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Articles 31 - 60 of 1235
Full-Text Articles in Engineering
Contributors To Pathologic Depolarization In Myotonia Congenita, Jessica Hope Myers
Contributors To Pathologic Depolarization In Myotonia Congenita, Jessica Hope Myers
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Myotonia congenita is an inherited skeletal muscle disorder caused by loss-of-function mutation in the CLCN1 gene. This gene encodes the ClC-1 chloride channel, which is almost exclusively expressed in skeletal muscle where it acts to stabilize the resting membrane potential. Loss of this chloride channel leads to skeletal muscle hyperexcitability, resulting in involuntary muscle action potentials (myotonic discharges) seen clinically as muscle stiffness (myotonia). Stiffness affects the limb and facial muscles, though specific muscle involvement can vary between patients. Interestingly, respiratory distress is not part of this disease despite muscles of respiration such as the diaphragm muscle also carrying this …
Effect Of Size And Shape Parameters On Microstructure Of Additively Manufactured Inconel 718, Showmik Ahsan
Effect Of Size And Shape Parameters On Microstructure Of Additively Manufactured Inconel 718, Showmik Ahsan
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Additive Manufacturing (AM) methods are promising in applications where complex part geometries, exotic materials and small lot sizes are required. Aerospace manufacturing stands to use AM methods extensively in the future, and frequently requires temperature- and corrosion-resistant alloy materials such as Inconel 718. However, the microstructural evolution of Inconel 718 during additive manufacturing is poorly understood and depends on part size and shape. We studied the microstructure of Inconel 718 parts manufactured by Laser Powder Bed Fusion in order to further elucidate these dependencies. Microstructural analysis, SEM imaging, EBSD scans and Microhardness testing were performed.
Comparative Study Of Mof's In Phosphate Adsorption, Eniya Karunamurthy
Comparative Study Of Mof's In Phosphate Adsorption, Eniya Karunamurthy
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High concentrations of phosphate are known to adversely affect the environment. Excess phosphate can lead to eutrophication that eventually fosters uncontrollable growth of aquatic plants and algae. This can result in depletion of oxygen content which adversely impacts underwater organism’s survival rates. Metal organic frameworks (MOFs) consist of organic linkers in conjunction with metal ions or clusters arranged within a crystalline structure. They are highly porous and have larger surface area due to their ability to possess extensive void spaces while remaining bulky in nature. MOFs can absorb phosphate from aqueous solutions. We have investigated the use of commercially available …
Multi-Variable Phase And Gain Calibration For Multi-Channel Transmit Signals, Ryan C. Ball
Multi-Variable Phase And Gain Calibration For Multi-Channel Transmit Signals, Ryan C. Ball
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A method for software-defined radio array calibration is presented. The method implements a matched filter approach to calculate the phase shift between channels. The temporal stability of the system and calibration coefficients are shown through the standard deviation over the course of four weeks. The standard deviation of the phase correction was shown to be less than 2 deg. for most channels in the array and within 8 deg. for the most extreme case. The standard deviation in amplitude scaling was calculated to be less than 0.06 for all channels in the array. The performance of the calibration is evaluated …
Rankine Cycle Investigation On Meeting Power And Thermal Requirements Of High-Speed Aircraft, Jacob J. Spark
Rankine Cycle Investigation On Meeting Power And Thermal Requirements Of High-Speed Aircraft, Jacob J. Spark
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This work is investigating a dual mode Rankine cycle for aircraft applications, specifically meeting vehicle thermal and power requirements. This multiconfigurational approach allows the Thermal Management System (TMS) to be controlled based on aircraft needs. In this design, waste heat is removed from critical areas of the aircraft (e.g., propulsion, structure, subsystems) using the fuel as a heat sink. Hot fuel is then forced through a heat exchanger actively boiling water. The vapor byproduct is fed to a turbine coupled to a generator, providing power. The low-pressure steam is then condensed using cold fuel drawn from its tank; however, when …
Encryption And Compression Classification Of Internet Of Things Traffic, Mariam Najdat M Saleh
