Physical Sciences and Mathematics Commons^™

Modeling Joint Survival Probabilities Of Runs Scored And Balls Faced In Limited Overs Cricket Using Copulas, Lochana K. Palayangoda, Hasika W. Senevirathne, Ananda B. Manage

Mathematics & Statistics Faculty Publications

In limited overs cricket, the goal of a batsman is to score a maximum number of runs within a limited number of balls. Therefore, the number of runs scored and the number of balls faced are the two key statistics used to evaluate the performance of a batsman. In cricket, as the batsmen play as pairs, having longer partnerships is also key to building strong innings. Moreover, having a steady opening partnership is extremely important as a team aims to build such a stronger innings. In this study, we have shown a way to evaluate the performance of opening partnerships …

Rock Paintings: Solutions For Fermi Questions, September 2022, John Adam

Mathematics & Statistics Faculty Publications

No abstract provided.

P-Adic Analysis: A Quick Introduction, Wilson A. Zuniga-Galindo

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

These notes aim to provide a fast introduction to p-adic analysis assuming basic knowledge in algebra and analysis. The text corresponds to the lecture notes for a Mini-Course in the L. Santal´o Research Summer School 2019. Palacio de la Magdalena, Santander, Spain, June 24-28, 2019.

Game Between The Third Party Payment Service Provider And Bank In Mobile Payment Market, Hui Jiang, Junhai Ma, Zhaosheng Feng

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

With the innovation and integration of the Internet and the financial industry, the third-party payment market has developed greatly and has great potential. This paper discusses the duopoly game between third-party payment service providers and banks, which are the main participants in the mobile payment market. By constructing Nash game model, the conditions of equilibrium point, stability and bifurcation are analyzed. The effects of adjusting parameters and cooperation coefficient on business volume and profit are discussed. The conclusions are as follows: excessive investment will lead to unpredictable fluctuations in the market and fall into chaos; By strengthening cooperation, all participants …

Maine Epscor, Vol. 1, Issue 1, Maine Epscor, University Of Maine, Kody Varahramyan, Shane Moeykens, Laurie Bragg, Daniel Timmermann, Jami Downing, Stefania Irene Marthakis, Christian Spindler, Bhavana Scalia-Bruce, Marcella Silver, Jennifer Smith-Mayo, Attis Bielecki, Grayson Huston, Markus Fredrich, Kristina Cammen

General University of Maine Publications

The University of Maine recently gained Carnegie R1 status, a level of recognition that speaks to the quality and scale of research happening at Maine’s land grant, sea grant, and space grant institution, and across the state as a whole. Research institutes, centers and labs established because of NSF EPSCoR RII Track-1 grants have created a significant and lasting impact in Maine. These entities include the Advanced Structures and Composites Center, Frontier Institute for Research in Sensor Technologies, Forest Bioproducts Research Institute, and Mitchell Center for Sustainability Solutions, which have generated over 500 million dollars in new R&D funding for …

Viscoelastic And Electromagnetic Materials With Nonlinear Memory, Claudio Giorgi, John Murrough Golden

Articles

A method is presented for generating free energies relating to nonlinear constitutive equations with memory from known free energies associated with hereditary linear theories. Some applications to viscoelastic solids and hereditary electrical conductors are presented. These new free energies are then used to obtain estimates for nonlinear integro-differential evolution problems describing the behavior of nonlinear plasmas with memory.

Free Energies For Nonlinear Materials With Memory, John Murrough Golden

Articles

An exploration of representations of free energies and associated rates of dissipation for a broad class of nonlinear viscoelastic materials is presented in this work. Also included are expressions for the stress functions and work functions derivable from such free energies. For simplicity, only the scalar case is considered. Certain standard formulae are generalized to include higher power terms.

It is shown that the correct initial procedure in this context is to specify the rate of dissipation as a positive semi-definite functional and then to determine the free energy from this, rather than the other way around, which would be …

Reducing Print Time While Minimizing Loss In Mechanical Properties In Consumer Fdm Parts, Long Le, Mitchel A. Rabsatt, Hamid Eisazadeh, Mona Torabizadeh

Mechanical & Aerospace Engineering Faculty Publications

Fused deposition modeling (FDM), one of various additive manufacturing (AM) technologies, offers a useful and accessible tool for prototyping and manufacturing small volume functional parts. Polylactic acid (PLA) is among the commonly used materials for this process. This study explores the mechanical properties and print time of additively manufactured PLA with consideration to various process parameters. The objective of this study is to optimize the process parameters for the fastest print time possible while minimizing the loss in ultimate strength. Design of experiments (DOE) was employed using a split-plot design with five factors. Analysis of variance (ANOVA) was employed to …

Editorial For The Special Issue On Micromachines For Non-Newtonian Microfluidics, Lanju Mei, Shizhi Qian

Mechanical & Aerospace Engineering Faculty Publications

In lieu of an abstract, this is an excerpt from the first page.

