Physical Sciences and Mathematics Commons^™

Using Machine Learning Models To Discover Promising Research, Akhil Pandey Akella

Graduate Research Theses & Dissertations

Endeavors to identify valuable research involve the factors of discovery, comprehensibility, and reproducibility. The purpose of this study is to assist scholars in finding research that is both promising and of high quality. I explain how we can approach the problem of reproducibility in relation to scholarly articles and propose gauging the public understanding of science as a way to determine the comprehensibility of given research articles. Additionally, I explain how the concept of long-term social media impact supports the discovery of scholarly articles likely to be impactful even with the passage of time. I build and describe machine-learning models …

Sky Surveys Scheduling Using Reinforcement Learning, Andres Felipe Alba Hernandez

Graduate Research Theses & Dissertations

Modern cosmic sky surveys (e.g., CMB S4, DES, LSST) collect a complex diversity of astronomical objects. Each of class of objects presents different requirements for observation time and sensitivity. For determining the best sequence of exposures for mapping the sky systematically, conventional scheduling methods do not optimize the use of survey time and resources. Dynamic sky survey scheduling is an NP-hard problem that has been therefore treated primarily with heuristic methods. We present an alternative scheduling method based on reinforcement learning (RL) that aims to optimize the use of telescope resources for scheduling sky surveys.

We present an exploration of …

A Review Of Reasons For Failure In Applying Machine Learning To Financial Trading And An Experiment Investigating Combinatorial Purged Cross Validation’S Merit In Preventing The Most Prominent Of These Reasons, Multiple Testing Bias, Colin Fritz

Graduate Research Theses & Dissertations

The interest in applying machine learning to financial trading in the hedge fund industry has exploded in the last five years due to the massive success of a handful of ‘quantitative’ investment firms like Renaissance Technologies who has pioneered the use of machine learning techniques in investment since the 1980s. The failure rate of such firms attempting to deploy financial machine learning strategies is very high. This thesis reviews many of the causes for failure such as harmful correlations between examples in the dataset, redundant observations, improper data sampling paradigm, and multiple testing bias. Of these, multiple testing bias is …

Simulating And Modelling Opinion Dynamics, Jennifer Heermance

Graduate Research Theses & Dissertations

The foundation of social media is conversation. Social media allows people to share ideas and opinions, as well as discuss those opinions. A point of intrigue for many social scientists is how those opinions change through interaction with others. What influences someone’s opinion? When is a person willing to adapt their opinion, and when does it remain the same? Is it possible to measure these opinion dynamics? Our overall goal is to develop a more comprehensive model for opinion dynamics. The first step of this process is to simulate data that can then be analyzed and used to develop a …

Using Reinforcement Learning In A Simulated Intelligent Tutoring System, Manohar Sai Jasti

Graduate Research Theses & Dissertations

I used reinforcement learning to investigate which categories of hints are most efficient in an intelligent tutoring system for human anatomy. Efficiency is defined as minimizing the time it takes the student to learn the material. When a student gives a wrong answer, the tutor can give them a text hint, a diagrammatic hint, or a video clip. Each type of hint takes a different amount of time to deliver and takes the student a different amount of time to understand.

I built a simulator for the intelligent tutoring system to collect data from simulated students. I implemented reinforcement learning, …

A Survey Of Big Data Tools And Technologies, Mrinal Kanti Roy

Graduate Research Theses & Dissertations

Big data analytics require the use of different sets of tools and technologies. This thesis categorizes big data analytics in three areas: storage, processing, and visualization and provides discussions of available tools and technologies for each area. It also provides a hands-on review of available tools and review of relevant research papers for such tools and technologies. The goal of this thesis is to summarize and organize current big data tools and technologies by surveying recent research papers, provide a synthesis and discuss observation current issues and future trends.

Visualization Of Large Time-Dependent Multidimensional Datasets Using Information Dashboards, Ankita Upadhyay

Graduate Research Theses & Dissertations

Visual summarization is the act of displaying the most important information in a single

view or on a single screen. There are many existing powerful and useful information visualization tools and techniques to visualize large datasets, but the major challenge in using

these visualization tools efficiently are assessing what is needed to create awareness,

where awareness is dependent on the situation and context of the user and surrounding

events.

For example, when a user is driving (context) and approaching an intersection (situation)

the traffic light being red creates an awareness that the driver needs to stop, or when a fire …

Exploring Cyber-Physical Systems, Misbah Uddin Mohammed

Graduate Research Theses & Dissertations

The advances in IOT, Computer Vision, AI and Machine Learning have made these technologies ubiquitous to our daily lives. From Smart Phones to Connected Vehicles, Cyber Physical systems have been interspersed into everything we interact in today’s world. The aim or this thesis was to explore these advances in Cyber Physical Systems and analyze the different sectors they were affecting. We then hand-picked certain domains and explored further by carrying out practical projects using some of the latest software and hardware resources available. Technologies like Amazon Alexa services, NVIDIA Jetson boards, TensorFlow, OpenCV, NodeJS were heavily employed in our various …