Satellite Servicing Capabilities Office Testing

While at the KSC, I was given the opportunity of assisting the Satellite Servicing Capabilities Office (SSCO) specifically the Propellant Transfer System (PTS) lead by my mentor, Brian Nufer. While waiting to test different components in the PTS, I was able to assist with testing for the Hose Management Assembly (HMA) and was able to work on a simulation in Labview. For the HMA, I was able to help with testing of a coating as well as to help test the durability of the pinch rollers in space. In Labview, I experimented with building a simulation for the PTS, to show where fluids and gases were flowing depending on which valves in the PTS were opened. Not all of the integrated parts required assembly level testing, which allowed me to test these parts individually by myself and document the results. I was also able to volunteer to assist project NEO, allowing me to gain some knowledge of cryogenic fluid systems

A comparison and contrast of APKTool and Soot for injecting blockchain calls into Android applications

The injection of blockchain calls into an Android Application is an emerging and important tool for Android application developers. Blockchain technology provides a way of securely storing sensitive data and distributing that data while providing immutability. This paper will compare two compiler-based tools, APKTool, and the Soot framework and how they can inject blockchain calls into Android applications. A major contribution of this paper is that it compares the APKTool, and the Soot framework compilers for injecting blockchain calls, and the difficulties each tool introduces when implementing the injection of a blockchain call. To the best of our knowledge, the use of the Soot framework and the APKTool have never been used to inject blockchain calls. The reason behind this situation is the complexity of configuring blockchain calls in Android applications. Part of the difficulty is because of the constant changes in the API calls in the Android framework. This presents a challenge because the Soot and APKTool compilers have to be modified to adapt to changes in the Android API

Guns and Voting: How to Protect Elections after Bruen

With more guns and more political polarization and violence, states need strong laws to limit risk. In Bruen, the Supreme Court recognized that prohibitions on guns in "sensitive places" — and specifically in "polling places" — were "presumptively lawful." Yet today only 12 states and Washington, DC, prohibit both open and concealed carry of firearms at poll sites. Ironically, the states with the strongest gun regulations — which had restricted the ability to carry guns in public generally, rather than prohibiting guns in particular locations — were made most vulnerable in the wake of Bruen. In fact, only one of the six states that had their laws struck down by the decision specifically prohibited guns in polling places at the time of the decision.Now these states that once had strong general gun laws must scramble to enact new protections for elections. Although some states have banned guns at polling placessince Bruen, there is far more work to do.This report evaluates the new risks that gun violence poses for U.S. elections and proposes policy solutions to limit those risks. Solutions include prohibitions on firearms wherever voting or election administration occurs — at or near polling places, ballot drop boxes, election offices, and ballot counting facilities. In addition, states need stronger laws preventing intimidation of voters, election officials, election workers, and anyone else facilitating voting, with express recognition of the role that guns play in intimidation.Brennan Center for Justice: http://brennancenter.org/Giffords Law Center to Prevent Gun Violence: https://giffords.org/lawcenter/gun-laws/

Techniques for the Analysis of Modern Web Page Traffic using Anonymized TCP/IP Headers

Analysis of traces of network traffic is a methodology that has been widely adopted for studying the Web for several decades. However, due to recent privacy legislation and increasing adoption of traffic encryption, often only anonymized TCP/IP headers are accessible in traffic traces. For traffic traces to remain useful for analysis, techniques must be developed to glean insight using this limited header information. This dissertation evaluates approaches for classifying individual web page downloads — referred to as web page classification — when only anonymized TCP/IP headers are available. The context in which web page classification is defined and evaluated in this dissertation is different from prior traffic classification methods in three ways. First, the impact of diversity in client platforms (browsers, operating systems, device type, and vantage point) on network traffic is explicitly considered. Second, the challenge of overlapping traffic from multiple web pages is explicitly considered and demultiplexing approaches are evaluated (web page segmentation). And lastly, unlike prior work on traffic classification, four orthogonal labeling schemes are considered (genre-based, device-based, navigation-based, and video streaming-based) — these are of value in several web-related applications, including privacy analysis, user behavior modeling, traffic forecasting, and potentially behavioral ad-targeting. We conduct evaluations using large collections of both synthetically generated data, as well as browsing data from real users. Our analysis shows that the client platform choice has a statistically significant impact on web traffic. It also shows that change point detection methods, a new class of segmentation approach, outperform existing idle time-based methods. Overall, this work establishes that web page classification performance can be improved by: (i) incorporating client platform differences in the feature selection and training methodology, and (ii) utilizing better performing web page segmentation approaches. This research increases the overall awareness on the challenges associated with the analysis of modern web traffic. It shows and advocates for considering real-world factors, such as client platform diversity and overlapping traffic from multiple streams, when developing and evaluating traffic analysis techniques.Doctor of Philosoph

Multi-fluid approach for the numerical prediction of wall erosion in an elbow

Multiphase pipelineflows are widely used in the oil and gas industry to transport solid-liquid or gas-solid mix-tures. Erosion caused by the impact of solid particles is a major challenge for equipment maintenance and safety,especially in complex geometries such as elbows. In this work, a CFD study on wall erosion in a 90° standardelbow has been performed using a multi-fluid approach, also called Euler/Euler, for poly-dispersedfluid-particleflows. A model is used for the erosion prediction taking into account particle turbulent kinetic energy obtainedfrom the Euler-Euler approach. A good agreement with experiments is observed. The effects of wall roughnessand solid massflow rate on the erosion rate are also investigated. For a certain amount of sand passing throughthe pipe elbow, there exists a solid massflow rate for which the particle impact damage is most dramatic

The interaction of dark traits with the perceptions of apprehension

This paper integrates dark personality traits with the economics of crime and rational choice theories to identify the role that the Dark Triad and thrill-seeking have on the perceptions of being caught engaging in violating privacy laws. Psychopathy and thrill-seeking had a moderate negative effect on the perceptions of the probability of being apprehended for distributing illegally obtained healthcare information. The implication is that individuals scoring high on the psychopathy and thrill-seeking scales will need less money or monetary incentives to violate HIPAA laws. We also found additional support that white hat hackers score high on the Machiavellian, psychopathy and thrill-seeking scales. We also validated a previous finding that a white hat hacker might drift towards grey hat and black hat hacking

Dark Traits and Hacking Potential

This paper investigates the psychological traits of individuals' attraction to engaging in hacking behaviors (both ethical and illegal/unethical) upon entering the workforce. A new set of scales have been developed to assist in the delineation of the three hat categories. We have also developed a scale to measure each subject's perception of the probability of being apprehended for violating privacy laws. The results suggest that white hat, grey hat, and black hat hackers score high on the Machiavellian and psychopathy scales. We also found evidence that grey hatters oppose authority, black hatters score high in the thrill-seeking dimension, and white hatters, the good guys, tend to be narcissists. Thrill-seeking was moderately important for white hat and black hat hacking, and opposition to authority was significant for grey hat hacking. Narcissism was not statistically significant in any of the models. A perceived probability of being apprehended had a negative effect on both grey hat and black hat hacking. Additional models were explored to examine the relationships among the research variables