Physical Sciences and Mathematics Commons^™

Cnn-Lstm Vs Ann: Option Pricing Theory, Edward Chang

Undergraduate Student Research Internships Conference

The modern derivatives market has been steadily growing since the development of the first accurate option pricing model by Fischer Black, Robert Merton, and Myron Scholes. Since then, there have been many different approaches to more accurately price options like the binomial option pricing model and approaches using technology such as machine learning. There are many different research papers on option pricing with artificial neural networks (“ANN”) but not many with other neural network types. We contribute to the existing literature by developing a convolutional neural network – long short-term memory (“CNN-LSTM”) model to price options and compare it to …

Proving Dirichlet's Theorem On Arithmetic Progressions, Owen T. Abma

Undergraduate Student Research Internships Conference

First proved by German mathematician Dirichlet in 1837, this important theorem states that for coprime integers a, m, there are an infinite number of primes p such that p = a (mod m). This is one of many extensions of Euclid’s theorem that there are infinitely many prime numbers. In this paper, we will formulate a rather elegant proof of Dirichlet’s theorem using ideas from complex analysis and group theory.

Rheological Characterization Of Blood-Mimicking Fluids For Use In Particle Image Velocimetry, Anorin S. Ali

Undergraduate Student Research Internships Conference

Blood-mimicking fluids (BMFs) are often used to investigate blood flow using physical replicas of vessels with cardiovascular disease. Particle image velocimetry (PIV) is used with silicone poly-dimethyl siloxane (PDMS) vascular models to visualize this flow. The challenge is creating a blood-mimicking fluid that matches the viscosity profile, viscoelasticity, and density of whole blood while also matching the refractive index (RI) of PDMS. Water-glycerol solutions are commonly used with sodium iodide (NaI) added to increase the RI without changing viscosity. However, NaI is expensive, stains easily, and turns fluids from optically clear to yellow in less than a day. Furthermore, without …

Exploring Human-Caused Fire Occurrence Prediction, Ruyi Jin

Undergraduate Student Research Internships Conference

Wildland Fire Science has become an increasingly hot topic in recent years. The goal of this report is to investigate human-caused wildland fire occurrence prediction. The two main predictors of interest are the mean value of the Fine Fuel Moisture Code (FFMC) and the month when a fire ignites. An Exploratory Data Analysis is presented first, after which we fit models to predict daily fire counts. We first consider Poisson models to fit the count data, but also attempt to fit Negative Binomial models to deal with overdispersion. We compare these models in the following ways: plotting the difference in …

A Transformer-Based Classification System For Volcanic Seismic Signals, Anthony P. Rinaldi, Cindy Mora Stock, Cristián Bravo Roman, Alexander Hemming

Undergraduate Student Research Internships Conference

Monitoring volcanic events as they occur is a task that, to this day, requires significant human capital. The current process requires geologists to monitor seismographs around the clock, making it extremely labour-intensive and inefficient. The ability to automatically classify volcanic events as they happen in real-time would allow for quicker responses to these events by the surrounding communities. Timely knowledge of the type of event that is occurring can allow these surrounding communities to prepare or evacuate sooner depending on the magnitude of the event. Up until recently, not much research has been conducted regarding the potential for machine learning …

Fabrication Of Gold Nanoraspberry Arrays By Soft Lithography, Christy Yu-Qing Xie

Undergraduate Student Research Internships Conference

Nanostructures and nanoparticles have garnered increasing interest over the past decade due to their unique properties and applications. These properties include localized surface plasmon resonance (LSPR) and allow for surface modification. We can tune these properties depending on the nanoparticle’s size, shape, and geometry.

This work aims to fabricate plasmonic platforms through patterning gold nanoparticles (raspberries) by microcontact printing, a simple and cost-effective soft lithography technique. This is done through large-scale patterning using polydimethylsiloxane (PDMS) stamps to pattern an adhesion template and spatially guide the adsorption of gold nanoparticles (AuNPs).

