Signal Processing Commons^™

Measuring Localization Confidence For Quantifying Accuracy And Heterogeneity In Single-Molecule Super-Resolution Microscopy, Hesam Mazidi, Tianben Ding, Arye Nehorai, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

We present a computational method, termed Wasserstein-induced flux (WIF), to robustly quantify the accuracy of individual localizations within a single-molecule localization microscopy (SMLM) dataset without ground- truth knowledge of the sample. WIF relies on the observation that accurate localizations are stable with respect to an arbitrary computational perturbation. Inspired by optimal transport theory, we measure the stability of individual localizations and develop an efficient optimization algorithm to compute WIF. We demonstrate the advantage of WIF in accurately quantifying imaging artifacts in high-density reconstruction of a tubulin network. WIF represents an advance in quantifying systematic errors with unknown and complex distributions, …

Coverage Guided Differential Adversarial Testing Of Deep Learning Systems, Jianmin Guo, Houbing Song, Yue Zhao, Yu Jiang

Publications

Deep learning is increasingly applied to safety-critical application domains such as autonomous cars and medical devices. It is of significant importance to ensure their reliability and robustness. In this paper, we propose DLFuzz, the coverage guided differential adversarial testing framework to guide deep learing systems exposing incorrect behaviors. DLFuzz keeps minutely mutating the input to maximize the neuron coverage and the prediction difference between the original input and the mutated input, without manual labeling effort or cross-referencing oracles from other systems with the same functionality. We also design multiple novel strategies for neuron selection to improve the neuron coverage. The …

Image Restoration Using Automatic Damaged Regions Detection And Machine Learning-Based Inpainting Technique, Chloe Martin-King

Computational and Data Sciences (PhD) Dissertations

In this dissertation we propose two novel image restoration schemes. The first pertains to automatic detection of damaged regions in old photographs and digital images of cracked paintings. In cases when inpainting mask generation cannot be completely automatic, our detection algorithm facilitates precise mask creation, particularly useful for images containing damage that is tedious to annotate or difficult to geometrically define. The main contribution of this dissertation is the development and utilization of a new inpainting technique, region hiding, to repair a single image by training a convolutional neural network on various transformations of that image. Region hiding is also …

Average Speech Directivity, Samuel D. Bellows, Claire M. Pincock, Jennifer K. Whiting, Timothy W. Leishman

Directivity

Speech directivity describes the angular dependence of acoustic radiation from a talker’s mouth and nostrils and diffraction about his or her body and chair (if seated). It is an essential physical aspect of communication affecting sounds and signals in acoustical environments, audio, and telecommunication systems. Because high-resolution, spherically comprehensive measurements of live, phonetically balanced speech have been unavailable in the past, the authors have undertaken research to produce and share such data for simulations of acoustical environments, optimizations of microphone placements, speech studies, and other applications. The measurements included three male and three female talkers who repeated phonetically balanced passages …

Paper-Based Flexible Electrode Using Chemically-Modified Graphene And Functionalized Multiwalled Carbon Nanotube Composites For Electrophysiological Signal Sensing, Md Faruk Hossain, Jae Sang Heo, John Nelson, Insoo Kim

Bioelectrics Publications

Flexible paper-based physiological sensor electrodes were developed using chemically-modified graphene (CG) and carboxylic-functionalized multiwalled carbon nanotube composites (f@MWCNTs). A solvothermal process with additional treatment was conducted to synthesize CG and f@MWCNTs to make CG-f@MWCNT composites. The composite was sonicated in an appropriate solvent to make a uniform suspension, and then it was drop cast on a nylon membrane in a vacuum filter. A number of batches (0%~35% f@MWCNTs) were prepared to investigate the performance of the physical characteristics. The 25% f@MWCNT-loaded composite showed the best adhesion on the paper substrate. The surface topography and chemical bonding of the proposed CG-f@MWCNT …

Demonstration Of Visible And Near Infrared Raman Spectrometers And Improved Matched Filter Model For Analysis Of Combined Raman Signals, Alexander Matthew Atkinson

Electrical & Computer Engineering Theses & Dissertations

Raman spectroscopy is a powerful analysis technique that has found applications in fields such as analytical chemistry, planetary sciences, and medical diagnostics. Recent studies have shown that analysis of Raman spectral profiles can be greatly assisted by use of computational models with achievements including high accuracy pure sample classification with imbalanced data sets and detection of ideal sample deviations for pharmaceutical quality control. The adoption of automated methods is a necessary step in streamlining the analysis process as Raman hardware becomes more advanced. Due to limits in the architectures of current machine learning based Raman classification models, transfer from pure …

