Systems and Communications Commons^™

Machine Learning-Based Design Of Doppler Tolerant Radar, Kyle Peter Wensell

Dissertations

In this work, machine learning theory is applied to the design of a radar detector in order to train a machine learning-based detector that is robust against Doppler shifts. The radar system is designed to work with data that would be otherwise intractable to conventional optimal detector design, such as transmitted noise waveforms and the effects of one-bit quantization at the receiver. The detection performance of the one-bit receiver is shown to match the performance of the derived square-law sign correlator detector. The resulting learning-based detector also introduces Doppler tolerance to the system, which allows for the successful detection of …

Marking Estimation In Petri Nets Using Dynamic Mode Decomposition, Aditya Kale

Theses

Petri Nets (PNs) are a well-established framework for modeling and analyzing complex systems with interacting, concurrent processes. This thesis extends traditional Petri Net methodologies by integrating Dynamic Mode Decomposition (DMD), a technique originally developed for fluid dynamics, to analyze Continuous Petri Nets (CPNs). By applying DMD to CPN marking evolution, this research constructs a reduced-order model that captures its dynamics through dynamic modes and eigenvalues, enabling prediction of future markings without detailed knowledge of transition firings or underlying deterministic models. The principal contribution of this research is extending the kit of tools available for analysis of CPN dynamics, providing insights …

Learning Proximal Operators With Gaussian Process And Adaptive Quantization In Distributed Optimization, Aldo Duarte Vera Tudela

LSU Doctoral Dissertations

In networks consisting of agents communicating with a central coordinator and working together to solve a global optimization problem in a distributed manner, the agents are often required to solve private proximal minimization subproblems. Such a setting often requires a further decomposition method to solve the global distributed problem, resulting in extensive communication overhead. In networks where communication is expensive, it is crucial to reduce the communication overhead of the distributed optimization scheme. Integrating Gaussian processes (GP) as a learning component to the Alternating Direction Method of Multipliers (ADMM) has proven effective in learning each agent's local proximal operator to …

Scalability And Connectivity Challenges For The Future Of Digital Radio Communication, Christopher Bayliss

Honors Program: Senior Projects (Public)

This thesis explores future challenges in digital radio communication, particularly focusing on scalability and connectivity issues that could impede technological advancements. With the increasing production of digital technology and reliance on radio frequencies, there is a need for innovative solutions to overcome limitations in spectrum availability, interference management, and bandwidth constraints. This work evaluates current modulation techniques, spectrum allocation strategies, and advanced communication technologies such as cognitive radio systems and reconfigurable intelligent surfaces. Through a comprehensive literature review and analysis, this thesis identifies promising developments, including dynamic spectrum sharing and symbiotic radio systems, that could significantly enhance spectrum efficiency and …

Effect Of Recommending Users And Opinions On The Network Connectivity And Idea Generation Process, Sriniwas Pandey, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

The growing reliance on online services underscores the crucial role of recommendation systems, especially on social media platforms seeking increased user engagement. This study investigates how recommendation systems influence the impact of personal behavioral traits on social network dynamics. It explores the interplay between homophily, users’ openness to novel ideas, and recommendation-driven exposure to new opinions. Additionally, the research examines the impact of recommendation systems on the diversity of newly generated ideas, shedding light on the challenges and opportunities in designing effective systems that balance the exploration of new ideas with the risk of reinforcing biases or filtering valuable, unconventional …

Intelligent Resource Allocation For Sdn/Nfv-Enabled Networks Through Reinforcement Learning, Jing Su

Computer Science and Engineering Theses and Dissertations

Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) are two emerging paradigms that enable the feasible and scalable deployment of Virtual Network Functions (VNFs) in commercial-off-the-shelf (COTS) devices, which deliver a range of network services with reduced cost. The deployment of these services requires efficient resource allocation that fulfills the requirements in terms of Quality of Service (QoS) and Service-Level Agreement (SLA) while considering the constraints of the underlying infrastructure, such as maximum latency tolerance and affinity policies.

An optimized resource allocation result can benefit the network in various aspects, such as energy-saving, performance boost, and latency reduction. To achieve …

Generalized Model To Enable Zero-Shot Imitation Learning For Versatile Robots, Yongshuai Wu

Master's Theses

The rapid advancement in Deep Learning (DL), especially in Reinforcement Learning (RL) and Imitation Learning (IL), has positioned it as a promising approach for a multitude of autonomous robotic systems. However, the current methodologies are predominantly constrained to singular setups, necessitating substantial data and extensive training periods. Moreover, these methods have exhibited suboptimal performance in tasks requiring long-horizontal maneuvers, such as Radio Frequency Identification (RFID) inventory, where a robot requires thousands of steps to complete.