Fluid Inclusion Analysis Of Halite: A Snapshot Of The Cambrian Explosion, Amy R.A. Lefebvre

Undergraduate Student Research Internships Conference

This research focused on obtaining a brief overview of information preserved within evaporite samples formed during the Early Cambrian. With the help of halite screening methods, fluid and gas analysis, through a micro thermometer and mass spectrometer, respectively, as well as trace element analysis conducted by Act Labs, results reflecting Earth's climate over 500 million years ago were obtained. These indicated the approximate weather conditions, and atmospheric composition, during this time period, within an intracontinental dessert location. Specifically, these results reflects a global warming period, with daily variations. Although much more research is needed in order to validate this summer's …

Uncovering The Mysteries Of Retention Ponds: Comparing The Abundance And Type Of Microplastics In Storm Water Ponds In London Ontario, Natalie Rose Minda

Undergraduate Student Research Internships Conference

Microplastics are plastics <5 mm (Liu, 2019; Arthur et al., 2009). They are created in two ways: Intentionally or from the fragmentation of larger pieces of plastic (National Ocean Service, 2021). They can negatively impact human, wildlife and ecosystem health in many ways depending on the exposure, type, size, and shape of the microplastic (Campanale, 2020). Retention ponds are often created in neighborhoods to collect water in order to prevent flooding. They also often serve as habitat for wildlife. Sediment samples were collected in two ponds in London Ontario both dredged in 2016. Samples were processed in the lab and further analyzed under the microscope to isolate the microplastics. Results have not been determined yet, but the abundance and type of microplastic varies in both ponds. Plastic pollution in retention ponds should be considered more, as it poses a threat to human and ecosystem health.

Enhancing Chemistry Education Through Team-Based Active Learning Strategies, Katelyn Helka

Undergraduate Student Research Internships Conference

Retention in STEM can be impacted by different psychosocial factors like sense of belonging, STEM identity, sense of community, and sense of support. The research conducted was used to design a study that will measures these psychosocial factors at the beginning and end of a first-year, general chemistry course. The research also aimed to determine the best active learning method to implement in the general chemistry course, that has over 2000 students enrolled in it, that could improve student feelings towards these psychosocial factors.

Solving Partial Differential Equations Using The Finite Difference Method And The Fourier Spectral Method, Jenna Siobhan Parkinson

Undergraduate Student Research Internships Conference

This paper discusses the finite difference method and the Fourier spectral method for solving partial differential equations.

Bias-Corrected Bagging In Active Learning With An Actuarial Application, Yangxuan Xu

Undergraduate Student Research Internships Conference

The variable annuity (VA) is a modern insurance product that offers certain guaranteed protection and tax-deferred treatment. Because of the inherent complexity of guarantees’ payoff, the closed-form solution of fair market values (FMVs) is often not available. Most insurance companies depend on Monte Carlo (MC) simulation to price the FMVs of these products, which is an extremely computational intensive and time-consuming approach. The metamodeling approach can be used to circumvent the heavy computation.

In the modeling stage, the bagged tree method has proved to outperform other parametric approaches. Also, a bias-corrected (BC) bagging model was tried and showed significant improvement …

Investigating Distributions Of Epochs In Wildland Fire Lifetimes, Xinlei Wang

Undergraduate Student Research Internships Conference

The objective of my research project is to explore the relationship between variables related to wildland fire and to model distributions of epochs in wildland fire lifetimes. Several distributional families are considered for modeling these epochs, including the exponential distribution, gamma distribution, Weibull distribution and continuous phase-type distribution. I explain each of these distributions in short terms and illustrate how they are fit. Visual results of my exploratory data analysis are illustrated in two parts, data visualization and data modeling, along with my interpretation of each. Since this work is preliminary, I conclude the report with a discussion on what …

Reporting Standards For Machine Learning Research In Type 2 Diabetes, Grace Kang

Undergraduate Student Research Internships Conference

In this project, three people scored 90 papers on machine learning predictive models for type 2 diabetes to assess their adherence to TRIPOD, MI-CLAIM, and DOME reporting guidelines.

The Q-Analogue Of The Extended Generalized Gamma Distribution, Wenhao Chen

Undergraduate Student Research Internships Conference

This project introduces a flexible univariate probability model referred to as the q-analogue of the Extended Generalized Gamma (or q-EGG) distribution, which encompasses the majority of the most frequently used continuous distributions, including the gamma, Weibull, logistic, type-1 and type-2 beta, Gaussian, Cauchy, Student-t and F. Closed form representations of its moments and cumulative distribution function are provided. Additionally, computational techniques are proposed for determining estimates of its parameters. Both the method of moments and the maximum likelihood approach are utilized. The effect of each parameter is also graphically illustrated. Certain data sets are modeled with q-EGG distributions; goodness of …

Lecture Note On Delay Differential Equation, Wenfeng Liu

Undergraduate Student Research Internships Conference

Delay differential equation is an important field in applied mathematics since it concerns more situations than the ordinary differential equation. Moreover, it makes the equations more applicable to the object's movement in real life.

