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Accurate Acoustic Ranging System Using Android Smartphones, mohammadbagher fotouhi 2017 Virginia Commonwealth University

Accurate Acoustic Ranging System Using Android Smartphones, Mohammadbagher Fotouhi

Theses and Dissertations

ACCURATE ACOUSTIC RANGING SYSTEM USING ANDROID SMARTPHONES

By Mohammadbagher Fotouhi, Master of Science

A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science at Virginia Commonwealth University

Virginia Commonwealth University 2017

Major Director: Dr. Ruixin Niu, Associate Professor of Department of Electrical and Computer Engineering

In this thesis, we present the design, implementation, and evaluation of an android ranging system, a high-accuracy acoustic-based ranging system which allows two android mobile phones to learn their physical distance from each other.

In this system we propose a practical solution for accurate ranging based on acoustic communication ...


Constant False Alarm Rate Performance Of Sound Source Detection With Time Delay Of Arrival Algorithm, Xipeng Wang 2017 University of Kentucky

Constant False Alarm Rate Performance Of Sound Source Detection With Time Delay Of Arrival Algorithm, Xipeng Wang

Theses and Dissertations--Electrical and Computer Engineering

Time Delay of Arrival (TDOA) based algorithms and Steered Response Power (SRP) based algorithms are two most commonly used methods for sound source detection and localization. SRP is more robust under high reverberation and multi-target conditions, while TDOA is less computationally intensive. This thesis introduces a modified TDOA algorithm, TDOA delay table search (TDOA-DTS), that has more stable performance than the original TDOA, and requires only 4% of the SRP computation load for a 3-dimensional space of a typical room. A 2-step adaptive thresholding procedure based on a Weibull noise peak distributions for the cross-correlations and a binomial distribution for ...


A Comprehensive Analysis On Eeg Signal Classification Using Advanced Computational Analysis, Kaushik Bhimraj 2017 Georgia Southern University

A Comprehensive Analysis On Eeg Signal Classification Using Advanced Computational Analysis, Kaushik Bhimraj

Electronic Theses and Dissertations

Electroencephalogram (EEG) has been used in a wide array of applications to study mental disorders. Due to its non-invasive and low-cost features, EEG has become a viable instrument in Brain-Computer Interfaces (BCI). These BCI systems integrate user's neural features with robotic machines to perform tasks. However, due to EEG signals being highly dynamic in nature, BCI systems are still unstable and prone to unanticipated noise interference. An important application of this technology is to help facilitate the lives of the tetraplegic through assimilating human brain impulses and converting them into mechanical motion. However, BCI systems are remarkably challenging to ...


Audio-Based Productivity Forecasting Of Construction Cyclic Activities, Chris A. Sabillon 2017 cs10852

Audio-Based Productivity Forecasting Of Construction Cyclic Activities, Chris A. Sabillon

Electronic Theses and Dissertations

Due to its high cost, project managers must be able to monitor the performance of construction heavy equipment promptly. This cannot be achieved through traditional management techniques, which are based on direct observation or on estimations from historical data. Some manufacturers have started to integrate their proprietary technologies, but construction contractors are unlikely to have a fleet of entirely new and single manufacturer equipment for this to represent a solution. Third party automated approaches include the use of active sensors such as accelerometers and gyroscopes, passive technologies such as computer vision and image processing, and audio signal processing. Hitherto, most ...


Sensor Characterization And Signal Fusion For Instanteye, Wyman T. Smith 2017 University of New Hampshire, Durham

Sensor Characterization And Signal Fusion For Instanteye, Wyman T. Smith

Honors Theses and Capstones

The practicality and effectiveness of using a TerraRanger Duo—a parallel sonar and infrared time-of-flight distance sensor—payload for obstacle detection is investigated for use with Physical Science Inc.’s InstantEye drone. A Python program was developed to interface with the serial data output before comparing the sensor’s empirical performance against its data sheet. The two signals from the distinct sensor modules, each with their characterized strengths and weaknesses, were then fused with a Kalman filter. This was further refined by imposing conditional weighting based on the known sensor characteristics. The filter output, with conditional corrections, was able to ...


