Statistics and Probability Commons^™

Predicting Wind Turbine Blade Erosion Using Machine Learning, Casey Martinez, Festus Asare Yeboah, Scott Herford, Matt Brzezinski, Viswanath Puttagunta

SMU Data Science Review

Using time-series data and turbine blade inspection assessments, we present a classification model in order to predict remaining turbine blade life in wind turbines. Capturing the kinetic energy of wind requires complex mechanical systems, which require sophisticated maintenance and planning strategies. There are many traditional approaches to monitoring the internal gearbox and generator, but the condition of turbine blades can be difficult to measure and access. Accurate and cost- effective estimates of turbine blade life cycles will drive optimal investments in repairs and improve overall performance. These measures will drive down costs as well as provide cheap and clean electricity …

Machine Learning In Support Of Electric Distribution Asset Failure Prediction, Robert D. Flamenbaum, Thomas Pompo, Christopher Havenstein, Jade Thiemsuwan

SMU Data Science Review

In this paper, we present novel approaches to predicting as- set failure in the electric distribution system. Failures in overhead power lines and their associated equipment in particular, pose significant finan- cial and environmental threats to electric utilities. Electric device failure furthermore poses a burden on customers and can pose serious risk to life and livelihood. Working with asset data acquired from an electric utility in Southern California, and incorporating environmental and geospatial data from around the region, we applied a Random Forest methodology to predict which overhead distribution lines are most vulnerable to fail- ure. Our results provide evidence …

Identifying Undervalued Players In Fantasy Football, Christopher D. Morgan, Caroll Rodriguez, Korey Macvittie, Robert Slater, Daniel W. Engels

SMU Data Science Review

In this paper we present a model to predict player performance in fantasy football. In particular, identifying high-performance players can prove to be a difficult problem, as there are on occasion players capable of high performance whose past metrics give no indication of this capacity. These "sleepers"' are often undervalued, and the acquisition of such players can have notable impact on a fantasy football team's overall performance. We constructed a regression model that accounts for players' past performance and athletic metrics to predict their future performance. The model we built performs favorably in predicting athlete performance in relation to other …

Seeing And Understanding Data, Beverly Wood, Charlotte Bolch

Publications

Visual displays of data are commonly used today in media reports online or in print. For example, data visualizations are sometimes used as a marketing tool to convince people to purchase a certain product, or they are displayed in articles or magazines as a way to graphically display data to emphasize a certain point. In general, it is hard to imagine the majority of disciplines in science and mathematics not using data visualizations. However, before standard data visualization techniques were developed (and accepted by the community), mathematicians and scientists very rarely used graphical displays or pictures to represent empirical data.

Machine Learning Predicts Aperiodic Laboratory Earthquakes, Olha Tanyuk, Daniel Davieau, Charles South, Daniel W. Engels

SMU Data Science Review

In this paper we find a pattern of aperiodic seismic signals that precede earthquakes at any time in a laboratory earthquake’s cycle using a small window of time. We use a data set that comes from a classic laboratory experiment having several stick-slip displacements (earthquakes), a type of experiment which has been studied as a simulation of seismologic faults for decades. This data exhibits similar behavior to natural earthquakes, so the same approach may work in predicting the timing of them. Here we show that by applying random forest machine learning technique to the acoustic signal emitted by a laboratory …

Longitudinal Analysis With Modes Of Operation For Aes, Dana Geislinger, Cory Thigpen, Daniel W. Engels

SMU Data Science Review

In this paper, we present an empirical evaluation of the randomness of the ciphertext blocks generated by the Advanced Encryption Standard (AES) cipher in Counter (CTR) mode and in Cipher Block Chaining (CBC) mode. Vulnerabilities have been found in the AES cipher that may lead to a reduction in the randomness of the generated ciphertext blocks that can result in a practical attack on the cipher. We evaluate the randomness of the AES ciphertext using the standard key length and NIST randomness tests. We evaluate the randomness through a longitudinal analysis on 200 billion ciphertext blocks using logistic regression and …

Texture-Based Deep Neural Network For Histopathology Cancer Whole Slide Image (Wsi) Classification, Nelson Zange Tsaku

Master of Science in Computer Science Theses

Automatic histopathological Whole Slide Image (WSI) analysis for cancer classification has been highlighted along with the advancements in microscopic imaging techniques. However, manual examination and diagnosis with WSIs is time-consuming and tiresome. Recently, deep convolutional neural networks have succeeded in histopathological image analysis. In this paper, we propose a novel cancer texture-based deep neural network (CAT-Net) that learns scalable texture features from histopathological WSIs. The innovation of CAT-Net is twofold: (1) capturing invariant spatial patterns by dilated convolutional layers and (2) Reducing model complexity while improving performance. Moreover, CAT-Net can provide discriminative texture patterns formed on cancerous regions of histopathological …

