Physical Sciences and Mathematics Commons^™

Detection, Containment And Scaling Relations Of Near Source Explosionsin Granite Through Moment Tensor Representations, Mason Macphail

Earth Sciences Theses and Dissertations

The Source Phenomenology Experiment (SPE) was a series of nine, single-fired chemical explosions within the Morenci Copper mine in Arizona. Its purpose was to design, detonate, record and analyze seismic waveforms from these single-fired, partially and fully contained explosions. Ground motion data from the SPE are analyzed in this study to assess the uniqueness of the source representation of these explosions and its ability to resolve yield and depth when containment and geology or physical parameters of the source region may have a range of possible values. The P-wave velocities (V_p) at the test site are well constrained …

An Analysis Of Mixed-Layer Clay Minerals And Major Element Geochemical Trends In Middle-Upper Pennsylvanian-Aged Paleosols As A Proxy For Characterizing Basin-Wide Diagenetic Patterns And The Paleoenvironment Of The Illinois Basin, U.S.A., Julia A. Mcintosh

Earth Sciences Theses and Dissertations

Pennsylvanian-aged paleosols from four Illinois Basin (IB) cores were sampled to characterize clay mineralogy, paleosol morphology, and major element geochemistry. This data combined with X-ray diffraction (XRD) and X-ray fluorescence (XRF) data from two other stratigraphically equivalent cores were used to better understand basin-wide diagenetic patterns. Paleosols unimpacted by diagenesis are considered reliable proxies for continued geochemical analyses and paleoclimate interpretations of middle to late Pennsylvanian (Desmoinesian-Missourian) low-latitude environments.

Reichweite Ordering, as determined from XRD analysis ofprofiles, indicates that diagenesis impacted the deep interior of the basin and the southern portion of the basin. Further investigation of illitization mechanisms derived …

Optical Micro-Seismometer Based On Evanescent Field Perturbation Of Whispering Gallery Modes, Jaime Da Silva

Mechanical Engineering Research Theses and Dissertations

This thesis proposes a light-weight, compact, and accurate optical micro-seismometer that could be used in many applications, such as planetary exploration. The sensor proposed here is based on the principle of whispering gallery optical mode (WGM) resonance shifts of a dielectric micro-resonator due to disturbances of its evanescent field. The micro-seismometer could be used in place of the traditional bulky seismometers. The design of a waveguide-resonator and mechanical structure to disturb the evanescent field are presented. A proof-of-concept a seismometer model that uses a 5µm ring resonator is numerically tested with actual seismic data. The results show that a WGM-based …

Black Networks In Smart Cities, Shaibal Chakrabarty

Computer Science and Engineering Theses and Dissertations

In this dissertation, we present the Black Networks solution to protect both the data and the metadata for mobile ad-hoc Internet of Things (IoT) networks in Smart Cities. IoT networks are gaining popularity with billions of deployed nodes, and increasingly carrying mission-critical data, whose compromise can lead to catastrophic consequences. IoT nodes are resource-constrained and often exist within insecure environments, making them vulnerable to a broad range of active and passive attacks. Black IoT networks are designed to mitigate multiple communication-based attacks by encrypting the data and the metadata, within a communication frame or packet, while remaining compatible with the …

An Early Late Cretaceous Nodosaur From The Marine Eagle Ford Group Of North Central Texas, A Test Of The Endothermy In The Mosasaurs From The Late Cretaceous Of Angola, And The Ontogeny Of A New Pipid Frog From The Miocene Of Ethiopia, Matt Clemens

Earth Sciences Theses and Dissertations

The first two chapters of this dissertation detail the study of the newly recovered Holland Farm nodosaur (SMU 77100) from the Eagle Ford Group (95.29 ± 0.04 MA) of Mansfield in north central Texas. The objectives of this research are (1) to describe the anatomy of the Holland Farm nodosaur, (2) to determine its phylogenetic position within Ankylosauria, (3) to elaborate the substantial differences in body size and osteoderm morphology in armored dinosaurs occurring in north central Texas during the short duration of the Late Albian and Early Cenomanian, and (4) to provide a radiometric date for the lowermost member …