Time-Frequency Masking Performance For Improved Intelligibility With Microphone Arrays, Joshua P. Morgan 2017 University of Kentucky

Time-Frequency Masking Performance For Improved Intelligibility With Microphone Arrays, Joshua P. Morgan

Theses and Dissertations--Electrical and Computer Engineering

Time-Frequency (TF) masking is an audio processing technique useful for isolating an audio source from interfering sources. TF masking has been applied and studied in monaural and binaural applications, but has only recently been applied to distributed microphone arrays. This work focuses on evaluating the TF masking technique's ability to isolate human speech and improve speech intelligibility in an immersive "cocktail party" environment. In particular, an upper-bound on TF masking performance is established and compared to the traditional delay-sum and general sidelobe canceler (GSC) beamformers. Additionally, the novel technique of combining the GSC with TF masking is investigated and ...


Experimental Investigation Of Reading Passive Uhf Tags In A Multi-Tag Environment, Yi Zhou 2017 University of Kentucky

Experimental Investigation Of Reading Passive Uhf Tags In A Multi-Tag Environment, Yi Zhou

Theses and Dissertations--Mechanical Engineering

Recently, the Internet of things (IoT) has emerged as a promising solution for several industrial applications. One of the key components in IoT is passive radio frequency identification (RFID) tags which do not require a power source for operations. Specifically, ultra-high frequency (UHF) tags are studied in this paper. However, due to factors such as tag-to-tag interference and inaccurate localization, RFID tags that are closely spaced together are difficult to detect and program accurately with unique identifiers. This thesis investigates several factors that affect the ability to encode a specific tag with unique information in the presence of other tags ...


Development Of An Agent-Based Distribution Test Feeder With Smart-Grid Functionality, Pedram Jahangiri, Di Wu, Wanning Li, Dionysios C. Aliprantis, Leigh Tesfatsion 2016 Iowa State University

Development Of An Agent-Based Distribution Test Feeder With Smart-Grid Functionality, Pedram Jahangiri, Di Wu, Wanning Li, Dionysios C. Aliprantis, Leigh Tesfatsion

Leigh Tesfatsion

This paper reports on the development of an agent-based distribution test feeder with smart-grid functionality. The test feeder is based on an actual distribution feeder with various additional features incorporated, including rooftop photovoltaic generation and price-responsive loads (e.g., plug-in electric vehicles and intelligent air-conditioning systems). This work aims to enable the integrated study of wholesale electric power markets coupled with detailed representations of the retail-side distribution systems.


Disrupting Long-Range Polar Order With An Electric Field, Hanzheng Guo, Xiaoming Liu, Fei Xue, Long-Qing Chen, Wei Hong, Xiaoli Tan 2016 Iowa State University

Disrupting Long-Range Polar Order With An Electric Field, Hanzheng Guo, Xiaoming Liu, Fei Xue, Long-Qing Chen, Wei Hong, Xiaoli Tan

Xiaoli Tan

lectric fields are known to favor long-range polar order through the aligning of electric dipoles in relation to Coulomb's force. Therefore, it would be surprising to observe a disordered polar state induced from an ordered state by electric fields. Here we show such an unusual phenomenon in a polycrystalline oxide where electric fields induce a ferroelectric-to-relaxor phase transition. The nonergodic relaxor phase with disordered dipoles appears as an intermediate state under electric fields during polarization reversal of the ferroelectric phase. Using the phenomenological theory, the underlying mechanism for this unexpected behavior can be attributed to the slow kinetics of ...


Data Logging System For A Synthetic Aperture Radar Unit, Nicholas J. Testin, Philip Davis, Ian Dorell, Alexander Gillespie 2016 Kennesaw State University

Data Logging System For A Synthetic Aperture Radar Unit, Nicholas J. Testin, Philip Davis, Ian Dorell, Alexander Gillespie

Honors College Capstones and Theses

A small, existing radar unit lacked the ability to automatically store the data it was receiving, which made its use clunky and cumbersome. A system was constructed to allow an on-board microprocessor to track distance traveled, and automatically store the data output from the radar unit to a portable memory unit for later data processing. Distance traveled is determined using a specially designed mobile cart, which electronically converts the rotation of a wheel into an electrical signal while also providing stability for taking accurate radar measurements. The output data from the radar unit is stored as a properly-formatted sound file ...


