Physical Sciences and Mathematics Commons^™

Software Protection And Secure Authentication For Autonomous Vehicular Cloud Computing, Muhammad Hataba

Dissertations

Artificial Intelligence (AI) is changing every technology we deal with. Autonomy has been a sought-after goal in vehicles, and now more than ever we are very close to that goal. Vehicles before were dumb mechanical devices, now they are becoming smart, computerized, and connected coined as Autonomous Vehicles (AVs). Moreover, researchers found a way to make more use of these enormous capabilities and introduced Autonomous Vehicles Cloud Computing (AVCC). In these platforms, vehicles can lend their unused resources and sensory data to join AVCC.

In this dissertation, we investigate security and privacy issues in AVCC. As background, we built our …

Data Collection And Machine Learning Methods For Automated Pedestrian Facility Detection And Mensuration, Joseph Bailey Luttrell Iv

Dissertations

Large-scale collection of pedestrian facility (crosswalks, sidewalks, etc.) presence data is vital to the success of efforts to improve pedestrian facility management, safety analysis, and road network planning. However, this kind of data is typically not available on a large scale due to the high labor and time costs that are the result of relying on manual data collection methods. Therefore, methods for automating this process using techniques such as machine learning are currently being explored by researchers. In our work, we mainly focus on machine learning methods for the detection of crosswalks and sidewalks from both aerial and street-view …

Analyzing And Detecting Android Malware And Deepfake, Md Shohel Rana

Dissertations

Rapid advances in artificial intelligence (AI), machine learning (ML), and deep learning (DL) over the past several decades have produced a variety of technologies and tools that, among numerous cybersecurity issues, have enticed cybercriminals and hackers to design malware for the Android operating systems and/or manipulate multimedia. For example, high-quality and realistic fake videos, images, or audios have been created to spread misinformation and propaganda, foment political discord and hate, or even harass and blackmail people; these manipulated, high-quality and realistic videos became known recently as Deepfake. There has been much work done in recent years on malware analysis and …

Ensemble Data Fitting For Bathymetric Models Informed By Nominal Data, Samantha Zambo

Dissertations

Due to the difficulty and expense of collecting bathymetric data, modeling is the primary tool to produce detailed maps of the ocean floor. Current modeling practices typically utilize only one interpolator; the industry standard is splines-in-tension.

In this dissertation we introduce a new nominal-informed ensemble interpolator designed to improve modeling accuracy in regions of sparse data. The method is guided by a priori domain knowledge provided by artificially intelligent classifiers. We recast such geomorphological classifications, such as ‘seamount’ or ‘ridge’, as nominal data which we utilize as foundational shapes in an expanded ordinary least squares regression-based algorithm. To our knowledge …

Data-Driven Approaches To Complex Materials: Applications To Amorphous Solids, Dil Kumar Limbu

Dissertations

While conventional approaches to materials modeling made significant contributions and advanced our understanding of materials properties in the past decades, these approaches often cannot be applied to disordered materials (e.g., glasses) for which accurate total-energy functionals or forces are either not available or it is infeasible to employ due to computational complexities associated with modeling disordered solids in the absence of translational symmetry. In this dissertation, a number of information-driven probabilistic methods were developed for the structural determination of a range of materials including disordered solids to transition metal clusters. The ground-state structures of transition-metal clusters of iron, nickel, and …

A Study Of Information Bots And Knowledge Bots, Amartya Hatua

Dissertations

In this dissertation, a study of different aspects of information bots and knowledge bots is done. The research contributes to a better understanding of the various characteristics of information bots as well as the different patterns and factors responsible for the information diffusion in a social network. This research also shows how these factors can be used to predict information diffusion for a particular topic in a social network. The second part of the research is focused on strategies for improving the knowledge base of knowledge bots, where two different approaches are studied. In the first approach, knowledge is transferred …

Empirical Studies Of Deep Learning On Information Diffusion On Social Networks And Collective Task Learning For Swarm Robotics, Trung T. Nguyen

Dissertations

Researchers in multiple disciplines have recently adopted deep learning because of its ability of high accuracy representation learning from big and complex data. My research goal in this thesis is developing deep learning models for information diffusion analysis on social networks and collective tasks learning in swarm robotics. Firstly, the information diffusion on social networks is modeled as a multivariate time series in three dimensions with ten features. Then, we applied time-series clustering algorithms with Dynamic Time Warping to discover different patterns of our models. Then, we build a prediction model based on LSTM, which outperforms traditional time-series prediction methods. …

A 3d Image-Guided System To Improve Myocardial Revascularization Decision-Making For Patients With Coronary Artery Disease, Haipeng Tang

