12th IEEE Integrated STEM Education Conference (On Demand Recording available now)
Poster Session 1
Hamstring Injury Detection Using Body-Centric Nano Networks
Lawrence He (Princeton High School, USA)
The hamstring group consists of many muscles and tendons. It is critical to accurately detect the injured part before applying any treatment. In this research project, Body-Centric Nano Network (BCNN) is implemented for hamstring injury detection.
I first propose an architecture to support hamstring injury detection. My architecture includes two types of nodes to collect bio-parameters for injury detection: nano sensors and data collectors. The nano sensors enter the patient's circulatory system via either injection or drinking with solutions. The data collectors are wearable devices covering the hamstring group area. Bio-parameters, such as blood cells, muscle enzymes, swelling, bruising, and dislocation, are collected by the data collectors for diagnosis purposes. By using the nano sensors for in-body monitoring, accurate bio-parameters can be collected to determine the root reason.
Performance of my proposal is further analyzed by evaluating key elements in the architecture. These elements are nano sensors, the hamstring area, the blood circulatory speed, and the frequency of collecting bio-parameters. The goal is to minimize the deployed nano sensors while collecting enough information to detect the injury. A mathematical model is established to relate all of the aforementioned elements. My model is based on the nano-scale communication framework in the IEEE Standard 1906.1. Its enhancement relies on employing the hamstring specific parameters to relax a portion of the constrains and thus reducing the computational complexity. Practical values from the bio-research literature are implemented to compare multiple scenarios. Results show this model provides salient guidelines for hamstring injury detection.
Controlling Wildfires though Aerial Seeding
Mrinalini Suresh Kumar (USA)
According to my research, 90% of the wildfires are caused by humans, and 10% are caused by nature(although more are caused by humans, there is a greater impact when the fire is caused by nature). In 2017, 12,306 structures were burned, in 2018, 25,790 were burned, in 2019, 963 structures were burned, and lastly, in 2020, 17,904 structures were burned, all during wildfires. Forest Fires occur during various conditions: drought, heat, and wind participate in drying out the timber or other fuel, making it easier to ignite. Once a fire is burning, drought, heat, and wind all increase its intensity. The arrangement of the natural and physical features of the area also affects wildfire, which spreads quickly uphill and slowly downhill. Dried grass, leaves, and light branches are considered flash fuels, and fire spreads quickly in them, often creating enough heat to ignite heavier fuels such as tree stumps, heavy limbs, and the organic matter of the forest floor. Such fuels, ordinarily slow to kindle, are difficult to extinguish. Green fuels-growing vegetation-are not considered flammable, but an intense fire can dry out leaves and needles quickly enough to allow ready ignition. Green fuels sometimes carry a special danger: evergreens, such as pine, cedar, fir, and spruce, contain flammable oils that burst into flames when heated sufficiently by the drafts of a forest fire.
To help stop the spread of wildfires near human settlements, I recommend a solution through Aerial Seeding. Aerial Seeding is when either a plane, helicopter, or drone drops seeds onto land. We propose dropping seed balls instead of raw seeds as this will greatly and precisely land the balls on soil surface even in mountain ranges.
To carry this project to the next level, I want to collect historical data from the types of trees and shrubs which were most effective in the spread of wildfires in the past. So that in the future I can use this data to create predictive models and help state and federal agencies to manage wildfires effectively.
Understanding the Geographic and Temporal Evolution of Asian Hate Crimes in the United States
Arthur Wang (Canada)
Using Mycelium for the Packaging and Transportation of Fossils
Victor I Robila (Hunter College High School, USA)
Using K-Wave to Simulate Ultrasound for Optimal Intravascular Ultrasound Device Frequencies
Zewen Ha (Canada)
Intravascular ultrasound (IVUS) is a catheter-based diagnostic device using echo-pulsed ultrasound for imaging from within arteries. IVUS can be used as an adjunct of angiography and, in contrast to the latter, it is critical for detailed imaging by detecting the exact location and morphology of plaques. A conventional IVUS device employs a piezoelectric transducer for transmitting and receiving ultrasound waves with a single frequency. Although higher ultrasound frequencies enable greater image resolution, it suffers stronger attenuation within biological tissues, which diminishes the penetration depth of the ultrasound signal and thus limits the view of imaging. This means that a single frequency cannot account for all situations as plaques may have various morphologies and sizes, and employing an IVUS catheter with a suitable frequency is crucial for the accurate identification of atherosclerotic plaques. Therefore, a systematic study of the impacts of ultrasound frequency on IVUS imaging of atherosclerotic plaques is significant. The ideal method would be testing IVUS catheters with different frequencies for various plaques, however, the cost of IVUS catheter and plaque prop fabrication will be staggeringly large as ultrasound frequency has a very wide range.
To address this issue, we present a solution in this work: a numerical simulation platform to mimic IVUS imaging of atherosclerotic plaques. The platform is built off the K-Wave toolbox in Matlab which is designed for time-domain acoustic simulations in complex and tissue-realistic media. The ultrasound transmitter and sensor functions were combined to simulate a piezoelectric transducer, which was spatially scanned to mimic imaging implementation in IVUS. The frequency of the IVUS was made adjustable in the simulation, and IVUS imaging of the same plaque was achieved with varying frequencies. The evolution of image quality was quantitively characterized with edge spread function, indicating that high-frequency IVUS can produce images with higher axial resolution but less penetration depth while lower-frequencies have the inverse effect, which is consistent with the physical theory. IVUS images of plaques with various shapes, sizes, and mechanical properties were also demonstrated. As such, this simulation platform offers a tool for the study of IVUS imaging. Further steps on this project will be taken to create a graphical user interface that is more user-friendly for clinicians, so it is promising to be used in clinical scenarios to guide IVUS catheter selection for the identification of atherosclerotic plaques.
