Signal Processing Commons^™

Radaround: A Field-Expedient Direction Finder For Contested Iot Sensing & Em Situational Awareness, Owen Maute, Blake Roberts

Discovery Day - Daytona Beach

This paper presents RadAround, a passive 2-D direction-finding system designed for adversarial IoT sensing in contested environments. Using mechanically steered narrowbeam antennas and field-deployable SCADA software, it generates high-resolution electromagnetic (EM) heatmaps using low-cost COTS or 3D-printed components. The microcontroller-deployable SCADA coordinates antenna positioning and SDR sampling in real time for resilient, on-site operation. Its modular design enables rapid adaptation for applications such as EMC testing in disaster-response deployments, battlefield spectrum monitoring, electronic intrusion detection, and tactical EM situational awareness (EMSA). Experiments show RadAround detecting computing machinery through walls, assessing utilization, and pinpointing EM interference (EMI) leakage sources from Faraday …

Design And Implementation Of A Synchronized Data Acquisition System For An Ihlp Cessna 182 Testbed, Celso Ferreira De Moura, Mariano Chavez Rangel

Discovery Day - Daytona Beach

This work presents the design and implementation of a fully integrated data acquisition system for a full scale Integrated High Lift Propulsion testbed based on a Cessna 182Q, with emphasis on hardware integration, sensor reliability, and time synchronization. A centralized architecture was developed in LabVIEW to acquire, process, and store data from both analog and digital sensors, including air data systems, inertial measurement units, control positions, and propulsion instrumentation. Analog sensors were carefully calibrated to ensure accurate conversion to engineering units, while digital sensors were incorporated into a unified framework to maintain consistency across all measurements. All ADC, GPS, INS, …

Investigating The Spatial Scales Of Ionospheric Irregularities Using Wavelet Analysis, Nash Mcleod

Discovery Day - Daytona Beach

Investigating the Spatial Scales of Ionospheric Irregularities Using Wavelet Analysis:   Ionospheric radio wave scintillation arises from plasma density irregularities in Earth’s ionosphere. Consequently, rapid fluctuations occur in the phase and amplitude of Global Navigation Satellite System (GNSS) signals and can impact communication and navigation systems. These irregularities span from a wide range of spatial and temporal scales and evolve dynamically under the influence of magnetosphere-ionosphere (MI) processes. We investigate phase and amplitude scintillation events using Continuous Wavelet Transform (CWT) to study the spatial evolution of ionospheric irregularities. These irregularities are thought to be formed via different plasma mechanisms such as …

Wind Tunnel Instrumentation And Testing, Nicholas Marek, Abraham Mezera, Laura Jin, Hayden Smith, Curtis Cook

Student Scholar Symposium

The Raymond B. Jones College of Engineering was contacted by an automotive engineering firm seeking to use the college’s wind tunnel for gathering data on the aerodynamic performance of a proprietary prototype automotive door. Specifically, the client requested the quantification of the drag coefficient of the model at extreme wind speeds. The drag coefficient, a dimensionless number that quantifies the resistance of a specific geometric shape to airflow, will be a valuable datapoint for the client’s design iteration. Due to the sensitive nature of their work, the client has wished to remain anonymous. RBJCOE professors tasked a senior design team …

Increasing Guard Band Size To Decrease Interference In V2x Communication, Nakira Oglesby, Mackenzie Prescott, Billy Kihei, Ph.D.

Symposium of Student Scholars

As technologies evolve and new devices are introduced, the demand for fast and reliable vehicle-to-everything (V2X) communication increases. As this demand increases, the interference level in the 5.9GHz Dedicated Short Range Communications (DSRC) band will inevitably increase. And thus, the task of somehow minimizing this interference becomes increasingly important as time passes. This report investigates the effects of increasing the guard band size of the lower 5.9 GHz DSRC band on the adjacent channel interference from Unlicensed National Information Infrastructure 4 band (U-NII-4) devices and to try and see if there is a significant decrease in the interference level. The …

Automated Solutions For Hydroponic Plant Growth, Sydney Mcclure, Adam Lachguar

Sustainability Conference

Within the past year, Project H.O.M.E. has been focusing on the design and development of a semi-automatic hydroponic system specifically for sustaining plant life in Martian-like conditions. Given the significance of extended space-based travel, where the duration of human life in space is a crucial factor, growing food becomes imperative. This project has integrated electrical engineering and computer science, with features like automated pH testing and sensor-based evaluations. Key functionalities, including timed watering and automatic adjustments, were coded to enhance plant care. Initially, the project’s comprehensive research and strategic planning resulted in detailed blueprints and computer-aided design models for the …