A Harmless Wireless Quantum Alternative To Cell Phones Based On Quantum Noise, Florentin Smarandache, Robert Neil Boyd, Victor Christianto

Branch Mathematics and Statistics Faculty and Staff Publications

In the meantime we know that 4G and 5G technologies cause many harms to human health. Therefore, here we submit a harmless wireless quantum alternative to cell phones. It is our hope that this alternative

Digital Holography Efficiency Experiments For Tactical Applications, Douglas E. Thornton

Theses and Dissertations

Digital holography (DH) uses coherent detection and offers direct access to the complex-optical field to sense and correct image aberrations in low signal-to-noise environments, which is critical for tactical applications. The performance of DH is compared to a similar, well studied deep-turbulence wavefront sensor, the self-referencing interferometer (SRI), with known efficiency losses. Wave optics simulations with deep-turbulence conditions and noise were conducted and the results show that DH outperforms the SRI by 10's of dB due to DH's strong reference. Additionally, efficiency experiments were conducted to investigate DH system losses. The experimental results show that the mixing efficiency (37%) is …

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

MODVIS Workshop

No abstract provided.

An Underground Radio Wave Propagation Prediction Model For Digital Agriculture, Abdul Salam

Faculty Publications

Underground sensing and propagation of Signals in the Soil (SitS) medium is an electromagnetic issue. The path loss prediction with higher accuracy is an open research subject in digital agriculture monitoring applications for sensing and communications. The statistical data are predominantly derived from site-specific empirical measurements, which is considered an impediment to universal application. Nevertheless, in the existing literature, statistical approaches have been applied to the SitS channel modeling, where impulse response analysis and the Friis open space transmission formula are employed as the channel modeling tool in different soil types under varying soil moisture conditions at diverse communication distances …

Deep-Turbulence Wavefront Sensing Using Digital Holography In The On-Axis Phase Shifting Recording Geometry With Comparisons To The Self-Referencing Interferometer, Douglas E. Thornton, Mark F. Spencer, Glen P. Perram

Faculty Publications

In this paper, we study the use of digital holography in the on-axis phase-shifting recording geometry for the purposes of deep-turbulence wavefront sensing. In particular, we develop closed-form expressions for the field-estimated Strehl ratio and signal-to-noise ratio for three separate phase-shifting strategies—the four-, three-, and two-step methods. These closed-form expressions compare favorably with our detailed wave-optics simulations, which propagate a point-source beacon through deep-turbulence conditions, model digital holography with noise, and calculate the Monte Carlo averages associated with increasing turbulence strengths and decreasing focal-plane array sampling. Overall, the results show the four-step method is the most efficient phase-shifting strategy and …

Improving Detection Of Dim Targets: Optimization Of A Moment-Based Detection Algorithm, Shannon R. Young

Theses and Dissertations

Wide area motion imagery (WAMI) sensor technology is advancing rapidly. Increases in frame rates and detector array sizes have led to a dramatic increase in the volume of data that can be acquired. Without a corresponding increase in analytical manpower, much of these data remain underutilized. This creates a need for fast, automated, and robust methods for detecting dim, moving signals of interest. Current approaches fall into two categories: detect-before-track (DBT) and track-before-detect (TBD) methods. The DBT methods use thresholding to reduce the quantity of data to be processed, making real time implementation practical but at the cost 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 …

High Dynamic Range Optical Devices And Applications., Elijah Robert Jensen

Electronic Theses and Dissertations

Much of what we know about fundamental physical law and the universe derives from observations and measurements using optical methods. The passive use of the electromagnetic spectrum can be the best way of studying physical phenomenon in general with minimal disturbance of the system in the process. While for many applications ambient visible light is sufficient, light outside of the visible range may convey more information. The signals of interest are also often a small fraction of the background, and their changes occur on time scales so quickly that they are visually imperceptible. This thesis reports techniques and technologies developed …

Dark Current Rts-Noise In Silicon Image Sensors, Benjamin William Hendrickson

Dissertations and Theses

Random Telegraph Signal (RTS) noise is a random noise source defined by discrete and metastable changes in the magnitude of a signal. Though observed in a variety of physical processes, RTS is of particular interest to image sensor fabrication where progress in the suppression of other noise sources has elevated its noise contribution to the point of approaching the limiting noise source in scientific applications.