Fueling the Future: A Study of Nuclear Fusion Reactors and Their Modern Capabilities
Suzanne Keilson (Loyola University Maryland, USA); Dahlia Shafiq (River Hill High School, USA)
One aspect of this work is to assess what people know and are interested in learning about nuclear fusion. Another is to introduce and explain current efforts to develop fusion reactors on a global scale. A survey has been developed to assess attitudes towards nuclear fusion. In particular, the survey is being distributed to high school students as they will be the important future decision makers about sources of energy. We also looked at some global data of the distribution and development of energy sources, which show that developed countries are not necessarily changing their power sources, but new sources may be more likely to be implemented in other parts of the world. The effort for a sustainable fusion reaction remains very much an international effort. This poster serves to illustrate the background and general process of modern nuclear fusion reactors, as well as dissect the benefits (both numerical and psychological) and roadblocks our planet faces to integrate fusion into our energy grid. From these factors we determine that the benefits to fusion are far beyond the problems that serve as walls towards its implementation.
Continuous-Release Mist Diffusion of Essential Oils For Varroa Control: A Field Study
Kaitlyn N Culbert (Toms River High School North, USA)
Evaluating the Safety of COVID-19 mRNA Vaccines by Comparing Its Side Effects to Conventional Vaccines'
Shichun Zhang (Carlucci American International School of Lisbon, Portugal)
A review of bionics for bird flight and potentially applicable mechanisms
Shu Zhitao (The Second High School Attached to Beijing Normal University, China); Lufan Wang (Florida International University, USA)
The Impact of Blurb Sentiments on Crowdfunding Success
Siyuan Liu (Beijing 101 High School, China)
Poster Session 2
Applying Face Recognition on Smart Family Album Player
Eckart M Schneider (Poolesville High School & John's Hopkins Applied Physics Laboratory, USA); Shunguang Wu (Johns Hopkins: Applied Physics Laboratory, USA)
In this poster, we present the design and function of a GUI that would work on many different devices with little set-up. At this moment, the GUI is programmed with C++ and the facial recognition engine is programmed with Python. The graphical-user interface was already programmed in C++ on a Windows device from a previous project before being used for this one. Python was the chosen programming language for facial recognition software as there are large sources of troubleshooting information and it can be implemented in a C++ program without much difficulty. The program as a whole would work through the user specifying a folder of images they have and the program would go through each file in the folder, including files inside other folders, and cluster them based on the people identified. For instance, the folder chosen contains photos of a family of a dad, mom, and a child. From there, each photo is clustered together under the respective person. The libraries used in both the GUI and facial recognition program will be shown and explained on the poster.
At the current stage, the facial recognition software is mostly complete as it is able to identify and recognize faces if given training data. In short, the program works by analyzing the commonalities of the training images and determining if the other images match with the data. Currently, the software is being worked on to allow for unsupervised machine learning, meaning the user doesn't need to give training data from beforehand. Furthermore, integrating the current Python program into the GUI is being looked at. With this project, we hope that any user will find it simple and efficient to sort their memorable family photos without spending any of their own precious time.
Effect of Cycle GAN in Melanoma Classification
Tyler R Jan (USA); Ava Miller (Tenafly High School, Tenafly, NJ, USA); Q'Andre Small (Bergen County Technical High School, Teterboro, NJ, USA); Ayushi Kumar (Monroe Township High School, Monroe Township, NJ, USA); Avimanyou K Vatsa (Fairleigh Dickinson University, Teaneck, USA)
In this paper, we explore a method to alter skin images to make it easier to identify whether a person has Melanoma. For example, if an image of a mole has a great deal of hair throughout the image that obscures the area, this method would increase the visibility of the mole by removing the hair. By doing so, Melanoma can be diagnosed more quickly and then receive medical care. For this, we will use the deep learning technique, Cycle GAN. Cycle GAN is trained through unpaired images. So, accessing data to train the algorithm will not be as problematic as finding paired images. Cycle GAN functions by translating an image into a new domain and translating an image again to recreate the original image. We are planning to implement this method onto data. We expect it to translate an image to make the image clearer such that performance metrics of classification methods (CNN, RNN, and XG-Boost) may be improved.
Using Computational Methods to Identify Small Molecules for Cancer Immunotherapy
Nicole Liang (USA)
One immunotherapy treatment against cancer activates the body's immune response by inhibiting interactions between cancer cells and T-cells (cells that fight against foreign substances or in this case, cancer). On the surface of T-cells lie immune checkpoint proteins, such as programmed cell death 1 (PD-1), that, by interacting with proteins on foreign cells, signal to the T-cells whether or not to attack. Cancer bypasses this system by presenting proteins, like programmed cell death ligand 2 (PD-L2), that could bind with PD-1 and thus not elicit an immune response.
