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An Introduction To Nanomaterials For Nanopackaging, James E. Morris
An Introduction To Nanomaterials For Nanopackaging, James E. Morris
Electrical and Computer Engineering Faculty Publications and Presentations
The multiple purposes of an electronics “package” include the provision of mechanical support to the silicon chip, for example, and protection from the environment, the delivery of power in and the facilitation of heat out, and the reliable input and output of information signals, whether electrical or optical. In the age of heterogeneous integration, this includes the internal conversion of signal modes between multiple technologies within the package, while maintaining the traditional requirement of reliable information transmission between packages, e.g., on a traditional circuit board. This article presents some selected examples of nanopackaging, i.e., the application of nanotechnologies, (nanoparticles, carbon …
Design Of A Launchable Remote-Controlled Rover And Protective Aeroshell, Matthew Loewer, Colby Weeks, Lake Williams, Jackson Zazzaro
Design Of A Launchable Remote-Controlled Rover And Protective Aeroshell, Matthew Loewer, Colby Weeks, Lake Williams, Jackson Zazzaro
Senior Theses
Planetary rovers, vehicles that can traverse challenging terrain, have excelled in their exploration missions to other celestial bodies. They have been especially suitable for exploring Mars, as rovers such as Opportunity and Perseverance have collected valuable geological, atmospheric, seismic, and magnetic information from the Martian surface. Rovers will remain vital in future space exploration missions, and it is necessary to understand their design and functionality. This paper focuses on the design and prototyping of a miniature rover that can survive the rough Martian terrain while collecting and submitting environmental data for scientific analysis. The design is based off proven Martian …
On-Device Intelligence For Ai-Enabled Bio-Inspired Autonomous Underwater Vehicles (Auvs), Aryan Anand, M Yuva Bharath, Prabha Sundaravadivel, J. Preetha Roselyn, R. Annie Uthra
On-Device Intelligence For Ai-Enabled Bio-Inspired Autonomous Underwater Vehicles (Auvs), Aryan Anand, M Yuva Bharath, Prabha Sundaravadivel, J. Preetha Roselyn, R. Annie Uthra
Electrical Engineering Faculty Publications and Presentations
This paper introduces an innovative approach to underwater exploration by integrating Artificial Intelligence (AI) into Autonomous Underwater Vehicles (AUVs). This collaboration between AI and biomimicry marks a new era for AUVs, enabling them to emulate marine creatures’ graceful and efficient movements. By infusing AI capabilities into AUVs, AUVs are empowered to learn and adapt, making autonomous real-time decisions without human intervention. This dynamic integration equips AUVs to effectively navigate complex underwater terrains, evade obstacles, and seamlessly interact with marine life. Inspired by the remarkable propulsion mechanisms found in marine organisms, this work proposes a pioneering propulsion system tailored for AUVs. …
Longitudinal Solid Polarized Target For Clas12 And Study Of Spin Structure Of Nucleons, Pushpa Pandey
Longitudinal Solid Polarized Target For Clas12 And Study Of Spin Structure Of Nucleons, Pushpa Pandey
Physics Theses & Dissertations
A suite of experiments measuring target-spin observables in electron-nucleon scattering (dubbed Run Group C) was conducted at Jefferson Lab’s Hall B in Newport News, VA with a new polarized nuclear target known as ‘APOLLO’ (Ammonia Polarized Longitudinally). This innovative target is engineered to seamlessly integrate with the advanced 12 GeV CEBAF (Continuous Electron Beam Accelerator Facility) accelerator and the Hall B CLAS12 (12 GeV CEBAF Large Acceptance Spectrometer) detector array. The ‘APOLLO’ target harnesses the power of Dynamic Nuclear Polarization (DNP) to achieve longitudinal polarization of solid ammonia, thereby creating a net polarization in both protons (NH3) and …
Preserving Location Authenticity: Multi-Sensor System To Thwart Gps Spoofing In Self-Driving Vehicles, Peng Jiang
Preserving Location Authenticity: Multi-Sensor System To Thwart Gps Spoofing In Self-Driving Vehicles, Peng Jiang