Indirect Imaging Using Computational Imaging Techniques, Aparna Viswanath

Electrical Engineering Theses and Dissertations

The work describes various methods employed towards solving the problem of indirect imaging. Computational techniques are employed to indirectly decipher information about an object hidden from view of a camera. Notion of virtualizing the source of illumination and detectors on real world rough surfaces was exploited to construct a non line of sight computational imager. Diversity was explored from the stand point of both illumination of the object and imaging of light reflected from the object. To understand the impact of scattering by real world rough surfaces, an instrument was developed that allows characterization of isoplanatic angle for different surface …

Overcoming Small Data Limitations In Heart Disease Prediction By Using Surrogate Data, Alfeo Sabay, Laurie Harris, Vivek Bejugama, Karen Jaceldo-Siegl

SMU Data Science Review

In this paper, we present a heart disease prediction use case showing how synthetic data can be used to address privacy concerns and overcome constraints inherent in small medical research data sets. While advanced machine learning algorithms, such as neural networks models, can be implemented to improve prediction accuracy, these require very large data sets which are often not available in medical or clinical research. We examine the use of surrogate data sets comprised of synthetic observations for modeling heart disease prediction. We generate surrogate data, based on the characteristics of original observations, and compare prediction accuracy results achieved from …

Fake News Detection: A Deep Learning Approach, Aswini Thota, Priyanka Tilak, Simrat Ahluwalia, Nibrat Lohia

SMU Data Science Review

Fake news is defined as a made-up story with an intention to deceive or to mislead. In this paper we present the solution to the task of fake news detection by using Deep Learning architectures. Gartner research [1] predicts that “By 2022, most people in mature economies will consume more false information than true information”. The exponential increase in production and distribution of inaccurate news presents an immediate need for automatically tagging and detecting such twisted news articles. However, automated detection of fake news is a hard task to accomplish as it requires the model to understand nuances in natural …

Random Forest Vs Logistic Regression: Binary Classification For Heterogeneous Datasets, Kaitlin Kirasich, Trace Smith, Bivin Sadler

SMU Data Science Review

Selecting a learning algorithm to implement for a particular application on the basis of performance still remains an ad-hoc process using fundamental benchmarks such as evaluating a classifier’s overall loss function and misclassification metrics. In this paper we address the difficulty of model selection by evaluating the overall classification performance between random forest and logistic regression for datasets comprised of various underlying structures: (1) increasing the variance in the explanatory and noise variables, (2) increasing the number of noise variables, (3) increasing the number of explanatory variables, (4) increasing the number of observations. We developed a model evaluation tool capable …

Predicting National Basketball Association Success: A Machine Learning Approach, Adarsh Kannan, Brian Kolovich, Brandon Lawrence, Sohail Rafiqi

SMU Data Science Review

In this paper, we present a machine learning based approach to projecting the success of National Basketball Association (NBA) draft prospects. With the proliferation of data, analytics have increasingly be- come a critical component in the assessment of professional and collegiate basketball players. We leverage player biometric data, college statistics, draft selection order, and positional breakdown as modelling features in our prediction algorithms. We found that a player's draft pick and their college statistics are the best predictors of their longevity in the National Basketball Association.

Minimizing The Perceived Financial Burden Due To Cancer, Hassan Azhar, Zoheb Allam, Gino Varghese, Daniel W. Engels, Sajiny John

SMU Data Science Review

In this paper, we present a regression model that predicts perceived financial burden that a cancer patient experiences in the treatment and management of the disease. Cancer patients do not fully understand the burden associated with the cost of cancer, and their lack of understanding can increase the difficulties associated with living with the disease, in particular coping with the cost. The relationship between demographic characteristics and financial burden were examined in order to better understand the characteristics of a cancer patient and their burden, while all subsets regression was used to determine the best predictors of financial burden. Age, …

Yelp’S Review Filtering Algorithm, Yao Yao, Ivelin Angelov, Jack Rasmus-Vorrath, Mooyoung Lee, Daniel W. Engels

SMU Data Science Review

In this paper, we present an analysis of features influencing Yelp's proprietary review filtering algorithm. Classifying or misclassifying reviews as recommended or non-recommended affects average ratings, consumer decisions, and ultimately, business revenue. Our analysis involves systematically sampling and scraping Yelp restaurant reviews. Features are extracted from review metadata and engineered from metrics and scores generated using text classifiers and sentiment analysis. The coefficients of a multivariate logistic regression model were interpreted as quantifications of the relative importance of features in classifying reviews as recommended or non-recommended. The model classified review recommendations with an accuracy of 78%. We found that reviews …