Encryption And Compression Classification Of Internet Of Things Traffic, Mariam Najdat M Saleh
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The Internet of Things (IoT) is used in many fields that generate sensitive data, such as healthcare and surveillance. Increased reliance on IoT raised serious information security concerns. This dissertation presents three systems for analyzing and classifying IoT traffic using Deep Learning (DL) models, and a large dataset is built for systems training and evaluation. The first system studies the effect of combining raw data and engineered features to optimize the classification of encrypted and compressed IoT traffic using Engineered Features Classification (EFC), Raw Data Classification (RDC), and combined Raw Data and Engineered Features Classification (RDEFC) approaches. Our results demonstrate …
Effective Systems For Insider Threat Detection, Muhanned Qasim Jabbar Alslaiman
Effective Systems For Insider Threat Detection, Muhanned Qasim Jabbar Alslaiman
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Insider threats to information security have become a burden for organizations. Understanding insider activities leads to an effective improvement in identifying insider attacks and limits their threats. This dissertation presents three systems to detect insider threats effectively. The aim is to reduce the false negative rate (FNR), provide better dataset use, and reduce dimensionality and zero padding effects. The systems developed utilize deep learning techniques and are evaluated using the CERT 4.2 dataset. The dataset is analyzed and reformed so that each row represents a variable length sample of user activities. Two data representations are implemented to model extracted features …
Prediction Of Ka-Band Radar Cross Section With Thz Scale Models With Varying Surface Roughness, Andrew J. Huebner
Prediction Of Ka-Band Radar Cross Section With Thz Scale Models With Varying Surface Roughness, Andrew J. Huebner
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Radar cross section (RCS) of electrically large targets can be challenging and expensive to measure. The use of scale models to predict the RCS of such large targets saves time and reduces facility requirements. This study investigates Ka-band (27 to 29 GHz) RCS prediction from scale model measurements at 500 to 750 GHz. Firstly, the coherent quasi-monostatic turntable RCS measurement system is demonstrated. Secondly, three aluminum 18:1 scale dihedrals with surface roughness up to 218 icroinches are measured to investigate how the roughness affects the Ka-band prediction. The measurements are compared to a parametric scattering model for the specular response, …
A Secure And Efficient Iiot Anomaly Detection Approach Using A Hybrid Deep Learning Technique, Bharath Reedy Konatham
A Secure And Efficient Iiot Anomaly Detection Approach Using A Hybrid Deep Learning Technique, Bharath Reedy Konatham
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The Industrial Internet of Things (IIoT) refers to a set of smart devices, i.e., actuators, detectors, smart sensors, and autonomous systems connected throughout the Internet to help achieve the purpose of various industrial applications. Unfortunately, IIoT applications are increasingly integrated into insecure physical environments leading to greater exposure to new cyber and physical system attacks. In the current IIoT security realm, effective anomaly detection is crucial for ensuring the integrity and reliability of critical infrastructure. Traditional security solutions may not apply to IIoT due to new dimensions, including extreme energy constraints in IIoT devices. Deep learning (DL) techniques like Convolutional …
Merit Study Of Battery Or Hydrogen Energy Storage For Large Scale, Combined Wind And Solar Electricity Generation, Ashley K. Moore
Merit Study Of Battery Or Hydrogen Energy Storage For Large Scale, Combined Wind And Solar Electricity Generation, Ashley K. Moore
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In the past several years, the energy sector has experienced a rapid increase in renewable energy installations due to declining capital costs for wind turbines, solar panels, and batteries. Wind and solar electricity generation are intermittent in nature which must be considered in an economic analysis if a fair comparison is to be made between electricity supplied from renewables and electricity purchased from the grid. Energy storage reduces curtailment of wind and solar and minimizes electricity purchases from the grid by storing excess electricity and deploying the energy at times when demand exceeds the renewable energy supply. The objective of …
Accelerating Precision Station Keeping For Automated Aircraft, James D. Anderson