An Hdg Method For Dirichlet Boundary Control Of Convection Dominated Diffusion Pdes, Gang Chen, John R. Singler, Yangwen Zhang

Mathematics and Statistics Faculty Research & Creative Works

We first propose a hybridizable discontinuous Galerkin (HDG) method to approximate the solution of a convection dominated Dirichlet boundary control problem without constraints. Dirichlet boundary control problems and convection dominated problems are each very challenging numerically due to solutions with low regularity and sharp layers, respectively. Although there are some numerical analysis works in the literature on diffusion dominated convection diffusion Dirichlet boundary control problems, we are not aware of any existing numerical analysis works for convection dominated boundary control problems. Moreover, the existing numerical analysis techniques for convection dominated PDEs are not directly applicable for the Dirichlet boundary control …

Dietary Inflammatory Index And Non-Communicable Disease Risk: A Narrative Review, Catherine M. Phillips, Ling-Wei Chen, Barbara Heude, Jonathan Y. Bernard, Nicholas C. Harvey, Liesbeth Duijts, Sara M. Mensink-Bout, Kinga Polanska, Giulia Mancano, Matthew Suderman, Nitin Shivappa, James R. Hébert

Faculty Publications

There are over 1,000,000 publications on diet and health and over 480,000 references on inflammation in the National Library of Medicine database. In addition, there have now been over 30,000 peer-reviewed articles published on the relationship between diet, inflammation, and health outcomes. Based on this voluminous literature, it is now recognized that low-grade, chronic systemic inflammation is associated with most non-communicable diseases (NCDs), including diabetes, obesity, cardiovascular disease, cancers, respiratory and musculoskeletal disorders, as well as impaired neurodevelopment and adverse mental health outcomes. Dietary components modulate inflammatory status. In recent years, the Dietary Inflammatory Index (DII^®), a literature-derived …

Increased Dietary Inflammatory Index Is Associated With Schizophrenia: Results Of A Case–Control Study From Bahrain, Haitham Jahrami, Moez Al-Islam Faris, Hadeel Ghazzawi, Zahra Saif, Layla Habib, Nitin Shivappa, James R. Hébert

Faculty Publications

Background: Several studies have indicated that chronic low-grade inflammation is associated with the development of schizophrenia. Given the role of diet in modulating inflammatory markers, excessive caloric intake and increased consumption of pro-inflammatory components such as calorie-dense, nutrient-sparse foods may contribute toward increased rates of schizophrenia. This study aimed to examine the association between dietary inflammation, as measured by the dietary inflammatory index (DII^®), and schizophrenia. Methods: A total of 120 cases attending the out-patient department in the Psychiatric Hospital/Bahrain were recruited, along with 120 healthy controls matched on age and sex. The energy-adjusted DII (E-DII) was computed …

Identifying Risk Factors Related To Premature Birth Through Binary Logistic And Proportional Odds Ordinal Logistic Regression, Clayton Elwood

Electronic Theses and Dissertations

Premature birth has been identified as the single greatest cause of death worldwide in children under the age of five. This thesis will implement binary logistic regression and proportional odds ordinal logistic regression to predict different levels of premature birth and identify associated risk factors. The models will be built from the Center for Disease Control and Prevention's 2014 Vital Statistics Natality Birth Data containing nearly 4 million live births within the United States. Odds ratios and confidence intervals on risk factors were produced utilizing binary logistic regression.

Garch Modeling Of Value At Risk And Expected Shortfall Using Bayesian Model Averaging, Ismail Kheir

Theses and Dissertations

This thesis conducts Value at Risk (VaR) and Expected Shortfall (ES) estimation using GARCH modeling and Bayesian Model Averaging (BMA). BMA considers multiple models weighted by some information criterion. Through BMA, this thesis finds that VaR and ES estimates can be improved through enhanced modeling of the data generation process.

Beta Regression Models For Repeated-Measures Data Analysis, Nicholas A. Hein

Theses & Dissertations

Bounded data often give rise to uncorrectable skew and heteroscedasticity. Bounded data are a relatively frequent occurrence in clinical and research settings. For example, in neuropsychology, most neurocognitive tests are bounded, and subjects are repeatedly measured over time. The statistician needs to choose a model that accounts for the correlated nature of the repeated measures. The Beta distribution is a natural choice for modeling bounded data. Currently, generalized linear mixed models (GLMM) and generalized estimating equations (GEE) are two methods that can be used to model Beta distributed data with repeated measures. However, GLMMs and GEEs have limitations, i.e., GLMMs …

Sharing Of Injection Drug Preparation Equipment Is Associated With Hiv Infection: A Cross-Sectional Study, Laura J. Ball, Klajdi Puka, Mark Speechley, Ryan Wong, Brian Hallam, Joshua C. Weiner, Sharon Koivu, Michael S. Silverman

Epidemiology and Biostatistics Publications

Background: Sharing needles/syringes and sexual transmission are widely appreciated as means of HIV transmission among persons who inject drugs (PWIDs). London, Canada, is experiencing an outbreak of HIV among PWIDs, despite a large needle/syringe distribution program and low rates of needle/syringe sharing.

