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Cyber Security Master's Degree Annual Program Outcomes Assessments, 2022-23, College Of Engineering And Computer Science, Wright State University Jan 2023

Cyber Security Master's Degree Annual Program Outcomes Assessments, 2022-23, College Of Engineering And Computer Science, Wright State University

Annual Program Outcomes Assessments - All

This report reviews Wright State University's Cyber Security Master's Degree program for the 2022-2023 academic year.

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Code Execution Capability As A Metric For Machine Learning–Assisted Software Vulnerability Detection Models, Daniel Grahn, Lingwei Chen, Junjie Zhang Jan 2023

Code Execution Capability As A Metric For Machine Learning–Assisted Software Vulnerability Detection Models, Daniel Grahn, Lingwei Chen, Junjie Zhang

Computer Science and Engineering Faculty Publications

In this paper, we consider how the ability to learn Code Execution Tasks affects a model’s accuracy on software vulnerability detection (SVD) benchmark datasets. We initially find that models can achieve near state-of-the-art accuracy on SVD benchmarks regardless of their ability to learn Code Execution Tasks. However, these models fail to generalize well across SVD benchmarks. The results indicate a bias in the datasets that allows models to predict non- SVD signals. Under the theory that different collection methods will reduce biases, we investigate combining the SVD datasets. When trained on combined datasets, SVD accuracy is reduced but correlation with …

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A Pattern For Representing Scientific Taxonomies, Shirly Stephen, Cogan Shimizu, Mark Schildhauer, Rui Zhu, Krzysztof Janowicz, Pascal Hitzler Jan 2023

A Pattern For Representing Scientific Taxonomies, Shirly Stephen, Cogan Shimizu, Mark Schildhauer, Rui Zhu, Krzysztof Janowicz, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Standard taxonomies that are meant to serve as reference specifications of specific scientific domains are developed through extensive review by scientists and experts. For data integration and interoperability needs within Knowledge Graphs (KGs), these taxonomies must be translated into formal ontologies. In this paper we present an ontology design pattern for modeling a scientific taxonomy as an ontology. The focus of the pattern is to 1) capture temporal dynamics of concepts as taxonomies evolve, 2) model the provenance of concepts to add context and enable governance, 3) assist the translation of taxonomic relations to ontological relations appropriately that will empower …

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The Expertise Ontology: Modeling Expertise In The Context Of Emergency Management, Shirly Stephen, Mark Schildhauer, Ling Cai, Yuanyuan Tian, Kitty Currier, Cogan Shimizu, Krzysztof Janowicz, Pascal Hitzler, Anna Lopez-Carr, Andrew Schroeder, Zilong Liu, Rui Zhu, Dean Rehberger, Colby K. Fisher, Gengchen Mai Jan 2023

The Expertise Ontology: Modeling Expertise In The Context Of Emergency Management, Shirly Stephen, Mark Schildhauer, Ling Cai, Yuanyuan Tian, Kitty Currier, Cogan Shimizu, Krzysztof Janowicz, Pascal Hitzler, Anna Lopez-Carr, Andrew Schroeder, Zilong Liu, Rui Zhu, Dean Rehberger, Colby K. Fisher, Gengchen Mai

Computer Science and Engineering Faculty Publications

It is crucial for emergency management organizations to have rapid access to relevant experts who can advise and assist following a disaster. To improve expert-mining and recommendation capabilities, creating a knowledge graph that links experts to their corresponding topics of expertise and other sources of relevant information is a natural choice to capture an integrated network of people and a rich taxonomy of expertise. In this paper, we present an ontology for modeling experts, their expertise topics and relations between them, and their spatiotemporal scoping. We go on to discuss the primary conceptual components and how they can be instantiated, …

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National Survey Of Student Engagement 2023 High-Impact Practices (Dayton Campus), National Survey Of Student Engagement Jan 2023

National Survey Of Student Engagement 2023 High-Impact Practices (Dayton Campus), National Survey Of Student Engagement

National Survey of Student Engagement (NSSE) Reports

The High-Impact Practices Report asks students about their participation in the six high-impact practices: Service-learning, learning community, research with faculty, internship or field experience, study abroad, and culminating senior experience.