Electrical & Computer Engineering Theses & Dissertations
The ubiquity of the Global Positioning System (GPS) has cemented its role as the cornerstone for an array of location-based services and navigation systems, spanning applications from autonomous vehicles and drones to maritime vessels and wearable technology. Nonetheless, ensuring the integrity of reported geographical coordinates poses a formidable challenge, owing to the proliferation of diverse GPS spoofing tools. This predicament is compounded by the pervasive availability of tools like Fake GPS, Lockito, and software-defined radios, enabling even unsophisticated users to commandeer and disseminate counterfeit GPS coordinates. This dissertation undertakes the task of devising an encompassing and resilient framework, integrating a …
Analysis And Improvement Of Efficient Charge Recovery Logic Adiabatic Circuits, William Morell
Analysis And Improvement Of Efficient Charge Recovery Logic Adiabatic Circuits, William Morell
LSU Doctoral Dissertations
Power consumption has been an ever-present concern since the dawn of electronic computing. Every operation that a device performs consumes some amount of energy and as the demand for computation increases, both in scale and ubiquity, reducing this energy loss becomes more important. While modern devices are orders of magnitude more efficient than their ancestors on a per-operation basis, they are increasingly used in more resource constrained applications. Tiny, Internet of Things (IoT) machines are prevalent these days and demanded to perform data collection and analysis at all hours of the day for days at a time on small battery. …
Estimating Direction Of Arrival For Multi-Arm Spiral Antennas Using Machine Learning, Samuel Pearson
Estimating Direction Of Arrival For Multi-Arm Spiral Antennas Using Machine Learning, Samuel Pearson
Honors Theses
Military systems require monitoring a wide frequency range of the RF spectrum to detect and monitor enemy targets. A vital component of that is calculating the direction of arrival of enemy radars. The use of compressive sensing architectures like the Nyquist Folding Receiver (NyFR) allow for computationally cheap capturing of wideband signals; however, these techniques make traditional direction of arrival (DOA) estimation techniques difficult. Given the advantages of compressive sensing, this research aims to apply machine learning (ML) techniques to multi-arm spiral antennas to estimate the incoming DOA. Software like MATLAB was used to simulate the multi-arm spiral antenna and …
Electrospun Nanofiber Technology Based Energy Storage And Biosensor Devices For Wearable Electronics, Bianca Seufert
Electrospun Nanofiber Technology Based Energy Storage And Biosensor Devices For Wearable Electronics, Bianca Seufert
USF Tampa Graduate Theses and Dissertations
As progress in the field of nanotechnology continues to evolve, it is becoming more and more prevalent to apply this small but powerful technology to portable wearable electronics. The unique scale of such a technology lends its expertise to the investigation of enzymes for biometric related diagnostics or in the development of light weight flexible energy storage devices. Furthermore, as the need for highly precise and durable wearable electronics grows, the next generation of electronics must keep pace with this development in terms of shape, flexibility, functionality, and performance.
The presented research reviews the current state of art of nanofiber …
A Gateway To Next-Generation Patient Monitoring System, Kishore Kumar Kadari
A Gateway To Next-Generation Patient Monitoring System, Kishore Kumar Kadari
USF Tampa Graduate Theses and Dissertations
Healthcare patient monitoring is undergoing a significant digital transformation, and the integration of Cyber-Physical Systems (CPS) and Artificial Intelligence (AI) is becoming increasingly crucial in reshaping patient care. In an era where digital technology is revolutionizing medical practices, this research aims to take a leading role in advancing a fundamental aspect of predictive and sustainable healthcare practices, enhancing patient outcomes and uplifting the practice of medicine.