Dissertations

OBJECTIVES. Coronary artery disease (CAD) is the most common type of heart disease and kills over 360,000 people a year in the United States. Myocardial revascularization (MR) is a standard interventional treatment for patients with stable CAD. Fluoroscopy angiography is real-time anatomical imaging and routinely used to guide MR by visually estimating the percent stenosis of coronary arteries. However, a lot of patients do not benefit from the anatomical information-guided MR without functional testing. Single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) is a widely used functional testing for CAD evaluation but limits to the absence of anatomical information. …

Developing A Computational Framework For A Construction Scheduling Decision Support Web Based Expert System, Feroz Ahmed

Dissertations

Decision-making is one of the basic cognitive processes of human behaviors by which a preferred option or a course of action is chosen from among a set of alternatives based on certain criteria. Decision-making is the thought process of selecting a logical choice from the available options. When trying to make a good decision, all the positives and negatives of each option should be evaluated. This decision-making process is particularly challenging during the preparation of a construction schedule, where it is difficult for a human to analyze all possible outcomes of each and every situation because, construction of a project …

Computational Modeling Of Radiation Interactions With Molecular Nitrogen, Tyler Reese

Dissertations

The ability to detect radiation through identifying secondary effects it has on its surrounding medium would extend the range at which detections could be made and would be a valuable asset to many industries. The development of such a detection instrument requires an accurate prediction of these secondary effects. This research aims to improve on existing modeling techniques and help provide a method for predicting results for an affected medium in the presence of radioactive materials. A review of radioactivity and the interactions mechanisms for emitted particles as well as a brief history of the Monte Carlo Method and its …

3d Printing Concrete Structures And Verifying Integrity Of Their G-Code Instructions: Border Wall A Case Study, Jason Breland

Dissertations

Thanks to advances in Additive Manufacturing (AM) technology and continued research by academics and entrepreneurs alike, the ability to “3d print” permanent concrete structures such as homes or offices is now a reality. Generally, AM is the process that allows for a 3d model of an object to be converted into hardware instructions to generate that object layer by layer using a malleable medium such as a plastic. Specifically, large scale concrete AM can now generate a structure, such as a building, layer by layer more quickly and efficiently than traditional construction methods [6, 39]. This innovative, semi-autonomous process promises …

Evaluating Relevance And Reliability Of Twitter Data For Risk Communication, Xiaohui Liu

Dissertations

While Twitter has been touted to provide up-to-date information about hazard events, the relevance and reliability of tweets is yet to be tested. This research examined the relevance and reliability of risk information extracted from Twitter during the 2013 Colorado floods using five different approaches. The first approach examined the relationship between tweet volume and precipitation amount. The second approach explored the relationship between geo-tagged tweets and degree of damage. In the third approach, the spatiotemporal distribution of tweets was compared with flood extent. In the fourth approach, risk information from tweets were compared with survey responses obtained in a …

Determining Feasibility Resilience: Set Based Design Iteration Evaluation Through Permutation Stability Analysis, James E. Ross

Dissertations

The goal of robust design is to select a design that will still perform satisfactorily even with unexpected variation in design parameters. A resilient design will accommodate unanticipated future system requirements. Through studying the variations of system parameters through the use of multi objective optimization, a designer hopes to locate a robustly resilient design, which performs current mission well even with varying system parameters and is able to be easily repurposed to new missions. This ability to withstand changes is critical because it is common for the product of a design to undergo changes throughout its life cycle. This subject …

Secure And Reliable Routing Protocol For Transmission Data In Wireless Sensor Mesh Networks, Nooh Adel Bany Muhammad

Dissertations

Abstract

Sensor nodes collect data from the physical world then exchange it until it reaches the intended destination. This information can be sensitive, such as battlefield surveillance. Therefore, providing secure and continuous data transmissions among sensor nodes in wireless network environments is crucial. Wireless sensor networks (WSN) have limited resources, limited computation capabilities, and the exchange of data through the air and deployment in accessible areas makes the energy, security, and routing major concerns in WSN. In this research we are looking at security issues for the above reasons. WSN is susceptible to malicious activities such as hacking and physical …

Gal: A Stepwise Model For Automated Cloud Shadow Detection In Hico Oceanic Imagery Utilizing Guided Filter, Pixel Assignment, And Geometric Linking, Jennerpher Renee Meyers

Dissertations

Detection of cloud shadow pixels is an important step in image processing in several remote sensing ocean-color application domains, such as obtaining chlorophyll content. While shadow detection algorithms do exist, the vast majority are for over land which leaves few options for detection over water.

