Metal Thin Film Stiffness Extraction Technique For Surface Acoustic Wave Filters, Travis R. Weismeyer

Electronic Theses and Dissertations

Accurate knowledge of the surface acoustic wave (SAW) properties propagating at the surface of a piezoelectric substrate with thin films, electrodes or temperature compensated films, is critical in SAW filter design to meet the target frequency response, power durability and performance prior to device fabrication. While reliable material constants exist for substrates such as LiNbO3 used in SAW filters, the absolute elastic constants associated with operational thin films used for electrodes or temperature compensation do not exist. Although the bulk values of the constituent materials are known, the composite film/substrate properties are difficult to predict since they depend strongly on …

Weed And Crop Discrimination Through An Offline Computer Vision Algorithm, Phillip J. Putney

ELAIA

With the recent global interest in organic farming and cultivation, many people are turning away from chemical-based herbicides and moving towards alternate methods to extirpate weeds living amongst their crops. Of the methods proposed, robotic weed detection and removal is the most promising because of its possibility to be completely autonomous. Several robust, fully-autonomous robots have been developed, although none have been approved for commercial use. This paper proposes a weed and crop discrimination algorithm that utilizes an excessive green filter paired with principal component analysis to detect specific spatial frequencies within an image corresponding to different types of weeds …

Accurate Vehicle Detection Using Multi-Camera Data Fusion And Machine Learning, Hao Wu

Electrical Engineering Theses and Dissertations

Computer-vision methods have recently been extensively used in intelligent transportation systems for vehicle detection. However, the detection of severely occluded or partially observed vehicles due to the limited camera fields of view remains a significant challenge. This paper presents a multi-camera vehicle detection system that significantly improves the detection performance under occlusion conditions. The key elements of the proposed method include a novel multi-view region proposal network that localizes the candidate vehicles on the ground plane. We also infer the vehicle occupancies by leveraging multi-view cross-camera context. Experiments are conducted on a dataset captured from a roadway in Richardson, TX, …

Electroacoustic Assessment Of Hearing Aids And Psaps, Manan Sheel

Electronic Thesis and Dissertation Repository

Hearing aids and personal sound amplification products (PSAPs) are commonly used assistive devices for treating hearing loss. Due to the diversity in the hardware and signal processing algorithms in these devices, comprehensive verification of their performance is essential. Existing standards for assistive hearing devices are primarily used for quality control purposes and do not quantify their performance in a perceptually-relevant manner. This thesis developed a comprehensive electroacoustic testing toolbox for hearing devices that encompasses both quality control and perceptually-relevant measures. In particular, a test sequence was developed to assess the effectiveness of noise reduction feature in assistive hearing devices. Several …

Vocal Processing With Spectral Analysis, Bradley J. Fitzgerald

ELAIA

A well-known signal processing issue is that of the “cocktail party problem,” which A well-known signal processing issue is that of the “cocktail party problem,” which refers to the need to be able to separate speakers from a mixture of voices. A solution to this problem could provide insight into signal separation in a variety of signal processing fields. In this study, a method of vocal signal processing was examined to determine if principal component analysis of spectral data could be used to characterize differences between speakers and if these differences could be used to separate mixtures of vocal signals. …

Objective Assessment Of Machine Learning Algorithms For Speech Enhancement In Hearing Aids, Krishnan Parameswaran

Electronic Thesis and Dissertation Repository

Speech enhancement in assistive hearing devices has been an area of research for many decades. Noise reduction is particularly challenging because of the wide variety of noise sources and the non-stationarity of speech and noise. Digital signal processing (DSP) algorithms deployed in modern hearing aids for noise reduction rely on certain assumptions on the statistical properties of undesired signals. This could be disadvantageous in accurate estimation of different noise types, which subsequently leads to suboptimal noise reduction. In this research, a relatively unexplored technique based on deep learning, i.e. Recurrent Neural Network (RNN), is used to perform noise reduction and …

Extraction Of Vital Signs Using Real Time Video Analysis For Neonatal Monitoring, Bhushan Lohani

Electrical Engineering Theses

Video data is now commonly used for analysis in surveillance, security, medical and many other fields. The development of low cost but high-quality portable cameras has contributed significantly to this trend. One such trend includes non-invasive vital statistics monitoring of infants in Neonatal Intensive Care Units (NICU). National Center for Health Statistics Publications has reported a high infant death rate (23,215 in 2014). This statistic has drawn the interest of health system professionals. Due to occurrence of conditions like bradycardia, apnea and hypoxia, these preterm infants are kept in an NICU for constant monitoring. One of the problems faced at …

Analysis And Simulation Of Convolution Reverb Using City Tech’S New Auditorium, Tian Leng

Publications and Research

In digital signal processing, convolution reverb can simulate the reverberation of a real acoustic space. The acoustics of different seating areas in an auditorium can vary from each other. To determine the reverberant characteristics of City Tech new building’s auditorium, impulse response (IR) signals are recorded in five key locations of the auditorium.