Accelerating Precision Station Keeping For Automated Aircraft, James D. Anderson
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Automated vehicles pose challenges in various research domains, including robotics, machine learning, computer vision, public safety, system certification, and beyond. These vehicles autonomously handle navigation and locomotion, often requiring minimal user interaction, and can operate on land, in water, or in the air. In the context of aircraft, one specific application is Automated Aerial Refueling (AAR). Traditional aerial refueling involves a "tanker" aircraft using a mechanism, such as a rigid boom arm or a flexible hose, to transfer fuel to another aircraft designated as the "receiver". For AAR, the boom arm may be maneuvered automatically, or in certain instances the …
Icing Mitigation Via High-Pressure Membrane Dehumidification In An Aircraft Thermal Management System, Danielle D. Hollon
Icing Mitigation Via High-Pressure Membrane Dehumidification In An Aircraft Thermal Management System, Danielle D. Hollon
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Icing, or the formation of ice from water via freezing or water vapor via desublimation, is a phenomenon that commonly occurs within air cycle-based refrigeration systems and requires thermal control that limits system performance. In aircraft applications icing frequently occurs in the heat exchangers and turbine(s) that are part of the air cycle machine, the refrigeration unit of the environmental control system. Traditionally, water vapor is removed from an air cycle machine via condensing in a heat exchanger and subsequent high-pressure water separation. This approach is not capable of removing all of the vapor present at low altitude conditions, corresponding …
Comparative Adjudication Of Noisy And Subjective Data Annotation Disagreements For Deep Learning, Scott David Williams
Comparative Adjudication Of Noisy And Subjective Data Annotation Disagreements For Deep Learning, Scott David Williams
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Obtaining accurate inferences from deep neural networks is difficult when models are trained on instances with conflicting labels. Algorithmic recognition of online hate speech illustrates this. No human annotator is perfectly reliable, so multiple annotators evaluate and label online posts in a corpus. Labeling scheme limitations, differences in annotators' beliefs, and limits to annotators' honesty and carefulness cause some labels to disagree. Consequently, decisive and accurate inferences become less likely. Some practical applications such as social research can tolerate some indecisiveness. However, an online platform using an indecisive classifier for automated content moderation could create more problems than it solves. …
Semantics-Driven Abstractive Document Summarization, Amanuel Alambo
Semantics-Driven Abstractive Document Summarization, Amanuel Alambo
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The evolution of the Web over the last three decades has led to a deluge of scientific and news articles on the Internet. Harnessing these publications in different fields of study is critical to effective end user information consumption. Similarly, in the domain of healthcare, one of the key challenges with the adoption of Electronic Health Records (EHRs) for clinical practice has been the tremendous amount of clinical notes generated that can be summarized without which clinical decision making and communication will be inefficient and costly. In spite of the rapid advances in information retrieval and deep learning techniques towards …
Behavior Of 3d Printed Polymeric Triply Periodic Minimal Surface (Tpms) Cellular Structures Under Low Velocity Impact Loads, Jesse James Leiffer
Behavior Of 3d Printed Polymeric Triply Periodic Minimal Surface (Tpms) Cellular Structures Under Low Velocity Impact Loads, Jesse James Leiffer
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Surface-based lattice structures such as triply periodic minimal surface (TPMS) lattices are lightweight structures that are widely being investigated for applications in automotive, aerospace, military, railway, and naval structures. Due to the recent advent of three-dimensional (3D) printing (3DP) technologies, architected cellular materials such as surface- or strut-based periodic lattice cell structures have emerged as a unique class of lightweight metamaterials. These materials possess enhanced strength to weight ratio, high stiffness, exceptional capabilities in reducing noise and vibration, insulating heat, and effective impact energy absorption. Understanding the impact behavior of such materials are important so that they can be reliably …
