Physical Sciences and Mathematics Commons^™

Models Of Pasture Production To Aid On-Farm Decision Making In New Zealand, J A. Baars, M D. Rollo

IGC Proceedings (1977-2023)

Two microcomputer-based predictive pasture models, for use in decision making by agricultural consultants and industry, are described. The first model (GRASS) was developed to understand the interactions between environment and management. The second model supplies pasture growth rates for current or predicted weather conditions by adjustment of stored actual average fortnightly pasture growth rates for a wide range of measurement sites. Ways are described in which the models are being used in transfer of technology.

Graze Model: Importance Of Simulating Conceptual Grazing Areas Within A Paddock, Otto J. Loewer, L D. Parsch, H D. Scott, C P. West, A L. Goetsch

IGC Proceedings (1977-2023)

The selective grazing logic within the computer simulation model GRAZE was tested to determine if predicted ·results differed appreciably from situations ·where non-selective grazing logic· was used. Results indicated that predictions would_ differ somewhat." The main cause of the differences was determined to be the simulated levels of plant dry matter availability, which were considerably higher when non-selective· grazing was used.

Cluster Effect For Snp-Snp Interaction Pairs For Predicting Complex Traits, Hui Yi Lin, Harun Mazumder, Indrani Sarkar, Po Yu Huang, Rosalind A. Eeles, Zsofia Kote-Jarai, Kenneth R. Muir, Johanna Schleutker, Nora Pashayan, Jyotsna Batra, David E. Neal, Sune F. Nielsen, Børge G. Nordestgaard, Henrik Grönberg, Fredrik Wiklund, Robert J. Macinnis, Christopher A. Haiman, Ruth C. Travis, Janet L. Stanford, Adam S. Kibel, Cezary Cybulski, Kay Tee Khaw, Christiane Maier, Stephen N. Thibodeau, Manuel R. Teixeira, Lisa Cannon-Albright, Hermann Brenner, Radka Kaneva, Hardev Pandha, Et Al

School of Public Health Faculty Publications

Single nucleotide polymorphism (SNP) interactions are the key to improving polygenic risk scores. Previous studies reported several significant SNP-SNP interaction pairs that shared a common SNP to form a cluster, but some identified pairs might be false positives. This study aims to identify factors associated with the cluster effect of false positivity and develop strategies to enhance the accuracy of SNP-SNP interactions. The results showed the cluster effect is a major cause of false-positive findings of SNP-SNP interactions. This cluster effect is due to high correlations between a causal pair and null pairs in a cluster. The clusters with a …

The Impact Of “Multiple Looks” When Performing Survival Analysis, Quentin Eloise

Electronic Theses and Dissertations

Survival analysis is a critical statistical method in healthcare to assess patient treatment effects and disease progression. Another critical area of statistical methodology in health care is the practice of adaptive designs. Adaptive designs allow for interim analyses to take place during a study and various decisions and actions can take place more ethically. This is beneficial for studies that take multiple years to complete and allows administrators and healthcare providers to make sound decisions as early as possible. A challenging aspect of adaptive designs is that the number of interim analyses is known in advance which is applicable in …

Simulation Study On Confidence Interval Estimation For Standard Deviation With Non-Normal Distributions, Theophilus Oppong Kyeremeh

Electronic Theses and Dissertations

This study explores innovative approaches to constructing confidence intervals for the population standard deviation, σ, in non-normal data scenarios. While the sample standard deviation, s, is widely used, its reliability is compromised when dealing with skewed or heavy-tailed distributions and exhibits sensitivity to outliers. Our research addresses these limitations by investigating alternative estimation methods that offer greater robustness and accuracy.