Microfluidics has seen a remarkable growth over the past few decades, with its extensive applications in engineering, medicine, biology, chemistry, etc [...]

Trust In Human-Robot Interaction Within Healthcare Services: A Review Study, Dedra Townsend, Amirhossein Majidirad

Mechanical & Aerospace Engineering Faculty Publications

There has always been a dilemma of the extent to which human can rely on machines in different activities of daily living. Ranging from riding on a self-driving car to having an iRobot vacuum clean the living room. However, when it comes to healthcare settings where robots are intended to work next to human, making decision gets difficult because repercussions may jeopardize people’s life. That has led scientists and engineers to take one step back and think out of the box. Having concept of trust under scrutiny, this study helps deciphering complex human-robot interaction (HRI) attributes. Screening essential constituents of …

Lasso: Listing All Subset Sums Obediently For Evaluating Unbounded Subset Sums, Christopher N. Burgoyne, Travis J. Wheeler

Graduate Student Theses, Dissertations, & Professional Papers

In this study we present a novel algorithm, LASSO, for solving the unbounded and bounded subset sum problem. The LASSO algorithm was designed to solve the unbounded SSP quickly and to return all subsets summing to a target sum. As speed was the highest priority, we benchmarked the run time performance of LASSO against implementations of some common approaches to the bounded SSP, as well as the only comparable implementation for solving the unbounded SSP that we could find. In solving the bounded SSP, our algorithm had a significantly faster run time than the competing algorithms when the target sum …

A Machine Learning Algorithm Improves Surface Freeze-Thaw Classification, Fredrick Bunt

Graduate Student Theses, Dissertations, & Professional Papers

The frozen or thawed state of the land surface is an important factor affecting a wide range of natural processes such as surface water movement, the carbon cycle, and ecosystem development. It is also important for human endeavors such as permafrost engineering and agricultural planning. This makes having an accurate record important. The Freeze-Thaw (FT) Earth System Data Record (FT-ESDR) is a global, daily product that strives to be a reliable record of the FT ground state. In its current form, the FT-ESDR uses annual regression analysis of reanalysis surface air temperatures (SAT) and brightness temperatures (Tb) at each grid …

Re-Modeling The Interior: Spatial Methods And Policy Revisions To Improve Inventory And Designation Of Blm’S Areas Of Critical Environmental Concern, Amy H. Katz

Graduate Student Theses, Dissertations, & Professional Papers

The Bureau of Land Management (BLM) manages a vast amount of public land in the western United States, most of which they currently manage for multiple uses. Specific conservation and management of these lands could mitigate climate change impacts and contribute to the global initiative to conserve 30 percent of lands and waters by 2030. Particularly, the agency can achieve this through more effective administration of Areas of Critical Environmental Concern (ACEC), a designation that is prioritized under the Federal Land Policy and Management Act (FLPMA). To do so requires updated regulations that set clear parameters around inventory and designation, …

Causes And Consquences Of Fire In Forest Ecosystems Of The Selway-Bitterroot Wilderness, Melissa Jaffe

Graduate Student Theses, Dissertations, & Professional Papers

No abstract provided.

A Non-Deterministic Deep Learning Based Surrogate For Ice Sheet Modeling, Hannah Jordan

Graduate Student Theses, Dissertations, & Professional Papers

Surrogate modeling is a new and expanding field in the world of deep learning, providing a computationally inexpensive way to approximate results from computationally demanding high-fidelity simulations. Ice sheet modeling is one of these computationally expensive models, the model used in this study currently requires between 10 and 20 minutes to complete one simulation. While this process is adequate for certain applications, the ability to use sampling approaches to perform statistical inference becomes infeasible. This issue can be overcome by using a surrogate model to approximate the ice sheet model, bringing the time to produce output down to a tenth …

Development Of Nanodisc Affinity Capillary Electrophoresis To Study The Interaction Of Giα Protein With Cell Membranes, Bethany R. Emeigh

Graduate Student Theses, Dissertations, & Professional Papers

Guanine nucleotide-binding proteins, or G-proteins, are crucial to cell signaling by acting as molecular switches through interactions with membrane-bound receptors. G-proteins have become of greater interest due to the possibility of novel drug targets. The G-protein alpha subunit, Gα, binds GTP before localizing to the membrane to interact with other G-protein subunits and G-protein-coupled receptors (GPCRs). Gi lacks a hydrophobic region to promote localization to the membrane, but a co-translational lipidation of the N-terminal residue stabilizes this interaction.

