Physical Sciences and Mathematics Commons^™

Machine Learning: Face Recognition, Mohammed E. Amin

Publications and Research

This project explores the cutting-edge intersection of machine learning (ML) and face recognition (FR) technology, utilizing the OpenCV library to pioneer innovative applications in real-time security and user interface enhancement. By processing live video feeds, our system encodes visual inputs and employs advanced face recognition algorithms to accurately identify individuals from a database of photos. This integration of machine learning with OpenCV not only showcases the potential for bolstering security systems but also enriches user experiences across various technological platforms. Through a meticulous examination of unique facial features and the application of sophisticated ML algorithms and neural networks, our project …

Unmasking Shadows: Unraveling Crime Patterns In Nyc's Boroughs, Jack Hachicho, Muhammad Hassan Butt

Publications and Research

New York City's crime dynamics have been on the rise for decades. Brooklyn and The Bronx have been disproportionately affected. This research aims to understand the crime landscape in these boroughs to formulate effective policies. Using crime data from official sources, statistical analyses, and data visualizations, the study identifies patterns and trends. The data encompasses over 400,000 reported incidents collected over the past 10 years, meticulously categorized by borough, crime type, and demographic information. Brooklyn has the highest overall crime rate, followed by The Bronx. Most shooting victims are Black. This highlights the need for holistic community programs to address …

Messiness: Automating Iot Data Streaming Spatial Analysis, Christopher White, Atilio Barreda Ii

Publications and Research

The spaces we live in go through many transformations over the course of a year, a month, or a day; My room has seen tremendous clutter and pristine order within the span of a few hours. My goal is to discover patterns within my space and formulate an understanding of the changes that occur. This insight will provide actionable direction for maintaining a cleaner environment, as well as provide some information about the optimal times for productivity and energy preservation.

Using a Raspberry Pi, I will set up automated image capture in a room in my home. These images will …

Introduction To Computers And Programming Using Python: A Project-Based Approach, Esma Yildirim, Daniel Garbin, Mathieu Sassolas, Kwang Hyun Kim

Open Educational Resources

Welcome to the “Introduction to Computers and Programming using Python: A Project-based Approach”. This book is designed to teach basic programming skills to students who are new to the field of computing using a project-based learning approach. It has been designed to give freedom to the instructor, both in format and topics ultimately used throughout the course. While we provide 13 turnkey projects, it is only expected that 3 or 4 are used over the course of a semester, and all projects are provided both as textual instructions (the student version of this OER) and Jupyter Notebooks (one with and …

Cs04all: Command Line Python, Hunter R. Johnson

Open Educational Resources

Command Line Tutorial

Students are presented with information relating to stand alone Python programs, stdin, stdout, and command line arguments. This is a lab exercise. After completion students should be able to create executable Python programs which can accept input from stdin or command line arguments.

Please begin with the READ_ME file.

https://cocalc.com/share/bde99afd-76c8-493d-9608-db9019bcd346/171/stdin?viewer=share/

This OER material was produced as a result of the CS04ALL CUNY OER project

Cs04all: List Comprehensions, Hunter R. Johnson

Open Educational Resources

List Comprehensions

This is a tutorial on list comprehensions in Python, suitable for use in an Intro or CS0 course. We also briefly mention set comprehensions and dictionary comprehensions.

https://cocalc.com/share/bde99afd-76c8-493d-9608-db9019bcd346/171/list_comprehensions?viewer=share/

This OER material was produced as a result of the CS04ALL CUNY OER project

Activity - Python Functions - Scrabble Game, Robert J. Domanski

Open Educational Resources

A Python Functions activity - "Scrabble game" - for CS0 students. Part of the CUNY CS04All project.

Activity - Python Lists - "Hangman Game", Robert J. Domanski

Open Educational Resources

A Python Lists activity - "Hangman game" - for CS0 students. Part of the CUNY CS04All project.

Activity - Python Functions - Drawing With Turtle, Robert J. Domanski

Open Educational Resources

A Python Functions activity - "Drawing with Turtle" - for CS0 students. Part of the CUNY CS04All project.

Activity - Python If-Else - "The Dating Equation", Robert J. Domanski

Open Educational Resources

A Python IF-ELSE activity - "The Dating Equation" - for CS0 students. Part of the CUNY CS04All project.

Activity - Python Lists - "Gift Exchange", Robert J. Domanski

Open Educational Resources

A Python Lists activity - "Gift Exchange" - for CS0 students. Part of the CUNY CS04All project.

Make A Twitter Bot In Python: Iterative Code Examples, Robin Camille Davis, Mark E. Eaton

Publications and Research

A tutorial based upon the LACUNY Emerging Technologies Committee’s “Build Your Own Twitter Bot” day in December 2015, which was billed as a gentle introduction to programming in Python.

Using Python To Solve The Navier-Stokes Equations - Applications In The Preconditioned Iterative Methods, Jia Liu, Lina Wu, Xingang Fang

Publications and Research

This article describes a new numerical solver for the Navier-Stokes equations. The proposed solver is written in Python which is a newly developed language. The Python packages are built to solve the Navier-Stokes equations with existing libraries. We have created discretized coefficient matrices from systems of the Navier-Stokes equations by the finite difference method. In addition we focus on the preconditioned Krylov subspace iterative methods in the linearized systems. Numerical results of performances for the Preconditioned iterative methods are demonstrated. The comparison between Python and Matlab is discussed at the end of the paper.