Intrinsic Universality In Tile Automata And Related Results, Elise C. Grizzell

Theses and Dissertations

The Tile Automata (TA) model describes self-assembly systems in which monomers can build structures and transition with an adjacent monomer to change their states. This paper shows that seeded TA is a non-committal intrinsically universal model of self-assembly. We present a single universal Tile Automata system containing approximately 4600 states that can simulate (a) the output assemblies created by any other Tile Automata system Γ, (b) the dynamics involved in building Γ’s assemblies, and (c) Γ’s internal state transitions. It does so in a non-committal way: it preserves the full non-deterministic dynamics of a tile’s potential attachment or transition by …

Using Cache Files To Improve The Efficiency Of The Ucgretina Simulation Code, Blake Mcnulty

Physics and Astronomy Summer Fellows

UCGretina is a program that is used to simulate the Gretina gamma-ray tracking array used in experiments at the Facility for Rare Isotope Beams (FRIB) to collect gamma rays produced in reactions such as proton scattering. This is done by generating a simulation of the beam particles used and sending them into a simulated recreation that mimics the experimental environment. My job this summer was to tackle a major issue that the program had which is the speed or efficiency at which it ran. The main issue was that it would take days for certain simulation sets to run which …

Integrating Biophysical And Economic Models For Assessing Impacts Of Change On Grazingland Ecosystems, J De Souza Neto, J R. Conner, J W. Stuth, W T. Hamilton, J W. Richardson

IGC Proceedings (1977-2023)

PHYGROW, a hydrologic-based forage simulation model, was parameterized to represent a typical South Texas ranch engaged in the production of cattle and meat goats with an indigenous population of white-tailed deer. Forage production and associated stocking rates for two cattle: goat ratios were simulated for 20 years. Two, ten-year weather scenarios, one representing normal conditions (30% drought years) and one representing dryer weather conditions (50% drought years) were analyzed. Management decision rules were developed for the region to produce estimates of annual animal production and operating cost for the enterprises in each of the four scenarios. These performance and cost …

Qwixx Strategies Using Simulation And Mcmc Methods, Joshua W. Blank

Master's Theses

This study explores optimal strategies for maximizing scores and winning in the popular dice game Qwixx, analyzing both single and multiplayer gameplay scenarios. Through extensive simulations, various strategies were tested and compared, including a scorebased approach that uses a formula tuned by MCMC random walks, and race-to-lock approaches which use absorbing Markov chain qualities of individual score sheet rows to find ways to lock rows as quickly as possible. Results indicate that employing a scorebased strategy, considering gap, count, position, skip, and likelihood scores, significantly improves performance in single player games, while move restrictions based on specific dice roll sums …

Value Added Tax Rate Variation, Import Demand And Sectoral Output In Nigeria, Joshua K. Nomkuha, Aondoawase Asooso, Philip T. Abachi

CBN Journal of Applied Statistics (JAS)

This study employs computable general equilibrium (CGE) model to estimate the effect of increase in value added tax (VAT), from 5 per cent to 7.5 per cent, on import demand and sectoral output in Nigeria. The study uses 2020 as the base year for the data analysis. The results show that increase in VAT affects import demand negatively, based on import penetration ratios, with mixed effect across six sectors. The implication of the result is that the VAT policy discourage consumption of foreign products, and constitute excess burden to consumers of such products in Nigeria. The results further reveal that …

Stock Market Volatility In The United Kingdom: Simulating Post-Covid-19 Recovery, Bala A. Dahiru, Mohammed Shuaibu, Najibullah Hassanov

CBN Journal of Applied Statistics (JAS)

This paper investigates the time it would take for the FTSE-100 index to reach its post-COVID-19 peak. The paper utilises an exponential generalised autoregressive conditional heteroscedasticity (EGARCH) model that accounts for leverage effect and asymmetries. The preferred models amongst competing variants was the Autoregressive Moving Average (ARMA)-EGARCH(2,1) specification and was used to predict daily FTSE-100 data from 5th January 2000 to 21st June 2024. The empirical exercise showed that the COVID-19-induced financial crisis negatively affected the United Kingdom’s stock market performance. The results show that the FTSE100 index could reach its post-pandemic peak around 27th August, 2024 (two months after …

Simulation Of Polymerization On Surfaces: Implications For Abiogenesis, Sylvia Greene

