Digital Commons Network^™

Folding Collision Probability In The Nyquist Folding Receiver, Hunter J. D. Miller

Honors Theses

As the radio-frequency spectrum becomes more crowded, there is a growing need for signal processing technology that can instantaneously interpret an ultra-wideband range of frequencies. Existing conventional systems, however, are not the most efficient solution due to the processing capability limitations of current analog-to-digital converter technology. Specifically, with regard to radars, traditional receivers are required to process large amounts of unused data, wasting time and energy. This project highlights a newer analog-to-information receiver that utilizes compressive sensing which is seeking to overcome these challenges. The innovative technology being evaluated allows users to sample far below the standard Nyquist/Shannon sample rates …

Sharprazor: Automatic Removal Of Hair And Ruler Marks From Dermoscopy Images, Reda Kasmi, Jason Hagerty, Reagan Harris Young, Norsang Lama, Januka Nepal, Jessica Miinch, William V. Stoecker, R. Joe Stanley

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Background: The removal of hair and ruler marks is critical in handcrafted image analysis of dermoscopic skin lesions. No other dermoscopic artifacts cause more problems in segmentation and structure detection. Purpose: The aim of the work is to detect both white and black hair, artifacts and finally inpaint correctly the image. Method: We introduce a new algorithm: SharpRazor, to detect hair and ruler marks and remove them from the image. Our multiple-filter approach detects hairs of varying widths within varying backgrounds, while avoiding detection of vessels and bubbles. The proposed algorithm utilizes grayscale plane modification, hair enhancement, segmentation using tri-directional …

Approximate Computing Based Processing Of Mea Signals On Fpga, Mohammad Emad Hassan

Dissertations

The Microelectrode Array (MEA) is a collection of parallel electrodes that may measure the extracellular potential of nearby neurons. It is a crucial tool in neuroscience for researching the structure, operation, and behavior of neural networks. Using sophisticated signal processing techniques and architectural templates, the task of processing and evaluating the data streams obtained from MEAs is a computationally demanding one that needs time and parallel processing.
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/="/">This thesis proposes enhancing the capability of MEA signal processing systems by using approximate computing-based algorithms. These algorithms can be implemented in systems that process parallel MEA channels using the Field …

A Wave Equation-Based Hybridizable Discontinuous Galerkin-Robin Transmission Condition Algorithm For Electromagnetic Problems Analyzing, Xuan Zhang, Shi Min Liu, Ran Zhao, Xiao Chun Li, Jun Fa Mao, Li (Lijun) Jun Jiang, Ping Li

Electrical and Computer Engineering Faculty Research & Creative Works

In this work, a wave-equation-based discontinuous Galerkin (DG) method hybridized with the Robin transmission condition (DG-RTC) is developed to solve the frequency-domain electromagnetic (EM) problems. The proposed DG method directly discretizes the vector electric field wave equation in each subdomain, and subsequently, a term named numerical flux is introduced at the subdomain interfaces to connect the solutions between neighboring subdomains. However, the numerical flux depends not only on the electric field E but also on the magnetic field H residing over the interface. Thereby, another equation is essential for solving E and H simultaneously. Realizing that H only situates at …

A Parametric Numerical Analysis Investigation To Optimize The Performance Of The Ranque-Hilsch Vortex Tube, Muneer Ahmad Sungur

Theses

A vortex tube is a device that separates compressed air into two streams: one with a higher temperature (hot stream) and the other with a lower temperature (cold stream). It is a popular cooling option because it is small, safe, and affordable. The main objective of this thesis is to examine the energy separation performance of RHVT by varying the internal tapering angles of convergent angles (2°, 1.75°, 1.5°, 1.25°, 1°, 0.75°, and 0.5°), straight angles (0°), and divergent angles (0.5°, 1°, 2°, 4°, and 6°), While the cold mass fraction is constant (0.317). Length-to-diameter ratio (Lt/Dt), inlet pressure, and …

A Novel Approach For Detection Fault In The Aircraft Exterior Body Using Image Processing, Noura Nayef Almansoori

