COLLEGE OF ENGINEERING & SCIENCE

Lunchpad is a Collaborative Dining Decision Platform. The goal of the project is to create a website for two or more people to choose a place to eat without having the hassle of trying to pick a place that everyone enjoys. This will be accomplished by allowing users to join a room using created codes on the website and enter their preferences for eating. Next, an algorithm will determine which types of food should be pulled by Google’s API based on what they enjoy or do not enjoy. Finally, a random decision algorithm will decide one place and suggest it to the users. Additional features include: a food allergy toggle, location on where to eat, and a reroll feature that chooses another place to eat.

Taking good group photos is difficult, and this app seeks to remedy that. When taking a group photo, this app allows the user to simply set up their camera and let the app take the photo when it’s ideal. Through facial detection technology, this app takes a photo when everyone is smiling and has their eyes open. The app gives feedback to the user, showing the user detected faces, smiles, and eyes, and letting the user know when a photo is taken, to make the app as intuitive as possible.

This project is a math-to-text formatting web application. At Louisiana Tech University, students enrolled in Calculus classes do their homework on a website called Webwork. Webwork requires that all answers be entered in a plain-text format, which can be very challenging when entering equations (for example, fourth degree Taylor polynomials). Math Input To Text (for) You, or MITTY, is a user-friendly website capable of taking images (e.g. camera, clipboard, file system, and snipping tool) of equations as well as handwritten input and converting it to plaintext. Since the result is returned as plaintext, the output of MITTY can also be used on other online homework websites.

AttendME is an automatic class attendance check-in webpage. There are various ways to take attendance, all with their own drawbacks. This idea seeks to minimize the amount of time required for a professor to take attendance in class. The webpage allows students to check in to classes via geolocation on a roll uploaded by the professor. This roll can specify classroom location and time of class in order to create parameters for check-in. This requires the student to be in attendance and for everything to be done automatically, easing the process while also making it more reliable. Core features will include:
• The ability of the student to check in using time and geolocation,
• The ability of the professor to upload class roll, location, and time,
• The option for students to check in automatically by uploading their class schedule or manually check in,
• The ability of the professor to manually check in students not using the app, and
• The ability of the professor to export the attendance records to Excel (via CVS format).

The goal of the project is to design a fully functional web app to be used by astronomers and stargazing hobbyists. The web app will feature a live feed of the night sky above Louisiana Tech, an image library of special events (e.g. shooting stars), a user rating system, and weather updates for Ruston, Louisiana. To achieve these features, an HD fisheye camera will be used to capture images and present a live feed; TensorFlow and a light sensor will be used to create and train a neural network to capture abnormal events. SQL will be used to manage databases that store images and user information; the DarkSky API will be used to pull weather data, and Flask (written in Python) will be used to build the web framework while using languages such as Jinja2, HTML 5, CSS 3, and JavaScript to build and design the website.

In a society that is as intertwined with technology as ours is, it is important that everyone has at least a basic understanding of cyber security and how to be safe online. The goal of this project is to teach the basic concepts of cyber security to kids through a game, so that they may be better prepared to navigate through the digital world. This game, which consists of a platformer and a series of mini-games, aims to teach concepts such as secure password creation, personally identifiable information, and secure communication. By playing this game, kids should learn about these concepts, along with others, and have a better understanding of how the internet at large operates.

csWherever is a foundation for an online learning environment for computer science concepts using Java, similar to the AP-CS course requirements. It will include a web-based GUI that includes space for students to code, an output window, and a window that will visualize what the variables and data structures are doing from the code. It will also collect a variety of user actions (e.g., mouse events, keyboard actions) to store in a database, which will later be used to provide feedback to the learner. If time allows, this framework will be further developed to provide lessons and coding practice for high school students and to analyze the data collected as feedback for the learner.

Today, game developers have three main options when choosing music for their games. They can choose to make an original soundtrack; they can pay artists directly for their music, or they can use free non-copyrighted music in their games. These options are either very expensive or entirely unsatisfying. In our project, we are giving game developers another option to consider when adding music to their games. Our project aims to connect the Spotify API with video games so that developers can use any music available on Spotify within their games. Games with this integration require that the players have a premium Spotify account and be logged in. When implemented properly, game developers can use Spotify’s extensive library of songs to create dynamic soundtracks that can change based on in-game events.

The purpose of our system is to track by GPS the employees of a company for accountability and safety. The application will be run on either iOS or Android phones. When the user logs in, the app will begin tracking the user’s location as they go to potential worksites and other errands. The application has the capability to turn off the tracking when the user goes on break and can be set to automatically stop tracking when the user clocks out. The data is sent to a secure database that can be monitored by an admin via a website. The website supports features to filter the data as well as the capability to create and edit users.

Our goal is to create a cross-platform mobile application (iOS and Android) that students at Louisiana Tech can use to submit reports of lost or found items to a database running on AWS. Additionally, the app will provide admin functionality such as viewing item reports and alerting users that an item of theirs has been found. Any user will be able to submit reports, while admins will need to securely log in to the app via a PIN.

Smart boards are expensive and not very common in the classroom. Our project will allow any projector/screen to become a smart board. By using the presenter’s own laptop camera, our project will track any laser pointer shined at the screen and dynamically draw lines over the displayed content. This allows the presenter to highlight text, circle important terminology, and otherwise annotate their displayed content by simply shining a laser pointer at the screen allowing our application to detect the laser pointer, drawing where the laser pointer goes. Our software can then clear out or save any annotations made. Our software aims to be cross platform and adapt to various types of laser pointers.

The goal of this project was to create a statistical model for predicting the outcome of college-level American football games. The software used to create this project includes React, NodeJS, ExpressJS, and mySQL. We made a website that has access to a database containing the data that creates our statistical model. The website also has three levels of users, with each user having a personal interface. Depending on the user’s level, they will have access to different actions and information. All users have access to a model displaying the odds of one team winning over another. With a higher level, a user will be allowed to alter certain factors for the model which could give a different statistical outcome to lower level users. This feature of allowing the end-user to modify factors within the model is not available in many models besides ours. Our model uses logistic regression, a method used in statistics to estimate the probability of an event occurring based on previous data, to predict the outcome of future games within the NCAA. Our model was inspired by a model created by Stephen Bouzianis of University of New Hampshire, Durham. His paper, “Predicting the Outcome of NFL Games Using Logistic Regression” details the model he invented.