Objective: To determine whether sharing of injection drug preparation equipment (IDPE) is associated with HIV infection.

Methods: Between August 2016 and June 2017, individuals with a history of injection drug use and residence in London were recruited to complete a comprehensive questionnaire and HIV testing.

Results: A total of 127 participants were recruited; 8 were excluded because of …

Sample Size Calculation Of Clinical Trials With Correlated Outcomes, Dateng Li

Statistical Science Theses and Dissertations

In this thesis, we investigate sample size calculation for three kinds of clinical trials: (1). Randomized controlled trials (RCTs) with longitudinal count outcomes; (2). Cluster randomized trials (CRTs) with count outcomes; (3). CRTs with multiple binary co-primary endpoints.

Effective Statistical Energy Function Based Protein Un/Structure Prediction, Avdesh Mishra

LSU New Orleans Theses and Dissertations

Proteins are an important component of living organisms, composed of one or more polypeptide chains, each containing hundreds or even thousands of amino acids of 20 standard types. The structure of a protein from the sequence determines crucial functions of proteins such as initiating metabolic reactions, DNA replication, cell signaling, and transporting molecules. In the past, proteins were considered to always have a well-defined stable shape (structured proteins), however, it has recently been shown that there exist intrinsically disordered proteins (IDPs), which lack a fixed or ordered 3D structure, have dynamic characteristics and therefore, exist in multiple states. Based on …

Dietary Inflammatory Index And Its Relationship With Cervical Carcinogenesis Risk In Korean Women: A Case-Control Study, Sundara Raj Sreeja, Hyun Yi Lee, Minji Kwon, Nitin Shivappa, James R. Hébert, Mi Kyung Kim

Faculty Publications

Several studies have reported that diet’s inflammatory potential is related to chronic diseases such as cancer, but its relationship with cervical cancer risk has not been studied yet. The aim of this study was to investigate the association between Dietary Inflammatory Index (DII^®) and cervical cancer risk among Korean women. This study consisted of 764 cases with cervical intraepithelial neoplasia (CIN)1, 2, 3, or cervical cancer, and 729 controls from six gynecologic oncology clinics in South Korea. The DII was computed using a validated semiquantitative Food Frequency Questionnaire (FFQ). Odds ratios and 95% CI were calculated using multinomial …

Effectiveness Of High-Intensity Interval Training For Fitness And Mobility Post Stroke: A Systematic Review., Joshua C. Wiener, Amanda Mcintyre, Scott Janssen, Jeffrey Ty Chow, Cristina Batey, Robert Teasell

Epidemiology and Biostatistics Publications

OBJECTIVE: To evaluate the evidence on the effectiveness of high-intensity interval training (HIIT) in improving fitness and mobility post stroke. TYPE: Systematic review.

LITERATURE SURVEY: Medline, Embase, CINAHL, PsycINFO, and Scopus were searched for articles published in English up to January 2018.

METHODOLOGY: Studies were included if the sample was adult human participants with stroke, the sample size was ≥3, and participants received >1 session of HIIT. Study and participant characteristics, treatment protocols, and results were extracted.

SYNTHESIS: Six studies with a total of 140 participants met inclusion criteria: three randomized controlled trials and three pre-post studies. HIIT protocols ranged …

Prediction Of High School Graduation With Decision Trees, Andrea M. Lee

Graduate Theses/Dissertations

While working as an educator for the past fourteen years, we are always looking at data and determining ways to help our students. Graduation status is one area of interest. I wanted to apply statistical methods to try and find early indicators of those students who may drop out, thus being able to provide early intervention to those students. With early intervention, we may be able to lower our dropout rate. While studying different methods of pattern recognition, I found that the decision tree method in machine learning was the best for the data that I had collected. Decision trees …

Spatio-Temporal Analysis Of Tree Ring Chronology And Precipitation, Ruizhe Yin

Graduate Theses and Dissertations

Tree ring chronology data is known to reflect regional climate due to the strong impact of rainfall and temperature. Therefore, tree ring data can be used to reconstruct historical climate in order to understand how climate changed in the past and make prediction about the future behavior of the climate. For simplicity, this research only considers the influence of precipitation on tree ring growth within the New England area. A total of 94 measurement sites are used to record tree ring width over 881 years and corresponding precipitation data are given at some locations for 121 years. We developed a …