Anomaly Mining and Visualization of Autonomous Aerial Vehicles

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Description
The drone industry is worth nearly 50 billion dollars in the public sector, and drone flight anomalies can cost up to 12 million dollars per drone. The project's objective is to explore various machine-learning techniques to identify anomalies in drone…

The drone industry is worth nearly 50 billion dollars in the public sector, and drone flight anomalies can cost up to 12 million dollars per drone. The project's objective is to explore various machine-learning techniques to identify anomalies in drone flight and express these anomalies effectively by creating relevant visualizations. The research goal is to solve the problem of finding anomalies inside drones to determine severity levels. The solution was visualization and statistical models, and the contribution was visualizations, patterns, models, and the interface.
Date Created
2022
Agent

Assessing Exhibit Interaction Through Bridging the Connections Between Biometrics and Traditional Tools

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Description

Engaging users is essential for designers of any exhibit, such as the human-computer interface, the visual effects, or the informational content. The need to understand users’ experiences and learning gains has motivated a focus on user engagement across computer science.…

Engaging users is essential for designers of any exhibit, such as the human-computer interface, the visual effects, or the informational content. The need to understand users’ experiences and learning gains has motivated a focus on user engagement across computer science. However, there has been limited review of how human-computer interaction research interprets and employs the concepts in museum and exhibit settings, specifically their joint effects. The purpose of this study is to assess users’ experience and learning outcome, while interacting with a web application part of an exhibit that showcases the NASA Psyche spacecraft model. This web application provides an interactive menu that allows the user to navigate on the touch panel installed within the Psyche Spacecraft Exhibit. The user can press the button on the menu which will light up the corresponding parts of the model with a detailed description displayed on the panel. For this study, participants were required to take a questionnaire, a pretest, and a posttest. They were also required to interact with the web application while wearing an Emotiv EPOC+ EEG headset that measures their emotions while they were visiting the exhibit. During the study, data such as questionnaire results, sensed emotions from the EEG headset, and pretest and posttest scores were collected. Using the information gathered, the study explores user experience and learning gains through both biometrics and traditional tools. The findings show that users felt engaged and frustrated the most and that users gained more knowledge but at varying degrees from the interaction. Future work can be done to lower the levels of frustration and keep learning gains at a more consistent rate by improving the exhibit design to better meet various learning needs and visitor profiles.

Date Created
2022-05
Agent

Lossless Data Compression by Representing Data as a Solution to the Diophantine Equations

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Description
There has been a substantial development in the field of data transmission in the last two decades. One does not have to wait much for a high-definition video to load on the systems anymore. Data compression is one of the…

There has been a substantial development in the field of data transmission in the last two decades. One does not have to wait much for a high-definition video to load on the systems anymore. Data compression is one of the most important technologies that helped achieve this seamless data transmission experience. It helps to store or send more data using less memory or network resources. However, it appears that there is a limit on the amount of compression that can be achieved with the existing lossless data compression techniques because they rely on the frequency of characters or set of characters in the data. The thesis proposes a lossless data compression technique in which the data is compressed by representing it as a set of parameters that can reproduce the original data without any loss when given to the corresponding mathematical equation. The mathematical equation used in the thesis is the sum of the first N terms in a geometric series. Various changes are made to this mathematical equation so that any given data can be compressed and decompressed. According to the proposed technique, the whole data is taken as a single decimal number and replaced with one of the terms of the used equation. All the other terms of the equation are computed and stored as a compressed file. The performance of the developed technique is evaluated in terms of compression ratio, compression time and decompression time. The evaluation metrics are then compared with the other existing techniques of the same domain.
Date Created
2021
Agent

Intelli-Trail

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Description
Intelli-Trail is a game where the player plays as a small blue man with the simple goal of reaching the purple door. The player will primarily interact with the game through combat. The game itself will react to…

Intelli-Trail is a game where the player plays as a small blue man with the simple goal of reaching the purple door. The player will primarily interact with the game through combat. The game itself will react to the patterns in the players behavior to progressively become harder for the player to win.
Date Created
2020-05
Agent

Interactive Traffic Simulation

Description
This document explains the design of a traffic simulator based on an integral-based state machine. This simulator is different from existing traffic simulators because it is driven by a flexible model that supports many different light configurations and has a user-friendly interface.
Date Created
2020-05
Agent

Examining and Evaluating the Window of Intervention in Autonomous Vehicles

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Description
As autonomous vehicle development rapidly accelerates, it is important to not lose sight of what the worst case scenario is during the drive of an autonomous vehicle. Autonomous vehicles are not perfect, and will not be perfect for the foreseeable…

As autonomous vehicle development rapidly accelerates, it is important to not lose sight of what the worst case scenario is during the drive of an autonomous vehicle. Autonomous vehicles are not perfect, and will not be perfect for the foreseeable future. These vehicles will shift the responsibility of driving to the passenger in front of the wheel, regardless if said passenger is prepared to do so. However, by studying the human reaction to an autonomous vehicle crash, researchers can mitigate the risk to the passengers in an autonomous vehicle. Located on the ASU Polytechnic campus, there is a car simulation lab, or SIM lab, that enables users to create and simulate various driving scenarios using the Drive Safety and HyperDrive software. Using this simulator and the Window of Intervention, the time a driver has to avoid a crash, vital research into human reaction time while in an autonomous environment can be safely performed. Understanding the Window of Intervention is critical to the development of solutions that can accurately and efficiently help a human driver. After first describing the simulator and its operation in depth, a deeper look will be offered into the autonomous vehicle field, followed by an in-depth explanation into the Window of Intervention and how it is studied and an experiment that looks to study both the Window of Intervention and human reactions to certain events. Finally, additional insight from one of the authors of this paper will be given documenting their contributions to the study as a whole and their concerns about using the simulator for further research.
Date Created
2020-05
Agent

All Purpose Textual Data Information Extraction, Visualization and Querying

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Description
Since the advent of the internet and even more after social media platforms, the explosive growth of textual data and its availability has made analysis a tedious task. Information extraction systems are available but are generally too specific and often…

Since the advent of the internet and even more after social media platforms, the explosive growth of textual data and its availability has made analysis a tedious task. Information extraction systems are available but are generally too specific and often only extract certain kinds of information they deem necessary and extraction worthy. Using data visualization theory and fast, interactive querying methods, leaving out information might not really be necessary. This thesis explores textual data visualization techniques, intuitive querying, and a novel approach to all-purpose textual information extraction to encode large text corpus to improve human understanding of the information present in textual data.

This thesis presents a modified traversal algorithm on dependency parse output of text to extract all subject predicate object pairs from text while ensuring that no information is missed out. To support full scale, all-purpose information extraction from large text corpuses, a data preprocessing pipeline is recommended to be used before the extraction is run. The output format is designed specifically to fit on a node-edge-node model and form the building blocks of a network which makes understanding of the text and querying of information from corpus quick and intuitive. It attempts to reduce reading time and enhancing understanding of the text using interactive graph and timeline.
Date Created
2018
Agent
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