Systems and Communications Commons^™

Reduced Fuel Emissions Through Connected Vehicles And Truck Platooning, Paul D. Brummitt

Electronic Theses and Dissertations

Vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication enable the sharing, in real time, of vehicular locations and speeds with other vehicles, traffic signals, and traffic control centers. This shared information can help traffic to better traverse intersections, road segments, and congested neighborhoods, thereby reducing travel times, increasing driver safety, generating data for traffic planning, and reducing vehicular pollution. This study, which focuses on vehicular pollution, used an analysis of data from NREL, BTS, and the EPA to determine that the widespread use of V2V-based truck platooning—the convoying of trucks in close proximity to one another so as to reduce air drag …

A Memory-Centric Customizable Domain-Specific Fpga Overlay For Accelerating Machine Learning Applications, Atiyehsadat Panahi

Graduate Theses and Dissertations

Low latency inferencing is of paramount importance to a wide range of real time and userfacing Machine Learning (ML) applications. Field Programmable Gate Arrays (FPGAs) offer unique advantages in delivering low latency as well as energy efficient accelertors for low latency inferencing. Unfortunately, creating machine learning accelerators in FPGAs is not easy, requiring the use of vendor specific CAD tools and low level digital and hardware microarchitecture design knowledge that the majority of ML researchers do not possess. The continued refinement of High Level Synthesis (HLS) tools can reduce but not eliminate the need for hardware-specific design knowledge. The designs …

Load Modeling And Evaluation Of Leds For Hardware Test Bed Application, Jillian M. Ruff

Masters Theses

The lighting industry was revolutionized with the emergence of LED lighting. Over the last 15 years, LED lighting device sales and utilization have grown immensely. The growth and popularity of LEDs is due to improved operation of the device when compared to previous lighting technologies. Efficient performance of the device is critical due to the growth of global energy consumption.

As nonrenewable generation fuel is finite, utilities have begun the transition to renewable energy generation. Generation and distribution systems become inherently complex to comprehend and maintain with incorporation of emerging supply and load technologies. With the unprecedented growth of LED …

Deep Learning Based Localization Of Zigbee Interference Sources Using Channel State Information, Dylan Kensler

All Theses

As the field of Internet of Things (IoT) continues to grow, a variety of wireless signals fill the ambient wireless environment. These signals are used for communication, however, recently wireless sensing has been studied, in which these signals can be used to gather information about the surrounding space. With the development of 802.11n, a newer standard of WiFi, more complex information is available about the environment a signal propagates through. This information called Channel State Information (CSI) can be used in wireless sensing. With the help of Deep Learning, this work attempts to generate a fingerprinting technique for localizing a …

An Evaluation Of Wi-Fi 802.11b Backscatter, Anthony Chen

All Theses

Internet of Things (IoT) devices are in need of low-power communications systems with longevity and reliability. With the use of backscatter technology, IoT devices can communicate at the cost of almost no power and can last for up to a decade. Furthermore, backscatter technology is compatible with everyday wireless signals such as Wi-Fi and Bluetooth, allowing for easy communication without specific hardware constraints. This thesis aims to evaluate a Wi-Fi backscatter system and analyze its ease in triggering off of such ambient signals and sources. The system will utilize Wi-Fi 802.11b as a backscatter source to trigger the backscatter system …

Algorithm Optimization And Hardware Acceleration For Machine Learning Applications On Low-Energy Systems, Jianchi Sun

All Dissertations

Machine learning (ML) has been extensively employed for strategy optimization, decision making, data classification, etc. While ML shows great triumph in its application field, the increasing complexity of the learning models introduces neoteric challenges to the ML system designs. On the one hand, the applications of ML on resource-restricted terminals, like mobile computing and IoT devices, are prevented by the high computational complexity and memory requirement. On the other hand, the massive parameter quantity for the modern ML models appends extra demands on the system's I/O speed and memory size. This dissertation investigates feasible solutions for those challenges with software-hardware …

Snap : A Software-Defined & Named-Data Oriented Publish-Subscribe Framework For Emerging Wireless Application Systems, Manveen Kaur

All Dissertations

The evolution of Cyber-Physical Systems (CPSs) has given rise to an emergent class of CPSs defined by ad-hoc wireless connectivity, mobility, and resource constraints in computation, memory, communications, and battery power. These systems are expected to fulfill essential roles in critical infrastructure sectors. Vehicular Ad-Hoc Network (VANET) and a swarm of Unmanned Aerial Vehicles (UAV swarm) are examples of such systems. The significant utility of these systems, coupled with their economic viability, is a crucial indicator of their anticipated growth in the future. Typically, the tasks assigned to these systems have strict Quality-of-Service (QoS) requirements and require sensing, perception, and …