Macalester Journal of Physics and Astronomy

How did life arise from the prebiotic conditions of the early earth? This problem has vexed scientists for decades with no consensus on its solution. Significant spontaneous formation of biopolymers such as proteins and nucleic acids in the aqueous phase appears to be improbable due to thermodynamic constraints. It has been proposed that mineral surfaces could have served as a catalyst for the initial formation of biopolymers. However, the feasibility of this mechanism has not been thoroughly studied. In this study, a particle simulation of polypeptide formation on surfaces is developed to assess the feasibility of this mechanism. Elementary processes …

Missing Wedge Completion Via Unsupervised Learning With Coordinate Networks, Dave Van Veen, Jesús G Galaz-Montoya, Liyue Shen, Philip Baldwin, Akshay S Chaudhari, Dmitry Lyumkis, Michael F Schmid, Wah Chiu, John Pauly

Faculty, Staff and Students Publications

Cryogenic electron tomography (cryoET) is a powerful tool in structural biology, enabling detailed 3D imaging of biological specimens at a resolution of nanometers. Despite its potential, cryoET faces challenges such as the missing wedge problem, which limits reconstruction quality due to incomplete data collection angles. Recently, supervised deep learning methods leveraging convolutional neural networks (CNNs) have considerably addressed this issue; however, their pretraining requirements render them susceptible to inaccuracies and artifacts, particularly when representative training data is scarce. To overcome these limitations, we introduce a proof-of-concept unsupervised learning approach using coordinate networks (CNs) that optimizes network weights directly against input …

The Analysis Of Mechanical Exfoliation Of Graphene For Various Fabrication And Automation Techniques, Lance Yarbrough

Physics Undergraduate Honors Theses

Mechanical Exfoliation

Proof-Of-Concept For Converging Beam Small Animal Irradiator, Benjamin Insley

Dissertations and Theses (Open Access)

The Monte Carlo particle simulator TOPAS, the multiphysics solver COMSOL., and

several analytical radiation transport methods were employed to perform an in-depth proof-ofconcept

for a high dose rate, high precision converging beam small animal irradiation platform.

In the first aim of this work, a novel carbon nanotube-based compact X-ray tube optimized for

high output and high directionality was designed and characterized. In the second aim, an

optimization algorithm was developed to customize a collimator geometry for this unique Xray

source to simultaneously maximize the irradiator’s intensity and precision. Then, a full

converging beam irradiator apparatus was fit with a multitude …

Comparing North American Professional Sports League Season Formats Using Monte Carlo Simulation, Lathan Gregg

Industrial Engineering Undergraduate Honors Theses

Each NFL, NBA, and MLB season consists of a regular season, in which teams play a set number of scheduled games and a playoff, in which qualifying teams compete for a championship. At the conclusion of each season, teams are ranked based on their performance throughout the season. This study aims to investigate the ability of each league's season format to accurately rank teams using Monte Carlo simulation. Matches between two teams are simulated by using the team’s assigned strength ranks to calculate a winning probability for each team. The winning probabilities are simulated with different skill values, dictating how …

The Analysis Of Mechanical Exfoliation Of Graphene For Various Fabrication And Automation Techniques, Lance Yarbrough

Mechanical Engineering Undergraduate Honors Theses

Mechanical Exfoliation of Graphene is an often-overlooked portion of the fabrication of quantum devices, and to create more devices quickly, optimizing this process to generate better flakes is critical. In addition, it would be valuable to simulate test pulls quickly, to gain insight on flake quality of various materials and exfoliation conditions. Physical pulls of graphene at various temperatures, pull forces, and pull repetitions were analyzed and compared to the results of ANSYS simulations, solved for similar results. Using ANSYS’ ability to predict trends in exfoliations, flake thickness and coverage using stress and deflection analyses were investigated. Generally, both strongly …

Deterministic Global 3d Fractal Cloud Model For Synthetic Scene Generation, Aaron M. Schinder, Shannon R. Young, Bryan J. Steward, Michael L. Dexter, Andrew Kondrath, Stephen Hinton, Ricardo Davila