Theses

The primary objective of this thesis is to develop innovative techniques for the inspection and maintenance of aircraft structures. We aim to streamline the entire process by utilizing images to detect potential defects in the aircraft body and comparing them to properly functioning images of the aircraft. This enables us to determine whether a specific section of the aircraft is faulty or not. We achieve this by employing image processing to train a model capable of identifying faulty images. The image processing methodology we use involves the use of images of both defective and operational parts of the aircraft's exterior. …

Pvpbc: Privacy- And Verifiability-Preserving E-Voting Based On Permissioned Blockchain, Muntadher Sallal, Ruairí De Fréin, Ali Malik

Articles

Privacy and verifiability are crucial security requirements in e-voting systems and combining them is considered to be a challenge given that they seem to be contradictory. On one hand, privacy means that cast votes cannot be traced to the corresponding voters. On the other hand, linkability of voters and their votes is a requirement of verifiability which has the consequence that a voter is able to check their vote in the election result. These two contradictory features can be addressed by adopting privacy-preserving cryptographic primitives, which at the same time as achieving privacy, achieve verifiability. Many end-to-end schemes that support …

Compressive Sensing Via Variational Bayesian Inference Under Two Widely Used Priors: Modeling, Comparison And Discussion, Mohammad Shekaramiz, Todd K. Moon

Electrical and Computer Engineering Faculty Publications

Compressive sensing is a sub-Nyquist sampling technique for efficient signal acquisition and reconstruction of sparse or compressible signals. In order to account for the sparsity of the underlying signal of interest, it is common to use sparsifying priors such as Bernoulli-Gaussian-inverse Gamma (BGiG) and Gaussian-inverse Gamma (GiG) priors on the compounds of the signal. With the introduction of variational Bayesian inference, the sparse Bayesian learning (SBL) methods for solving the inverse problem of compressive sensing have received significant interest as the SBL methods become more efficient in terms of execution time. In this paper, we consider the sparse signal recovery …

Remote Medical Diagnosis Via Infrared Thermography And Augmented Reality, Frederick M. Selkey

USF Tampa Graduate Theses and Dissertations

Fast, accurate, and non-invasive diagnostic techniques are required by the medical industry to increase the success of medical treatments and enhance the quality of patient care. Medical IRT has been demonstrated reasonably effective at diagnosing and monitoring several physiological conditions. Diversities in the human body, physical and psychological condition, measurement equipment, and environment all influence the sensitive readings obtained by passive IR measurement devices. New standards for medical IRT and fever screening have been demonstrated effective, but there is limited adherence to the guidelines [36]. Absolute temperature readings require regular calibration checks and can easily be thrown off by noise. …

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

Design And Optimization With Quantum And Memristor Platforms, Yiwei Li

Dissertations and Theses

The complexity and diversity of modern computing challenges have made it difficult for traditional computers to efficiently handle tasks such as computer-aided design, design optimization, and combinatorial problems within a reasonable time frame. In applications such as bitcoin mining and robotic control, power consumption and circuit size are critical factors. To overcome these limitations, this dissertation examines alternative computing technologies such as quantum computers and hybrid memristive circuits. The research demonstrates that these technologies hold the potential to offer more efficient and effective solutions for particular problems, whether in terms of faster computation or reduced power consumption.

An Evaluation Of A Computational Technique For Measuring The Embeddedness Of Sustainability In The Curriculum Aligned To Aashe-Stars And The United Nations Sustainable Development Goals, Philippe Lemarchand, Cormac H. Macmahon Dr, Mick Mckeever, Philip Owende

Articles

Introduction: SDG 4.7 mandates university contributions to the United Nations (UN) Sustainable Development Goals (SDGs) through their education provisions. Hence, universities increasingly assess their curricular alignment to the SDGs. A common approach to the assessment is to identify keywords associated with specific SDGs and to analyze for their presence in the curriculum. An inherent challenge is associating the identified keywords as used in the diverse set of curricular contexts to relevant sustainability indicators; hence, the urgent need for more systematic assessment as SDG implementation passes its mid-cycle.