There have been two basic physical sources of RTS noise reported in image sensors. The first involves a charge trap in the oxide layer of the source follower in a CMOS image sensor. The capture …

Longitudinal Tracking Of Physiological State With Electromyographic Signals., Robert Warren Stallard

Electronic Theses and Dissertations

Electrophysiological measurements have been used in recent history to classify instantaneous physiological configurations, e.g., hand gestures. This work investigates the feasibility of working with changes in physiological configurations over time (i.e., longitudinally) using a variety of algorithms from the machine learning domain. We demonstrate a high degree of classification accuracy for a binary classification problem derived from electromyography measurements before and after a 35-day bedrest. The problem difficulty is increased with a more dynamic experiment testing for changes in astronaut sensorimotor performance by taking electromyography and force plate measurements before, during, and after a jump from a small platform. A …

Mitigating The Effects Of Boom Occlusion On Automated Aerial Refueling Through Shadow Volumes, Zachary C. Paulson

Theses and Dissertations

In flight refueling of Unmanned Aerial Vehicles (UAVs) is critical to the United States Air Force (USAF). However, the large communication latency between a ground-based operator and his/her remote UAV makes docking with a refueling tanker unsafe. This latency may be mitigated by leveraging a tanker-centric stereo vision system. The vision system observes and computes an approaching receiver's relative position and orientation offering a low-latency, high frequency docking solution. Unfortunately, the boom -- an articulated refueling arm responsible for physically pumping fuel into the receiver -- occludes large portions of the receiver especially as the receiver approaches and docks with …

Near Earth Space Object Detection Utilizing Parallax As Multi-Hypothesis Test Criterion, Joseph C. Tompkins

Theses and Dissertations

The US Strategic Command (USSTRATCOM) operated Space Surveillance Network (SSN) is tasked with Space Situational Awareness (SSA) for the US military. This system is made up of Electro-Optic sensors such as the Space Surveillance Telescope (SST) and Ground-based Electro-Optical Deep Space Surveillance (GEODSS) as well as RADAR based sensors such as the Space Fence. While Lockheed Martin’s Space Fence is very adept at detecting & tracking objects in Low Earth Orbit (LEO) below 3000 Km in height [1], gaps remain in the tracking of Resident Space Objects (RSO’s) in Geosynchronous Orbits (GEO) due to limitations associated with the implementation of …

Rss-Based Device-Free Passive Detection And Localization Using Home Automation Network Radio Frequencies, Tiffany M. Phan

Theses and Dissertations

This research provided a proof of concept for a device-free passive (DfP) system capable of detecting and localizing a target through exploitation of a home automation network’s radio frequency (RF) signals. The system was developed using Insteon devices with a 915 MHz center frequency. Without developer privileges, limitations of the Insteon technology like no intrinsic received signal strength (RSS) field and silent periods between messages were overcome by using software-defined radios to simulate Insteon devices capable of collecting and reporting RSS, and by creating a message generation script and implementing a calibrated filter threshold to reduce silent periods. Evaluation of …

Plasmonic Grating Geometrics And Wavelength-Dependent Focus Depth In Infrared Detectors, Patrick R. Kennedy

Theses and Dissertations

The objective for this research is to determine a relationship between plasmonic grating geometries and the wavelength-dependent focus depth. This research is focused on enhancing the signal collected by infrared detectors by using a metal grating as a planar lens to focus light in the detecting region of the substrate. This can be used to maintain a thinner absorbing region and possibly to create multi-color imaging in a single pixel. Simulations demonstrate that the plasmonic lens is capable of creating a wavelength dependent focus spot.

Intelligent And Secure Underwater Acoustic Communication Networks, Chaofeng Wang

Dissertations, Master's Theses and Master's Reports

Underwater acoustic (UWA) communication networks are promising techniques for medium- to long-range wireless information transfer in aquatic applications. The harsh and dynamic water environment poses grand challenges to the design of UWA networks. This dissertation leverages the advances in machine learning and signal processing to develop intelligent and secure UWA communication networks. Three research topics are studied: 1) reinforcement learning (RL)-based adaptive transmission in UWA channels; 2) reinforcement learning-based adaptive trajectory planning for autonomous underwater vehicles (AUVs) in under-ice environments; 3) signal alignment to secure underwater coordinated multipoint (CoMP) transmissions.

