Engineering Commons^™

Flight Simulator Modeling Using Recurrent Neural Networks, Nickolas Sabatini, Andreas Natsis

Undergraduate Research & Mentoring Program

Recurrent neural networks (RNNs) are a form of machine learning used to predict future values. This project uses RNNs tor predict future values for a flight simulator. Coded in Python using the Keras library, the model demonstrates training loss and validation loss, referring to the error when training the model.

From Inductive To Deductive Learning, Mikhail Mayers, Brian Henson

Undergraduate Research & Mentoring Program

Using Machine Vision as a way to give information to Prolog. Using Prolog to solve deductive problems and analogical problems without having to manually enter all facts and information.

An Exploration Of Software Defined Radio And Gnu Radio Companion For Use In Drone-To-Drone Communication, Amanda K. H. Voegtlin

Undergraduate Research & Mentoring Program

In a world that increasingly relies on automation and intelligent robotics, there is a need for drones to expand their independence and adaptability in navigating their environments. One approach to this problem is the use of wireless communication between units in order to coordinate their sensor data and build real-time maps of the environments they are navigating. However, especially indoors, relying on a fixed transmission tower to provide data to the units faces connectivity challenges.

The purpose of this research was to determine the fitness of an on-drone assembly that uses the the NI B200mini software-defined radio board and Gnu …

Improvement Of 802.11 Protocol On Fully Programmable Wireless Radio, Eunji Lee

Undergraduate Research & Mentoring Program

The growth in the number of connected device usage has led to a rapidly increased data traffic on wireless network and the demand for access to high speed and stable Internet connection is becoming more prominent. However, current off the shelf wireless cards are not programmable or observable across layers of the standard protocol stack, which leads to poor practical performance. Thus, Wireless Open Access Research Platform (WARP), a scalable wireless platform providing programmable functionality at every layer of the network stack, has been used for the real-time implementation and improvement of 802.11 protocol.

An Analysis Of Lora Low Power Technology And Its Applications, Gomathy Venkata Krishnan

Undergraduate Research & Mentoring Program

The number of Internet of Things (IoT) devices has exponentially increased in the last decade. With the increase in these devices, there is a necessity to effectively connect and control these devices remotely. Cellular technologies cannot handle this demand since they are not cost effective and easy to deploy. This is where LoRa technology comes handy. LoRa is long-range, low-power, low cost technology that supports internet of things applications. LoRa has many advantages in terms of capacity, mobility, battery lifetime and cost. It uses the unlicensed 915MHz ISM band and can be easily deployed.

This research is focused on setting …

Improving Quality Of Patient Care Through Automated Nerve Segmentation, Madisen D. Phillips

Undergraduate Research & Mentoring Program

A continuous peripheral nerve block cPNB is most commonly used in patients during the post-operative period, with documented benefits that include a decrease in reported pain, a decrease of opioid related side effects, and an increase in patient satisfaction. Accurately identifying nerve structures for cPNB placement is a critical step for proper insertion. The aim of this research is to use supervised learning techniques (least squares regression and Receiver Operating Characteristic (ROC) curve analysis) to build a model that can segment and annotate a bundle of nerves known as the brachial plexus (BP) while minimizing segmentation error. Dependent on large …

Design And Test Of 3d Printed Lenses For Sub-Thz Radiation, Justin Patterson

Undergraduate Research & Mentoring Program

The terahertz gap in the electromagnetic spectrum provides promising advantages for applications such as increased airport security and medical diagnosis. Quasi-optical systems used to study THz radiation require multiple mirrors or lenses, which can be quite costly. In order to manipulate THz beams we investigated production of inexpensive lenses using additive 3D printing. 3D printing technology promises to be not only accessible and inexpensive, but should also enable quick experimentation with different lens designs. The Picometrix time-domain spectroscopy (TDS) system was used to characterize 3D printable plastics. The absorption coefficient and refractive index were analyzed from 0.2 to 2 THz …

3d Fpga Cell Matrix By Self-Assembly, Jeffrey Udall

Undergraduate Research & Mentoring Program

Physical size limitations in miniaturizing two-dimensional (2D) transistors are becoming more difficult to overcome. In order to continue increasing the processing power of electronic circuits, new design paradigms are needed. Three-dimensional (3D) architectures provide a solution to this issue and are currently being implemented via wafer stacking. However, more significant gains in terms of packing and speed can be achieved by CMOS components with truly integrated 3D cellular architectures. One of these is the Cell Matrix, a self-configurable defect- and fault-tolerant architecture, which is ideally suited for ultra large-scale integration. For this project, we worked to expand the Cell Matrix …

Sparse Adaptive Local Machine Learning Algorithms For Sensing And Analytics, Jack Cannon

Undergraduate Research & Mentoring Program

The goal of digital image processing is to capture, transmit, and display images as efficiently as possible. Such tasks are computationally intensive because an image is digitally represented by large amounts of data. It is possible to render an image by reconstructing it with a subset of the most relevant data. One such procedure used to accomplish this task is commonly referred to as sparse coding. For our purpose, we use images of handwritten digits that are presented to an artificial neural network. The network implements Rozell's locally competitive algorithm (LCA) to generate a sparse code. This sparse code is …