new severity scoring system framework, called Common Vulnerability Scoring System for Industrial Control Systems (CVSS-ICS), was recommended for calculating the severity score in Industrial Control Systems (ICS).The broader …

Development Of Novel Compound Controllers To Reduce Chattering Of Sliding Mode Control, Mehran Rahmani

Theses and Dissertations

The robotics and dynamic systems constantly encountered with disturbances such as micro electro mechanical systems (MEMS) gyroscope under disturbances result in mechanical coupling terms between two axes, friction forces in exoskeleton robot joints, and unmodelled dynamics of robot manipulator. Sliding mode control (SMC) is a robust controller. The main drawback of the sliding mode controller is that it produces high-frequency control signals, which leads to chattering. The research objective is to reduce chattering, improve robustness, and increase trajectory tracking of SMC. In this research, we developed controllers for three different dynamic systems: (i) MEMS, (ii) an Exoskeleton type robot, and …

Wound Image Classification Using Deep Convolutional Neural Networks, Behrouz Rostami

Theses and Dissertations

Artificial Intelligence (AI) includes subfields like Machine Learning (ML) and DeepLearning (DL) and discusses intelligent systems that mimic human behaviors. ML has been used in a wide range of fields. Particularly in the healthcare domain, medical images often need to be carefully processed via such operations as classification and segmentation. Unlike traditional ML methods, DL algorithms are based on deep neural networks that are trained on a large amount of labeled data to extract features without human intervention. DL algorithms have become popular and powerful in classifying and segmenting medical images in recent years. In this thesis, we shall study …

A Simulation Framework For Traffic Safety With Connected Vehicles And V2x Technologies, Md Abu Sayed

Theses and Dissertations

With the advancement in automobile technologies, existing research shows that connected vehicle (CV) technologies can provide better traffic safety through Surrogate Safety Measure (SSM). CV technologies involves two network systems: traffic network and wireless communication network. We found that the research in the wireless communication network for CV did not interact properly with the research in SSM in transportation network, and vice versa. Though various SSM has been proposed in previous studies, a few of them have been tested in simulation software in limited extent. On the other hand, A large body of researchers proposed various communication architecture for CV …

Application Of Deep Learning For Imaging-Based Stream Gaging, Ryan Lee Vanden Boomen

Theses and Dissertations

In the field of water resources management, one vital instrument utilized is the stream gage. Stream gages monitor and record flow and water height within some water body. The United States Geological Survey maintains a network of stream gages at many locations across the country. Many of these sites are also equipped with webcams monitoring the state of the water body at the moment of measurement. Previous studies have outlined methods to approximate stream gage data remotely with limitations such as the requirement of detailed depth information for each site. This study seeks to create a process for training a …

Multi-Robot Coordination With Environmental Disturbances, Adem Coskun

Theses and Dissertations

Multi-robot systems are increasingly deployed in environments where they interact with humans. From the perspective of a robot, such interaction could be considered a disturbance that causes a well-planned trajectory to fail. This dissertation addresses the problem of multi-robot coordination in scenarios where the robots may experience unexpected delays in their movements.

Prior work by Čáp, Gregoire, and Frazzoli introduced a control law, called RMTRACK, which enables robots in such scenarios to execute pre-planned paths in spite of disturbances that affect the execution speed of each robot while guaranteeing that each robot can reach its goal without collisions and without …

Deep Learning Based Sound Event Detection And Classification, Alireza Nasiri

Theses and Dissertations

Hearing sense has an important role in our daily lives. During the recent years, there has been many studies to transfer this capability to the computers. In this dissertation, we design and implement deep learning based algorithms to improve the ability of the computers in recognizing the different sound events.