Cryptocurrency Price Prediction Using Tweet Volumes And Sentiment Analysis, Jethin Abraham, Daniel Higdon, John Nelson, Juan Ibarra

SMU Data Science Review

In this paper, we present a method for predicting changes in Bitcoin and Ethereum prices utilizing Twitter data and Google Trends data. Bitcoin and Ethereum, the two largest cryptocurrencies in terms of market capitalization represent over \$160 billion dollars in combined value. However, both Bitcoin and Ethereum have experienced significant price swings on both daily and long term valuations. Twitter is increasingly used as a news source influencing purchase decisions by informing users of the currency and its increasing popularity. As a result, quickly understanding the impact of tweets on price direction can provide a purchasing and selling advantage to …

Design And Synthesis Of Circadian Clock Modulators And The Study Of Lov Domain Protein Lkp2 In Arabidosis Thaliana And Brassica Rapa, Aditi Nagar

Chemistry Theses and Dissertations

Circadian rhythms are self-autonomous endogenous clocks synchronized with the rotation of the Earth. With the Earth’s rotation and revolution on its axis, the internal clock undergoes oscillation in the period of ~24 hour and governs day to day activities in most organisms. In humans, it regulates the day to day physiological activities. Today’s modern lifestyle has an impact on health: shift work, jet lag, and irregular eating habits contribute to the misalignment of the endogenous circadian oscillator, thereby, increasing the risk of many metabolic disorders including diabetes, irregular blood pressure, sleep disorders, obesity, depression, and cancer. The primary goal of …

Cloud Service Reliability And Usability Measurement, Abdullah Bokhary

Computer Science and Engineering Theses and Dissertations

Cloud computing has become a major resource for fulfilling people's computational and storage needs. Investing in these services requires measuring and assuring its quality in general, and reliability and usability are primary concerns. However, using traditional reliability models can be challenging because of the environmental constraints and limited data availability due to the heterogeneous environment and diverse stakeholders. Also, the quality of cloud service Application Programming Interfaces (APIs) has a direct impact on the usability and reliability of the service.

We developed a framework to measure reliability with alternative available information that most cloud providers offer in three stages: 1) …

The Transition From Sevier To Laramide Orogeny Captured In Upper-Plate Magmatic Structures, Eastern Transverse Ranges, Ca, Brody Friesenhahn

Earth Sciences Theses and Dissertations

The onset of the Laramide orogeny is of great tectonic significance to the geologic history of the US, but the timing and nature of the shift between Sevier and Laramide tectonics remains enigmatic. The eastern Transverse Ranges of southern California provide the opportunity to observe the effects of Laramide tectonics on the mid-crust. Wide Canyon is a north/south-trending canyon in the northern Little San Bernardino Mountains of the eastern Transverse Ranges. Al-in-hornblende thermobarometry of Needy et al. (2009) yields a projected paleodepth depth of ~20 km for Wide Canyon where Cretaceous granitoids intrude metamorphic country rock of Proterozoic age in …

Goalie Analytics: Statistical Evaluation Of Context-Specific Goalie Performance Measures In The National Hockey League, Marc Naples, Logan Gage, Amy Nussbaum

SMU Data Science Review

In this paper, we attempt to improve upon the classic formulation of save percentage in the NHL by controlling the context of the shots and use alternative measures than save percentage. In particular, we find save percentage to be both a weakly repeatable skill and predictor of future performance, and we seek other goalie performance calculations that are more robust. To do so, we use three primary tests to test intra-season consistency, intra-season predictability, and inter-season consistency, and extend the analysis to disentangle team effects on goalie statistics. We find that there are multiple ways to improve upon classic save …

Fuel Flow Reduction Impact Analysis Of Drag Reducing Film Applied To Aircraft Wings, Damon Resnick, Chris Donlan, Nimish Sakalle, Cody Pinkerman

SMU Data Science Review

In this paper, we present an analysis of flight data in order to determine whether the application of the Edge Aerodynamix Conformal Vortex Generator (CVG), applied to the wings of aircraft, reduces fuel flow during cruising conditions of flight. The CVG is a special treatment and film applied to the wings of an aircraft to protect the wings and reduce the non-laminar flow of air around the wings during flight. It is thought that by reducing the non-laminar flow or vortices around and directly behind the wings that an aircraft will move more smoothly through the air and provide a …