Biocorrosion Analysis Via Multiscale Time Series Analysis, Victor Hugo Mendoza Vejar, Eliseo Hernandez Martinez, Hector Puebla

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Real-Time Filters, Spencer Smith

Thinking Matters Symposium

This project's goal is to create a visual representation of digital signal processing using a Raspberry Pi Pico board. External components will interface with the Pico to supply digital signals and display the results after processing the signal. A microphone will supply the signal to the Pico which will perform a Fourier Transform on the data and output a spectrogram to a display. The display is named ILI9341 which includes an SPI interface, micro SD card slot, and a 2.2 inch screen. The spectrogram includes the magnitudes of the transformed signal at each frequency and time. Each magnitude is illustrated …

Extracting Edges In Space And Time During Visual Fixations, Lynn Schmittwilken, Marianne Maertens

MODVIS Workshop

No abstract provided.

Portable Diffuse Reflectance Spectroscopy For Non-Invasive And Quantitative Assessment Of The Parathyroid Glands Viability During Surgery, Mark Romine, Linh Luong, Alex Moazzen, Katie Cho, Paul Lee

Symposium of Student Scholars

Portable Diffuse Reflectance Spectroscopy for Non-invasive and Quantitative Assessment of the Parathyroid Glands Viability During Surgery

Mark Romine, Linh Luong, Alex Moazzen, Katie Cho and Paul Lee

The parathyroid glands (PTGs) are responsible for the regulation of calcium levels in the blood by secreting a parathyroid hormone. This parathyroid hormone then regulates the body’s absorption, storage, and secretion of calcium, which can directly affect the way muscles and nerves operate. PTGs are often at risk of damage, or accidental removal during thyroid surgeries, because it is challenging to identify PTGs and to determine their viability. Current methods of visual inspections …

Small-Separation Speckle Contrast Optical Spectroscopy For Intraoperative Assessment Of Parathyroid Glands Viability During Thyroid Surgery, Connor Berger

Symposium of Student Scholars

The parathyroid glands (PTGs) are often damaged during thyroid surgeries due to a lack of methods identifying PTGs and assessing their viability. Damage to PTGs can cause hypocalcemia, a deficiency of calcium in the body. This complication can lead to detrimental consequences with economic burden. The surgeon’s current method of viability assessment is qualitative and subjective. Our technical solution is to employ an optical technique called speckle contrast optical spectroscopy (SCOS) that noninvasively quantifies the blood flow index (Db) of biological tissues at deep tissue levels (>1cm). The goal of this project is to verify SCOS at small source-detector-separation …

Physiological Signal Analysis For Emotion Estimation Of Children With Autism Spectrum Disorder, Janet Pulgares Soriano, Karla Conn Welch Phd

Posters-at-the-Capitol

The diagnosis of Autism Spectrum Disorder (ASD) in children is based on human observations by a clinician. The medical evaluation assesses deficits in social communication, social interaction, and restricted, repetitive behaviors. Robotic technology can assist in quantitatively measuring the observations to be used as a future tool for autism diagnosis and intervention. The project explores this technology to produce robotic partners that can adapt to the needs of the ASD population. This way, such robots could serve as instructors or learning peers. A friendly, partner robot, specifically designed for children with ASD could be used to investigate the effect of …

Comparative Analysis Of Rgb-Based Eye-Tracking For Large-Scale Human-Machine Applications, Brett Thaman, Trung Cao

Posters-at-the-Capitol

Gaze tracking has become an established technology that enables using an individual’s gaze as an input signal to support a variety of applications in the context of Human-Computer Interaction. Gaze tracking primarily relies on sensing devices such as infrared (IR) cameras. Nevertheless, in the recent years, several attempts have been realized at detecting gaze by acquiring and processing images acquired from standard RGB cameras. Nowadays, there are only a few publicly available open-source libraries and they have not been tested extensively. In this paper, we present the result of a comparative analysis that studied a commercial eye-tracking device using IR …

Pulmon-C: A Real-Time Monitoring Framework Of Pulmonary Function, Md Saiful Islam, Maria Valero, Shahriar Hossain

Symposium of Student Scholars

This project will develop PulMon-C, a real-time monitoring framework of pulmonary function to diagnose COVID-19 patients who are being self-quarantined at home. The tool will identify anomalies in breathe rate and predict pulmonary deterioration to raise alert for immediate actions. The uniqueness of the tool is using non-invasive sensors placed under-mattress that are able to communicate data about the respiratory signal. The customer segment of PulMon-C will be the diagnosed COVID-19 patients and healthcare providers. PulMon-C will assist with the remote monitoring of COVID-19 patients as an urgent need in the USA and will bring larger impact in delivering …