In the first topic, we investigate sound event detection, which identifies the time boundaries of the sound events in addition to the type of the events. For sound event detection, we propose a new method, AudioMask, to benefit from the object-detection techniques in computer vision. In this method, we convert …

A Cyber Threat Taxonomy And A Viability Analysis For False Injections In The Tcas, John W. Hannah

Theses and Dissertations

This thesis provided background information on the Traffic Collision Avoidance System (TCAS). Additionally, the thesis developed a threat taxonomy for TCAS, resulting in the determination that a false injection attack presents the most comprehensive risk. Moreover, the thesis presents the development of a program to determine what ranges, altitudes, and relative bearings are most vulnerable to a false injection attack. The program includes test for all requirements of a successful false injection. Furthermore, the thesis presents an analysis of results and creates threat maps as situational awareness tools. Lastly, the thesis discusses potential solutions to the false injection attack, covers …

Laser Illuminated Imaging: Beam And Scene Deconvolution Algorithm, Benjamin W. Davis

Theses and Dissertations

Laser illuminated imaging systems deal with several physical challenges that must be overcome to achieve high-resolution images of the target. Noise sources like background noise, photon counting noise, and laser speckle noise will all greatly affect the imaging systems ability to produce a high-resolution image. An even bigger challenge to laser illuminated imaging systems is atmospheric turbulence and the effect that it will have on the imaging system. The illuminating beam will experience tilt, causing the beam to wander off the center of the target during propagation. The light returning to the detector will similarly be affected by turbulence, and …

Infiniband Network Monitoring: Challenges And Possibilities, Kyle D. Hintze

Theses and Dissertations

Within the realm of High Performance Computing, the InfiniBand Architecture is among the leading interconnects used today. Capable of providing high bandwidth and low latency, InfiniBand is finding applications outside the High Performance Computing domain. One of these is critical infrastructure, encompassing almost all essential sectors as the work force becomes more connected. InfiniBand is not immune to security risks, as prior research has shown that common traffic analyzing tools cannot effectively monitor InfiniBand traffic transmitted between hosts, due to the kernel bypass nature of the IBA in conjunction with Remote Direct Memory Access operations. If Remote Direct Memory Access …

Remote Monitoring Of Memory Data Structures For Malware Detection In A Talos Ii Architecture, Robert A. Willburn

Theses and Dissertations

New forms of malware, namely xC;leless malware and rootkits, pose a threat to traditional anti-malware. In particular, Rootkits have the capacity to obscure the present state of memory from the user space of a target machine. If thishappens, anti-malware running in the user space of an axB;ected machine cannot be trusted to operate properly. To combat this threat, this research proposes the remote monitoring of memory from a second, secure processor runningOpenBMC, serving as a baseboard management controller for a POWER9 processor, which is assumed vulnerable to exploitation. The baseboard management controller includes an application called pdbg, used for debugging …

Stereo Camera Calibrations With Optical Flow, Joshua D. Larson

Theses and Dissertations

Remotely Piloted Aircraft (RPA) are currently unable to refuel mid-air due to the large communication delays between their operators and the aircraft. AAR seeks to address this problem by reducing the communication delay to a fast line-of-sight signal between the tanker and the RPA. Current proposals for AAR utilize stereo cameras to estimate where the receiving aircraft is relative to the tanker, but require accurate calibrations for accurate location estimates of the receiver. This paper improves the accuracy of this calibration by improving three components of it: increasing the quantity of intrinsic calibration data with CNN preprocessing, improving the quality …

Optimizing A Bank Of Kalman Filters For Navigation Integrity, Luis E. Sepulveda

Theses and Dissertations

Alternative navigation is an area of research which employs a variety of sensor technologies to provide a navigation solution in Global Navigation Satellite System degraded or denied environments. The Autonomy and Navigation Technology Center at the Air Force Institute of Technology has recently developed the Autonomous and Resilient Management of All-source Sensors (ARMAS) navigation framework which utilizes an array of Kalman Filters to provide a navigation solution resilient to sensor failures. The Kalman Filter array size increases exponentially as system sensors and detectable faults are scaled up, which in turn increases the computational power required to run ARMAS in areal-world …

Exploring Fog Of War Concepts In Wargame Scenarios, Dillon N. Tryhorn

Theses and Dissertations

This thesis explores fog of war concepts through three submitted journal articles. The Department of Defense and U.S. Air Force are attempting to analyze war scenarios to aid the decision-making process; fog modeling improves realism in these wargame scenarios. The first article "Navigating an Enemy Contested Area with a Parallel Search Algorithm" [1] investigates a parallel algorithm's speedup, compared to the sequential implementation, with varying map configurations in a tile-based wargame. The parallel speedup tends to exceed 50 but in certain situations. The sequential algorithm outperforms it depending on the configuration of enemy location and amount on the map. The …