Directly recorded balloon burst is chosen as the source of impulse source. An omnidirectional and a cardioid microphone with flat frequency response curves are used to record IR signals to 24-bit monophonic wav files. Each IR signal, along with a vocal, is convoluted in MATLAB through both …

Study On The Pattern Recognition Enhancement For Matrix Factorizations With Automatic Relevance Determination, Hau Tao

Electronic Theses, Projects, and Dissertations

Learning the parts of objects have drawn more attentions in computer science recently, and they have been playing the important role in computer applications such as object recognition, self-driving cars, and image processing, etc… However, the existing research such as traditional non-negative matrix factorization (NMF), principal component analysis (PCA), and vector quantitation (VQ) has not been discovering the ground-truth bases which are basic components representing objects. On this thesis, I am proposed to study on pattern recognition enhancement combined non-negative matrix factorization (NMF) with automatic relevance determination (ARD). The main point of this research is to propose a new technique …

Distance-Based Cluster Head Election For Mobile Sensing, Ruairí De Fréin, Liam O'Farrell

Conference papers

Energy-efficient, fair, stochastic leader-selection algorithms are designed for mobile sensing scenarios which adapt the sensing strategy depending on the mobile sensing topology. Methods for electing a cluster head are crucially important when optimizing the trade-off between the number of peer-to- peer interactions between mobiles and client-server interactions with a cloud-hosted application server. The battery-life of mobile devices is a crucial constraint facing application developers who are looking to use the convergence of mobile computing and cloud computing to perform environmental sensing. We exploit the mobile network topology, specifically the location of mobiles with respect to the gateway device, to stochastically …

3d Signal Strength Mapping Of 2.4ghz Wifi Networks, Brett D. Glidden

Electrical Engineering

Many commercial businesses operate out of multi-story office buildings. These companies often use many Wi-Fi access points to set up their own wireless network. IT personnel determine proper Wi-Fi access point placement using Wi-Fi strength maps. Conventional Wi-Fi strength maps only provide a two-dimensional view representing the wireless access point's effective range. The signal quality and strength measurements do not include changing vertical elevation. Efficient network layout in a multi-story building requires a system calculating signal quality metrics in three dimensions.

This project involves designing and prototyping a system to achieve 2.4GHz Wi-Fi signal quality measurements in a three-dimensional reference …

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 …

Transcribing Braille Code: Learning Equations Across Platforms, Deegan Atha, Courtney Balogh

Purdue Journal of Service-Learning and International Engagement

Deegan Atha, a graduating senior in electrical engineering and a future engineer, is interested in human-centered design and developing technology that helps students engage and be successful in STEM.

Courtney Balogh, a junior in mechanical engineering, is interested in human-centered design and the importance it plays in product development. Deegan and Courtney are members of the Purdue EPICS project, Learning Equations Across Platforms (LEAP). They partnered with the Indiana School for the Blind and Visually Impaired (ISBVI) to develop a braille transcription device and web application that converts braille to print in real time.

Programmable Time-Domain Digital-Coding Metasurface For Non-Linear Harmonic Manipulation And New Wireless Communication Systems, Jie Zhao, Xi Yang, Jun Yan Dai, Qiang Cheng, Xiang Li, Ning Hua Qi, Jun Chen Ke, Guo Dong Bai, Shuo Liu, Shi Jin, Andrea Alù, Tie Jun Cui

Publications and Research

Optical non-linear phenomena are typically observed in natural materials interacting with light at high intensities, and they benefit a diverse range of applications from communication to sensing. However, controlling harmonic conversion with high efficiency and flexibility remains a major issue in modern optical and radio-frequency systems. Here, we introduce a dynamic time-domain digital-coding metasurface that enables efficient manipulation of spectral harmonic distribution. By dynamically modulating the local phase of the surface reflectivity, we achieve accurate control of different harmonics in a highly programmable and dynamic fashion, enabling unusual responses, such as velocity illusion. As a relevant application, we propose and …

