Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 5 of 5
Full-Text Articles in Engineering
Project Khepri: Mining Asteroid Bennu For Water, Erika Frost, Gowtham Boyala, Adam Gremm, Ahmet Gungor, Amirhossein Taghipour, Massimo Biella, Jiawei "Jackson" Qiu, Athip Thirupathi Raj, Arjun Chhabra, Adam Gee, Saanjali Maharaj, Erin Richardson, Julia Empey, Haidar Ali Abdul-Nabi, Lindsay Richards, Ariyaan Talukder, Aaron Groh, Brie Miklaucic, Jd Carlson, Kristina Kim, Maverick Cue
Project Khepri: Mining Asteroid Bennu For Water, Erika Frost, Gowtham Boyala, Adam Gremm, Ahmet Gungor, Amirhossein Taghipour, Massimo Biella, Jiawei "Jackson" Qiu, Athip Thirupathi Raj, Arjun Chhabra, Adam Gee, Saanjali Maharaj, Erin Richardson, Julia Empey, Haidar Ali Abdul-Nabi, Lindsay Richards, Ariyaan Talukder, Aaron Groh, Brie Miklaucic, Jd Carlson, Kristina Kim, Maverick Cue
Undergraduate Student Research Internships Conference
Deep space asteroid mining presents the opportunity for the collection of critical resources required to establish a cis-lunar infrastructure. In specific, the Project Khepri team has focused on the collection of water from asteroid Bennu. This water has the potential to provide a source of clean-energy propellant as well as an essential consumable for humans or agriculture on crewed trips to the Moon or Mars. This would avoid the high costs of launching from Earth - making it a highly desirable element for the future of cis-lunar infrastructure. The OSIRIS-REx mission provided a complete survey of asteroid Bennu and is …
Introduction To Pub/Sub Systems Using Opcua, Mete Isiksalan
Introduction To Pub/Sub Systems Using Opcua, Mete Isiksalan
Undergraduate Student Research Internships Conference
The purpose of the project was to learn and implement the fundamental basics of OPCUA system architecture using pub/sub systems. The system allows the users to create multiple different publishers and subscribers while accessing data from a local server and a primary HTTP server. The system is designed to be a multi-client and multi-server system to simulate real-life scenarios while having two different sources of generated values to send via sockets in OPCUA protocols, multiple different APIs were used for the clients on how they retrieve data as well.
Triple-Motor Driver For Hand Simulator, Yamaan Bakir
Triple-Motor Driver For Hand Simulator, Yamaan Bakir
Undergraduate Student Research Internships Conference
No abstract provided.
Data Preprocessing For Machine Learning Modules, Rawan El Moghrabi
Data Preprocessing For Machine Learning Modules, Rawan El Moghrabi
Undergraduate Student Research Internships Conference
Data preprocessing is an essential step when building machine learning solutions. It significantly impacts the success of machine learning modules and the output of these algorithms. Typically, data preprocessing is made-up of data sanitization, feature engineering, normalization, and transformation. This paper outlines the data preprocessing methodology implemented for a data-driven predictive maintenance solution. The above-mentioned project entails acquiring historical electrical data from industrial assets and creating a health index indicating each asset's remaining useful life. This solution is built using machine learning algorithms and requires several data processing steps to increase the solution's accuracy and efficiency. In this project, the …
Credit Card Fraud Detection, Charles Wang
Credit Card Fraud Detection, Charles Wang
Undergraduate Student Research Internships Conference
In recent years, credit card fraud poses a significant threat to banks and customers financially over the world. However, in the banking industry, to counter this issue, machine learning algorithms has become a growing trend to put proactive intervention of credit card fraud in place. In this project, we are going to detect fraudulent credit card transactions with machine learning models. This data set includes 284807 credit card transactions of European cardholders over a period of two days with their personal information kept anonymous. Among all transactions, 492 were fraudulent.