MecSimCalc had it's first ever hackathon in July 2022. This competition sponsored by 1984 Ventures, was aimed to increase the number of users and showcase the versatility of the platform. Users would create an app on the MecSimCalc website, tag it as "Comp07092022" and publish it for a chance to win up $500. $400 would be given to the app with the highest score and $100 would be given to the most viewed app. However, since we had received so many high quality submissions, three additional bonus prizes were given out to apps that had not won but were innovative uses of the platform. Throughout the competition there were 77 sign-ups and 13 submissions. This blog post is dedicated to the top 5 scoring apps from MecSimCalc's July 9th - July 16th, 2022 Build-A-Thon. To view all apps submitted during the competition, look for the tag "Comp07092022" on the MecSimCalc Explore page.
Bio: Dorsa Rohani
Dorsa Rohani is a current high school student at Pierre Elliott Trudeau High School in Ontario, Canada. From electrical and computer engineering to healthcare and medicine, Dorsa is passionate about the intersection between technology and healthcare. In creating iMedic, Dorsa aimed to define the patient experience, and to address the ongoing predicament surrounding the chronic lack of access to efficient and accurate medical diagnosis. Indeed, across the continuum of care, the execution of ethical medical examination is of high precedence. In her spare time, she enjoys challenging herself, as well as performing the cello with her local string orchestra.
Bio: Videet Mehta
Videet Mehta is a rising Junior at Dulles High School in Sugar Land Texas. He is passionate about both medicine and technology. For the last four years, he has built robots that have been placed at the top of the First Tech Challenge state and world championships. He also does competitive programming and is currently in the silver division of the USACO competition. He learned python and ML just over a year ago. And since then, he has created many medically related machine learning projects. Additionally, he is the co-founder of two ed-tech companies: Project SUCCEED (projectsucceed.org) and Xceleration (xceleration.org).
Bio: Zarik Khan
Hi, I'm Zarik Khan and I'm a rising junior at Dulles High School. I'm passionate about machine learning, bioinformatics, web development, biomedical engineering, and app development. I worked with Videet and Dorsa to create iMedic to contribute to the distribution of medical technology in areas around the world that lack accessible access. Our project was made to detect some of the fatal causes of death in these areas to provide people a way to monitor their health and take necessary action quickly. MecsimCalc allowed us to integrate our python code into an easy, aesthetic, and secure front-end system. We hope to innovate on our current project by improving the accuracy of our calculations, expanding our app's reach, and developing new features.
From the detection of infectious, cancerous, and cardiovascular diseases using a variety of means; to academic tools such as 3D computations of Chaos Theory, iMedic is a multipurpose platform that uses ML, AI, libraries, and big data. As an app created for Third World countries & rural areas, it is for individuals who do not have access to medical support nor fast and efficient examination. iMedic is designed to be used frequently to evaluate one's risks for the most common medical conditions, and to provide users with knowledge of their current health. In addition, iMedic includes cutting-edge tools for research. By including a chaos calculator—that computes & graphs chaotic systems such as the Lorenz Attractor & Logistic Map with yielded data via input—iMedic has many applications to fields extending far beyond medicine, such as data science, math, and CS as well.
Bio: Chetan Tyagi
I am Chetan Tyagi, who will be joining University of Alberta for the undergraduate in Computing Science this fall, and is very keen to learn new things about the subject and keep up to date with the latest technologies.
About Javelin Power Saver
My app is called "Javelin Power Saver". As the name suggests, this application aims to conserve your energy, and therefore cut your bill. With the help of this easy-to-use app, you will be able to
-calculate the power your appliances uses per month -the total money you spend on them in a month
-compare yourself with the electricity bill of an average citizen
-compare your appliances with popular products in the same range
Why I made this app
As per a report by World Economic Forum, the end use efficiency of electricity in residential environment in USA is a mere 65%, signifying the level of wastage of energy. The waste of electricity ends up in increasing the costs for the user, while also making a carbon footprint on the environment. The application will focus on conserving electricity. The target users of this application will be all the people who use electricity in their homes.
A big proportion of people in both urban and rural areas use electrical appliances and pay the electricity bill. It is common to look at the bill and thinking how the cost can be reduced. But as there is no way of accurately understanding how, we guess on different appliances, which makes the process harder. This application solves this. Also, before getting a new electrical appliance, we will be able to estimate the total power consumption, estimate total costs, compare with average households, and recommend how the user can make the combination of electrical appliances more efficient.