The detection of cloud shadow over water in HICO imagery is a unique problem. As its name implies, HICO (Hyperspectral Imager for the Coastal Ocean) imagery is produced for coastal and oceanic regions. Since land based algorithms remove water before processing, these approaches would not be applicable. The only currently published HICO shadow pixel detection …

Selective Detection Of Volatile Organic Compounds Using Metal Oxide Sensor Arrays, Anton Dmitrievich Netchaev

Dissertations

Selective detection of organic contaminant using widely available and inexpensive metal oxide sensors has the potential to be used in various robotic platforms for navigation, harmful chemical leak detection, mobile environmental monitoring, etc. Selective gas detection in real world environments using easily available sensors has not been reported and can be used in many industries. A sensor system using only four commercially available sensors with accompanying signal conditioning and clustering algorithm capable of discriminatory detection of chemical marker is possible. Tests have shown that temperature, humidity and concentration fluctuations can be accounted for to produce systems for real world environments. …

Multi-Sensory Emotion Recognition With Speech And Facial Expression, Qingmei Yao

Dissertations

Emotion plays an important role in human beings’ daily lives. Understanding emotions and recognizing how to react to others’ feelings are fundamental to engaging in successful social interactions. Currently, emotion recognition is not only significant in human beings’ daily lives, but also a hot topic in academic research, as new techniques such as emotion recognition from speech context inspires us as to how emotions are related to the content we are uttering.

The demand and importance of emotion recognition have highly increased in many applications in recent years, such as video games, human computer interaction, cognitive computing, and affective computing. …

Synergy Of The Developed 6d Bim Framework And Conception Of The Nd Bim Framework And Nd Bim Process Ontology, Shawn Edward O'Keeffe

Dissertations

The author developed a unified nD framework and process ontology for Building Information Modeling (BIM). The research includes a framework developed for 6D BIM, nD BIM, and nD ontology that defines the domain and sub-domain constructs for future nD BIM dimensions. The nD ontology defines the relationships of kinds within any new proposed dimensional domain for BIM. The developed nD BIM framework and ontology takes into account the current 2D-5D BIM dimensions. There is a synergy between the 6D and nD framework that allows the nD framework and ontology to be utilized as a unified template for future dimensional development. …

Gene Regulatory Network Analysis And Web-Based Application Development, Yi Yang

Dissertations

Microarray data is a valuable source for gene regulatory network analysis. Using earthworm microarray data analysis as an example, this dissertation demonstrates that a bioinformatics-guided reverse engineering approach can be applied to analyze time-series data to uncover the underlying molecular mechanism. My network reconstruction results reinforce previous findings that certain neurotransmitter pathways are the target of two chemicals - carbaryl and RDX. This study also concludes that perturbations to these pathways by sublethal concentrations of these two chemicals were temporary, and earthworms were capable of fully recovering. Moreover, differential networks (DNs) analysis indicates that many pathways other than those related …

Gene Regulatory Network Reconstruction Using Dynamic Bayesian Networks, Haoni Li

Dissertations

High-content technologies such as DNA microarrays can provide a system-scale overview of how genes interact with each other in a network context. Various mathematical methods and computational approaches have been proposed to reconstruct GRNs, including Boolean networks, information theory, differential equations and Bayesian networks. GRN reconstruction faces huge intrinsic challenges on both experimental and theoretical fronts, because the inputs and outputs of the molecular processes are unclear and the underlying principles are unknown or too complex.

In this work, we focused on improving the accuracy and speed of GRN reconstruction with Dynamic Bayesian based method. A commonly used structure-learning algorithm …

A Time Series Analysis Method Using Hidden Variables For Gene Network Reconstruction, Xi Wu

Dissertations

The DNA microarray technology can be applied to obtain time series data which contains thousands of genes and tens of time points. When confront the great amount of data points a fast and effective method must be constructed to extract useful information. The assumption that the interactions between genes are static in the time series data is made. After made the assumption how to reconstruct those interactions becomes a difficulty problem. Since the underlying interactions between genes are complicated, which involve transcription, translation and protein-protein interaction, to construct a model from physicochemistry is almost impossible/effortless. The popular methods constructed from …

Reification: A Process To Configure Java Realtime Processors, John Huddleston Heath

Dissertations

Real-time systems require stringent requirements both on the processor and the software application. The primary concern is speed and the predictability of execution times. In all real-time applications the developer must identify and calculate the worst case execution times (WCET) of their software. In almost all cases the processor design complexity impacts the analysis when calculating the WCET. Design features which impact this analysis include cache and instruction pipelining. With both cache and pipelining the time taken for a particular instruction can vary depending on cache and pipeline contents. When calculating the WCET the developer must ignore the speed advantages …

Error Estimation Techniques To Refine Overlapping Aerial Image Mosaic Processes Via Detected Parameters, William Glenn Bond

Dissertations

In this paper, I propose to demonstrate a means of error estimation preprocessing in the assembly of overlapping aerial image mosaics. The mosaic program automatically assembles several hundred aerial images from a data set by aligning them, via image registration using a pattern search method, onto a GIS grid.