My project is the lecture note on the delay differential equation provides a basic introduction to the delay differential equation, its application in real life, improving the ordinary differential equation, the primary method and definition for solving the delay differential equation and the use of the way in the ordinary differential equation to estimate the periodic solution to the delay differential equation.

Investigation Of Key Factors To Earthquake Insurance Take-Up Rates In Quebec And British Columbia Households And Prediction Model Building, Yongcheng Jiang

Undergraduate Student Research Internships Conference

Maintaining an adequate level of earthquake take-up rate could protect the insurance industry from systemic failure. Past research has shown that British Columbia and Quebec have significant differences in earthquake insurance take-up rate. This report investigates key factors from the structure (default options and various types) of the insurance plan and personal characteristics along with socioeconomic/demographic profiles that affect the demand for earthquake protection in the form of insurance. The report also provides a prediction model for earthquake insurance take-up rate. The results show an importance ranking of key factors of earthquake insurance take up, the most important three are …

Modified Synthesis Of A Photoswitchable Aa-Dd Hemthioindigo-Based Hydrogen Bond Complex, Victoria Chou, Paul Winiarz, James Wisner, Fereshteh Davoud,

Undergraduate Student Research Internships Conference

No abstract provided.

A Qualitative Look Into Repair Practices, Jumana Labib

Undergraduate Student Research Internships Conference

This research poster is based on a working research paper which moves beyond the traditional scope of repair and examines the Right to Repair movement from a smaller, more personal lens by detailing the 6 categorical impediments as dubbed by Dr. Alissa Centivany (design, law, economic/business strategy, material asymmetry, informational asymmetry, and social impediments) have continuously inhibited repair and affected repair practices, which has consequently had larger implications (environmental, economic, social, etc.) on ourselves, our objects, and our world. The poster builds upon my research from last year (see "The Right to Repair: (Re)building a better future"), this time pulling …

Generating Light Curves From Simulated Active Galactic Nuclei Data, William Yuan

Undergraduate Student Research Internships Conference

Active Galactic Nuclei (AGN) are growing supermassive black holes found at the centers of massive galaxies. My research involves gathering data by simulating the light emitted by AGN, and then plotting the simulated light in the form of light curves.

Comparing Computational Methods By Stretching Diatomic Molecules, Aaron Mitchell

Undergraduate Student Research Internships Conference

A comparison of functionals was done by comparing full electron density profiles along the bond axis of H₂ and N₂. Additionally, based on the success of the (HF)-DFT method, the goal of this project was to compare the mRKS method to (HF)-DFT.

Bismuth Binding In Human Metallothionein, Emily M. Toswell

Undergraduate Student Research Internships Conference

Bismuth metal is one of the least toxic heavy metals for humans. It is used in a wide variety of applications including organic synthesis, cosmetics and pharmaceutical applications. In biomedicine, bismuth is a therapeutic metal used in metallodrugs such as Pepto Bismol for its antimicrobial and antibacterial properties. Metallothionein (MT) is a cysteine rich protein found in the liver, kidneys, brain and central nervous system. MT can bind a variety of metals including essential metals such as zinc and copper. This research investigates the binding pathway of Bi[EDTA]- with fully metallated Zn₇MT by using mass-spectrometry and UV-vis absorption.

Model Transformations Between Sequence Diagram And Activity Diagram With Qvto, Yutong Xia

Undergraduate Student Research Internships Conference

Complex software systems are specified by various models denoting the behavior of the system components, the exchanges of messages and data among components, the intents of the system stakeholders, the flow of system processes, and the structure of the system as a collection of modules.

When such systems are maintained and evolved (e.g. by adding new functionality, fixing bugs, or porting to a new operating environment), one or more of these models are altered. This brings the system specification to an inconsistent state since some models reflect the new behavior while other models were not appropriately evolved.