In this thesis, we address the aforementioned challenges by presenting the Cross-modal Reasoning Model (CMRM), a novel zero-shot Imitation Learning policy, to tackle long-horizontal robotic …

Machine Learning For Intrusion Detection Into Unmanned Aerial System 6g Networks, Faisal Alrefaei

Doctoral Dissertations and Master's Theses

Progress in the development of wireless network technology has played a crucial role in the evolution of societies and provided remarkable services over the past decades. It remotely offers the ability to execute critical missions and effective services that meet the user's needs. This advanced technology integrates cyber and physical layers to form cyber-physical systems (CPS), such as the Unmanned Aerial System (UAS), which consists of an Unmanned Aerial Vehicle (UAV), ground network infrastructure, communication link, etc. Furthermore, it plays a crucial role in connecting objects to create and develop the Internet of Things (IoT) technology. Therefore, the emergence of …

Detection Of Unauthorized Transmissions In A Frequency Spectrum Using A Wireless Sensor Network, Benjamin Roehrig, Joel Brinkman, Dylan Zupec, Jannette Gonzalez

Honors Capstones

A prototype for a wireless sensor network has been designed to detect and identify unauthorized wireless transmissions in a frequency spectrum. This prototype design is intended to detect unauthorized transmissions within the FM band of frequencies independently at individual nodes with Software Defined Radio receivers and transmit that information to a fusion center for aggregation using a Bluetooth Low Energy mesh network. Aggregated results will be displayed to the user through a Graphical User Interface at the fusion center.

Detection Of Unauthorized Transmissions In A Frequency Spectrum Using Wireless Sensor Network, Joel Brinkman, Jannette Gonzalez, Benjamin Roehrig, Dylan Zupec

Honors Capstones

A prototype for a wireless sensor network has been designed to detect and identify unauthorized wireless transmissions in a frequency spectrum. This prototype design is intended to detect unauthorized transmissions within the FM band of frequencies independently at individual nodes with Software Defined Radio receivers and transmit that information to a fusion center for aggregation using a Bluetooth mesh network. Aggregated results will be displayed to the user through a Graphical User Interface at the fusion center.

Building A Wireless Electronic Control Unit For An Electric Vehicle, Hector S. Sosa

2024 Spring Honors Capstone Projects - Archive

Modern vehicles have a variety of features such remote start systems, advance drive assist systems, smart suspension systems, and a feature rich infotainment system. With all this technology in the car, there exists a complex network of computers working together in conjunction to deliver the modern driving experience that many people have today. To be competitive in the market, auto manufacturers are tasked to add additional features to vehicles by adding additional or modifying electronic control units (ECUs). In this study, an ECU will be designed for a mock electric vehicle which contains an already established network of ECU’s. The …

Summonable Construction Delivery Robot, Kevin M. Lewis

Honors Capstones

In many different construction industries, there is a need for tools, parts, and other necessary items to be transported quickly and efficiently over various types of terrain. Human resources have often been used to address these needs, which can become very time and cost inefficient over long periods. The design proposal here is aimed at addressing this need by developing an autonomous outdoor mobile robot based on a quadrupedal robot design. This approach differs by incorporating a wheeled and quadrupedal hybrid actuation system that provides terrain negotiation and speed at the appropriate times. The team uses Robot Operating System (ROS) …

Mems Optical Cavities For Low Power Communication., Jacob Schopp

Electronic Theses and Dissertations

This thesis discusses the use of MEMS (microelectromechanical systems) optical cavities for use in low power communication. MEMS optical cavities are thin air gaps between an actuated MEMS mirror and a fixed glass encapsulation. By moving the MEMS mirror the reflectivity of the MEMS optical cavity can be changed. This change in reflectivity can be used to transmit information passively by modulating reflected light intensity instead of generating new light using a light source. These MEMS optical cavities are demonstrated using optical fibers for illumination delivery and reflected light collection. In addition to being reflected for communication, the illuminating light …

High Performance Silicon Carbide Based Converters For Powertrain Electrification, Nan Lin

