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Tag Archives: Science
By Megan Christy, VI Form
Treating AAA (Abdominal Aortic Aneurysms)
I am captivated by one particularly compelling question: how can we manipulate the body so it fixes itself? Could a combination of biology, chemistry, physics, and engineering be the answer?
I began exploring this question in the summer of 2017 while participating in a biomedical engineering program at Boston Leadership Institute. There, I applied this question to the way in which we treat aneurysms. Abdominal aortic aneurysms (AAA) are a “silent killer.” They form when the walls of a blood vessel weaken and are difficult to diagnose due to the lack of symptoms prior to rupture. Once ruptured, AAAs have a mortality rate of 90%. When an unruptured AAA is diagnosed, it is vitally important to treat it in a minimally invasive and lasting manner. (more…)
By Cathy Zhou, IV Form
Computer Vision: Mapping Poverty in Uganda
This summer, I attended an all-girls program called Ai-4-ALL, formerly known as SAILORS (Stanford Artificial Intelligence Laboratory’s Outreach Summer Program). Inspired by the camp’s model “AI will change the world. Who will change AI?” I believe that people, instead of perceiving artificial intelligence (AI) as threats, should use it as a tool for impact. During this camp, I, along with seven other AI-enthusiasts, created a model for mapping poverty using satellite images. (more…)
By Gillian Yue, VI Form
Software Pipeline Connecting Close-Range Photogrammetry and 3D Printing
The aim of this project is to make it possible for an average person with no prior knowledge in photogrammetry to 3D-print small objects found in daily lives. My work is to create a software that serves as a pipeline; the software connects the multiple processes that are required to transform the input of of photos of the target object into an output of a 3D printable model file. In other words, what used to be a complicated process of switching between different tools and manually processing the model to make it 3D printable becomes a simple one-click routine where the user can provide the initial group of photos, and then simply sit next to the 3D printer to wait for the object to come out half an hour later. (more…)
By Izzy Kim & Riya Shankar, VI Form and Haley Dion & Laura Drepanos, V Form
Autism-Vaccine Controversy: Video
Editors’ Note: In Advanced Biology, students were encouraged to tell the story that they felt compelled to relate about their Public Health issue (click here for assignment). In this video, the students integrated a given Case Study with relevant information gathered through independent research. Their integration of the Case Study with additional research reflects an advanced understanding of, and ability to convey, scientific content.
By Geetika Surapaneni, Frances Hornbostel, & Graham Butterfield, III Form with Will Figueroa, V Form
Diminishing the Diversity of Devastating Diarrhea
CLICK ON EACH IMAGE BELOW TO ZOOM TO EACH PIECE OF PROJECT. (more…)
By Jeongyong Chris Yang, VI Form
Autonomous Navigation and Decision-Making Process Using Machine Learning and Deep Learning
Autonomous vehicles are self-driving cars that do not require human drivers. They use sensors that are attached to the vehicle as their vision to detect their environment. After the vehicle detects other objects or signals, computer programming (coding) allows them to react to the situations adaptively. Even though the sensors do not need to be improved, the millions of situations the cars can face on roads create difficulties for people to build a sophisticated computer program that makes the autonomous vehicles completely safe on roads.
First, I decided to build an algorithm pseudocode to help resolve this problem. During this process, I built mazes and followed the instructions based on the algorithm manually to check whether the algorithm is effective. I mainly used three different models for my mazes, each with different difficulty levels to ensure that the algorithm works every time. Then, I decided to record the information (velocity and displacement for both x and y directions) about the vehicle on the map so that the following vehicles can get a picture of the map automatically. However, if the subsequent vehicle detects a different or an altered map with its sensors, the new information will also be recorded on the map. Finally, the final vehicle will follow the path set by the first vehicle, but the map will guide the car with the most efficient path after completely learning and optimizing the possible paths.