This research focuses on the study of Digital Twins for precision health, which are designed to monitor and provide intricate, personalized feedback dynamically during a patient's healthcare experience. The architecture of the system is …
The Determination Of Pzc And Differential Capacitance Curve Of Platinum-Alkaline Polymer Electrolyte Interfaces, Chen-Xi Liu, Ze-Ping Zou, Mei-Xue Hu, Yu Ding, Yu Gu, Shuai Liu, Wen-Jing Nan, Yi-Chang Ma, Zhao-Bin Chen, Dong-Ping Zhan, Qiu-Gen Zhang, Lin Zhuang, Jia-Wei Yan, Bing-Wei Mao
The Determination Of Pzc And Differential Capacitance Curve Of Platinum-Alkaline Polymer Electrolyte Interfaces, Chen-Xi Liu, Ze-Ping Zou, Mei-Xue Hu, Yu Ding, Yu Gu, Shuai Liu, Wen-Jing Nan, Yi-Chang Ma, Zhao-Bin Chen, Dong-Ping Zhan, Qiu-Gen Zhang, Lin Zhuang, Jia-Wei Yan, Bing-Wei Mao
Journal of Electrochemistry
Alkaline polymer electrolyte (APE) is the core component of modern alkaline hydrogen and oxygen fuel cells, and its single ion conductor nature makes the "electrode/APE" interfaces different from the conventional "electrode/solution" interfaces in terms of ion distribution, electrical double layer structure and polarization behavior. Due to the complexity of the APE and the associated solid-solid interfaces, fundamental investigations are challenging and deeper understanding of the structures and properties of such interfaces is in the infant stage. In this work, we aim to investigate the double layer structure from the aspects of differential capacitance curve and potential of zero charge (PZC) …
Effect Of Fabrication Parameters On The Ferroelectricity Of Hafnium Zirconium Oxide Films: A Statistical Study, Guillermo A. Salcedo, Ahmad E. Islam, Elizabeth Reichley, Michael Dietz, Christine M. Schubert Kabban, Kevin D. Leedy, Tyson C. Back, Weison Wang, Andrew Green, Timothy S. Wolfe, James M. Sattler
Effect Of Fabrication Parameters On The Ferroelectricity Of Hafnium Zirconium Oxide Films: A Statistical Study, Guillermo A. Salcedo, Ahmad E. Islam, Elizabeth Reichley, Michael Dietz, Christine M. Schubert Kabban, Kevin D. Leedy, Tyson C. Back, Weison Wang, Andrew Green, Timothy S. Wolfe, James M. Sattler
Faculty Publications
Ferroelectricity in hafnium zirconium oxide (Hf1−xZrxO2) and the factors that impact it have been a popular research topic since its discovery in 2011. Although the general trends are known, the interactions between fabrication parameters and their effect on the ferroelectricity of Hf1−xZrxO2 require further investigation. In this paper, we present a statistical study and a model that relates Zr concentration (x), film thickness (tf), and annealing temperature (Ta) with the remanent polarization (Pr) in tungsten (W)-capped Hf1−xZrxO2. …
Lrs: Enhancing Adversarial Transferability Through Lipschitz Regularized Surrogate, Tao Wu, Tony Tie Luo, Donald C. Wunsch
Lrs: Enhancing Adversarial Transferability Through Lipschitz Regularized Surrogate, Tao Wu, Tony Tie Luo, Donald C. Wunsch
Computer Science Faculty Research & Creative Works
The Transferability of Adversarial Examples is of Central Importance to Transfer-Based Black-Box Adversarial Attacks. Previous Works for Generating Transferable Adversarial Examples Focus on Attacking Given Pretrained Surrogate Models While the Connections between Surrogate Models and Adversarial Trasferability Have Been overlooked. in This Paper, We Propose Lipschitz Regularized Surrogate (LRS) for Transfer-Based Black-Box Attacks, a Novel Approach that Transforms Surrogate Models towards Favorable Adversarial Transferability. using Such Transformed Surrogate Models, Any Existing Transfer-Based Black-Box Attack Can Run Without Any Change, Yet Achieving Much Better Performance. Specifically, We Impose Lipschitz Regularization on the Loss Landscape of Surrogate Models to Enable a Smoother …
Intelligent Protection Scheme Using Combined Stockwell-Transform And Deep Learning-Based Fault Diagnosis For The Active Distribution System, Latha Maheswari Kandasamy, Kanakaraj Jaganathan
Intelligent Protection Scheme Using Combined Stockwell-Transform And Deep Learning-Based Fault Diagnosis For The Active Distribution System, Latha Maheswari Kandasamy, Kanakaraj Jaganathan
Turkish Journal of Electrical Engineering and Computer Sciences