Electronic Deer Warning System, David Zhuo, Anlang Lu 2016 California Polytechnic State University, San Luis Obispo

Electronic Deer Warning System, David Zhuo, Anlang Lu

Computer Engineering

Deer-vehicle collisions (DVCs) are extremely dangerous, often injuring or even killing drivers. Unfortunately, this form of automotive accident is commonplace in the United States. According to the NHTSA, DVCs result in 200 human deaths a year.2

Despite these deadly incidents, there currently are no deployed federal or state systems for preventing DVCs. There are many consumer electronic deer deterrent products, but their long-term effectiveness is questionable.3 In fact, there does not appear to be much research into electronic deer deterrent systems. Aside from constant audio output and electric shock, no other means of electronic deterrent exist. Even if ...


A Quantitative Measure Of Mono-Componentness For Time-Frequency Analysis, Austin P. Albright 2016 University of Tennessee, Knoxville

A Quantitative Measure Of Mono-Componentness For Time-Frequency Analysis, Austin P. Albright

Doctoral Dissertations

Joint time-frequency (TF) analysis is an ideal method for analyzing non-stationary signals, but is challenging to use leading to it often being neglected. The exceptions being the short-time Fourier transform (STFT) and spectrogram. Even then, the inability to have simultaneously high time and frequency resolution is a frustrating issue with the STFT and spectrogram. However, there is a family of joint TF analysis techniques that do have simultaneously high time and frequency resolution – the quadratic TF distribution (QTFD) family. Unfortunately, QTFDs are often more troublesome than beneficial. The issue is interference/cross-terms that causes these methods to become so difficult ...


Psychophysiological Analysis Of A Pedagogical Agent And Robotic Peer For Individuals With Autism Spectrum Disorders., Mohammad Nasser Saadatzi 2016 University of Louisville

Psychophysiological Analysis Of A Pedagogical Agent And Robotic Peer For Individuals With Autism Spectrum Disorders., Mohammad Nasser Saadatzi

Electronic Theses and Dissertations

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by ongoing problems in social interaction and communication, and engagement in repetitive behaviors. According to Centers for Disease Control and Prevention, an estimated 1 in 68 children in the United States has ASD. Mounting evidence shows that many of these individuals display an interest in social interaction with computers and robots and, in general, feel comfortable spending time in such environments. It is known that the subtlety and unpredictability of people’s social behavior are intimidating and confusing for many individuals with ASD. Computerized learning environments and robots, however, prepare a ...


Single Carrier Frequency Domain Equalization And Energy Efficiency Optimization For Mimo Cognitive Radio., Xiaohui Zhang 2016 University of Louisville

Single Carrier Frequency Domain Equalization And Energy Efficiency Optimization For Mimo Cognitive Radio., Xiaohui Zhang

Electronic Theses and Dissertations

This dissertation studies two separate topics in wireless communication systems. One topic focuses on the Single Carrier Frequency Domain Equalization (SC-FDE), which is a promising technique to mitigate the multipath effect in the broadband wireless communication. Another topic targets on the energy efficiency optimization in a multiple input multiple output (MIMO) cognitive radio network. For SC-FDE, the conventional linear receivers suffer from the noise amplification in deep fading channel. To overcome this, a fractional spaced frequency domain (FSFD) receiver based on frequency domain oversampling (FDO) is proposed for SC-FDE to improve the performance of the linear receiver under deep fading ...


New Approaches For Estimating Hemispheric Lateralization From Resting State Fmri Data With Relationship To Age, Gender And Mental Disorders, Oktay Agcaoglu 2016 University of New Mexico

New Approaches For Estimating Hemispheric Lateralization From Resting State Fmri Data With Relationship To Age, Gender And Mental Disorders, Oktay Agcaoglu

Electrical and Computer Engineering ETDs

Lateralization is specialization of the brain hemispheres in certain tasks, such as language, mathematics, cognition and motor skills. It is one of the most queried topics related to the human brain. After the invention of modern medical imaging techniques including functional magnetic resonance imaging (fMRI), scientific research about the human brain, including lateralization, gained huge momentum. There have been a remarkable numbers of studies about lateralization and most of these studies focused on investigating which part of the brain dominates in which tasks. However, there have been very few lateralization studies on brain intrinsic activity, i.e., resting state activity ...