Framework For Collecting Data From Iot Device, Md Saiful Islam

Symposium of Student Scholars

The Internet of Things (IoT) is the most significant and blooming technology in the 21st century. IoT has rapidly developed by covering hundreds of applications in the civil, health, military, and agriculture areas. IoT is based on the collection of sensor data through an embedded system, and this embedded system uploads the data on the internet. Devices and sensor technologies connected over a network can monitor and measure data in real-time. The main challenge is to collect data from IoT devices, transmit them to store in the Cloud, and later retrieve them at any time for visualization and data analysis. …

Data Analysis Methods For Health Monitoring Sensors, Shahriar Sobhan

Symposium of Student Scholars

Innovations in health monitoring systems are fundamental for the continuous improvement of remote healthcare. With the current presence of SARS-CoV-2, better known as COVID-19, in people’s daily lives, solutions for monitoring heart and especially respiration and pulmonary functions are more needed than ever. Besides, health monitoring systems are widely used for patients who need isolated care, unconscious patients who cannot get medical attention for themselves. As it is well-known, monitoring systems rely on sensor technologies. Currently, there are multiple research studies for remote monitoring using different types of sensors. In this effort, we survey the current approaches that utilize the …

Cybersecurity Strategy Against Cyber Attacks Towards Smart Grids With Pvs, Fangyu Li, Maria Valero, Liang Zhao, Yousef Mahmoud

KSU Proceedings on Cybersecurity Education, Research and Practice

Cyber attacks threaten the security of distribution power grids, such as smart grids. The emerging renewable energy sources such as photovoltaics (PVs) with power electronics controllers introduce new potential vulnerabilities. Based on the electric waveform data measured by waveform sensors in the smart grids, we propose a novel cyber attack detection and identification approach. Firstly, we analyze the cyber attack impacts (including cyber attacks on the solar inverter causing unusual harmonics) on electric waveforms in distribution power grids. Then, we propose a novel deep learning based mechanism including attack detection and attack diagnosis. By leveraging the electric waveform sensor data …

Virtual Eye: A Spatial-Temporal Bottom-Up Eye Sensitivity Model, Todd Goodall

MODVIS Workshop

Video quality and compression models use the

spatial contrast sensitivity function (CSF), which is solved

based on a linear system approximation. This function measures

the eye’s sensitivity to sinusoid gratings, ignoring the subtle

connectivity and inhomogeniety of cell density across the

visual field. Non-linear aspects of the eye, such as the change

in frequency sensitivity with changing illumination, are not

captured by this simple approximation. We propose Virtual

Eye, a bottom-up approach that models the spatio-temporal

dynamics of the eye across the visual field. Each functional

retinal cell layer in the eye is modeled using non-uniform spatial

cell responses, which …

The Challenge For Vision Of Fluctuating Real-World Illumination, David H. Foster

MODVIS Workshop

No abstract provided.

An Unsupervised Channel Selection Method For Ssvep-Based Brain Computer Interfaces, Ethan Webster, Hadi Habibzadeh, Tolga Soyata

CURCE Annual Undergraduate Conference

Brain-computer interfaces (BCIs) provide an alternative communication channel for people with motor deficits that prevent normal communication. The underlying premise of a BCI is that a neuroimaging process such as electroencephalography (EEG) can be used to measure the user’s brain activity as signals. The obtained signals are analyzed to determine the user’s intended actions and a computer system can be used to replace voluntary muscle activity as a means of communication. The information transfer rate (ITR) of an algorithm used for determining the user’s intentions greatly affects the perceived practicality of the BCI system. Such algorithms are divided into two …

Interactive Simulations In Signals And Systems, Anthony Richardson

ASEE IL-IN Section Conference

Several interactive simulations that promote a better understanding of concepts traditionally encountered in an undergraduate Signals and Systems course are described. The simulations were developed to support the text “Signals & Systems: Theory and Applications” by Ulaby and Yagle. The text and all simulation programs are available for free download (ss2.eecs.umich.edu) as part of the Free Electrical Engineering Textbook Initiative from the University of Michigan.