Small molecule drugs aim to inhibit such PD-1/PD-L2 interactions and increase the immune response against cancer. None are FDA-approved yet, but research has been done with success, analyzing similar interactions between PD-1 and PD-L1 (another ligand found on cancer cells). Other inhibitors have also been researched, including IgG and monoclonal antibodies. Small molecule treatments are advantageous in that they have oral bioavailability, lower costs, better tissue penetration, and a shorter half-life.
Computational methods are highly effective ways that can be employed to screen a large number of small molecules to help identify potential candidates for drugs. Four steps are taken in this research project.
The first experiment determines whether possible binding sites exist on PD-1 for small molecules. A geometric method was used to find binding sites with the correct size. Next, an energy-based method was used to identify sites with a reasonable binding energy level.
The second step involves virtual screening of small molecules using Pocketquery (Pocketquery) to find ones that match the amino acid clusters on PD-L2 that bind with previously identified PD-1 binding sites. A series of screening tests were conducted in search of the optimal RMSD scores, indicating a good fit.
The next experiment conducts the molecular docking of the selected small molecules from the second experiment and quantifies the energy of the interactions with Swissdock (Swissdock) to ensure that the corresponding molecule can successfully bind to the protein.
Lastly, the small molecules with the right docking energy were inputted into SwissADME (SwissADME) and checked for any violations of Lipinski's rules, which ensure the drugs perform well when taken by a human.
Despite issues with database codes, unsuccessful file procedures, and many failed results, revised techniques eventually produced successful outcomes after applying computational screening to a large candidate pool.
16 small molecules have been identified to inhibit PD-1/PD-L2 binding, including one with an especially promising result. Since all experiments were conducted entirely with virtual tools, the next step would be to verify the bindings in a lab with actual compounds. With further physical screening, these molecules may be eligible for drugs for future use in patients.
Development of chitosan encapsulated thyme essential oil as an alternative fruit fly repellent for household use
Vivian Wu (Palo Alto High School, USA)
GAN Assistance in Diagnosis of Melanoma
Ava Miller (Tenafly High School, Tenafly, NJ, USA); Tyler R Jan (USA); Q'Andre Small (Bergen County Technical High School, Teterboro, NJ, USA); Ayushi Kumar (Monroe Township High School, Monroe Township, NJ, USA); Avimanyou K Vatsa (Fairleigh Dickinson University, Teaneck, USA)
Moreover, in order to classify skin images among benign or malignant or other types of skin cancer, the skin images are used for accurate testing and prediction by trained classification algorithms. These data-centric-based deep learning methods may detect skin cancers accurately and in the early stages and delineate them properly from healthy tissue. These methods use multiple layers of nonlinear models to recognize correct patterns. Therefore, The GAN's outcome will be processed through classification algorithms (CNN, RNN, and XG-Boost) and measured their six performance metrics - loss, accuracy, precision, recall, F1 score, and ROC - and compared against the performance metrics of original images of the dataset.
Tactic classification of broadcast soccer videos by using AI
Jioh In (Princeton International School of Mathematics and Science)
However, data scientists' game video analysis has problems. Data scientists directly review the game and add labels to the video hand by hand, which is a time-consuming task and makes it impossible to analyze the game in real-time. In addition, wearable trackers are expensive and heavy, which can be a price burden for amateur clubs and affect players' performance. This research aims to extract tactics from broadcasting soccer game videos automatically. Since it analyzes soccer broadcast videos, I expect that not only coaches and data scientists but also ordinary soccer fans can easily analyze tactics.
There are two ways to do this research. The first method is detecting the players and the ball in the video with convolutional neural network(CNN)-based object detection. Teams and player names are assigned to each player after object detection. The objects are tracked by using the deepSORT algorithm. The detected players and ball location information and interactions such as passes, shots, and tackles between players and players or between players and ball are quantified in each game. Using the quantified information from videos as inputs, the tactics are finally classified with supervised machine learning algorithms. The second method is to train and classify preprocessed frames with the deep neural network model without going through the detection process.
I am currently working on player identification and object tracking. Broadcasting soccer video datasets are preprocessed with action labels and video labels. I used You Look Only Once(YOLO) v5, which is CNN-based object detection algorithm, to detect players, balls, and referees in preprocessed videos.
A Quantum Optimization Algorithm for Single Machine Total Weighted Tardiness Minimization
Youhao S. Wang (Union County Magnet High School, USA); Julian Cheng (University of British Columbia, Canada)
Grover's search algorithm uses quantum mechanics principles to search an unstructured list, in which items are arranged in a completely random manner and no knowledge about the structure of the solution is assumed or used. The algorithm identifies the item in the list satisfying a given condition as the solution. For the unstructured search problem, while the computational complexity of classical algorithms grows at least at the order of the list size, the computational complexity of Grover's quantum search algorithm only grows at most at the order of the square root of the list size. For this type of problem, quantum computing is more efficient than classical computing.
Furthermore, there is another class of search problems in which quantum computing excels, and this class is called the combinatorial search problem or combinatorial optimization problem. In these problems, a cost value is associated with each item in the searching list and the goal is to find the item associated with the minimum (or maximum) cost value. This type of problem is NP-hard and has no known solution using classical computers that has computational complexity increasing in a polynomial relationship to the searching list size. While multiple suboptimal classical algorithms were developed based on classical computers, hoping to find suboptimal solutions with polynomial computational complexity, Trugenberger's quantum optimization algorithm was proposed for unconstrained combinatorial search problems based on quantum mechanics principles. Its idea, like that of Grover's quantum search algorithm, is to manipulate quantum parallelism so that the desired solution can be measured with a higher probability compared with nonsolutions. The computational complexity of this quantum optimization algorithm is independent of the list size.
