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Casual Bike Rental Volume Prediction via Artificial Neural Network

By Jenny Shan, VI Form

 

Casual Bike Rental Volume Prediction via Artificial Neural Network

Abstract

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Aim: This study aimed to build a predictive model for casual bike rental volume using artificial neural network and compare its performance with traditional regression method, linear regression.

Method: The data set under study is related to 2-year usage log of a bike sharing system namely Capital Bike Sharing (CBS) at Washington, D.C., USA. There were some external sources that corresponding historical environmental values such as weather conditions, weekday and holidays are extractable. All the records were randomly assigned into 2 groups: training sample (50%) and testing sample (50%). Two models were built using training sample: artificial neural network and linear regression. For artificial neural network, the input layer has 11 inputs, the two hidden layers have 3 and 2 neurons and the output layer has a single output.  Mean squared errors (MSE) were calculated and compared between both models. A cross-validation was conducted using a loop for the neural network and the cv.glm() function in the boot package for the linear model. A package called “neuralnet” in R was used to conduct neural network analysis.
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What My Brain Learned via the Dissection of Another

By Julian Yang, V Form

What My Brain Learned via the Dissection of Another

Before walking into class on Monday, I was filled with curiosity and excitement. It has been six years since I saw an actual brain, and I was barely engaged at that time – although there was a parent who worked with brains and explained the information to us, no actual dissection was involved. The closest I got was holding the brain in my hand

My anticipation began to build during the “instructing” phase. Two feelings stirred inside me: one, I would be able to see everything that I learned in the past two weeks, and two, I was going to feel like a surgeon while using the scalpel. I made sure, however, to be careful: the way it sliced during Ms. Lohwater’s demonstration was enough to curb my excitement. (more…)

CAR T Cell–Giving Cancer Patients New Hope

By Grant Gattuso and Frank Hua, VI Form

CAR T Cell–Giving Cancer Patients New Hope

This past summer we had the opportunity to work in a cancer research lab in Seattle for four weeks— a very unique experience, especially for high schoolers.  We worked in Dr. Michael Jensen’s ‘82 lab in the Ben Towne Center For Childhood Cancer Research, which is affiliated with Seattle Children’s Hospital. The lab focuses on CAR T Cell, a immunotherapy that gives cancer patients a new hope. (more…)

Boys to Businessmen: A Blog About Industrial Real Estate

By Nick Karlsson, Filip Kierzenka, and Nick Bechard, VI Form

Boys to Businessmen: A Blog About Industrial Real Estate

Jed Raymond ’95, Nick B., Nick K., Fil, Howard Hodgson ’74

This past summer, we traveled to the United Kingdom and Poland to experience international business and commercial real estate. The previous summer, we were fortunate to intern at Cabot Properties, an industrial real estate firm in Boston. That summer, we compiled data on the Polish industrial real estate market and economy. This information proved to be beneficial during our 11-day trip when we visited the UK branch of Cabot and met with various other firms and market experts. Our adventures are organized into one website. This trip was an unforgettable learning experience that was made possible by the A.A. Jones Grant.  (more…)

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…)

From The Writers’ Room: Extracurricular, An Original TV Series

By Riya Shankar, Lulu Eastman, Lillian Stout, Cooper Giblin, Tony Banson, Nick Hallal, Sophie Haugen, Sada Nichols-Worley, Ben Hunnewell, and Jimmy Tobin, VI Form

From The Writers’ Room: Extracurricular, An Original TV Series

(Above title sequence scene: music composed and played by Riya Shankar & Sophie Haugen)

Check out Extracurricular’s fan website here: https://extracurricular.squarespace.com

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