All simulations use graphical control elements that allow the student to interact with the simulation. Many of the simulations use either real audio or image data so that the student can vary parameters of the …

End-To-End Deep Learning Systems For Scene Understanding, Path Planning And Navigation In Fire Fighter Teams, Manish Bhattarai

Shared Knowledge Conference

Firefighting is a dynamic activity with many operations occurring simultaneously. Maintaining situational awareness, defined as knowledge of current conditions and activities at the scene, are critical to accurate decision making. Firefighters often carry various sensors in their personal equipment, namely thermal cameras, gas sensors, and microphones. Improved data processing techniques can mine this data more effectively and be used to improve situational awareness at all times thereby improving real-time decision making and minimizing errors in judgment induced by environmental conditions and anxiety levels. This objective of this research employs state of the art Machine Learning (ML) techniques to create an …

Remote Sensing Using I-Band And S-Band Signals Of Opportunity, Kadir Efecik, Benjamin R. Nold, James L. Garrison

The Summer Undergraduate Research Fellowship (SURF) Symposium

Measurement of soil moisture, especially the root zone soil moisture, is important in agriculture, meteorology, and hydrology. Root zone soil moisture is concerned with the first meter down the soil. Active and passive remote sensing methods used today utilizing L-band(1-2GHz) are physically limited to a sensing depth of about 5 cm or less. To remotely sense the soil moisture in the deeper parts of the soil, the frequency should be lowered. Lower frequencies cannot be used in active spaceborne instruments because of their need for larger antennas, radio frequency interference (RFI), and frequency spectrum allocations. Ground-based passive remote sensing using …

Deep Neural Network Architectures For Modulation Classification Using Principal Component Analysis, Sharan Ramjee, Shengtai Ju, Diyu Yang, Aly El Gamal

The Summer Undergraduate Research Fellowship (SURF) Symposium

In this work, we investigate the application of Principal Component Analysis to the task of wireless signal modulation recognition using deep neural network architectures. Sampling signals at the Nyquist rate, which is often very high, requires a large amount of energy and space to collect and store the samples. Moreover, the time taken to train neural networks for the task of modulation classification is large due to the large number of samples. These problems can be drastically reduced using Principal Component Analysis, which is a technique that allows us to reduce the dimensionality or number of features of the samples …

Gui For Mri-Compatible Neural Stimulator And Recorder, Soo Han Soon, Nishant Babaria, Ranajay Mandal, Zhongming Liu

The Summer Undergraduate Research Fellowship (SURF) Symposium

Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are useful tools to analyze brain activities given active stimulation. However, the electromagnetic noise from the MRI distorts the brain signal recording and damages the subject with excessive heat generated on the electrodes attached to the skin. MRI-compatible recording and stimulation systems previously developed at LIBI lab were capable of removing the electromagnetic noise during the imaging process. Previously, the hardware systems had required the integrative software that could control both circuits simultaneously and enable users to easily change recording and stimulation parameters. Graphical user interface (GUI) programmed with computer language informed …

Perception Of 3d Symmetrical And Near-Symmetrical Shapes, Vijai Jayadevan, Aaron Michaux, Edward Delp, Zygmunt Pizlo

MODVIS Workshop

No abstract provided.

Color Algebras, Jeffrey B. Mulligan

MODVIS Workshop

No abstract provided.

Source Anonymization Of Digital Images: A Counter–Forensic Attack On Prnu Based Source Identification Techniques, Prithviraj Sengupta, Venkata Udaya Sameer, Ruchira Naskar, Ezhil Kalaimannan

Annual ADFSL Conference on Digital Forensics, Security and Law

A lot of photographers and human rights advocates need to hide their identity while sharing their images on the internet. Hence, source–anonymization of digital images has become a critical issue in the present digital age. The current literature contains a number of digital forensic techniques for “source–identification” of digital images, one of the most efficient of them being Photo–Response Non–Uniformity (PRNU) sensor noise pattern based source detection. PRNU noise pattern being unique to every digital camera, such techniques prove to be highly robust way of source–identification. In this paper, we propose a counter–forensic technique to mislead this PRNU sensor noise …

T1, T2, And Off-Resonance Mapping Using A Non-Linear Least-Squares Fit Of The Bssfp Signal, Meredith Taylor, Joseph Valentine, Steven Whitaker, Neal Bangerter

Biomedical Engineering Western Regional Conference

The mapping of MR relaxation times has found a broad variety of applications in the study of disease. Unfortunately, the gold standards for acquiring T₁ and T₂ maps require long scan times, and are therefore more suited to 2D acquisitions with limited slices. For reasonable scan times, resolution is limited making these scans less useful for showing fine morphological detail. A rapid 3D sequence at higher resolutions that could be used to provide both morphological detail and relaxation time maps would be particularly useful. We propose a technique with potential to provide simultaneous band-free 3D datasets and estimates …

Water Fat Separation With Multiple-Acquisition Bssfp Mri, Michael A. Mendoza 8232743, Joseph Valentine, Neal Bangerter

Biomedical Engineering Western Regional Conference

We present a technique that combines the advantages of bSSFP MRI with Dixon reconstruction in order to produce robust water fat separation with high SNR in a short imaging time, while simultaneously reducing banding artifacts that traditionally degrade image quality.