Non-Orthogonal Multi-Dimensional Modulation And Nonlinear Distortion Compensation For Beyond 5g, Thakshanth Uthayakumar

Electronic Thesis and Dissertation Repository

The introduction of new advanced technologies such as higher carrier frequencies, ultra-wide bandwidth, and increased transmission rate in 5G to support ever growing quality-of-service (QoS) demands have brought new challenges such as transmitter-receiver pair specific and domain specific non-orthogonality induced among spatial, time-frequency, and delay-doppler domain radio resource blocks and nonlinear distortions induced among multiple-input multiple-output (MIMO) antennas in spatial domain. In such conditions, current communication systems encounter severe performance degradation and incur higher operational cost. Based on this observation, this thesis aims at creating new multi-dimensional modulation techniques and nonlinear predistortion architectures to achieve higher communication performance with less …

Load-Adjusted Prediction For Proactive Resource Management And Video Server Demand Profiling, Obinna Izima, Ruairí De Fréin

Articles

To lower costs associated with providing cloud resources, a network manager would like to estimate how busy the servers will be in the near future. This is a necessary input in deciding whether to scale up or down computing requirements. We formulate the problem of estimating cloud computational requirements as an integrated framework comprising of a learning and an action stage. In the learning stage, we use Machine Learning (ML) models to predict the video Quality of Delivery (QoD) metric for cloud-hosted servers and use the knowledge gained from the process to make resource management decisions during the action stage. …

A Stochastic Spectrum Trading And Resource Allocation Framework For Opportunistic Dynamic Spectrum Access Networks, Mohamed Abdelraheem, Mohammad Mahmoud Abdellatif

Electrical Engineering

In this article, the spectrum trading problem between primary users and secondary networks is investigated. The secondary network requests multiple channels with the targeted availability to satisfy its users’ demands. Due to the uncertainty about the channels availability, stochastic optimization techniques are adopted to find the optimal set of channels for each secondary network for the lowest cost. Two different constraints on the secondary demand are defined. The first one is when the throughput has to be fully satisfied for a certain percentage of time, and the second one is when the expected value of the throughput has to exceed …

Credit Card Fraud Detection Using Machine Learning Techniques, Nermin Samy Elhusseny, Shimaa Mohamed Ouf, Amira M. Idrees Ami

Future Computing and Informatics Journal

This is a systematic literature review to reflect the previous studies that dealt with credit card fraud detection and highlight the different machine learning techniques to deal with this problem. Credit cards are now widely utilized daily. The globe has just begun to shift toward financial inclusion, with marginalized people being introduced to the financial sector. As a result of the high volume of e-commerce, there has been a significant increase in credit card fraud. One of the most important parts of today's banking sector is fraud detection. Fraud is one of the most serious concerns in terms of monetary …

Empirical Models Of 3d Air-To-Air Communication Channels, Neil Matson

Electrical Engineering Theses and Dissertations

Unmanned Aerial Vehicles (UAVs) often lack the size, weight, and power to support large antenna arrays or a large number of radio chains. Despite such limitations, emerging applications that require the use of swarms, where UAVs form a pattern and coordinate towards a common goal, must have the capability to transmit in any direction in three-dimensional (3D) space from moment to moment. In this work, we design a measurement study to evaluate the role of antenna polarization diversity on UAV systems communicating in arbitrary 3D space. To do so, we construct flight patterns where one transmitting UAV is hovering at …

Measuring The Rol Of Digital Engineering: It's A Journey, Not A Number, Tom Mcdermott, Kaitlin Henderson, Eileen Van Aken, Alejandro Salado, Joseph Bradley

Engineering Management & Systems Engineering Faculty Publications

Systems engineering as a discipline has long had difficulty providing quantifiable evidence of its value (Honour 2004); DE transformation provides an opportunity to better measure its value. Transitioning from a document-based to a model-based approach is expensive, and organizations want to know if the effort and cost to adopt MBSE is worth it.

