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Computer Vision: Mapping Poverty in Uganda

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…)

Software Pipeline Connecting Close-Range Photogrammetry and 3D Printing

By Gillian Yue, VI Form

Software Pipeline Connecting Close-Range Photogrammetry and 3D Printing

Click on Image to View Full Poster

Abstract/Introduction

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…)

Autism-Vaccine Controversy: Video

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.

Click on Image for Video

 

Diminishing the Diversity of Devastating Diarrhea

By Geetika Surapaneni, Frances Hornbostel, & Graham Butterfield, III Form with Will Figueroa, V Form

Diminishing the Diversity of Devastating Diarrhea

Please click the image to download/see the poster. Scroll below to see each individual piece.

CLICK ON EACH IMAGE BELOW TO ZOOM TO EACH PIECE OF PROJECT. (more…)

Autonomous Navigation and Decision-Making Process Using Machine and Deep Learning

By Jeongyong Chris Yang, VI Form

 

Autonomous Navigation and Decision-Making Process Using Machine Learning and Deep Learning

Abstract

Please click the image to download/see the poster. Zoom in to read specifics.

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.

To read the full project write-up, CLICK HERE. (more…)

20% Time Project: Gardening–The Long Process of Planting

By Eve Elkins, III Form

20% Time Project: Gardening–The Long Process of Planting

Editors’ Note: In Ms. Amanda Hultin’s III Form English classes, her students pursue 20% Time (or “Genius Hour”) projects. Some essential elements include taking control of one’s own learning, choosing an individual topic, deciding how to learn and to produce a public product, and reflecting on the process.

Click on image to view Eve’s Padlet.

Reflection on learning:

*What content/information did you learn during this project?

I learned about gardening. I learned that the perfect time to water the plants is in the afternoon. If you water them at night or early morning, they are more likely to grow fungus. I also learned that snap peas, which was the vegetable I was growing, grow best in mid-spring, which was when we started this project. They also have the quickest growing rate which was about two months. That is how I came to choose snap peas. When I contacted the manager of Chestnut Hill Farms, I was able to find out about the evolution about gardening. Now, in current times, gardening has shifted to being grown indoors all year round. Gardening used to be seasonal but now, due to modern technology, there have been trucks and trailers developed to sustain plants even in winter. Lots of people still garden but the way we do it has changed. (more…)