Graduate Theses and Dissertations

With the increasing concern towards environment protection, electric vehicles (EVs) and hybrid electric vehicles (HEVs) have become popular in recent years. They not only help reduce carbon emissions, but also come with other benefits such higher efficiency and better user experience. Many countries and vehicle manufactures have made their plans to keep up with this trend in vehicle electrification. Powertrain is an assembly of components in a vehicle that pushes it forward. As for EVs and HEVs, their powertrains are composed of one or more power electronics converters, which are significant to the system. Silicon carbide MOSFETs have shown superior …

Analyzing A Software Based Lossy Compression Algorithm On An Fpga Platform, Tripp Herlong

All Theses

In HPC, the ability to generate data is outpacing our hardware capabilities of storing said data. This presents the need for compression so we can keep important data preserved without costly hardware upgrades or worrying about hardware speed limitations. Traditional forms of compression are software based, which presents a speed issue that can lead to bottlenecks when storing data.Scientific data lossy compression methods such as SZ enable a speedup on memory transfer by simplifying computation to minimize the essential data size. SZx is a lightweight version of the popular SZ floating point compressor that may benefit from hardware acceleration. This …

Design And Optimization Of An Azeotropic Distillation Pilot Plant For The Production Of Pure Ethanol, Samwel V. Manyele

Tanzania Journal of Engineering and Technology (TJET)

This study aimed to design an azeotropic distillation plant using Aspen Plus® V10 software and determine optimal process conditions for producing pure ethanol greater than 95% from pre-concentrated near-azeotropic ethanol-water solution. The non-random two-liquid Redlich-Kwong thermodynamic model was the base method for property analysis and performance prediction. Modelling and simulation of the converged process were conducted for fixed column variables (R = 5, N = 12 and p = 1 atm). Plant operating parameters were varied in the range of 0 to 1 for the pre-heater vapour fraction, 2 to 10 for the column feed plates (NFP), 2 to 6 …

Evaluation Of Cybersecurity In Remote Working Settings For Mobile Network Operators, Victoria Mahabi

Tanzania Journal of Engineering and Technology (TJET)

Cybersecurity has increasingly been a primary concern to people as technology advances and allows them to work remotely. This study thus evaluated the cybersecurity posture for organisations that have opted for remote working culture, whereas emerging cyber threats, practices to combat them, and appropriate guidelines for managing cyber threats were discussed. The study used a descriptive design with a quantitative approach from 118 information technology personnel working for Tanzania's three major mobile network operators (MNOs). SPSS analysed the collected data. The study revealed that predominant cyber-threats affecting MNOs in remote working include human errors, phishing attacks, malicious domains, denial of …

Applications, Challenges, And Research Issues For Enabling A Uav Swarm, Jennifer Hahner

Senior Honors Theses

Unmanned aerial vehicle (UAV) swarms have the potential to be useful in numerous applications due to their versatility and ability to operate without human intervention. However, this promising technology still requires further investigation, research, and testing before UAV swarms can be implemented extensively. The level of human intervention needed to control the system determines the differing levels of autonomy for UAV swarms. For swarms to become more independent, efficient algorithms for task and path planning are essential. In addition, accurate communication is essential for swarms to be able to coordinate and accomplish tasks successfully. This paper seeks to provide a …

Optimising The Fashion E-Commerce Journey: A Data-Driven Approach To Customer Retention, Hasna Luthfiana Fadhila, Vynska Amalia Permadi, Sylvert Prian Tahalea

Knowledge Engineering and Data Science

A fashion e-commerce company offers a wide range of products from domestic and international brands that are popular with young people. However, there has been an increase in non-organically acquired customers, many of whom do not return to make repeat purchases. This has led to a higher customer churn rate, with a significant proportion of non-organically sourced customers failing to become repeat purchasers. Consequently, a churn analysis and prediction model were developed to address this issue. This paper employs the Recency, Frequency, and Monetary (RFM) framework for churn analysis and prediction. The framework is underpinned by three key dimensions: last …

Docker Optimization Of An Automotive Sector Virtual Server Infrastructure, Leonel Hernandez, Carlos Eduardo Uc Rios

Knowledge Engineering and Data Science

Server virtualization is a powerful strategy for optimizing network infrastructure. It allows multiple virtual servers to run on a single physical server, maximizing resource utilization and improving efficiency. Deploying server virtualization using Docker technology offers a lightweight and flexible approach to optimizing network infrastructure. Docker contains package applications and their dependencies, enabling consistent and efficient deployment across various environments. Specifically, optimizing virtual server infrastructure using Docker Technology in the automotive sector focuses on improving the efficiency and management of the company's virtual server resources. By implementing Docker technology, a container platform that allows the packaging and running of applications in …