Power-Weighted Divergences For Relative Attenuation And Delay Estimation, Ruairí de Fréin, Scott T. Rickard Prof 2016 Dublin Institute of Technology

Power-Weighted Divergences For Relative Attenuation And Delay Estimation, Ruairí De Fréin, Scott T. Rickard Prof

Articles

Power-weighted estimators have recently been proposed for relative attenuation and delay estimation in blind source separation. Their provenance lies in the observation that speech is approximately windowed-disjoint orthogonal (WDO) in the time-frequency (TF) domain; it has been reported that using WDO, derived from TF representations of speech, improves mixing parameter estimation. We show that power-weighted relative attenuation and delay estimators can be derived from a particular case of a weighted Bregman divergence. We then propose a wider class of estimators, which we tune to give better parameter estimates for speech.


Channel And Noise Variance Estimation For Future 5g Cellular Networks, Jorge Iscar Vergara 2016 Florida International University

Channel And Noise Variance Estimation For Future 5g Cellular Networks, Jorge Iscar Vergara

FIU Electronic Theses and Dissertations

Future fifth generation (5G) cellular networks have to cope with the expected ten-fold increase in mobile data traffic between 2015 and 2021. To achieve this goal, new technologies are being considered, including massive multiple-input multiple-output (MIMO) systems and millimeter-wave (mmWave) communications. Massive MIMO involves the use of large antenna array sizes at the base station, while mmWave communications employ frequencies between 30 and 300 GHz. In this thesis we study the impact of these technologies on the performance of channel estimators.

Our results show that the characteristics of the propagation channel at mmWave frequencies improve the channel estimation performance in ...


A Biologically Plausible Supervised Learning Method For Spiking Neurons With Real-World Applications, Lilin Guo 2016 Florida International University

A Biologically Plausible Supervised Learning Method For Spiking Neurons With Real-World Applications, Lilin Guo

FIU Electronic Theses and Dissertations

Learning is central to infusing intelligence to any biologically inspired system. This study introduces a novel Cross-Correlated Delay Shift (CCDS) learning method for spiking neurons with the ability to learn and reproduce arbitrary spike patterns in a supervised fashion with applicability tospatiotemporalinformation encoded at the precise timing of spikes. By integrating the cross-correlated term,axonaland synapse delays, the CCDS rule is proven to be both biologically plausible and computationally efficient. The proposed learning algorithm is evaluated in terms of reliability, adaptive learning performance, generality to different neuron models, learning in the presence of noise, effects of its learning parameters and ...


Gaussian Nonlinear Line Attractor For Learning Multidimensional Data, Theus H. Aspiras, Vijayan K. Asari, Wesam Sakla 2016 University of Dayton

Gaussian Nonlinear Line Attractor For Learning Multidimensional Data, Theus H. Aspiras, Vijayan K. Asari, Wesam Sakla

Vijayan K. Asari

The human brain’s ability to extract information from multidimensional data modeled by the Nonlinear Line Attractor (NLA), where nodes are connected by polynomial weight sets. Neuron connections in this architecture assumes complete connectivity with all other neurons, thus creating a huge web of connections. We envision that each neuron should be connected to a group of surrounding neurons with weighted connection strengths that reduces with proximity to the neuron. To develop the weighted NLA architecture, we use a Gaussian weighting strategy to model the proximity, which will also reduce the computation times significantly. Once all data has been trained ...


Brain Machine Interface Using Emotiv Epoc To Control Robai Cyton Robotic Arm, Daniel P. Prince, Mark J. Edmonds, Andrew J. Sutter, Matthew Thomas Cusumano, Wenjie Lu, Vijayan K. Asari 2016 University of Dayton

Brain Machine Interface Using Emotiv Epoc To Control Robai Cyton Robotic Arm, Daniel P. Prince, Mark J. Edmonds, Andrew J. Sutter, Matthew Thomas Cusumano, Wenjie Lu, Vijayan K. Asari

Vijayan K. Asari

The initial framework for an electroencephalography (EEG) thought recognition software suite is developed, built, and tested. This suite is designed to recognize human thoughts and pair them to actions for controlling a robotic arm. Raw EEG brain activity data is collected using an Emotiv EPOC headset. The EEG data is processed through linear discriminant analysis (LDA), where an intended action is identified. The EEG classification suite is being developed to increase the number of distinct actions that can be identified compared to the Emotiv recognition software. The EEG classifier was able to correctly distinguish between two separate physical movements. Future ...


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