Engineering Commons^™

Evaluating The Effect Of Noise On Secure Quantum Networks, Karthick Anbalagan

Master's Theses

This thesis focuses on examining the resilience of secure quantum networks to environmental noise. Specifically, we evaluate the effectiveness of two well-known quantum key distribution (QKD) protocols: the Coherent One-Way (COW) protocol and Kak’s Three-Stage protocol (Kak06). The thesis systematically evaluates these protocols in terms of their efficiency, operational feasibility, and resistance to noise, thereby contributing to the progress of secure quantum communications. Using simulations, this study evaluates the protocols in realistic scenarios that include factors such as noise and decoherence. The results illustrate each protocol’s relative benefits and limitations, highlighting the three-stage protocol’s superior security characteristics, resistance to interference, …

Decentralized Machine Learning On Blockchain: Developing A Federated Learning Based System, Nikhil Sridhar

Master's Theses

Traditional Machine Learning (ML) methods usually rely on a central server to per-
form ML tasks. However, these methods have problems like security risks, data
storage issues, and high computational demands. Federated Learning (FL), on the
other hand, spreads out the ML process. It trains models on local devices and then
combines them centrally. While FL improves computing and customization, it still
faces the same challenges as centralized ML in security and data storage.

This thesis introduces a new approach combining Federated Learning and Decen-
tralized Machine Learning (DML), which operates on an Ethereum Virtual Machine
(EVM) compatible blockchain. The …

Contextually Dynamic Quest Generation Using In-Session Player Information In Mmorpg, Shangwei Lin

Master's Theses

Massively multiplayer online role-playing games (MMORPGs) are one of the most

popular genres in video games that combine massively multiplayer online genres with

role-playing gameplay. MMORPGs’ featured social interaction and forms of level pro-

gression through quest completion are the core for gaining players’ attention. Varied

and challenging quests play an essential part in retaining that attention. However,

well-crafted content takes much longer to develop with human efforts than it does to

consume, and the dominant procedural content generation models for quests suffer

from the drawback of being incompatible with dynamic world changes and the feeling

of repetition over time. …

A Design Of A Digital Lockout Tagout System With Machine Learning, Brandon H. Chen

Master's Theses

Lockout Tagout (LOTO) is a safety procedure instated by the Occupational Safety and Health Administration (OSHA) when doing maintenance on dangerous machinery and hazardous power sources. In this procedure, authorized workers shut off the machinery and use physical locks and tags to prevent operation during maintenance. LOTO has been the industry standard for 32 years since it was instantiated, being used in many different industries such as industrial work, mining, and agriculture. However, LOTO is not without its issues. The LOTO procedure requires employees to be trained and is prone to human error. As well, there is a clash between …

Viability And Implementation Of A Vector Cryptography Extension For Risc-V, Jonathan W. Skelly

Master's Theses

RISC-V is an open-source instruction-set architecture (ISA) forming the basis of thousands of commercial and experimental microprocessors. The Scalar Cryptography extension ratified in December 2021 added scalar instructions that target common hashing and encryption algorithms, including SHA2 and AES. The next step forward for the RISC-V ISA in the field of cryptography and digital security is the development of vector cryptography instructions.

This thesis examines if it is viable to add vector implementations of existing RISC-V scalar cryptography instructions to the existing vector instruction format, and what improvements they can make to the execution of SHA2 and AES algorithms. Vector …

Specialized Named Entity Recognition For Breast Cancer Subtyping, Griffith Scheyer Hawblitzel

Master's Theses

The amount of data and analysis being published and archived in the biomedical research community is more than can feasibly be sifted through manually, which limits the information an individual or small group can synthesize and integrate into their own research. This presents an opportunity for using automated methods, including Natural Language Processing (NLP), to extract important information from text on various topics. Named Entity Recognition (NER), is one way to automate knowledge extraction of raw text. NER is defined as the task of identifying named entities from text using labels such as people, dates, locations, diseases, and proteins. There …

Accelerating Graphics Rendering On Risc-V Gpus, Joshua Simpson

Master's Theses

Graphics Processing Units (GPUs) are commonly used to accelerate massively parallel workloads across a wide range of applications from machine learning to cryptocurrency mining. The original application for GPUs, however, was to accelerate graphics rendering which remains popular today through video gaming and video rendering. While GPUs began as fixed function hardware with minimal programmability, modern GPUs have adopted a design with many programmable cores and supporting fixed function hardware for rasterization, texture sampling, and render output tasks. This balance enables GPUs to be used for general purpose computing and still remain adept at graphics rendering. Previous work at the …