However, combinatorial optimization problems with constraints occur in certain practical applications. For example, the total weighted tardiness (TWT) minimization problem, which is a well-known NP-hard problem, can be found in operational planning. This problem requires the construction of a schedule for a single machine with a fixed start time and multiple tasks with various due times that minimizes the sum of weighted tardiness of tasks relative to their respective due times. The problem can be formulated as a constrained combinatorial optimization problem.
To solve the TWT minimization problem, we propose a novel efficient quantum optimization algorithm based on Grover's quantum search algorithm and Trugenberger's quantum optimization algorithm to ensure that the desired solution satisfying the searching constraints and showing the minimal TWT value in the searching list will be measured with the highest probability. In the proposed quantum optimization algorithm, a more powerful cost function normalization method is also proposed.
Statistical Analyses for Fantasy Sports
Zachary Wu (Johns Hopkins University Applied Physics Laboratory, USA); Vince Pulido (Johns Hopkins University Applied Physics Laboratory)
In this poster, we present the steps it took for our FPL lineup, from data collection to mathematical analysis. Initially, for data collection, Premier League data CSV and XLS files from the past five years were acquired to make our analysis. However, since these data files did not include live data, it was difficult to achieve our task of continuous and live FPL predictions. Therefore, we then resorted to using the official FPL application programming interface (API) (https://fantasy.premierleague.com/api/bootstrap-static/), in order to request and pull live data from their database. Our work then moved on to player analysis: determining how much opponent difficulty impacted certain player performances. To do this, we created a Points vs. Fixture scatterplot for Premier League soccer players. The "r-squared" value indicated how much a difficult fixture impacted a player's performance. Looking at these scatterplots, it was evident which players needed to be targeted in order to optimize fantasy points. Since an athlete's FPL points are significantly boosted when they score a goal, we then looked at which factors most influenced goals scored over the past season. Correlation matrices were created through Python which allowed us to see that assists and fixture difficulty were largely correlated with goals scored. Finally, in order to draft our optimal team, a Python program was created using Pandas dataframes. Using the previous factors that were deemed significant (player goals scored and opponent difficulty) an optimal lineup was drafted.
Our team_picker program shows that statistics, math, and computer science can all be fused to make objective FPL decisions that are smarter than the average human. Currently, only opponent difficulty and goals scored were considered with our model. Given sufficient data, it is able to go use the API and go through the dataframe and draft a team. In the future, dozens of other factors could be considered (Ex. Home/Away Status, Game Time, Defensive Stats, etc.) to further optimize this drafting algorithm. Our project is not limited to FPL and we hope others will do the same with other Fantasy Sports such as Baseball, Cricket, Football, and even in the real world field of using data-driven decisions for professional sports management.
Coding Classical Logic Gates on the D-Wave Quantum Annealer
Naren K Sathishkumar (American High School, USA)
Objectives: This project was conducted in order to build and write a program which would allow the quantum annealer to replicate the behavior of classical logic gates. Given a certain input, the quantum computer should be able to realize the correct outputs based on the behavior of the gate that is being encoded.
Methods: The technical report "Boosting Integer Factoring Performance via Quantum Annealing Offsets" was used in order to formulate a binary quadratic model which replicates the behavior of the AND gate, and the half- and full-adder circuits. These models use the Ising penalty model, where constraints are set in order to achieve the wanted behavior; these models are encoded using binary, or in this case, the Ising model. This project took place over the course of 5 months, under the mentorship of Professor Terrill Frantz and Alex Khan from Harrisburg University.
Results: In the report, the binary formulation is used to encode the constraints. In practice, it is more practical to use the Ising formulation, which encodes 0 as -1, and 1 as 1. In this binary quadratic model, two dictionaries are required as inputs: the linear dictionary (for the values of qubits) and the quadratic dictionary (for the connections between these qubits). These values were taken from the charts and graphics from the "Boosting" report, and then implemented in a Python program. The results showed inputs and outputs that correspond with the expected values from an AND gate, and the half- and full-adders. The results of the project were posted in full detail in an article on Medium.com (https://tinyurl.com/yj55fc7m).
Conclusion: The program successfully replicates the AND gate and other small circuits (the half- and full-adders). Continuing on the success in encoding logical gates (such as the AND gate), more complex and useful circuits can be created, to solve problems never done before on a quantum annealer.
Bird Audio Recognition Using Convolutional Neural Networks
Kelsey H Lo (Johns Hopkins University Applied Physics Laboratory, USA)
In this poster, we present our method to identify the species of birds through analyzing audio profiles in convolutional neural networks (CNN). The first part visualizes the audio profile, using a MatLab program. The CNN algorithm analyzes two-dimensional images instead of one-dimensional audio files. Therefore, the MatLab program applies the Short-Time Fourier Transform onto the waveform audio file to create a spectrogram. It visualizes an audio profile by representing the magnitude of the signal frequencies in relation to time. The spectrograms are cropped to four seconds segments to increase the amount of training data and unify the spectrogram dimensions. Then, the next section inputs the spectrograms into a CNN algorithm. The CNN algorithm analyzes the spectrograms to extract the distinct features present throughout the spectrograms of one species. Since each bird has a distinct vocal sound, it has a distinct pattern in the spectrogram. This two-part process is reiterated for various species to introduce variety in the database as well as test the accuracy of the algorithm.