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National Survey Of Student Engagement 2023 High-Impact Practices (Lake Campus), National Survey Of Student Engagement Jan 2023

National Survey Of Student Engagement 2023 High-Impact Practices (Lake Campus), National Survey Of Student Engagement

National Survey of Student Engagement (NSSE) Reports

The High-Impact Practices Report asks students about their participation in the six high-impact practices: Service-learning, learning community, research with faculty, internship or field experience, study abroad, and culminating senior experience.

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Festival Of Research Abstracts, 2023, College Of Science And Mathematics, Wright State University Jan 2023

Festival Of Research Abstracts, 2023, College Of Science And Mathematics, Wright State University

Festival of Research

The collection of abstracts accepted for the 2023 Festival of Research hosted by the Wright State University College of Science and Mathematics.

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College Of Graduate Programs And Honors Studies Newsletter - January 2023, College Of Graduate Programs And Honor Studies, Wright State University Jan 2023

College Of Graduate Programs And Honors Studies Newsletter - January 2023, College Of Graduate Programs And Honor Studies, Wright State University

College of Graduate Programs and Honors Studies Newsletter

A four page newsletter created by the College of Graduate Programs and Honors Studies at Wright State University. This newsletter includes a upcoming events, message from the dean, and more.

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Brain Morphometry From Neuroimaging As A Biomarker For Alzheimer's Disease, Nonyelum Benedicta Aniebo Jan 2023

Brain Morphometry From Neuroimaging As A Biomarker For Alzheimer's Disease, Nonyelum Benedicta Aniebo

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Alzheimer’s disease (AD) is the seventh leading cause of death globally with an estimated 6.5 million Americans aged 65 and above living with Alzheimer’s dementia in 2022 and at a projected national cost of $321 billion. AD is characterized by a progressive and irreversible neurodegenerative dysfunction with clinical symptoms such as deterioration in cognition and memory loss. The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is a multi-site, public-private global research initiative that supports both investigation and development of treatments that slow or terminate AD progression. The study included 60 participants, comprising 30 AD and 30 control cohorts respectively. All participants were …

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Teaching Physics While Female : A Phenomenological Study Of Female High School Physics Teachers, Hope Strickland Jan 2023

Teaching Physics While Female : A Phenomenological Study Of Female High School Physics Teachers, Hope Strickland

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The lived experiences of female high school physics teachers were researched in this study with the aim of gaining a better understanding of their decisions to remain in the classroom or to leave the teaching profession. To allow the participants to describe their background and teaching experiences, as well as the meaning they found in them, a transcendental phenomenological approach was used during this research. To create a richer representation of the phenomenon, fourteen women ranging from 0-31 years of experience teaching high school physics were interviewed for this study. The data from the interviews was analyzed through the lens …

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Accelerating Precision Station Keeping For Automated Aircraft, James D. Anderson Jan 2023

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 …

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Comparative Adjudication Of Noisy And Subjective Data Annotation Disagreements For Deep Learning, Scott David Williams Jan 2023

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. …

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Enhancing Graph Convolutional Network With Label Propagation And Residual For Malware Detection, Aravinda Sai Gundubogula Jan 2023

Enhancing Graph Convolutional Network With Label Propagation And Residual For Malware Detection, Aravinda Sai Gundubogula

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Malware detection is a critical task in ensuring the security of computer systems. Due to a surge in malware and the malware program sophistication, machine learning methods have been developed to perform such a task with great success. To further learn structural semantics, Graph Neural Networks abbreviated as GNNs have emerged as a recent practice for malware detection by modeling the relationships between various components of a program as a graph, which deliver promising detection performance improvement. However, this line of research attends to individual programs while overlooking program interactions; also, these GNNs tend to perform feature aggregation from neighbors …

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Rheological Modeling And Inkjet Printability Of Electrode Ink Formulation For Miniature And Interdigital Lithium-Ion Batteries, Habib Temitope-Adebayo Ajose Jan 2023

Rheological Modeling And Inkjet Printability Of Electrode Ink Formulation For Miniature And Interdigital Lithium-Ion Batteries, Habib Temitope-Adebayo Ajose

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The rapid advancement of technology has resulted in a greater need for effective energy storage systems to meet the demands of the transportation and electronics industries. Among various energy storage systems, batteries are the most widely used, primarily because of their ability to store significant amounts of energy. In addition, lithium-ion batteries are prevalent for powering portable electronic devices due to their long cycle life, high energy density, and high operating voltage. The traditional doctor-blade approach has been used over the years for producing batteries. Currently, research is being directed to additively manufacture Li-ion batteries via Drop-on-Demand Inkjet Printing with …

