BBDC Basic:
Come by & experience big data!
The Basic Track is aimed at high school students. In the data analysis competition of the Cognitive Systems Lab (CSL), Center for Applied Space Technology and Microgravity (ZARM), and the Fraunhofer Institute for Digital Medicine (MEVIS) of the University of Bremen participants compete for prize money up to 2.000 Euro, and attractive prizes.
Primary Responsibility: Hui Liu (hui.liu@uni-bremen.de)
ZARM-Track: Ina Barwich (ina.barwich@zarm.uni-bremen.de)
MEVIS-Track: Anna Rörich (anna.roerich@mevis.fraunhofer.de)
Technical Support:_____ Jordan Behrendt, Matthew White, Anthony Mendil, Lourenco Rodriguez, Arthur Belousov
Supervisor(s): Tanja Schultz and Heinz Brandt
FInancial Support:______ Bremen Stock Exchange Foundation
Gallery: BBDC and BBDC Basic
MEVIS-Track Challenge
Introduction:
The future of medicine is digital, and that's essential! Doctors are confronted with a flood of data in their daily work, from which they must derive diagnoses, treatment plans, and individual prognoses for their patients. AI can help manage this volume of data more effectively. MEVIS demonstrates, using the example of heart attack cases, how AI assists in processing data and making doctors' work easier. However, the limitations of predictions and prognoses also need careful consideration.
Submission Deadlines:
- MEVIS-Challenge Part 1 : 06.11.2024
- MEVIS-Challenge Part 2 : 19.01.2025
Task Description:
- Load the data from the CSV file and analyze it. You will notice that some datasets are incomplete. However, an AI can only be trained on complete data. How do you handle missing information?
- Define an appropriate train/validation split.
- Challenge Part 1: Train a random forest model to predict whether any complication will occur after a heart attack, without differentiating the type of complication. You may use existing routines from freely available Python packages.
- Challenge Part 2: Train a random forest or any other freely available AI model to predict the specific complications. In this case, the model should explicitly indicate which complication(s) are likely to occur.
Challenge your AI! – Testing:
- Save the predictions of your AI for the validation dataset as a CSV file named "Prognosen.csv." Each row should represent a patient, and each column should correspond to a specific complication. If a complication occurs, a "1" should be entered in the respective column, following the format of the provided training and test data. The first row of the CSV file should contain the column names. An example format can be found in the file "Beispiel-Ergebnisse.csv."
- Please upload your "Prognosen.csv" file here to receive your score. The maximum score is 1.0, and the minimum is 0.0. The score indicates the percentage of patients for whom your predictions are correct.
- Not satisfied with your result, or others are scoring higher? Then tune your AI and give it another try!
Notes (Please Note):
- Challenge Part 1: For the evaluation of Part 1, only the last collumn of your submitted results table will be used. Therefore, all other columns may remain empty in this case.
- Challenge Part 2: For the evaluation of Part 2, all collumns of your submitted results table will be used. Therefore, the last column should also be filled according to your predictions.
Leaderboard: BBDC Basic MEVIS-Track Part 1
Leaderboard: BBDC Basic MEVIS-Track Part 2
ZARM-Track Challenge
Introduction:
Sending humans to Mars and exploring our red neighboring planet has long been a dream of space exploration. However, Mars differs from Earth in many ways. The lack of atmosphere, absence of liquid water, and high radiation levels currently make it impossible to send a crew on such a journey. Instead, Mars rovers are used, but even they face numerous challenges on the Martian surface, with no direct intervention possible from Earth. When the first humans step onto Mars in a few years, additional difficulties will arise. One of these is the scarcity of resources, which must be brought from Earth and carefully utilized and recycled on Mars.
To address the wide range of challenges presented by a Mars mission (with or without humans), ZARM is offering two tasks for the 2024/25 Challenge.
Task Description:
Task 1 – Stress on Mars:
Using a CAD program, design a small rover (maximum dimensions of 30 cm in length, width, and height) capable of completing the following tasks:
- Navigate slopes of 5%, 10%, and 15%, both ascending and descending
- Drive despite headwinds and crosswinds
- Drive on smooth surfaces, sand, and gravel
- Drive while carrying a load of 100g, 300g, and 500g
For propulsion, you will receive the motors and the brick from Lego Spike Prime at the kickoff.
Document your work process and outline how you approached finding the solution.
Task 2 – Life Support System:
Build a water recycling system capable of purifying a liquid provided by ZARM as effectively as possible, making it reusable.
- Create a project outline. Identify the types of contaminants in the water. How can these be removed? In what sequence should the recycling process occur? What materials do we need?
- Conduct initial tests at home or at school and create a list of all required materials. Send this list by November 17, 2024, to Challenge@zarm.uni-bremen.de. The material list should include all items, materials, and chemicals you need.
- Build the recycling system together with ZARM in the lab and test your idea.
- Document your work process and outline how you approached finding the solution.
Submission Deadlines:
- Final Parkour: 10.01.2025
- Final Labtest: 16.01.2025
- The final submission date for both tasks is January 19, 2025.