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- First year seminar; Engaged student learning; Remote learning; STEM (1)
- Infection; Epidemiology; Machine learning; COVID-19 (1)
- QAOA; Machine learning; Neural networks; Quantum computing (1)
- Raman; Spectroscopy; DAC (Diamond Anvil Cell); Oxalate (1)
- Renewable; Grid; Renewable Portfolio Standards (RPS) (1)
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Modeling Covid-19 Infection Rates Using Sir And Arima Models, Janelle Domantay, Ilya Pivavaruk, Victor Taksheyev
Modeling Covid-19 Infection Rates Using Sir And Arima Models, Janelle Domantay, Ilya Pivavaruk, Victor Taksheyev
Undergraduate Research Symposium Posters
With the onset of the COVID-19 pandemic, it has become of increasing interest to both monitor and predict the growth of its infection rates. In order to analyze the accuracy of epidemiological prediction, we consider two different models for prediction, the Susceptible Infected and Removed (SIR), and Autoregressive Integrated Moving Average (ARIMA) models. Using a dataset of Clark County COVID-19 infections, we create various ARIMA and SIR models that attempt to predict the progression of COVID-19 infections whilst comparing these predictions to the dataset. We observed that the ARIMA model performed more accurately overall, having a much lower Root Mean …
Investigating The Varying Behaviors Of Magnesium, Tin, And Lead Oxalate Under High-Pressure, Kevin Ayala Pineda
Investigating The Varying Behaviors Of Magnesium, Tin, And Lead Oxalate Under High-Pressure, Kevin Ayala Pineda
Undergraduate Research Symposium Posters
Recent developments in the field of useful hard x-ray induced chemistry synthesized a novel strontium-based CO derived material under extreme conditions. In hopes of synthesizing this material in larger quantities and in less expensive costs, we report three high-pressure Diamond Anvil Cell investigations on Tin Oxalate (SnC2O4), Magnesium Oxalate (MgC2O4), and Lead Oxalate (PbC2O4) subjected to extreme conditions without the use of hard x-rays. MgC2O4 were acquired up to 25 GPa, with a possible phase transition at 2.4 Gpa. SnC2O4 was pressurized up to 31 GPa inducing irreversible changes in both the Raman spectra and its qualitative properties. Three phase …
Increasing Analysis Efficiency Through Automation Of Inductively Coupled Plasma Mass Spectrometry (Icp-Ms) Data Reduction Process Using Python, Grace Abigail Martin
Increasing Analysis Efficiency Through Automation Of Inductively Coupled Plasma Mass Spectrometry (Icp-Ms) Data Reduction Process Using Python, Grace Abigail Martin
Undergraduate Research Symposium Posters
The Inductively Coupled Plasma Mass Spectrometry (ICP-MS) provides elemental analysis through ionization of samples. Numerous geochemistry laboratories utilize the ICP-MS and has become a community standard. The ICP-MS data reduction process is time intensive and involves correction for blank contribution and sensitivity drift during measurement, as well as construction of standard calibration lines based on measurements of standard solutions. We look to decrease turnaround time and increase efficiency through automation of the data reduction process using Python. The ICP-MS data reduction process was 3 hours or more, in our observations. Python packages such as Openpyxl and Pandas, allow us to …
Overcoming The Overgeneration Of Renewables, Joshua Kaze, Ryan Barnard
Overcoming The Overgeneration Of Renewables, Joshua Kaze, Ryan Barnard
Undergraduate Research Symposium Posters
Many states are addressing the issues of climate change, by changing how they produce their energy. The effects of these policies are causing many renewable sources to be underutilized. This paper analyzes how the diversification of energy generation is leading to inefficiencies in the California energy market and the western US market as a whole. The change in curtailment of non-dispatchable renewables is positively correlated with the growth of renewables. Summary statistics and regression analysis show that an increasing portion of renewables is being wasted as the quantity of renewables is increasing. The Renewable Portfolio Standards (RPS) that California introduced …
Toward A Quantum Neural Network: Proposing The Qaoa Algorithm To Replace A Feed Forward Neural Network, Erick Serrano
Toward A Quantum Neural Network: Proposing The Qaoa Algorithm To Replace A Feed Forward Neural Network, Erick Serrano
Undergraduate Research Symposium Posters
With a surge in popularity of machine learning as a whole, many researchers have sought optimization methods to reduce the complexity of neural networks; however, only recent attempts have been made to optimize neural networks via quantum computing methods. In this paper, we describe the training process of a feed forward neural network (FFNN) and the time complexity of the training process. We highlight the inefficiencies of the FFNN training process, particularly when implemented with gradient descent, and introduce a call to action for optimization of a FFNN. Afterward, we discuss the strides made in quantum computing to improve the …
Spike Nozzle Design For Use In Nanosat Orbital Maneuvering, Drew Nemeth
Spike Nozzle Design For Use In Nanosat Orbital Maneuvering, Drew Nemeth
Undergraduate Research Symposium Podium Presentations
Annular spike nozzle engines have long been the holy grail of rocket engine design, promising superior performance in a smaller footprint when compared to conventional bell nozzles. However, flaws inherent to the design of spike nozzles have prevented widespread adoption and testing. As a result, research on potential applications has been quite sparse. This project aims to further spike nozzle research by investigating rarely tested materials that literature suggests have potential for use in a spike nozzle design. The goal of the overall research project is to examine 3D printed polycarbonate component longevity under conditions representative of a small satellite …
Science In Your Naturehood, Alison Sloat
Science In Your Naturehood, Alison Sloat
UNLV Best Teaching Practices Expo
Engaging students in hands-on scientific research in their NatureHoods, or local neighborhoods, improves student outcomes, learning, and success in remote learning environments.