Improving The Programmability Of Networked Energy Systems, Noman Bashir

Doctoral Dissertations

Global warming and climate change have underscored the need for designing sustainable energy systems. Sustainable energy systems, e.g., smart grids, green data centers, differ from the traditional systems in significant ways and present unique challenges to system designers and operators. First, intermittent renewable energy resources power these systems, which break the notion of infinite, reliable, and controllable power supply. Second, these systems come in varying sizes, spanning over large geographical regions. The control of these dispersed and diverse systems raises scalability challenges. Third, the performance modeling and fault detection in sustainable energy systems is still an active research area. Finally, …

Soft-Mask De-Mixing For Anechoic Mixtures, Swarnadeep Bagchi, Ruairí De Fréin

Articles

This paper extends a computationally efficient, soft-mask based source separation (SS) technique called Redress, to anechoic mixing scenarios. SS methods are an integral part of hearing aid research. We call the resulting method D-Redress. In its original form, Redress was intended for instantaneous mixing scenarios. Numerical evaluations demonstrate that soft-mask based techniques reduce the level of artifacts in the separated speech. Monte Carlo trials on 1000 real speech mixtures demonstrate that the D-Redress successfully extends Redress in terms of Overall-Perceptual (OPS), Target-Perceptual (TPS) scores and Human-Ear Intelligibility (HEI).

Barrier Knockdown Test Control System For The Cal Poly Kinesiology Department, Regina M. Chapuis

Computer Engineering

The goal of this project is to design and implement a new control system for the LEDs and buttons on an existing Barrier Knockdown setup in the Cal Poly Kinesiology department. The Barrier Knockdown test is a testing apparatus in which subjects knock down a series of mechanical barriers in one of three patterns. The computer system times their reaction and movement time, and the test as a whole provides students with data to study the phenomenon of Contextual Interference. This system was previously controlled by an old computer setup that ultimately crashed. This project recreates the logic and user …

Mars Prototype Rover Environmental Measurement System, James A. Renick

Computer Engineering

In my senior project, the problem I am trying to solve is how to efficiently design, create, and install an original library onto a Mars prototype rover operating system and to further use that library to integrate a new weather measurement sensor device into the rover system with the necessary software and hardware implementations. This is an important and highly valued problem as many aerospace and other engineering companies utilize rovers and other autonomous systems for important research, explorations, and reconnaissance missions and goals. In solving this problem, I utilized many resources that were available to me such as advisors, …

Developing A Miniature Smart Boat For Marine Research, Michael Isaac Eirinberg

Computer Engineering

This project examines the development of a smart boat which could serve as a possible marine research apparatus. The smart boat consists of a miniature vessel containing a low-cost microcontroller to live stream a camera feed, GPS telemetry, and compass data through its own WiFi access point. The smart boat also has the potential for autonomous navigation. My project captivated the interest of several members of California Polytechnic State University, San Luis Obispo’s (Cal Poly SLO) Marine Science Department faculty, who proposed a variety of fascinating and valuable smart boat applications.

X-Band Rf Transmitter Design For Multi-Purpose Small Satellite Communication Operations, Omer F. Gumus

Master's Theses

This thesis provides a description of the analysis, design, and tests of an X-band RF Transmitter communication system for small satellites. X-band transmitter systems are becoming popular in the upcoming deep space missions. Most of the deep-space ground stations have been using X-band frequencies to receive or transmit signals. The X-band (<10 GHz) can offer lower atmospheric losses and up to a couple of Mbps data rates for multiple satellite operations. Nowadays, many small satellites have been using frequency bands such as VHF, UHF, L, and S-band frequencies for communication. From deep space to the ground station, the low-frequency ranges are inadequate in providing Mbps level data rates and enough bandwidth for deep space missions.

The main focus of this thesis was the development of the subsystems such as gain block amplifier, Mixer, Bandpass Filter, and RF power amplifier. The subsystems were designed separately, then they were connected together to perform an end-to-end system test. One of the thesis aims is to design …

Hvac Hardware Modeling Using Programmable Automatic Controller, Panthil Ketan Patel, Lumanti Tuladhar

Electrical Engineering

The primary purpose of this project is to use the donated programmable logic controllers (PLC) from Schneider Electric to develop experiments for a future lab class at Cal Poly. Our goal as the first group working on this project is to develop an experiment where the PLC can control the HVAC system based on temperature and humidity sensors and user inputs to maintain a desired consistent temperature. The PLC will be controlled using Unity Pro XLS/Control Expert software for simulations. The overall purpose of the experiments will be to demonstrate the potential of the PLC to minimize manual intervention while …