This research presents …

Functional Structure Of Excess Return And Volatility, Chenxi Zhao

Undergraduate Student Research Internships Conference

Capturing the relation between excess returns and volatility can help making better decisions in the stock market in terms of portfolio allocation and assets risk management. This paper takes the data of a minute-by-minute series of S&P500 from January 2009 to January 2021 as the research object and explores the best structural representation for the excess return as a function of the volatility, for a well-known index. This is implemented via regression models for volatility and excess returns. The results reveal that there’s a structural break in the relationship between the excess return and volatility based on the sign of …

Damage Assessment In Aging Structures Using Augmented Reality, Omar Zuhair Awadallah, Ayan Sadhu

Undergraduate Student Research Internships Conference

Structural Health Monitoring (SHM) is the assessment of bridges and observation of data regarding these bridges over time to monitor their evolution and detect the presence of any possible damages. However, existing methods to perform structural inspections in bridges are high in cost, time-consuming and risky. Inspectors use expensive equipment to reach a certain area of the bridge to inspect it, and at different heights, this can pose a risk to the inspector’s safety. This study aims to find cheaper, faster, and safer ways to perform structural inspections using augmented reality and artificial intelligence. The developed system uses a machine …

How Can Social Networks Impact Careers In Game Development?, Tongzhang Wang

Undergraduate Student Research Internships Conference

The game development industry is one characterized by young workers and fast worker turnover. The popularity of using twitter as a professional tool within the video games industry presents a potentially insightful view port into a professional's informal network. Investigating characteristics of the social networks of newly graduated students in the game development industry may reveal what factors contribute to fast worker turnover and how certain cohorts may face additional barriers.

Using Stable-Isotopes To Determine The Effects Of Land-Use Change On Carbon Storage, Morgan Basile

Undergraduate Student Research Internships Conference

Over the last century, there has been drastic conversion of natural vegetation to agriculture. The decomposition of plant tissue is transformed into soil organic matter that is rich in carbon and stored within soil aggregates. This research examines the effects of land-use change on carbon storage by using stable-isotopes of organic matter. The stable-isotopes of organic matter within aggregates will be used to quantify the amount of carbon that has been added to the soil after a change in land-use (e.g. restoration of agricultural land to grassland).

Optimization Of The Synthesis Parameters Of Sapo-34, Adam Honchar

Undergraduate Student Research Internships Conference

A microporous material known as SAPO-34 is a very efficient catalyst in methanol-to-olefins reactions. My project aimed to optimize synthesis parameters of SAPO-34 to reduce crystallization time in order to study the formation mechanism using In-situ NMR spectroscopy. Understanding the crystallization mechanism would allow us to make it more efficient and tailor-made to fit for other applications.

Meteorite Investigation And Classification, Olivia N. Benest

Undergraduate Student Research Internships Conference

Several meteorites arrive on Earth every day, but only a small percentage of them are found. They are easiest to spot on deserts or frozen ice. Western has a large number of unclassified meteorites found in the Northwest Africa (NWA) and Oman deserts. These meteorites include chondrites, achondrites, irons, and even Lunar and Martian meteorites. Classifying a meteorite requires detailed examination by optical microscopy, as well as micro X-ray diffraction (µXRD), and Electron Probe Microanalysis (EPMA), to observe their mineralogy (metal, oxide, sulfide, and silicate mineral phases), textures (e.g. chondrules, CAIs) and composition, in order to classify their petrologic type …

Data Preprocessing For Machine Learning Modules, Rawan El Moghrabi

Undergraduate Student Research Internships Conference

Data preprocessing is an essential step when building machine learning solutions. It significantly impacts the success of machine learning modules and the output of these algorithms. Typically, data preprocessing is made-up of data sanitization, feature engineering, normalization, and transformation. This paper outlines the data preprocessing methodology implemented for a data-driven predictive maintenance solution. The above-mentioned project entails acquiring historical electrical data from industrial assets and creating a health index indicating each asset's remaining useful life. This solution is built using machine learning algorithms and requires several data processing steps to increase the solution's accuracy and efficiency. In this project, the …

Semantic Analysis Of Stock Market-Related Posts, Jiangqi Cui

Undergraduate Student Research Internships Conference

No abstract provided.