Home » Posts tagged 'Interdisciplinary'
Tag Archives: Interdisciplinary
By Colin Capenito, Laura Drepanos, Will Figueroa, Katherine Gao, Nathan Laudani, Zoe Maddox, and Gunnar Vachris, VI Form
Read the First Season of a TV Series: 404
Editor’s Note: 404 is a six-episode television drama written in Getting LOST II: The Writers’ Room during the Spring Semester. This course examines the process that any network goes through to establish and produce a tv show. The class forms a “Writers’ Room,” in which all of the students collaborate on brainstorming ideas and writing episodes for a full premiere season of a show of the class’ design.
By Sarah Bechard, III Form
American Sign Language to “Youth” by Troye Sivan
Editor’s Note: In the St. Mark’s Saturdays’ course “American Sign Language,” the students found resources and learned the signs to perform one whole song in ASL. The goals of the assignment were to learn ASL vocabulary, understand how to sign songs, understand ASL word order, and practice sign fluency. The subtitles reflect ASL word choice and grammar, rather than spoken English grammar.
By Jason Zhang, VI Form
An Examination of the Ethics of Examining with Hitchcock and Foucault
Surveillance requires two groups: those who are watching and those who are being watched, which brings up the morality of surveillance. Is it appropriate for someone to observe another person intentionally? Does a person’s behavior change if they know that they are being watched? How is a person affected when their privacy is stripped away from them? Both the film Rear Window by Alfred Hitchcock and the essay “To Discipline and Punish” by Michel Foucault attempt to answer these questions. In Rear Window, Jeff is a brave man who has a history of racing sports cars and being in the military. Unfortunately, his adventurous life comes to a halt when he injures his leg. Jeff is forced to remain in his small, New York City apartment for weeks. Besides the occasional visit from his caretaker and his girlfriend, Jeff’s life is unbearably uneventful until he begins to watch his neighbors from the rear window. Likewise, Foucault’s essay “To Discipline and Punish” tries to understand the consequences of surveillance, but from the perspective of a prison’s architectural design. The prison cells of a Panopticon are arranged so that they all surround one viewing tower placed at the center of the circular building. Therefore, a person inside the viewing tower can see every cell and every person in a cell can see the person inside the viewing tower. Although it is never explicitly said whether or not surveillance is good or bad, both Rear Window and “To Discipline and Punish” come to the conclusion that surveillance is a powerful action. (more…)
By Cadence (Catie) Summers, IV Form
Green Sea Turtle – Chelonia mydas & Marine Turtle Exhibition
Green Sea Turtle – Chelonia mydas
Stage in Maturity – Adult (more…)
By Sarah Bechard, Michael Ferlisi, and Sydni Williams, III Form
Project Based Learning in The Global Seminar: The Zamibia Presentation
Editor’s Note: All III Formers took part in The Global Seminar’s project to create a proposal to improve the state of the fictitious country Zamibia. The students collaborated in groups as United Nations Development Programme Sustainable Development Teams. The two artifacts below include the slide presentation that the students delivered to their classmates, teachers, and visitors as well as the video of the presentation.
By Jenny Shan, VI Form
Casual Bike Rental Volume Prediction via Artificial Neural Network
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.