My experience with MecSimCalc
Compared from my previous experiences of creating web-apps, making apps here is much easier than anywhere else I have seen on the internet. It is completely free, encouraging both beginners and professionals to create apps without any hindrance. Overall, this is a great website to work on and I will recommend it to everyone interested in creating apps using Python.
Bio: Camilo Andrés Rojas Hernández
I am Camilo Andrés Rojas Hernández, mathematics student at the Universidad Nacional de Colombia Medellin, since about 6 years ago I have learned on my own the development in python, its libraries and frameworks, something that identifies me is self-taught learning because over the years I have developed both soft skills and technical skills in the language, I am very motivated by programming and learning things every day.
About Grids for artists
I made this application because since my sister studies plastic arts, sometimes she has problems when it comes to making guide grids for her canvases, so I wanted to satisfy that need she had using python and the MecSimCalc tool, it is very easy to use, plus it has the main libraries, such as machine learning and image processing, in this case with Pillow, the input and output of data is very comfortable, anyone can share and create applications in record time. Awesome!
Bio: Jasper Eitzen and About 2D Heat Equation Visualizer
My name is Jasper Eitzen, I’m currently a graduate student at the University of Alberta, pursuing a Master of Science in Mechanical Engineering. The work I do for my thesis mostly consists of lab experiments, although I do have experience using Python to analyse experimental data as well as some programming experience from my undergrad and graduate studies. I came up with the idea for 2D Heat Equation Visualizer from having written some simple numerical solvers in the past and seeing that MecSimCalc could provide a convenient way to get inputs from the user. I thought that the results of such an app could look quite interesting since I’ve done similar projects in the past, and I always found it cool to set up an initial condition and see how it evolves over time based on math and physics. With contour plots as outputs, users can play around with the app’s inputs to try and get unique results. I needed quite a few inputs and the input page on MecSimCalc was very useful in letting me lay them all out and provide explanations so that the user could pick values that provide good results. As someone with no experience in web development, I wouldn’t have been able to make something like this app without the interface that MecSimCalc provided.
Bio: Soham Jain
Soham Jain is currently a sophomore with a passion for machine learning at Thomas Jefferson High School for Science and Technology, a prestigious high school that is ranked #1 in the United States. He works as a Machine Learning Engineer for a local start-up company called Vytal, where he assists in creating novel ML algorithms for fast and comprehensive neurologic and cardiac assessment through smartphone-based applications. In the past, he has worked closely with machine learning models using classification techniques to diagnose medical conditions, such as Malaria and Lyme disease. He has also won several awards from hackathons in the past through developing contemporary algorithms and deploying applications to assist with effective clinical diagnoses. As a technology specialist on the executive committee for his school's Student Government Association, Soham has used his experience in computer science to assist the student body with leading events and initiatives. Soham is also passionate about competition math, as he has competed in numerous national-level contests such as AIME, AMC 10, and MathCounts. Outside of school, Soham likes to tutor other students, play the piano, spend time with friends, and listen to music.
LymeML is an application built on MecSimCalc that uses novel machine learning algorithms to diagnose Lyme disease, a prevalent issue in numerous countries around the world. Research suggests that 14% of the world's population is currently affected or has been affected in the past with Lyme disease, contributing to the significance of this issue. Contemporary methods to diagnose this disease require a blood test. with lab reports anticipated to arrive three or four weeks after the patient seeks medical attention. However, waiting several days to receive a diagnosis allows symptoms to worsen, causing detrimental and irreversible damage to the brain or heart. Soham Jain, a current high school sophomore in the United States and Machine Learning Engineer at a local startup company, noticed that this issue can be resolved through creating a machine learning algorithm that sends an effective and immediate result to the user through image classification and a self-check symptoms diagnosis. This app implements convolutional neural networks (CNNs) and Python libraries such as NumPy and TensorFlow to accurately diagnose Lyme disease. Implementing this app will help several individuals living in remote areas to expedite the process of receiving a medical diagnosis, and differentiate their symptoms/rashes from those of other diseases. With the help of machine learning and MecSimCalc for making this app available to others, countless individuals will receive an instant diagnosis of Lyme disease and can treat their symptoms faster.
My experience with MecSimCalc
With the help of MecSimCalc, LymeML will continue on its mission to aid countless more individuals living in remote areas to receive an instant diagnosis for Lyme disease, and can treat their symptoms more efficiently. Through featuring LymeML as a winner for this hackathon, the opportunities for telemedicine and machine learning algorithms in the future has opened, and soon more accurate and immediate models will be created to diagnose several diseases. Creating the LymeML app through MecSimCalc was very straightforward and many Python libraries were accessible. The documentation and app analytics were also available, making my experience with this website more professional and enjoyable.