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Statistical Improvements For Ecological Learning About Spatial Processes, Gaetan L. Dupont 2021 University of Massachusetts Amherst

Statistical Improvements For Ecological Learning About Spatial Processes, Gaetan L. Dupont

Masters Theses

Ecological inquiry is rooted fundamentally in understanding population abundance, both to develop theory and improve conservation outcomes. Despite this importance, estimating abundance is difficult due to the imperfect detection of individuals in a sample population. Further, accounting for space can provide more biologically realistic inference, shifting the focus from abundance to density and encouraging the exploration of spatial processes. To address these challenges, Spatial Capture-Recapture (“SCR”) has emerged as the most prominent method for estimating density reliably. The SCR model is conceptually straightforward: it combines a spatial model of detection with a point process model of the spatial distribution of ...


Monitoring Mammals At Multiple Scales: Case Studies From Carnivore Communities, Kadambari Devarajan 2021 University of Massachusetts Amherst

Monitoring Mammals At Multiple Scales: Case Studies From Carnivore Communities, Kadambari Devarajan

Doctoral Dissertations

Carnivores are distributed widely and threatened by habitat loss, poaching, climate change, and disease. They are considered integral to ecosystem function through their direct and indirect interactions with species at different trophic levels. Given the importance of carnivores, it is of high conservation priority to understand the processes driving carnivore assemblages in different systems. It is thus essential to determine the abiotic and biotic drivers of carnivore community composition at different spatial scales and address the following questions: (i) What factors influence carnivore community composition and diversity? (ii) How do the factors influencing carnivore communities vary across spatial and temporal ...


Characterizing Convolutional Neural Network Early-Learning And Accelerating Non-Adaptive, First-Order Methods With Localized Lagrangian Restricted Memory Level Bundling, Benjamin O. Morris 2021 Air Force Institute of Technology

Characterizing Convolutional Neural Network Early-Learning And Accelerating Non-Adaptive, First-Order Methods With Localized Lagrangian Restricted Memory Level Bundling, Benjamin O. Morris

Theses and Dissertations

This dissertation studies the underlying optimization problem encountered during the early-learning stages of convolutional neural networks and introduces a training algorithm competitive with existing state-of-the-art methods. First, a Design of Experiments method is introduced to systematically measure empirical second-order Lipschitz upper bound and region size estimates for local regions of convolutional neural network loss surfaces experienced during the early-learning stages. This method demonstrates that architecture choices can significantly impact the local loss surfaces traversed during training. Next, a Design of Experiments method is used to study the effects convolutional neural network architecture hyperparameters have on different optimization routines' abilities to ...


Wavelet Methods For Very-Short Term Forecasting Of Functional Time Series, Jared K. Nystrom 2021 Air Force Institute of Technology

Wavelet Methods For Very-Short Term Forecasting Of Functional Time Series, Jared K. Nystrom

Theses and Dissertations

Space launch operations at Kennedy Space Center and Cape Canaveral Space Force Station (KSC/CCSFS) are complicated by unique requirements for near-real time determination of risk from lightning. Lightning forecast weather sensor networks produce data that are noisy, high volume, and high frequency time series for which traditional forecasting methods are often ill-suited. Current approaches result in significant residual uncertainties and consequentially may result in forecasting operational policies that are excessively conservative or inefficient. This work proposes a new methodology of wavelet-enabled semiparametric modeling to develop accurate and timely forecasts robust against chaotic functional data. Wavelets methods are first used ...


Eradicating Zebra Mussels: What Works?, Elijah Davies 2021 Kennesaw State University

Eradicating Zebra Mussels: What Works?, Elijah Davies

Symposium of Student Scholars

The invasion of U.S lakes and rivers by the invasive species of zebra mussels called Dreissena polymorpha has caused catastrophic harm to the local ecosystem by reproducing and outcompeting native mussel species as well as harm to pipes leading into water sources by binding to surfaces and reproducing to the point that the mussels clog pipes. In addition, recreation areas must be closed due to the sharp shells making areas unusable. In the past, research has focused on individual molluscicides and their eradication of zebra mussels, as well as their effect on native flora and fauna. My research will ...