First, a RL-based algorithm is developed for adaptive transmission in …

Self-Image Multimedia Technologies For Feedforward Observational Learning, Nkiruka M. A. Uzuegbunam

Theses and Dissertations--Electrical and Computer Engineering

This dissertation investigates the development and use of self-images in augmented reality systems for learning and learning-based activities. This work focuses on self- modeling, a particular form of learning, actively employed in various settings for therapy or teaching. In particular, this work aims to develop novel multimedia systems to support the display and rendering of augmented self-images. It aims to use interactivity (via games) as a means of obtaining imagery for use in creating augmented self-images. Two multimedia systems are developed, discussed and analyzed. The proposed systems are validated in terms of their technical innovation and their clinical efficacy in …

Offline And Online Density Estimation For Large High-Dimensional Data, Aref Majdara

Dissertations, Master's Theses and Master's Reports

Density estimation has wide applications in machine learning and data analysis techniques including clustering, classification, multimodality analysis, bump hunting and anomaly detection. In high-dimensional space, sparsity of data in local neighborhood makes many of parametric and nonparametric density estimation methods mostly inefficient.

This work presents development of computationally efficient algorithms for high-dimensional density estimation, based on Bayesian sequential partitioning (BSP). Copula transform is used to separate the estimation of marginal and joint densities, with the purpose of reducing the computational complexity and estimation error. Using this separation, a parallel implementation of the density estimation algorithm on a 4-core CPU is …

Underwater Acoustic Signal Analysis Toolkit, Kirk Bienvenu Jr

LSU New Orleans Theses and Dissertations

This project started early in the summer of 2016 when it became evident there was a need for an effective and efficient signal analysis toolkit for the Littoral Acoustic Demonstration Center Gulf Ecological Monitoring and Modeling (LADC-GEMM) Research Consortium. LADC-GEMM collected underwater acoustic data in the northern Gulf of Mexico during the summer of 2015 using Environmental Acoustic Recording Systems (EARS) buoys. Much of the visualization of data was handled through short scripts and executed through terminal commands, each time requiring the data to be loaded into memory and parameters to be fed through arguments. The vision was to develop …

Multiple Content Adaptive Intelligent Watermarking Schemes For The Protection Of Blocks Of A Document Image, Chetan Kr Mr., S Nirmala Dr.

Journal of Digital Forensics, Security and Law

Most of the documents contain different types of information such as white space, static information and dynamic information or mix of static and dynamic information. In this paper, multiple watermarking schemes are proposed for protection of the information content. The proposed approach comprises of three phases. In Phase-1, the edges of the source document image are extracted and the edge image is decomposed into blocks of uniform size. In Phase-2, GLCM features like energy, homogeneity, contrast and correlation are extracted from each block and the blocks are classified as no-information, static, dynamic and mix of static and dynamic information content …

Synthesis Of Non-Uniformly Correlated Partially Coherent Sources Using A Deformable Mirror, Milo W. Hyde Iv, Santasri Bose-Pillai, Ryan A. Wood

Faculty Publications

The near real-time synthesis of a non-uniformly correlated partially coherent source using a low-actuator-count deformable mirror is demonstrated. The statistical optics theory underpinning the synthesis method is reviewed. The experimental results of a non-uniformly correlated source are presented and compared to theoretical predictions. A discussion on how deformable mirror characteristics such as actuator count and pitch affect source generation is also included.

Real-Time Camera Tracking System Using Optical Flow Feature Points, Daniel D. Doyle, Alan L. Jennings, Jonathan T. Black

AFIT Patents

A new apparatus and method for tracking a moving object with a moving camera provides a real-time, narrow field-of-view, high resolution and on target image by combining commanded motion with an optical flow algorithm for deriving motion and classifying background. Commanded motion means that movement of the pan, tilt and zoom (PTZ) unit is “commanded” by a computer, instead of being observed by the camera, so that the pan, tilt and zoom parameters are known, as opposed to having to be determined, significantly reducing the computational requirements for tracking a moving object. The present invention provides a single camera pan …

Multispectral Identification Array, Zachary D. Eagan

Computer Engineering

The Multispectral Identification Array is a device for taking full image spectroscopy data via the illumination of a subject with sixty-four unique spectra. The array combines images under the illumination spectra to produce an approximate reflectance graph for every pixel in a scene. Acquisition of an entire spectrum allows the array to differentiate objects based on surface material. Spectral graphs produced are highly approximate and should not be used to determine material properties, however the output is sufficiently consistent to allow differentiation and identification of previously sampled subjects. While not sufficiently advanced for use as a replacement to spectroscopy the …