Signal Processing Commons^™

Visualization And Marker-Less Tracking Of User-Defined Pre-Processed Mri Articulator Data Using Deep Learning, Michael De George

Student Theses

This thesis presents a comprehensive framework for the automated tracking and visualization of articulatory movements based on magnetic resonance imaging (MRI) data. A well-known data analysis tool for markerless pose estimation, known as DeepLabCut, is investigated for this purpose. The performance of this tool is enhanced through the design and implementation of a pre-processor. DeepLabCut is a markerless pose estimation toolbox based on deep learning, which overcomes the issue of making manual annotations frame-by-frame. Limitations from manually marking the MRI images are addressed by implementing transfer learning with convolutional neural networks to achieve accurate, user-defined articulator tracking without markers. Current …

Scalable Hypergraph Structure Learning With Diverse Smoothness Priors, Benjamin T. Brown

Theses and Dissertations--Electrical and Computer Engineering

In graph signal processing, learning weighted connections between nodes from signals is a fundamental task when the underlying relationships are unknown. With the extension of graphs to hypergraphs, where edges can connect more than two nodes, graph learning methods have similarly been generalized to hypergraphs. However, the absence of a unified framework for calculating total variation has led to divergent definitions of smoothness and, consequently, differing approaches to hyperedge recovery. This challenge is confronted in this work through generalization of several previously proposed hypergraph total variations, allowing ease of substitution into a vector-based optimization. To this end, a novel hypergraph …

Investigation Of Gas Dynamics In Water And Oil-Based Muds Using Das, Dts, And Dss Measurements, Temitayo S. Adeyemi

LSU Master's Theses

Reliable prediction of gas migration velocity, void fraction, and length of gas-affected region in water and oil-based muds is essential for effective planning, control, and optimization of drilling operations. However, there is a gap in our understanding of gas behavior and dynamics in water and oil-based muds. This is a consequence of the use of experimental systems that are not representative of field-scale conditions. This study seeks to bridge the gap via the well-scale deployment of distributed fiber-optic sensors for real-time monitoring of gas behavior and dynamics in water and oil-based mud. The aforementioned parameters were estimated in real-time using …

Electronic Note-String Detector, Gavin Garcia-Rossi, Tommy Smail

Electrical Engineering

As the virtual space has become a dominant part of everyone’s day-to-day lives, many normal face-to-face interactions and services have not yet been facilitated by adapting technology. One of these prevailing areas is music lessons. Over Zoom meetings, or other virtual platforms, it is tremendously challenging to teach students. These challenges include recognizing student mistakes audibly and visually, and being able to give confident feedback on the incorrect notes played by learning musicians. Without having to delve into improving the complex systems that would be required to improve audio, video, and connection quality of these connections, we have another solution …

A Machine Learning Approach For The Early Detection Of Bronchopulmonary Dysplasia (Bpd) In Preterm Infants Using Inter Hypoxemia Intervals, Ratri Mukherjee

Electrical Engineering Theses

Preterm birth is a significant global public health concern, affecting millions of babies yearly. Despite advancements in medical care that have improved the survival rates of preterm infants, preterm birth remains a leading cause of neonatal morbidity and mortality worldwide. It has both short-term and long-term health consequences that can profoundly impact the child's growth and development, as well as their family and society.

One of the challenges preterm infants face is their underdeveloped immune system, which makes them more vulnerable to infections and other health problems. Their delicate condition requires specialized care, often provided in a Neonatal Intensive Care …

Application Of Distributed Fiber-Optic Sensing For Pressure Predictions And Multiphase Flow Characterization, Gerald Kelechi Ekechukwu

LSU Doctoral Dissertations

In the oil and gas industry, distributed fiber optics sensing (DFOS) has the potential to revolutionize well and reservoir surveillance applications. Using fiber optic sensors is becoming increasingly common because of its chemically passive and non-magnetic interference properties, the possibility of flexible installations that could be behind the casing, on the tubing, or run on wireline, as well as the potential for densely distributed measurements along the entire length of the fiber. The main objectives of my research are to develop and demonstrate novel signal processing and machine learning computational techniques and workflows on DFOS data for a variety of …