Protein interactions with biological membranes are challenging to study due to the complex structure of membranes and the often-limited quantities of the …

Trading Financial Instruments Like A Video Game: Searching For Profit Using Deep Reinforcement Learning., Sebastian Coombs

Graduate Student Theses, Dissertations, & Professional Papers

Buying and selling Stocks, Foreign Currencies (FOREX), Commodities, and Cryptocurrencies have been a source of wealth generation, and more often, wealth loss for many brave enough to enter the financial markets. In this paper, the author builds on the work of Williams, J. 2022 and develops an agent-based method to solve this wealth generation problem with the use of neural networks. The author points out some assumptions made by Williams, J. 2022 that were sound in theory, but made the implementation of the algorithm presented in their paper diverge from the theory. The author proposes a fundamentally different algorithmic method, …

Development Of Regional Landslide Susceptibility Models: A First Step Towards Model Transferability, Gina M. Belair

Graduate Student Theses, Dissertations, & Professional Papers

Landslides are a globally pervasive problem with the potential to cause significant fatalities and economic losses. Although landslides are widespread, many at-risk regions may not have the high-quality data or resources used in most landslide susceptibility analyses. This study aims to develop regional susceptibility relationships that are versatile and use publicly available data and open-sourced software. Logistic Regression and Frequency Ratio susceptibility relationships were developed in 23 regions in Washington, Utah, North Carolina, and Kentucky, with a region referring to a unique area and data combination. Regions were diverse in their geology, morphology, climate, and nature and quality of their …

Voices Of The Often Unheard: The Environmental Impacts Of Catastrophic Wildfire Events On Individuals With Developmental Disabilities, Mary Madison Mckenzie

Graduate Student Theses, Dissertations, & Professional Papers

The Thomas Fire for a time was the largest wildfire in California history, burning 281,893 acres and destroying 1,063 structures. Within three years, the August Complex Fire, at 1,032,649 acres, almost quadrupled that record. Climate related disasters such as these have impelled social science researchers to heed calls for a paradigm shift in understanding the risks climate change poses to the social world, in particular, disaster risks for vulnerable groups. Existing research tends to focus on disasters such as hurricanes, featuring risks for vulnerable populations by race, class, and/or individuals with disabilities in general, but not for individuals with developmental …

1-D Crustal Seismic Velocity Models For West-Central And Western Montana, Courtenay Duzet

Graduate Student Theses, Dissertations, & Professional Papers

In seismically active areas with infrequent, large-magnitude earthquakes, high-quality seismic data are critical for determining high-resolution, accurate seismic velocity models. Here, we present a new local-scale seismic velocity model for the crust in west-central Montana as well as a new regional-scale seismic velocity model for the crust and upper mantle across broader western Montana. The new models are constrained by phase arrivals from several passive seismic networks, including the University of Montana Seismic Network (UMSN), the Montana Regional Seismic Network (MRSN), the Advanced National Seismic System (ANSS), temporary deployments by the United States Geological Survey (USGS), and the USArray Transportable …

Catch My Drift? Perceptions And Experiences Of Pesticide Contamination Of Organic Crops In Montana, Sarah Rodgers

Graduate Student Theses, Dissertations, & Professional Papers

Pesticide drift and inadvertent contamination pose particular risks to organic production. Some organic producers have lost their crops, certification, and/or organic markets because of contamination events. Through this thesis research, I explain the perceptions and experiences that certified organic farmers in Montana have about drift and inadvertent pesticide contamination. I conducted semi-structured interviews with eleven certified organic farmers from various regions of Montana. Along with one-on-one interviews with organic farmers, interviews with industry and regulatory officials were conducted to better understand the policies and procedures that control what happens when drift occurs at the state level. Industry and regulatory official …

Combined Effects Of Temperature And Heavy Metals On The Performance Of The Giant Salmonfly., James Frakes, Amanda Andreas, Benjamin P. Colman, Aurthur Woods

Graduate Student Theses, Dissertations, & Professional Papers

In many freshwater ecosystems, communities of aquatic insects are facing the combined stresses of warmer waters due to climate change and increased exposure to heavy metal toxicants. Although each stressor may threaten aquatic insects independently, they also likely interact in important ways to affect insect physiology and performance. Here we investigate this potential interaction using two populations of aquatic nymphs of the giant salmonfly, Pteronarcys californica, collected from adjacent rivers in Montana: naïve individuals from Rock Creek, a relatively pristine stream, and individuals from the Upper Clark Fork River, which has a history of heavy metal pollution and higher …

Determining Spatial Controls On Snow Isotopic Signature And Tracing The Snowmelt Pulse As It Moves Through Two Montane Catchments, Jenna K. Rolle

Graduate Student Theses, Dissertations, & Professional Papers

In this study, we investigate the spatial and temporal distribution of stable isotopes of oxygen and hydrogen in water across two mountainous catchments in west-central Montana to trace the input of snow to local soil, bedrock aquifers, and streams. Snowpack and snowmelt samples were collected throughout the winter season at ten sites selected to encompass a range of elevation, aspect, slope angle and hillslope position. Soil and bedrock wells at five of the ten sites were sampled after the initial snowmelt pulse and stream samples were collected weekly at the outlets of both catchments to trace the timing and partitioning …