Building An Understanding Of Human Activities In First Person Video Using Fuzzy Inference, Bradley A. Schneider
Building An Understanding Of Human Activities In First Person Video Using Fuzzy Inference, Bradley A. Schneider
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Activities of Daily Living (ADL’s) are the activities that people perform every day in their home as part of their typical routine. The in-home, automated monitoring of ADL’s has broad utility for intelligent systems that enable independent living for the elderly and mentally or physically disabled individuals. With rising interest in electronic health (e-Health) and mobile health (m-Health) technology, opportunities abound for the integration of activity monitoring systems into these newer forms of healthcare. In this dissertation we propose a novel system for describing ’s based on video collected from a wearable camera. Most in-home activities are naturally defined by …
Reconfigurable Array Control Via Convolutional Neural Networks, Garrett A. Harris
Reconfigurable Array Control Via Convolutional Neural Networks, Garrett A. Harris
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A method for the beam forming control of an array of reconfigurable antennas is presented. The method consists of using two parallel convolutional neural networks (CNNs) to analyze a desired radiation pattern image, or mask, and provide a suggestion for the reconfigurable element state, array shape, and steering weights necessary to obtain the radiation pattern. This research compares beam forming systems designed for three distinct element types: a patch antenna, a reconfigurable square spiral antenna restricted to a single reconfigurable state, and the fully reconfigurable square spiral. The parametric sweeps for the design of the CNNs are presented along with …
Modeling The Tribo-Dynamic Behavior Of Roller Contact, Ali Kolivand
Modeling The Tribo-Dynamic Behavior Of Roller Contact, Ali Kolivand
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This study proposes dynamic modeling of lubricated rolling contact and a numerical sub-model for fatigue life prediction of rollers under starved lubrication conditions. Excitation caused by surface defects in rolling disks is numerically calculated and used as a metric in predicting surface pitting failure occurrence. Surface topography of mating surfaces is used as input to the model for determining maximum acceleration, approach velocity, and approach distance of rollers in presence of pits (defects). Resultant bearing force, contacting force versus approach distance are generated and compared for different pit sizes, developing an accurate tool for design purposes. Maximum acceleration and displacement …
Simulation Of Residual Stress Generation In Additive Manufacturing Of Complex Lattice Geometries, Katie Sue Bruggeman
Simulation Of Residual Stress Generation In Additive Manufacturing Of Complex Lattice Geometries, Katie Sue Bruggeman
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Residual stresses developed during additive manufacturing (AM) can influence the mechanical performance of structural components in their intended applications. In this study, thermomechanical residual stress simulations of the laser powder bed fusion (LPBF) process are conducted for both simplified (plate and cube-shaped) geometries as well as five complex lattice geometries fabricated with Inconel 718. These simulations are conducted with the commercial software package Simufact Additive©, which uses a non-linear finite element analysis and layer-by-layer averaging approach in determining residual stresses. To verify the efficacy of the Simufact Additive© simulations, numerical results for the plate and cube-shape geometries are analyzed for …
Cmos Wide Tuning Gilbert Mixer With Controllable If Bandwidth In Upcoming Rf Front End For Multi-Band Multi-Standard Applications, Jianfeng Ren
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The current global system for mobile communications, wireless local area, Bluetooth, and ultra-wideband demands a multi-band/multi-standard RF front end that can access all the available bandwidth specifications. Trade-offs occur between power consumption, noise figure, and linearity in CMOS Gilbert mixer wide tuning designs. Besides, it is preferable to have a constant IF bandwidth for different gain settings as the bandwidth varies with the load impedance when an RF receiver is tuned to a higher frequency. My dissertation consists of three parts. First, a tunable constant IF bandwidth Gilbert mixer is introduced for multi-band standard wireless applications such as 802.11 a/b/g …
A Design Thinking Framework For Human-Centric Explainable Artificial Intelligence In Time-Critical Systems, Paul Benjamin Stone