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Effective Systems For Insider Threat Detection, Muhanned Qasim Jabbar Alslaiman Jan 2023

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 …

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Fuzzing Php Interpreters By Automatically Generating Samples, Jacob S. Baumgarte Jan 2023

Fuzzing Php Interpreters By Automatically Generating Samples, Jacob S. Baumgarte

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Modern web development has grown increasingly reliant on scripting languages such as PHP. The complexities of an interpreted language means it is very difficult to account for every use case as unusual interactions can cause unintended side effects. Automatically generating test input to detect bugs or fuzzing, has proven to be an effective technique for JavaScript engines. By extending this concept to PHP, existing vulnerabilities that have since gone undetected can be brought to light. While PHP fuzzers exist, they are limited to testing a small quantity of test seeds per second. In this thesis, we propose a solution for …

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Modeling, Simulation, And Hardware Testing Of A Noise-Canceller Adc Architecture, Ethan R. Rando Jan 2023

Modeling, Simulation, And Hardware Testing Of A Noise-Canceller Adc Architecture, Ethan R. Rando

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Analog-to-Digital Converters (ADCs) are essential elements of most complex electronic devices. ADCs allow for an analog signal to be converted into the digital domain, and thus interpreted by a digital circuit or model. While ADCs are extremely common, they are not immune from common tradeoffs when being designed and implemented. The most prominent tradeoff when selecting or designing an ADC is whether to pursue a high conversion rate or a high resolution on the digital output. There are some ADC designs that allow for relatively high resolution while maintaining a respectable conversion rate, however these designs often come at the …

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Calpains In The Peripheral Nerve And During Demyelination And Degeneration In Rodents, John A. Miller Jan 2023

Calpains In The Peripheral Nerve And During Demyelination And Degeneration In Rodents, John A. Miller

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Myelin formed around axons ensures rapid and efficient action potential propagation. Disruption of myelinated axons in the peripheral nervous system (PNS) often causes nerve conduction failure, neurological symptoms and can lead to long-term disability. Calpains are calcium dependent cysteine proteases that play many roles during both normal physiology and pathogenesis. Calpain-1 (CAPN1) and calpain-2 (CAPN2) are key calpain paralogs found in the nervous system and potentially have opposing roles, with CAPN2 having a more neurodegenerative function. In the central nervous system (CNS), calpains have a role in developmental myelination as well as in the pathological demyelination of multiple sclerosis and …

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Icing Mitigation Via High-Pressure Membrane Dehumidification In An Aircraft Thermal Management, Danielle D. Hollon Jan 2023

Icing Mitigation Via High-Pressure Membrane Dehumidification In An Aircraft Thermal Management, 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 …

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Unsupervised-Based Distributed Machine Learning For Efficient Data Clustering And Prediction, Vishnu Vardhan Baligodugula Jan 2023

Unsupervised-Based Distributed Machine Learning For Efficient Data Clustering And Prediction, Vishnu Vardhan Baligodugula

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Machine learning techniques utilize training data samples to help understand, predict, classify, and make valuable decisions for different applications such as medicine, email filtering, speech recognition, agriculture, and computer vision, where it is challenging or unfeasible to produce traditional algorithms to accomplish the needed tasks. Unsupervised ML-based approaches have emerged for building groups of data samples known as data clusters for driving necessary decisions about these data samples and helping solve challenges in critical applications. Data clustering is used in multiple fields, including health, finance, social networks, education, and science. Sequential processing of clustering algorithms, like the K-Means, Minibatch K-Means, …

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Experimental And Numerical Studies On The Projective Dye Visualization Velocimetry In A Squared Vertical Tube, Mark Bradley Johnson Jan 2023

Experimental And Numerical Studies On The Projective Dye Visualization Velocimetry In A Squared Vertical Tube, Mark Bradley Johnson

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In fluid flow experiments, there have been numerous techniques developed over the years to measure velocity. Most popular techniques are non-intrusive such as particle image velocimetry (PIV), but these techniques are not suitable for all applications. For instance, PIV cannot be used in examining in-vivo measurements since the laser is not able to penetrate through the patient, which is why medical applications typically use X-rays. However, the images obtained from X-rays, in particular digital subtraction angiography, are projective images which compress 3D flow features onto a 2D image. Therefore, when intensity techniques, such as optical flow method (OFM), are applied …

