Physical Sciences and Mathematics Commons^™

Optimizing Barrier Removal To Restore Connectivity In Utah’S Weber Basin, Maggi Kraft

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

River barriers, such as dams, culverts and diversions are important for water conveyance, but disrupt river ecosystems and hydrologic processes. River barrier removal is increasingly used to restore and improve river habitat and connectivity. Most past barrier removal projects prioritized individual barriers using score-and-rank techniques, neglecting the spatial structure and cumulative change from multiple barrier removals. Similarly, most water demand models satisfy human water uses or, only prioritize aquatic habitat, failing to include both human and environmental water use benefits. In this study, a dual objective optimization model identified in-stream barriers that impede quality-weighted aquatic habitat connectivity for Bonneville cutthroat …

Investigating Genetic Algorithm Optimization Techniques In Video Games, Nathan Ambuehl

Undergraduate Honors Theses

Immersion is essential for player experience in video games. Artificial Intelligence serves as an agent that can generate human-like responses and intelligence to reinforce a player’s immersion into their environment. The most common strategy involved in video game AI is using decision trees to guide chosen actions. However, decision trees result in repetitive and robotic actions that reflect an unrealistic interaction. This experiment applies a genetic algorithm that explores selection, crossover, and mutation functions for genetic algorithm implementation in an isolated Super Mario Bros. pathfinding environment. An optimized pathfinding AI can be created by combining an elitist selection strategy with …

Evolutionary Game Theoretic Multi-Objective Optimization Algorithms And Their Applications, Yi Ren Cheng

Graduate Doctoral Dissertations

Multi-objective optimization problems require more than one objective functions to be optimized simultaneously. They are widely applied in many science fields, including engineering, economics and logistics where optimal decisions need to be taken in the presence of trade-offs between two or more conicting objectives. Most of the real world multi-objective optimization problems are NP-Hard problems. It may be too computationally costly to find an exact solution but sometimes a near optimal solution is sufficient. In these cases, Multi-Objective Evolutionary Algorithms (MOEAs) provide good approximate solutions to problems that cannot be solved easily using other techniques. However Evolutionary Algorithm is not …

Generalized Clusterwise Regression For Simultaneous Estimation Of Optimal Pavement Clusters And Performance Models, Mukesh Khadka

UNLV Theses, Dissertations, Professional Papers, and Capstones

The existing state-of-the-art approach of Clusterwise Regression (CR) to estimate pavement performance models (PPMs) pre-specifies explanatory variables without testing their significance; as an input, this approach requires the number of clusters for a given data set. Time-consuming ‘trial and error’ methods are required to determine the optimal number of clusters. A common objective function is the minimization of the total sum of squared errors (SSE). Given that SSE decreases monotonically as a function of the number of clusters, the optimal number of clusters with minimum SSE always is the total number of data points. Hence, the minimization of SSE is …

Deterministic And Probabilistic Methods For Seismic Source Inversion, Juan Pablo Madrigal Cianci

Mathematics & Statistics ETDs

The national Earthquake Information Center (NEIC) reports an occurrence of about 13,000 earthquakes every year, spanning different values on the Richter scale from very mild (2) to "giant earthquakes'' (8 and above). Being able to study these earthquakes provides useful information for a wide range of applications in geophysics. In the present work we study the characteristics of an earthquake by performing seismic source inversion; a mathematical problem that, given some recorded data, produces a set of parameters that when used as input in a mathematical model for the earthquake generates synthetic data that closely resembles the measured data. There …

Artificial Immune Systems: Applications, Multi-Class Classification, Optimizations, And Analysis, Brian Haroldo Schmidt

Dissertations

The focus of this research is the application of the Artificial Immune System (AIS) paradigm to a new research area along with the modifications necessary to adapt it to a new problem. In the past 10 years, there has been much research into the use of various Machine Learning (ML) algorithms in Network Flow Traffic Classification. AIS algorithms have thus far not been applied to this problem. Because AIS algorithms have been used extensively for Network Intrusion Detection applications, which is a similar area of research, the motivation to extend them to the network flow classification problem is clear.