The method presented first locates the images from a data set that it predicts will not align well via the mosaic process, then it uses a correlation function, optimized by a modified Hooke and Jeeves algorithm, to provide a more optimal transformation function input to the mosaic program. Using this improved …

Monte Carlo Simulation Of Electron-Induced Air Fluorescence Utilizing Mobile Agents: A New Paradigm For Collaborative Scientific Simulation, Christopher Daniel Walker

Dissertations

A new paradigm for utilization of mobile agents in a modular architecture for scientific simulation is demonstrated through a case study involving Monte Carlo simulation of low energy electron interactions with molecular nitrogen gas. Design and development of Monte Carlo simulations for physical systems of moderate complexity can present a seemingly overwhelming endeavor. The researcher must possess or otherwise develop a thorough understanding the physical system, create mathematical and computational models of the physical system’s components, and forge a simulation utilizing those models. While there is no single route between a collection of physical concepts and a Monte Carlo simulation …

A Methodology To Develop A Communication Protocol For Visualizing Simulations In A Collaborative Virtual Reality Environment, Lacey Suzanne Duckworth

Dissertations

In the technology field, simulations and collaborative virtual reality environments (CVREs) are not generally combined because it is complicated to develop large scale simulations within CVREs. The complexity of combining these two technologies in order to form a better form of visualization stems from the lack of a methodology to help derive these scalable simulations. Simulations require very complex calculations that the CVRE cannot perform as it is overloaded in calculations for the maintenance and stability of the environment itself. Since the simulation cannot be held within the CVRE, the solution is to move the simulation external to the CVRE …

Cloud Shadow Detection And Removal From Aerial Photo Mosaics Using Light Detection And Ranging (Lidar) Reflectance Images, Glover Eugene George

Dissertations

The process of creating aerial photo mosaics can be severely affected by clouds and the shadows they create. In the CZMIL project discussed in this work, the aerial survey aircraft flies below the clouds, but the shadows cast from clouds above the aircraft cause the resultant mosaic image to have sub-optimal results. Large intensity variations, caused both from the cloud shadow within a single image and the juxtaposition of areas of cloud shadow and no cloud shadow during the image stitching process, create an image that may not be as useful to the concerned research scientist. Ideally, we would like …

Stereo Matching Using A Modified Efficient Belief Propagation In A Level Set Framework, Stephen Goyer Rogers

Dissertations

Stereo matching determines correspondence between pixels in two or more images of the same scene taken from different angles; this can be handled either locally or globally. The two most common global approaches are belief propagation (BP) and graph cuts.

Efficient belief propagation (EBP), which is the most widely used BP approach, uses a multi-scale message passing strategy, an O(k) smoothness cost algorithm, and a bipartite message passing strategy to speed up the convergence of the standard BP approach. As in standard belief propagation, every pixel sends messages to and receives messages from its four neighboring pixels in EBP. Each …

Dnagents: Genetically Engineered Intelligent Mobile Agents, Jeremy Otho Kackley

Dissertations

Mobile agents are a useful paradigm for network coding providing many advantages and disadvantages. Unfortunately, widespread adoption of mobile agents has been hampered by the disadvantages, which could be said to outweigh the advantages. There is a variety of ongoing work to address these issues, and this is discussed. Ultimately, genetic algorithms are selected as the most interesting potential avenue. Genetic algorithms have many potential benefits for mobile agents. The primary benefit is the potential for agents to become even more adaptive to situational changes in the environment and/or emergent security risks. There are secondary benefits such as the natural …

Guppie: A Coordination Framework For Parallel Processing Using Shared Memory Featuring A Master-Worker Relationship, Sean Christopher Mccarthy

Dissertations

Most programs can be parallelized to some extent. The processing power available in computers today makes parallel computing more desirable and attainable than ever before. Many machines today have multiple processors or multiple processing cores making parallel computing more available locally, as well as over a network. In order for parallel applications to be written, they require a computing language, such as C++, and a coordination language (or library), such as Linda. This research involves the creation and implementation of a coordination framework, Guppie, which is easy to use, similar to Linda, but provides more efficiency when dealing with large …