Engineering Commons^™

Analysis Of Computer Audit Data To Create Indicators Of Compromise For Intrusion Detection, Steven Millett, Michael Toolin, Justin Bates

SMU Data Science Review

Network security systems are designed to identify and, if possible, prevent unauthorized access to computer and network resources. Today most network security systems consist of hardware and software components that work in conjunction with one another to present a layered line of defense against unauthorized intrusions. Software provides user interactive layers such as password authentication, and system level layers for monitoring network activity. This paper examines an application monitoring network traffic that attempts to identify Indicators of Compromise (IOC) by extracting patterns in the network traffic which likely corresponds to unauthorized access. Typical network log data and construct indicators are …

Network Traffic Behavioral Analytics For Detection Of Ddos Attacks, Alma D. Lopez, Asha P. Mohan, Sukumaran Nair

SMU Data Science Review

As more organizations and businesses in different sectors are moving to a digital transformation, there is a steady increase in malware, facing data theft or service interruptions caused by cyberattacks on network or application that impact their customer experience. Bot and Distributed Denial of Service (DDoS) attacks consistently challenge every industry relying on the internet. In this paper, we focus on Machine Learning techniques to detect DDoS attack in network communication flows using continuous learning algorithm that learns the normal pattern of network traffic, behavior of the network protocols and identify a compromised network flow. Detection of DDoS attack will …

Visualization And Machine Learning Techniques For Nasa’S Em-1 Big Data Problem, Antonio P. Garza Iii, Jose Quinonez, Misael Santana, Nibhrat Lohia

SMU Data Science Review

In this paper, we help NASA solve three Exploration Mission-1 (EM-1) challenges: data storage, computation time, and visualization of complex data. NASA is studying one year of trajectory data to determine available launch opportunities (about 90TBs of data). We improve data storage by introducing a cloud-based solution that provides elasticity and server upgrades. This migration will save $120k in infrastructure costs every four years, and potentially avoid schedule slips. Additionally, it increases computational efficiency by 125%. We further enhance computation via machine learning techniques that use the classic orbital elements to predict valid trajectories. Our machine learning model decreases trajectory …

Parametric Amplification Study And Applications In Millimeter-Wave Transmitters, Sherry Huang

Electrical Engineering Theses and Dissertations

In wireless communication systems, the millimeter-wave frequency band has been gaining more interests recently, mainly due to its wide bandwidth and ability to support high data-rate. However, challenges come with the advantages. To transmit and receive complexed data, the quadrature amplitude modulation (QAM) scheme paired with orthogonal frequency-division multiplexing (OFDM) is used most commonly. In transmitter designs of such modulation schemes and frequency access schemes, two important requirements are high linearity and high efficiency. The building blocks of transmitters include power amplifiers (PA) and mixers. Nevertheless, traditional design techniques exhibit trade-offs between linearity and efficiency for PAs, and between conversion …

Equilibrium-Based Workload Balancing For Robust Emergency Response Operations In Metropolitan Areas, Parya Roustaee

Civil and Environmental Engineering Theses and Dissertations

This thesis presents an equilibrium-based modeling framework for emergency response (ER) workload balancing to achieve robust operation in large-scale metropolitan areas. The problem is formulated as a non-linear mathematical program (NLP), which determines the optimal workload cutoff for each ER station such that the weighted sum of the area-wide expected response time and its variation are minimized. The concept of Marginal Cost of Uncertainty (MCU) is introduced to measure the impact of a station’s workload increase on the area-wide service performance. The solution of the NLP is proved to be equivalent to a state of equilibrium in which all stations …

Hybrid Laser/Arc Welding Of Difficult-To-Weld Thick Steel Plates In Different Joint Configurations: Issues And Resolutions, Nima Yazdian

Mechanical Engineering Research Theses and Dissertations

Difficult-to-weld steels are ferrous alloys that are characterized by a low thermal conductivity, and large thermal expansion coefficient. These intrinsic features contribute to a high level of distortion and cracking susceptibility during joining of these types of steels. In an effort to address the issues associated with difficult-to-weld steels, highly concentrated beam spots like electron and laser beam welding were developed. Usage of tightly focused heat sources have been accompanied by several challenges. An extremely precise fit-up requirement was considered as the most significant issue corresponding to application of either laser or electron beam. Recently, it was found that the …

Analytical And Experimental Study Of Laser Cladding Of Ni/Wc Metal Matrix Powders Reinforced With Rare Earth Elements Using A High Power Direct Diode Laser, Mohammed Sayeed