Evaluating Large Delay Estimation Techniques For Assisted Living Environments, Swarnadeep Bagchi, Ruairí De Fréin

Articles

Abstract Phase wraparound due to large inter-sensor spacings in multi-channel demixing limits the range of relative delays that many time–frequency relative delay estimators can estimate. The performance of a large relative delay estimation method, called the elevatogram, is evaluated in the presence of significant phase wraparound. This paper compares the elevatogram with the popular relative delay estimator used in DUET and the brute-force approach in D-AdRess and analyses its computational efficiency. The elevatogram can accurately estimate relative delays of speech signals of up to 800 samples, whereas DUET and D-AdRess were limited to delays of 7 and 35 samples, given …

Computational Models To Detect Radiation In Urban Environments: An Application Of Signal Processing Techniques And Neural Networks To Radiation Data Analysis, Jose Nicolas Gachancipa

Beyond: Undergraduate Research Journal

Radioactive sources, such as uranium-235, are nuclides that emit ionizing radiation, and which can be used to build nuclear weapons. In public areas, the presence of a radioactive nuclide can present a risk to the population, and therefore, it is imperative that threats are identified by radiological search and response teams in a timely and effective manner. In urban environments, such as densely populated cities, radioactive sources may be more difficult to detect, since background radiation produced by surrounding objects and structures (e.g., buildings, cars) can hinder the effective detection of unnatural radioactive material. This article presents a computational model …

Automatic Contact Tracing Using Bluetooth Low Energy Signals And Imu Sensor Readings, Suriyadeepan Ramamoorthy, Joyce Mahon, Michael O'Mahony, Jean Francois Itangayenda, Tendai Mukande, Tlamelo Makati

Other resources

In this report, we present our solution to the challenge provided by the SFI Centre for Machine Learning (ML-Labs) in which the distance between two phones needs to be estimated. It is a modified version of the NIST Too Close For Too Long (TC4TL) Challenge, as the time aspect is excluded. We propose a feature-based approach based on Bluetooth RSSI and IMU sensory data, that outperforms the previous state of the art by a significant margin, reducing the error down to 0.071. We perform an ablation study of our model that reveals interesting insights about the relationship between the distance …

Dynamic Response Of Elastic Two-Story Steel Moment Frame Scaled Structure Equipped With Viscous Dampers, Garrett L. Barker, Alexander L. Poirier

Architectural Engineering

The authors of this report are Architectural Engineering undergraduate students at California Polytechnic State University, San Luis Obispo. Damping is a complex, experimentally derived value that is affected by many structural properties and has a profound effect on the dynamic response of structures. Deducing the inherent damping of a steel moment frame and affecting the damping ratio with viscous dampers are two topics explored in this paper. Dampers are commonly implemented in resilient structures that perform better in a design basis earthquake, reducing the seismic cost and downtime. Undergraduate coursework does not delve into the factors that affect damping and …

Synthetic Aperture Optical Imaging Interferometric Microscopy With Improved Image Quality, Preyom K. Dey

Electrical and Computer Engineering ETDs

The resolution limit of optical microscopy can be extended by using Imaging Interferometric Microscopy (IIM), which uses a low numerical aperture (NA) objective lens to achieve resolution equivalent to that of a high-NA objective lens with multiple sub-images. Along with the resolution enhancement challenge, IIM often suffers from poor image quality. In this dissertation, several image quality improvement methods are proposed and verified with simulation and experimental results. Next, techniques to extend the resolution limit of IIM to ≤ 100nm using a low-NA objective lens are demonstrated. An experimental technique of using a grating coupler on …

Extending Instantaneous De-Mixing Algorithms To Anechoic Mixtures, Swarnadeep Bagchi, Ruairí De Fréin