Method: In this study, a more nuanced technique was evaluated with notable capabilities …

Machine Learning Techniques For Stock Price Prediction And Graphic Signal Recognition, Junde Chen, Yuxin Wen, Y. A. Nanehkaran, M. D. Suzauddola, Weirong Chen, Defu Zhang

Engineering Faculty Articles and Research

Stock market analysis is extremely important for investors because knowing the future trend and grasping the changing characteristics of stock prices will decrease the risk of investing capital for profit. Thereupon, the prediction of stock prices and identifying the graphic signals of candlestick charts, which are two crucial tasks in stock price analysis, attract much attention from investors owing to the returns and risks that coexist in financial markets. To introduce a reliable approach for addressing these challenges, this paper proposes the modeling strategies based on machine learning (ML) techniques. A vector autoregression (VAR)-based rolling prediction model is proposed for …

H-Plane Siw Horn Antenna With Enhanced Front-To-Back Ratio For 5g Applications, Özlem Akgün, Nurhan Türker Tokan

Turkish Journal of Electrical Engineering and Computer Sciences

Millimeter-wave (mmWave) antennas are indispensable components in the fifth-generation (5G) wireless communication systems. With the inherent advantages of integration capability, substrate integrated waveguide (SIW) antenna is an excellent choice for applications in the mmWave frequency bands. However, reflection losses occur at dielectric-filled thin apertures of SIW antennas. These reflections can be overcome by impedance matching between the aperture and the free space. In this study, we introduce an mmWave SIW horn antenna having impedance matching transitions (IMTs) across the horn's aperture width. The designed antenna, operating in the 24-28 GHz band, is simulated with a full-wave analysis tool. The simulation …

Boomerang Algorithm Based On Swarm Optimization For Inverse Kinematics Of 6 Dof Open Chain Manipulators, Okan Duymazlar, Di̇lşad Engi̇n

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a feasible swarm intelligence algorithm is proposed that computes the inverse kinematics solution of 6 degree of freedom (DOF) industrial robot arms, which are frequently used in industrial and medical applications. The proposed algorithm is named as Boomerang algorithm due to its recursive structure. The proposed algorithm aims to reduce the computation time to feasible levels without increasing the position and orientation errors. In order to reduce the computational time in swarm optimization algorithms and increase feasibility, an alternative definition method was used instead of the DH method in defining the robot arm kinematic configuration. The effect …

3d Point Cloud Classification With Acgan-3d And Vacwgan-Gp, Onur Ergün, Yusuf Sahi̇lli̇oğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Machine learning and deep learning techniques are widely used to make sense of 3D point cloud data which became ubiquitous and important due to the recent advances in 3D scanning technologies and other sensors. In this work, we propose two networks to predict the class of the input 3D point cloud: 3D Auxiliary Classifier Generative Adversarial Network (ACGAN-3D) and Versatile Auxiliary Conditional Wasserstein Generative Adversarial Network with Gradient Penalty (VACWGAN-GP). Unlike other classifiers, we are able to enlarge the limited data set with the data produced by generative models. We consequently aim to increase the success of the model by …

A Multistep Fusion Matcher Approach For Large Scale Latent Fingerprint/Palmprint Recognition, İsmai̇l Kilinç, Yusuf Oğuzhan Artan, Emre Başeski̇

Turkish Journal of Electrical Engineering and Computer Sciences

Latent fingerprints are ubiquitously used as forensic evidence by law enforcement agencies in solving crimes. However, due to deformations and artifacts within latent fingerprint images, performance of the automated latent recognition systems are far from desired levels. A basic matcher specifically designed for clean fingerprints using a minutiae-based matching algorithm can have high speed and accuracy in a sensor-to-sensor matching task, but low accuracy in matching latent prints, due to scale, rotation and quality differences between latent and sensor images. In this study, we propose a unique multistep fusion matcher (FM) on top of a base matcher that would utilize …

Solving Turkish Math Word Problems By Sequence-To-Sequence Encoder-Decoder Models, Esi̇n Gedi̇k, Tunga Güngör