Ensemble Data Fitting For Bathymetric Models Informed By Nominal Data, Samantha Zambo 2021 The University of Southern Mississippi

Ensemble Data Fitting For Bathymetric Models Informed By Nominal Data, Samantha Zambo

Dissertations

Due to the difficulty and expense of collecting bathymetric data, modeling is the primary tool to produce detailed maps of the ocean floor. Current modeling practices typically utilize only one interpolator; the industry standard is splines-in-tension.

In this dissertation we introduce a new nominal-informed ensemble interpolator designed to improve modeling accuracy in regions of sparse data. The method is guided by a priori domain knowledge provided by artificially intelligent classifiers. We recast such geomorphological classifications, such as ‘seamount’ or ‘ridge’, as nominal data which we utilize as foundational shapes in an expanded ordinary least squares regression-based algorithm. To our knowledge ...


Investigation And Statistical Modeling Of The Mechanical Properties Of Additively Manufactured Lattices, Derek G. Spear, Anthony N. Palazotto 2021 Air Force Institute of Technology

Investigation And Statistical Modeling Of The Mechanical Properties Of Additively Manufactured Lattices, Derek G. Spear, Anthony N. Palazotto

Faculty Publications

This paper describes the background, test methodology, and experimental results associated with the testing and analysis of quasi-static compression testing of additively manufactured open-cell lattice structures. The study aims to examine the effect of lattice topology, cell size, cell density, and surface thickness on the mechanical properties of lattice structures. Three lattice designs were chosen, the Diamond, I-WP, and Primitive Triply Periodic Minimal Surfaces (TPMSs). Uniaxial compression tests were conducted for every combination of the three lattice designs, three cell sizes, three cell densities, and three surface thicknesses. In order to perform an efficient experiment and gain the most information ...


Weather, Values, Capacity And Concern: Toward A Social-Cognitive Model Of Specialty Crop Farmers’ Perceptions Of Climate Change Risk, Guang Han, Ethan D. Schoolman, J. Gordon Arbuckle, Lois Wright Morton 2021 University of Vermont

Weather, Values, Capacity And Concern: Toward A Social-Cognitive Model Of Specialty Crop Farmers’ Perceptions Of Climate Change Risk, Guang Han, Ethan D. Schoolman, J. Gordon Arbuckle, Lois Wright Morton

Sociology Publications

As specialty crop production has become increasingly important to U.S. agriculture, public and private stakeholders have called for research and outreach efforts centered on risks posed by climate change. Drawing on a survey of specialty crop farmers, this study explores farmers’ perceptions of climate change risks. Underlying cognitive, experiential, and socio-cultural factors hypothesized to influence farmers’ climate change risk perceptions are tested using structural equation modeling techniques. Results show that specialty crop farmers exhibit an overall moderate concern about climatic risks. The more capable and prepared farmers feel themselves to be, the less concerned they are about climate change ...


Rattle Detection – An Automotive Case Study, Orla Hartley 2021 Jaguar Land Rover

Rattle Detection – An Automotive Case Study, Orla Hartley

International Conference on Lean Six Sigma

This case study showcases the use of statistical tools to develop an objective Squeak and Rattle (S&R) measurement and detection test for End Of Line (EOL) sign off in an automotive manufacturing environment. Audio Induced S&R is an unwanted vibration within the vehicle caused by the sound system, impacting on customer perception of vehicle quality. Testing for S&R in an automotive environment has a key challenge; how to robustly detect a rattle at the EOL and thus prevent plant escapes to the customer. The objective test developed used microphones and analysers in order to replace an e subjective listening test. Within the testing equipment settings, the length of the frequency sweep and the volume level of the sweep can be adapted, which in turn influences the output graph of calculated rattle. A Design of Experiment (DOE) was employed to find the optimised parameters required for these factors. The DOE ...


Statistically Defensible Wind Tunnel Models, Timothy A. Roche 2021 Air Force Institute of Technology

Statistically Defensible Wind Tunnel Models, Timothy A. Roche

Theses and Dissertations

Wind tunnels are used to test scale-model air frames in order to collect aerodynamic data. The Subsonic Aerodynamic Research Laboratory (SARL) Wind Tunnel is a low speed wind tunnel located at Wright-Patterson Air Force Base. The SARL Wind Tunnel team approached AFIT for assistance in creating statistically defensible models for the conditions inside the wind tunnel. During a wind tunnel test, pressure sensors cannot be placed at the test model. Instead, pressure is measured by a pitot probe permanently mounted in the corner of the test chamber. The pressure at the model location is predicted from the measurements taken by ...