In the current stage, the CNN algorithm is trained to identify a few local species in Maryland. The algorithm requires additional fine-tuning to ensure accurate identification for every input. To create a program that promotes user convenience, integrating the components of the MatLab program and CNN algorithm into a streamlined program is in development. Moreover, once the CNN algorithm is finalized, we plan to expand the database of recognized birds by training the algorithm with more data. With this program, we aspire to encourage environmental sustainability by using birds as bioindicators. People can be a part of monitoring the welfare of their environment by recording nature's music.
Poster Session 3
Analyzing the environmental effect of Chlorophyta using Convolutional Neural Network
Heyu Li (PRISMS, USA)
Author: Henry Li
School: Princeton International School of Mathematics and Science
Determining a Correlation Between Common Skin Conditions and Anxiety
Janice Chao (High Technology High School, USA); Ching-yu Huang (Kean University, USA)
The datasets associated with the survey results were then converted to .csv files in order to load the data sets into the MySQL database. Structured Query Language (SQL) was used to create two tables. Table DEQ contains skin disorder information and it contains the column DED071, which indicates the skin disorder information with possible values 1, 2, and nan. Table CIQGAD contains anxiety information and it contains the column CIQG06, which indicates the presence of anxiety with possible values 1, 2, and nan.
SQL SELECT, INNER JOIN, and GROUP BY statements were used to efficiently join the datasets and generate the 2x2 matrix based on the categorical variables. From the dermatology dataset, 3140 people partook in the survey and the GAD dataset had 850 surveyors. Between the two datasets, a total of 850 common surveyors were found, 55 of which presented valid results in both surveys. A surveyor was excluded from the statistical analysis if it is missing information. A chi-square test based on the two variables was then performed on the resulting data to calculate the p-value of 0.038. This proves the existence of a significant correlation between anxiety and chronic skin problems within this dataset.
Reducing Plastic Consumption with Molecular Gastronomy
Shreya Dutt (MCVTS, USA)
Rapid and Automated Detection of Cancer and Immune Cells Using Novel Machine Learning Recognition Algorithms
Nesara Shree (Portland State University, USA); Eva Vu-Stern (Catlin Gabel School, USA)
Chess4Girls - Empowering Girls through Chess
Nesara Shree (Portland State University, USA)
As a girl with a thriving passion for Chess and a top-ranked female scholastic Chess player in my grade in the State, I have been frequently bothered by this underrepresentation, which neglects to provide aspiring girls with role models. Many of the friends I started with stopped competing through Elementary/Middle School. I believe that the Chess community is responsible for bridging this gap and motivating girls in the sport to pursue their interest.
My idea to stem this pipeline is by organizing All-Girls Chess Tournaments and tutoring Chess lessons for other girls in an effort to encourage, bring together and create the much-needed space for young female chess players. These events are held online, rated, incentivizing participation, and are regularly ongoing to continually foster girls' Chess careers. I want to help bring to light the valuable life skills that Chess can afford- critical thinking, planning ahead, strategizing, visualization, calculation and tactical analysis.
Visualizing Territorial Overlap of New Jersey Grapevines and Spotted Lanternflies using GIS
Sreya Jonnalagadda (Princeton International School of Matematics and Science, USA)
Color Melting Ice
Bela Sameep Sanghavi (1312 Ashton Falls Drive & O'Fallon Township High School, USA)
E = hν
with red color waves having the lowest energy and violet or purple waves having the highest.
During this experiment, ½ cup of ice will be dyed different colors-red, green, yellow, and blue-with food dye to see which one will melt the fastest. This will determine whether the amount of energy in each color wave will affect how fast the ice melts. 1 teaspoon of salt will be added to the ice to act as a catalyst for the melting process. The ice will be monitored the entire time to note any changes in melting.
Creating an app using AI to analyze eye movements to screen for Neurological Disorders
Srihithaa Vaidya (USA)
Using Unmanned Aerial Vehicles to Test Water Quality
Arnav Machavarapu (Westwood High School, USA); Aadet Samant and Zubin Chhabra (USA)
How to Design Single-Sheet Origami Models
Qi Ao (Princeton Academy of the Sacred Heart, USA)
I began folding origami when I was 9 years old, following instructions from books and watching YouTube videos. Within a year, I was experimenting and modifying different models. I learned how various parts were formed by playing around with paper and gradually started creating my own designs.
My goal is to share my passion by teaching others how much fun it is to fold origami and how much more fun it is to create original designs.
Poster Session 4
Automatic Clothes Finder for the Colorblind
Bao T To (USA)
Stem project-Straw roller coaster
Juliette Hancock, Jeanine Hancock, Julia Rodriguez, Alex Albiter and Carina Tullo (Goetz Middle School Jackson, NJ USA, USA)
We will be experimenting how forces act on a roller coaster. We are also manipulating the slope of an inclined plane to observe the effects of height on an object's speed. We will then learn about how gravity and normal force affects objects on an inclined plane.
We will be designing a roller coaster similar to the Batman coaster at Six Flags Great Adventure. We will be working on the following:
• The height of the coaster
• 90˚ turns with drops
• Keeping the ping pong ball on the track
We are using a cardboard box top as our base, glue guns to anchor the straws to the base, and we're going to be gluing straws together to create the tracks. We will also be testing each section as we build it.