This study aims to perform fast fault diagnosis and intelligent protection in an active distribution network (ADN) with high renewable energy penetration. Several time-domain simulations are carried out in EMTP-RV to extract time-synchronized current and voltage data. The Stockwell transform (ST) was used in MATLAB/SIMULINK to preprocess these input datasets to train the adaptive fault diagnosis deep convolutional neural network (AFDDCNN) for fault location identification, fault type identification, and fault phase-detection for different penetration levels. Based on the AFDDCNN output, the intelligent protection scheme (IDOCPS) generates the signal for isolating a faulty section of the ADN. An intelligent fault diagnosis …
Lower Data Attacks On Advanced Encryption Standard, Orhun Kara
Lower Data Attacks On Advanced Encryption Standard, Orhun Kara
Turkish Journal of Electrical Engineering and Computer Sciences
The Advanced Encryption Standard (AES) is one of the most commonly used and analyzed encryption algorithms. In this work, we present new combinations of some prominent attacks on AES, achieving new records in data requirements among attacks, utilizing only 2 4 and 2 16 chosen plaintexts (CP) for 6-round and 7-round AES 192/256, respectively. One of our attacks is a combination of a meet-in-the-middle (MiTM) attack with a square attack mounted on 6-round AES-192/256 while another attack combines an MiTM attack and an integral attack, utilizing key space partitioning technique, on 7-round AES-192/256. Moreover, we illustrate that impossible differential (ID) …
Cascade Controller Design Via Controller Synthesis For Load Frequency Control Of Electrical Power Systems, Yavuz Güler, Mustafa Nalbantoğlu, Ibrahim Kaya
Cascade Controller Design Via Controller Synthesis For Load Frequency Control Of Electrical Power Systems, Yavuz Güler, Mustafa Nalbantoğlu, Ibrahim Kaya
Turkish Journal of Electrical Engineering and Computer Sciences
The regulation of tie-line electricity flow and frequency of electrical power systems (EPS) is crucial for ensuring their robustness to parameter changes and efficient management of disturbances. To this end, a novel cascade control design approach utilizing a serial Proportional-Integral-Derivative controller with a filter (PIDF) is proposed in this paper. The parameters of the controllers are derived analytically, and it is employed in both loops of the cascade control system to regulate the Load Frequency Control (LFC) of EPS. The implementation of PIDF controllers in both loops is utilized in the cascade control scheme for various power systems featuring different …
Resolving The Nanoscale Structure Of Β-Sheet Peptide Self-Assemblies Using Single-Molecule Orientation–Localization Microscopy, Weiyan Zhou, Conor L. O'Neill, Tianben Ding, Oumeng Zhang, Jai S. Rudra, Matthew D. Lew
Resolving The Nanoscale Structure Of Β-Sheet Peptide Self-Assemblies Using Single-Molecule Orientation–Localization Microscopy, Weiyan Zhou, Conor L. O'Neill, Tianben Ding, Oumeng Zhang, Jai S. Rudra, Matthew D. Lew
Electrical & Systems Engineering Publications and Presentations
Synthetic peptides that self-assemble into cross-β fibrils are versatile building blocks for engineered biomaterials due to their modularity and biocompatibility, but their structural and morphological similarities to amyloid species have been a long-standing concern for their translation. Further, their polymorphs are difficult to characterize using spectroscopic and imaging techniques that rely on ensemble averaging to achieve high resolution. Here, we utilize Nile red (NR), an amyloidophilic fluorogenic probe, and single-molecule orientation-localization microscopy (SMOLM) to characterize fibrils formed by the designed amphipathic enantiomers KFE8L and KFE8D and the pathological amyloid-beta peptide Aβ42. Importantly, NR SMOLM reveals the helical (bilayer) …
Development Of A Plant Growth And Health Monitoring System Using Imaging And Sensor Array Information For Cubesat Applications, Kat-Kim Phan
Development Of A Plant Growth And Health Monitoring System Using Imaging And Sensor Array Information For Cubesat Applications, Kat-Kim Phan
USF Tampa Graduate Theses and Dissertations
