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Articles 1 - 16 of 16
Full-Text Articles in Physical Sciences and Mathematics
Eelgrass (Zostera Marina) Population Decline In Morro Bay, Ca: A Meta-Analysis Of Herbicide Application In San Luis Obispo County And Morro Bay Watershed, Tyler King Sinnott
Eelgrass (Zostera Marina) Population Decline In Morro Bay, Ca: A Meta-Analysis Of Herbicide Application In San Luis Obispo County And Morro Bay Watershed, Tyler King Sinnott
Master's Theses
The endemic eelgrass (Zostera marina) community of Morro Bay Estuary, located on the central coast of California, has experienced an estimated decline of 95% in occupied area (reduction of 344 acres to 20 acres) from 2008 to 2017 for reasons that are not yet definitively clear. One possible driver of degradation that has yet to be investigated is the role of herbicides from agricultural fields in the watershed that feeds into the estuary. Thus, the primary research goal of this project was to better understand temporal and spatial trends of herbicide use within the context of San Luis …
Dataset And Evaluation Of Self-Supervised Learning For Panoramic Depth Estimation, Ryan Nett
Dataset And Evaluation Of Self-Supervised Learning For Panoramic Depth Estimation, Ryan Nett
Master's Theses
Depth detection is a very common computer vision problem. It shows up primarily in robotics, automation, or 3D visualization domains, as it is essential for converting images to point clouds. One of the poster child applications is self driving cars. Currently, the best methods for depth detection are either very expensive, like LIDAR, or require precise calibration, like stereo cameras. These costs have given rise to attempts to detect depth from a monocular camera (a single camera). While this is possible, it is harder than LIDAR or stereo methods since depth can't be measured from monocular images, it has to …
Envrment: Investigating Experience In A Virtual User-Composed Environment, Matthew Key
Envrment: Investigating Experience In A Virtual User-Composed Environment, Matthew Key
Master's Theses
Virtual Reality is a technology that has long held society's interest, but has only recently began to reach a critical mass of everyday consumers. The idea of modern VR can be traced back decades, but because of the limitations of the technology (both hardware and software), we are only now exploring its potential. At present, VR can be used for tele-surgery, PTSD therapy, social training, professional meetings, conferences, and much more. It is no longer just an expensive gimmick to go on a momentary field trip; it is a tool, and as with the automobile, personal computer, and smartphone, it …
Attentional Parsing Networks, Marcus Karr
Attentional Parsing Networks, Marcus Karr
Master's Theses
Convolutional neural networks (CNNs) have dominated the computer vision field since the early 2010s, when deep learning largely replaced previous approaches like hand-crafted feature engineering and hierarchical image parsing. Meanwhile transformer architectures have attained preeminence in natural language processing, and have even begun to supplant CNNs as the state of the art for some computer vision tasks.
This study proposes a novel transformer-based architecture, the attentional parsing network, that reconciles the deep learning and hierarchical image parsing approaches to computer vision. We recast unsupervised image representation as a sequence-to-sequence translation problem where image patches are mapped to successive layers …
Predicting Personality Type From Writing Style, Tanay Gottigundala
Predicting Personality Type From Writing Style, Tanay Gottigundala
Master's Theses
The study of personality types gained traction in the early 20th century, when Carl Jung's theory of psychological types attempted to categorize individual differences into the first modern personality typology. Iterating on Jung's theories, the Myers-Briggs Type Indicator (MBTI) tried to categorize each individual into one of sixteen types, with the theory that an individual's personality type manifests in virtually all aspects of their life. This study explores the relationship between an individual's MBTI type and various aspects of their writing style. Using a MBTI-labeled dataset of user posts on a personality forum, three ensemble classifiers were created to predict …
An Application Of The Unscented Kalman Filter For Spacecraft Attitude Estimation On Real And Simulated Light Curve Data, Kent A. Rush
An Application Of The Unscented Kalman Filter For Spacecraft Attitude Estimation On Real And Simulated Light Curve Data, Kent A. Rush
Master's Theses
In the past, analyses of lightcurve data have been applied to asteroids in order to determine their axis of rotation, rotation rate and other parameters. In recent decades, these analyses have begun to be applied in the domain of Earth orbiting spacecraft. Due to the complex geometry of spacecraft and the wide variety of parameters that can influence the way in which they reflect light, these analyses require more complex assumptions and a greater knowledge about the object being studied. Previous investigations have shown success in extracting attitude parameters from unresolved spacecraft using simulated data. This paper presents a focused …
Free Space Detection And Trajectory Planning For Autonomous Robot, Zachary Ross Winger
Free Space Detection And Trajectory Planning For Autonomous Robot, Zachary Ross Winger
Computer Science and Software Engineering
Autonomous robots need to know what is around them and where it is safe for them to move to. Because having this ability is so important, Dr. Seng and myself have created a model to predict the free space in front of his autonomous robot, Herbie. We then use this prediction to enforce a driving policy to ensure Herbie drives around safely.
Design And Implementation Of A Deterministic And Nondeterministic Finite Automaton Simulator, Camron C. Dennler
Design And Implementation Of A Deterministic And Nondeterministic Finite Automaton Simulator, Camron C. Dennler
Computer Science and Software Engineering
The purpose of this project is to assist students in visualizing and understanding the structure and operation of deterministic and nondeterministic finite automata. This software achieves this purpose by providing students with the ability to build, modify, and test automata in an intuitive environment. This enables a simple and efficient avenue for experimentation, which upholds the Cal Poly ideal of Learning by Doing.
Readers of this report should be familiar with basic concepts in the theory of finite state machines; a general understanding of object-oriented programming is also necessary.