We will be doing the following:
Calculating the force of gravity (Mass * acceleration)
• Mass of the ping pong ball
• Acceleration due to gravity
• The force of gravity
We will be using rulers and protractors to measure the track and angles.
We will consider the following:
• With higher heights, the acceleration will increase, which causes the time to decrease.
• As the angle increases, acceleration increases causing the time to decrease.
• Roller Coasters build up momentum and accelerate on straight tracks. Longer track lengths before turning gives roller coasters more times to accelerate before they have to decelerate before turning
• We will be calculating the average speed of the Roller Coaster, equal to the total length of the track divided by the time it takes to complete the ride, the shorter it takes the higher the average speed.
The result should be a working coaster that looks similar to the Batman coaster at Six Flags.
Teachers can use this as a Stem project for their classrooms.
Detecting Anomalies in IoT Device Communication Based on MUD Profiles With Zeek and Python
Rohan Nunugonda (Peddie School & Carnegie Mellon University CyLab, USA); Vyas Sekar (Carnegie Mellon University, USA)
Project NARWHAL (Nautical Autonomous Robot for Wire Hunting through Analysis and Localization) Poster Abstract
Thomas Edwards (Johns Hopkins University Applied Physics Laboratory, USA)
Comparing the Gains of Bipolar Junction Transistor's (BJT) using the IV characteristics of a Transistor
Roshan S Natarajan (Georgetown Day School, USA)
The objective of this experiment is to compare the gain (href) of an NPN to a PNP transistor by finding the Current vs Voltage (IV) characteristics of each type of transistor. The data collected from the IV characteristics will be used to extract the gain.
To find the IV characteristics of a transistor two schematics will be made: one for a NPN and another for a PNP transistor. The PASCO Science Workshop 750 will be used to collect data. Since the PASCO 750 only has voltage sensors, the voltage over the collector resistor will be taken and then the current will be extracted using Ohm's Law. Then the current gain will be calculated by dividing the base current by the collector current. The gain for the NPN transistor will then be compared to the PNP transistor to see which transistor has a stronger amplification.
Unsupervised GAN for Melanoma
Q'Andre Small (Bergen County Technical High School, Teterboro, NJ, USA); Avimanyou K Vatsa (Fairleigh Dickinson University, Teaneck, USA); Tyler R Jan (USA); Ava Miller (Tenafly High School, Tenafly, NJ, USA); Ayushi Kumar (Monroe Township High School, Monroe Township, NJ, USA)
Girls teaching Girls: Mentoring Middle School students in Mathematics
Sowmya Natarajan (Whittle School and Studios, USA)
Minimizing Weight in High Performing Gaming Mice
Judah Lerman (Community Park Elementary School, Princeton NJ, USA)
ATmega328P-Based Portable Heartrate Monitoring System That Can Transmit SMS Messages in Case of a Cardiac Arrest
Eugene John (Korea (South)); Joseph Matthew Y. Espinas and Ramon Carmelo Y. Calimbahin (Philippines); Randy O. Zebroff (Canada)
Facial Recognition for Deepfake Detection
Firaol Desta (JHU/APL Intern, USA)
Poster Session 5
Darwin's Finches Population - Will it Thrive or Dwindle under Climate Change?
Kavin S Sankar (Enloe High School, USA)
1 - Junior, Enloe High School, Raleigh
2- PhD Student, Department of Statistics, North Carolina State University, Raleigh
The Galapagos Islands are famed for their beauty and ecological diversity. They are also known for playing an integral part in the formation of Charles Darwin's theories of evolution and natural selection. The Galapagos Islands even have their own group of finches known as Darwin's Finches, whose beak dimensions were foundational to Darwin's theory of evolution, recorded in The Origin of Species. The Galapagos Islands have a tropical climate, and frequently experience El Nino and La Nina oscillations. This kind of climate comes with high variability on temperature and precipitation, which can affect the reproductivity of the Darwinian Finches. Studies have shown that increased rainfall during El-Nino results in hatching success up to some extent, but after a threshold rainfall, it starts decreasing. A factor that could affect rainfall is climate change, which can also very seriously diminish or increase the reproductivity of Darwin's Finches depending on the range of projected rainfall. This is because climate change can alter temperature and precipitation in the tropical area and change the frequency of El Nino and La Nina cycles, which in turn will affect the reproductive rates of the Finches.
This paper explores the relationship between finch reproductivity and environmental factors to predict the reproductivity of the Darwin Finches in the short and long term under scenarios of climate change. We have acquired some data on the Darwinian Finches in the Galapagos Islands from the book 40 Years of Evolution: Darwin's Finches on Daphne Major Island by Drs. Peter and Rosemary Grant. The book contains data on various factors such as the climate and rainfall of the islands, as well as the phenotypes and reproductivity rates of different species of Darwinian Finches. Using some of the data from this book we created a quadratic model that relates rainfall to the hatchling rates for the Geospiza fortis species (R2 = 0.6 and p-value - 0.006). Using climate data, particularly rainfall, from CMIP6 models, this study predicts finches' reproductive rates in 2050 and 2100. Based on this, a quantitative assessment of how finches' population may thrive or dwindle due to climate change will be provided under rainfall projections developed under different emission pathways.