Space exploration has been a topic of interest in the scientific community, such as the planned missions to Mars. To accomplish this would require being able to provide astronauts with a steady supply of food beyond freeze-dried foods leading to the need to grow food in space. Although this is a topic still being investigated, the CubeSat platform opens the possibility of carrying out studies on plant growth under more strenuous space conditions unlike that in the International Space Station (ISS). Developing a plant-focused mission for a CubeSat, though, entails being able to develop a system to sustain plant life …
Quantum-Powered Battery Scheduling In Modern Distribution Grids, Diba Ehsani
Quantum-Powered Battery Scheduling In Modern Distribution Grids, Diba Ehsani
Electronic Theses and Dissertations
The rising need for exploiting a novel and evolved computation is an increasing concern in the power distribution system to address the exponential growth of distribution-connected devices. Scheduling numerous battery energy storage systems in an optimal way is one of the emerging challenges that will be more noticeable as the number of batteries, including residential, community, and vehicle batteries, increases in the grid. This thesis focuses on this topic and offers a necessary component in building the quantum-compatible distribution system of the future. Using a constrained quadratic model (CQM) on D-Wave’s hybrid solver as well as a binary quadratic model …
Data-Driven Approaches For Enhancing Power Grid Reliability, Behrouz Sohrabi
Data-Driven Approaches For Enhancing Power Grid Reliability, Behrouz Sohrabi
Electronic Theses and Dissertations
This thesis explores the transformative potential of data-driven approaches in addressing key operational and reliability issues in power systems. The first part of this thesis addresses a prevalent problem in power distribution networks: the accurate identification of load phases. This study develops a data-driven model leveraging consumption measurements from smart meters and corresponding substation data to reconstruct topology information in low-voltage distribution networks. The proposed model is extensively tested using a dataset with more than 5,000 real load profiles, demonstrating satisfactory performance for large-scale networks. The second part of the thesis pivots to a crucial safety concern: the risk and …
Investigating Customer Churn In Banking: A Machine Learning Approach And Visualization App For Data Science And Management, Pahul Preet Singh, Fahim Islam Anik, Rahul Senapati, Arnav Sinha, Nazmus Sakib, Eklas Hossain
Investigating Customer Churn In Banking: A Machine Learning Approach And Visualization App For Data Science And Management, Pahul Preet Singh, Fahim Islam Anik, Rahul Senapati, Arnav Sinha, Nazmus Sakib, Eklas Hossain
Electrical and Computer Engineering Faculty Publications and Presentations
Customer attrition in the banking industry occurs when consumers quit using the goods and services offered by the bank for some time and, after that, end their connection with the bank. Therefore, customer retention is essential in today’s extremely competitive banking market. Additionally, having a solid customer base helps attract new consumers by fostering confidence and a referral from a current clientele. These factors make reducing client attrition a crucial step that banks must pursue. In our research, we aim to examine bank data and forecast which users will most likely discontinue using the bank’s services and become paying customers. …
The Impact Of N-Doped Carbon Quantum Dots On Dye-Sensitized Solar Cells Operating Under Diffused- And Low-Light Intensity, Mona Samir, Ahmed Agour, Zahraa Ismail, Hassan Nageh, Sameh O. Abdellatif
The Impact Of N-Doped Carbon Quantum Dots On Dye-Sensitized Solar Cells Operating Under Diffused- And Low-Light Intensity, Mona Samir, Ahmed Agour, Zahraa Ismail, Hassan Nageh, Sameh O. Abdellatif
Electrical Engineering
This study investigates the double role of N-doped carbon quantum dots (N-CQDs) in dye-sensitized solar cells (DSSCs) that operate under diffused- and low-light intensity conditions. We demonstrate that the incorporation of N-CQDs leads to a substantial improvement in the performance of DSSCs. Under standard one-sun illumination, the maximum power conversion efficiency (PCE) achieved with N-CQDs is 2% higher than that of the bare cell. Moreover, we introduce two new metrics, the diffused-light coefficient and the low-light intensity coefficient, to evaluate the performance of DSSCs under nonideal illumination conditions. The diffused-light coefficient is recorded at 1.55, which indicates a notable enhancement …