Faculty Publications

This paper describes the creation of a fast, deterministic, 3D fractal cloud renderer for the AFIT Sensor and Scene Emulation Tool (ASSET). The renderer generates 3D clouds by ray marching through a volume and sampling the level-set of a fractal function. The fractal function is distorted by a displacement map, which is generated using horizontal wind data from a Global Forecast System (GFS) weather file. The vertical windspeed and relative humidity are used to mask the creation of clouds to match realistic large-scale weather patterns over the Earth. Small-scale detail is provided by the fractal functions which are tuned to …

Advancing Game Development And Ai Integration: An Extensible Game Engine With Integrated Ai Support For Real-World Deployment And Efficient Model Development, Ryan Anderson

All Graduate Theses and Dissertations, Fall 2023 to Present

This thesis introduces Acacia, a game engine with built-in artificial intelligence (AI) capabilities. Acacia allows game developers to effortlessly incorporate Reinforcement Learning (RL) algorithms into their creations. By tagging game elements to convey information about the game state or rewards, developers gain precise control over how RL algorithms interact with their games, mirroring real player behavior or providing full knowledge of the game world.

To showcase Acacia’s versatility, the thesis presents three games across different genres, each demonstrating the engine’s AI plugin. The goal is to establish Acacia as a preferred resource for creating 2D games with RL support without …

Simulating Ice Particle Properties Under Varying Electric Fields, Joseph Thomas Cooney

Undergraduate Honors Capstone Projects

In this study, the interactions between atmospheric water molecules and an electrically charged dust particle were simulated in python to determine the role of electric charge and electric fields in atmospheric ice formation. Multiple levels of electric charge were tested, corresponding to different strengths of atmospheric electric fields. The TIP4P-2005 model for water was used to simulate these molecules under the influence of a central electric potential to represent the charged dust particle. These included a control group with no electric field (0 C), a group under a fair-weather strength of electric field (1.6*10-14 C), a foul-weather electric field (1.6*10-12 …

Adaptive Content-Aware Influence Maximization Via Online Learning To Rank, Konstantinos Theocharidis, Panagiotis Karras, Manolis Terrovitis, Spiros Skiadopoulos, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

How can we adapt the composition of a post over a series of rounds to make it more appealing in a social network? Techniques that progressively learn how to make a fixed post more influential over rounds have been studied in the context of the Influence Maximization (IM) problem, which seeks a set of seed users that maximize a post’s influence. However, there is no work on progressively learning how a post’s features affect its influence. In this article, we propose and study the problem of Adaptive Content-Aware Influence Maximization (ACAIM), which calls to find k features to form a …

Establishing Practical Equivalence Of Factor Loadings In Multigroup Confirmatory Factor Analysis, Christopher Edward Shank

Dissertations

This dissertation compares the performance of equivalence test (EQT) and null hypothesis test (NHT) procedures for identifying invariant and noninvariant factor loadings under a range of experimental manipulations. EQT is the statistically appropriate approach when the research goal is to find evidence of group similarity rather than group difference; despite this, the conventional approach to measurement invariance analysis relies upon NHT. EQT has proved effective for invariance detection using global model-data fit statistics in simulated and real-world data (Counsell et al., 2020) but its use in partial measurement invariance (PMI) analysis for evaluation of factor loading differences between groups has …

Using Cuticular Wax Alkanes And Computer Simulation To Estimate Diet Selection, Herbage Intake And Nutrient Cycling In Grazing Sheep, H Dove, R J. Simpson

IGC Proceedings (1977-2023)

In grazing ewes, plant cuticular wax alkanes were used as markers to estimate diet selection, herbage intake, N intake and N excretion in faeces. Pasture and animal data were then used as inputs to the decision-support system GrazFeed, which simulates grazing and digestion to predict herbage intake, N intake and N excretion. Estimated and predicted intakes agreed closely, especially for N intake, and it is concluded that, subject to further investigation of the possibility that GrazFeed slightly under-estimated faecal N excretion, the close agreement between estimated and predicted OM and N intakes suggests that this combined use of alkane methods …

Modelling Leucaena Biomass Under Rainfed Production Systems Of Semiarid Regions, M. J. D. Cândido, J. L. G. Santos, A. C. R. Cavalcante, S. R. Maranhão, M. A. Santos, J. M. Osorio Leyton

IGC Proceedings (1977-2023)