A Nano-Drone Safety Architecture, Connor J. Sexton

Master's Theses

As small-form factor drones grow more intelligent, they increasingly require more sophisticated capabilities to record sensor data and system state, ensuring safe and improved operation. Already regulations for black boxes, electronic data recorders (EDRs), for determining liabilities and improving the safety of large-form factor autonomous vehicles are becoming established. Conventional techniques use hardened memory storage units that conserve all sensor (visual) and system operational state; and N-way redundant models for detecting uncertainty in system operation. For small-form factor drones, which are highly limited by weight, power, and computational resources, these techniques become increasingly prohibitive. In this paper, we propose a …

A Method For Monitoring Operating Equipment Effectiveness With The Internet Of Things And Big Data, Carl D. Hays Iii

Master's Theses

The purpose of this paper was to use the Overall Equipment Effectiveness productivity formula in plant manufacturing and convert it to measuring productivity for forklifts. Productivity for a forklift was defined as being available and picking up and moving containers at port locations in Seattle and Alaska. This research uses performance measures in plant manufacturing and applies them to mobile equipment in order to establish the most effective means of analyzing reliability and productivity. Using the Internet of Things to collect data on fifteen forklift trucks in three different locations, this data was then analyzed over a six-month period to …

Bootstrapping Massively Multiplayer Online Role Playing Games, Mitchell Miller

Master's Theses

Massively Multiplayer Online Role Playing Games (MMORPGs) are a prominent genre in today's video game industry with the most popular MMORPGs generating billions of dollars in revenue and attracting millions of players. As they have grown, they have become a major target for both technological research and sociological research. In such research, it is nearly impossible to reach the same player scale from any self-made technology or sociological experiments. This greatly limits the amount of control and topics that can be explored. In an effort to make up a lacking or non-existent player-base for custom-made MMORPG research scenarios A.I. agents, …

Relevance Analysis For Document Retrieval, Eric Labouve

Master's Theses

Document retrieval systems recover documents from a dataset and order them according to their perceived relevance to a user’s search query. This is a difficult task for machines to accomplish because there exists a semantic gap between the meaning of the terms in a user’s literal query and a user’s true intentions. Even with this ambiguity that arises with a lack of context, users still expect that the set of documents returned by a search engine is both highly relevant to their query and properly ordered. The focus of this thesis is on document retrieval systems that explore methods of …

Amplifying The Prediction Of Team Performance Through Swarm Intelligence And Machine Learning, Erick Michael Harris

Master's Theses

Modern companies are increasingly relying on groups of individuals to reach organizational goals and objectives, however many organizations struggle to cultivate optimal teams that can maximize performance. Fortunately, existing research has established that group personality composition (GPC), across five dimensions of personality, is a promising indicator of team effectiveness. Additionally, recent advances in technology have enabled groups of humans to form real-time, closed-loop systems that are modeled after natural swarms, like flocks of birds and colonies of bees. These Artificial Swarm Intelligences (ASI) have been shown to amplify performance in a wide range of tasks, from forecasting financial markets to …

Corridor Navigation For Monocular Vision Mobile Robots, Matthew James Ng

Master's Theses

Monocular vision robots use a single camera to process information about its environment. By analyzing this scene, the robot can determine the best navigation direction. Many modern approaches to robot hallway navigation involve using a plethora of sensors to detect certain features in the environment. This can be laser range finders, inertial measurement units, motor encoders, and cameras.

By combining all these sensors, there is unused data which could be useful for navigation. To draw back and develop a baseline approach, this thesis explores the reliability and capability of solely using a camera for navigation. The basic navigation structure begins …

A Data-Driven Approach To Cubesat Health Monitoring, Serbinder Singh

Master's Theses

Spacecraft health monitoring is essential to ensure that a spacecraft is operating properly and has no anomalies that could jeopardize its mission. Many of the current methods of monitoring system health are difficult to use as the complexity of spacecraft increase, and are in many cases impractical on CubeSat satellites which have strict size and resource limitations. To overcome these problems, new data-driven techniques such as Inductive Monitoring System (IMS), use data mining and machine learning on archived system telemetry to create models that characterize nominal system behavior. The models that IMS creates are in the form of clusters that …

Quantifying Parkinson's Disease Symptoms Using Mobile Devices, Charles R. Aylward

Master's Theses

Current assessments for evaluating the progression of Parkinson’s Disease are largely qualitative and based on small sets of data obtained from occasional doctor-patient interactions. There is a clinical need to improve the techniques used for mitigating common Parkinson’s Disease symptoms. Available data sets for researching the disease are minimal, hindering advancement toward understanding the underlying causes and effectiveness of treatment and therapies. Mobile devices present an opportunity to continuously monitor Parkinson’s Disease patients and collect important information regarding the severity of symptoms. The evolution of digital technology has opened doors for clinical research to extend beyond the clinic by incorporating …