Turkish Journal of Electrical Engineering and Computer Sciences

Solving math word problems (MWP) is a challenging task due to the semantic gap between natural language texts and mathematical equations. The main purpose of the task is to take a written math problem as input and produce a proper equation as output for solving that problem. This paper describes a sequence-to-sequence (seq2seq) neural model for automatically solving Turkish MWPs based on their semantic meanings in the text. It comprises a bidirectional encoder to comprehend the semantics of the problem by encoding the input sequence and a decoder with attention to extract the equation by tracking the semantic meanings of …

Assessing Hardware Security Threats Posed By Hardware Trojans In Power Electronics, Quinn Kinzie

All Theses

This study investigates the threat of hardware Trojans (HTs) in power electronics applications, a rising concern due to the growing demand for cost-effective embedded solutions in power systems. With the supply chain for electronic hardware devices expanding globally, particularly to low-cost foundries in foreign locations, there is an increasing risk of HT attacks. While there has been extensive research on HTs in computer applications, little consideration has been given to their threat in power electronics. This study demonstrates the effectiveness of a power electronics HT by implementing a novel HT design into a gate drive circuit. Additionally, the research proposes …

Phone Microwave, Khanh Kim Hoang, Emily Zhou

Computer Engineering

This project involves the installation of remote-control capabilities in an antique 1980s microwave, effectively turning the microwave into a “smart” device. While preserving the original functionality of the microwave, a combination of software and hardware components allows for remote microwave operations. The microwave can be remotely operated by calling the built-in number, and more advanced settings and options can be utilized by texting. The microwave is also secured against unauthorized use with the addition of a PIN code that is required to operate the device.

Time-Domain Evaluation Of Atmospheric Ducting Effects On X-Band Propagation Over Water, Jack A. Gallegos

Master's Theses

The marine atmospheric boundary layer (MABL) is the region of atmosphere that interacts with the ocean surface. The atmospheric variability (i.e. temperature and relative humidity) in this region can result in rapid changes in the refractive index with increasing height from the sea surface. The complex region can result in non-standard propagation of electromagnetic (EM) waves beyond the horizon under atmospheric ducting conditions. However, when ducting layers are not present, EM waves are limited to line-of-sight transmission. Atmospheric ducting research is typically conducted using radio frequencies in the X-band (around 8-12 GHz) due to its impact on performance of marine …

Description Of Reaction And Vibrational Energetics Of Co2-Nh3interaction Using Quantum Computing Algorithms, Manh Tien Nguyen, Yueh-Lin Lee, Dominic Alfonso, Qing Shao, Yuhua Duan

Markey Cancer Center Faculty Publications

CO2 capture is critical to solving global warming. Amine-based solvents are extensively used to chemically absorb CO2. Thus, it is crucial to study the chemical absorption of CO2 by amine-based solvents to better understand and optimize CO2 capture processes. Here, we use quantum computing algorithms to quantify molecular vibrational energies and reaction pathways between CO2 and a simplified amine-based solvent model—NH3. Molecular vibrational properties are important to understanding kinetics of reactions. However, the molecule size correlates with the strength of anharmonicity effect on vibrational properties, which can be challenging to address using classical computing. Quantum computing can help enhance molecular …

Simple Open-Source Formal Verification Of Industrial Programs, Christopher Disney Peterson

Master's Theses

Industrial programs written on Programmable Logic Controllers (PLCs) have become an essential component of many modern industries, including automotive, aerospace, manufacturing, infrastructure, and even amusement parks. As these safety-critical systems become larger and more complex, ensuring their continuous error-free operation has become a significant and important challenge. Formal methods are a potential solution to this issue but have traditionally required substantial time and expertise to deploy. This usability issue is compounded by the fact that PLCs are highly proprietary and have substantial licensing costs, making it difficult to learn about or deploy formal methods on them.