A Design Thinking Framework For Human-Centric Explainable Artificial Intelligence In Time-Critical Systems, Paul Benjamin Stone
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Artificial Intelligence (AI) has seen a surge in popularity as increased computing power has made it more viable and useful. The increasing complexity of AI, however, leads to can lead to difficulty in understanding or interpreting the results of AI procedures, which can then lead to incorrect predictions, classifications, or analysis of outcomes. The result of these problems can be over-reliance on AI, under-reliance on AI, or simply confusion as to what the results mean. Additionally, the complexity of AI models can obscure the algorithmic, data and design biases to which all models are subject, which may exacerbate negative outcomes, …
A Digital Twin For Synchronized Multi-Laser Powder Bed Fusion (M-Lpbf) Additive Manufacturing, Shayna Petitjean
A Digital Twin For Synchronized Multi-Laser Powder Bed Fusion (M-Lpbf) Additive Manufacturing, Shayna Petitjean
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One of the technological challenges in the widespread application of additive manufacturing is the formation of undesired material microstructure and defects. Specifically, in metal additive manufacturing, the microstructural formation of columnar grains in Ti-6Al-4V is common and results in anisotropic mechanical properties and a reduction in properties such as ductility and endurance limit. This work presents the application of hexagonal and circular arrays of synchronized lasers to alter the microstructure of Ti-6Al-4V in favor of equiaxed grains. An anisotropic heat transfer model obtains the temporal/spatial temperature distribution and constructs the solidification map for various process parameters, including laser power, laser …
Development Of Improved Cfd Tools For The Optimization Of A Scramjet Engine, Francis A. Centlivre
Development Of Improved Cfd Tools For The Optimization Of A Scramjet Engine, Francis A. Centlivre
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In the present work, a plugin has been developed for use with the DoD HPCMP CREATE-AV Kestrel multi-physics solver that adds volumetric source terms to the energy equation. These source terms model the heat released due to combustion, but are much more computationally efficient than a full chemistry model. A thrust-based optimization study was then carried out under the control of Sandia National Laboratories' Dakota toolkit. Dakota was allowed to control the amount of heat added to three regions of the scramjet combustor. The plugin was then extended to consider ignition delay time. By comparing ignition delay time to dwell …
Novel Natural Language Processing Models For Medical Terms And Symptoms Detection In Twitter, Farahnaz Golrooy Motlagh
Novel Natural Language Processing Models For Medical Terms And Symptoms Detection In Twitter, Farahnaz Golrooy Motlagh
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This dissertation focuses on disambiguation of language use on Twitter about drug use, consumption types of drugs, drug legalization, ontology-enhanced approaches, and prediction analysis of data-driven by developing novel NLP models. Three technical aims comprise this work: (a) leveraging pattern recognition techniques to improve the quality and quantity of crawled Twitter posts related to drug abuse; (b) using an expert-curated, domain-specific DsOn ontology model that improve knowledge extraction in the form of drug-to-symptom and drug-to-side effect relations; and (c) modeling the prediction of public perception of the drug’s legalization and the sentiment analysis of drug consumption on Twitter. We collected …
A Cloud Computing-Based Dashboard For The Visualization Of Motivational Interviewing Metrics, E Jinq Heng
A Cloud Computing-Based Dashboard For The Visualization Of Motivational Interviewing Metrics, E Jinq Heng
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Motivational Interviewing (MI) is an evidence-based brief interventional technique that has been demonstrated to be effective in triggering behavior change in patients. To facilitate behavior change, healthcare practitioners adopt a nonconfrontational, empathetic dialogic style, a core component of MI. Despite its advantages, MI has been severely underutilized mainly due to the cognitive overload on the part of the MI dialogue evaluator, who has to assess MI dialogue in real-time and calculate MI characteristic metrics (number of open-ended questions, close-ended questions, reflection, and scale-based sentences) for immediate post-session evaluation both in MI training and clinical settings. To automate dialogue assessment and …