Frameworks To Investigate Robustness And Disease Characterization/Prediction Utility Of Time-Varying Functional Connectivity State Profiles Of The Human Brain At Rest, Anees Abrol

Electrical and Computer Engineering ETDs

Neuroimaging technologies aim at delineating the highly complex structural and functional organization of the human brain. In recent years, several unimodal as well as multimodal analyses of structural MRI (sMRI) and functional MRI (fMRI) neuroimaging modalities, leveraging advanced signal processing and machine learning based feature extraction algorithms, have opened new avenues in diagnosis of complex brain syndromes and neurocognitive disorders. Generically regarding these neuroimaging modalities as filtered, complimentary insights of brain’s anatomical and functional organization, multimodal data fusion efforts could enable more comprehensive mapping of brain structure and function.

Large scale functional organization of the brain is often studied by …

Connectivity Analysis Of Electroencephalograms In Epilepsy, Panuwat Janwattanapong

FIU Electronic Theses and Dissertations

This dissertation introduces a novel approach at gauging patterns of informa- tion flow using brain connectivity analysis and partial directed coherence (PDC) in epilepsy. The main objective of this dissertation is to assess the key characteristics that delineate neural activities obtained from patients with epilepsy, considering both focal and generalized seizures. The use of PDC analysis is noteworthy as it es- timates the intensity and direction of propagation from neural activities generated in the cerebral cortex, and it ascertains the coefficients as weighted measures in formulating the multivariate autoregressive model (MVAR). The PDC is used here as a feature extraction …

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 …

Hand Motion Tracking System Using Inertial Measurement Units And Infrared Cameras, Nonnarit O-Larnnithipong

FIU Electronic Theses and Dissertations

This dissertation presents a novel approach to develop a system for real-time tracking of the position and orientation of the human hand in three-dimensional space, using MEMS inertial measurement units (IMUs) and infrared cameras. This research focuses on the study and implementation of an algorithm to correct the gyroscope drift, which is a major problem in orientation tracking using commercial-grade IMUs. An algorithm to improve the orientation estimation is proposed. It consists of: 1.) Prediction of the bias offset error while the sensor is static, 2.) Estimation of a quaternion orientation from the unbiased angular velocity, 3.) Correction of the …

Multivariate Analysis For The Quantification Of Transdermal Volatile Organic Compounds In Humans By Proton Exchange Membrane Fuel Cell System, Ahmed Hasnain Jalal

FIU Electronic Theses and Dissertations

In this research, a proton exchange membrane fuel cell (PEMFC) sensor was investigated for specific detection of volatile organic compounds (VOCs) for point-of-care (POC) diagnosis of the physiological conditions of humans. A PEMFC is an electrochemical transducer that converts chemical energy into electrical energy. A Redox reaction takes place at its electrodes whereas the volatile biomolecules (e.g. ethanol) are oxidized at the anode and ambient oxygen is reduced at the cathode. The compounds which were the focus of this investigation were ethanol (C₂H₅OH) and isoflurane (C₃H₂ClF₅O), but theoretically, the sensor …

Signal Flow Graph Approach To Efficient Dst I-Iv Algorithms, Sirani M. Perera

Sirani Mututhanthrige Perera

In this paper, fast and efficient discrete sine transformation (DST) algorithms are presented based on the factorization of sparse, scaled orthogonal, rotation, rotation-reflection, and butterfly matrices. These algorithms are completely recursive and solely based on DST I-IV. The presented algorithms have low arithmetic cost compared to the known fast DST algorithms. Furthermore, the language of signal flow graph representation of digital structures is used to describe these efficient and recursive DST algorithms having (n􀀀1) points signal flow graph for DST-I and n points signal flow graphs for DST II-IV.