A Sindy Hardware Accelerator For Efficient System Identification On Edge Devices, Michael Sean Gallagher
A Sindy Hardware Accelerator For Efficient System Identification On Edge Devices, Michael Sean Gallagher
Master's Theses
The SINDy (Sparse Identification of Non-linear Dynamics) algorithm is a method of turning a set of data representing non-linear dynamics into a much smaller set of equations comprised of non-linear functions summed together. This provides a human readable system model the represents the dynamic system analyzed. The SINDy algorithm is important for a variety of applications, including high precision industrial and robotic applications. A Hardware Accelerator was designed to decrease the time spent doing calculations. This thesis proposes an efficient hardware accelerator approach for a broad range of applications that use SINDy and similar system identification algorithms. The accelerator is …
A Study Of Random Partitions Vs. Patient-Based Partitions In Breast Cancer Tumor Detection Using Convolutional Neural Networks, Joshua N. Ramos
A Study Of Random Partitions Vs. Patient-Based Partitions In Breast Cancer Tumor Detection Using Convolutional Neural Networks, Joshua N. Ramos
Master's Theses
Breast cancer is one of the deadliest cancers for women. In the US, 1 in 8 women will be diagnosed with breast cancer within their lifetimes. Detection and diagnosis play an important role in saving lives. To this end, many classifiers with varying structures have been designed to classify breast cancer histopathological images. However, randomly partitioning data, like many previous works have done, can lead to artificially inflated accuracies and classifiers that do not generalize. Data leakage occurs when researchers assume that every image in a dataset is independent of each other, which is often not the case for medical …
Dynamic Model Of Ac-Ac Dual Active Bridge Converter Using The Extended Generalized Average Modeling Framework, Kartikeya Jayadurga Prasad Veeramraju, Jonathan W. Kimball
Dynamic Model Of Ac-Ac Dual Active Bridge Converter Using The Extended Generalized Average Modeling Framework, Kartikeya Jayadurga Prasad Veeramraju, Jonathan W. Kimball
Electrical and Computer Engineering Faculty Research & Creative Works
The ac-ac dual active bridge (DAB) converter is an advanced bidirectional two-port grid interface converter that facilitates active and reactive power flow control between two grids without a dc-link capacitor. This article presents a novel modeling approach for the ac-ac DAB converter using the extended generalized average modeling (EGAM) technique. Unlike the conventional generalized average modeling (GAM) framework, the ac-ac DAB converter's dynamic state variables, including the leakage inductor current and ac grid side LC filters, exhibit grid and switching frequency components, making the standard GAM framework unsuitable for dynamic modeling involving two distinct excitation frequencies. Furthermore, the 2-D GAM …
Estimating Stimulated Raman Scattering Noise In Cwdm O-Band Channels Induced By Two Classical Dwdm Sources In A Quantum Network Fiber Segment, Kurt T. Spranger Ii
Estimating Stimulated Raman Scattering Noise In Cwdm O-Band Channels Induced By Two Classical Dwdm Sources In A Quantum Network Fiber Segment, Kurt T. Spranger Ii
Theses and Dissertations
The purpose of this research is to estimate the stimulated Raman scattering noise induced in CWDM O-band channels by two DWDM classical sources in a terrestrial quantum optical network containing classical and quantum optical signal coexistence in the same fiber segment. A use case is defined and analyzed which extracts a single fiber segment from a notional Bell state measurement found in a notional terrestrial quantum network. A stimulated Raman scattering noise model is employed in a Python simulation to estimate and rank-order the five O-band channels with the least amount of relative induced stimulated Raman scattering noise when given …