Aircraft Inspection By Multirotor Uav Using Coverage Path Planning, Patrick H. Silberberg

Theses and Dissertations

All military and commercial aircraft must undergo frequent visual inspections in order to identify damage that could pose a danger to safety of flight. Currently, these inspections are primarily conducted by maintenance personnel. Inspectors must scrutinize the aircraft’s surface to find and document defects such as dents, hail damage, broken fasteners, etc.; this is a time consuming, tedious, and hazardous process. The goal of this work is to develop a visual inspection system which can be used by an Unmanned Aerial Vehicle (UAV), and to test the feasibility of this system on military aircraft. Using an autonomous system in place …

Long Distance Bluetooth Low Energy Exploitation On A Wireless Attack Platform, Stephanie L. Long

Theses and Dissertations

In the past decade, embedded technology, known as the Internet of Things, has expanded for many uses. The smart home infrastructure has drastically grown to include networked refrigerators, lighting systems, speakers, watches, and more. This increase in the use of wireless protocols provides a larger attack surface for cyber actors than ever before. Wireless loT traffic is susceptible for sniffing by an attacker. The attack platform skypie is upgraded to incorporate Bluetooth Low Energy (BLE) beacon collection for pattern-of-life data, as well as device characteristic enumeration and potential characteristic modification. This platform allows an attacker to mount the skypie to …

Delayed Authentication System For Civilian Satellite, Sean M. Feschak

Theses and Dissertations

This thesis presents the feasibility of a Delayed Authentication System (DAS) for civilian satellite navigation (satnav) receivers. In satnav systems, encrypted signal components are transmitted synchronously with civilian components. Hence, the civilian signals can be authenticated by detecting the presence of encrypted signal components within the received signal. To authenticate, a reference station transmits estimated encrypted signal spreading code symbols processed using a high gain antenna. In this thesis, it is shown that a 1-meter diameter dish antenna is adequate to provide a high probability of successful authentication, thereby reducing overall system complexity and cost.

Low-Cost Terrestrial Demonstration Of Autonomous Satellite Proximity Operations, Zackary R. Hewitt

Theses and Dissertations

The lack of satellite servicing capabilities significantly impacts the development and operation of current orbital assets. With autonomous solutions under consideration for servicing, the purpose of this research is to build and validate a low-cost hardware platform to expedite the development of autonomous satellite proximity operations. This research aims to bridge the gap between simulation and existing higher fidelity hardware testing with an affordable alternative. An omnidirectional variant of the commercially available TurtleBot3 mobile robot is presented as a 3-DOF testbed that demonstrates a satellite servicing inspection scenario. Reference trajectories for the scenario are generated via optimal control using the …

Comparison Of Conic Ray Tracing For Occlusion Determination On 3d Point Cloud Data, Henry Cho

Theses and Dissertations

The US Air Force has been increasing the use of automation in its weapon systems to include the remotely piloted aircraft (RPA) platforms. The RPA career field has had issues with poor pilot retention due to job stressors. For example, RPA operators spend a lot of time and attention surveilling a suspect on the ground for many hours, so adding automation to this activity could help improve pilot retention. The research problem in this thesis attempted to automate the process of observing a ground target. This thesis presents a method termed conic ray tracing for determining visibility and occlusion of …

Display Design To Avoid And Mitigate Limit Cycle Oscillations (Lco) On The F-16c, David J. Feibus

Theses and Dissertations

The U.S. Air Force F-16 Fighting Falcons flying characteristics and flight envelope are dynamic and defined by its external weapon stores configuration. The employment of its munitions at certain speeds can put the F-16 into a flutter-like state in which Limit Cycle Oscillations (LCO) are induced. In LCO, a pilots fine motor control might be hindered, and the aircraft may lose combat effectiveness until flight conditions are reduced. The current research attempted to provide pilots with a predictive feedback display to avoid an LCO-susceptible configuration by increasing their situation awareness about the consequences of employing certain munitions to their flight …