Machine Learning In Requirements Elicitation: A Literature Review, Cheligeer Cheligeer, Jingwei Huang, Guosong Wu, Nadia Bhuiyan, Yuan Xu, Yong Zeng

Engineering Management & Systems Engineering Faculty Publications

A growing trend in requirements elicitation is the use of machine learning (ML) techniques to automate the cumbersome requirement handling process. This literature review summarizes and analyzes studies that incorporate ML and natural language processing (NLP) into demand elicitation. We answer the following research questions: (1) What requirement elicitation activities are supported by ML? (2) What data sources are used to build ML-based requirement solutions? (3) What technologies, algorithms, and tools are used to build ML-based requirement elicitation? (4) How to construct an ML-based requirements elicitation method? (5) What are the available tools to support ML-based requirements elicitation methodology? Keywords …

Exploring Blockchain Adoption Supply Chains: Opportunities And Challenges, Adrian V. Gheorghe, Omer F. Keskin, Farinaz Sabz Ali Pour

Engineering Management & Systems Engineering Faculty Publications

In modern supply chains, acquisition often occurs with the involvement of a network of organizations. The resilience, efficiency, and effectiveness of supply networks are crucial for the viability of acquisition. Disruptions in the supply chain require adequate communication infrastructure to ensure resilience. However, supply networks do not have a shared information technology infrastructure that ensures effective communication. Therefore decision-makers seek new methodologies for supply chain management resilience. Blockchain technology offers new decentralization and service delegation methods that can transform supply chains and result in a more flexible, efficient, and effective supply chain. This report presents a framework for the application …

Precursors Of Email Response To Cybersecurity Scenarios: Factor Exploration And Scale Development, Miguel A. Toro-Jarrin, Pilar Pazos-Lago, Miguel Padilla

Engineering Management & Systems Engineering Faculty Publications

In the last decade, information security research has further expanded to include human factors as key elements of the organization's cybersecurity infrastructure. Numerous factors from several theories have been explored to explain and predict the multitude of information security-related behaviors in organizations. Lately, there has been a call for the study of specific cybersecurity behaviors in contextualized scenarios that reflect specific and realistic situations of a potential cyber-attack. This paper focuses on precursors of email response in situations that can be the origin of cybersecurity incidents in organizations (i.e., phishing attacks, ransomware, etc.). This study explores participants' intentions to follow …

A Literature Review On Combining Heuristics And Exact Algorithms In Combinatorial Optimization, Hesamoddin Tahami, Hengameh Fakhravar

Engineering Management & Systems Engineering Faculty Publications

There are several approaches for solving hard optimization problems. Mathematical programming techniques such as (integer) linear programming-based methods and metaheuristic approaches are two extremely effective streams for combinatorial problems. Different research streams, more or less in isolation from one another, created these two. Only several years ago, many scholars noticed the advantages and enormous potential of building hybrids of combining mathematical programming methodologies and metaheuristics. In reality, many problems can be solved much better by exploiting synergies between these approaches than by “pure” classical algorithms. The key question is how to integrate mathematical programming methods and metaheuristics to achieve such …

Humans And The Core Partition: An Agent-Based Modeling Experiment, Andrew J. Collins, Sheida Etemadidavan

Engineering Management & Systems Engineering Faculty Publications

Although strategic coalition formation is traditionally modeled using cooperative game theory, behavioral game theorists have repeatedly shown that outcomes predicted by game theory are different from those generated by actual human behavior. To further explore these differences, in a cooperative game theory context, we experiment to compare the outcomes resulting from human participants’ behavior to those generated by a cooperative game theory solution mechanism called the core partition. Our experiment uses an interactive simulation of a glove game, a particular type of cooperative game, to collect the participant’s decision choices and their resultant outcomes. Two different glove games are considered, …

A Probabilistic Perspective Of Human-Machine Interaction, Mustafa Canan, Mustafa Demir, Samuel Kovacic

Engineering Management & Systems Engineering Faculty Publications

Human-machine interaction (HMI) has become an essential part of the daily routine in organizations. Although the machines are designed with state-of-the-art Artificial Intelligence applications, they are limited in their ability to mimic human behavior. The human-human interaction occurs between two or more humans; when a machine replaces a human, the interaction dynamics are not the same. The results indicate that a machine that interacts with a human can increase the mental uncertainty that a human experiences. Developments in decision sciences indicate that using quantum probability theory (QPT) improves the understanding of human decision-making than merely using classical probability theory (CPT). …

The Other Legacy Of Qasim Amin: The View From 1908, Hoda Yousef

Faculty Publications

No abstract provided.