The Effects Of A Non-Uniform Magnetic Field On Solar Cell Efficiency, Jason A. Burdette
The Effects Of A Non-Uniform Magnetic Field On Solar Cell Efficiency, Jason A. Burdette
Theses and Dissertations
Commercial-grade silicon-based solar cells have an efficiency in the 20-30% range. The addition of a non-uniform magnetic field manipulates the movement of charge carriers within the silicon of a solar cell. With this manipulation, one hypothesis is that the magnetic field increases the current produced by the solar cell which helps to increase the power and efficiency of the solar cell. Measuring a solar cell’s output current and voltage both with and without the presence of a non-uniform magnetic field tests this theory. Voltage multiplied by current gives output power, and to be calculated, efficiency needs maximum output power. The …
Reconstruction Of Radar Range Profiles Using Dropped Channel Polarimetric Compressive Sensing, Nat Thomason
Reconstruction Of Radar Range Profiles Using Dropped Channel Polarimetric Compressive Sensing, Nat Thomason
Theses and Dissertations
This thesis documents the design, construction and testing of a bench-top level measurement system and verifies previously established Dropped Channel Polarimetric Synthetic Aperture Radar Compressive Sensing (DCPCS) simulation results. Compressive Sensing is a mathematical technique which can capture and represent compressible signals at sampling rates significantly below the Nyquist rate. DCPCS is a technique which enhances Compressive Sensing techniques using known physical antenna crosstalk values. The DCPCS technique enables reconstruction of fully polarimetric signals whilst only measuring part of the signal, reducing data capture requirements.
Improving Rogue Radio Emitter Detection Using Siamese Networks, Mason Wright
Improving Rogue Radio Emitter Detection Using Siamese Networks, Mason Wright
Theses and Dissertations
Radio Frequency Fingerprinting (RFF) is the process of creating discerning signatures of emitted radio signals, most often with the goal of identifying specific devices again in the future. The security benefits of this task are intended to build upon current software-based authentication by making use of multi-factor authentication (MFA), but the related task of being able to reject unwanted emitters is limited. This paper presents a Siamese network trained on two different extracted fingerprints of raw Wi-Fi signals, along with a verifier to perform classification and rogue device detection. It was found that fingerprints using the Distortion Reconstruction (DR) technique …
Machine Learning Predictions Of Electricity Transfers Between Balancing Authorities In The Carolinas, Victoria Groleau
Machine Learning Predictions Of Electricity Transfers Between Balancing Authorities In The Carolinas, Victoria Groleau
Theses and Dissertations
Climate change through reduced streamflow, increased temperatures, and other factors impacts the efficiency of energy generation systems. The United States electric grid is comprised of a large network of balancing authorities engaged in trading electricity to maintain balance between supply and demand. The generation of electricity, a pivotal component of this balance, is impacted by climate change and weather variability as well as the growing demand for energy. Several hydro climatological factors such as streamflow, air temperature, and wind speed significantly influence the efficiency of power plant electricity generation. Due to the exchange of electricity between balancing authorities, impacts to …
Accelerating Homomorphic Encryption In Risc-V Architectures With Hardware Based Number Theory Transform, Zachary Legg
Accelerating Homomorphic Encryption In Risc-V Architectures With Hardware Based Number Theory Transform, Zachary Legg
Theses and Dissertations
Fully Homomorphic Encryption is an encryption paradigm enabling computations on encrypted data without the need for decryption. Such behavior is promising for securing DoD cloud computing but is also computationally demanding. To alleviate some of the computational load and accelerate FHE schemes, this research proposes adding a hardware accelerator, for the Number Theory Transform (NTT) operation, to a RISC-V processor. Thus enhancing FHE capabilities for potentially resource-constrained devices.