Engineering Commons^™

An Application Of Clustering And Cluster Update Methods To Boiler Sensor Prediction And Case-Based-Reasoning To Boiler Repair, Timothy Edward Rooney

Theses and Dissertations

Driven by demand from both consumers and manufacturers alike, Internet of Things (IoT)

capabilities are being built into more products. Consumers want more control and access to their

devices, while manufacturers can find data gathered from IoT-capable products invaluable. In

this thesis, we use data from a growing fleet of IoT-connected boilers in the residential, lightcommercial, and medium-commercial ranges to demonstrate a framework for cluster initialization

and updating. We compare two methods of dynamically updating clusters: a sequential method

inspired by sequential K-means clustering and a cohesion-based method called DYNC. A predictive

artificial neural network system demonstrates the effectiveness of …

A Machine Learning Approach To Predicting Alcohol Consumption In Adolescents From Historical Text Messaging Data, Adrienne Bergh

Computational and Data Sciences (MS) Theses

Techniques based on artificial neural networks represent the current state-of-the-art in machine learning due to the availability of improved hardware and large data sets. Here we employ doc2vec, an unsupervised neural network, to capture the semantic content of text messages sent by adolescents during high school, and encode this semantic content as numeric vectors. These vectors effectively condense the text message data into highly leverageable inputs to a logistic regression classifier in a matter of hours, as compared to the tedious and often quite lengthy task of manually coding data. Using our machine learning approach, we are able to train …

Framework For Validation Of Different Media Types Using A Model Based On Consensus, Adilahmed Patel

All ETDs from UAB

Increasingly people of all ages consume news and entertainment through electronic media and social media [1]. As the internet in general and social media in particular are a recent phenomenon, the laws governing them and the technologies to monitor them are still evolving. There is a general consensus on the ubiquity and power of these media, hence the worry of how to handle these media. In this context, validating the online content becomes of paramount importance. Fighting fake content is not only relevant to news and current affairs but is very useful in other areas like technical content, legal content …