The climatic variability of semiarid regions is the main source of uncertainties associated with forage and animal production, indicating a need for tools that accurately estimate forage production in order to construct a forage budgeting plan for livestock. This study simulated the biomass of Leucaena (Leucaena leucocephala) using the PHYGROW model in four locations located in Brazilian Semiarid. The work was carried out based on field data collected from 2019 to 2021. After sowing in 2018, leucaena was harvested when it reached 200 cm and to a target residual height of 70 cm. The biomass (fresh matter) was …

Strategy Optimization Method Of Multi-Dimension Projection Based On Deep Reinforcement Learning, Jing An, Guangya Si, Lei Zhang

Journal of System Simulation

Abstract: Based on the perfect performance of deep reinforcement learning (DRL) in strategy optimization, this paper proposes a strategy optimization method of action taking the multi-dimension projection action as the main research object. The method combines the simulation experiment method with the DRL method. After analyzing the current situation of strategy optimization research, the deep learning framework is selected according to the research problems, and a DRL multi-dimension projection strategy model based on the asynchronous advantage actor-critic (A3C) algorithm is constructed. Through simulation experiments, the interactive learning between the DRL model and the simulation of "out of the loop" is …

Blue Whale And Krill Populations Modeling, Li Zhang

CODEE Journal

We present an intriguing topic in an undergraduate mathematical modeling course where predator-prey models are taught to our students. We describe modeling activities and the use of technology that can be implemented in teaching this topic. Through modeling activities, students are expected to use the numerical and graphical methods to observe the qualitative long-term behavior of predator and prey populations. Although there are other choices of predators and prey, we find that using blue whales and krill as predator and prey, respectively, would be most beneficial in strengthening our students' awareness of protecting endangered species and its impact on climate …

Attochemistry Regulation Of Charge Migration, Aderonke Folorunso

LSU Doctoral Dissertations

Charge migration (CM) is a coherent attosecond process that involves the movement of localized holes across a molecule. This phenomenon is potentially useful to understand the fundamental principles of photochemistry, such as light harvesting. The first part of this dissertation discusses the molecular modes of attosecond charge migration. In this work, we used first-principles calculations to investigate the modes of charge migration (CM) in halogenated hydrocarbon chains at attosecond timescales. We have simulated the creation of a localized hole on the halogen atom using constrained density functional theory (DFT) and then tracked its subsequent dynamics with time-dependent DFT (TDDFT). Our …

Simulation Of Soil Temperature Under Maize: An Inter-Comparison Among 33 Maize Models, B. A. Kimball, K. R. Thorp, K. J. Boote, C. Stockle, Andrew E. Suyker Et Al.

School of Natural Resources: Faculty Publications

No abstract provided.

Data Driven Trade-Off Analysis For Cybersecurity, Goskel Kucukkaya, Murat Ozer, Murat Balci, Emrah Ugurlu

Engineering Management & Systems Engineering Faculty Publications

Trade-off analysis, a specialization of systems engineering, addresses design criteria like security, cost, performance, and compliance. Monte Carlo simulations are commonly employed to generate impact scenarios for trade-off analysis combined with solution alternatives that accommodate industry-specific considerations and uncertainties. In the cyber domain, this paper proposes a methodology for data-driven trade-off analysis in cybersecurity, leveraging industry reports as primary data sources using confidentiality, integrity, and availability as trade-off analysis objectives. Distribution functions are derived to manage and model uncertainties for various industries. The approach given in this study aims to facilitate informed choices and to enhance cybersecurity decision making and …

A Virtual Time Driven Simulator For Devs Models, Ronald R. Stempien

Dissertations, Master's Theses and Master's Reports

When simulating a system that includes some software component, simulation authors are faced with the problem of how to appropriately model the software within the simulation. While many formal methods for modeling software exist, in some contexts these may not be appropriate or viable for a given simulation. Instead, simulation authors may model a computer within the simulation, and run the software in question “as is” on the modeled machine. In this work, we introduce a theoretical framework to allow for the use of hardware virtualization technologies as a hardware accelerator for CPU models in Discrete Event System Specification (DEVS) …