Matching Items (7)

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A Science Communicator's Guide to Social Media Engagement

Description

The scientific research conducted by science, technology, engineering, and mathematics (STEM) institutions is groundbreaking. Everyday, scientists create a deeper understanding of the world around us, and then communicate that understanding

The scientific research conducted by science, technology, engineering, and mathematics (STEM) institutions is groundbreaking. Everyday, scientists create a deeper understanding of the world around us, and then communicate that understanding through journal papers, articles, and conferences. To strengthen these traditional forms of communication, science communicators can use social media platforms such as Twitter and Facebook to promote themselves and earn digital audience engagement that will grow the impact and success of their research. This thesis synthesizes research on human communication theories, digital user behavior, and science communication practices in order to create the “Science Communicator’s Guide to Social Media Engagement”. This guide empowers science communicators to utilize social media in a way that can increase their digital audience engagement, expand the reach of their research, and ultimately amplify their professional presence in the scientific community.

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Created

Date Created
  • 2020-12

Rock Traits from Machine Learning: Application to Rocky Fault Scarps

Description

Rock traits (grain size, shape, orientation) are fundamental indicators of geologic processes including geomorphology and active tectonics. Fault zone evolution, fault slip rates, and earthquake timing are informed by examinations

Rock traits (grain size, shape, orientation) are fundamental indicators of geologic processes including geomorphology and active tectonics. Fault zone evolution, fault slip rates, and earthquake timing are informed by examinations of discontinuities in the displacements of the Earth surface at fault scarps. Fault scarps indicate the structure of fault zones fans, relay ramps, and double faults, as well as the surface process response to the deformation and can thus indicate the activity of the fault zone and its potential hazard. “Rocky” fault scarps are unusual because they share characteristics of bedrock and alluvial fault scarps. The Volcanic Tablelands in Bishop, CA offer a natural laboratory with an array of rocky fault scarps. Machine learning mask-Region Convolutional Neural Network segments an orthophoto to identify individual particles along a specific rocky fault scarp. The resulting rock traits for thousands of particles along the scarp are used to develop conceptual models for rocky scarp geomorphology and evolution. In addition to rocky scarp classification, these tools may be useful in many sedimentary and volcanological applications for particle mapping and characterization.

Contributors

Agent

Created

Date Created
  • 2020

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Image Recognition Software Reveals Potential for Detection of Hypolith Colonization in the Namib Desert

Description

Drylands, though one of the largest biomes, are also one of the most understudied biomes on the planet. This leaves scientists with limited understanding of unique life forms that have

Drylands, though one of the largest biomes, are also one of the most understudied biomes on the planet. This leaves scientists with limited understanding of unique life forms that have adapted to live in these arid environments. One such life form is the hypolithic microbial community; these are autotrophic cyanobacteria colonies that can be found on the underside of translucent rocks in deserts. With the light that filters through the rock above them, the microbes can photosynthesize and fix carbon from the atmosphere into the soil. In this study I looked at hypolith-like rock distribution in the Namib Desert by using image recognition software. I trained a Mask R-CNN network to detect quartz rock in images from the Gobabeb site. When the method was analyzed using the entire data set, the distribution of rock sizes between the manual annotations and the network predictions was not similar. When evaluating rock sizes smaller than 0.56 cm2 the method showed statistical significance in support of being a promising data collection method. With more training and corrective effort on the network, this method shows promise to be an accurate and novel way to collect data efficiently in dryland research.

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Agent

Created

Date Created
  • 2021-05

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Lunar Rover Navigation: Impact of Illumination Conditions on AI and Human Perception of Crater Sizes

Description

When rover mission planners are laying out the path for their rover, they use a combination of stereo images and statistical and geological data in order to plot a course