Investigation of the physics of creating fire with a plasma lighter
Juliet Lopez (William F. Halloran School No. 22, USA); Jose L Lopez (Seton Hall University, USA)
The Ethics of Artificial Intelligence: How to Avoid Bias in Machine Learning Systems
Maya Lerman (Princeton High School, USA)
The STEM of Origami
Rishi Balaji (Gates Elementary School, USA)
Fortune Teller Game
Anish Chaganti (JP Stevens High School, USA)
The sequencing is very important in the part of the code that selects the season. The order in which the months are tested is critical to identifying the season. I implemented code that minimizes the number of tests that have to be made. For example, I eliminated the winter months of Jan, Feb, Mar on my first test, so my second test for the spring season checks for Apr, May, and Jun with a single test for the first six months of the year, and similarly for the summer and fall seasons. Iteration in this function helps me save storage because I loop on one-second audio clips to get the duration I want. I had difficulty implementing the loop in the same function because of Unity's limitations.
Overall, the game is very fun and interactive to the user.
How Climate Change Effects the Ocean's Reefs
Skylar E Glass (Visitation School, USA)
Historical Re-creation of Marconi's Wireless Telegraph
Stella C Firmenich and Richard Wegmann (Community Project Studios, Princeton University, USA)
The transmitter of the wireless telegraph uses a circuit, a solenoid and a spark gap to create an electric spark. This electricity is then sent from the transmitter's antenna to the receiver's antenna in the form of an electromagnetic wave. The receiver's antenna brings the signal to a coherer. The coherer-a glass tube with metal filling in it-becomes a conductor allowing the signal to continue to a polarized relay. When the signal reaches the relay, the "arm" attached to the relay strikes a bell and the coherer at the same time. This both produces audible noise and resets the coherer, preparing it for the next signal. The wireless telegraph combines the topics of make and break circuits, electromagnetism, radio waves, and early technological devices.
The goal of this project is to research and recreate a Marconi wireless telegraph from the early 20th century using similar methods and materials that were available to scientists then. This will enable students to not only study the history of the device, but also the exact parts and materials which were used in the invention. This allows a more developed understanding of wireless communication, make and break circuits, and other concepts that are key to the wireless telegraph.
Creating a model of the wireless telegraph is a great teacher for people who wish to fully understand how these devices functioned and were built. The model allows a visual as to how improvements in electricity and technology were pioneered over time. This develops a deep understanding of the electrical and technological concepts. While the building of a wireless telegraph can be an intensive process, the simple learning of models and study of them can help students further their studies.
We are working on this project under the guidance of Professor Littman of Princeton University, Harini Fredrickson, and Nathan Yates-a Princeton University senior. The project is part of a program spearheaded by Professor Littmann called the Community Project Studios.
Faraday's Ice Pail Experiment
Tvisha K Faria (20 Rowland drive, USA)
Michael Faraday, was an English scientist during the 19th century, greatly known for studying electromagnetism and electrochemistry. For his experiment, he acquired an ice pail (hence the name), to act as a metal container, an electroscope to measure the electricity, and a charged metal ball. By placing the metal ball into the pail without touching the sides, the free electrons around the metal pail repel the negatively charged sphere, leaving positive charges on the outside of the ice pal and negative charges on the inside. Whereas, if the metal sphere were to touch the pail, the electron charges would exchange with one another, and become neutral, without any charge.
My poster board will include information about the history, methodology, and takeaways of the ice pail experiment.
Modeling Historical Devices Using Computer Aided Design (CAD)
Vanisha S Nagali (Allentown High School, USA); Rohan Deb (Hillsborough High School, USA)
Using Fusion 360, I digitally recreated Joule's original design and modified it by adding a block-and-tackle system to allow a greater change in temperature. The next step was to animate the motion of the paddles caused by the falling weight. Since Fusion 360's animation feature is fairly basic, I researched alternative methods to simulate the movements. I wrote a script in Python to incrementally change parameters in Fusion 360, took frame-by-frame screenshots, and stitched them into a video. The result was a smooth stop-motion animation of the apparatus.
Bridging the Economic Divide through Blockchain
Jaden H Bethel (NONE, USA)
Ashutosh Dutta (Johns Hopkins University Applied Physics Lab)
Poster Session 6
Data Science and Analytics for Esports
Arjun Agrawal (Peddie School, USA)
The data for each CS: GO match, which includes both player actions and non-player events, is stored in a demofile. A demofile is a recording of the match generated by CS: GO that stores the data as a text of sequential sets of events with no contextualization of information. In order to perform analytics on the stored data, it must be modeled into organized data structures. The data parser developed by Dr. Claudio Silva and Peter Xenopoulos parses the data into Pandas DataFrames, which are spreadsheet-like data structures with rows and columns. Using the data parser, we introduce an analytics package consisting of (1) generalized functions to allow for the efficient filtering and aggregation of CS: GO data; and (2) specialized functions to allow for the efficient calculation of CS: GO statistics. The analytics package has been incorporated into a public software library and commercialized, with professionals and the worldwide CS: GO community currently using it.
Art and Science Education United
Helena Rittenhouse (Princeton University EPICS, USA)
Consider Leonardo DaVinci, creator of the Mona Lisa, among the most valuable paintings in the world. While he is a renowned artist, he was also a very successful engineer and architect. In fact, he designed a bridge in 1502 that would have been the longest bridge in the world at the time. It was dismissed as impossible to build, but in 2019, MIT engineers determined that the form of the bridge would have been structurally stable. Karly Bast, a recent MIT grad, herself said that it is a good example of how design and engineering are so closely linked.