Data Center Application Security: Lateral Movement Detection Of Malware Using Behavioral Models, Harinder Pal Singh Bhasin, Elizabeth Ramsdell, Albert Alva, Rajiv Sreedhar, Medha Bhadkamkar

SMU Data Science Review

Data center security traditionally is implemented at the external network access points, i.e., the perimeter of the data center network, and focuses on preventing malicious software from entering the data center. However, these defenses do not cover all possible entry points for malicious software, and they are not 100% effective at preventing infiltration through the connection points. Therefore, security is required within the data center to detect malicious software activity including its lateral movement within the data center. In this paper, we present a machine learning-based network traffic analysis approach to detect the lateral movement of malicious software within the …

Predictions Generated From A Simulation Engine For Gene Expression Micro-Arrays For Use In Research Laboratories, Gopinath R. Mavankal, John Blevins, Dominique Edwards, Monnie Mcgee, Andrew Hardin

SMU Data Science Review

In this paper we introduce the technical components, the biology and data science involved in the use of microarray technology in biological and clinical research. We discuss how laborious experimental protocols involved in obtaining this data used in laboratories could benefit from using simulations of the data. We discuss the approach used in the simulation engine from [7]. We use this simulation engine to generate a prediction tool in Power BI, a Microsoft, business intelligence tool for analytics and data visualization [22]. This tool could be used in any laboratory using micro-arrays to improve experimental design by comparing how predicted …

Data Scientist’S Analysis Toolbox: Comparison Of Python, R, And Sas Performance, Jim Brittain, Mariana Cendon, Jennifer Nizzi, John Pleis

SMU Data Science Review

A quantitative analysis will be performed on experiments utilizing three different tools used for Data Science. The analysis will include replication of analysis along with comparisons of code length, output, and results. Qualitative data will supplement the quantitative findings. The conclusion will provide data support guidance on the correct tool to use for common situations in the field of Data Science.

Predicting Game Day Outcomes In National Football League Games, Josh Klein, Anna Frowein, Chris Irwin

SMU Data Science Review

In this paper, we present a model for predicting the game day outcomes of National Football League games. 3 of the most popular sources for game day predictions are analyzed for comparison. Player data and outcomes from previous games are used, but we also incorporate several weather factors into our models. Over 1,700 games were incorporated and 3 separate models are created using simple regression, principal component analysis, and a recursive model. We also discuss the ethicality of using data science techniques by individuals with the knowledge in order to gain an advantage over a population lacking this specialized training.

Supervised Machine Learning Bot Detection Techniques To Identify Social Twitter Bots, Phillip George Efthimion, Scott Payne, Nicholas Proferes

SMU Data Science Review

In this paper, we present novel bot detection algorithms to identify Twitter bot accounts and to determine their prevalence in current online discourse. On social media, bots are ubiquitous. Bot accounts are problematic because they can manipulate information, spread misinformation, and promote unverified information, which can adversely affect public opinion on various topics, such as product sales and political campaigns. Detecting bot activity is complex because many bots are actively trying to avoid detection. We present a novel, complex machine learning algorithm utilizing a range of features including: length of user names, reposting rate, temporal patterns, sentiment expression, followers-to-friends ratio, …

Cryptovisor: A Cryptocurrency Advisor Tool, Matthew Baldree, Paul Widhalm, Brandon Hill, Matteo Ortisi

SMU Data Science Review

In this paper, we present a tool that provides trading recommendations for cryptocurrency using a stochastic gradient boost classifier trained from a model labeled by technical indicators. The cryptocurrency market is volatile due to its infancy and limited size making it difficult for investors to know when to enter, exit, or stay in the market. Therefore, a tool is needed to provide investment recommendations for investors. We developed such a tool to support one cryptocurrency, Bitcoin, based on its historical price and volume data to recommend a trading decision for today or past days. This tool is 95.50% accurate with …

Case Study: Using Crime Data And Open Source Data To Design A Police Patrol Area, Brent Allen

SMU Data Science Review

This case study examines how to use existing crime data augmented with open source data to design a patrol area. We used the a demand signal of "calls for service" vice reports which summarize calls for service. Additionally, we augmented our existing data with traffic data from Google Maps. Traffic delays did not correspond to traffic incidents reported in the area examined. These data were plotted geographically to aid in the determination of the new patrol area. The new patrol area was created around natural geographic boundaries, the density of calls for service and police operational experience.