This …

Inference In Networking Systems With Designed Measurements, Chang Liu

Doctoral Dissertations

Networking systems consist of network infrastructures and the end-hosts have been essential in supporting our daily communication, delivering huge amount of content and large number of services, and providing large scale distributed computing. To monitor and optimize the performance of such networking systems, or to provide flexible functionalities for the applications running on top of them, it is important to know the internal metrics of the networking systems such as link loss rates or path delays. The internal metrics are often not directly available due to the scale and complexity of the networking systems. This motivates the techniques of inference …

Renewable Energy Systems Optimization Using Monte Carlo Simulation And Evolutionary Algorithms, Nicolas Lopez

Open Access Theses & Dissertations

This Dissertation explores the Renewable Energy Integration Problem, and proposes a Genetic Algorithm embedded with a Monte Carlo simulation to solve large instances of the problem that are impractical to solve via full enumeration. The Renewable Energy Integration Problem is defined as finding the optimum set of components to supply the electric demand to a hybrid

microgrid. The components considered are solar panels, wind turbines, diesel generators, electric batteries, connections to the power grid and converters, which can be inverters and/or rectifiers. The methodology developed is explained as well as the combinatorial formulation. In addition, 2 case studies of a …

Nursing Approaches For Use And Sustainability Of Barcode Medication Administration Technology, Jackson Ngigi Njeru

Walden Dissertations and Doctoral Studies

Approximately 43.4% of medication errors occur at the time of administration despite the use of bar code medication administration (BCMA) System. This trend has prompted a national effort to mitigate this problem in the United States. Implementing BCMA in health care settings is one of those efforts. Studies focusing on the approaches employed by nurses when using this system are scant. The purpose of this qualitative case study was to investigate strategies nurses and their leaders use to ensure BCMA is implemented, maximized, and sustained. The technology acceptance model was used to guide the study. The 2 research questions addressed …

Deployment, Coverage And Network Optimization In Wireless Video Sensor Networks For 3d Indoor Monitoring, Tisha Lafaye Brown

Electronic Theses and Dissertations

As a result of extensive research over the past decade or so, wireless sensor networks (wsns) have evolved into a well established technology for industry, environmental and medical applications. However, traditional wsns employ such sensors as thermal or photo light resistors that are often modeled with simple omni-directional sensing ranges, which focus only on scalar data within the sensing environment. In contrast, the sensing range of a wireless video sensor is directional and capable of providing more detailed video information about the sensing field. Additionally, with the introduction of modern features in non-fixed focus cameras such as the pan, tilt …

Genetic Algorithm For University Course Timetabling Problem, Achini Kumari Herath

Electronic Theses and Dissertations

Creating timetables for institutes which deal with transport, sport, workforce, courses, examination schedules, and healthcare scheduling is a complex problem. It is difficult and time consuming to solve due to many constraints. Depending on whether the constraints are essential or desirable they are categorized as ‘hard’ and ‘soft’, respectively. Two types of timetables, namely, course and examination are designed for academic institutes. A feasible course timetable could be described as a plan for the movement of students and staff from one classroom to another, without conflicts. Being an NP-complete problem, many attempts have been made using varying computational methods to …

Maintaining High Performance Across All Problem Sizes And Parallel Scales Using Microkernel-Based Linear Algebra, Md Rakib Hasan

LSU Doctoral Dissertations

Linear algebra underlies a large proportion of computational problems. With the continuous increase of scale on modern hardware, performance of small sized linear algebra has become increasingly important. To overcome the shortcomings of conventional approaches, we employ a new approach using a microkernel framework provided by ATLAS to improve the performance of a few linear algebra routines for all problem sizes. Our initial research consists of improving the performance of parallel LU factorization in ATLAS for which we were able to achieve up to 2.07x and 2.66x speedup for small problems, up to 91% and 87% of theoretical peak performance …

Network Analytics For The Mirna Regulome And Mirna-Disease Interactions, Joseph Jayakar Nalluri

Theses and Dissertations

miRNAs are non-coding RNAs of approx. 22 nucleotides in length that inhibit gene expression at the post-transcriptional level. By virtue of this gene regulation mechanism, miRNAs play a critical role in several biological processes and patho-physiological conditions, including cancers. miRNA behavior is a result of a multi-level complex interaction network involving miRNA-mRNA, TF-miRNA-gene, and miRNA-chemical interactions; hence the precise patterns through which a miRNA regulates a certain disease(s) are still elusive. Herein, I have developed an integrative genomics methods/pipeline to (i) build a miRNA regulomics and data analytics repository, (ii) create/model these interactions into networks and use optimization techniques, motif …

Smart Ev Charging For Improved Sustainable Mobility, Ashutosh Shivakumar

Browse all Theses and Dissertations

The landscape of energy generation and utilization is witnessing an unprecedented change. We are at the threshold of a major shift in electricity generation from utilization of conventional sources of energy like coal to sustainable and renewable sources of energy like solar and wind. On the other hand, electricity consumption, especially in the field of transportation, due to advancements in the field of battery research and exponential technologies like vehicle telematics, is seeing a shift from carbon based to Lithium based fuel. Encouraged by 1. Decrease in the cost of Li – ion based batteries 2. Breakthroughs in battery chemistry …