Anatomy Of A Conspiracy Theory: Law, Politics, And Science Denialism In The Era Of Covid-19, Brie Sherwin 2021 Texas Tech University School of Law

Anatomy Of A Conspiracy Theory: Law, Politics, And Science Denialism In The Era Of Covid-19, Brie Sherwin

Texas A&M Law Review

With COVID-19, we are facing the most serious public health threat of our lifetime. Now, more than ever, we need experts and sound scientific advice to guide critical decision-making during the pandemic. With conspiracy theories and other similar rhetorical weapons being used to discredit our scientific experts, we face a myriad of misinformation, mistruths, and all-out attacks on our experts, breeding distrust between the public and the policymakers leading the fight against the pandemic. As President Trump took office, scientists were routinely denigrated and isolated. Furthermore, science denialism has permeated its way up to the highest levels of government, resulting ...


Tennis Anyone? Teaching Experimental Design By Designing And Executing A Tennis Ball Experiment, Laura Pyott 2021 West Chester University of Pennsylvania

Tennis Anyone? Teaching Experimental Design By Designing And Executing A Tennis Ball Experiment, Laura Pyott

Mathematics Faculty Publications

Understanding the abstract principles of statistical experimental design can challenge undergraduate students, especially when learned in a lecture setting. This article presents a concrete and easily replicated example of experimental design principles in action through a hands-on learning activity for students enrolled in an experimental design course. The activity, conducted during five 50-min classes, requires the students to work as a team to design and execute a simple and safe factorial experiment and collect and analyze the data. During three in-class design meetings, the students design and plan all aspects of the experiment, including choosing the response variable and factors ...


The Wargaming Commodity Course Of Action Automated Analysis Method, William T. DeBerry 2021 Air Force Institute of Technology

The Wargaming Commodity Course Of Action Automated Analysis Method, William T. Deberry

Theses and Dissertations

This research presents the Wargaming Commodity Course of Action Automated Analysis Method (WCCAAM), a novel approach to assist wargame commanders in developing and analyzing courses of action (COAs) through semi-automation of the Military Decision Making Process (MDMP). MDMP is a seven-step iterative method that commanders and mission partners follow to build an operational course of action to achieve strategic objectives. MDMP requires time, resources, and coordination – all competing items the commander weighs to make the optimal decision. WCCAAM receives the MDMP's Mission Analysis phase as input, converts the wargame into a directed graph, processes a multi-commodity flow algorithm on ...


Analysis Of Functional Responses In Experimental Design, Matthew E. Scherer 2021 Air Force Institute of Technology

Analysis Of Functional Responses In Experimental Design, Matthew E. Scherer

Theses and Dissertations

The growth of sensor streamed data in recent years increases the demand for an analytical technique to properly address data measured continuously. The design and analysis of experiments (DOE) of U.S. Air Force assets are based off of sensor streamed data. Functional data analysis (FDA) is an approach of analyzing data existing over a continuum. This research aids in filling the intersection of FDA and DOE by examining a case study of an experimental design with a functional response in addition to insight on software capabilities in FDA. The case study considers a functional linear model of a whole-plot ...


Does Omitting Downstream Water Quality Change The Economic Benefits Of Nutrient Reduction? Evidence From A Discrete Choice Experiment, Yau-Huo (Jimmy) Shr, Wendong Zhang 2021 National Taiwan University

Does Omitting Downstream Water Quality Change The Economic Benefits Of Nutrient Reduction? Evidence From A Discrete Choice Experiment, Yau-Huo (Jimmy) Shr, Wendong Zhang

Economics Presentations, Posters and Proceedings

Discrete choice experiments have been extensively used to value environmental quality; however, some important attributes may be often omitted due to design challenges. In the case of agricultural water pollution, overlooking downstream water quality benefits could lead to biased estimates and misinterpretations of local water quality attributes presented in the choice experiments. Using a split-sample design and a statewide survey of Iowa residents, we provide the first systematic evaluation of how households’ willingness-to-pay for water quality change when downstream water quality benefits, hypoxic zone reduction in our case, are omitted. We find that omitting non-local water quality attributes significantly reduces ...