Conference papers

The AdRess algorithm separates sources that are mixed using stereo, pan-mixing in a computationally efficient way. Pan-mixing gives the sources a location in the stereo field by introducing a relative attenuation between the versions of the sources that appear on each channel. AdRess achieves separation by constructing only a frequency-attenuation matrix. We introduce a new algorithm called Delayed-AdRess (D-AdRess), where, in addition to the frequency-attenuation matrix, two other matrices namely, frequency-delay and time-delay are used to separate sources from anechoic mixtures. By anechoic mixtures, we mean mixing scenarios where both attenuation and delays are experienced by the source signals.

Source Localization With Machine Learning, Arjun Gupta

Electrical and Computer Engineering ETDs

Source localization with sensor arrays have found applications across domains beginning with radar and sonar, astronomy, acoustics, bio-medical devices and more recently in autonomous cars and adaptive communication systems. The knowledge of the spatial spectrum not only provide information about the source and interference but also assists in increasing signal integrity and avoid interference. This provides an added degree of freedom in the form of spatial diversity. This research investigates spatial spectrum estimation of waveforms from the signals sampled by arbitrarily distributed sensors. Conventional high resolution algorithms such as root-MuSiC fails to perform accurate source localization due to the reliance …

Time Series Data Analysis Using Machine Learning-(Ml) Approach, Mvv Prasad Kantipudi Dr., Pradeep Kumar N.S Dr., S.Sreenath Kashyap Dr., Ss Anusha Vemuri Ms

Library Philosophy and Practice (e-journal)

Healthcare benefits related to continuous monitoring of human movement and physical activity can potentially reduce the risk of accidents associated with elderly living alone at home. Based on the literature review, it is found that many studies focus on human activity recognition and are still active towards achieving practical solutions to support the elderly care system. The proposed system has introduced a joint approach of machine learning and signal processing technology for the recognition of human's physical movements using signal data generated by accelerometer sensors. The framework adopts the concept of DSP to select very descriptive feature sets and uses …

An Lpc Pole Processing Method For Enhancing The Identification Of Dominant Spectral Features, Jin Xu, Mark Davis, Ruairí De Fréin

Articles

This paper proposes a new time-resolved spectral analysis method based on a modification to the Linear Predictive Coding (LPC) method for enhancing the identification of the dominant frequencies of a signal. The method described here is based on a z-plane analysis of the LPC poles. These poles are used to produce a series of reduced order filter transfer functions which can accurately identify and estimate the frequency of the dominant spectral features. The standard LPC method has been shown to suffer from a sensitivity to noise and its performance is dependent on the filter order. The proposed method can accurately …

Analog & Digital Remote Synthesizer, Adam Brunner, Andrew Cihon-Scott, Scott Grisso, Linus Wright

Williams Honors College, Honors Research Projects

The purpose of this project is to develop and design an analog synthesizer musical instrument that integrates embedded digital hardware into the design to enable control from a remote source. The use of digital hardware enables the potential for a wide range of convenient features such as sound profile saving and loading, output recording functionality, and the ability to accept digital input from another musical instrument utilizing the Musical Instrument Digital Interface (MIDI). In addition to the synthesizer itself, this project also includes the design of a companion application that can be hosted on a wide variety of consumer computing …

Vibro-Acoustic Codling Moth Larvae Infestation Detection In Apples, Chadwick A. Parrish

Theses and Dissertations--Electrical and Computer Engineering

Within recent years, the demand for organic produce has greatly increased due to many factors, including increasing knowledge about such things as dietary fiber and balanced gastrointestinal bacterial ecosystems. This increase in demand, coupled with the financial penalties for sending invasive species and pests across borders, presents a need for a scalable and accurate system to non-destructively detect infestation. The proposed work addresses this problem by testing the performance of a non-destructive vibro-acoustic method for detecting lava activity in apples. This involved 3 steps; design a mechanical data collection prototype for testing apples, a evaluate a set of features, and …