Astro – A Low-Cost, Low-Power Cluster For Cpu-Gpu Hybrid Computing Using The Jetson Tk1, Sean Kai Sheen

Master's Theses

With the rising costs of large scale distributed systems many researchers have began looking at utilizing low power architectures for clusters. In this paper, we describe our Astro cluster, which consists of 46 NVIDIA Jetson TK1 nodes each equipped with an ARM Cortex A15 CPU, 192 core Kepler GPU, 2 GB of RAM, and 16 GB of flash storage. The cluster has a number of advantages when compared to conventional clusters including lower power usage, ambient cooling, shared memory between the CPU and GPU, and affordability. The cluster is built using commodity hardware and can be setup for relatively low …

An Investigation Into Partitioning Algorithms For Automatic Heterogeneous Compilers, Antonio M. Leija

Master's Theses

Automatic Heterogeneous Compilers allows blended hardware-software solutions to be explored without the cost of a full-fledged design team, but limited research exists on current partitioning algorithms responsible for separating hardware and software. The purpose of this thesis is to implement various partitioning algorithms onto the same automatic heterogeneous compiler platform to create an apples to apples comparison for AHC partitioning algorithms. Both estimated outcomes and actual outcomes for the solutions generated are studied and scored. The platform used to implement the algorithms is Cal Poly’s own Twill compiler, created by Doug Gallatin last year. Twill’s original partitioning algorithm is chosen …

Rest Api To Access And Manage Geospatial Pipeline Integrity Data, Alexandra Michelle Francis

Master's Theses

Today’s economy and infrastructure is dependent on raw natural resources, like crude oil and natural gases, that are optimally transported through a net- work of hundreds of thousands of miles of pipelines throughout America[28]. A damaged pipe can negatively a↵ect thousands of homes and businesses so it is vital that they are monitored and quickly repaired[1]. Ideally, pipeline operators are able to detect damages before they occur, but ensuring the in- tegrity of the vast amount of pipes is unrealistic and would take an impractical amount of time and manpower[1].

Natural disasters, like earthquakes, as well as construction are just …

Toward The Systematization Of Active Authentication Research, Daniel Fleming Gerrity

Master's Theses

Authentication is the vital link between your real self and your digital self. As our digital selves become ever more powerful, the price of failing authentication grows. The most common authentication protocols are static data and employed only once at login. This allows for authentication to be spoofed just once to gain access to an entire user session. Behaviometric protocols continuously consume a user’s behavior as a token of authentication and can be applied throughout a session, thereby eliminating a fixed token to spoof. Research into these protocols as viable forms of authentication is relatively recent and is being conducted …

Decafs: A Modular Distributed File System To Facilitate Distributed Systems Education, Halli Elaine Meth

Master's Theses

Data quantity, speed requirements, reliability constraints, and other factors encourage industry developers to build distributed systems and use distributed services. Software engineers are therefore exposed to distributed systems and services daily in the workplace. However, distributed computing is hard to teach in Computer Science courses due to the complexity distribution brings to all problem spaces. This presents a gap in education where students may not fully understand the challenges introduced with distributed systems. Teaching students distributed concepts would help better prepare them for industry development work.

DecaFS, Distributed Educational Component Adaptable File System, is a modular distributed file system designed …

Regen: Optimizing Genetic Selection Algorithms For Heterogeneous Computing, Scott Kenneth Swinkleb Winkleblack

Master's Theses

GenSel is a genetic selection analysis tool used to determine which genetic markers are informational for a given trait. Performing genetic selection related analyses is a time consuming and computationally expensive task. Due to an expected increase in the number of genotyped individuals, analysis times will increase dramatically. Therefore, optimization efforts must be made to keep analysis times reasonable.

This thesis focuses on optimizing one of GenSel’s underlying algorithms for heterogeneous computing. The resulting algorithm exposes task-level parallelism and data-level parallelism present but inaccessible in the original algorithm. The heterogeneous computing solution, ReGen, outperforms the optimized CPU implementation achieving a …

Optimizing Lempel-Ziv Factorization For The Gpu Architecture, Bryan Ching

Master's Theses

Lossless data compression is used to reduce storage requirements, allowing for the relief of I/O channels and better utilization of bandwidth. The Lempel-Ziv lossless compression algorithms form the basis for many of the most commonly used compression schemes. General purpose computing on graphic processing units (GPGPUs) allows us to take advantage of the massively parallel nature of GPUs for computations other that their original purpose of rendering graphics. Our work targets the use of GPUs for general lossless data compression. Specifically, we developed and ported an algorithm that constructs the Lempel-Ziv factorization directly on the GPU. Our implementation bypasses the …