Attacking Computer Vision Models Using Occlusion Analysis To Create Physically Robust Adversarial Images, Jacobsen Loh
Attacking Computer Vision Models Using Occlusion Analysis To Create Physically Robust Adversarial Images, Jacobsen Loh
Master's Theses
Self-driving cars rely on their sense of sight to function effectively in chaotic and uncontrolled environments. Thanks to recent developments in computer vision, specifically convolutional neural networks, autonomous vehicles have developed the ability to see at or above human-level capabilities, which in turn has allowed for rapid advances in self-driving cars. Unfortunately, much like humans being confused by simple optical illusions, convolutional neural networks are susceptible to simple adversarial inputs. As there is no overlap between the optical illusions that fool humans and the adversarial examples that threaten convolutional neural networks, little is understood as to why these adversarial examples …
Quantum Random Walk Search And Grover's Algorithm - An Introduction And Neutral-Atom Approach, Anna Maria Houk
Quantum Random Walk Search And Grover's Algorithm - An Introduction And Neutral-Atom Approach, Anna Maria Houk
Physics
In the sub-field of quantum algorithms, physicists and computer scientist take classical computing algorithms and principles and see if there is a more efficient or faster approach implementable on a quantum computer, i.e. a ”quantum advantage”. We take random walks, a widely applicable group of classical algorithms, and move them into the quantum computing paradigm. Additionally, an introduction to a popular quantum search algorithm called Grover’s search is included to guide the reader to the development of a quantum search algorithm using quantum random walks. To close the gap between algorithm and hardware, we will look at using neutral-atom (also …
Towards Security And Privacy In Networked Medical Devices And Electronic Healthcare Systems, Isabel Jellen
Towards Security And Privacy In Networked Medical Devices And Electronic Healthcare Systems, Isabel Jellen
Master's Theses
E-health is a growing eld which utilizes wireless sensor networks to enable access to effective and efficient healthcare services and provide patient monitoring to enable early detection and treatment of health conditions. Due to the proliferation of e-health systems, security and privacy have become critical issues in preventing data falsification, unauthorized access to the system, or eavesdropping on sensitive health data. Furthermore, due to the intrinsic limitations of many wireless medical devices, including low power and limited computational resources, security and device performance can be difficult to balance. Therefore, many current networked medical devices operate without basic security services such …
Writing For Each Other: Dynamic Quest Generation Using In Session Player Behaviors In Mmorpg, Sean Christopher Mendonca
Writing For Each Other: Dynamic Quest Generation Using In Session Player Behaviors In Mmorpg, Sean Christopher Mendonca
Master's Theses
Role-playing games (RPGs) rely on interesting and varied experiences to maintain player attention. These experiences are often provided through quests, which give players tasks that are used to advance stories or events unfolding in the game. Traditional quests in video games require very specific conditions to be met, and for participating members to advance them by carrying out pre-defined actions. These types of quests are generated with perfect knowledge of the game world and are able to force desired behaviors out of the relevant non-player characters (NPCs). This becomes a major issue in massive multiplayer online (MMO) when other players …
Using Generative Adversarial Networks To Classify Structural Damage Caused By Earthquakes, Gian P. Delacruz
Using Generative Adversarial Networks To Classify Structural Damage Caused By Earthquakes, Gian P. Delacruz
Master's Theses
The amount of structural damage image data produced in the aftermath of an earthquake can be staggering. It is challenging for a few human volunteers to efficiently filter and tag these images with meaningful damage information. There are several solution to automate post-earthquake reconnaissance image tagging using Machine Learning (ML) solutions to classify each occurrence of damage per building material and structural member type. ML algorithms are data driven; improving with increased training data. Thanks to the vast amount of data available and advances in computer architectures, ML and in particular Deep Learning (DL) has become one of the most …
Neural Network Pruning For Ecg Arrhythmia Classification, Isaac E. Labarge
Neural Network Pruning For Ecg Arrhythmia Classification, Isaac E. Labarge
Master's Theses
Convolutional Neural Networks (CNNs) are a widely accepted means of solving complex classification and detection problems in imaging and speech. However, problem complexity often leads to considerable increases in computation and parameter storage costs. Many successful attempts have been made in effectively reducing these overheads by pruning and compressing large CNNs with only a slight decline in model accuracy. In this study, two pruning methods are implemented and compared on the CIFAR-10 database and an ECG arrhythmia classification task. Each pruning method employs a pruning phase interleaved with a finetuning phase. It is shown that when performing the scale-factor pruning …
Human Path Prediction Using Auto Encoder Lstms And Single Temporal Encoders, Hayden Hudgins
Human Path Prediction Using Auto Encoder Lstms And Single Temporal Encoders, Hayden Hudgins
Master's Theses
Due to automation, the world is changing at a rapid pace. Autonomous agents have become more common over the last several years and, as a result, have created a need for improved software to back them up. The most important aspect of this greater software is path prediction, as robots need to be able to decide where to move in the future. In order to accomplish this, a robot must know how to avoid humans, putting frame prediction at the core of many modern day solutions. A popular way to solve this complex problem of frame prediction is Auto Encoder …
Intelligent Cinematic Camera Control For Real-Time Graphics Applications, Ian Harris Meeder
Intelligent Cinematic Camera Control For Real-Time Graphics Applications, Ian Harris Meeder
Master's Theses
E-sports is currently estimated to be a billion dollar industry which is only growing in size from year to year. However the cinematography of spectated games leaves much to be desired. In most cases, the spectator either gets to control their own freely-moving camera or they get to see the view that a specific player sees. This thesis presents a system for the generation of cinematically-pleasing views for spectating real-time graphics applications. A custom real-time engine has been built to demonstrate the effect of this system on several different game modes with varying visual cinematic constraints, such as the rule …