Mechanical Engineering Research Theses and Dissertations

The corrosion and wear are major limiting factors for steel in the harsh environments and can be controlled by depositing protective passive coatings. Nickel based alloy cladding of steel offers a solution by enabling better corrosion and wear resistance, and high bonding strength. The laser surface cladding of steel was conducted using a high power direct diode laser. Layers of tungsten carbide in Ni (40%Ni-60%WC) combined with 1% and 2% Lanthanum Oxide (La₂O₃) and Cerium Oxide (CeO₂) were deposited on ASTM A36 steel substrate. The X-ray diffraction and scanning electron microscopy were employed to …

Geo-Spatial Mapping As A Catalyst For Creative And Engaged Design In Engineering Education, Jessie Zarazaga

Multidisciplinary Studies Theses and Dissertations

Exploiting the technology of geo-spatial mapping student designers can develop deep understandings of the rich and layered data of a spatial context, a situational understanding essential to responsible civic design. However the actions inherent in the construction of spatial data armatures can simultaneously be harnessed as creative strategies, in which mapping processes become the context for generative spatial play. The ambition of this study is to propose efficient pedagogic structures to help prepare civil and environmental student engineers to be not only strong participants, but leaders, in the design of the built environment. The interpretation of site data, mapped as …

Behavior Of Geothermal Energy Piles Embedded In Rock, Ehab Sabi

Civil and Environmental Engineering Theses and Dissertations

Geothermal energy piles are categorized as closed systems. Energy piles are a relatively new technology which couples the structural role of traditional pile foundations to that of heat exchangers to fulfill the required energy demand of buildings and infrastructures. These foundations are equipped with pipes embedded in the concrete forming the pile. While connected to a heat pump, the fluid circulating inside these pipes provides the exchange of heat with the ground for heating and cooling purposes. As the undisturbed temperature at the shallower depths of the ground stays comparatively constant the whole year, being warmer than the surrounding temperature …

A Grammar Based Approach To Distributed Systems Fault Diagnosis Using Log Files, Stephen Hanka

Computer Science and Engineering Theses and Dissertations

Diagnosing and correcting failures in complex, distributed systems is difficult. In a network of perhaps dozens of nodes, each of which is executing dozens of interacting applications, sometimes from different suppliers or vendors, finding the source of a system failure is a confusing, tedious piece of detective work. The person assigned this task must trace the failing command, event, or operation through the network components and find a deviation from the correct, desired interaction sequence. After a deviation is identified, the failing applications must be found, and the fault or faults traced to the incorrect source code.

Often the primary …

Engineering A Bacterial Flagella Forest For Sensing And Actuation – A Progress Report, Xihe Liu, Shulin Ye, Isaac Oti, Lauren Metzinger

SMU Journal of Undergraduate Research

Flagella can be used to make magnetically-controlled microfluidic and nanoscale devices for biomedical applications in both vitro and vivo environments. They are capable of operating with high precision on the cellular and subcellular level. So far, scientists and engineers have successfully used monolithic inorganic materials or photoactive polymers [1] to mimic the helical bacterial flagella whose rotary-propulsion mechanism effectively overcomes the dominant viscous forces that prevail in a low Reynolds-number environment. Here, we focus on bacterial flagella and their rotary motion. The bacterial flagellum is an ideal biomaterial for constructing self-propelling nanoswimmers because it can reversibly change its geometry in …

Electrical System For Bioelectric Impedance Using Ad5933 Impedance Converter, Allison Garcia, Ahmet C. Sabuncu

SMU Journal of Undergraduate Research

Benchtop lab equipment, such as the HP4194A Precision Impedance Analyzer, offer accuracy and functionality but are often expensive and bulky. Although integrated circuits offer less functionality than benchtop equivalents, they can be a cheaper alternative for smaller applications. In this study, the AD5933 Impedance Converter was investigated as a low-cost option for impedance analysis of the bicep brachii. The AD5933 evaluation board was properly calibrated to measure human muscle by using an equivalent parallel circuit consisting of a 5 nF capacitor and a 1 kOhm resistor. Next, the impedance of the bicep was measured using the AD5933 as the experimental …

Finding Truth In Fake News: Reverse Plagiarism And Other Models Of Classification, Matthew Przybyla, David Tran, Amber Whelpley, Daniel W. Engels

SMU Data Science Review

As the digital age creates new ways of spreading news, fake stories are propagated to widen audiences. A majority of people obtain both fake and truthful news without knowing which is which. There is not currently a reliable and efficient method to identify “fake news”. Several ways of detecting fake news have been produced, but the various algorithms have low accuracy of detection and the definition of what makes a news item ‘fake’ remains unclear. In this paper, we propose a new method of detecting on of fake news through comparison to other news items on the same topic, as …