Deep Understanding Of Technical Documents : Automated Generation Of Pseudocode From Digital Diagrams & Analysis/Synthesis Of Mathematical Formulas, Nikolaos Gkorgkolis
Deep Understanding Of Technical Documents : Automated Generation Of Pseudocode From Digital Diagrams & Analysis/Synthesis Of Mathematical Formulas, Nikolaos Gkorgkolis
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The technical document is an entity that consists of several essential and interconnected parts, often referred to as modalities. Despite the extensive attention that certain parts have already received, per say the textual information, there are several aspects that severely under researched. Two such modalities are the utility of diagram images and the deep automated understanding of mathematical formulas. Inspired by existing holistic approaches to the deep understanding of technical documents, we develop a novel formal scheme for the modelling of digital diagram images. This extends to a generative framework that allows for the creation of artificial images and their …
Synthetic Aperture Ladar Automatic Target Recognizer Design And Performance Prediction Via Geometric Properties Of Targets, Jacob W. Ross
Synthetic Aperture Ladar Automatic Target Recognizer Design And Performance Prediction Via Geometric Properties Of Targets, Jacob W. Ross
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Synthetic Aperture LADAR (SAL) has several phenomenology differences from Synthetic Aperture RADAR (SAR) making it a promising candidate for automatic target recognition (ATR) purposes. The diffuse nature of SAL results in more pixels on target. Optical wavelengths offers centimeter class resolution with an aperture baseline that is 10,000 times smaller than an SAR baseline. While diffuse scattering and optical wavelengths have several advantages, there are also a number of challenges. The diffuse nature of SAL leads to a more pronounced speckle effect than in the SAR case. Optical wavelengths are more susceptible to atmospheric noise, leading to distortions in formed …
Evaluating Similarity Of Cross-Architecture Basic Blocks, Elijah L. Meyer
Evaluating Similarity Of Cross-Architecture Basic Blocks, Elijah L. Meyer
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Vulnerabilities in source code can be compiled for multiple processor architectures and make their way into several different devices. Security researchers frequently have no way to obtain this source code to analyze for vulnerabilities. Therefore, the ability to effectively analyze binary code is essential. Similarity detection is one facet of binary code analysis. Because source code can be compiled for different architectures, the need can arise for detecting code similarity across architectures. This need is especially apparent when analyzing firmware from embedded computing environments such as Internet of Things devices, where the processor architecture is dependent on the product and …
Printing, Characterization, And Mechanical Testing Of Additively Manufactured Refractory Metal Alloys, Brianna M. Sexton
Printing, Characterization, And Mechanical Testing Of Additively Manufactured Refractory Metal Alloys, Brianna M. Sexton
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Refractory metal alloys in the tungsten molybdenum rhenium ternary system were additively manufactured using laser power bed fusion. Four ternary alloys with varying concentrations of tungsten, molybdenum, and rhenium were manufactured and manufactured again with an addition of 1 wt% hafnium carbide. Samples were heat treated to heal cracks, reduce porosity, and reduce inhomogeneity. Material microstructure was characterized before and after heat treatment using microscopy, energy dispersive x-ray spectroscopy, and electron backscatter diffraction mapping. Mechanical testing was conducted on both three-point bend specimens and compression specimens, resulting in maximum bending strengths of 677.86 MPa, and maximum compression 0.2% yield strengths …
Validating Software States Using Reverse Execution, Nathaniel Christian Boland
Validating Software States Using Reverse Execution, Nathaniel Christian Boland
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A key feature of software analysis is determining whether it is possible for a program to reach a certain state. Various methods have been devised to accomplish this including directed fuzzing and dynamic execution. In this thesis we present a reverse execution engine to validate states, the Complex Emulator. The Complex Emulator seeks to validate a program state by emulating it in reverse to discover if a contradiction exists. When unknown variables are found during execution, the emulator is designed to use constraint solving to compute their values. The Complex Emulator has been tested on small assembly programs and is …