When rover mission planners are laying out the path for their rover, they use a combination of stereo images and statistical and geological data in order to plot a course for the vehicle to follow for its mission. However, there is a lack of detailed images of the lunar surface that indicate the specific presence of hazards, such as craters, and the creation of such crater maps is time-consuming. There is also little known about how varying lighting conditions caused by the changing solar incidence angle affects perception as well. This paper addresses this issue by investigating how varying the incidence angle of the sun affects how well the human and AI can detect craters. It will also see how AI can accelerate the crater-mapping process, and how well it performs relative to a human annotating crater maps by hand. To accomplish this, several sets of images of the lunar surface were taken with varying incidence angles for the same spot and were annotated both by hand and by an AI. The results are observed, and then the AI performance was rated by calculating its resulting precision and recall, considering the human annotations as being the ground truth. It was found that there seems to be a maximum incidence angle for which detect rates are the highest, and that, at the moment, the AI’s detection of craters is poor, but it can be improved. With this, it can inform future and more expansive investigations into how lighting can affect the perception of hazards to rovers, as well as the role AI can play in creating these crater maps.

Contributors

Agent

Created

Date Created
  • 2021-05

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Coordinated Navigation and Localization of an Autonomous Underwater Vehicle Using an Autonomous Surface Vehicle in the OpenUAV Simulation Framework

Description

The need for incorporating game engines into robotics tools becomes increasingly crucial as their graphics continue to become more photorealistic. This thesis presents a simulation framework, referred to as OpenUAV,

The need for incorporating game engines into robotics tools becomes increasingly crucial as their graphics continue to become more photorealistic. This thesis presents a simulation framework, referred to as OpenUAV, that addresses cloud simulation and photorealism challenges in academic and research goals. In this work, OpenUAV is used to create a simulation of an autonomous underwater vehicle (AUV) closely following a moving autonomous surface vehicle (ASV) in an underwater coral reef environment. It incorporates the Unity3D game engine and the robotics software Gazebo to take advantage of Unity3D's perception and Gazebo's physics simulation. The software is developed as a containerized solution that is deployable on cloud and on-premise systems.

This method of utilizing Gazebo's physics and Unity3D perception is evaluated for a team of marine vehicles (an AUV and an ASV) in a coral reef environment. A coordinated navigation and localization module is presented that allows the AUV to follow the path of the ASV. A fiducial marker underneath the ASV facilitates pose estimation of the AUV, and the pose estimates are filtered using the known dynamical system model of both vehicles for better localization. This thesis also investigates different fiducial markers and their detection rates in this Unity3D underwater environment. The limitations and capabilities of this Unity3D perception and Gazebo physics approach are examined.

Contributors

Agent

Created

Date Created
  • 2020

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Design, Development, and Modeling, of a Novel Underwater Vehicle for Autonomous Reef Monitoring

Description

A novel underwater, open source, and configurable vehicle that mimics and leverages advances in quad-copter controls and dynamics, called the uDrone, was designed, built and tested. This vehicle was developed

A novel underwater, open source, and configurable vehicle that mimics and leverages advances in quad-copter controls and dynamics, called the uDrone, was designed, built and tested. This vehicle was developed to aid coral reef researchers in collecting underwater spectroscopic data for the purpose of monitoring coral reef health. It is designed with an on-board integrated sensor system to support both automated navigation in close proximity to reefs and environmental observation. Additionally, the vehicle can serve as a testbed for future research in the realm of programming for autonomous underwater navigation and data collection, given the open-source simulation and software environment in which it was developed. This thesis presents the motivation for and design components of the new vehicle, a model governing vehicle dynamics, and the results of two proof-of-concept simulation for automated control.

Contributors

Agent

Created

Date Created
  • 2020

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Environment Sensor Coverage using Multi-Agent Headings

Description

This work describes an approach for distance computation between agents in a

multi-agent swarm. Unlike other approaches, this work relies solely on signal Angleof-

Arrival (AoA) data and local trajectory data. Each

This work describes an approach for distance computation between agents in a

multi-agent swarm. Unlike other approaches, this work relies solely on signal Angleof-

Arrival (AoA) data and local trajectory data. Each agent in the swarm is able

to discretely determine distance and bearing to every other neighbor agent in the

swarm. From this information, I propose a lightweight method for sensor coverage

of an unknown area based on the work of Sameera Poduri. I also show that this

technique performs well with limited calibration distances.

Contributors

Agent

Created

Date Created
  • 2020