This thesis presents the …

Improved Object Re-Identification Via More Efficient Embeddings, Ertugrul Bayraktar

Turkish Journal of Electrical Engineering and Computer Sciences

Object reidentification (ReID) in cluttered rigid scenes is a challenging problem especially when same-looking objects coexist in the scene. ReID is accepted to be one of the most powerful tools for matching the correct identities to each individual object when issues such as occlusion, missed detections, multiple same-looking objects coexisting in the same scene, and disappearance of objects from the view and/or revisiting the same region arise. We propose a novel framework towards more efficient object ReID, improved object reidentification (IO-ReID), to perform object ReID in challenging scenes with real-time processing in mind. The proposed approach achieves distinctive and efficient …

Characterizing Location-Based Electromagnetic Leakage Of Computing Devices Using Convolutional Neural Networks To Increase The Effectiveness Of Side-Channel Analysis Attacks, Ian C. Heffron

Theses and Dissertations

SCA attacks aim to recover some sort of secret information, often in the form of a cipher key, from a target device. Some of these attacks focus on either power-based leakage, or EM-based leakage. Neural networks have recently gained in popularity as tools in SCA attacks. Near-field EM probes with high-spatial resolution enable attackers to isolate physical locations above a processor. This enables attackers to exploit the spatial dependencies of algorithms running on said processor. These spatial dependencies result in different physical locations above a chip emanating different signal strengths. The strengths of different locations can be mapped using the …

Magnetic Anomaly Mapping For Navigation, Luke T. Bergeron

Theses and Dissertations

Magnetic navigation (MagNav) has the potential to provide a global form of navigation that uses magnetic measurements of the Earth’s anomaly magnetic field and compares those measurements to a magnetic anomaly map in order to determine the user’s position. Widespread use of MagNav will require a database of fully-sampled, low-altitude magnetic anomaly maps. Existing magnetic anomaly map databases usually come from under- or poorly-sampled surveys. In this work, we provide an easy to follow MagNav anomaly map generation framework and set of survey collection metrics/requirements in an effort to help facilitate and standardize the creation of such a database. We …

Effects Of Calibration Errors On Dropped-Channel Polarimetric Synthetic Aperture Radar, Jacob C. Morrison

Theses and Dissertations

Compressed Sensing (CS) is a mathematical technique that can be applied to sparse data sets to allow for sub-Nyquist sampling. DCPCS is a CS technique that recovers the signal from unmeasured polarisation channels due to antenna crosstalk coupling the information onto the remaining channels. DCPCS reduces data storage/transmission and receiver hardware requirements. This thesis examines the robustness of DCPCS to calibration errors on the antenna crosstalk matrix. Although the antenna design problem is relaxed to a large region of acceptable crosstalk values, very accurate calibration may be required in a monostatic radar. This thesis also looks at the importance of …

Robust Feature Matching For Visual-Based Aerial Navigation Using Registered Imagery, Luis Montenegro

Theses and Dissertations

This work leverages the SIFT detector along with known robust feature matching techniques for vision-aided sUAS navigation solutions. The proposed algorithm focuses on a sufficient number of features extracted, their quality and their distribution.

Comparison Of Federated Kalman Filter And Autonomous Resilient Management Of All-Source Sensors (Armas) Framework For Fault Detection And Exclusion, Flavio Fernandes

Theses and Dissertations

In recent times, there is a great demand for resilient and robust PNT solutions. Current navigation systems rely heavily on GNSS to provide this solution. This dependence is a major concern and therefore it is prudent to use additional aids to provide the best solution possible. However, traditional methods to address this need require a nontrivial number of Kalman filters to maintain a fault-free solution. The federated filter approach provides an attractive alternative to the current solutions. In this thesis, we examine the use of the federated filter design to address this need in today’s integrated navigation systems. We compared …

Quantum Algorithm For Mining Frequent Patterns For Association Rule Mining, Abdirahman Alasow, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

Maximum frequent pattern generation from a large database of transactions and items for association rule mining is an important research topic in data mining. Association rule mining aims to discover interesting correlations, frequent patterns, associations, or causal structures between items hidden in a large database. By exploiting quantum computing, we propose an efficient quantum search algorithm design to discover the maximum frequent patterns. We modified Grover’s search algorithm so that a subspace of arbitrary symmetric states is used instead of the whole search space. We presented a novel quantum oracle design that employs a quantum counter to count the maximum …