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Topography Measurements Using An Airborne Ka-Band Fmcw Interferometric Synthetic Aperture Radar, Kan Fu 2017 University of Massachusetts - Amherst

Topography Measurements Using An Airborne Ka-Band Fmcw Interferometric Synthetic Aperture Radar, Kan Fu

Doctoral Dissertations

Radar interferometry at millimeter-wave frequencies has the ability of topography measurement of different types of terrain, such as water surfaces and tree canopies. A Ka-band interferometric radar was mounted on an airborne platform, and flown over the Connecticut river region in western Massachusetts near Amherst on June 11, 2012. More than 20 Gigabytes of raw data was recorded. This dissertation outline presents the results of the data processing, which includes (1) the estimation and removal of the embedded high frequency phase error in the raw data; (2) the synthetic aperture processing; (3) the interferometric processing. The digital elevation model (DEM ...


Time Domain Sar Processing With Gpus For Airborne Platforms, Dustin Lagoy 2017 University of Massachusetts Amherst

Time Domain Sar Processing With Gpus For Airborne Platforms, Dustin Lagoy

Masters Theses

A time-domain backprojection processor for airborne synthetic aperture radar (SAR) has been developed at the University of Massachusetts’ Microwave Remote Sensing Lab (MIRSL). The aim of this work is to produce a SAR processor capable of addressing the motion compensation issues faced by frequency-domain processing algorithms, in order to create well focused SAR imagery suitable for interferometry. The time-domain backprojection algorithm inherently compensates for non-linear platform motion, dependent on the availability of accurate measurements of the motion. The implementation must manage the relatively high computational burden of the backprojection algorithm, which is done using modern graphics processing units (GPUs), programmed ...


Explorations Into Machine Learning Techniques For Precipitation Nowcasting, Aditya Nagarajan 2017 University of Massachusetts Amherst

Explorations Into Machine Learning Techniques For Precipitation Nowcasting, Aditya Nagarajan

Masters Theses

Recent advances in cloud-based big-data technologies now makes data driven solutions feasible for increasing numbers of scientific computing applications. One such data driven solution approach is machine learning where patterns in large data sets are brought to the surface by finding complex mathematical relationships within the data. Nowcasting or short-term prediction of rainfall in a given region is an important problem in meteorology. In this thesis we explore the nowcasting problem through a data driven approach by formulating it as a machine learning problem.

State-of-the-art nowcasting systems today are based on numerical models which describe the physical processes leading to ...


Kasi: A Ka-Band And S-Band Cross-Track Interferometer, Gerard Ruiz Carregal 2017 University of Massachusetts Amherst

Kasi: A Ka-Band And S-Band Cross-Track Interferometer, Gerard Ruiz Carregal

Masters Theses

A dual-frequency system is needed to better understand natural processes that constitute the environment and seasonal cycles of the Earth. A system working at two different wavelengths acquiring data simultaneously will give a valuable dataset since the conditions on the ground will be exactly the same. Hence, elements such as wind, soil moisture or any other changes on the ground will not interfere in the mea- surements. This thesis explains how an S-band radar was built and tested. Moreover, the experiments done with a Ka-band radar used as a scatterometer are explained as well as the data processing and analysis ...


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 & 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 ...


High Performance Multiview Video Coding, Caoyang Jiang 2017 Michigan Technological University

High Performance Multiview Video Coding, Caoyang Jiang

Dissertations, Master's Theses and Master's Reports

Following the standardization of the latest video coding standard High Efficiency Video Coding in 2013, in 2014, multiview extension of HEVC (MV-HEVC) was published and brought significantly better compression performance of around 50% for multiview and 3D videos compared to multiple independent single-view HEVC coding. However, the extremely high computational complexity of MV-HEVC demands significant optimization of the encoder. To tackle this problem, this work investigates the possibilities of using modern parallel computing platforms and tools such as single-instruction-multiple-data (SIMD) instructions, multi-core CPU, massively parallel GPU, and computer cluster to significantly enhance the MVC encoder performance. The aforementioned computing tools ...


Detection Of Fatigue Damage In Shear Connections Using Acoustic Wave Propagation, Zichao Wang 2017 Michigan Technological University

Detection Of Fatigue Damage In Shear Connections Using Acoustic Wave Propagation, Zichao Wang

Dissertations, Master's Theses and Master's Reports

Fatigue damage is an important concern in structural steel connections where frequent load reversals are expected. Detection of fatigue damage is typically done with infrequent visual inspections that are subjective and limited to surface features. A permanent embedded structural health monitoring (SHM) system could be helpful in detecting damage as it occurs. Current methods for detecting fatigue damage include inference of fatigue life expended through cycle counting from long-term strain measurement campaigns, and through short-term impedance measurements. The first approach has the advantage that it is relatively simple from an algorithmic point of view, but it is an indirect measure ...


Smart Sensing Skin For Detection And Localization Of Fatigue Cracks, Sari Kharroub, Simon Laflamme, Chunhui Song, Daji Qiao, Brent M. Phares, Jian Li 2016 Iowa State University

Smart Sensing Skin For Detection And Localization Of Fatigue Cracks, Sari Kharroub, Simon Laflamme, Chunhui Song, Daji Qiao, Brent M. Phares, Jian Li

Simon Laflamme

Fatigue cracks on steel components may have strong consequences on the structure's serviceability and strength. Their detection and localization is a difficult task. Existing technologies enabling structural health monitoring have a complex link signal-to-damage or have economic barriers impeding large-scale deployment. A solution is to develop sensing methods that are inexpensive, scalable, with signals that can directly relate to damage. The authors have recently proposed a smart sensing skin for structural health monitoring applications to mesosystems. The sensor is a thin film soft elastomeric capacitor (SEC) that transduces strain into a measurable change in capacitance. Arranged in a network ...


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.


Derivation Of Locational Marginal Prices For Restructured Wholesale Power Markets, Haifeng Liu, Leigh Tesfatsion, Ali A. Chowdhury 2016 California Independent System Operator Corporation

Derivation Of Locational Marginal Prices For Restructured Wholesale Power Markets, Haifeng Liu, Leigh Tesfatsion, Ali A. Chowdhury

Leigh Tesfatsion

Although locational marginal pricing (LMP) plays an important role in many restructured wholesale power markets, the detailed derivation of LMP as it is actually used in industrial practice is not readily available. This lack of transparency greatly hinders the efforts of researchers to evaluate the performance of these markets. In this paper, different alternating current and direct current optimal power flow models are presented to help us understand the derivation of LMP. As a byproduct of this analysis, we are able to provide a rigorous explanation of the basic LMP and LMP-decomposition formulas (neglecting real power losses) that are presented ...


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 ...


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 ...


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 ...


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 ...


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 ...


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 ...


Dynamic Visualization Of Three- Dimensional Images From Multiple Texel Images Created From Fused Ladar/ Digital Imagery, Cody C. Killpack, Scott Budge 2016 Utah State University

Dynamic Visualization Of Three- Dimensional Images From Multiple Texel Images Created From Fused Ladar/ Digital Imagery, Cody C. Killpack, Scott Budge

Scott Budge

The ability to create three-dimensional (3-D) image models, using registered texel images (fused ladar
and digital imagery), is an important topic in remote sensing. These models are automatically generated
by matching multiple texel images into a single common reference frame. However, rendering a sequence of
independently registered texel images often provides challenges. Although accurately registered, the model
textures are often incorrectly overlapped and interwoven when using standard rendering techniques.
Consequently, corrections must be done after all the primitives have been rendered by determining the best
texture for any viewable fragment in the model. This paper describes a technique to visualize ...


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