Machine Learning To Predict College Course Success, Anthony R.Y. Dalton, Justin Beer, Sriharshasai Kommanapalli, James S. Lanich Ph.D.

SMU Data Science Review

In this paper, we present an analysis of the predictive ability of machine learning on the success of students in college courses in a California Community College. The California Legislature passed assembly bill 705 in order to place students in non-remedial coursework, based on high school transcripts, to increase college completion. We utilize machine learning methods on de-identified student high school transcript data to create predictive algorithms on whether or not the student will be successful in college-level English and Mathematics coursework. To satisfy the bill’s requirements, we first use exploratory data analysis on applicable transcript variables. Then we use …

Association Tests For Genetic Effect And Its Interaction With Environmental Factors, Zhengyang Zhou

Statistical Science Theses and Dissertations

My research is in the area of statistical genetics, and it contains three projects: (1) Differentiating the Cochran-Armitage (CA) trend test and Pearson’s chi-square test: location and dispersion; (2) Decomposing Pearson’s chi-square test: a linear regression and its departure from linearity; (3) Testing nonlinear gene-environment (GxE) interaction through varying coefficient and linear mixed models.

(1) In genetic case-control association studies, a standard practice is to perform the CA trend test with 1 degree-of-freedom (df) under the assumption of an additive model. However, when the true genetic model is recessive or near recessive, it is outperformed by Pearson’s chi-square test with …

A Microresonator-Based Laser Doppler Velocity Sensor For Interplanetary Atmospheric Re-Entry, Benjamin Wise

Mechanical Engineering Research Theses and Dissertations

In this thesis, a laser velocity sensor concept based on optical microresonators is presented and the application to spacecraft atmospheric entry is explored. The concept is based on the measurement of Doppler shift of back-scattered laser light. Specifically, the Doppler shift is detected by observing the whispering gallery optical modes (WGM) of a dielectric microresonator excited by the back scattered light from particulates and gas molecules. The microresonator replaces the typical Fabry-Perot interferometer and CCD camera system, thereby significantly reducing the size and weight of the overall detection system. This thesis presents proof-of-concept results for this measurement approach. The Doppler …

Multi-Reference Systems In Chemistry; Unconventional Bonding In Organic Chemistry; Covalent Bonding In Transition Metal Clusters, Alan Wilfred Humason

Chemistry Theses and Dissertations

The geometries, chemical properties, and reactivities of molecules are determined by their electronic structure. The field of ab initio computational chemistry works to calculate the kinetic and potential energies between the nuclei and electrons of a molecule. These calculations usually begin with the determination the electronic ground state.

Molecules that cannot be adequately described with a single, ground state configuration are called \textit{multi-reference systems}, which require the calculation of a linear combination of all pertinent electronic configurations, with a corresponding increase in computational cost. This is not `black box' methodology, because solving these systems requires a good understanding of the …

Cretaceous Dinosaurs And The World They Lived In: A New Species Of Ornithischian Dinosaur From The Early Cretaceous (Aptian) Of Texas, Reconstruction Of The Brain Endocast And Inner Ear Of Malawisaurus Dixeyi, And Reconstruction Of The Paleoclimate And Paleoenvironment Of Cretaceous Terrestrial Formations In Texas And Oklahoma Using Pedogenic Minerals, Kate Andrzejewski

Earth Sciences Theses and Dissertations

Material from over thirty individuals of a new ornithopod was recovered from the Proctor Lake locality in the Twin Mountains Formation (Aptian) of north-central Texas. This material includes various ontogenetic stages, providing insight into the growth patterns of this species. The new ornithopod is recovered basal to Iguanodontia, but more derived than Hypsilophodon foxii. The presence and morphology of 4 premaxillary teeth along with a combination of both basal and derived characters distinguish this taxon from all other ornithopods.

A braincase of the Cretaceous titanosaurian sauropod Malawisaurus dixeyi was CT scanned and a 3D rendering of the endocast and inner …