Health Monitoring Using Deep Learning Of Acoustic And Speech Signals, Eric E. Hamke

Electrical and Computer Engineering ETDs

The focus of the research is to identify stress markers in a firefighter's speech. These markers include changes in breathing patterns and changes in the fundamental frequency of an individual’s voice. The breathing patterns are characterized using the number of breaths taken in a minute and the time spent inhaling. These measures are estimated using a Restricted Boltzmann Machine to process a firefighters’ SCBA regulator sounds, as open and closed. The classifications are then combined into continuous intervals. Observing the length of the intervals and the number of interval-starts represents time spent inhaling and the breathing rates (breaths per minute). …

Biometric Identification With Ecg Signals, Connor Lindstrom, Jonathan Wood, Jacob Torchia, Jonathan Lee

Electrical Engineering

This project introduces a new form of biometric identification with an ECG signal with the use of machine learning concepts. The ECG signal makes a good candidate for identification because of its unique characteristics that make it easy to distinguish individuals from one another. A patient who has previously had ECG scans stored in a database before, can be verified using this program. This project has the capability of identifying a person or verifying a person solely using their ECG signal. Utilizing this biometric identification, hospitals would be able to add to the reliability of their identification process. Additionally, companies …

Development Of A Model And Imbalance Detection System For The Cal Poly Wind Turbine, Ryan Miki Takatsuka

Master's Theses

This thesis develops a model of the Cal Poly Wind Turbine that is used to determine if there is an imbalance in the turbine rotor. A theoretical model is derived to estimate the expected vibrations when there is an imbalance in the rotor. Vibration and acceleration data are collected from the turbine tower during operation to confirm the model is useful and accurate for determining imbalances in the turbine.

Digital signal processing techniques for analyzing the vibration data are explored and tested with simulation data. This includes frequency shifts, lock-in amplifiers, phase-locked loops, discrete Fourier transforms, and decimation filters. The …

Portable Electrocardiogram Device And Signal Processing Design, Ryan F. Blaalid

Electrical Engineering

Full 12-lead electrocardiogram (ECG) measurements require inconvenient and time consuming adhesive electrode placement. This project proposes a design for a Bluetooth based ECG for remote patient measurement. The device is designed to measure up to 6-leads and utilizes 5 dry (non-adhesive) electrodes to accomplish this. The device delivers the ECG data to the user’s mobile smart phone and can then be sent to the patient’s doctor for analysis. Since the contact of the dry electrodes to the skin is not perfect, low-frequency noise called baseline wandering is introduced. A signal processing technique borrowed from image processing called morphological filtering is …

Study Of Obstacle Effect On The Gpsr Protocol And A Novel Intelligent Greedy Routing Protocol For Vanets, Ravikumar Chilmula

Dissertations, Master's Theses and Master's Reports

In recent years, connected vehicle technologies have been developed by automotive companies, academia, and researchers as part of Intelligent Transportation Systems (ITS). This group of stakeholders continue to work on these technologies to make them as reliable and cost-effective as possible. This attention is because of the increasing connected vehicles safety-related, entertainment, and traffic management applications, which have the potential to decrease the number of road accidents, save fuel and time for millions of daily commuters worldwide.

Vehicular Ad-Hoc Network (VANET), which is a subgroup of Mobile Ad-Hoc Network (MANET), is being developed and implemented in vehicles as the critical …

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 …

An Acoustic-Based Approach For Condition Monitoring Of Pipes, Muhammad S. Khan, Turaj Ashuri, Mitchell Collins, Geoffrey Birkemeier, Emad Almohmmedali

Journal of the Arkansas Academy of Science

Polyvinyl chloride pipes are extensively used in municipal sewer systems. As the sewer system ages, polyvinyl chloride pipes become prone to developing cracks that can release toxic effluents into the environment. Traditionally, utility operators pass a close circuit television camera mounted on a guided vehicle through the pipe to monitor the defects. The video is observed by a trained operator who records the condition of the pipe. This arrangement has two major limitations. First, it is expensive due to complex set up. Second, if a pipe is blocked the guided vehicle cannot pass through its entire length. A more economical …

