Other Engineering Commons^™

Identifying Key Activity Indicators In Rats' Neuronal Data Using Lasso Regularized Logistic Regression, Avery Woods

Honors Theses

This thesis aims to identify timestamps of rats’ neuronal activity that best determine behavior using a machine learning model. Neuronal data is a complex and high-dimensional dataset, and identifying the most informative features is crucial for understanding the underlying neuronal processes. The Lasso regularization technique is employed to select the most relevant features of the data to the model’s prediction. The results of this study provide insights into the key activity indicators that are associated with specific behaviors or cognitive processes in rats, as well as the effect that stress can have on neuronal activity and behavior. Ultimately, it was …

Dimensionless Analysis Of Trajectories Of Cylindrical Objects Dropped Into Water In Two Dimensions, Yi Zhen

University of New Orleans Theses and Dissertations

Nondimensionalization is powerful technique and is widely applied in the study of fluid mechanics and engineering because it helps to reduce the number of free parameters, identify the relative size of effects of parameters, and gain a deeper insight of the essential nature of phenomena. The nondimensionalization of 2D theory has been completed by the author (Zhen et.al.,2020) and new dimensionless equations of motion were obtained. In this study, new dimensionless dynamic equations are extended by incorporating new parameters to cope with various environmental conditions. The new dimensionless analysis of dropped cylindrical objects is consisted of four parts.

Part 1, …

Convolutional Neural Networks For Deflate Data Encoding Classification Of High Entropy File Fragments, Nehal Ameen

University of New Orleans Theses and Dissertations

Data reconstruction is significantly improved in terms of speed and accuracy by reliable data encoding fragment classification. To date, work on this problem has been successful with file structures of low entropy that contain sparse data, such as large tables or logs. Classifying compressed, encrypted, and random data that exhibit high entropy is an inherently difficult problem that requires more advanced classification approaches. We explore the ability of convolutional neural networks and word embeddings to classify deflate data encoding of high entropy file fragments after establishing ground truth using controlled datasets. Our model is designed to either successfully classify file …

Optimizing Critical Values And Combining Axes For Multi-Axial Neck Injury Criteria, Ethan J. Gaston

Theses and Dissertations

The Air Force employs ejection seats in its high-performance aircraft. While these systems are intended to ensure aircrew safety, the ejection process subjects the aircrew to potentially injurious forces. System validation includes evaluation of forces against a standard which is linked to the probability of injury. The Muti-Axial Neck Injury Criteria (MANIC) was developed to account for forces in all six degrees of freedom. Unfortunately, the MANIC is applied to each of the three linear input directions separately and applies different criterion values for each direction. These three separate criteria create a lack of clarity regarding acceptable neck loading, leading …

They're Only Nuclear Weapons: An Exploratory Analysis Of Safety Climate Within The Nuclear Enterprise, Brandon M. Clements

Theses and Dissertations

By possessing nuclear weapons, the United States Air Force is inherently exposed to extreme safety concerns. With multiple setbacks in recent years (e.g., unauthorized transport of nuclear weapons, cheating scandals, and career dissatisfaction), some have begun to wonder how safe the nuclear enterprise truly is. Building upon the concept of safety climate, this study explores safety climate constructs and trends associated with current nuclear maintenance safety climate survey data.

A Study Of Mathematics Achievement, Placement, And Graduation Of Engineering Students, Sara Hahler Blazek

Doctoral Dissertations

The purpose of this study was to determine how background knowledge impacts freshmen engineering students' success at Louisiana Tech University in terms of grades in two different freshman classes and graduation. To determine what factors impact students, three different studies were implemented. The first study used linear regression to analyze which demographic and academic variables significantly impacted freshman math and engineering courses. Using regression discontinuity, the second study determined if the university's placement requirement for Pre-Calculus was appropriate. The final study analyzed factors that impact graduation for engineering students as well as other disciplines to determine which significant variables were …

Developing An Optimal Model For Infant Home Visitation, Isaac Atuahene

Doctoral Dissertations

The United States, Great Britain, Denmark, Canada and many other countries have accepted home visitation (HV) as a promising strategy for interventions for infants after births and for their mothers. Prior HV studies have focused on theoretical foundations, evaluations of programs, cost/benefit analysis and cost estimation by using hospital/payer/insurance data to prove its effectiveness and high cost. As governments and private organizations continue to fund HVs, it is an opportune time to develop and formulate operations research (OR) models of HV coverage, quality and cost so they might be used in program implementation as done for adult home healthcare (HHC) …

Modelling Supercomputer Maintenance Interrupts: Maintenance Policy Recommendations, Jagadish Cherukuri

Masters Theses

A supercomputer is a repairable system with large number of compute nodes interconnected to work in harmony to achieve superior computational performance. Reliability of such a complex system depends on an effective maintenance strategy that involves both emergency and preventive maintenance. This thesis analyzes the maintenance records of four supercomputers operational at The National Institute of Computational Science located at Oak Ridge National Laboratory. We propose to use the generalized proportional intensities model (GPIM) to model the maintenance interrupts as it can capture both the reliability parameters and maintenance parameters and allows the inclusion of both emergency and preventive maintenance. …

The Simulation & Evaluation Of Surge Hazard Using A Response Surface Method In The New York Bight, Michael H. Bredesen

UNF Graduate Theses and Dissertations

Atmospheric features, such as tropical cyclones, act as a driving mechanism for many of the major hazards affecting coastal areas around the world. Accurate and efficient quantification of tropical cyclone surge hazard is essential to the development of resilient coastal communities, particularly given continued sea level trend concerns. Recent major tropical cyclones that have impacted the northeastern portion of the United States have resulted in devastating flooding in New York City, the most densely populated city in the US. As a part of national effort to re-evaluate coastal inundation hazards, the Federal Emergency Management Agency used the Joint Probability Method …