Non-Parametric Classification Of Time Series Using Permutation Ordinal Statistics, Aldo Duarte Vera Tudela

LSU Master's Theses

The present thesis explores some approaches to classify time series without prior statistical information using the concept of permutation entropy. Motivated by the results from a previous published and relevant work that set similarity relationships between EEG time series, a reproduction of the proposed approach was performed giving negative results. The failure to reproduce those results led to the conclusion that the approach of building statistics from permutation patterns have to be complemented with another metric in order to be used for classification purposes. The concept of Total Variation Distance (TVD) was then used to develop three algorithms to classify …

A Novel Indoor Positioning System For Firefighters In Unprepared Scenarios, Vamsi Karthik Vadlamani

Electrical and Computer Engineering ETDs

Situational awareness and indoor positioning of firefighters are types of information of paramount importance to the success of search and rescue operations. GPS units are undependable for use in Indoor Positioning Systems due to their associated mar- gins of error in position and their reliance on satellite communication that can be interrupted inside large structures. There are few other techniques like dead reck- oning, Wifi and bluetooth based triangulation, Structure from Motion (SFM) based scene reconstruction for Indoor positioning system. However due to high temper- atures, the rapidly changing environment of fires, and low parallax in the thermal images, the …

An Accurate And Efficient Time Delay Estimation Method Of Ultra-High Frequency Signals For Partial Discharge Localization In Substations, Pengfei Li, Kejie Dai, Tong Zhang, Yantao Jin, Yushun Liu, Yuan Liao

Electrical and Computer Engineering Faculty Publications

Partial discharge (PD) localization in substations based on the ultra-high frequency (UHF) method can be used to efficiently assess insulation conditions. Localization accuracy is affected by the accuracy of the time delay (TD) estimation, which is critical for PD localization in substations. A review of existing TD estimation methods indicates that there is a need to develop methods that are both accurate and computationally efficient. In this paper, a novel TD estimation method is proposed to improve both accuracy and efficiency. The TD is calculated using an improved cross-correlation algorithm based on full-wavefronts of array UHF signals, which are extracted …

Brain Connectivity Networks For The Study Of Nonlinear Dynamics And Phase Synchrony In Epilepsy, Hoda Rajaei

FIU Electronic Theses and Dissertations

Assessing complex brain activity as a function of the type of epilepsy and in the context of the 3D source of seizure onset remains a critical and challenging endeavor. In this dissertation, we tried to extract the attributes of the epileptic brain by looking at the modular interactions from scalp electroencephalography (EEG). A classification algorithm is proposed for the connectivity-based separation of interictal epileptic EEG from normal. Connectivity patterns of interictal epileptic discharges were investigated in different types of epilepsy, and the relation between patterns and the epileptogenic zone are also explored in focal epilepsy.

A nonlinear recurrence-based method is …

Investigating The Effect Of Detecting And Mitigating A Ring Oscillator-Based Hardware Trojan, Lakshmi Ramakrishnan

Electrical Engineering Theses and Dissertations

The outsourcing of the manufacturing process of integrated circuits to fabrications plants all over the world has exposed these chips to several security threats, especially at the hardware level. There have been instances of malicious circuitry, such as backdoors, being added to circuits without the knowledge of the chip designers or vendors. Such threats could be immensely powerful and dangerous against confidentiality, among other vulnerabilities.

Defense mechanisms against such attacks have been probed and defense techniques have been developed. But with the passage of time, attack techniques have improved immensely as well. From directly observing the inputs or outputs, adversaries …

Signal Identification In Discrete-Time Based On Internal-Model-Principle, Jie Chen

Electronic Thesis and Dissertation Repository

This work presents an implementation of a signal identification algorithm which is based on the internal model principle. By using several internal models in feedback with a tuning function, this algorithm can decompose a signal into narrow-band signals and identify the frequencies, amplitudes and relative phases. A desired band-pass filter response can be achieved by selecting appropriate coefficients of the controllers and tuning functions, which can reject the noise and improve the performance. To achieve a result with fast transient characteristics, this system is then modified by adding a low-pass filter. This work is based on the previous work in …

The Hilbert-Huang Transform: A Theoretical Framework And Applications To Leak Identification In Pressurized Space Modules, Kenneth R. Bundy

Electronic Theses and Dissertations

Any manned space mission must provide breathable air to its crew. For this reason, air leaks in spacecraft pose a danger to the mission and any astronauts on board. The purpose of this work is twofold: the first is to address the issue of air pressure loss from leaks in spacecraft. Air leaks present a danger to spacecraft crew, and so a method of finding air leaks when they occur is needed. Most leak detection systems localize the leak in some way. Instead, we address the identification of air leaks in a pressurized space module, we aim to determine the …

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 …