Framework For Evaluation Of Flash Flood Models In Wildfire-Prone Areas, Brian Cunningham, David Benepe, Bryan Cikatz, Evangelos Giakoumakis

SMU Data Science Review

Abstract. In this paper, we present an innovative framework for evaluating the increased risk of flash flooding in areas that have been subjected to wildfires. Wildfires cause large-scale damage to an area’s soil and vegetation thus increasing both the likelihood and severity of flash flooding. Utilizing remote sensing to analyze aerial imagery of areas that have been affected by wildfires, we can investigate how much a landscape has changed and how that may adversely affect downstream areas in the event of a flash flooding event. There are currently no established frameworks from which downstream local officials can quickly assess the …

Pedestrian Safety -- Fundamental To A Walkable City, Joshua Herrera, Patrick Mcdevitt, Preeti Swaminathan, Raghuram Srinivas

SMU Data Science Review

In this paper, we present a method to identify urban areas with a higher likelihood of pedestrian safety related events. Pedestrian safety related events are pedestrian-vehicle interactions that result in fatalities, injuries, accidents without injury, or near--misses between pedestrians and vehicles. To develop a solution to this problem of identifying likely event locations, we assemble data, primarily from the City of Cincinnati and Hamilton County, that include safety reports from a five year period, geographic information for these events, citizen survey of pedestrian reported concerns, non-emergency requests for service for any cause in the city, property values and public transportation …

Comparative Study Of Sentiment Analysis With Product Reviews Using Machine Learning And Lexicon-Based Approaches, Heidi Nguyen, Aravind Veluchamy, Mamadou Diop, Rashed Iqbal

SMU Data Science Review

In this paper, we present a comparative study of text sentiment classification models using term frequency inverse document frequency vectorization in both supervised machine learning and lexicon-based techniques. There have been multiple promising machine learning and lexicon-based techniques, but the relative goodness of each approach on specific types of problems is not well understood. In order to offer researchers comprehensive insights, we compare a total of six algorithms to each other. The three machine learning algorithms are: Logistic Regression (LR), Support Vector Machine (SVM), and Gradient Boosting. The three lexicon-based algorithms are: Valence Aware Dictionary and Sentiment Reasoner (VADER), Pattern, …

Improving Vix Futures Forecasts Using Machine Learning Methods, James Hosker, Slobodan Djurdjevic, Hieu Nguyen, Robert Slater

SMU Data Science Review

The problem of forecasting market volatility is a difficult task for most fund managers. Volatility forecasts are used for risk management, alpha (risk) trading, and the reduction of trading friction. Improving the forecasts of future market volatility assists fund managers in adding or reducing risk in their portfolios as well as in increasing hedges to protect their portfolios in anticipation of a market sell-off event. Our analysis compares three existing financial models that forecast future market volatility using the Chicago Board Options Exchange Volatility Index (VIX) to six machine/deep learning supervised regression methods. This analysis determines which models provide best …

Project Insight: A Granular Approach To Enterprise Cybersecurity, Sunna Quazi, Adam Baca, Sam Darsche

SMU Data Science Review

In this paper, we disambiguate risky activity corporate users are propagating with their software in real time by creating an enterprise security visualization solution for system administrators. The current problem in this domain is the lag in cyber intelligence that inhibits preventative security measure execution. This is partially due to the overemphasis of network activity, which is a nonfinite dataset and is difficult to comprehensively ingest with analytics. We address these concerns by elaborating on the beta of a software called "Insight" created by Felix Security. The overall solution leverages endpoint data along with preexisting whitelist/blacklist designations to unambiguously communicate …

Improving Gas Well Economics With Intelligent Plunger Lift Optimization Techniques, Atsu Atakpa, Emmanuel Farrugia, Ryan Tyree, Daniel W. Engels, Charles Sparks

SMU Data Science Review

In this paper, we present an approach to reducing bottom hole plunger dwell time for artificial lift systems. Lift systems are used in a process to remove contaminants from a natural gas well. A plunger is a mechanical device used to deliquefy natural gas wells by removing contaminants in the form of water, oil, wax, and sand from the wellbore. These contaminants decrease bottom-hole pressure which in turn hampers gas production by forming a physical barrier within the well tubing. As the plunger descends through the well it emits sounds which are recorded at the surface by an echo-meter that …