Digital Commons Network^™

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 …

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 …

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 …

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 …

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 …

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.

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 …

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).

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 …

Polymer Translocation Through A Nanopore: Controlling Capture Conformations Using An Electrical Force, Matthew D. Wei

Undergraduate Student Research Internships Conference

Solid-state nanopore sensors remain a promising solution to the rising global demand for genome sequencing. These single-molecule sensing technologies require single-file translocation for high resolution and accurate detection. This study uses molecular dynamics-lattice Boltzmann simulations of the capture of a single polymer chain under pressure-driven hydrodynamic flow to investigate a method of increasing the single-file capture and translocation rate. By using a model force of two oppositely electrically charged rings, single-file capture in hydrodynamic flow can be amplified from about 45% to 51.5%. This paper found that the optimal values of force location, force strength, and system pressure/flow velocity are …

Simple And Fast Fabrication Methodology For Platinum And Carbon Ultramicroelectrodes (Ume) In Scanning Electrochemical Microscopy (Secm), Emma Mae Lord, Jiju Joseph, Samantha M. Gateman, Zhifeng Ding

Undergraduate Student Research Internships Conference

Scanning electrochemical microscopy (SECM) is a highly versatile method for measuring and imaging a wide range of systems. When paired with an intricately made ultramicroelectrode (UME) probe, SECM becomes an even more powerful tool for imaging microscale features in a system. However, purchasing these UME’s comes at a high cost with less ability for modification. Having high quality UME’s expands the ability of SECM and enables precise measuring and imaging in a wide range of applications such as solar cells in Dr. Ding’s lab, and corroding metals in Dr. Gateman’s lab. To combat this issue of high cost and set …

Travelling Wave Solutions On A Cylindrical Geometry, Karnav R. Raval

Undergraduate Student Research Internships Conference

Fluid equations are generally quite difficult and computationally-expensive to solve. However, if one is primarily interested in how the surface of the fluid deforms, we can re-formulate the governing equations purely in terms of free surface variables. Reformulating equations in such a way drastically cuts down on computational cost, and may be useful in areas such as modelling blood flow. Here, we study one such free-boundary formulation on a cylindrical geometry.

Where Are The Habitable Planets In Our Local Group Of Galaxies?, William C. Windsor

Undergraduate Student Research Internships Conference

No abstract provided.

Development Of A Low Field Mri-Based Approach For Observation Of Water Penetration Into Clay: Preliminary Results, Shivam Gupta

Undergraduate Student Research Internships Conference

Magnetic resonance imaging (MRI) are considered one of the most efficient and non-invasive methods of observing water content in permeable substances. MRI can visualize and quantify the movement of water in real time. In this study, MRI was used to observe the water penetration through clay. Furthermore, MRI can acquire three-dimensional data due to its radio-frequency signals from any orientation. The contrast of the images produced by MRI is a display of the fluid concentration. As such, any change in the contrast intensity is interpreted as a regional change in the concentration of fluid. This report summarizes the preliminary results …

The Impacts Of Mid-Holocene Warming On Water Quality In A Southwestern Ontario Kettle Pond, Morgan E. Peicheff

Undergraduate Student Research Internships Conference

No abstract provided.

Simulating 129-Xe Hyperpolarization, Jacob F. Abiad

Undergraduate Student Research Internships Conference

Hyperpolarized 129-Xe is an important resource in many fields of medical physics and MRI research. The physics of the efficient production of hyperpolarized 129-Xe is therefore equally worth investigation. The main process of hyperpolarizing 129-Xe is Spin Exchange Optical Pumping (SEOP) and is dependent on several physical factors that can be difficult to constantly change in a lab setting. Physical modelling of 129-Xe hyperpolarization allows for the more efficient testing of hyperpolarization physics in a wide array of experimental setups to better determine the optimal values for hyperpolarization. This research project attempted to create a working model for 129-Xe hyperpolarization …

A Transformer-Based Classification System For Volcanic Seismic Signals, Cristian Bravo Roman, Cindy Mora Stock, Alexander James Hemming

Undergraduate Student Research Internships Conference

Volcanic seismic signals are a key element in volcano monitoring to assess the state of unrest and a possible eruption style and timing. Different sources such as brittle fracture (volcano-tectonic - VT) or fluid movement (long period - LP) generate signals with distinct characteristics in frequency content and shape, but site effects such as attenuation or background noise make their determination difficult to the untrained eye. In cases of unrest or an eminent eruption, the amount of data would require a fast and reliable source of pre-classification to classify and catalogue to aid in the job usually done by a …

Numerical Simulation Of Adaptive Metabolic Response To Anti-Angiogenic Treatment In Renal Cell Carcinoma, Saranya Varakunan

Undergraduate Student Research Internships Conference

Renal cell carcinoma, a malignant kidney cancer, is often treated using anti-angiogenic drugs to prevent the growth of blood vessels within the tumour. Although tumours initially respond to this treatment, they eventually develop resistance. This resistance is hypothesized to be caused by a switch to a symbiotic metabolism that allows cells to survive even with a low blood supply.

This project seeks to computationally model the transport of oxygen, lactate, and glucose within a tumour in order to examine how cancer metabolism adapts to changes in blood vessels.

Numerical Modelling Of A Novel 3d T-Junction Microfluidic Droplet Generator, Andrew G.H. Roberts

Undergraduate Student Research Internships Conference

No abstract provided.

Optimizing Hospital Capacity To Deal With Hallway Medicine, Megan Wismer

Undergraduate Student Research Internships Conference

A model adapted from Hillier and Liebermann, 2017 that optimizes hospital capacity to deal with hallway medicine.

Modeling Weather Vulnerability Dynamically: Applications Of Multiple Linear Regression To Weather Index Microinsurance, Sophie Wu

Undergraduate Student Research Internships Conference

This paper offers a broad overview of the philanthropic goals of microinsurance — namely, to provide vulnerable populations with more self-sufficient and sustainable methods of coping with risk — and through this lens, analyses the applications of multiple linear regression in developing dynamic models for microinsurance. We explain the foundations of MLR (multiple linear regression), and then give two examples for how a simple multiple linear regression model can be adapted with a novel outcome variable (famine) and dependent variables (climate change related costs). Overall, a better understanding of MLR can lend to a better understanding of how microinsurance can …