Virtual Reality Engine Development, Varun Varahamurthy

Master's Theses

With the advent of modern graphics and computing hardware and cheaper sensor and display technologies, virtual reality is becoming increasingly popular in the fields of gaming, therapy, training and visualization. Earlier attempts at popularizing VR technology were plagued by issues of cost, portability and marketability to the general public. Modern screen technologies make it possible to produce cheap, light head-mounted displays (HMDs) like the Oculus Rift, and modern GPUs make it possible to create and deliver a seamless real-time 3D experience to the user. 3D sensing has found an application in virtual and augmented reality as well, allowing for a …

Twill: A Hybrid Microcontroller-Fpga Framework For Parallelizing Single- Threaded C Programs, Douglas S. Gallatin

Master's Theses

Increasingly System-On-A-Chip platforms which incorporate both micropro- cessors and re-programmable logic are being utilized across several fields ranging from the automotive industry to network infrastructure. Unfortunately, the de- velopment tools accompanying these products leave much to be desired, requiring knowledge of both traditional embedded systems languages like C and hardware description languages like Verilog. We propose to bridge this gap with Twill, a truly automatic hybrid compiler that can take advantage of the parallelism inherent in these platforms. Twill can extract long-running threads from single threaded C code and distribute these threads across the hardware and software domains to more …

Compacting Loads And Stores For Code Size Reduction, Isaac Asay

Master's Theses

It is important for compilers to generate executable code that is as small as possible, particularly when generating code for embedded systems. One method of reducing code size is to use instruction set architectures (ISAs) that support combining multiple operations into single operations. The ARM ISA allows for combining multiple memory operations to contiguous memory addresses into a single operation. The LLVM compiler contains a specific memory optimization to perform this combining of memory operations, called ARMLoadStoreOpt. This optimization, however, relies on another optimization (ARMPreAllocLoadStoreOpt) to move eligible memory operations into proximity in order to perform properly. This mover optimization …

Paris: A Parallel Rsa-Prime Inspection Tool, Joseph R. White

Master's Theses

Modern-day computer security relies heavily on cryptography as a means to protect the data that we have become increasingly reliant on. As the Internet becomes more ubiquitous, methods of security must be better than ever. Validation tools can be leveraged to help increase our confidence and accountability for methods we employ to secure our systems.

Security validation, however, can be difficult and time-consuming. As our computational ability increases, calculations that were once considered “hard” due to length of computation, can now be done in minutes. We are constantly increasing the size of our keys and attempting to make computations harder …

Cuda Enhanced Filtering In A Pipelined Video Processing Framework, Austin Aaron Dworaczyk Wiltshire

Master's Theses

The processing of digital video has long been a significant computational task for modern x86 processors. With every video frame composed of one to three planes, each consisting of a two-dimensional array of pixel data, and a video clip comprising of thousands of such frames, the sheer volume of data is significant. With the introduction of new high definition video formats such as 4K or stereoscopic 3D, the volume of uncompressed frame data is growing ever larger.

Modern CPUs offer performance enhancements for processing digital video through SIMD instructions such as SSE2 or AVX. However, even with these instruction sets, …

Low Cost Neurochairs, Frankie Pike

Master's Theses

Electroencephalography (EEG) was formerly confined to clinical and research settings with the necessary hardware costing thousands of dollars. In the last five years a number of companies have produced simple electroencephalograms, priced below $300 and available direct to consumers. These have stirred the imaginations of enthusiasts and brought the prospects of "thought-controlled" devices ever closer to reality. While these new devices were largely targeted at video games and toys, active research on enabling people suffering from debilitating diseases to control wheelchairs was being pursued. A number of neurochairs have come to fruition offering a truly hands-free mobility solution, but whether …

Amaethon – A Web Application For Farm Management And An Assessment Of Its Utility, Tyler Yero

Master's Theses

Amaethon is a web application that is designed for enterprise farm management. It takes a job typically performed with spreadsheets, paper, or custom software and puts it on the web. Farm administration personnel may use it to schedule farm operations and manage their resources and equipment. A survey was con- ducted to assess Amaethon’s user interface design. Participants in the survey were two groups of students and a small group of agriculture professionals. Among other results, the survey indicated that a calendar interface inside Amaethon was preferred, and statistically no less effective, than a map interface. This is despite the …

Detecting Netflix Service Outages Through Analysis Of Twitter Posts, Cailin Cushing

Master's Theses

Every week there are over a billion new posts to Twitter services and many of those messages contain feedback to companies about their services. One company that has recognized this unused source of information is Netflix. That is why Netflix initiated the development of a system that will let them respond to the millions of Twitter and Netflix users that are acting as sensors and reporting all types of user visible outages. This system will enhance the feedback loop between Netflix and its customers by increasing the amount of customer feedback that is being received by Netflix and reducing the …