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Effects Of Elastic Anisotropy On Residual Stress Measurements Performed Using The Hole-Drilling Technique, Joshua T. Ward Jan 2023

Effects Of Elastic Anisotropy On Residual Stress Measurements Performed Using The Hole-Drilling Technique, Joshua T. Ward

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In the present work, the variation in through-thickness residual stress profiles driven by elastic anisotropy is investigated using the incremental hole-drilling method. The standardized hole-drilling technique allows for the calculation of in-plane stresses based on measured surface strains, however, these calculations assume elastic isotropy. The assumption of elastic isotropy allows for the material constants to be reduced down to two values, however, this assumption is invalid for many materials used in aerospace design. These materials are often times elastically anisotropic, which leads to inaccuracy and uncertainty in measured stress profiles. An interference fit ring and plug sample was designed, using …

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Effect Of Size And Shape Parameters On Microstructure Of Additively Manufactured Inconel 718, Showmik Ahsan Jan 2023

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.

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Rankine Cycle Investigation On Meeting Power And Thermal Requirements Of High-Speed Aircraft, Jacob J. Spark Jan 2023

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 …

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Multi-Variable Phase And Gain Calibration For Multi-Channel Transmit Signals, Ryan C. Ball Jan 2023

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 …

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Anomaly Detection In Multi-Seasonal Time Series Data, Ashton Taylor Williams Jan 2023

Anomaly Detection In Multi-Seasonal Time Series Data, Ashton Taylor Williams

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Most of today’s time series data contain anomalies and multiple seasonalities, and accurate anomaly detection in these data is critical to almost any type of business. However, most mainstream forecasting models used for anomaly detection can only incorporate one or no seasonal component into their forecasts and cannot capture every known seasonal pattern in time series data. In this thesis, we propose a new multi-seasonal forecasting model for anomaly detection in time series data that extends the popular Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Our model, named multi-SARIMA, utilizes a time series dataset’s multiple pre-determined seasonal trends to increase …

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Comparative Study Of Mof's In Phosphate Adsorption, Eniya Karunamurthy Jan 2023

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 …

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Path-Safe: Enabling Dynamic Mandatory Access Controls Using Security Tokens, James P. Maclennan Jan 2023

Path-Safe: Enabling Dynamic Mandatory Access Controls Using Security Tokens, James P. Maclennan

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Deploying Mandatory Access Controls (MAC) is a popular way to provide host protection against malware. Unfortunately, current implementations lack the flexibility to adapt to emergent malware threats and are known for being difficult to configure. A core tenet of MAC security systems is that the policies they are deployed with are immutable from the host while they are active. This work looks at deploying a MAC system that leverages using encrypted security tokens to allow for redeploying policy configurations in real-time without the need to stop a running process. This is instrumental in developing an adaptive framework for security systems …

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Characterization Of Aerosol Jet Printed Silver Thin Films Sintered By A Scanning Laser, William A. Metzger Jan 2023

Characterization Of Aerosol Jet Printed Silver Thin Films Sintered By A Scanning Laser, William A. Metzger

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Direct write printing, which is part of additive manufacturing (AM) technology, offers unique capabilities that can complement traditional methods of electronics fabrication. Printing of electrical interconnects via aerosolization is one of the areas in AM that is very important in electronics fabrication. Post-print sintering is a critical step in printed electrical interconnects because it strongly influences the electrical resistivity of the interconnects. Interconnects require the lowest possible resistivity to achieve better performance. Thermal sintering is the most common technique employed in printed interconnects. However, it is limited to substrates that can handle the high temperature requirement for sintering. For polymers …

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Fault Diagnosis And Accommodation In Quadrotor Simultaneous Localization And Mapping Systems, Anthony J. Green Jan 2023

Fault Diagnosis And Accommodation In Quadrotor Simultaneous Localization And Mapping Systems, Anthony J. Green

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Simultaneous Localization and Mapping (SLAM) is the process of using distance measurements to points in the surrounding environment to build a digital map and perform localization. It has been observed that featureless environments like tunnels or straight hallways will cause positioning faults in SLAM. This research investigates the fault diagnosis and accommodation problem for a laser-rangefinder-based SLAM systems on a quadrotor. A potential solution of using optical flow as velocity estimate and an extended Kalman filter (EKF) to perform position estimation is proposed. A fault diagnosis method for detecting faults in positional SLAM data or optical flow velocity data is …

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