Carbon Dioxide And Particulate Matter Concentration On Hampton Roads Air Quality, Gregory Hubbard 2021 Old Dominion University

Carbon Dioxide And Particulate Matter Concentration On Hampton Roads Air Quality, Gregory Hubbard

OUR Journal: ODU Undergraduate Research Journal

Hampton Roads has been a maritime crossroads for the last 400 years. Industrialization has impacted the coastal region for the last 250 years. The expansion of the Port of Virginia in 2019 has created dense traffic in the region resulting in impacts to air quality. Two waste products that affect humans are particulate matter and carbon dioxide. Both respective emissions can cause adverse effects on humans, such as asthma, some lung cancers, and other respiratory distress. Scientists and health practitioners are studying the effects of particulate matter on human health. Hampton Roads, in particular, because of its unique location on ...


Joint Modeling Of Distances And Times In Point-Count Surveys, Adam Martin-Schwarze, Jarad Niemi, Philip Dixon 2021 University of Michigan

Joint Modeling Of Distances And Times In Point-Count Surveys, Adam Martin-Schwarze, Jarad Niemi, Philip Dixon

Statistics Publications

Removal and distance modeling are two common methods to adjust counts for imperfect detection in point-count surveys. Several recent articles have formulated models to combine them into a distance-removal framework. We observe that these models fall into two groups building from different assumptions about the joint distribution of observed distances and first times to detection. One approach assumes the joint distribution results from a Poisson process (PP). The other assumes an independent joint (IJ) distribution with its joint density being the product of its marginal densities. We compose an IJ+PP model that more flexibly models the joint distribution and ...


Exponential-Growth Prediction Bias And Compliance With Safety Measures Related To Covid-19, Ritwik Banerjee, Joydeep Bhattacharya, Priyama Majumdar 2021 Indian Institute of Management Bangalore

Exponential-Growth Prediction Bias And Compliance With Safety Measures Related To Covid-19, Ritwik Banerjee, Joydeep Bhattacharya, Priyama Majumdar

Economics Publications

We conduct a unique, Amazon MTurk-based global experiment to investigate the importance of an exponential growth prediction bias (EGPB) in understanding why the COVID-19 outbreak has exploded. The scientific basis for our inquiry is the well-established fact that disease spread, especially in the initial stages, follows an exponential function meaning few positive cases can explode into a widespread pandemic if the disease is sufficiently transmittable. We define prediction bias as the systematic error arising from faulty prediction of the number of cases x-weeks hence when presented with y-weeks of prior, actual data on the same. Our design permits us to ...


Management Of Multiple Sources Of Risk In Livestock Production, Melissa G. S. McKendree, Glynn T. Tonsor, Lee L. Schulz 2021 Michigan State University

Management Of Multiple Sources Of Risk In Livestock Production, Melissa G. S. Mckendree, Glynn T. Tonsor, Lee L. Schulz

Economics Publications

Firm operators continually manage multiple sources of risk. In an application to cattle feedlot operations, our objective is to determine if producers view output price and animal health risks separately or jointly. We conduct a survey with a choice experiment placing operators in forward looking, decision-making scenarios, and capture information on past risk management approaches. Evidence regarding a relationship between animal health and output price risk mitigation is mixed and depends on the decision being made. Combined, these results provide new insight into how managers approach multiple risks when facing resource constraints.


A Transdisciplinary Analysis Of Just Transition Pathways To 100% Renewable Electricity, Adewale Aremu Adesanya 2021 Michigan Technological University

A Transdisciplinary Analysis Of Just Transition Pathways To 100% Renewable Electricity, Adewale Aremu Adesanya

Dissertations, Master's Theses and Master's Reports

The transition to using clean, affordable, and reliable electrical energy is critical for enhancing human opportunities and capabilities. In the United States, many states and localities are engaging in this transition despite the lack of ambitious federal policy support. This research builds on the theoretical framework of the multilevel perspective (MLP) of sociotechnical transitions as well as the concept of energy justice to investigate potential pathways to 100 percent renewable energy (RE) for electricity provision in the U.S. This research seeks to answer the question: what are the technical, policy, and perceptual pathways, barriers, and opportunities for just transition ...


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