Engineering Commons^™

Iot Garden Frost Alarm, Andrew James

Honors Theses

Home gardeners are faced with yearly challenges due to spring frosts harming young plants. This is frequently mitigated by covering crops with frost blankets, but only on nights when a frost is predicted. In areas with less predictable climate, an unexpected frost can kill vulnerable plants, reducing the amount of food produced. A system is proposed and designed here to use internet of things (IoT) technology to enable a small weather station in the home garden to report current climate data and predict frosts, then alert the gardener in time for them to cover their plants.

The system as designed …

Human Facial Emotion Recognition System In A Real-Time, Mobile Setting, Claire Williamson

Honors Theses

The purpose of this project was to implement a human facial emotion recognition system in a real-time, mobile setting. There are many aspects of daily life that can be improved with a system like this, like security, technology and safety.

There were three main design requirements for this project. The first was to get an accuracy rate of 70%, which must remain consistent for people with various distinguishing facial features. The second goal was to have one execution of the system take no longer than half of a second to keep it as close to real time as possible. Lastly, …

Exploring The Behavior Repertoire Of A Wireless Vibrationally Actuated Tensegrity Robot, Zongliang Ji

Honors Theses

Soft robotics is an emerging field of research due to its potential to explore and operate in unstructured, rugged, and dynamic environments. However, the properties that make soft robots compelling also make them difficult to robustly control. Here at Union, we developed the world’s first wireless soft tensegrity robot. The goal of my thesis is to explore effective and efficient methods to explore the diverse behavior our tensegrity robot. We will achieve that by applying state-of-art machine learning technique and a novelty search algorithm.

2018 Ieee Signal Processing Cup: Forensic Camera Model Identification Challenge, Michael Geiger

Honors Theses

The goal of this Senior Capstone Project was to lead Union College’s first ever Signal Processing Cup Team to compete in IEEE’s 2018 Signal Processing Cup Competition. This year’s competition was a forensic camera model identification challenge and was divided into two separate stages of competition: Open Competition and Final Competition. Participation in the Open Competition was open to any teams of undergraduate students, but the Final Competition was only open to the three finalists from Open Competition and is scheduled to be held at ICASSP 2018 in Calgary, Alberta, Canada. Teams that make it to the Final Competition will …

A Graph Based Departmental Spoken Dialogue System, Julia Isaac

Honors Theses

Spoken dialogue systems are automatic, computer based systems that are a great way for people to receive important information. In this project, I created a spoken dialogue system that people can use to learn about the Computer Science Department at Union College. The system was built by populating an open source dialogue system using a graph based dialogue manager. I improved upon a previous working dialogue system by making the conversations sound more natural, improving the flexibility of the system and making the system more robust. To help with this process a corpus was created using about 200 different dialogues …

Classifying System Call Traces Using Anomalous Detection, William Doyle

Honors Theses

We used data mining techniques to detect intrusions among system call traces and have outlined our results. Recent work at the intersection of security and machine learning has lead to better understanding of anomalous intrusion detection. There is a need to more thoroughly understand how anomaly detection can be used because of its potential applications and advantages over current standard methods. In this thesis, we report on a new approach of anomalous detection using system call traces. Our goal is to be able to create a system that can accurately detect hacking attacks by analyzing the sequences of system calls …

Evolving Soft Robots With Vibration Based Movement, Andrew Danise

Honors Theses

Creating effective designs for soft robots is extremely difficult due to the large number of different possibilities for shape, material properties, and movement mechanisms. Due to the lack of methods to design soft robots, previous research has used evolutionary algorithms to tackle this problem of overwhelming options. A popular technique is to use generative encodings to create designs using evolutionary algorithms because of their modularity and ability to induce large scale coordinated change. The main drawback of generative encodings is that it is difficult to know where along the ontogenic trajectory resides the phenotype with the highest fitness. The two …