Somewhere along the line, we started considering kids who are good at math and science as "smarter" as kids who pursue artwork. This is wildly off-base, and schools need to begin emphasizing art programs just as much as they do science programs. While science and math are traditionally thought of as rigid subjects, they must be seen with a creative eye, which requires artistic education as well!
Non-existence of the Algorithm that can Obtain the Optimal Solution for a Few Given Options of Investment in Constructive Mathematics
Jiahong Toby Sun (USA)
Using Social Media to Predict Stock Market Prices
Samuel T. Ghezae ( & Johns Hopkin's Applied Physics Laboratory, USA); Alexandru Cara ( & John Hopkins Applied Physics Laboratory, USA); Nicholas P Farber ( & Johns Hopkins Applied Physics Laboratory, USA)
These stories caught our attention which led us to wonder how strong of an impact social media had on the stock market, and if it can be used to predict the increase in prices in the future. We are examining data from social media and looking at any possible correlation to GME stock data.
If there is a predictable relationship between social media activity and stock price, people could make better stock purchases based on online data. This can encourage people to share what they believe are good stock choices with others and share conversations on the topic.
Using Machine Learning to Identify Gender Bias in Screenplays
Faith Comising, Hanna E Wosenu, Jason H Kang and Irene Shijo (Johns Hopkins University Applied Physics Laboratory, USA)
In 2015, Apoorv Agarwal of Columbia University and his team created a methodology that automates the task of determining whether a movie passes or fails the Bechdel Test. By categorizing each line of a screenplay into one of five tags ("N" for scene description, "C" for character name, "D" for dialogue, etc.), the machine learning algorithm finds the pertinent lines of the script and efficiently analyzes whether the movie meets the three criteria. Our group will be applying Agarwal's automated Bechdel Test methodology to recent movies in order to test the robustness of the proposed methodology.
Our project ultimately aims to contribute to the work being done on the Bechdel Test. Although the test is not an objective measure of whether movies are "sexist" or not, it is important to be cognizant that gender representations in the media, or the lack thereof, have the power to subconsciously enforce harmful gender stereotypes.
Distraction Osteogenesis Rign System (DORS)
Trung Q Tchiong (Upper Darby School District, USA)
The reversed engineering of the Synthes' DORS (http://synthes.vo.llnwd.net/o16/LLNWMB8/INT%20Mobile/Synthes%20International/Product%20Support%20Material/legacy_Synthes_PDF/DSEM-TRM-0714-0136-3_LR.pdf) provided CAD students various challenging learning opportunities such as AutoDesk Fusion 360 3-D parametric solid modeling and static stress analysis software, the Lulzbot TAZ 6 3-D printer (rapid prototyping technology), and a large scale poster printer operations.
CAD students discovered an alternate assembled rings' locking that provides an improvement to the ring system. They also gained an insight into the components of Team Dynamics, win-win negotiation, and the urgency of deadlines that real-life industries are facing.
The large-scale DORS poster shows names and titles of all members, the Synthes-DORS system, the engineering hands-written notes, the 3-D Lulzbot assembled parts, the G-Codes, and one basic Fusion 360 static stress analysis result.
Multiverse Network Management System: Developing an IP-Based Network Discovery Agent
Shane E Jayasundera (Montgomery Blair High School, USA)
Developing a Noise Canceling Device for Ranged Sound Suppression
Jason J Lai and Joseph Townsend (Gwinnett School of Math, Science, and Technology, USA)
Our experimentation materials consisted of the noise cancelling device, a sound source, a preset field with consistent distance increments between the device and source, and a decibel meter which measures the sound's volume. Testing was done by placing the device between the noise source - where a smartphone was used to generate three notes, (G4 (392 hertz), A4 (440 hertz), and B4 (494 hertz)) - and the target area where the decibel meter recorded volume levels. Data from the experiment was consisted of the volume levels in the target after a control test was taken so that the ambient volume of the testing environment was taken into consideration. The data from the testing was averaged out and the results are as follows: The two lower notes, G4 and A4, revealed a decrease in volume from 67.8 dB to 64.3dB and 66.8 dB to 63.7 dB respectively, while the highest note B4 had a slight increase in volume from 67.8 dB to 68.0 dB. Using a t-test to conduct data analysis, the volume change for notes G4 and A4 were found to be statistically significant, rejecting the null hypothesis. The note B4 on the other hand did not have a statistically significant decrease, thus accepting the null hypothesis.
By analyzing the results, we concluded that the device performed better at lower frequencies than higher frequencies. This may be influenced by the testing environment, where higher frequency noises are more susceptible to interference, affecting the device's ability to reduce the noise. Furthermore, the irregularity could be due to higher frequency noises having shorter wavelengths which are harder to position out phase with. Overall, the device did accomplish our project's goal of reducing low to medium pitched noise within an area, with future goals to extend the device's effectiveness to higher pitched noises.
Dynamic Fused Deposition Modeling for Rapid Development of Aerial Swarms
Ryan A Ellis (Johns Hopkins Applied Physics Laboratory, USA)
The Fading Of Chinese Ethnic Minority Culture - A Case Study Of Five Inner Mongolia Novels
Hao Wen (High School, China)
Ashutosh Dutta (Johns Hopkins University Applied Physics Lab)