Source Separation Approach To Video Quality Prediction In Computer Networks, Ruairí De Fréin

Articles

Time-varying loads introduce errors in the estimated model parameters of service-level predictors in Computer Networks. A load-adjusted modification of a traditional unadjusted service-level predictor is contributed, based on Source Separation (SS). It mitigates these errors and improves service-quality predictions for Video-on-Demand (VoD) by :6 to 2dB.

Ecg Classification With An Adaptive Neuro-Fuzzy Inference System, Brad Thomas Funsten

Master's Theses

Heart signals allow for a comprehensive analysis of the heart. Electrocardiography (ECG or EKG) uses electrodes to measure the electrical activity of the heart. Extracting ECG signals is a non-invasive process that opens the door to new possibilities for the application of advanced signal processing and data analysis techniques in the diagnosis of heart diseases. With the help of today’s large database of ECG signals, a computationally intelligent system can learn and take the place of a cardiologist. Detection of various abnormalities in the patient’s heart to identify various heart diseases can be made through an Adaptive Neuro-Fuzzy Inference System …

Hybrid Single And Dual Pattern Structured Light Illumination, Minghao Wang

Theses and Dissertations--Electrical and Computer Engineering

Structured Light Illumination is a widely used 3D shape measurement technique in non-contact surface scanning. Multi-pattern based Structured Light Illumination methods reconstruct 3-D surface with high accuracy, but are sensitive to object motion during the pattern projection and the speed of scanning process is relatively long. To reduce this sensitivity, single pattern techniques are developed to achieve a high speed scanning process, such as Composite Pattern (CP) and Modified Composite Pattern (MCP) technique. However, most of single patter techniques have a significant banding artifact and sacrifice the accuracy. We focus on developing SLI techniques can achieve both high speed, high …

Touch Screen Sound Controller, James Fenley, Jonathan Law

Electrical Engineering

The Touch Screen Sound Controller sets out to explore the use of a touch screen as a sound control interface for the disk jockey profession. In addition, the project aims to provide an alternate means of transferring audio data by way of TCP/IP communications as opposed to MIDI. By applying our method, a user may stream pulse-code modulated data from a server onto a client’s RAM via an Ethernet connection. A 32bit, 200MHz ARM9 microprocessor addresses data from the RAM and proceeds with executing DSP instructions from the user. The connection between the touch screen and the central microprocessor is …

Digital Delay Device, Guna Seetharaman, Paul E. Kladitis

AFIT Patents

A digitally controlled optical delay apparatus providing optical signal delays electrically selectable in the picosecond to nanosecond range by way of selectable signal path lengths. Path lengths are incremented in physical length and path delay time according to digital ratios. The delay element includes micro-miniature path changing mirrors controlled in path length selecting positioning by input signals of logic level magnitude. Fiber optic coupling of signals to and from the delay element and a combination of fixed position and movable mirror included optical signal path lengths are included.

Afit/Afosr Symposium On Applications Of Wavelets To Signal Processing, Volume Ii, Tutorial Notes, Gregory T. Warhola, Mark E. Oxley, Steven K. Rogers, Matthew Kabrisky, Bruce W. Suter

AFIT Documents

The Air Force Institute of Technology (AFIT) hosted the Symposium on Applications of Wavelets to Signal processing during 20-22 March 1991 at the AFIT Science and Research Center, Wright-Patterson AFB, OH. This was the first major academic meeting of its kind held at AFIT. The symposium was sponsored by the Air Force Office of Scientific Research (AFOSR), Bolling AFB, DC. It focused on applications of wavelets to problems in image and speech processing, communications, and graphics and opened with a one-day short course, 'A Tutorial on Wavelets.' The symposium was attended by more than 220 researchers worldwide. They represented 15 …